Journal of Hospitality and Tourism Management

Journal of Hospitality and Tourism Management 57 (2023) 29–39 34 indicates that the item score was 4, and a 95% threshold indicates that the item score was 1. Based on Ragin’s (2009) recommendation, a required condition has a consistency (the degree to which the cases comply with the necessity rule) that is greater than 0.90. According to the results of fsQCA, the essential criteria for WOM are EDE, ENE, ECE, ESE, BI, and AOM (See Table 6). According to Ragin (2009), the frequency threshold in this study was set to 1 and the consistency threshold was set to 0.80. This study identified five potential solutions that could lead to WOM in the museum (Table 7). The overall solution has a consistency of 0.973 and a coverage of 0.952, both of which are greater than the acceptable minimum standard of 0.75. In particular, in configuration 1, both ENE and ESE worked as core conditions, resulting in WOM. Furthermore, when compared to configurations 1a, 1b, and 1c, the coverage of the three solutions is 0.779, 0.860, and 0.844, with little difference in values, indicating little difference in their effects on WOM. Concerning configuration 2, both TP and AOM are core conditions, indicating that the formulation of WOM may result from attractive and temporary performances. In configuration 3, BI as a core condition and TP as a peripheral element work together to achieve WOM with a consistency of 0.980 and raw coverage of 0.159. 6. Concluding remarks 6.1. Conclusions and discussion Based on the Howard-Sheth model, we aimed to identify the mechanism by which the experience at museums (EAM, acting as the stimulating factor) influences the word of mouth (WOM, acting as the response factor) of visitors, with the brand image (BI, acting as the internal factor) and attractiveness of the museum (AOM, acting as the internal factor) as mediators and temporary performance (TP, acting as the external factor) as moderator. To the best of our knowledge, this study is not only the first attempt to reveal the process by which WOM forms via the mediating effects of BI and AOM, but it is also the first time to investigate and validate the moderating effect of an external factor (i. e. TP) in the Howard-Sheth model. Following that, we came to the following important conclusions. First, according to the Howard-Sheth model, all of the EAM, BI, and AOM positively and directly affect WOM. Additionally, the stimulating factor (i.e. experience at museums) and internal factor (i.e. brand image and attractiveness of museums) have effects on the response factor (i.e. word of mouth). Even though the effect of experience on WOM or EWOM has been studied in various fields (Lopez ´ & Sicilia, 2014; Yadav et al., 2021), the findings of this study confirmed the effect of EAM on WOM in the museum field to some extent. As a result, we concluded that the experience at museums is one of the important antecedents of WOM. Furthermore, both BI and AOM have a direct impact on WOM, which is consistent with previous research. For example, Nyadzayo et al. (2020) discovered a positive effect of brand image on word of mouth; Wirtz et al. (2018) claimed that attractiveness has a positive effect on word-of-mouth intention. As a result, we can conclude that both BI and AOM are necessary for the generation of WOM. This research determined the mediating effect of BI and AOM between EAM and WOM, indicating that EAM affects WOM not only directly but also via the transmission effects of BI and AOM. Additionally, EAM influences WOM via the sequential mediation of BI and AOM. We infer that when visitors have a positive experience at a museum, they may have a favorable perception of the museum’s brand image and attractiveness, thereby enhancing the museum’s WOM. The revealed mediation of BI and AOM is consistent with previous findings regarding the mediators of BI (Lee & Lee, 2018; Ramesh et al., 2019) and AOM (Joglekar & Tan, 2022; Sharma et al., 2018). Besides, we also revealed the serial mediation of BI and AOM, which has rarely been addressed previously. In conclusion, by employing BI and AOM as mediators, this study clarified the mechanism by which EAM generates stronger positive WOM through BI and AOM. Third, this study revealed that temporary performance moderated the impact of BI on AOM, highlighting the significance of TP for museums. Moreover, if visitors experienced the temporary performance Table 2 Descriptive statistics and confirmatory factor analysis. Items Factor loading CR AVE Cronbach’s α ETM 1: My visit to this museum has increased my knowledge. 0.725 0.943 0.509 0.943 ETM 2: My visit to this museum taught me a lot. 0.745 ETM 3: Visiting this museum piqued my interest in learning new things. 0.687 ETM 4: My visit to this museum was extremely educational. 0.767 EAM 5: I enjoyed watching the activities at this museum. 0.697 EAM 6: It was fascinating to watch people perform at this museum. 0.722 EAM 7: I did enjoy observing what other people were doing in this museum. 0.658 EAM 8: It was a lot of fun to watch the activities at this museum. 0.717 EAM 9: I felt like a different person when I went to this museum. 0.753 EAM 10: I felt as if I were in another place or time when I went to this museum. 0.751 EAM 11: This museum experience allowed me to imagine myself as someone else. 0.645 EAM 12: I completely disconnected from reality at this museum. 0.629 EAM 13: I felt a strong sense of harmony in this museum. 0.701 EAM 14: The atmosphere in this museum was pleasing to my senses. 0.732 EAM 15: Just being in this museum was pleasurable. 0.736 EAM 16: The museum’s setting was very appealing. 0.735 BI 1: This museum reflects how I see myself. 0.743 0.830 0.550 0.830 BI 2: I am quite similar to the museum’s image. 0.762 BI 3: This museum represents how I would like to see myself. 0.717 BI 4: I would like to be perceived as being similar to the image of this museum. 0.744 AOM 1: This museum would be a good place for me to visit. 0.740 0.841 0.571 0.835 AOM 3: As a place to visit, this museum appeals to me. 0.761 AOM 4: I would like to learn more about this museum. 0.720 AOM 5: I am very interested in visiting this museum. 0.798 WOM 1: I will recommend this museum to friends, family, and/ or colleagues. 0.730 0.802 0.575 0.802 WOM 2: I will say positive things about this museum. 0.752 WOM 3: I am pleased to inform others that I have visited this museum. 0.792 Note: EAM = Experience at museums, BI= Brand image, AOM = Attractiveness of museums, WOM= Word of mouth, CR = Composite reliability, and AVE = Average variance extracted (see Table 2). J. Yin et al.

Journal of Hospitality and Tourism Management 57 (2023) 29–39 35 provided by the museum, the positive impact of EAM on AOM would be amplified because the temporary performance may attract visitors and increase their revisit. Nevertheless, the moderating effect of TP on the effects of EAM and BI is not statistically significant. We argued that most museums are likely to have temporary performances that may not do much to boost and strengthen brand image (i.e., the attitudes or ideas that consumers associate with the self-image and social image in terms of brand personality (Boo et al., 2009)). Therefore, we asserted that temporary performances in museums are an essential means of enhancing their appeal and that museums should focus on enhancing the quality of their temporary performances. Fourth, this study proposed that the generation of WOM in museums results from a configuration of multiple conditions. At a museum, the combination of entertainment experience (ENE) and aesthetic experience (ESE) may directly lead to word-of-mouth (WOM). Furthermore, if visitors experience temporary performance (TP) and perceive the attractiveness of the museum (AOM), the museum may generate positive WOM. Moreover, positive WOM may occur if visitors perceive the museum’s brand image without having an entertainment experience (ENE). 6.2. Research implications This research examined the association between EAM and WOM using BI and AOM as mediators and TP as a moderator for museum visitors. We contend that our findings can add to the advancement of the existing literature by providing the following theoretical and practical implications. 6.2.1. Theoretical implications First and foremost, this study determined the process of WOM Table 3 Measuring fitting models. Models Factor structures χ2 df χ2 /df GFI NFI IFI TLI CFI RMSEA SRMR Four-factor EAM; BI; AOM; WOM 473.966 281.000 1.687 0.902 0.923 0.967 0.958 0.967 0.047 0.031 Three-factor EAM; BI＋AOM; WOM 493.727 284.000 1.738 0.897 0.919 0.964 0.955 0.964 0.049 0.031 Two-factor EAM＋BI＋AOM; WOM 524.303 286.000 1.833 0.892 0.914 0.959 0.949 0.959 0.052 0.322 One-factor EAM + BI + AOM + WOM 529.612 287.000 1.845 0.890 0.914 0.958 0.949 0.958 0.052 0.323 Suggested indices – – [1,3] >0.90 >0.90 >0.90 >0.90 >0.90 <0.08 <0.05 Note: EAM = Experience at museums, BI= Brand image, AOM = Attractiveness of museums, WOM= Word of mouth. Table 4 Differentiation validity test. Dimension M SD VIF EAM BI AOM WOM EAM 5.188 1.038 5.308 0.714 BI 5.153 1.143 4.169 0.653** 0.742 AOM 5.188 1.194 4.676 0.670** 0.631** 0.755 WOM 5.187 1.160 – 0.632** 0.628** 0.651** 0.758 Note: EAM = Experience at museums, BI= Brand image, AOM = Attractiveness of museums, WOM= Word of mouth, **P < 0.05, Correlations, α values, are shown below the diagonal that represents the discriminant validity among constructs. Table 5 Hypothesis testing. Variable Model I(BI) Model II(AOM) Model III(WOM) β S.E. P β S.E. P β S.E. P Con. 0.111 0.170 0.513 − 0.164 0.153 0.284 0.254 0.141 0.072 EAM 0.916*** 0.066 0.000 0.499* 0.076 0.000 0.196*** 0.063 0.002 BI 0.324* 0.052 0.000 0.321*** 0.055 0.000 AOM 0.413*** 0.057 0.000 TP − 0.044 0.083 0.600 − 0.003 0.075 0.971 EAM*TP − 0.057 0.073 0.438 0.125* 0.066 0.060 Gender 0.092 0.062 0.142 0.050 0.056 0.370 − 0.002 0.056 0.972 Age 0.070** 0.029 0.018 0.019 0.027 0.485 − 0.088*** 0.027 0.001 Job − 0.088** 0.042 0.036 0.033 0.038 0.386 0.012 0.038 0.762 Education − 0.006 0.011 0.606 0.011 0.010 0.237 0.008 0.010 0.415 Monthly Income − 0.032 0.030 0.280 − 0.023 0.027 0.385 − 0.037 0.027 0.167 R2 0.742*** 0.792** 0.790*** F 108.725 127.489 142.271 Note: EAM = Experience at museums, BI= Brand image, AOM = Attractiveness of museums, WOM= Word of mouth, TP = temporary experience * P < 0.1, **P < 0.05, ***P < 0.01. Fig. 2. Moderated effect. J. Yin et al.

Journal of Hospitality and Tourism Management 57 (2023) 29–39 36 formation in a museum context. Despite the fact that WOM and E-WOM have been extensively researched in various fields such as hotels (Yang, 2022), online travel community (Agag & El-Masry, 2016), glamping (Lu et al., 2021), Halal tourism (Wardi et al., 2018), and backpacker travelers (Alves et al., 2016). To some extent, this study shed light on WOM issues in the museum context, which may provide more explanation for WOM formulation, especially in the context of individuals’ experiences. Furthermore, this study not only investigated the antecedents of WOM in the museum but also determined how the antecedents of WOM interact and form the WOM, which may provide a new understanding of the antecedents of WOM in the museum. Second, based on the Howard-Sheth model, this study looked into the mechanisms by which EAM affects WOM in museums, which may broaden the application of the Howard-Sheth model to the museum field. In detail, this study discovered that not only does EAM have a direct effect on WOM, but it may also have an effect through the mediation of BI and WOM. To some extent, this study may provide a better understanding of how EAM affects WOM via the mediating effects of BI and AOM, which would not only acknowledge the role of EAM but also demonstrate WOM’s presence in museum practice. Third, we demonstrated TP moderation between EAM and WOM, which is a modified effort for the Howard-Sheth model. This study may have the potential to extend the Howard-Sheth model by disclosing the moderating role of an external variable (i.e. temporary performance) rather than its direct effect on an internal factor, which is commonly used. According to the Howard-Sheth model (Juan et al., 2017), external variables (such as culture and personality) and stimulating factors have a direct influence on individuals’ internal factors (i.e. perception of individuals). This study investigated and validated the moderating effect of external factors (i.e. temporary performance) on the relationship between stimuli factors and internal factors, potentially providing a new perspective on the traditional Howard-Sheth model. 6.2.2. Practical implications First, museum managers should pay attention to demand and improve the quality of the museum experience, which has a significant impact on WOM. It is necessary to train the tour guides, improve their familiarity with the exhibits in the exhibition area, and expand their professional knowledge, which will help to enrich the educational experience of visitors. To enhance visitors’ entertainment experiences, the museum may update the cinema, Game Park, interactive experience, and other enjoyment projects. Furthermore, museums may provide immersive effects for visitors through scene setting, atmosphere building, sound, light, electricity, and other scientific and technological means. Moreover, museums should improve the exhibition elements such as environment, color, exhibitions, decoration, lighting, music, and Fig. 3. Results of model Note: *P＜0.1, **P＜0.05, ***P＜0.01. Table 6 Analysis of necessary conditions. Conditions Tested WOM ~WOM Consistency Coverage Consistency Coverage EDE 0.940 0.933 0.773 0.230 ~EDE 0.224 0.767 0.775 0.796 ENE 0.947 0.913 0.834 0.241 ~ENE 0.213 0.810 0.698 0.799 ECE 0.917 0.932 0.780 0.238 ~ECE 0.251 0.791 0.777 0.737 ESE 0.933 0.934 0.786 0.236 ~ESE 0.237 0.786 0.780 0.778 TP 0.849 0.796 0.725 0.204 ~TP 0.151 0.646 0.275 0.354 BI 0.945 0.943 0.779 0.233 ~BI 0.232 0.777 0.811 0.817 AOM 0.943 0.940 0.762 0.228 ~AOM 0.227 0.760 0.801 0.808 Note: “~” represents the absence of conditions. EDE = Education experience, ENE = Entertainment experience, ECE = Escapism experience, ESE = Esthetics experience, TP= Temporary experience, BI= Brand image, AOM = Attractiveness of museums. Table 7 Configuration for achieving WOM. Casual Configuration Configuration 1a 1b 1c 2 3 EDE • ENE ● ● ● ⊗ ECE • ESE ● ● ● TP • ● • BI • • ● AOM • • ● Consistency 0.953 0.981 0.982 0.948 0.980 Raw coverage 0.779 0.860 0.848 0.802 0.159 Unique coverage 0.013 0.007 0.002 0.036 0.006 Overall solution coverage 0.952 Overall solution consistency 0.937 Note: ● Represents core condition present; ⊗ represents core condition absence; • represents peripheral condition present; blank space denotes a condition that could be present or absent. EDE = Education experience, ENE = Entertainment experience, ECE = Escapism experience, ESE = Esthetics experience, TP= Temporary experience, BI= Brand image, AOM = Attractiveness of museums. J. Yin et al.

Journal of Hospitality and Tourism Management 57 (2023) 29–39 37 so on to create an aesthetic feeling. Second, museum managers should focus on how to improve the museum’s attractiveness, as this can influence visitors’ WOM of museums. Museums have to dynamically update exhibits and exhibition themes to keep them fresh. In addition, loan exhibitions and temporary exhibitions can be used to supplement museum exhibits. Furthermore, museums had better improve their display methods, such as simulation, multimedia interaction, VR exhibits, and other highly interactive ways to present exhibits, to increase their attractiveness. Third, this study discovered that there is a positive moderation of temporary performance between museum attractiveness and word-ofmouth. As a result, museums should maximize the positive impact of temporary performance by increasing the frequency of temporary performance and regularly updating the theme and content of the temporary performance. Meanwhile, museums had better broaden and supplement the types of temporary performance available, such as melodrama, sketch, and dance. 6.3. Limitations and further research This study not only determined how EAM affects WOM in the museum field but also revealed the condition configuration of antecedents to formulate WOM. However, this study looked at the formation of WOM from the perspective of experience. In the future, we could investigate various paths to the formation of WOM from various perspectives including the communication activity (e.g., social media advertising) of museums. Furthermore, this study determined the moderation of an external factor, temporary performance. Further investigation should be conducted on a variety of other environmental elements, including light, sound, technology, and so on. Funding Jie Yin has really appreciated the financial support from Youth Project of National Social Science Foundation, China (20CGL022). Yensen Ni has really appreciated the financial support from National Science and Technology Council, Taiwan (NSTC 112-2410-H-032-047). Availability of data and materials The datasets used and/or analyzed during the current study are available from the first author on reasonable request at 1598030168 [email protected]. Declaration of competing interest The authors declare that they have no competing interests. References Agag, G., & El-Masry, A. A. (2016). Understanding consumer intention to participate in online travel community and effects on consumer intention to purchase travel online and WOM: An integration of innovation diffusion theory and TAM with trust. Computers in Human Behavior, 60, 97–111. Alves, S., Abrantes, J. L., Antunes, M. J., Seabra, C., & Herstein, R. (2016). WOM antecedents in backpacker travelers. Journal of Business Research, 69(5), 1851–1856. Anderson, J. C., & Gerbing, W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 27(1), 5–24. Anton, ´ C., Camarero, C., & Garrido, M.-J. (2017). Exploring the experience value of museum visitors as a co-creation process. Current Issues in Tourism, 21(12), 1406–1425. Bankins, S., & Waterhouse, J. (2018). Organizational identity, image, and reputation: Examining the influence on perceptions of employer attractiveness in public sector organizations. International Journal of Public Administration, 42(3), 218–229. Baumgartner, H., & Homburg, C. (1996). Applications of structural equation modeling in marketing and consumer research: A review. International Journal of Research in Marketing, 13(2), 139–161. Bellou, V., Stylos, N., & Rahimi, R. (2018). Predicting hotel attractiveness via personality traits of applicants. International Journal of Contemporary Hospitality Management, 30 (10), 3135–3155. Bitner, M. J. (1992). Servicescapes: The impact of physical surroundings on customers and employees. Journal of Marketing, 56(2), 57–71. Boo, S., Busser, J., & Baloglu, S. (2009). A model of customer-based brand equity and its application to multiple destinations. Tourism Management, 30(2), 219–231. Briand Decr´e, G., & Cloonan, C. (2019). A touch of gloss: Haptic perception of packaging and consumers’ reactions. The Journal of Product and Brand Management, 28(1), 117–132. Carpentier, M., Van Hoye, G., Stockman, S., Schollaert, E., Van Theemsche, B., & Jacobs, G. (2017). Recruiting nurses through social media: Effects on employer brand and attractiveness. Journal of Advanced Nursing, 73(11), 2696–2708. Casado-Díaz, A. B., P´erez-Naranjo, L. M., & Sellers-Rubio, R. (2016). Aggregate consumer ratings and booking intention: The role of brand image. Service Business, 11(3), 543–562. Chapman, D. S., Uggerslev, K. L., Carroll, S. A., Piasentin, K. A., & Jones, D. A. (2005). Applicant attraction to organizations and job choice: A meta-analytic review of the correlates of recruiting outcomes. Journal of Applied Psychology, 90(5), 928–944. Chen, Y.-S., Huang, A. F., Wang, T.-Y., & Chen, Y. R. (2018). Greenwash and green purchase behaviour: The mediation of green brand image and green brand loyalty. Total Quality Management and Business Excellence, 31(1–2), 194–209. Chen, Y. C., Tsui, P. L., Chen, H. I., Tseng, H. L., & Lee, C. S. (2019). A dining table without food: The floral experience at ethnic fine dining restaurants. British Food Journal, 122(6), 1819–1832. Conti, E., Vesci, M., Castellani, P., & Rossato, C. (2020). The role of the museumscape on positive word of mouth: Examining Italian museums. The TQM Journal. Cox, M. A. (2016). Intermedial museum performance: A reflection on the use of intermedial performance as a medium of immersion at the Barbados museum & historical society. Research in Drama Education: The Journal of Applied Theatre and Performance, 21(3), 349–354. Dijkstra, K., Pieterse, M. E., & Pruyn, A. (2008). Stress-reducing effects of indoor plants in the built healthcare environment: The mediating role of perceived attractiveness. Preventive Medicine, 47(3), 279–283. Erkmen, E., & Hancer, M. (2019). Building brand relationship for restaurants. International Journal of Contemporary Hospitality Management, 31(3), 1469–1487. Fan, Y., & Luo, J. M. (2022). Impact of generativity on museum visitors’ engagement, experience, and psychological well-being. Tourism Management Perspectives, 42. Forgas-Coll, S., Palau-Saumell, R., Matute, J., & T´ arrega, S. (2017). How do service quality, experiences and enduring involvement influence tourists’ behavior? An empirical study in the picasso and miro ´ museums in barcelona. International Journal of Tourism Research, 19(2), 246–256. Gieling, J., & Ong, C. E. (2016). Warfare tourism experiences and national identity: The case of Airborne Museum ‘Hartenstein’ in Oosterbeek, The Netherlands. Tourism Management, 57, 45–55. Gomez-Rico, ´ M., Molina-Collado, A., Santos-Vijande, M. L., Molina-Collado, M. V., & Imhoff, B. (2023). The role of novel instruments of brand communication and brand image in building consumers’ brand preference and intention to visit wineries. Current Psychology, 42(15), 12711–12727. Guo, K., Fan, A., Lehto, X., & Day, J. (2021). Immersive digital tourism: The role of multisensory cues in digital museum experiences. Journal of Hospitality & Tourism Research, 47(6), 1017–1039. Han, H., Kim, W., & Lee, S. (2018). Stimulating visitors’ goal-directed behavior for environmentally responsible museums: Testing the role of moderator variables. Journal of Destination Marketing & Management, 8, 290–300. Harman, H. (Ed.). (1976). Modern factor analysis. Chicago: University of Chicago. Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: Guilford Press. He, Z., Wu, L., & Li, X. (2018). When art meets tech: The role of augmented reality in enhancing museum experiences and purchase intentions. Tourism Management, 68, 127–139. Highhouse, S., Lievens, F., & Sinar, E. (2003). Measuring attraction to organizations. Educational and Psychological Measurement, 63(6), 986–1001. Hsiao, A., Ma, E., Lloyd, K., & Reid, S. (2020). Organizational ethnic diversity’s influence on hotel employees’ satisfaction, commitment, and turnover intention: gender’s moderating role. Journal of Hospitality & Tourism Research, 44(1), 76–108. Huang, C. E., & Liu, C. H. (2018). The creative experience and its impact on brand image and travel benefits: The moderating role of culture learning. Tourism Management Perspectives, 28, 144–155. Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. Hu, Y., & Ritchie, J. (2016). Measuring destination attractiveness: A contextual approach. Journal of Travel Research, 32(2), 25–34. Hu, Y., Sun, W., Liu, X., Gan, Q., & Shi, J. (2020). Tourism demonstration system for large-scale museums based on 3D virtual simulation technology. The Electronic Library, 38(2), 367–381. Huertas-Valdivia, I., Llorens-Montes, F. J., & Ruiz-Moreno, A. (2018). Achieving engagement among hospitality employees: a serial mediation model. International Journal of Contemporary Hospitality Management, 30(1), 217–241. Jeon, J.-H., Byon, K. K., Song, H., & Park, S. B. R. (2022). The influence of core service quality associated with Korean women’s volleyball on national image and consumption engagement of Korean products: Perspective of Korean Wave in Thailand. Frontiers in Psychology, 13, Article 788257. Jiang, J. (2020). The role of natural soundscape in nature-based tourism experience: An extension of the stimulus–organism–response model. Current Issues in Tourism, 25(5), 707–726. Jin, L., Xiao, H., & Shen, H. (2020). Experiential authenticity in heritage museums. Journal of Destination Marketing & Management, 18, Article 100493. J. Yin et al.

Journal of Hospitality and Tourism Management 57 (2023) 29–39 38 Ji, C., & Yang, P. (2022). What makes integrated resort attractive? Exploring the role of experience encounter elements. Journal of Travel & Tourism Marketing, 39(3), 305–319. Joglekar, J., & Tan, C. S. L. (2022). The impact of LinkedIn posts on employer brand perception and the mediating effects of employer attractiveness and corporate reputation. Journal of Advances in Management Research, 19(4), 624–650. Juan, Y. K., Hsu, Y. H., & Xie, X. (2017). Identifying customer behavioral factors and price premiums of green building purchasing. Industrial Marketing Management, 64, 36–43. Kang, J. H., Jang, J. C., & Jeong, C. (2017). Understanding museum visitor satisfaction and revisit intentions through mobile guide system: Moderating role of age in museum mobile guide adoption. Asia Pacific Journal of Tourism Research, 23(2), 95–108. Khan, I., & Fatma, M. (2021). Online destination brand experience and authenticity: Does individualism-collectivism orientation matter? Journal of Destination Marketing & Management, 20, Article 100597. Kim, S.-E., & Jung, S. (2022). Exploring virtual race participants’ perceptions of event mobile apps and behavioral intention: The stimulus-organism-response approach. Journal of Convention & Event Tourism, 23(4), 365–383. Kim, M. J., Lee, C. K., & Jung, T. (2018). Exploring consumer behavior in virtual reality tourism using an extended stimulus-organism-response model. Journal of Travel Research, 59(1), 69–89. Kim, M., & Thapa, B. (2018). Perceived value and flow experience: Application in a nature-based tourism context. Journal of Destination Marketing & Management, 8, 373–384. Komarac, T., & Ozreti´c Doˇsen, Đ. (2021). Discovering the determinants of museum visitors’ immersion into experience: The impact of interactivity, expectations, and skepticism. Current Issues in Tourism, 25(22), 3675–3693. Kucherov, D., & Zhiltsova, E. (2020). Social media in employer branding in FMCG in Russia: Millennials’ perspective. Journal of East-West Business, 27(2), 160–183. Kumar, S., Jain, A., & Hsieh, J. K. (2021). Impact of apps aesthetics on revisit intentions of food delivery apps: The mediating role of pleasure and arousal. Journal of Retailing and Consumer Services, 63, Article 102686. Lee, J., & Lee, Y. (2018). Effects of multi-brand company’s CSR activities on purchase intention through a mediating role of corporate image and brand image. Journal of Fashion Marketing and Management: International Journal, 22(3), 387–403. Liang, S. H., & Lai, I. K. W. (2022). Tea tourism: Designation of origin brand image, destination image, and visit intention. Journal of Vacation Marketing, 29(3), 409–427. Lin, P. M. C., Qiu Zhang, H., Gu, Q., & Peng, K.-L. (2017). To go or not to go: Travel constraints and attractiveness of travel affecting outbound Chinese tourists to Japan. Journal of Travel & Tourism Marketing, 34(9), 1184–1197. Liu, C.-R., Liu, H.-K., & Lin, W.-R. (2015). Constructing Customer-based museums brand equity model: The mediating role of brand value. International Journal of Tourism Research, 17(3), 229–238. Lohneiss, A., & Hill, B. (2013). The impact of processing athlete transgressions on brand image and purchase intent. European Sport Management Quarterly, 14(2), 171–193. Lopez, ´ M., & Sicilia, M. (2014). Determinants of e-WOM influence: The role of consumers’ internet experience. Journal of theoretical and applied electronic commerce research, 9(1), 7–8. Luo, J. M., & Ye, B. H. (2020). Role of generativity on tourists’ experience expectation, motivation and visit intention in museums. Journal of Hospitality and Tourism Management, 43, 120–126. Lu, J., Wang, X., Dai, Z., Chen, G., & Feng, Y. (2021). Antecedents of customer WOM in glamping: The critical role of original ecology. International Journal of Hospitality Management, 95, Article 102919. Manhas, P. S., & Tukamushaba, E. K. (2015). Understanding service experience and its impact on brand image in hospitality sector. International Journal of Hospitality Management, 45, 77–87. Manna, R., & Palumbo, R. (2018). What makes a museum attractive to young people? Evidence from Italy. International Journal of Tourism Research, 20(4), 508–517. Manosuthi, N., Lee, J.-S., & Han, H. (2022). Investigating residents’ support for muslim tourism: The application of IGSCA-SEM and fsQCA. Journal of Travel & Tourism Marketing, 39(4), 412–431. Manthiou, A., Lee, S., Tang, L. R., & Chiang, L. (2014). The experience economy approach to festival marketing: Vivid memory and attendee loyalty. Journal of Services, 28(1), 22–35. Mavragani, E. (2015). Greek museums and tourists’ perceptions: An empirical research. Journal of the Knowledge Economy, 12(1), 120–133. Mkedder, N., Bakır, M., & Lachachi, A. (2021). Investigating the antecedents of purchase intention toward local dairy products: An empirical study based on the SOR model. Central European Management Journal, 29(4), 124–148. Mohammad Shafiee, M., Foroudi, P., & Tabaeeian, R. A. (2021). Memorable experience, tourist-destination identification and destination love. International Journal of Tourism Cities, 7(3), 799–817. Mohseni, S., Jayashree, S., Rezaei, S., Kasim, A., & Okumus, F. (2016). Attracting tourists to travel companies’ websites: The structural relationship between website brand, personal value, shopping experience, perceived risk and purchase intention. Current Issues in Tourism, 21(6), 616–645. Montoya, A. K., & Hayes, A. F. (2017). Two-condition within-participant statistical mediation analysis: A path-analytic framework. Psychological Methods, 22(1), 6–27. Niblett, H., & Allison, J. (2016). Performance as interpretation: A museum studies perspective. Research in Drama Education: The Journal of Applied Theatre and Performance, 21(4), 574–580. Nowacki, M., & Kruczek, Z. (2020). Experience marketing at polish museums and visitor attractions: The co-creation of visitor experiences, emotions and satisfaction. Museum Management and Curatorship, 36(1), 62–81. Nyadzayo, M. W., Johnson, L. W., & Rossi, M. (2020). Drivers and outcomes of brand engagement in self-concept for luxury fashion brands. Journal of Fashion Marketing and Management: International Journal, 24(4), 589–609. Ordanini, A., Parasuraman, A., & Rubera, G. (2014). When the recipe is more important than the ingredients: A qualitative comparative analysis (qca) of service innovation configurations. Journal of Service Research, 17(2), 134–149. Ozdemir, B., Çizel, B., & Bato Cizel, R. (2012). Satisfaction with all-inclusive tourism resorts: The effects of satisfaction with destination and destination loyalty. International Journal of Hospitality & Tourism Administration, 13(2), 109–130. Podsakoff, P. M., Mackenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. Ponsignon, F., & Derbaix, M. (2020). The impact of interactive technologies on the social experience: An empirical study in a cultural tourism context. Tourism Management Perspectives, 35, Article 100723. Ragin, C. C. (2009). Redesigning social inquiry: Fuzzy sets and beyond. Chicago, IL, USA: University of Chicago Press. Ramesh, K., Saha, R., Goswami, S., Sekar, & Dahiya, R. (2019). Consumer’s response to CSR activities: Mediating role of brand image and brand attitude. Corporate Social Responsibility and Environmental Management, 26(2), 377–387. Rasoolimanesh, S. M., Ringle, C. M., Sarstedt, M., & Olya, H. (2021). The combined use of symmetric and asymmetric approaches: Partial least squares-structural equation modeling and fuzzy-set qualitative comparative analysis. International Journal of Contemporary Hospitality Management, 33(5), 1571–1592. Roy, S. K., Singh, G., Hope, M., Nguyen, B., & Harrigan, P. (2019). The rise of smart consumers: Role of smart servicescape and smart consumer experience co-creation. Journal of Marketing Management, 35(15–16), 1480–1513. Schlesinger, W., Cervera-Taulet, A., & Wymer, W. (2023). The influence of university brand image, satisfaction, and university identification on alumni WOM intentions. Journal of Marketing for Higher Education, 33(1), 1–19. Shaby, N., & Vedder-Weiss, D. (2021). Embodied interactions in a science museum. Science Education, 105(5), 938–960. Sharma, R. R., Sraha, G., & Crick, D. (2018). Export promotion programmes and the export performance of Ghanaian firms: The mediating role of foreign market attractiveness. International Marketing Review, 35(4), 661–682. Sheth, J. N., & Parvatiyar, A. (1995). Relationship marketing in consumer markets: Antecedents and consequences. Journal of the Academy of Marketing Science, 23(4), 255–271. Trunfio, M., Jung, T., & Campana, S. (2022). Mixed reality experiences in museums: Exploring the impact of functional elements of the devices on visitors’ immersive experiences and post-experience behaviours. Information & Management, 59(8), Article 103698. Trunfio, M., Lucia, M. D., Campana, S., & Magnelli, A. (2021). Innovating the cultural heritage museum service model through virtual reality and augmented reality: The effects on the overall visitor experience and satisfaction. Journal of Heritage Tourism, 17(1), 1–19. Vazquez, D., Dennis, C., & Zhang, Y. (2017). Understanding the effect of smart retail brand – consumer communications via mobile instant messaging (MIM): An empirical study in the Chinese context. Computers in Human Behavior, 77, 425–436. Vesci, M., Conti, E., Rossato, C., & Castellani, P. (2021). The mediating role of visitor satisfaction in the relationship between museum experience and word of mouth: Evidence from Italy. TQM Journal, 33(1), 141–162. Wang, Y., Fardouly, J., Vartanian, L. R., & Lei, L. (2019). Selfie-viewing and facial dissatisfaction among Chinese adolescents: A moderated mediation model of general attractiveness internalization and body appreciation. Body Image, 30, 35–43. Wardi, Y., Abror, A., & Trinanda, O. (2018). Halal tourism: Antecedent of tourist’s satisfaction and word of mouth (WOM). Asia Pacific Journal of Tourism Research, 23 (5), 463–472. Wirtz, B. W., Gottel, ¨ V., Langer, P. F., & Thomas, M.-J. (2018). Antecedents and consequences of public administration’s social media website attractiveness. International Review of Administrative Sciences, 86(1), 38–61. Wong, I. A. (2014). A multimethod multilevel study of heritage transmission. Journal of Travel Research, 54(5), 672–685. Wu, P.-C. (2017). Make a loyal visitor: A study of leisure experience at farglory corporate museum in taiwan. Asia Pacific Journal of Tourism Research, 22(5), 554–564. Yadav, R., Paul, J., & Mittal, A. (2021). Impact of nation brand experience on nation brand loyalty, and positive WOM in a changing environment: The role of nation brand love. International Marketing Review, 40(1), 28–48. Yang, Y. (2022). Impacts of temporal contiguity on creation and consumption of e-WOM in hotel context: A combined perspective of review rating and text. International Journal of Hospitality Management, 105, Article 103256. Yang, X., & Zhang, L. (2022). Smart tourism technologies towards memorable experiences for museum visitors. Tourism Review, 77(4), 1009–1023. Yin, J., Bi, Y., & Ni, Y. (2022). The impact of COVID-19 on turnover intention among hotel employees: A moderated mediation model. Journal of Hospitality and Tourism Management, 51, 539–549. Yin, J., Cheng, Y., Bi, Y., & Ni, Y. (2020). Tourists perceived crowding and destination attractiveness: The moderating effects of perceived risk and experience quality. Journal of Destination Marketing & Management, 18, Article 100489. Yin, J., Cheng, Y., & Ni, Y. (2024). Staging a comeback? The influencing mechanism of tourist crowding perception on adaptive behavior. Tourism Management, 100, 104827. Yin, J., Ji, Y., & Ni, Y. (2023a). Does “nei juan” affect “tang ping” for hotel employees? The moderating effect of effort-reward imbalance. International Journal of Hospitality Management, 109, Article 103421. J. Yin et al.

Journal of Hospitality and Tourism Management 57 (2023) 29–39 39 Yin, J., Ji, Y., & Ni, Y. (2023b). How does cultural confidence awaken community citizenship behaviors? The moderating effect of cultural involvement. Journal of Hospitality and Tourism Management, 55, 425–434. Yin, J., & Ni, Y. (2021). COVID-19 event strength, psychological safety, and avoidance coping behaviors for employees in the tourism industry. Journal of Hospitality and Tourism Management, 47, 431–442. Younis, R. A. A., & Hammad, R. (2020). Employer image, corporate image and organizational attractiveness: The moderating role of social identity consciousness. Personnel Review, 50(1), 244–263. Yu, K. C., Williams, K., Neafus, D., Gaston, L., & Downing, G. (2009). Gaia journeys: A museum-based immersive performance exploration of the earth. International Journal of Digital Earth, 2(1), 44–58. Zhang, S. N., Li, Y. Q., Liu, C. H., & Ruan, W. Q. (2021). Reconstruction of the relationship between traditional and emerging restaurant brand and customer WOM. International Journal of Hospitality Management, 94, Article 102879. Zhao, X., Lynch, J. G., & Chen, Q. (2010). Reconsidering baron and kenny: Myths and truths about mediation analysis. Journal of Consumer Research, 37(2), 197–206. Zou, Y., & Arif, M. (2022). Computational technologies on modeling of museum interactive virtual display based on user experience. Security and Communication Networks, Article 5659269, 2022. J. Yin et al.

Journal of Hospitality and Tourism Management 57 (2023) 315–326 Available online 10 November 2023 1447-6770/© 2023 The Authors. Published by Elsevier Ltd. on behalf of CAUTHE - COUNCIL FOR AUSTRALASIAN TOURISM AND HOSPITALITY EDUCATION. All rights reserved. Eco-destination image, environment beliefs, ecotourism attitudes, and ecotourism intention: The moderating role of biospheric values☆ The-Bao Luong Faculty of Fashion and Tourism, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Viet Nam ARTICLE INFO Keywords: Ecotourism Biospheric values Eco-destination image Environment beliefs Attitudes Behavioral intention ABSTRACT This study examines the relationship between eco-destination image, environment beliefs, ecotourism attitudes, eco-behavioral intention, and ecotourism intention while also exploring the moderating role of biospheric values within the context of the Values-Identity-Personal (VIP) theory. The research aims to understand the correlation between these variables and the motivational forces driving individuals toward ecotourism. Drawing on a sample of 683 respondents from a well-known emerging eco-destination, Mang Den, the study tests the hypotheses using structural equation modeling. The findings reveal that eco-destination image, environment beliefs, and ecotourism attitudes significantly impact ecotourism intention. The moderating effects of biospheric values are also discovered in this study. The results of this study provide a theoretical framework for future research that integrates the VIP theory into the ecotourism context. The findings can be useful for policymakers and ecotourism operators in developing strategies that promote sustainable tourism by targeting tourists’ values. 1. Introduction Sustainable tourism has received a growing amount of attention over the years as travelers have become more conscientious of their environmental impact. For instance, ecotourism offers tourists a sustainable alternative to enjoy unique experiences while minimizing environmental impact (Shasha et al., 2020). However, ecotourism’s success relies on tourists’ attitudes and behaviors toward sustainable tourism practices. Despite the existence of numerous academic studies on the causes of ecotourism behavior, the comprehension of the factors that drive ecotourism demand remains limited. Therefore, additional research is required to identify unaddressed factors influencing travelers’ intentions to visit ecotourism destinations. Ecotourism growth can be promoted more effectively through such research, resulting in a better understanding of ecotourism intentions. Ecotourism has been recognized worldwide as an innovative and sustainable way to promote tourism growth while preserving the environment and supporting local communities (Pham & Khanh, 2021; Said & Maryono, 2018). With its diverse natural resources and cultural heritage, such as Ha Long Bay and Phong Nha-Ke Bang National Park, Vietnam is an emerging market for ecotourism development. Although ecotourism is gaining popularity in Vietnam, there is still limited understanding of the factors influencing eco-intentions. As a result of this study, tourism practitioners, policymakers, and governments can gain insight into the factors influencing ecotourism and sustainability in Vietnam, which is essential to advancing ethical and environmentally friendly tourism in Vietnam and other developing nations with underdeveloped ecotourism sectors (Hoang et al., 2022; Long & Bui, 2020; Tien et al., 2021). Visitors’ environmental values, attitudes, and actions have been studied for their roles in encouraging sustainability (Morren & Grinstein, 2016). Examining moderating factors that might influence these associations is crucial, as they significantly promote sustainable tourism practices (N. T. K. Chi & Pham, 2022; Mohaidin et al., 2017; Tarinc et al., 2023). To address this knowledge vacuum, this study investigates how biospheric values moderate between eco-destination image, environmental views, ecotourism attitude, and ecotourism intention. Wesley Schultz (2001)posits that an individual’s biospheric values encompass caring for the environment and acknowledging humanity’s reliance on the natural world. Research indicates that individuals with high biospheric values are more likely to participate in environmentally sustainable behavior (Beall et al., 2021; Tsung Hung Lee & Jan, 2018; Van der Werff et al., 2014). Despite the significance of these values in promoting sustainable tourism practices, research on the moderating ☆ The-Bao Luong: A Lecturer from the Faculty of Fashion and Tourism, Ho Chi Minh City University of Technology and Education. Research interests include Food Tourism, Cultural Tourism, and Tourist Behavior. E-mail address: [email protected]. Contents lists available at ScienceDirect Journal of Hospitality and Tourism Management journal homepage: www.elsevier.com/locate/jhtm https://doi.org/10.1016/j.jhtm.2023.11.002 Received 3 July 2023; Received in revised form 2 November 2023; Accepted 3 November 2023

Journal of Hospitality and Tourism Management 57 (2023) 315–326 316 function of biospheric values in the context of ecotourism remains limited. Understanding how biospheric values moderate the relationship between these variables would enhance understanding of the motivations and decision-making processes of potential ecotourists in Vietnam. To address the fragmented approach caused by the frequent existence of multiple conceptual and behavioral frameworks, this study adopts the Values-Identity-Personal Norms (VIP) theory (van der Werff & Steg, 2016). The VIP theory integrates various psychological constructs, including values, identity, and personal norms, to elucidate individual participation in ecotourism activities (Tsung Hung Lee & Jan, 2018). By utilizing the VIP theory, this study aims to understand how biospheric values and factors influence ecotourism behavior comprehensively. This study aims to enrich the existing knowledge on ecotourism by examining three pivotal factors influencing tourists’ intentions to visit ecotourism destinations: perceptions of eco-destination image, environmental beliefs, and ecotourism attitudes. These parameters have been recognized as major predictors in earlier studies (Hadinejad et al., 2019; Pham & Khanh, 2021), but their aggregate effects and interrelationships have not been completely investigated. The study wants to explore the underlying processes promoting sustainable tourism by analyzing the links between eco-destination images, environmental views, and ecotourism attitudes. Furthermore, this research aims to clarify the moderating effect of biospheric values in the ecotourism literature. While prior research has emphasized the importance of biospheric values as a primary predictor of ecotourism intention, its possible moderating role has not been well studied. The author intends to address this research vacuum and contribute to a better understanding of the function of biospheric values in encouraging sustainable tourism practices via this study. Furthermore, by concentrating on Vietnam as a unique study setting, this research solves a gap in the ecotourism literature. The results may give significant insights for destination management organizations (DMOs) in developing successful interventions and campaigns to encourage sustainable tourism behaviors by identifying the correlations between these factors. 2. Literature review 2.1. Values-Identity-Personal norms (VIP) model The VIP model, developed by Ates¸ (2020) and van der Werff and Steg (2016), is a comprehensive framework that emphasizes the important role of biospheric values in encouraging environmentally responsible behavior. Biospheric values represent individuals’ recognition of environmental significance, characterized by consistent and generalized evaluations of its importance (Beall et al., 2021; Bouman et al., 2018). These values, coupled with environmental self-identity, which indicates a person’s affiliation with the environment, have promoted sustainable behavior (Van der Werff et al., 2013). In addition to biospheric values and environmental self-identity, the VIP model contains the idea of personal norms. Personal norms are the sense of moral duty a person feels while contemplating activities that benefit others (Godin et al., 2005; S. Lee et al., 2021). The VIP model emphasizes the need to nurture and reinforce biospheric values and foster a sense of personal standards in encouraging more sustainable actions (Godin et al., 2005). The research recognizes the necessity of citing relevant works to support the better use of the VIP model in empirical work (Ates¸, 2020; S. Lee et al., 2021; Van der Werff et al., 2013). As a result, the study will contain relevant references in this part that indicate the use of the VIP model in earlier research. The study aims to give a more thorough grasp of the model’s theoretical foundations and empirical base. 2.2. Ecotourism intention Ecotourism has been characterized in a variety of ways in the literature. Although Bjork ¨ ’s (2000) definition of ecotourism is extensive, it may be too complicated for the investigation. Therefore, for the purposes of this research, ecotourism intention is understood to be a kind of tourism that places a premium on visiting an ecotourism destination. The term “ecotourism intention” refers to a tourist’s plan to go to a designated environmentally friendly area in the near future (Pham & Khanh, 2021). Although prior research has examined the effects of factors such as motivation (Hultman et al., 2015; Luo & Deng, 2008), environmental attitudes and identity (Teeroovengadum, 2019), environmental concern (Pham & Khanh, 2021), environmental knowledge (Schaffer & Tham, 2020; H. Zhang & Lei, 2012), personal norms and social return (Beall et al., 2021) and ecotourism experience (Brochado, 2019; Y. C. Huang & Liu, 2017) on ecotourism intention, the worth of the biosphere is hardly considered. Biospheric values influence ecotourism since they reflect individuals’ concern for the environment and their motivation to take environmental responsibility into account (Schultz et al., 2004). As a result, this research aims to examine how biospheric values moderate the connection between eco-destination image, environmental beliefs, ecotourism attitudes, and ecotourism intentions. It is hypothesized that biospheric values will increase the association between these variables, as travelers with higher biospheric values will be more inclined to engage in ecotourism and support environmentally responsible practices. This study attempts to bridge a knowledge gap by giving fresh information on the elements influencing people’s choices to participate in ecotourism. 2.3. Eco-destination image A destination’s image is important in determining whether or not people decide to come since it shapes people’s initial thoughts and ideas about a location (Phelps, 1986). Due to the increased desire for ecologically and socially responsible travel, there has been an increase in interest in the notion of an eco-destination image in recent years (Emir et al., 2016). Natural beauty, conservation measures, and sustainable tourism practices distinguish a location as an “eco-destination,” according to Buhalis and Costa (2005). Evaluating the current research that investigates the elements affecting this correlation is critical to comprehend the link between an eco-destination’s image and environmental attitudes. While prior research has shown a favorable relationship between eco-destination image and environmental attitudes, it is crucial to note that intentions may not always convert into actions. For example, Gursoy et al. (2014) and Nam et al. (2022) suggest that the image of an eco-destination does not always correspond to visitors’ actual ecologically responsible conduct. The effect of an eco-destination’s image on environmental attitudes may also be impacted by tourists’ values and motivations (N. T. K. Chi & Pham, 2022). Furthermore, sustainable tourism infrastructure and services must be considered in molding tourists’ environmental attitudes and activities (Bilynets & Knezevic Cvelbar, 2022). Furthermore, past environmental views and experiences of tourists may modify the relationship between eco-destination image and environmental concern (C. G. Q. Chi et al., 2018). While these characteristics may impose some constraints, some studies have shown a link between perceptions of ecotourism sites and actual environmental conservation actions. Pham and Khanh (2021), for example, discovered that the image of an eco-destination affected environmental concerns among Vietnamese ecotourists. Similarly, in Taiwan, Chiu et al. (2014b) showed a favorable association between an ecotourism destination’s image and tourists’ ecological attitudes and practices. The research offered the following hypothesis based on the current literature: T.-B. Luong

Journal of Hospitality and Tourism Management 57 (2023) 315–326 317 Hypothesis 1. Eco-destination image is positively associated with environmental beliefs. The research on ecotourism and destination image has underlined the relevance of environmental elements in determining passengers” views and actions (Ballantyne & Packer, 2011; Buhalis & Fletcher, 1995, pp. 3–24; Chiu et al., 2014b; Y. C. Huang & Liu, 2017; Hughes, 2013). These studies, for example, discovered that tourists’ views toward ecotourism are highly influenced by their assessment of an eco-destination’s natural features. While the general association between eco-destination and ecotourism mindset has been investigated, a better knowledge of the underlying processes and contextual subtleties is required. One difficulty in investigating the relationship between ecodestination and ecotourism mindset is the uncertainty surrounding the word “ecotourism.” According to Newsome et al. (2012), the absence of a standard definition for ecotourism makes it challenging to quantify and compare across situations. Moreover, several psychological aspects affect how a site is seen by visitors, which in turn affects their eco-friendly behavior (S. Huang & Hsu, 2009). Therefore, some researchers have identified a favorable link between the eco-friendly attitudes of tourists and the reputation of an eco-destination, while others have not (Tasci & Gartner, 2007; Thi Khanh & Phong, 2020). Furthermore, the influence of natural resources on visitors’ perceptions of the environment is not fully within the control of the site’s characteristics. Ecotourism perceptions and beliefs may be shaped by travelers’ backgrounds, upbringings, and worldviews (Gossling ¨ et al., 2015). All of these pieces help researchers get a fuller picture of how ecotourism influences how people see a destination. Therefore, a more nuanced and thorough understanding of the dynamic connection between ecotourism and public perception of a site is necessary. Thus, the hypothesis was proposed: Hypothesis 2. Eco-destination image positively affects ecotourism attitude. The impression of a location is important in choosing a vacation destination and the behavior of tourists (Stylidis et al., 2017). Research indicates that cognitive and affective images impact destination loyalty (Stylidis et al., 2020). Moreover, tourists consider destination perceptions among the most significant factors when choosing a vacation spot (Pereira et al., 2021). In the context of ecotourism, according to previous studies (C. F. Chen & Tsai, 2007; Chiu et al., 2014a); Chiu et al., 2014b destination’s eco-friendly reputation may greatly influence how likely people are to attend. For example, C. F. Chen and Tsai (2007) discovered that tourists were more likely to visit an ecotourism spot if they had a favorable impression of the area. In addition, Chiu et al. (2014a) showed that a favorable image of an ecotourism site directly benefits travelers’ decisions to go there. However, it is worth noting that tourists’ environmental values and beliefs might impact how they perceive ecotourism destinations (Kotler et al., 2021). The intricacy of the eco-destination image and its influence on ecotourism intention calls for a more careful literature analysis. Thus, the following hypothesis was proposed: Hypothesis 3. Eco-destination image positively affects ecotourism intention. 2.4. Environmental beliefs Several studies have demonstrated that human behavior, including environmental behavior, is largely driven by beliefs (Ajzen & Fishbein, 2000; Line & Hanks, 2015; Schultz et al., 2004). People’s environmental beliefs have been categorized as general or specific depending on their attitudes and belief systems (Dietz et al., 1998; Stern et al., 1995). The environmental issues of water scarcity, ozone depletion, and global warming are specific beliefs (Stern, 2000). Environmental folklore is used to characterize common beliefs about the association between humans and the environment (Stern, 2000). Ecotourism is often considered a sustainable alternative to traditional tourism, promoting environmental awareness and conservation (N. T. K. Chi & Pham, 2022; Hunitie et al., 2022). Although there has been considerable research on the topic, there are still gaps and ambiguities in understanding how environmental values affect perspectives on ecotourism. While some research has found a positive correlation between ecotourism attitudes and environmental convictions (Cheng et al., 2013; Thi Khanh & Phong, 2020), other research has reported mixed or insignificant effects on ecotourism attitudes, environmental beliefs, knowledge, and ecological conservation-related behavior (M. F. Chen & Tung, 2014; T. T. H. Nguyen et al., 2019) (M. F. Chen & Tung, 2014; T. T. H. Nguyen et al., 2019). The level of impact that ecotourism has on individuals’ sense of connection to the natural environment is multifaceted and contingent upon several factors, including the specific activities and destinations individuals choose, as well as their backgrounds and objectives (Beaumont, 2001; N. T. K. Chi & Pham, 2022; Thi Khanh & Phong, 2020). Considering this, a more nuanced and critical perspective is required to comprehend the connection between ecotourism and environmental belief. Hence, the hypothesis was formulated: Hypothesis 4. Environmental belief positively affects ecotourism attitude. Specifically, several factors, including cultural expectations, individual priorities, and environmental contexts, might influence the strength of the connection between beliefs and actions (Bamberg & Moser, ¨ 2007; Li et al., 2021). Other factors, such as routines, convenience, and social identity, may have a role in shaping actual behavior, as has been established in research (Gifford, 2014; Verplanken & Roy, 2016). Some studies have shown a clear correlation between ecological attitudes and intentions to do environmentally friendly actions (Line & Hanks, 2015; Schultz et al., 2004), while others have found no correlation or a weak one (Bamberg & Moser, ¨ 2007; Gifford, 2014). Furthermore, depending on the environment and behavior under consideration, the type and degree of the link may change (Van der Werff et al., 2014). These complexities highlight the need to approach the study of the connection between beliefs and behavior with a healthy dose of skepticism and consider all factors that may affect that relationship. Tourists’ intentions to engage in ecological behaviors within the context of ecotourism may be influenced by some factors, including environmental beliefs, but also by, for example, the perceived benefits and costs of such behaviors, the availability of alternatives, and the impact of social norms and group identity (Korpela et al., 2008). As a result, the hypothesis was developed: Hypothesis 5. Environmental beliefs positively affect ecotourism intention. 2.5. Ecotourism attitudes The Theory of Planned Behavior (TPB) is widely used to describe and anticipate human behavior (Ajzen, 1991), including in environmental circumstances. The term “perceived behavioral control” describes how much power people believe they have over their actions. However, the TPB approach has been critiqued by some scholars for ignoring cultural norms and other contextual elements (Bamberg & Moser, ¨ 2007; Stern, 2000). It has been investigated how environmental attitude and behavior are related to environmental behavior (Milfont & Duckitt, 2010). Environmental attitude and behavior positively correlate with tourism (T. H. Lee, 2007; Tsung Hung Lee & Jan, 2015; W. H. Lee & Moscardo, 2005). It has been pointed out that these studies rely too heavily on self-reported behaviors and fail to consider social norms and other contextual factors (Gossling ¨ et al., 2015; Kim & Stepchenkova, 2020). This research posits that a good ecotourism mindset impacts ecotourism T.-B. Luong

Journal of Hospitality and Tourism Management 57 (2023) 315–326 318 intention to address this gap in the existing knowledge. However, it is critical to understand TPB’s limits and the possible effect of the environment on behavior. Thus, the hypothesis was formulated: Hypothesis 6. Ecotourism attitudes positively affect ecotourism intention. 2.6. Biospheric values Previously, consumers’ environmental beliefs and behaviors were influenced by three distinct value orientations: egoistic, social-altruistic, and biospheric (de Groot & Steg, 2008; Stern, 2000). Biospheric values were defined as “people judging phenomena based on costs or benefits to ecosystems or the biosphere” (Stern & Dietz, 1994, p. 70). Studies of biospheric values have been conducted in various settings to understand better the factors that influence adopting environmentally friendly practices. Research in this area encompasses consumer habits related to the environment (T. N. Nguyen et al., 2016), dietary changes (Van der Werff et al., 2014), the energy sector (Van der Werff et al., 2013), and the determinants of biospheric values (Beall et al., 2021; Martin & Czellar, 2017). Identifying research needs and limits requires a comprehensive review of the available literature. According to some scholars, the conceptualization of biospheric values (Beall et al., 2021; de Groot & Steg, 2008; Norgaard, 2011) is insufficiently nuanced to encompass the complexities of individuals’ environmental beliefs and motivations. For instance, de Groot and Steg (2008) suggested that the biospheric value orientation may not adequately capture individuals’ ethical considerations, such as their beliefs regarding justice and impartiality in environmental decision-making. Similarly, Norgaard (2011) suggested that social and cultural elements impact environmental attitudes and actions, which the biospheric value orientation may overlook. Some academics have questioned the assumption that biospheric values always benefit the ecosystem. Trade-offs between environmental and non-environmental objectives may occur, for example, when people with high biospheric values simultaneously have opposing beliefs about economic development or personal convenience (Kurz & Prosser, 2021; Levi, 2021). The link between biospheric values and environmental behavior may be moderated by other variables, such as perceived behavioral control and social standards (Bamberg & Moser, ¨ 2007; Gatersleben et al., 2014). Despite these limitations, biospheric values have been widely used in tourism and hospitality research to understand customers’ attitudes and actions regarding sustainable tourism practices (Tanford et al., 2020; X. Zhang et al., 2020). Biospheric values moderate the outcomes of various stimuli on ecotourism attitudes and intentions, such as gain-framed corporate social responsibility messages and environmentally framed destination images (O’Rourke & Ringer, 2016; Stadlthanner et al., 2022). In the context of this study, researchers argue that biospheric values may play a role in moderating the associations between perceptions of eco-destinations as environmentally friendly, positive attitudes toward eco-travel, and actual ecotourism behavior. As a result, the following hypotheses were put forward: Hypothesis 7. Biospheric values positively moderate the relationship between eco-destination image and ecotourism intention. Hypothesis 8. Biospheric values positively moderate the relationship between environmental beliefs and ecotourism intention. Hypothesis 9. Biospheric values positively moderate the relationship between ecotourism attitudes and ecotourism intention. According to the research hypotheses, a conceptual model was developed to demonstrate the interrelationships among eco-destination image, environment beliefs, ecotourism attitudes, eco-behavioral intention, biospheric values, and ecotourism intention, as shown in Fig. 1. 3. Methodology 3.1. Eco-destination site Due to its pristine natural beauty and rich cultural heritage, Mang Den, as shown in Fig. 2, is a concealed jewel gaining popularity in ecotourism. The region has numerous minority ethnic groups with traditions and customs. In addition to immersing themselves in the local culture, visitors to Mang Den can experience outdoor activities such as hiking, camping, and bird watching. The area, with its pristine lakes, waterfalls, and mountainous terrain, offers breathtaking vistas and opportunities to reconnect with nature. Mang Den offers a distinctive ecotourism experience that appeals to tourists interested in responsible and sustainable tourism practices. Vietnam’s ecotourism initiatives aim to positively impact local communities and the environment by promoting environmentally friendly activities and preserving the natural beauty of destinations. Fig. 1. The research theoretical framework. T.-B. Luong

Journal of Hospitality and Tourism Management 57 (2023) 315–326 319 3.2. Measurements A survey questionnaire was developed using latent variables such as eco-destination image, environmental beliefs, ecotourism attitudes, and ecotourism intention, as well as the moderating effect of biospheric values. The questionnaire was sent to three ecotourism specialists for review. A preliminary questionnaire evaluation was administered to a sample of the prospective target audience. An item analysis was performed on each questionnaire item. Any item that failed to meet two or more criteria was eliminated. In addition, research questionnaire items were modified for readability and clarity based on feedback from the three academicians and participants. Finally, the formal questionnaire was developed. The eco-destination image was evaluated using five items adapted from earlier studies (N. T. K. Chi & Pham, 2022; Chiu et al., 2014b; Sharma & Nayak, 2018). For measuring environmental beliefs, five items were selected from previous research (Dunlap et al., 2000; Li et al., 2021) and were modified suitably. To measure ecotourism attitudes, five items were derived from earlier studies (S. Huang & Hsu, 2009; Kim & Stepchenkova, 2020) (references). Ecotourism intention was evaluated with four items adapted from previous studies (Y. C. Huang & Liu, 2017; Hultman et al., 2015; Pham & Khanh, 2021). The biospheric values constructs were examined using four items (Tsung Hung Lee & Jan, 2018; Wang et al., 2021). All variables (Fig. 1) were measured on a five-point scale. 3.3. Data collection and analysis Data for the study was collected through an online survey distributed across popular social media platforms, such as Facebook, Zalo, and Instagram. This method, specifically convenient sampling, was appropriate for the study, given its convenience and the ability to reach a large sample size within the given time frame. Convenient sampling allowed researchers to select participants based on their accessibility and willingness to participate. The survey questions were created in the English language prior to undergoing translation into Vietnamese. In order to guarantee the accuracy of the translation, two researchers who are native Vietnamese speakers and specialize in the domains of hospitality and tourism conducted a reverse translation. This approach aids in preserving the consistency and accuracy of the survey’s questions and responses. Convenience sampling was used for collecting data between March 7 and June 25, 2023. This method is effective in earlier research (Akhtar et al., 2020; Zhou et al., 2023). At the beginning of the survey, respondents were given a screening question, “Was your visit to Mang Den motivated by ecotourism activities?” Only those who answered yes were included in the final count. The respondents’ frequency of visits to Mang Den was also inquired about using a filter question. Those who answered “0″ were later excluded from the study. This ensured the respondents were familiar with Mang Den as an ecotourism destination. In summary, the study received 723 responses after the first filter questionnaire. However, only 683 of these responses met the eligibility criteria, as they were received from individuals under 18 years of age and had previously visited Mang Den. These 683 responses were used for analysis after applying the relevant filters. The proposed research model was evaluated using partial least squares structural equation modeling (PLS-SEM) analysis. PLS-SEM is suitable for exploratory investigations because it imposes fewer restrictions on the normal data distribution (Hair et al., 2019). Thus, SmartPLS 4.0 was utilized (Henseler et al., 2015). 4. Results 4.1. Participants’ characteristic The table presents the demographic characteristics and past visitation frequency of the participants. The majority of the respondents were female (58.86%), married (55.64%), and aged between 18 and 29 years (55.34%). Regarding education, most of the respondents had an undergraduate degree (69.99%). Regarding occupation, the largest group was private company employees (30.16%), followed by students (20.94%). Regarding past visits to Mang Den, most respondents had Fig. 2. Mang den tourism maps (Cuongphuot.info, 2023; Touringvietnam.com, 2023). T.-B. Luong

Journal of Hospitality and Tourism Management 57 (2023) 315–326 320 visited once (63.10%), while 36.90% had visited two times or more (See Table 1). 4.2. Normality and common method bias test; reliability and validity All the values for skewness and kurtosis between − 3 and +3 (Table 2) are considered acceptable in order to prove normal univariate distribution (Kallner, 2017) (see Table 3). All variance inflation factor (VIF) values were less than 5 (Table 2), indicating that there was no collinearity problem in the study (Hair et al., 2019). After a Smart-PLS 4.0 reliability analysis, the overall Cronbach’s alpha values and CR values for all variables were greater than 0.7, indicating that the questionnaire had acceptable internal consistency (Hair et al., 2014) (Table 2). All factor loading values exceeded 0.6 (Hair et al., 2006) (Table 2 and Fig. 3). The AVE scores were also greater than 0.50 (Fornell & Larcker, 1981) (Table 2), supporting the convergent validity further (Hair et al., 2019). Discriminant validity of the model was established since all the results of the (heterotrait-monotrait) HTMT criterion were below the critical value of 0.9 (Hair et al., 2019); however, some HTMT values are higher than 0.9 and under 0.95 (Table 2). Previous studies have mentioned HTMT values under 0.95, and discriminant validity is established (Antoniadis et al., 2022; Zabukovˇsek et al., 2022). For example, Antoniadis et al. (2022) stated that “the HTMT is under 0.85 or at least under 0.95, discriminant validity is established” (p. 8). Thus, the HTMT values in this study are accepted (Table 2). 4.3. Predictive capability Predictive accuracy and relevance were evaluated to assess a model’s predictive capability. The coefficient of determination (R2 ), which described variance for separately endogenous latent variables, was used for an initial evaluation (Hair et al., 2014). The outcomes resulted in a 76.6% variance in ecotourism attitudes (ATT), 74.3% in environmental beliefs (BEL), and 76.2% in ecotourism intention (INT) explained by model constructs. Second, the value of Q2 > 0 was applied to Smart-PLS 4.0 using the blindfolding procedure to evaluate the predictive meaning of the endogenous variable in the comprehensive concept (Chin, 2010). The outcomes showed that all Q2 values, including ATT (0.545), BEL (0.522), and INT (0.525), are positive and greater than 0.35, thus having a strong predictive significance (Hair et al., 2019). 4.4. Hypothesis analysis The outcomes presented that all hypotheses were accepted (Table 4 and Fig. 4). The hypothesis showed that eco-destination images positively impact environmental beliefs (H1: β = 0.862, t = 57.856, p < 0.01). Eco-destination image positively impacts ecotourism attitudes (H2: β = 0.285, t = 6.042, p < 0.01). Eco-destination image positively impacts ecotourism intention (H3: β = 0.186, t = 4.137, p < 0.01). Environmental beliefs significantly impact ecotourism attitudes (H4: β = 0.617, t = 13.205, p < 0.01). Environmental beliefs positively impact ecotourism intention (H5: β = 0.158, t = 3.341, p < 0.01). Ecotourism attitudes positively impact ecotourism intention (H6: β = 0.398, t = 9.254, p < 0.01). In addition, the biospheric values variable is also found to moderate the relationship between eco-destination image and ecotourism intention (H7: β = − 0.064, t = 2.154, p < 0.05); between environmental beliefs and ecotourism intention (H8: β = − 0.080, t = 2.111, p < 0.05); and between place attachment and behavior intention (H9: β = 0.160, t = 4.701, p < 0.01). 5. Discussion and conclusion 5.1. Discussion The results of this study corroborate the first hypothesis, as there is a positive correlation between eco-destination images and environmental beliefs. This conclusion is consistent with prior studies suggesting that tourists’ environmental attitudes and actions are positively influenced by eco-destination image (Bilynets & Knezevic Cvelbar, 2022; Chiu et al., 2014b; Line & Hanks, 2015; Pham & Khanh, 2021). The image of an eco-destination reflects a positive view of the environment and a dedication to sustainability, which may inspire visitors to acquire stronger environmental values and beliefs (J. S. Chen & Gursoy, 2001; Pham & Khanh, 2021). This finding underscores the importance of using ecotourism marketing and communication strategies to enhance tourists’ perception of eco-destinations and raise their awareness about the natural environment. Environmentally conscious businesses may profit from promoting the region as an ecotourism destination (Mowforth & Munt, 2015). The result confirms the second hypothesis, establishing a link between ecotourism attitudes and eco-destination images. Because of this research, tourists’ views toward ecotourism may be significantly influenced by their opinions of an eco-destination’s image. The importance of the eco-destination image has also been investigated previously (Ballantyne & Packer, 2011; Y. C. Huang & Liu, 2017; Line & Hanks, 2015; Thi Khanh & Phong, 2020). Because the eco-destination image represents a commitment to sustainability and environmental protection, it may improve tourists’ perception of the destination’s environmental and socio-cultural values, increasing the likelihood of engaging in ecotourism there (Mihaliˇc, 2000). As a result, visitors may form more favorable impressions of ecotourism pursuits, including hiking, animal watching, and cultural immersion (Gossling ¨ et al., 2015). This discovery has real-world applications for ecotourism businesses and destination marketers that prioritize sustainable tourism and want to entice eco-travelers. Ecotourism businesses may enhance visitors’ views of ecotourism and get them to adopt sustainable habits by stressing the eco-destination image in their advertising and public relations efforts (Gossling ¨ et al., 2015; Thi Khanh & Phong, 2020). Based on the findings, the fourth hypothesis is supported by a Table 1 Respondents’ information. Variable Responses Frequency Percent Gender Male 281 41.14 Female 402 58.86 Marital status Single 303 44.36 Married 380 55.64 Age (year) 18–29 378 55.34 30–40 225 32.94 41–50 80 11.71 Education High school 87 12.74 Undergraduate 478 69.99 Postgraduate 118 17.28 Occupation Student 143 20.94 Government officials 92 13.47 Private company 206 30.16 Own business 111 16.25 Others 131 19.18 Past visitation to Mang Den One time 431 63.10 Two times or more 252 36.90 Table 2 The results of discriminant validity analysis (HTMT criterion). Constructs ATT BEL BIO EDI INT Ecotourism attitudes (ATT) Environmental beliefs (BEL) 0.926 Biospheric values (BIO) 0.720 0.679 Eco-destination image (EDI) 0.928 0.885 0.719 Ecotourism intention (INT) 0.937 0.909 0.810 0.925 T.-B. Luong

Journal of Hospitality and Tourism Management 57 (2023) 315–326 321 significant positive correlation between environmental beliefs and ecotourism attitudes. According to this study (Beaumont, 2001; Cheng et al., 2013; N. T. K. Chi & Pham, 2022; Hunitie et al., 2022; Thi Khanh & Phong, 2020), sustainable tourism attitudes and actions are significantly influenced by visitors’ environmental beliefs. Since visitors who hold strong environmental beliefs are more likely to value sustainable tourism and take environmentally responsible actions, there is a positive relationship between environmental beliefs and ecotourism attitudes (N. T. K. Chi & Pham, 2022; Hunitie et al., 2022). As a result, people could see ecotourism in a more favorable light and be more willing to try it. The ramifications of this discovery for ecotourism businesses and destination marketers that want to entice ecotourists and promote Table 3 Results of first-order factor. Latent variable/items Excess kurtosis Skewness VIF Factor loading AVE CR Cronbach’s alpha Eco-destination image (EDI) 0.634 0.856 0.856 EDI1 Mang Den boasts a pleasant climate. 1.477 − 0.943 2.153 0.817 EDI2 The destination enjoys political stability, ensuring tourists’ safe and secure trips. 0.302 − 0.361 2.133 0.793 EDI3 The landscape of Mang Den is breathtakingly beautiful, making it a must-visit destination. 0.659 − 0.782 2.088 0.803 EDI4 Mang Den has an excellent reputation as an eco-friendly destination among travelers. 2.677 − 1.845 2.357 0.772 EDI5 The natural environment of Mang Den remains unpolluted and unspoiled, offering a unique and authentic experience to visitors. 2.078 − 2.223 2.510 0.796 Environmental beliefs (BEL) 0.711 0.899 0.897 BEL1 If things continue on their present course, we will soon experience a major ecological catastrophe. 2.331 − 2.021 1.679 0.753 BEL2 When humans interfere with nature, it often produces disastrous results. 0.267 − 0.636 2.016 0.811 BEL3 The Earth is like a spaceship with limited room and resources. 0.721 − 0.84 2.543 0.859 BEL4 The balance of nature is very delicate and easily upset. 0.566 − 0.663 3.879 0.894 BEL5 Despite our special abilities, humans are still subject to the laws of nature. 0.564 − 0.664 3.614 0.891 Ecotourism attitudes (ATT) 0.719 0.905 0.902 ATT1 I find ecotourism to be enjoyable. 0.342 − 0.497 2.764 0.857 ATT2 I have a favorable attitude towards ecotourism. 1.094 − 0.739 2.771 0.858 ATT3 Ecotourism is fun and exciting for me. 0.939 − 0.796 2.570 0.864 ATT4 I find ecotourism to be a pleasant experience 1.024 − 1.015 3.113 0.858 ATT5 It is a positive experience that leaves me feeling fulfilled and satisfied. 0.716 − 1.085 2.637 0.801 Biospheric values (BIO) 0.581 0.789 0.765 BIO1 I prioritize preventing environmental pollution. − 0.488 − 0.58 1.916 0.763 BIO2 I believe in protecting the environment. 0.237 − 0.844 1.982 0.838 BIO3 Respecting nature is important to me. − 0.086 − 0.72 1.380 0.667 BIO4 I strive to be in harmony with nature. 2.771 − 1.592 1.351 0.773 Ecotourism intention (INT) 0.696 0.864 0.852 INT1 I prioritize choosing ecotourism in my travels. 0.698 − 0.804 2.440 0.870 INT2 I plan to visit an eco-friendly destination like Mang Den in the near future. 1.04 − 0.958 2.486 0.880 INT3 I carefully select ecotourism tours that align with my values and beliefs. 1.694 − 1.112 2.208 0.858 INT4 I strongly believe that ecotourism is the responsible and sustainable way to travel. − 0.511 − 0.434 1.496 0.718 Note: CR: Composite Reliability; AVE: Average Variance Extracted. Fig. 3. Factor loading values. T.-B. Luong

Journal of Hospitality and Tourism Management 57 (2023) 315–326 322 sustainable tourism are substantial. By spreading environmental awareness and education, ecotourism businesses may change visitors’ negative perceptions of the environment and increase interest in ecotourism. Moreover, by offering eco-friendly facilities and services, ecotourism operators may encourage visitors to participate in sustainable tourism activities that help conserve natural resources and biodiversity. As a result of the findings, hypotheses three, five, and six are supported since eco-destination image, environmental beliefs, and ecotourism attitudes all predict ecotourism intention. The findings of this study are in alignment with previous research indicating that tourists’ intentions to participate in ecotourism activities are significantly influenced by their impressions of eco-destinations, their environmental beliefs, and their ecotourism attitudes (Bamberg & Moser, ¨ 2007; Brown et al., 2010; Chiu et al., 2014a; Han et al., 2010; W. H. Lee & Moscardo, 2005; Li et al., 2021; Van der Werff et al., 2014). A positive impact of eco-destination image, environmental beliefs, and ecotourism attitudes on ecotourism intention is likely to be attributed to tourists’ perceptions of eco- and socio-cultural values, as well as their commitment to sustainability (Gossling ¨ et al., 2015; Kim & Stepchenkova, 2020). Visitors with a favorable impression of eco-destinations, similar environmental values, and positive views about ecotourism are likelier to participate in conservation efforts. This discovery has real-world applications for ecotourism businesses and destination marketers that prioritize sustainable tourism and want to entice eco-travelers. Ecotourism operators may promote eco-tourist intents and support sustainable tourism behaviors by stressing the eco-destination image, environmental awareness, and ecotourism activities in their marketing and communication methods. The results support hypotheses seven, eight, and nine by showing that biospheric values moderate the relationship between ecodestination image, environmental beliefs, place attachment, and ecotourism intention. As a result of this finding, ecotourism research must consider individual differences when analyzing relationships between these variables (Wesley Schultz, 2001). Vital biospheric value tourists may have more significant requirements for eco-friendly travel. They may be more critical of destinations that do not meet them, which may explain the negative moderating effect of biospheric values on the relationship between eco-destination image and ecotourism intention (Dietz et al., 1998). Consequently, individuals may be less inclined to visit ecotourism sites that contradict their environmental values. In addition, as a result of stronger biospheric values, tourists with greater ecotourism intention may have a more holistic and interconnected view of the environment and may also take into account other social and economic factors when assessing the sustainability of tourism practices (Wesley Schultz, 2001) that moderate the relationship between environmental beliefs and ecotourism intention. As a result, people may exercise more caution and care in their conduct during ecotourism-related activities. In addition, biospheric values may positively moderate the association between ecotourism attitudes and behavior intentions (O’Rourke & Ringer, 2016; Ramkissoon et al., 2013; Stadlthanner et al., 2022). Consequently, tourists with higher biospheric values are more committed and emotionally attached to eco-destinations and are more Table 4 SEM results. Hypothesis Path Beta STDEV t-value P-value Decision H1 Eco-destination image → Environmental beliefs 0.862 0.015 57.856 0.000 AC H2 Eco-destination image → Ecotourism attitudes 0.285 0.047 6.042 0.000 AC H3 Eco-destination image → Ecotourism intention 0.186 0.045 4.137 0.000 AC H4 Environmental beliefs → Ecotourism attitudes 0.617 0.047 13.205 0.000 AC H5 Environmental beliefs → Ecotourism intention 0.158 0.047 3.341 0.001 AC H6 Ecotourism attitudes → Ecotourism intention 0.398 0.043 9.254 0.000 AC H7 Eco-destination image*Biospheric values → Ecotourism intention − 0.064 0.030 2.154 0.031 AC H8 Environmental beliefs*Biospheric values → Ecotourism intention − 0.080 0.038 2.111 0.035 AC H9 Ecotourism attitudes*Biospheric values → Ecotourism intention 0.160 0.034 4.701 0.000 AC Note: STDEV: Standard deviation; AC: accepted; NA: not accepted. Fig. 4. Results of PLS-SEM analysis. T.-B. Luong

Journal of Hospitality and Tourism Management 57 (2023) 315–326 323 inclined to engage in sustainable tourism practices to conserve and protect them. In order to fully understand the dynamics between eco-destination image, environmental beliefs, place attachment, and ecotourism purpose, it is crucial to account for individual characteristics like biospheric values. More study is needed to fully understand the interaction between these factors and uncover more factors that may affect tourists’ perspectives and decisions regarding ecotourism. In conclusion, this study examined visitors’ ecotourism intentions by incorporating the VIP model into a conceptual framework. This research focused on ecotourists who visited Mang Den, Vietnam’s emerging ecotourism destination. Significant progressive relationships were found between eco-destination image, environmental beliefs, and ecotourism attitudes, influencing ecotourism intention. In addition, the results indicate that biospheric values moderate the relationships between the variables above and ecotourism intention. 5.2. Theoretical implications Important theoretical implications for understanding the interconnected nature of eco-destination image, environmental views, ecotourism attitudes, biospheric values, place attachment, and ecotourism intention are generated by this research using the VIP model as a conceptual framework. Stern (2000) and van der Werff and Steg (2016) propose that values, identity, and personal norms are key determinants of pro-environmental behavior. Connections between eco-destination image, environmental beliefs, place connection, and ecotourism intention were shown to be moderated by biospheric values, which stand for a personal value associated with environmental preservation and conservation. This is consistent with previous research emphasizing the importance of considering individual differences in ecotourism research (Ramkissoon et al., 2013; Wesley Schultz, 2001). This research indicates that visitors’ ethical beliefs significantly influence their perspectives and decisions about ecotourism. The positive associations between eco-destination image, environmental beliefs, ecotourism attitudes, and ecotourism intention, which reflect a sense of responsibility to engage in environmentally conscious actions, may also be significant predictors of ecotourism behavior. According to the literature (Bamberg & Moser, ¨ 2007), individual values and beliefs are strong indicators of environmentally friendly actions. It was also shown that a favorable outlook on one’s hometown positively affected the likelihood of participating in ecotourism. According to the VIP model (Dietz et al., 1998; van der Werff & Steg, 2016), which emphasizes the importance of a person’s sense of self, this data reveals that identity is a strong predictor of ecological behavior. This study underscores the significance of individual heterogeneity in ecotourism research by showing how biospheric values moderate the connection between location sentiments and action intention. Building upon the work of Stern (2000) and van der Werff and Steg (2016), who emphasize the role of values, identity, and personal norms in pro-environmental behavior, the research reveals important connections between eco-destination image, environmental beliefs, place attachment, and ecotourism intention. The study demonstrates that biospheric values moderate these connections and highlight the significance of individual differences in ecotourism studies (Beall et al., 2021; S. Lee et al., 2021). Moreover, these findings support the proposition that ecodestination images positively influence environmental beliefs and ecotourism attitudes. This result aligns with previous research suggesting that positive perceptions of eco-destinations can contribute to the development of pro-environmental attitudes (Bilynets & Knezevic Cvelbar, 2022; Line & Hanks, 2015; Pham & Khanh, 2021; Thi Khanh & Phong, 2020). It underlines the need to advertise eco-destinations that conjure powerful positive images to encourage tourists’ environmental views and values. Furthermore, the research found that environmental views influenced ecotourism attitudes and intentions considerably. This conclusion emphasizes the significance of personal environmental values in determining people’s views about ecotourism and intentions to participate in ecotourism activities (Beall et al., 2021; N. T. K. Chi & Pham, 2022; Hunitie et al., 2022; Li et al., 2021). By recognizing the influence of environmental beliefs on intention, policymakers and destination managers can focus on fostering and nurturing these beliefs among visitors to promote sustainable tourism practices. Overall, this study enhances the theoretical understanding of ecodestination image, environmental beliefs, ecotourism attitudes, and ecotourism intention. By employing the VIP model as a conceptual framework and providing empirical evidence, the study contributes to the literature by highlighting the interconnectedness of these variables and the moderating role of biospheric values. These findings have implications for destination managers, policymakers, and marketers to design effective strategies and interventions that promote sustainable tourism practices. 5.3. Practical implication The findings of this study have substantial practical significance for developing effective marketing and public relations initiatives to boost ecotourism and lessen its detrimental effects on natural habitats. More specifically, to boost the number of individuals who want to visit an ecodestination, the findings suggest that marketing materials and campaigns should emphasize the eco-destination’s image, environmental views, and ecotourism attitudes (N. T. K. Chi & Pham, 2022). Tourists’ impressions of a place and interest in participating in ecotourism activities are influenced by various variables, including the destination’s dedication to environmental protection and sustainable tourism practices. One approach is to highlight the destination’s efforts to protect the environment and its economic benefits to visitors. In addition, the findings suggest that raising awareness and understanding of environmental issues among tourists is a promising avenue for fostering ecotourism. One way to do this is to educate visitors about the environment, stress the need for conservation, and inspire them to practice sustainable tourism while in town. Important implications for creating niche marketing and communication strategies stem from biospheric values mediating between ecodestination image, environmental beliefs, and ecotourism intention. Messages emphasizing the need to protect and conserve the environment may find more receptive audiences among these people (Stern et al., 1995; van der Werff & Steg, 2016). The findings also suggest that a sense of connection to one’s geographic location may significantly predict ecotourism behavior. Biospheric values may moderate the link between place attitudes and ecotourism intention. This result indicates that ecotourism locations may want to focus on fostering eco-destination attitudes among tourists by highlighting the location’s unique natural elements or cultural legacy. For example, tour operators might arrange for their clients to participate in community service projects or environmental education programs (Ramkissoon et al., 2013). Based on the results, ecotourism hotspots should focus on appealing to visitors’ values and identities through tailored marketing and communication strategies and on creating opportunities for visitors to develop an emotional connection to the places they visit. Eco-friendly venues may promote sustainable tourism by enticing tourists to embrace ecologically responsible habits. 5.4. Limitations and recommendations In light of these results, the following limitations should be considered. The convenience sampling used in this research may restrict the capacity to reliably transfer the findings to other ecotourism destinations. As a result, it is critical to note that the results of this research are peculiar to the Mang Den ecotourism location in Vietnam. Moreover, the potential bias in the demographic profile of the participants was also a limitation in this study. It is advised that future studies include a larger T.-B. Luong

Journal of Hospitality and Tourism Management 57 (2023) 315–326 324 variety of ecotourism venues to establish the degree to which these results may be generalized across diverse locales and cultures. Furthermore, a more extensive and varied sample might improve the findings’ generalizability. The research did not look at other factors affecting ecotourism behavior, such as the cost or difficulty of getting to ecotourism destinations. Understanding ecotourism in the future may need research into these areas. More in-depth knowledge of ecological behavior may emerge from future studies that combine quantitative and qualitative approaches. This research only examined the moderating influence of biospheric values on the relationships between ecodestination image, environmental perspectives, and ecotourism intention. Future studies need to look at the moderating impacts of other factors, such as cultural values, individual traits, and environmental knowledge, to get a fuller picture of the factors that shape ecotourism behavior. Furthermore, higher HTMT values in this study may imply that certain constructs have less internal consistency. This could be attributed to the unique nature of the components within the variable scale or other aspects that require further investigation. Future studies could explore alternative measurements or modify the elements of the construct to enhance dependability. Declaration of competing interest None. References Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T Ajzen, I., & Fishbein, M. (2000). Attitudes and the attitude-behavior relation: Reasoned and automatic processes. European Review of Social Psychology, 11(1), 1–33. https:// doi.org/10.1080/14792779943000116 Akhtar, N., Jin, S., Alvi, T. H., & Siddiqi, U. I. (2020). Conflicting halal attributes at halal restaurants and consumers’ responses: The moderating role of religiosity. Journal of Hospitality and Tourism Management, 45, 499–510. https://doi.org/10.1016/j. jhtm.2020.10.010 Antoniadis, K., Zafiropoulos, K., & Mitsiou, D. (2022). Measuring distance learning system adoption in a Greek university during the pandemic using the UTAUT model, trust in government, perceived university efficiency and coronavirus fear. Education Sciences, 12(9), 1–19. https://doi.org/10.3390/educsci12090625 Ates¸, H. (2020). Merging theory of planned behavior and value identity personal norm model to explain pro-environmental behaviors. Sustainable Production and Consumption, 24, 169–180. https://doi.org/10.1016/j.spc.2020.07.006 Ballantyne, R., & Packer, J. (2011). Using tourism free-choice learning experiences to promote environmentally sustainable behaviour: The role of post-visit “action resources.”. Environmental Education Research, 17(2), 201–215. https://doi.org/ 10.1080/13504622.2010.530645 Bamberg, S., & Moser, ¨ G. (2007). Twenty years after hines, hungerford, and tomera: A new meta-analysis of psycho-social determinants of pro-environmental behaviour. Journal of Environmental Psychology, 27(1), 14–25. https://doi.org/10.1016/j. jenvp.2006.12.002 Beall, J. M., Boley, B. B., Landon, A. C., & Woosnam, K. M. (2021). What drives ecotourism: Environmental values or symbolic conspicuous consumption? Journal of Sustainable Tourism, 29(8), 1215–1234. https://doi.org/10.1080/ 09669582.2020.1825458 Beaumont, N. (2001). Ecotourism and the conservation ethic: Recruiting the uninitiated or preaching to the converted? Journal of Sustainable Tourism, 9(4), 317–341. https://doi.org/10.1080/09669580108667405 Bilynets, I., & Knezevic Cvelbar, L. (2022). Tourist pro-environmental behaviour: The role of environmental image of destination and daily behaviour. Annals of Tourism Research Empirical Insights, 3(2), Article 100070. https://doi.org/10.1016/j. annale.2022.100070 Bjork, ¨ P. (2000). Ecotourism from a conceptual perspective, an extended definition of a unique tourism form. International Journal of Tourism Research, 2(3), 189–202. https://doi.org/10.1002/(sici)1522-1970(200005/06)2:3<189::aid-jtr195>3.3.co; 2-k Bouman, T., Steg, L., & Kiers, H. A. L. (2018). Measuring values in environmental research: A test of an environmental portrait value questionnaire. Frontiers in Psychology, 9(APR). https://doi.org/10.3389/fpsyg.2018.00564 Brochado, A. (2019). Nature-based experiences in tree houses: Guests’ online reviews. Tourism Review, 74(3), 310–326. https://doi.org/10.1108/TR-10-2017-0162 Brown, T. J., Ham, S. H., & Hughes, M. (2010). Picking up litter: An application of theory-based communication to influence tourist behaviour in protected areas. Journal of Sustainable Tourism, 18(7), 879–900. https://doi.org/10.1080/ 09669581003721281 Buhalis, D., & Costa, C. (2005). Tourism business frontiers: Consumers, products and industry. In Tourism business frontiers: Consumers, products and industry. https://doi. org/10.4324/9780080455914 Buhalis, D., & Fletcher, J. (1995). Environmental impacts on tourist destinations: An economic analysis. Sustainable Tourism Development. Chen, J. S., & Gursoy, D. (2001). An investigation of tourists’ destination loyalty and preferences. International Journal of Contemporary Hospitality Management, 13(2), 79–85. https://doi.org/10.1108/09596110110381870 Cheng, T. M., Wu H, C., & Huang, L. M. (2013). The influence of place attachment on the relationship between destination attractiveness and environmentally responsible behavior for island tourism in Penghu, Taiwan. Journal of Sustainable Tourism, 21(8), 1166–1187. https://doi.org/10.1080/09669582.2012.750329 Chen, C. F., & Tsai, D. C. (2007). How destination image and evaluative factors affect behavioral intentions? Tourism Management, 28(4), 1115–1122. https://doi.org/ 10.1016/j.tourman.2006.07.007 Chen, M. F., & Tung, P. J. (2014). Developing an extended Theory of Planned Behavior model to predict consumers’ intention to visit green hotels. International Journal of Hospitality Management, 36, 221–230. https://doi.org/10.1016/j.ijhm.2013.09.006 Chin, W. W. (2010). How to write up and report PLS analyses. In Handbook of partial least squares (pp. 655–690). https://doi.org/10.1007/978-3-540-32827-8_29 Chi, C. G. Q., Pan, L., & Del Chiappa, G. (2018). Examining destination personality: Its antecedents and outcomes. Journal of Destination Marketing & Management, 9, 149–159. https://doi.org/10.1016/j.jdmm.2018.01.001 Chi, N. T. K., & Pham, H. (2022). The moderating role of eco-destination image in the travel motivations and ecotourism intention nexus. Journal of Tourism Futures, 1–17. https://doi.org/10.1108/JTF-01-2022-0014 Chiu, Y. T. H., Lee, W. I., & Chen, T. H. (2014a). Environmentally responsible behavior in ecotourism: Antecedents and implications. Tourism Management, 40, 321–329. https://doi.org/10.1016/j.tourman.2013.06.013 Chiu, Y. T. H., Lee, W. I., & Chen, T. H. (2014b). Environmentally responsible behavior in ecotourism: Exploring the role of destination image and value perception. Asia Pacific Journal of Tourism Research, 19(8), 876–889. https://doi.org/10.1080/ 10941665.2013.818048 Cuongphuot.info. (2023). Kinh nghiệm du lịch Mang ˘ Đen, Kon Tum. Cuongphuot.Info. https://cungphuot.info/kinh-nghiem-du-lich-mang-den-kon-tum-post27030. cp. Dietz, T., Stern, P. C., & Guagnano, G. A. (1998). Social structural and social psychological bases of environmental concern. Environment and Behavior, 30(4), 450–471. https://doi.org/10.1177/001391659803000402 Dunlap, R. E., Van Liere, K. D., Mertig, A. G., & Jones, R. E. (2000). Measuring endorsement of the new ecological paradigm: A revised nep scale. Journal of Social Issues, 56(3), 425–442. https://doi.org/10.1111/0022-4537.00176 Emir, O., Bayer, U., Erdogan, ˘ K., & Karamas¸a, Ç. (2016). Evaluating the destination attractions from the point of experts’ view: An application in eskis¸ehir. Turizam, 20 (2), 92–104. https://doi.org/10.5937/turizam1602092e Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312 Gatersleben, B., Murtagh, N., & Abrahamse, W. (2014). Values, identity and proenvironmental behaviour. Contemporary Social Science, 9(4), 374–392. https://doi. org/10.1080/21582041.2012.682086 Gifford, R. (2014). Environmental psychology matters. Annual Review of Psychology, 65, 541–579. https://doi.org/10.1146/annurev-psych-010213-115048 Godin, G., Conner, M., & Sheeran, P. (2005). Bridging the intention-behaviour “gap”: The role of moral norm. British Journal of Social Psychology, 44(4), 497–512. https://doi. org/10.1348/014466604X17452 de Groot, J. I. M., & Steg, L. (2008). Value orientations to explain beliefs related to environmental significant behavior: How to measure egoistic, altruistic, and biospheric value orientations. Environment and Behavior, 40(3), 330–354. https:// doi.org/10.1177/0013916506297831 Gossling, ¨ S., Scott, D., & Hall, C. M. (2015). Tourism and water: Interactions, impacts and challenges. Channel View Publications. Gursoy, D., Chen J, S., & Chi C, G. (2014). Theoretical examination of destination loyalty formation. International Journal of Contemporary Hospitality Management, 26(5), 809–827. https://doi.org/10.1108/IJCHM-12-2013-0539 Hadinejad, A., Moyle B, D., Scott, N., Kralj, A., & Nunkoo, R. (2019). Residents’ attitudes to tourism: A review. Tourism Review, 74(2), 157–172. https://doi.org/10.1108/TR01-2018-0003 Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis. Analysis. Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi. org/10.1108/EBR-11-2018-0203 Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106–121. https://doi.org/10.1108/EBR-10-2013- 0128 Han, H., Hsu, L. T., Jane), & Sheu, C. (2010). Application of the theory of planned behavior to green hotel choice: Testing the effect of environmental friendly activities. Tourism Management, 31(3), 325–334. https://doi.org/10.1016/j. tourman.2009.03.013 Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747- 014-0403-8 Hoang, S., Dey, S., Nguyen, V., & Tuckova, Z. (2022). A study on the positive impact of eWOM in eco-tourism destinations of Vietnam. International Conference on Tourism Research, 15(1), 149–158. https://doi.org/10.34190/ictr.15.1.134 T.-B. Luong

Journal of Hospitality and Tourism Management 57 (2023) 315–326 325 Huang, S., & Hsu, C. H. C. (2009). Effects of travel motivation, past experience, perceived constraint, and attitude on revisit intention. Journal of Travel Research, 48(1), 29–44. https://doi.org/10.1177/0047287508328793 Huang, Y. C., & Liu, C. H. S. (2017). Moderating and mediating roles of environmental concern and ecotourism experience for revisit intention. International Journal of Contemporary Hospitality Management, 29(7), 1854–1872. https://doi.org/10.1108/ IJCHM-12-2015-0677 Hughes, M. (2013). Ecotourists and views of nature. In International handbook on ecotourism (pp. 108–116). https://doi.org/10.4337/9780857939975.00015 Hultman, M., Kazeminia, A., & Ghasemi, V. (2015). Intention to visit and willingness to pay premium for ecotourism: THE impact of attitude, materialism, and motivation. Journal of Business Research, 68(9), 1854–1861. https://doi.org/10.1016/j. jbusres.2015.01.013 Hunitie, M. F., Saraireh, S., Al-Srehan, H. S., Al-Quran, A. Z., Alneimat, S., AlHawary, S. I., & Alshurideh, M. T. (2022). Ecotourism intention in Jordan: The role of ecotourism attitude, ecotourism interest, and destination image. Information Sciences Letters, 11(5), 1815–1822. https://doi.org/10.18576/isl/110537 Kallner, A. (2017). Laboratory statistics: Methods in chemistry and health sciences. In Laboratory statistics: Methods in chemistry and health sciences. https://doi.org/ 10.1016/C2017-0-00959-X Kim, M.-S., & Stepchenkova, S. (2020). Altruistic values and environmental knowledge as triggers of pro-environmental behavior among tourists. Current Issues in Tourism, 23 (13), 1575–1580. https://doi.org/10.1080/13683500.2019.1628188 Korpela, K. M., Yl´en, M., Tyrv¨ ainen, L., & Silvennoinen, H. (2008). Determinants of restorative experiences in everyday favorite places. Health & Place, 14(4). https:// doi.org/10.1016/j.healthplace.2007.10.008 Kotler, P., Bowen, J. T., Makens, J. C., & Baloglu, S. (2021). Marketing for hospitality and tourism (Global Edition). Pearson. Kurz, T., & Prosser, A. M. B. (2021). Understanding the social dynamics of climate change through analyses of discourse. Current Opinion in Psychology, 42, 71–75. https://doi.org/10.1016/j.copsyc.2021.03.010 Lee, T. H. (2007). An ecotourism behavioural model of national forest recreation areas in Taiwan. International Forestry Review, 9(3), 771–785. https://doi.org/10.1505/ ifor.9.3.771 Lee, T. H., & Jan, F. H. (2015). The influence of recreation experience and environmental attitude on the environmentally responsible behavior of community-based tourists in Taiwan. Journal of Sustainable Tourism, 23(7), 1063–1094. https://doi.org/10.1080/ 09669582.2015.1032298 Lee, T. H., & Jan, F. H. (2018). Ecotourism behavior of nature-based tourists: An integrative framework. Journal of Travel Research, 57(6), 792–810. https://doi.org/ 10.1177/0047287517717350 Lee, W. H., & Moscardo, G. (2005). Understanding the impact of ecotourism resort experiences on tourists’ environmental attitudes and behavioural intentions. Journal of Sustainable Tourism, 13(6), 546–565. https://doi.org/10.1080/ 09669580508668581 Lee, S., Park, H., Jason), Kim, K. H., & Lee, C.-K. (2021). A moderator of destination social responsibility for tourists’ pro-environmental behaviors in the VIP model. Journal of Destination Marketing & Management, 20, Article 100610. https://doi.org/ 10.1016/j.jdmm.2021.100610 Levi, S. (2021). Why hate carbon taxes? Machine learning evidence on the roles of personal responsibility, trust, revenue recycling, and other factors across 23 European countries. Energy Research & Social Science, 73, Article 101883. https:// doi.org/10.1016/j.erss.2020.101883 Line, N., & Hanks, L. (2015). The effects of environmental and luxury beliefs on intention to patronize green hotels: The moderating effect of destination image. Journal of Sustainable Tourism, 1–22. https://doi.org/10.1080/09669582.2015.1091467 Li, X., Yu, R., & Su, X. (2021). Environmental beliefs and pro-environmental behavioral intention of an environmentally themed exhibition audience: The mediation role of exhibition attachment. Sage Open, 11(2), 1–19. https://doi.org/10.1177/ 21582440211027966 Long, P. H., & Bui, H. T. (2020). Ecotourism and sustainable development in Vietnam’s protected areas. In Tourism and development in southeast asia (pp. 59–72). https://doi. org/10.4324/9780429264191-4 Luo, Y., & Deng, J. (2008). The new environmental paradigm and nature-based tourism motivation. Journal of Travel Research, 46(4), 392–402. https://doi.org/10.1177/ 0047287507308331 Martin, C., & Czellar, S. (2017). Where do biospheric values come from? A connectedness to nature perspective. Journal of Environmental Psychology, 52, 56–68. https://doi. org/10.1016/j.jenvp.2017.04.009 Mihaliˇc, T. (2000). Environmental management of a tourist destination: A factor of tourism competitiveness. Tourism Management, 21(1), 65–78. https://doi.org/ 10.1016/S0261-5177(99)00096-5 Milfont, T. L., & Duckitt, J. (2010). The environmental attitudes inventory: A valid and reliable measure to assess the structure of environmental attitudes. Journal of Environmental Psychology, 30(1), 80–94. https://doi.org/10.1016/j. jenvp.2009.09.001 Mohaidin, Z., Wei, K. T., & Ali Murshid, M. (2017). Factors influencing the tourists’ intention to select sustainable tourism destination: A case study of penang, Malaysia. International Journal of Tourism Cities, 3(4), 442–465. https://doi.org/10.1108/IJTC11-2016-0049 Morren, M., & Grinstein, A. (2016). Explaining environmental behavior across borders: A meta-analysis. Journal of Environmental Psychology, 47, 91–106. https://doi.org/ 10.1016/j.jenvp.2016.05.003 Mowforth, M., & Munt, I. (2015). Tourism and sustainability: Development, globalisation and new tourism in the Third World. In Tourism and sustainability: Development, globalisation and new tourism in the third world (4th ed.). Routledge. https://doi.org/ 10.4324/9781315795348. Nam, S., Oh, Y., Hong, S., Lee, S., & Kim, W. H. (2022). The moderating roles of destination regeneration and place attachment in how destination image affects revisit intention: A case study of incheon metropolitan city. Sustainability, 14(7), 3839. https://doi.org/10.3390/su14073839 Newsome, D., Moore, S. A., & Dowling, R. K. (2012). Natural area tourism: Ecology, impacts and management. In Natural area tourism: Ecology, impacts and management. Channel View Publications. https://doi.org/10.1080/00049182.2016.1247492. Nguyen, T. N., Lobo, A., & Greenland, S. (2016). Pro-environmental purchase behaviour: The role of consumers’ biospheric values. Journal of Retailing and Consumer Services, 33, 98–108. https://doi.org/10.1016/j.jretconser.2016.08.010 Nguyen, T. T. H., Yang, Z., Nguyen, N., Johnson, L. W., & Cao, T. K. (2019). Greenwash and green purchase intention: The mediating role of green skepticism. Sustainability, 11(9), 1–16. https://doi.org/10.3390/su11092653 Norgaard, K. M. (2011). Living in denial: Climate change, emotions, and everyday life. In Living in denial: Climate change, emotions, and everyday life. The MIT Press. https:// doi.org/10.2134/jeq2012.0004br. O’Rourke, D., & Ringer, A. (2016). The impact of sustainability information on consumer decision making. Journal of Industrial Ecology, 20(4), 882–892. https://doi.org/ 10.1111/jiec.12310 Pereira, M. de L., Anjos, F. A. dos, Ana˜ na, ˜ E. da S., & Weismayer, C. (2021). Modelling the overall image of coastal tourism destinations through personal values of tourists: A robust regression approach. Journal of Outdoor Recreation and Tourism, 35, 100–412. https://doi.org/10.1016/j.jort.2021.100412 Pham, H. S. T., & Khanh, C. N. T. (2021). Ecotourism intention: The roles of environmental concern, time perspective and destination image. Tourism Review, 76 (5), 1141–1153. https://doi.org/10.1108/TR-09-2019-0363 Phelps, A. (1986). Holiday destination image - the problem of assessment. An example developed in Menorca. Tourism Management, 7(3), 168–180. https://doi.org/ 10.1016/0261-5177(86)90003-8 Ramkissoon, H., Graham Smith, L. D., & Weiler, B. (2013). Testing the dimensionality of place attachment and its relationships with place satisfaction and pro-environmental behaviours: A structural equation modelling approach. Tourism Management, 36, 552–566. https://doi.org/10.1016/j.tourman.2012.09.003 Said, J., & Maryono, M. (2018). Motivation and perception of tourists as push and pull factors to visit national Park. E3S Web of Conferences, 31, Article 08022. https://doi. org/10.1051/e3sconf/20183108022 Schaffer, V., & Tham, A. (2020). Engaging tourists as citizen scientists in marine tourism. Tourism Review, 75(2), 333–346. https://doi.org/10.1108/TR-10-2018-0151 Schultz, P. W., Shriver, C., Tabanico, J. J., & Khazian, A. M. (2004). Implicit connections with nature. Journal of Environmental Psychology, 24(1), 31–42. https://doi.org/ 10.1016/S0272-4944(03)00022-7 Sharma, P., & Nayak, J. K. (2018). Testing the role of tourists’ emotional experiences in predicting destination image, satisfaction, and behavioral intentions: A case of wellness tourism. Tourism Management Perspectives, 28, 41–52. https://doi.org/ 10.1016/j.tmp.2018.07.004 Shasha, Z. T., Geng, Y., Sun, H. ping, Musakwa, W., & Sun, L. (2020). Past, current, and future perspectives on eco-tourism: A bibliometric review between 2001 and 2018. Environmental Science and Pollution Research, 27(19), 23514–23528. https://doi.org/ 10.1007/s11356-020-08584-9 Stadlthanner, K. A., Andreu, L., Font, X., Ribeiro, M. A., & Curr´ as-P´erez, R. (2022). How environmental gain messages affect cause involvement, attitude and behavioural intentions: The moderating effects of CSR scepticism and biospheric values. Corporate Communications, 27(4), 781–799. https://doi.org/10.1108/CCIJ-11-2021- 0125 Stern, P. C. (2000). New environmental theories: Toward a coherent theory of environmentally significant behavior. Journal of Social Issues, 56(3), 407–424. Stern, P. C., & Dietz, T. (1994). The value basis of environmental concern. Journal of Social Issues, 50(3), 65–84. https://doi.org/10.1111/j.1540-4560.1994.tb02420.x Stern, P. C., Dietz, T., & Guagnano, G. A. (1995). The new ecological paradigm in socialpsychological context. Environment and Behavior, 27(6), 723–743. Stylidis, D., Shani, A., & Belhassen, Y. (2017). Testing an integrated destination image model across residents and tourists. Tourism Management, 58, 184–195. https://doi. org/10.1016/j.tourman.2016.10.014 Stylidis, D., Woosnam, K. M., Ivkov, M., & Kim, S. S. (2020). Destination loyalty explained through place attachment, destination familiarity and destination image. International Journal of Tourism Research, 22(5), 604–616. https://doi.org/10.1002/ jtr.2359 Tanford, S., Kim, M., & Kim, E. J. (2020). Priming social media and framing cause-related marketing to promote sustainable hotel choice. Journal of Sustainable Tourism, 28 (11), 1762–1781. https://doi.org/10.1080/09669582.2020.1760287 Tarinc, A., Ergun, G. S., Aytekin, A., Keles, A., Ozbek, O., Keles, H., & Yayla, O. (2023). Effect of climate change belief and the new environmental paradigm (NEP) on ecotourism attitudes of tourists: Moderator role of green self-identity. International Journal of Environmental Research and Public Health, 20(6), 4967. https://doi.org/ 10.3390/ijerph20064967 Tasci, A. D. A., & Gartner, W. C. (2007). Destination image and its functional relationships. Journal of Travel Research, 45(4), 413–425. https://doi.org/10.1177/ 0047287507299569 Teeroovengadum, V. (2019). Environmental identity and ecotourism behaviours: Examination of the direct and indirect effects. Tourism Review, 74(2), 280–292. https://doi.org/10.1108/TR-11-2017-0190 Thi Khanh, C. N., & Phong, L. T. (2020). Impact of environmental belief and nature-based destination image on ecotourism attitude. Journal of Hospitality and Tourism Insights, 3(4), 489–505. https://doi.org/10.1108/JHTI-03-2020-0027 T.-B. Luong

Journal of Hospitality and Tourism Management 57 (2023) 315–326 326 Tien, N. H., Viet, P. Q., Duc, N. M., & Tam, V. T. (2021). Sustainability of tourism development in Vietnam’s coastal provinces. World Review of Entrepreneurship Management and Sustainable Development, 17(5), 579–598. https://doi.org/10.1504/ WREMSD.2021.117443 Touringvietnam.com. (2023). Vietnam travel Maps. Absolute asia travel. touringvietnam. com/touringvietnam-images/news/img1/Q2V9L2SVL_Vietnam_Map.jpg. Van der Werff, E., Steg, L., & Keizer, K. (2013). The value of environmental self-identity: The relationship between biospheric values, environmental self-identity and environmental preferences, intentions and behaviour. Journal of Environmental Psychology, 34, 55–63. https://doi.org/10.1016/j.jenvp.2012.12.006 Van der Werff, E., Steg, L., & Keizer, K. (2014). I Am what I Am, by looking past the present: The influence of biospheric values and past behavior on environmental selfidentity. Environment and Behavior, 46(5), 626–657. https://doi.org/10.1177/ 0013916512475209 Verplanken, B., & Roy, D. (2016). Empowering interventions to promote sustainable lifestyles: Testing the habit discontinuity hypothesis in a field experiment. Journal of Environmental Psychology, 45, 127–134. https://doi.org/10.1016/j. jenvp.2015.11.008 Wang, X., Van der Werff, E., Bouman, T., Harder, M. K., & Steg, L. (2021). I Am vs. We are: How biospheric values and environmental identity of individuals and groups can influence pro-environmental behaviour. Frontiers in Psychology, 12, 1–11. https:// doi.org/10.3389/fpsyg.2021.618956 van der Werff, E., & Steg, L. (2016). The psychology of participation and interest in smart energy systems: Comparing the value-belief-norm theory and the value-identitypersonal norm model. Energy Research & Social Science, 22, 107–114. https://doi. org/10.1016/j.erss.2016.08.022 Wesley Schultz, P. (2001). The structure of environmental concern: Concern for self, other people, and the biosphere. Journal of Environmental Psychology, 21(4), 327–339. https://doi.org/10.1006/jevp.2001.0227 Zabukovˇsek, S. S., Bobek, S., Zabukovˇsek, U., Kalini´c, Z., & Tominc, P. (2022). Enhancing PLS-SEM-Enabled research with ANN and IPMA: Research study of enterprise resource planning (ERP) systems’ acceptance based on the technology acceptance model (TAM). Mathematics, 10(9), 1379. https://doi.org/10.3390/math10091379 Zhang, X., Jeong, E. H., Olson, E. D., & Evans, G. (2020). Investigating the effect of message framing on event attendees’ engagement with advertisement promoting food waste reduction practices. International Journal of Hospitality Management, 89, Article 102589. https://doi.org/10.1016/j.ijhm.2020.102589 Zhang, H., & Lei, S. L. (2012). A structural model of residents’ intention to participate in ecotourism: The case of a wetland community. Tourism Management, 33(4), 916–925. https://doi.org/10.1016/j.tourman.2011.09.012 Zhou, B., Xiong, Q., Li, P., Liu, S., Wang, L., & Ryan, C. (2023). Celebrity involvement and film tourist loyalty: Destination image and place attachment as mediators. Journal of Hospitality and Tourism Management, 54, 32–41. https://doi.org/10.1016/ j.jhtm.2022.11.004 T.-B. Luong

Journal of Hospitality and Tourism Management 57 (2023) 303–314 Available online 6 November 2023 1447-6770/© 2023 The Authors. Published by Elsevier Ltd. on behalf of CAUTHE - COUNCIL FOR AUSTRALASIAN TOURISM AND HOSPITALITY EDUCATION. All rights reserved. Examining the role of generativity on tourists’ environmentally responsible behavior: An inter-generational comparison Guoquan Wang a , Yanbo Yao a,* , Lianping Ren b , Si Zhang c , Mengyao Zhu d a College of Tourism and Service Management, Nankai University, Jinnan District, Tianjin, 300350, China b Macao Institute for Tourism Studies, Colina de Mong-Ha, Macao, China c School of Tourism Planning and Design, Tourism College of Zhejiang, Xiaoshan District, Hangzhou, 311231, China d School of Tourism Sciences, Beijing International Studies University, Chaoyang District, Beijing, 100024, China ARTICLE INFO Keywords: Environmentally responsible behavior Generativity Environmental concern Personal norm Value-attitude-behavior model Generation Z ABSTRACT Sustainability means developing without compromising the benefit of future generations, which concurs with generative concern, a future value orientation characterized by concern for the future generation. Drawing on the value-attitude-behavior (VAB) hierarchy model, this study established a theoretical framework and empirically examined structural relationships among tourists’ generativity, environmental concern, personal norm, and environmentally responsible behavior (ERB) via PLS-SEM. Potential generational differences were analyzed using an independent sample t-test and multigroup analysis. A total of 702 questionnaires from on-site tourists were collected in Xixi Wetland National Park, Hangzhou, China. Results showed that generative concern positively influences ERB, mediated by tourists’ environmental concern and personal norm. Additionally, intergenerational comparison indicated that Generation Z (Gen Z) has a lower level of generative concern but exhibited greater predictive power for ERB. The effect of environmental concern on personal norm is more robust among Gen Z. Further, academic implications and practical strategies were discussed. 1. Introduction While the booming development of the contemporary tourism industry contributes greatly to the economy, it simultaneously brings challenges to the destination environment (Liu et al., 2021). Wetlands, known as the “Kidneys of Earth”, are one of the world’s three major ecosystems (Zhou et al., 2023). In recent years, wetlands are receiving an increasing number of tourists, which has posed negative impacts to wetland’s ecological environment because of some tourists’ improper behaviors (Xu & Hu, 2021), such as trampling on the lawn, littering, and destroying floras. Literature suggests that tourists’ environmentally responsible behavior (ERB) is an essential aspect in maintaining tourism sites sustainably (Chiu et al., 2013). Thus, understanding tourist ERB and its triggering mechanism in the wetland context is of great practical significance. Personal values are deemed one of the core explanatory variables in predicting tourist ERB (Lin et al., 2022). Although studies have confirmed the role of some personal values such as altruistic and egoistic value (Prakash et al., 2019), biospheric value (Lee & Jan 2015), self-transcendence and conservation (Ahmad et al., 2020; Raza & Farrukh, 2023), and materialism (Kilbourne & Pickett, 2008), this stream of research is still at its infancy (Raza & Farrukh, 2023), many other values may also impact tourists’ ERB, but remain unexplored. Scholars appealed that more values should be explored to gain deeper insights (Ahmad et al., 2020). Value orientation theory argues that a person’s values can be categorized as past, present and future orientations (Hills, 2002). Carmi and Arnon (2014, p. 1) considered that “the concept of sustainability includes a personal and societal imperative to assume responsibility for the future outcomes of present actions, to look forward, or in other words, to have a future orientation.” This suggests that individuals with future value orientation are more likely to behave pro-environmentally in their daily routines because they favor long-term environmental well-being over short-term benefits (Carmi & Arnon, 2014). Researchers have revealed the predicting role of future value orientation on pro-environmental attitudes and behaviors (e.g., Arnocky et al., 2013). However, few extant studies have touched on the effect of tourists’ future value orientation on their pro-environmental attitudes and behaviors in tourism destinations, * Corresponding author. E-mail addresses: [email protected] (G. Wang), [email protected] (Y. Yao), [email protected] (L. Ren), [email protected] (S. Zhang), [email protected] (M. Zhu). Contents lists available at ScienceDirect Journal of Hospitality and Tourism Management journal homepage: www.elsevier.com/locate/jhtm https://doi.org/10.1016/j.jhtm.2023.10.008 Received 10 May 2023; Received in revised form 30 August 2023; Accepted 8 October 2023

Journal of Hospitality and Tourism Management 57 (2023) 303–314 304 which warrants further exploration. Generativity, which represents “a concern for the future generation,” is a value orientation that looks beyond the present (Lacroix & Jolibert, 2015). People with generative concern want to live in a way where their actions have a positive impact that lasts beyond their lifespan (Kotre, 1984). Studies have confirmed a positive link between generativity and consumers’ sustainable behavior (e.g., Urien & Kilbourne, 2011; Shiel et al., 2020). In the hospitality domain, studies have identified the predictive role of generativity in triggering consumers’ ERB in aspects such as water and energy conservation (Wells et al., 2016) and food waste avoidance (Sharma et al., 2023). However, it is currently unknown whether tourists’ generativity influences their ERB. This study aims to verify this speculation through empirical investigation. Prior studies indicate that different generations may hold different environmental values and attitudes that affect their ERBs when travelling (e.g., Pan et al., 2022; Qiu, Wang, Morrison et al., 2022; Sharma et al., 2023). Studies have identified that Gen Z is more conscious of environmental issues and sustainability challenges than other generations (Chen et al., 2019; Monaco, 2018). However, most studies on tourist ERB tend to treat tourists as a homogeneous population and fail to compare the differences among different generations (Salinero et al., 2022). Therefore, more inter-generational comparison between Gen Z and other cohorts is necessary to fill this gap. To fill the research gaps mentioned above, this study put forward the following research questions: (1) Would tourists’ generative concern significantly predict tourists’ on-site ERBs? (2) If so, in what way do tourists’ generative concerns influence their ERBs? (3) Are there any differences between Gen Z and other cohorts? To answer these questions, situated on the value-attitude-behavior (VAB) theory, this study established a theoretical framework to investigate the structural relationships among generativity, environmental concern, personal norm, and ERB by adopting PLS-SEM, and the potential differences between Gen Z and other generations were explored via an independent-sample ttest and multi-group analysis. This study contributes to the extant knowledge in a few ways. First, the study enriches VAB theory by including generativity in the theoretical model and attesting it in the wetland national park context. Second, this study reveals the role of generativity in influencing tourists’ pro-environmental attitudes and ERBs. Third, generativity has been conventionally applied to adults. It is applied to the younger generation in the on-site ERB context for the first time. The results may generate novel insights into the values of the Gen Z, and how they impact behaviors. 2. Literature review and hypotheses development 2.1. Theoretical background This study is guided by the VAB theory. This theory was initially proposed by Homer and Kahle (1988), who maintained that values influence specific behavior through the mediation of individual attitudes towards this behavior (Liu et al., 2021). Values refer to an individual’s persistent conviction that a particular behavior or mode of conduct is morally preferable (Rokeach, 1973). They guide a person’s attitude towards objects and influence their actions (Cheung & To, 2019). In the tourism and hospitality field, the VAB model is proved to have substantive explanatory power to predict consumer sustainable behavior (e. g., Cheung & To, 2019; Han et al., 2019; Kim et al., 2020; Kim & Hall, 2022; Liu et al., 2021). Recently, some scholars (e.g., Kim et al., 2021; Liu et al., 2021) extended this model to promote its predictability by including new variables (such as environmental concern and personal norm) or combining this theory with other theories, such as norm-activation theory and personality theory. Previous studies have demonstrated that individuals with altruistic values are more likely to form pro-environmental attitudes and engage in ERB than those with egoistic values (Ahmad et al., 2020; Kilbourne & Pickett, 2008; Landon et al., 2018; Liu et al., 2021). Generativity, an altruistic value orientation (Yan et al., 2022) which denotes concern and care for future generations, may also positively trigger tourists’ environmental attitudes and engagement in ERB. However, this has only been hypothesized and lacks empirical support. Hence, underpinned by the VAB model, this study constructed a theoretical model to examine the predictive role of generativity (value) on tourist environmental concern and personal norm (attitude), as well as ERB (behavior). 2.2. Tourists’ environmentally responsible behavior ERB in the tourism context refers to any actions taken by individuals or groups to prevent or at least minimize the adverse impacts to the destination environment, or to benefit the environment (Cheng & Wu, 2015; J. Wu et al., 2022). It is often used with other similar terminologies in a mixed way, such as pro-environmental behavior, environmentally sustainable tourist behaviour and environmentally friendly behavior (Juvan & Dolnicar, 2016; Qin & Hsu, 2022). The subject of ERB can be any groups, such as tourists (Qin & Hsu, 2022), residents (Wang et al., 2021), or business entrepreneurs (M. Wu et al., 2022). This stream of research mainly concentrated on nature-based destinations, such as national park (Esfandiar et al., 2021), wetland park (Qiu et al., 2022) and forest park (Zhang et al., 2023), because understanding tourists’ ERBs is of critical and practical value for the sustainable development of these areas (Esfandiar et al., 2019). As for the measurement of tourist ERB, self-reporting assessment is the most frequently used tool (Lange & Dewitte, 2019; Lee & Jan 2015). However, scholars also pointed out this tool has limitations and may not be the most accurate way to measure ERB (e.g., Lange & Dewitte, 2019). Most research tend to measure tourist ERB as a single-dimension construct (e.g., Esfandiar et al., 2023; Su & Swanson, 2017), while some scholars considered this construct encompassing multiple dimensions, such as low-effort and high-effort ERB (Ramkissoon et al., 2013), general and site-specific ERB (Lee et al., 2013), ethical and philanthropic ERB (Chen & Huang, 2022). Besides, existing studies also explored tourist specific ERB, such as binning behavior (Esfandiar et al., 2023), food waste avoidance behavior (Sharma et al., 2023), and pro-environmental dining style (Kim et al., 2020). Researchers elucidated how tourists’ ERB is triggered from multiple perspectives, including values (e.g., Kim et al., 2021), cognitions (e.g., Qiu, Wang, Wu et al., 2022), emotions (e.g., Chen & Huang, 2022), and experiences (e.g., Zhang et al., 2023). Meanwhile, various theories such as theory of planned behavior (TPB), norm-activation theory (NAT), value-belief-norm theory (VBN) were applied, and were proved to have a sound predictive power toward tourist ERBs (e.g., Han, 2021; Lin et al., 2022). In the recent years, increasing scholars explored ERBs from the view of tourists’ value orientation under different theoretical lenses (e. g., Ahmad et al., 2020; Gupta et al., 2022; Lee & Jan 2023; Raza & Farrukh, 2023). This study utilized VAB theory to investigate the role of tourists’ generative concern on their on-site ERBs. 2.3. Generativity “Generativity” can be defined as “concern for and commitment to the well-being of future generations” (McAdams & Logan, 2004, p. 16). It represents the willingness to do something meaningful for future generations and is considered a crucial element of healthy adult development and a key dimension for a sustainable society (Wells et al., 2016; Timilsina et al., 2019). McAdams and de St Aubin (1992) identified that generativity contained several aspects, such as knowledge, contribution, and responsibility, which are recognized by the mainstream academia (Urien & Kilbourne, 2011). Recently, this concept was introduced to the tourism and hospitality field to explain consumer psychology and behavior (See Table A1 in the Appendix). Extant literature has attested to the positive effect of generativity concerns on consumers’ sustainable behavior such as green buying (e.g., G. Wang et al.

Journal of Hospitality and Tourism Management 57 (2023) 303–314 305 Urien & Kilbourne, 2011; Do Paço et al., 2013; Shiel et al., 2020). For example, Wells et al. (2016) confirmed that hotel employees’ generativity concerns positively affect water- and energy-saving attitudes and behaviors at home and work. In recent years, there has been a growing interest in understanding the role of generativity in influencing sustainable behavior in tourism and hospitality. For example, Sharma et al. (2023) attested that travelers’ generativity directly influences their prosocial attitudes and food waste avoidance behavior. However, no studies have explored the relationship between tourists’ generativity concerns and site-specific ERB. Therefore, the following hypothesis was formulated. H1. Generativity exerts a positive influence on ERB. Scholars have noted that people’s environmental concern is positively tied to their altruistic value (e.g., Fransson & Garling, ¨ 1999). Schultz (2001) considered a person’s value system as the source of their environmental concern and explained that a person would become concerned about environmental issues if their value orientations are threatened by current environmental problems. Studies on generativity also suggested a positive correlation between generativity and consumers’ environmental concern (e.g., Do Paço et al., 2013). For example, Pan et al. (2022) revealed that customers’ generativity exerts a positive influence on their environmental concern toward organic foods. Thus, tourists’ generative concern, an altruistic value epitomized by their concern and care for future generations, raises their concern about the increasingly severe environmental issues. The following hypothesis is proposed. H2. Generativity exerts a positive influence on environmental concern. 2.4. Personal norm Personal norm in ERB refers to an “individual’s sense of moral obligation to conduct a particular action” for environmentally responsible tourism (Liu et al., 2021). It is often used interchangeably with other terms such as “moral norm” and “moral obligation” (Denley et al., 2020; Han, 2014). Personal norm is a core concept in predicting ERB and occupies a central position in norm-activation theory and value-belief-norm theory, both of which maintain that personal norm is activated once a person realizes negative consequences for others or the environment and ascribes responsibility to themselves (Gao et al., 2017; Han, 2021). Scholars argue that a person’s values serve as fundamental principles that affect individual obligations or responsibilities toward ERB (e.g., Kim & Seock, 2019; Stern et al., 1999). Studies have discovered the positive effect of individual’s altruistic value orientation on personal norm (e.g.,Kim et al., 2021; Roos & Hahn, 2019). Engel et al. (2020) confirmed that tourists’ care and concern for the ocean affects their personal norm in marine tourism. The current study infers that tourists with generativity convictions can more easily activate personal norm to conform to their value orientation in tourism consumption. In the ERB field, personal norm is regarded as one of the main determinants of tourists’ ERB (D’Arco et al., 2023). Scholars demonstrated the predicting role of personal norm on tourist ERBs in various nature-based tourism contexts (e.g., J. Wu et al., 2022). It is believed that tourists engage in ERBs because they feel morally responsible for reducing negative environmental impacts (Lin et al., 2022). Given this, two hypotheses are postulated. H3. Generativity exerts a positive influence on personal norm. H4. Personal norm exerts a positive influence on ERB. 2.5. Environmental concern Environmental concern refers to the evaluation towards facts, one’s own behavior, or others’ behavior that has consequences for the natural environment (Fransson & Garling, ¨ 1999). It is also known as pro-environmental attitude or environmental belief (Han et al., 2017; Pham & Khanh, 2021), and represents a strong attitude towards protecting the natural environment (Crosby et al., 1981). Prior research suggested that people with strong environmental concern are more environmentally-conscious, and are prone to behaving in an environmentally-sustainable manner (Foroughi et al., 2022). Studies have demonstrated the predictive role of environmental concern in various green-consumption contexts (e.g., Gomes et al., 2023; Kilbourne & Pickett, 2008; Liu et al., 2021). For example, Prakash et al. (2019) confirmed that consumers’ environmental concern could effectively foster their purchase intention towards eco-friendly products. In addition, scholars have also revealed the effect of environmental concern on the activation of personal norm in the field of tourism and hospitality (e.g., Chen & Tung, 2014; Han et al., 2017). For example, Choe et al. (2020) showed that consumers’ environmental concern affects personal norm in edible insect restaurants. Given the above, two hypotheses are proposed. H5. Environmental concern exerts a positive influence on ERB. H6. Environmental concern exerts a positive influence on personal norm. 2.6. Mediating effects of environmental concern and personal norm Literature indicates that attitudinal mediators transmit the effect of value orientation on individual behavior (e.g., Ahmad et al., 2020; Kim et al., 2021; Sharma et al., 2023). Stern and Dietz (1994) validated the theoretical model “value orientation → belief about consequences → behavioral intention”, suggesting that one’s environmental concern serves as a mediator between value orientation and ERB. Nordlund and Garvill (2002) deemed that personal norm mediates the effects of general and environmental values on pro-environmental behaviors. In recent years, scholars further confirmed the mediating role of proenvironmental attitudes between consumers’ generativity and proenvironmental behaviors. For example, Pan et al. (2022) uncovered that both customers’ environmental concern and attitudes toward organic food mediate the effect of generativity on dining intentions. In the hospitality context, Sharma et al. (2023) verified that pro-social attitudes mediate the effect of generativity on tourists’ food waste avoidance behavior. This study speculates that tourists with higher generative concern would be more conscious of environmental issues and have a stronger sense of moral obligation to behave sustainably, which would further trigger their pro-active engagement in on-site ERBs when travelling in the nature-based destinations. Thus, the following two hypotheses are proposed. H7. Environmental concern mediates the relationship between generativity and ERB. H8. Personal norm mediates the relationship between generativity and ERB. In the context of tourism and hospitality, some scholars have revealed the indirect effect of personal norm in the relationship between environmental attitudes/beliefs and ERBs. For instance, Chen and Tung (2014) identified that consumer’s environmental concern can exert indirect impact on one’s intention to visit green hotels through perceived moral obligation. Han and Hyun (2017) also attested that personal norm significantly mediates the influence of ascribed responsibility on intention to visit an environmentally responsible museum. This study inferred that tourists’ personal norm could also mediate the effect of environmental concern on their on-site ERBs. Furthermore, VBN theory postulates that tourist ERB is activated by the chain relationship of value orientations, environmental beliefs, and sense of obligation. Accordingly, we argue that tourists’ environmental concern and personal norm could also chain-mediate the relationship G. Wang et al.

Journal of Hospitality and Tourism Management 57 (2023) 303–314 306 between generativity and ERB. Given the above, two hypotheses are postulated. H9. Personal norm mediates the relationship between environmental concern and ERB. H10. Environmental concern and personal norm chain-mediate the relationship between generativity and ERB. 2.7. Gen Z and environmentally responsible tourism Gen Z refers to the generation born between 1995 and 2009 (Goh & Lee, 2018). It has emerged as “the largest and most challenging consumer group” for tourism destinations (Liu et al., 2023). Research has shown that Gen Z-ers are more environmentally conscious, more aware of sustainability issues, and are more globally focused and open-minded than their senior counterparts (Casalegno et al., 2022; Monaco, 2018; Salinero et al., 2022). In recent years, Gen Z travelers have attracted the attention of tourism scholars, and numerous studies have been conducted to understand their psychology and behavior (e.g., Ding et al., 2022; Sakdiyakorn et al., 2021). Besides, studies on their tourism-related ERB have expanded increasingly (See Table A2 in the Appendix). Some researchers compared the differences between Gen Z and other generations to understand how they behave differently in proenvironmental consumption (e.g., Casalegno et al., 2022). In tourism, Qiu, Wang, Morrison et al. (2022) revealed that the effect of subjective norms on ERB intention was significantly lower in older generations than in Gen Z tourists. Sharma et al. (2023) found that Gen Z travelers have a higher level of generative concerns, prosocial attitudes, and green consumption values and are more likely to engage in food waste avoidance behavior than older travelers. It can be inferred that Gen Z and other generations differ in terms of tourism consumption. Thus, the following hypothesis is proposed. H11. Tourists’ generativity, pro-environmental attitudes, and behaviors and their influence differ between Gen Z and other generations. 3. Methodology 3.1. Research site Xixi Wetland National Park was selected as the research site (see Fig. 2). It is located in the west of Hangzhou City, Zhejiang Province, China. It is the first and most well-known national wetland park in China and is rated as a National AAAAA Level Scenic Spot. Xixi Wetland National Park is deemed a representative Chinese ecological tourism site because of its abundant ecological resources, elegant natural landscapes, and profound cultural heritage. This 11.5 km2 wetland has more than 85% greening rate, which is praised as the “Kidney of Hangzhou,” and is recognized as a must-visit site for tourists visiting Hangzhou (Li & Wu, 2020). Tourists’ environmental behavior is particularly important there for its unique ecological environment. Hence, Xixi Wetland National Park is representative of this investigation as the research site. 3.2. Questionnaire design and pretest All measures were derived from the existing scales (Table 3). The questionnaire comprised four parts. The first part was about tourists’ generative concern. Eleven items were adapted from the study of McAdams and de St Aubin (1992). The second part addressed tourists’ environmental attitudes. For environmental concern, three items were taken from Lee et al. (2014). For personal norm, four items were extracted from Landon et al. (2018). The third part addressed tourist ERB. Four items were extracted from Su and Swanson (2017), Wu et al. (2021) and Wang et al. (2022), which incorporate both low-effort ERBs (i.e., “I didn’t litter the garbage while visiting Xixi Wetland.” “I complied with the environmental protection rules of Xixi Wetland.” “I convinced my travel companions (e.g., family, relatives, and friends) not to damage the environment in Xixi Wetland.”) and high-effort ERB (i.e., “When I saw others damaging the environment, I persuaded them to stop.”). The last part collected respondents’ demographic information, including gender, age, education level, occupation, and monthly income. All variables in Part 1–3 were operationalized using a 5-point Likert rating scale ranging from “completely disagree” (1) to “completely agree” (5). All measurement items were translated into Chinese by two authors who are proficient in both Chinese and English. Seven tourism researchers were invited to check the face validity of the variables. They reported expressive ambiguity of some measurement items and the layout of the questionnaire could be further optimized. The statement of the corresponding items and layout of the questionnaire was revised accordingly. To ensure quality, a pilot test was conducted using convenience sampling method. Forty-one participants who had visited Xixi Wetland National Park in the last year completed the questionnaire online. They were invited to provide feedback on the Fig. 1. Theoretical model. G. Wang et al.

Journal of Hospitality and Tourism Management 57 (2023) 303–314 307 readability of the questionnaire as well. The results showed that all indicators’ Cronbach’s alpha surpassed 0.70 and standard factor loadings were greater than 0.50, implying acceptable reliability and validity. Besides, participants responded that the items in the questionnaire are clear and easy to understand, and corresponded to the actual situation of Xixi Wetland National Park. Hence, the questionnaire was adopted for the official survey. 3.3. Data collection and sample characteristics Formal data collection was conducted at Xixi Wetland National Park onsite in March 2023. The target population of this research was tourists visiting Xixi Wetland National Park. Convenience sampling method was employed to approach on-site tourists. It is a prevailing non-probability sampling strategy in which investigators recruit participants based on relative ease of access (Stratton, 2021). Compared with probability sampling method such as random sampling techniques, this method is cost-effectiveness (e.g., saving time and money) and deemed appropriate for on-site tourist questionnaire surveys (Choi & Heo, 2016; Speak et al., 2018). The researchers, along with research assistants recruited from a local university, conducted the survey. All the research assistants were trained prior to the field investigation. They were dispersed in the main scenic spots and approached tourists via random interception by asking them whether they were willing to participate in an academic survey. The surveyors encouraged the respondents to complete the questionnaire based on their actual thoughts. All participants were informed that this survey would only be used for academic research and that their personal information would be kept anonymous. A total of 800 paperand-pencil questionnaires were sent and 767 were returned, resulting in a response rate of 95.86%. After excluding those with incomplete or identical answers, 702 questionnaires were retained for analysis. Among the 702 respondents (Table 4), men (52.6%) slightly outnumbered women (47.4%). People aged 18–25 and 26–35 occupied the highest proportions, at 37.6% and 24.1%, respectively. Most participants were undergraduates (35.2%) or junior college students (26.5%). Regarding occupation, students accounted for the highest proportion (29.6%). Regarding monthly income, most people earned RMB 3000 or below (32.5%) and RMB 3001–8000 (25.1%). 3.4. Data analysis This study used SPSS and PLS-SEM for data analysis. SPSS was used to perform Harman’s single-factor analysis to examine the common method variance (CMV) issue, and descriptive statistics and independent-sample t-test to assess non-response bias, and the differences between Gen Z and other generations. PLS-SEM was adopted to assess the measurement model, structural model, mediation analysis, and multi-group analysis between Gen Z and other generational cohorts. 4. Results 4.1. Common method variance and non-response bias The results showed that the total variance explained by one factor was 40.12%, which was below the suggested threshold value of 50.0% (Podsakoff et al., 2003). Furthermore, the highest correlation between the latent constructs was 0.624, far below the benchmark of 0.9 (Bagozzi et al., 1991). Therefore, the CMV issue was not a concern in this study. Besides, this study tested the non-response bias by comparing characteristics of early respondents with late respondents (Cascio, 2012). In this study, we compared the first and last 40 questionnaires received (Kwahk & Lee, 2008). There were no significant differences in the demographic characteristics and major variables, suggesting that non-response bias was not an issue. 4.2. Measurement model This study utilized the Smart PLS-SEM software (version 3.0) to test the reliability and validity of the measurement model with overall sample, Gen Z’s sample, and other generations’ sample. The results are summarized in Table 5. The factor loadings of all the items were greater than 0.7, with the exception of “GEN1,” which was slightly below 0.7. Cronbach’s alpha and rho_A values of the constructs surpassed 0.8, thus Fig. 2. Ecological landscapes in Xixi Wetland National Park. Note. Photos were taken by the authors. G. Wang et al.

Journal of Hospitality and Tourism Management 57 (2023) 303–314 308 meeting the threshold suggested by Hair et al. (2011). The values of CR and AVE were all greater than 0.7 and 0.5 respectively, implying sound internal consistency (Fornell & Larcker, 1981). Fornell and Larcker (1981)’s criterion and the Heterotrait-Monotrait (HTMT) ratio of correlations were used to evaluate discriminant validity among constructs. Table 6 shows that all the constructs’ square roots of AVE were higher than the correlations between constructs, suggesting that all constructs possessed good discriminant validity (Fornell & Larcker, 1981). Furthermore, all HTMT values were lower than 0.85 (Table 7), meeting the requirements proposed by Henseler et al. (2015). Both methods demonstrated satisfactory discriminant validity. The measurement model with the sample of Gen Z and other cohorts was also reported in Tables 5–7 Results show that the model’s reliability and validity is stable across groups, which paves the way for inter-generational comparisons. 4.3. Structural model The Variance Inflation Factor (VIF), variance-explained R2 , and predictive relevance Q2 were examined to comprehensively assess the structural model. VIF was used to diagnose multicollinearity, and the results showed an absence of multicollinearity. R2 determines the predictive power of the structural model. Here, the R2 values for EC, PN, and ERB ranged from 11.9% to 43.5% (Fig. 3). All Q2 values calculated using the blindfolding procedure were greater than zero, indicating that exogenous variables could predict endogenous variables (Chen et al., 2022). A bootstrapping program with 5000 iterations was used to estimate the hypothesized relationships in the structural model. The results of the hypotheses tests are presented in Table 8 and Fig. 3. Specifically, GEN positively affected ERB (β = 0.186, t = 5.810, p < 0.001), EC (β = 0.345, t = 8.359, p < 0.001), and PN (β = 0.167, t = 5.759, p < 0.001), thus supporting H1-H3. Additionally, both PN (β = 0.439, t = 10.824, p < 0.001) and EC (β = 0.174, t = 4.438, p < 0.001) positively influenced ERB, thus supporting H4-H5. Additionally, EC had a positive effect on PN (β = 0.566, t = 16.921, p < 0.001), hence supporting H6. 4.4. Mediation effect Table 9 presents the mediating test results. In the influence path of “GEN → EC → ERB,” the indirect effect of EC was 0.060***, with 95% confidence interval [CI: 0.035, 0.087] excluding 0, suggesting that EC mediated the effect of GEN on ERB, thus supporting H7. In the influence paths of “GEN → PN → ERB” and “EC → PN → ERB”, the indirect effects of PN were 0.074*** and 0.249***, respectively, with 95% confidence interval [CI: 0.049, 0.099] and [CI: 0.202, 0.295] excluding 0, indicating that PN mediated the effect of GEN on ERB and EC on ERB, thus supporting H8 and H9. Furthermore, in the influence path of “GEN → EC → PN → ERB,” the indirect effect is 0.086***, with 95% confidence interval [CI: 0.062, 0.115] excluding 0, proving that EC and PN chain-mediate this relationship. Hence, H10 is supported. 4.5. Inter-generational comparison To categorize Gen Z and other generations, a choose-one question was set up by asking respondents “Do you belong to Gen Z (born between 1995 and 2009)?” The overall sample (N = 702) was divided into Gen Z (N1 = 334) and other generations (N2 = 368). The “other generations” here is a counterpart to Gen Z, which refers to age groups born before 1995. To compare the generational differences between Gen Z and other generations, an independent-sample t-test was conducted using SPSS 25.0. The results (Table 10) showed that for the mean value Table 3 Measurement instruments and sources. Constructs and measurement instruments Sources Generativity (GEN) McAdams and de St Aubin (1992) GEN1. I try to pass along the knowledge I have gained through my experiences. GEN2. I feel that other people need me. GEN3. I feel as though I have made a difference to many people. GEN4. I think that I will be remembered for a long time after I die. GEN5. Others would say that I have made unique contributions to society. GEN6. I have important skills that I try to teach others. GEN7. In general, my actions have a positive effect on other people. GEN8. I have made and created things that have had an impact on other people. GEN9. I have a responsibility to improve the neighborhood in which I live. GEN10. People come to me for advice. GEN11. I feel as though my contributions will exist after I die. Environmental concern (EC) Lee et al. (2014) EC1. Humans are severely abusing the environment. EC2. Humans are prone to serious risks if they upset the laws of nature. EC3. The balance of nature is very delicate and easily upset. Personal Norm (PN) Landon et al. (2018) PN1. As a tourist, I feel morally obliged to do whatever I can to minimize environmental impact. PN2. I would feel guilty if I were responsible for damaging the environment as a tourist. PN3. Minimizing my impact on the environment is the right thing to do. Environmentally responsible behavior (ERB) Su and Swanson (2017), Wu et al. ERB1. I didn’t litter the garbage while visiting (2021) and Wang et al. (2022) Xixi Wetland. ERB2. I complied with the environmental protection rules of Xixi Wetland. ERB3. When I saw others damaging the environment, I persuaded them to stop. ERB4. I convinced my travel companions (e.g., family, relatives, and friends) not to damage the environment in Xixi Wetland. Table 4 Demographic profile of respondents (N = 702). Characteristics Frequency Percentage Gender Male 369 52.6 Female 333 47.4 Age 18–25 264 37.6 26–35 169 24.1 36–45 128 18.2 46–55 89 12.7 56 and above 52 7.4 Education Junior school and below 64 9.1 Senior high school 148 21.1 Junior college 186 26.5 Undergraduate 247 35.2 Postgraduate and above 57 8.1 Occupation Enterprise employee 83 11.8 Civil servant 29 4.1 Student 208 29.6 Self-employed 103 14.7 Service and sale staff 75 10.7 Teacher 43 6.1 Worker/farmer 14 2.0 Retiree 39 5.6 Other 108 15.4 Monthly income ¥3000 or below 228 32.5 ¥3001-8000 176 25.1 ¥8001-12000 154 21.9 ¥12001-15000 66 9.4 ¥15001-20000 35 5.0 ¥20001 or above 43 6.1 G. Wang et al.

Journal of Hospitality and Tourism Management 57 (2023) 303–314 309 of GEN, a significant difference (p = 0.09, Cohen’s d = 0.125) existed between Gen Z (Mean value = 3.57) and other generations (Mean value = 3.66). This suggests that Gen Z tourists had a slightly lower GEN than their senior counterparts. With the remaining variables, although Gen Z scored higher on PN and ERB and other generations scored higher on EC, no significant difference existed between the two groups (p > 0.1). To further examine the potential differences in the influence paths, multi-group analysis (MGA) was conducted using PLS-SEM. The results are summarized in Table 11. Two influence paths “GEN → ERB” (p = 0.042) and “EC → PN” (p = 0.044) were significantly different between the two generations. Specifically, the effects of GEN on ERB and EC on PN were significantly higher for Gen Z tourists than for others, indicating that, compared to other generations, Gen Z-ers’ generativity Table 5 Assessment of the measurement model. Factor Mean Loading Cronbach’s α rho_A CR AVE GEN 0.933 (0.942, 0.923) 0.948 (0.950, 0.952) 0.942 (0.949, 0.932) 0.596 (0.630, 0.557) GEN1 3.929 (3.886, 3.967) 0.671 (0.702, 0.647) GEN2 3.631 (3.599, 3.660) 0.781 (0.795, 0.766) GEN3 3.566 (3.509, 3.617) 0.790 (0.787, 0.795) GEN4 3.464 (3.437, 3.489) 0.746 (0.766, 0.721) GEN5 3.400 (3.332, 3.462) 0.797 (0.838, 0.740) GEN6 3.634 (3.590, 3.674) 0.795 (0.838, 0.745) GEN7 3.691 (3.635, 3.742) 0.803 (0.840, 0.753) GEN8 3.479 (3.434, 3.519) 0.790 (0.807, 0.766) GEN9 3.722 (3.677, 3.764) 0.759 (0.777, 0.740) GEN10 3.748 (3.701, 3.791) 0.778 (0.784, 0.771) GEN11 3.474 (3.419, 3.524) 0.774 (0.787, 0.755) EC 0.815 (0.831, 0.800) 0.818 (0.835, 0.805) 0.891 (0.899, 0.883) 0.731 (0.748, 0.715) EC1 3.950 (3.925, 3.973) 0.847 (0.860, 0.837) EC2 4.170 (4.144, 4.193) 0.887 (0.888, 0.888) EC3 4.044 (4.021, 4.065) 0.830 (0.846, 0.809) PN 0.827 (0.857, 0.796) 0.828 (0.858, 0.804) 0.897 (0.913, 0.880) 0.743 (0.778, 0.710) PN1 4.214 (4.219, 4.209) 0.857 (0.890, 0.819) PN2 4.187 (4.171, 4.201) 0.859 (0.879, 0.839) PN3 4.214 (4.243, 4.188) 0.870 (0.877, 0.869) ERB 0.859 (0.876, 0.842) 0.863 (0.883, 0.846) 0.905 (0.916, 0.895) 0.705 (0.733, 0.680) ERB1 4.399 (4.449, 4.353) 0.864 (0.890, 0.837) ERB2 4.400 (4.422, 4.380) 0.859 (0.882, 0.830) ERB3 3.946 (3.928, 3.962) 0.750 (0.830, 0.758) ERB4 4.258 (4.281, 4.236) 0.879 (0.895, 0.869) Note. The data in each parenthesis are from Gen Z and other generations, respectively. Table 6 Results of the discriminant validity test. Construct GEN EC PN ERB GEN 0.772 (0.794, 0.746) EC 0.345 (0.392, 0.301) 0.855 (0.865, 0.846) PN 0.363 (0.393, 0.346) 0.624 (0.683, 0.567) 0.862 (0.882, 0.843) ERB 0.405 (0.482, 0.341) 0.512 (0.575, 0.456) 0.615 (0.634, 0.598) 0.840 (0.856, 0.825) Note. The boldface diagonal elements are the square roots of the AVE; The data in each parenthesis are from Gen Z and other generations, respectively. Table 7 Results of Heterotrait-Monotrait ratio of correlations. Construct GEN EC PN EC 0.370 (0.417, 0.317) PN 0.377 (0.412, 0.341) 0.757 (0.805, 0.709) ERB 0.423 (0.511, 0.332) 0.611 (0.670, 0.553) 0.727 (0.727, 0.725) Note. The data in each parenthesis are from Gen Z and other generations, respectively. Fig. 3. Path coefficient of the conceptual framework. Table 8 Results of the hypotheses tests. Hypothesis Path coefficient T value P value Test result H1: GEN → ERB 0.186*** 5.810 0.000 Supported H2: GEN → EC 0.345*** 8.359 0.000 Supported H3: GEN → PN 0.167*** 5.759 0.000 Supported H4: PN → ERB 0.439*** 10.824 0.000 Supported H5: EC → ERB 0.174*** 4.438 0.000 Supported H6: EC → PN 0.566*** 16.921 0.000 Supported Note. ***p < 0.001. G. Wang et al.

Journal of Hospitality and Tourism Management 57 (2023) 303–314 310 exerted a stronger influence on ERB, and EC exerted a stronger influence on PN. In summary, H11 is partially supported. 5. Discussion 5.1. Conclusion and discussion Based on a sample of 702 on-site tourists visiting Xixi Wetland National Park, this study examined the structural relationships among generativity, environmental concern, personal norm, and ERB, and compared the potential differences between Gen Z and other generations. All the proposed hypotheses are empirically supported. First, this study demonstrated that tourists’ generative concerns could positively influence their engagement in site-specific ERB, which is in line with previous studies in the context of ERB (e.g., Urien & Kilbourne, 2011; Shiel et al., 2020). Previous studies in hospitality domain examined this relationship in the context of water- and energy-saving behaviors (Wells et al., 2016) and food waste avoidance behavior (Sharma et al., 2023). This study echoes previous research and extends the robustness of this relationship to tourism consumption. Importantly, the findings contribute to the extant knowledge on tourist ERB by identifying and verifying generativity as an important antecedent that drives tourists’ adoption of ERB and confirming that future value orientation could trigger tourists’ participation in ERB. Second, this study revealed that tourists’ generative concern as an altruistic value exerts a positive influence on their pro-environmental attitudes, that is, environmental concern and personal norm. This aligns with previous studies suggesting that altruistic value orientations are effective predictors of pro-environmental attitudes (e.g., Filimonau et al., 2018; Kim et al., 2020; Kim et al., 2021; Liu et al., 2021; Sharma et al., 2023). This study demonstrated the positive effect of tourists’ generativity on the formation of their pro-environmental attitudes. Specifically, if a tourist has a strong concern and care for the future generations, he or she concerns more about the environmental issues, and has a stronger sense of moral obligation to behave pro-environmentally. Results also confirmed that tourists’ environmental concern exert a positive influence on ERB, which corroborates existing research in the context of green consumption (e.g., Ahmed et al., 2021; Gomes et al., 2023). The finding of this study demonstrated that environmental concern could effectively drive the adoption of on-site ERBs in the context of wetland park. In addition, results suggested that personal norm is a robust antecedent of tourist ERB, which concurs with prior studies (Salinero et al., 2022; D’Arco et al., 2023). Although the effect of personal norm on ERB has been extensively examined in the tourism and hospitality field, few of which validated this relationship in the context of wetland park. This study thus benefits ERB field by identifying personal norm a strong predictor of tourist ERB in the wetland park context. Third, the mediation analysis suggested that both environmental concern and personal norm serve as mediators between tourists’ generative concerns and ERB. This corresponds to the findings of Pan et al. (2022), who found that environmental concerns and attitudes toward organic food are mediating variables between generativity and dining intentions. In the tourism context, although studies have applied the VAB theory as the framework and examined the variables in their research models (e.g., Kim et al., 2020; Kim et al., 2021), few have investigated the mediating effect of attitudinal variables. Thus, this conclusion advances this stream of research and deepens the understanding of VAB theory. This study also confirmed that personal norm mediates the effect of environmental concern on tourist on-site ERBs, which concurs with the findings of Han and Hyun (2017) in the context of visiting environmentally responsible museums. Our study is pioneer in revealing this mediating effect in the context of wetland park. In addition, the chain Table 9 Results of the mediating tests. Hypothesis Indirect effect t 95% confidence interval Test result Lower bound Upper bound H7: GEN→EC→ERB 0.060*** 3.749 0.035 0.087 Supported H8: GEN→PN→ERB 0.074*** 4.817 0.049 0.099 Supported H9: EC→PN→ERB 0.249*** 8.851 0.202 0.295 Supported H10: GEN→EC→PN→ERB 0.086*** 5.374 0.062 0.115 Supported Note. ***p < 0.001. Table 10 Results of independent-samples T test between Gen Z and other groups. Construct Sample Size Mean SE MD t p Cohen’s d GEN Gen Z 334 3.57 0.76 − 0.09 − 1.654† 0.099 0.125 Other groups 368 3.66 0.68 Overall 702 3.61 0.72 EC Gen Z 334 4.03 0.69 − 0.05 − 0.914 0.361 0.069 Other groups 368 4.08 0.68 Overall 702 4.05 0.68 PN Gen Z 334 4.21 0.67 0.01 0.230 0.818 0.017 Other groups 368 4.20 0.63 Overall 702 4.20 0.65 ERB Gen Z 334 4.27 0.64 0.04 0.793 0.428 0.060 Other groups 368 4.23 0.60 Overall 702 4.25 0.62 Note. SE denotes standard error; MD denotes mean difference; † p < 0.10. Table 11 Results of multi-group analysis between Gen Z and other groups. Hypothesis Gen Z (N1 = 334) Other generations (N2 = 368) Coefficient difference P value H1: GEN → ERB 0.245*** 0.135** 0.109* 0.042 H2: GEN → EC 0.391*** 0.301*** 0.090 0.125 H3: GEN → PN 0.149*** 0.190*** − 0.041 0.225 H4: PN → ERB 0.393*** 0.468*** − 0.074 0.178 H5: EC → ERB 0.211*** 0.148*** 0.063 0.217 H6: EC → PN 0.625*** 0.513*** 0.112* 0.044 Note. ***p < 0.001, *p < 0.05. G. Wang et al.

Journal of Hospitality and Tourism Management 57 (2023) 303–314 311 mediation effect of environmental concern and personal norm further reveals the transmission mechanism of tourists’ value orientation towards their pro-environmental behavior, which supports the theory of VBN. Specifically, tourists’ generative concerns promote their concern about environmental pollution, which reinforces their moral responsibility towards environmental protection. On this basis, tourists would have a stronger intention to behave pro-environmentally when travelling. The chain mediation analysis of this study thus provides more insights to the field of tourist ERB. Fourth, inter-generational analysis confirmed that Gen Z tourists have a lower level of generative concern than tourists from other generations. This is similar to Shiel et al. (2020)’s conclusion that people aged less than 25 years scored lower on generativity than those aged over 25 years. A likely reason for this is that generativity is crucial to individuals in the later stages of their lifespan and essential for human growth and maturity (Pan et al., 2022). This also supports Urien and Kilbourne (2011)’s assertion that generativity is present at each stage of the life cycle but possibly at different levels of intensity. Interestingly, the results of the multi-group analysis showed that the effects of generativity on tourist ERB were significantly stronger for Gen Z tourists than it was for the other cohorts. This corroborates Sharma et al. (2023), who demonstrated that the positive effect of generativity on tourists’ food waste avoidance behavior is stronger among Gen Z members. This means that although Gen Z’s generativity is not as high as that of other generational cohorts, its predictive power for ERB seems to be greater. This implies that Gen Z’s concern for the future, if any, has more potential to transform to actions and behaviors that are conducive to the environment. In addition, multi-group analysis results also indicated that Gen Z-ers’ environmental concern exerted a more robust influence on personal norm. This means that Gen Z-ers’ personal norm was more strongly activated by their environmental concern, which is likely explained by the fact that Gen Z has greater environmental consciousness, stronger awareness, and responsibility towards environmental protection (e.g., Casalegno et al., 2022; D’Arco et al., 2023), which help to form their sense of moral obligation towards on-site ERBs. This study contributes to the understanding of tourist ERB and its inner transmission mechanisms by recognizing age as a boundary condition and identifying differences between Gen Z and other age groups. 5.2. Theoretical implications The results of this study have several theoretical implications. First, although prior studies have applied the VAB theory to predict tourist ERB, most of them were limited from several perspectives, such as altruistic, egoistic, and biosphere values. This study introduced generativity into the VAB framework to explain tourist ERB. The results confirmed that generativity as a type of future-oriented value is applicable under the VAB framework, which extends the application of the VAB theory. Second, although the literature has seen a growing trend in exploring tourist ERB from various perspectives, less attention has been paid to individual value orientations. Recent studies have confirmed the predictive role of generativity in fostering consumers’ pro-environmental attitudes and behaviors in hospitality field (e.g., Sharma et al., 2023; Wells et al., 2016), but its applicability to the tourism is not tested. This study fills this gap by revealing that generativity, as a value of future orientation, can effectively trigger consumers’ pro-environmental attitudes and behaviors in the context of wetland park, which advances the theoretical understanding of tourist ERB. Third, this study identified that both environmental concern and personal norm serve as mediators in the research model, thus generating an additional perspective for understanding the transmission mechanism between tourists’ generative concern and on-site ERBs in the context of wetland park. The chain mediating path “Gen → EC → PN → ERB” offers empirical evidence to support the relevant theories (e.g., VBN, NAT). Although previous studies have explored the direct effect of environmental concern and personal norm in the field of ERB, few studies have examined their mediating roles. This study thus extends this stream of research by identifying their mediating roles in the relationship of generativity and tourist ERB. Fourth, this study compared the performance of the proposed model between Gen Z and other generations, which contributes to the ERB knowledge pool by adding generational comparisons. Although recent studies in tourism have made pioneering attempts to compare the differences between Gen Z and others in the ERB field (e.g., Qiu, Wang, Morrison et al., 2022; Sharma et al., 2023), this stream of study is still in its infancy. This study made inter-generational comparisons using independent sample t-test and multi-group analyses, which provides a methodological reference for future studies. In addition, intergenerational analysis extends the understanding of the VAB theory by identifying age as a boundary condition. 5.3. Practical implications This study provides practical and managerial references. First, given the predictive role of tourists’ generative concern on their proenvironmental attitudes and ERB, it is important for the government to instill this altruistic concept in the public to cultivate their generativity concern, such as care for the well-being of future generations and collective well-being, and environmental intergenerational equity. In addition, destination management organizations (DMOs) should pay more attention to activate tourists’ future orientation and to arouse and awareness towards environmental protection. For example, DMOs could play promotional videos to display consequences of irresponsible environmental behavior and the cost to the future generations. Besides, DMOs can put up relevant posters and slogans, such as “Please protect the environment and leave the beautiful nature to the future generations” “Please preserve the beautiful and fragile natural environment for our future generations.” Second, results indicated that environmental concern significantly affects tourist ERB. Hence, government departments, DMOs, media, and tourism companies should work together on online and offline promotional activities to encourage citizens to be more aware of the fragility of the ecological environment and the cost of environmental pollution. To let the public understand the wetland ecosystem and the ecological value of wetlands, the media could film public service announcements to display the importance and vulnerability of wetlands to improve their awareness of wetland protection. In the destination level, DMOs could present facts of environmental deterioration to tourists to raise their concerns and arrange awareness-raising activities regularly. Besides, DMOs can install LCD screens at the entrance of scenic spots and popular attractions of wetland national parks, and play photos and videos concerning the survival conditions of the rare species of flora and fauna. Third, personal norm was also found to have a significant effect on tourist ERB. To increase tourists’ sense of moral responsibility, at the macro level, different stakeholders should pull efforts together toward a more civilized tourism behavioral norm and culture at the social level. At the micro level, personal norm can be activated by devising specific messages and tactics in the scenic spots, such as “Scenic environment needs every tourist’s joint care” “Please bring your garbage, please keep your virtue.” Fourthly, this study found that Gen Z tourists’ generative concern played a prominent role in ERB, although it presented at a lower level compared to others. Thus, to cultivate Gen Z ’s generative concerns, some role models of this age group can be invited to shoot public service advertisements or documentaries that impact Gen Z. Destination sites should devise strategies for different generations. For Gen Z, DMOs should arrange activities to promote their generative concern, such as setting exhibition areas to present the benefits of ecotourism sites for the future generation and advocating the importance of inter-generational environmental equity. For older generations, DMOs could add more pro-environmental elements to the interpretation system and actively G. Wang et al.

Journal of Hospitality and Tourism Management 57 (2023) 303–314 312 publicize their role models for environmental protection. 5.4. Limitations and future research directions This study had several limitations that invite further investigation. First, it utilized only quantitative research methods and adopted crosssectional questionnaire data. Future research could employ qualitative research methods, such as in-depth interviews and thematic analysis, to deepen the understanding of the what, how, and why aspects of this phenomenon. Second, this study used a Chinese sample to examine generativity and site-specific ERBs in the context of wetland park. Future studies will expand the sample to other geographic locations and expand the site-specific ERBs to more types (such as general ERBs) and more contexts (such as water-based destinations) to improve the robustness of the conclusions. Third, the age group of Gen Z participants included in this study predominantly consists of individuals in their mid to late Gen Z age range (only age 18–28 currently included in this study). Future research should incorporate the rest of Gen Zers to verify the reliability and robustness of the research results, with a research design that complies necessary ethical standard. Fourth, this study only adopted four items to measure high-effort and low-effort ERBs, which may not be sufficient to properly explain tourist ERB. Future studies should use more items to comprehensively measure this construct. Appendix Table A1 Studies on generativity in the tourism and hospitality field Reference Context/Theme Methods Main findings Wells et al. (2016) Hotel employee proenvironmental behaviour Structural equation modelling Generativity positively influences hotel employee’s attitudes, which further influence proenvironmental behaviour both at workplace and home. Luo and Ren (2020) Heritage tourism In-depth interview The generative motivation of Macao residents mainly originated from desire of transmission, the concern for the next generation, community development, and the identity pride pertinent to the city’s heritage resources. Luo and Ye (2020) Museum tourism Structural equation modelling Generativity influences experience expectation and visit intention. Both experience expectation and motivation mediate generativity and visit intention. Yan et al. (2022) Watching Giant Panda on live streaming platform Structural equation modelling Platform subscribers’ generative inclinations mediated the relationship of perceptions of cuteness and perceived values of the platform. Pan et al. (2022) Organic food dining Structural equation modelling Customers’ generativity exerted a positive effect on environmental concerns, attitudes toward organic food and dining intentions. Fan and Luo (2022) Museum tourism Semi-structured interviews and structural equation modelling Generativity influenced tourist engagement, experience, and psychological well-being positively; both engagement and experience mediate the relationship between generativity and psychological well-being. Wu et al. (2023) Cultural heritage tourism Multiple linear regression analysis College students’ generativity, attitude, subjective norm, and perceived behavioral control all positively affect participating intention. Pan and Shang (2023) Family tourism Structural equation modelling Confucian culture is linked with parents’ generativity, which further drives their motive for children’s education and forms their psychological well-being. Sharma et al. (2023) Food waste behavior Structural equation modelling Generativity positively influences prosocial attitudes and consumption values, whilst it only influences Generation Z tourists’ food waste avoidance behaviors. Table A2 Studies on pro-environmental behaviors of the Gen Z tourists. References Theoretical basis Context/Theme Source of sample Main findings Huang et al. (2022) Norm activation theory and moral disengagement theory Restaurant food waste behavior United States Gen Z diners’ food waste behaviors are predicted by different psychological mechanisms. Pan, Teng et al. (2022) Theory of planned behavior Green hotel China Gen Zer’s attitude, subjective norms, and perceived behavioral control positively affect their green hotel visit intention. Salinero et al. (2022) Norm activation theory and social norm theory Pro-sustainable tourism behavior Britain Three internal antecedents (awareness of consequences, ascription of responsibility and personal norm) and two external factors (social media and online community) could predict sustainable tourism behaviors. Prayag et al. (2022) New Environmental Paradigm Sustainability practices Multinational Compared to other generations, Gen Z tourists are more likely to engage in sustainable practices related to resource saving and buying local food. Lin, Wong et al. (2022) Self-determination theory and self-efficacy theory Environmentalists’ citizenship China For Gen Zers, the presence of environmental citizenship leads to an avenue of fostering environmental goal attainment and subsequent selfactualization. Qiu et al. (2022 Theory of planned behavior Pro-environmental behavior China The levels of ERB intention are significantly lower among Gen Z tourists; the effect of subjective norms on ERB intention is stronger for Gen Z. D’Arco et al. (2023) Social norm theory and norm activation theory Sustainable transportation and eco-friendly hotel Italy Personal norm is the main predictor of sustainable behavior. Injunctive social norms exert a positive effect on Generation Z’s intention to opt for sustainable transportation modes through personal norm. Ribeiro et al. (2023) Value-belief-norm (VBN) theory Pro-environmental travel behaviour Britain Values and ascribed responsibility affect environmental concern, which, in turn, affects attitudes, willingness to sacrifice, and pro-environmental travel behaviour. Sharma et al. (2023) Motivation-opportunityability theory Food waste avoidance India Generativity exerts a positive influence on prosocial attitudes and food waste avoidance behavior only for Generation Z travelers. G. Wang et al.

Journal of Hospitality and Tourism Management 57 (2023) 303–314 313 References Ahmad, W., Kim, W. G., Anwer, Z., & Zhuang, W. (2020). Schwartz personal values, theory of planned behavior and environmental consciousness: How tourists’ visiting intentions towards eco-friendly destinations are shaped? Journal of Business Research, 110, 228–236. Ahmed, N., Li, C., Khan, A., Qalati, S. A., Naz, S., & Rana, F. (2021). Purchase intention toward organic food among young consumers using theory of planned behavior: Role of environmental concerns and environmental awareness. Journal of Environmental Planning and Management, 64(5), 796–822. Arnocky, S., Milfont, T. L., & Nicol, J. R. (2013). Time perspective and sustainable behavior: Evidence for the distinction between consideration of immediate and future consequences. Environment and Behavior, 46(5), 556–582. Bagozzi, R. P., Yi, Y., & Phillips, L. W. (1991). Assessing construct validity in organizational research. Administrative Science Quarterly, 421–458. Carmi, N., & Arnon, S. (2014). The role of future orientation in environmental behavior: Analyzing the relationship on the individual and cultural levels. Society & Natural Resources, 27(12), 1304–1320. Casalegno, C., Candelo, E., & Santoro, G. (2022). Exploring the antecedents of green and sustainable purchase behaviour: A comparison among different generations. Psychology and Marketing, 39(5), 1007–1021. Cascio, W. F. (2012). Methodological issues in international HR management research. International Journal of Human Resource Management, 23(12), 2532–2545. Chen, M. H., Chen, B. H., & Chi, C. G. Q. (2019). Socially responsible investment by generation Z: A cross-cultural study of Taiwanese and American investors. Journal of Hospitality Marketing & Management, 28(3), 334–350. Cheng, T. M., & Wu, H. C. (2015). How do environmental knowledge, environmental sensitivity, and place attachment affect environmentally responsible behavior? An integrated approach for sustainable island tourism. Journal of Sustainable Tourism, 23 (4), 557–576. Chen, G., & Huang, X. (2022). From good feelings to good behavior: Exploring the impacts of positive emotions on tourist environmentally responsible behavior. Journal of Hospitality and Tourism Management, 50, 1–9. Chen, G., So, K. K. F., Hu, X., & Poomchaisuwan, M. (2022). Travel for affection: A stimulus-organism-response model of honeymoon tourism experiences. Journal of Hospitality & Tourism Research, 46(6), 1187–1219. Chen, M. F., & Tung, P. J. (2014). Developing an extended theory of planned behavior model to predict consumers’ intention to visit green hotels. International Journal of Hospitality Management, 36, 221–230. Cheung, M. F., & To, W. M. (2019). An extended model of value-attitude-behavior to explain Chinese consumers’ green purchase behavior. Journal of Retailing and Consumer Services, 50, 145–153. Chiu, Y.-T. H., Lee, W.-I., & Chen, T.-H. (2013). Environmentally responsible behavior in ecotourism: Exploring the role of destination image and value perception. Asia Pacific Journal of Tourism Research, 19(8), 876–889. Choe, J. Y. J., Kim, J. J., & Hwang, J. (2020). The environmentally friendly role of edible insect restaurants in the tourism industry: Applying an extended theory of planned behavior. International Journal of Contemporary Hospitality Management, 32(11), 3581–3600. Choi, M., Law, R., & Heo, C. Y. (2016). Shopping destinations and trust–tourist attitudes: Scale development and validation. Tourism Management, 54, 490–501. Crosby, L. A., Gill, J. D., & Taylor, J. R. (1981). Consumer/voter behavior in the passage of the Michigan container law. Journal of Marketing, 45(2), 19–32. D’Arco, M., Marino, V., & Resciniti, R. (2023). Exploring the pro-environmental behavioral intention of generation Z in the tourism context: The role of injunctive social norms and personal norm. Journal of Sustainable Tourism, 1–22. Denley, T. J., Woosnam, K. M., Ribeiro, M. A., Boley, B. B., Hehir, C., & Abrams, J. (2020). Individuals’ intentions to engage in last chance tourism: Applying the valuebelief-norm model. Journal of Sustainable Tourism, 28(11), 1860–1881. Ding, L., Jiang, C., & Qu, H. (2022). Generation Z domestic food tourists’ experienced restaurant innovativeness toward destination cognitive food image and revisit intention. International Journal of Contemporary Hospitality Management, 34(11), 4157–4177. Do Paço, A., Alves, H., Shiel, C., & Filho, W. L. (2013). Development of a green consumer behaviour model. International Journal of Consumer Studies, 37(4), 414–421. Engel, M., Vaske, J. J., & Bath, A. J. (2020). Value orientations and beliefs contribute to the formation of a marine conservation personal norm. Journal for Nature Conservation, 55, Article 125806. Esfandiar, K., Dowling, R., Pearce, J., & Goh, E. (2021). What a load of rubbish! The efficacy of theory of planned behaviour and norm activation model in predicting visitors’ binning behaviour in national parks. Journal of Hospitality and Tourism Management, 46, 304–315. Esfandiar, K., Pearce, J., & Dowling, R. (2019). Personal norms and pro-environmental binning behaviour of visitors in national parks: The development of a conceptual framework. Tourism Recreation Research, 44(2), 163–177. Esfandiar, K., Pearce, J., Dowling, R., & Goh, E. (2023). The extended theory of planned behaviour model and national parks visitors’ pro-environmental binning behaviour: A cross-cultural perspective. Journal of Outdoor Recreation and Tourism, 42, Article 100602. Fan, Y., & Luo, J. M. (2022). Impact of generativity on museum visitors’ engagement, experience, and psychological well-being. Tourism Management Perspectives, 42, Article 100958. Filimonau, V., Matute, J., Mika, M., & Faracik, R. (2018). National culture as a driver of pro-environmental attitudes and behavioural intentions in tourism. Journal of Sustainable Tourism, 26(10), 1804–1825. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. Foroughi, B., Arjuna, N., Iranmanesh, M., Kumar, K. M., Tseng, M. L., & Leung, N. (2022). Determinants of hotel guests’ pro-environmental behaviour: Past behaviour as moderator. International Journal of Hospitality Management, 102, Article 103167. Fransson, N., & Garling, ¨ T. (1999). Environmental concern: Conceptual definitions, measurement methods, and research findings. Journal of Environmental Psychology, 19(4), 369–382. Gao, J., Huang, Z., & Zhang, C. (2017). Tourists’ perceptions of responsibility: An application of norm-activation theory. Journal of Sustainable Tourism, 25(2), 276–291. Goh, E., & Lee, C. (2018). A workforce to be reckoned with: The emerging pivotal Generation Z hospitality workforce. International Journal of Hospitality Management, 73, 20–28. Gomes, S., Lopes, J. M., & Nogueira, S. (2023). Willingness to pay more for green products: A critical challenge for gen Z. Journal of Cleaner Production, Article 136092. Gupta, A., Arora, N., Sharma, R., & Mishra, A. (2022). Determinants of tourists’ sitespecific environmentally responsible behavior: An eco-sensitive zone perspective. Journal of Travel Research, 61(6), 1267–1286. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. Han, H. (2014). The norm activation model and theory-broadening: Individuals’ decision-making on environmentally-responsible convention attendance. Journal of Environmental Psychology, 40, 462–471. Han, H. (2021). Consumer behavior and environmental sustainability in tourism and hospitality: A review of theories, concepts, and latest research. Journal of Sustainable Tourism, 29(7), 1021–1042. Han, H., Hwang, J., Lee, M. J., & Kim, J. (2019). Word-of-mouth, buying, and sacrifice intentions for eco-cruises: Exploring the function of norm activation and valueattitude-behavior. Tourism Management, 70, 430–443. Han, H., & Hyun, S. S. (2017). Drivers of customer decision to visit an environmentally responsible museum: Merging the theory of planned behavior and norm activation theory. Journal of Travel & Tourism Marketing, 34(9), 1155–1168. Han, H., Kim, W., & Kiatkawsin, K. (2017). Emerging youth tourism: Fostering young travelers’ conservation intentions. Journal of Travel & Tourism Marketing, 34(7), 905–918. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. Hills, M. (2002). Kluckhohn and Strodtbeck’s Values Orientation Theory.” In Online Readings in Psychology and Culture (Unit 6, Chapter 3). Bellingham, Washington: Western Washington University, Center for Cross-Cultural Research. Homer, P. M., & Kahle, L. R. (1988). A structural equation test of the value-attitudebehavior hierarchy. Journal of Personality and Social Psychology, 54(4), 638–646. Huang, Y., Ma, E., & Yen, T. H. (2022). Generation Z diners’ moral judgements of restaurant food waste in the United States: A qualitative inquiry. Journal of Sustainable Tourism, 1–20. Juvan, E., & Dolnicar, S. (2016). Measuring environmentally sustainable tourist behaviour. Annals of Tourism Research, 59, 30–44. Kilbourne, W., & Pickett, G. (2008). How materialism affects environmental beliefs, concern, and environmentally responsible behavior. Journal of Business Research, 61 (9), 885–893. Kim, M. J., & Hall, C. M. (2022). Is walking or riding your bike when a tourist different? Applying VAB theory to better understand active transport behavior. Journal of Environmental Management, 311, Article 114868. Kim, M. J., Hall, C. M., & Bonn, M. (2021). Can the value-attitude-behavior model and personality predict international tourists’ biosecurity practice during the pandemic? Journal of Hospitality and Tourism Management, 48, 99–109. Kim, M. J., Hall, C. M., & Kim, D. K. (2020). Predicting environmentally friendly eating out behavior by value-attitude-behavior theory: Does being vegetarian reduce food waste? Journal of Sustainable Tourism, 28(6), 797–815. Kim, S. H., & Seock, Y. K. (2019). The roles of values and social norm on personal norms and pro-environmentally friendly apparel product purchasing behavior: The mediating role of personal norms. Journal of Retailing and Consumer Services, 51, 83–90. Kotre, J. (1984). Outliving the Self. Baltimore, MD: Johns Hopkins University Press. Kwahk, K. Y., & Lee, J. N. (2008). The role of readiness for change in ERP implementation: Theoretical bases and empirical validation. Information & Management, 45(7), 474–481. Lacroix, C., & Jolibert, A. (2015). Targeting consumers who care about future generations. Psychology & Marketing, 32(8), 783–794. Landon, A. C., Woosnam, K. M., & Boley, B. B. (2018). Modeling the psychological antecedents to tourists’ pro-sustainable behaviors: An application of the value-beliefnorm model. Journal of Sustainable Tourism, 26(6), 957–972. Lange, F., & Dewitte, S. (2019). Measuring pro-environmental behavior: Review and recommendations. Journal of Environmental Psychology, 63, 92–100. Lee, T. H., & Jan, F. H. (2015). The effects of recreation experience, environmental attitude, and biospheric value on the environmentally responsible behavior of nature-based tourists. Environmental Management, 56, 193–208. Lee, T. H., & Jan, F. H. (2023). How do smart tourism experiences affect visitors’ environmentally responsible behavior? Influence analysis of nature-based tourists in taiwan. Journal of Hospitality and Tourism Management, 55, 1–10. G. Wang et al.

Journal of Hospitality and Tourism Management 57 (2023) 303–314 314 Lee, T. H., Jan, F. H., & Yang, C. C. (2013). Conceptualizing and measuring environmentally responsible behaviors from the perspective of community-based tourists. Tourism Management, 36, 454–468. Lee, Y-k., Kim, S., Kim, M-s., & Choi, J-g. (2014). Antecedents and interrelationships of three types of pro-environmental behavior. Journal of Business Research, 67(10), 2097–2105. Lin, Z., Wong, I. A., Wu, S., Lian, Q. L., & Lin, S. K. (2022). Environmentalists’ citizenship behavior: Gen Zers’ eudaimonic environmental goal attainment. Journal of Sustainable Tourism, 1–21. Lin, M. T. B., Zhu, D., Liu, C., & Kim, P. B. (2022). A meta-analysis of antecedents of proenvironmental behavioral intention of tourists and hospitality consumers. Tourism Management, 93, Article 104566. Liu, J., Wang, C., Zhang, T., & Qiao, H. (2023). Delineating the effects of social media marketing activities on Generation Z travel behaviors. Journal of Travel Research, 62 (5), 1140–1158. Liu, J., Zhao, Y., & Jang, S. (2021). Understanding beach tourists’ environmentally responsible behaviors: An extended value-attitude-behavior model. Journal of Travel & Tourism Marketing, 38(7), 696–709. Lee, Y. K., Kim, S., Kim, M. S., & Choi, J. G. (2014). Antecedents and interrelationships of three types of pro-environmental behavior. Journal of Business Research, 67(10), 2097–2105. Li, Q., & Wu, M. (2020). Tourists’ pro-environmental behaviour in travel destinations: Benchmarking the power of social interaction and individual attitude. Journal of Sustainable Tourism, 28(9), 1371–1389. Luo, J. M., & Ren, L. (2020). Qualitative analysis of residents’ generativity motivation and behaviour in heritage tourism. Journal of Hospitality and Tourism Management, 45, 124–130. Luo, J. M., & Ye, B. H. (2020). Role of generativity on tourists’ experience expectation, motivation and visit intention in museums. Journal of Hospitality and Tourism Management, 43, 120–126. McAdams, D. P., & de St Aubin, E. D. (1992). A theory of generativity and its assessment through self-report, behavioral acts, and narrative themes in autobiography. Journal of Personality and Social Psychology, 62(6), 1003. McAdams, D. P., & Logan, R. L. (2004). What is generativity? In E.de St. Aubin, D. P. McAdams, & T.-C. Kim (Eds.), The generative society: Caring for future generations (pp. 15–31). American Psychological Association. Monaco, S. (2018). Tourism and the new generations: Emerging trends and social implications in Italy. Journal of Tourism Futures, 4(1), 7–15. Nordlund, A. M., & Garvill, J. (2002). Value structures behind pro-environmental behavior. Environment and Behavior, 34(6), 740–756. Pan, Y., Luo, J. M., & Xu, J. (2022). How generativity affects organic dining intention: Case study of Shanghai. Frontiers in Psychology, 5692. Pan, Y., & Shang, Z. (2023). Linking culture and family travel behaviour from generativity theory perspective: A case of confucian culture and Chinese family travel behaviour. Journal of Hospitality and Tourism Management, 54, 212–220. Pan, J., Teng, Y. M., Wu, K. S., & Wen, T. C. (2022). Anticipating Z-generation tourists’ green hotel visit intention utilizing an extended theory of planned behavior. Frontiers in Psychology, 13. Pham, H. S. T., & Khanh, C. N. T. (2021). Ecotourism intention: The roles of environmental concern, time perspective and destination image. Tourism Review, 76 (5), 1141–1153. Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879. Prakash, G., Choudhary, S., Kumar, A., Garza-Reyes, J. A., Khan, S. A. R., & Panda, T. K. (2019). Do altruistic and egoistic values influence consumers’ attitudes and purchase intentions towards eco-friendly packaged products? An empirical investigation. Journal of Retailing and Consumer Services, 50, 163–169. Prayag, G., Aquino, R. S., Hall, C. M., Chen, N., & Fieger, P. (2022). Is gen Z really that different? Environmental attitudes, travel behaviours and sustainability practices of international tourists to canterbury, New Zealand. Journal of Sustainable Tourism, 1–22. Qin, Q., & Hsu, C. H. (2022). Urban travelers’ pro-environmental behaviors: Composition and role of pro-environmental contextual force. Tourism Management, 92, Article 104561. Qiu, H., Wang, X., Morrison, A. M., Kelly, C., & Wei, W. (2022). From ownership to responsibility: Extending the theory of planned behavior to predict tourist environmentally responsible behavioral intentions. Journal of Sustainable Tourism, 1–24. Qiu, H., Wang, X., Wei, W., Morrison, A. M., & Wu, M. Y. (2022). Breaking bad: How anticipated emotions and perceived severity shape tourist civility? Journal of Sustainable Tourism, 1–21. Qiu, H., Wang, X., Wu, M. Y., Wei, W., Morrison, A. M., & Kelly, C. (2022). The effect of destination source credibility on tourist environmentally responsible behavior: An application of stimulus-organism-response theory. Journal of Sustainable Tourism, 1–21. Ramkissoon, H., Smith, L. D. G., & Weiler, B. (2013). Testing the dimensionality of place attachment and its relationships with place satisfaction and pro-environmental behaviours: A structural equation modelling approach. Tourism Management, 36, 552–566. Raza, A., & Farrukh, M. (2023). Going green: An application of personal value theory to understand consumers visiting intention toward green hotels in Pakistan. International Journal of Contemporary Hospitality Management. Ribeiro, M. A., Seyfi, S., Elhoushy, S., Woosnam, K. M., & Patwardhan, V. (2023). Determinants of generation Z pro-environmental travel behaviour: The moderating role of green consumption values. Journal of Sustainable Tourism, 1–21. Rokeach, M. (1973). The nature of human values. Free press. Roos, D., & Hahn, R. (2019). Understanding collaborative consumption: An extension of the theory of planned behavior with value-based personal norm. Journal of Business Ethics, 158, 679–697. Sakdiyakorn, M., Golubovskaya, M., & Solnet, D. (2021). Understanding Generation Z through collective consciousness: Impacts for hospitality work and employment. International Journal of Hospitality Management, 94, Article 102822. Salinero, Y., Prayag, G., Gomez-Rico, ´ M., & Molina-Collado, A. (2022). Generation Z and pro-sustainable tourism behaviors: Internal and external drivers. Journal of Sustainable Tourism, 1–20. Schultz, P. W. (2001). The structure of environmental concern: Concern for self, other people, and the biosphere. Journal of Environmental Psychology, 21, 327–339. Sharma, N., Goel, P., Nunkoo, R., Sharma, A., & Rana, N. P. (2023). Food waste avoidance behavior: How different are generation Z travelers? Journal of Sustainable Tourism, 1–16. Shiel, C., do Paço, A., & Alves, H. (2020). Generativity, sustainable development and green consumer behaviour. Journal of Cleaner Production, 245, 118865. Speak, A., Escobedo, F. J., Russo, A., & Zerbe, S. (2018). Comparing convenience and probability sampling for urban ecology applications. Journal of Applied Ecology, 55 (5), 2332–2342. Stern, P. C., & Dietz, T. (1994). The value basis of environmental concern. Journal of Social Issues, 50(3), 65–84. Stern, P. C., Dietz, T., Abel, T., Guagnano, G. A., & Kalof, L. (1999). A value-belief-norm theory of support for social movements: The case of environmentalism. Human Ecology Review, 81–97. Stratton, S. J. (2021). Population research: Convenience sampling strategies. Prehospital and Disaster Medicine, 36(4), 373–374. Su, L., & Swanson, S. R. (2017). The effect of destination social responsibility on tourist environmentally responsible behavior: Compared analysis of first-time and repeat tourists. Tourism Management, 60, 308–321. Timilsina, R. R., Kotani, K., & Kamijo, Y. (2019). Generativity and social value orientation between rural and urban societies in a developing country. Futures, 105, 124–132. Urien, B., & Kilbourne, W. (2011). Generativity and self-enhancement values in ecofriendly behavioral intentions and environmentally responsible consumption behavior. Psychology and Marketing, 28(1), 69–90. Wang, S., Berbekova, A., Uysal, M., & Wang, J. (2022). Emotional solidarity and Cocreation of experience as determinants of environmentally responsible behavior: A stimulus-organism-response theory perspective. Journal of Travel Research, Article 00472875221146786. Wang, J., Wang, S., Wang, H., Zhang, Z., & Ru, X. (2021). Examining when and how perceived sustainability-related climate influences pro-environmental behaviors of tourism destination residents in China. Journal of Hospitality and Tourism Management, 48, 357–367. Wells, V. K., Taheri, B., Gregory-Smith, D., & Manika, D. (2016). The role of generativity and attitudes on employees home and workplace water and energy saving behaviours. Tourism Management, 56, 63–74. Wu, G. M., Chen, S. R., & Xu, Y. H. (2023). Generativity and inheritance: Understanding generation Z’s intention to participate in cultural heritage tourism. Journal of Heritage Tourism, 1–18. Wu, J., Font, X., & Liu, J. (2021). Tourists’ pro-environmental behaviors: Moral obligation or disengagement? Journal of Travel Research, 60(4), 735–748. Wu, J., Wu, H. C., Hsieh, C. M., & Ramkissoon, H. (2022). Face consciousness, personal norms, and environmentally responsible behavior of Chinese tourists: Evidence from a lake tourism site. Journal of Hospitality and Tourism Management, 50, 148–158. Xu, S., & Hu, Y. (2021). How do residents respond to negative environmental impacts from tourism? The role of community participation in empowering residents’ environmentally responsible behavior. International Journal of Tourism Research, 23 (6), 1099–1111. Yan, Q., Shen, H., & Ye, H. (2022). Embracing panda—assessing the leisure pursuits of subscribers to China’s iPanda live streaming platform. Leisure Studies, 41(3), 341–355. Zhang, H., Zhang, X., Yang, Y., & Ma, J. (2023). From nature experience to visitors’ proenvironmental behavior: The role of perceived restorativeness and well-being. Journal of Sustainable Tourism, 1–22. Zhou, Y., Zhao, L., & Li, Z. (2023). Wetland ecological restoration and payment for ecosystem service standard: A case study of ganjiangyuan national wetland park. Wetlands, 43(3), 22. Wu, M. Y., Wu, X., Li, Q. C., Wang, J., & Wang, Y. (2022). Justice and community citizenship behavior for the environment: Small tourism business entrepreneurs’ perspectives. Journal of Sustainable Tourism. Advance online publication https://doi. org/10.1080/09669582.2022.2122061. G. Wang et al.

Journal of Hospitality and Tourism Management 57 (2023) 112–116 Available online 20 September 2023 1447-6770/© 2023 The Authors. Published by Elsevier Ltd. on behalf of CAUTHE - COUNCIL FOR AUSTRALASIAN TOURISM AND HOSPITALITY EDUCATION. All rights reserved. Functions and types of travel-related dark humour created during pandemics☆ Tomaˇz Kolar a , Walanchalee Wattanacharoensil b,* a Faculty of Economics, School of Economics and Business, University of Ljubljana, Kardeljeva ploˇsˇcad 17, 1000, Ljubljana, Republic of Slovenia b Tourism and Hospitality Management Division, Mahidol University International College, 999 Bhuthamonthon Sai 4, Salaya, Nakhon Pathom, 73170, Thailand ARTICLE INFO Keywords: Humour COVID-19 Stress-coping Functions and types of humour UGC ABSTRACT This paper examines role of a dark humour as stress-coping resource during COVID-19 pandemics. For this purpose, a theoretical framework is first proposed, that taxonomically relate pandemic stressors with relevant functions, styles and types of humour. In empirical part, an exploratory study of 180 topical online jokes was conducted, by means of content (thematic) analysis. Obtained results reveal four dominant and naturally occurring themes (termed New travelling realities, Rising travel urges, Infected people like to travel and Hypocritical tourism providers), that expose commonly experienced travel-related stressors. In order to cope with them, versatile functions of humour are discerned, namely cognitive re-appraisal, emotional regulation and social critique. These functions correspond with distinctive components of humour, where positive styles (affiliative one in particular) and particular types (i.e. exaggeration and sarcasm) are dominant. Derived theoretical and practical implications for effective application of humour for stress-management during tourism crises are also discussed. 1. Introduction To limit the detrimental impacts and spreading of the COVID-19 virus, restrictive measures for social distancing were adopted, such as quarantines, and travel restrictions. These measures were the antithesis of all that tourism represents and imposed the ‘toughest stress test for the tourism industry’ (Carbone, 2021). Detrimental effects of psychological nature were affecting all involved stakeholders, including tourism providers, workers (Agarwal, 2021; Bichler et al., 2021; Roth-Cohen & Lahav, 2021) and tourists (Han et al., 2022; Yang & Wong, 2020). Such a situation was experienced as stress, which is defined as the feeling of frustration and mental (emotional and cognitive) tension resulting from inability to cope with adverse events or circumstances, that threat well-being (Schwarzer & Schulz, 2003). Prospective tourists thus, has had seek for various means of coping with COVID-19 lockdown stress, where humour and its functions appear to be an underexplored topic. Beneficial effects of humour on health, resilience and well-being are well documented (see e.g. Martin & Ford, 2018) and humour is an established coping mechanism (Boyle & Joss-Reid, 2004; Crawford & Caltabiano, 2011). Positive effects of humour are due to its general emotional, cognitive, social and behavioural functions – themselves explained by key theories of humour. Three main theories (i.e. relief, incongruity and superiority), namely postulate that humour serves for releasing of physiological (emotional) tension, resolution of (cognitive) incongruity and assertion of (social) power and control (Carell). Humour is however a complex phenomenon that appears in different situations and forms, and consists of different components. These distinctions are important since different components of humour were found to have different effects on coping with stress and well-being (Olah & Ford, 2021; Oliveira et al., 2023; Kupier, 2012) and have diverse practical implications for interventions (see e.g. Miller et al., 2021; Shin & Larson, 2020). While in tourism research on the psychological reactions to COVID-19 has been emphasized (see Cheung et al., 2021; Sigala, 2020), dark humour (i.e humour that arises in response to dangerous situations such as wide-scale disasters and crises), and its stress-coping role during COVID-19 pandemic, remain largely neglected. Accordingly, the purpose of this study is to redress this gap and contribute to knowledge on this topic. For this purpose, based on literature overview, an exploratory empirical study was conducted, aimed at following research goals. Firstly, to find out which travel-related stressors are exposed and ☆ During the preparation of this work the authors minorly used ChatGPT in order to improve the readability. The AI score from the Turnitin software return 0% in AI detection. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication. * Corresponding author. E-mail addresses: [email protected] (T. Kolar), [email protected] (W. Wattanacharoensil). Contents lists available at ScienceDirect Journal of Hospitality and Tourism Management journal homepage: www.elsevier.com/locate/jhtm https://doi.org/10.1016/j.jhtm.2023.09.007 Received 14 June 2023; Received in revised form 21 August 2023; Accepted 10 September 2023

Journal of Hospitality and Tourism Management 57 (2023) 112–116 113 appraised by humour. Secondly, to identify noticeable functions and components (i.e. styles and types) of humour that are predominantly used for stress-coping purposes. Thirdly, to explore how identified stressors correspond with functions and components of employed humour. 2. Literature review and theoretical framework Although peculiar, dark humour is common phenomenon and flourishes when people are facing different disasters, including pandemics (Dynel, 2018; Dynel, 2021; Foss, 2020). During COVID-19, humour has proven to be an effective stress-relieving mechanism (Cancelas-Ouvina, 2021; Cauberghe et al., 2021; Hussein & Aljamili, 2020; M˘ ada & Gomoescu, 2020; Nicholls, 2020; Oduor & Kodak, 2020; Walker & McCabe, 2021). Humorous responses during crises help people to cope with disasters through diverse functions of humour. It can namely serve as a way to lighten the heaviness associated with crises and as a “safety valve” for our emotional and physical well-being (Chinery, 2007). Humour acts as mental hygiene mechanism, promotes solidarity and has a liberating function (Dynel, 2018). When feeling helpless, humour can help to “master the horror”, reducing anxiety and providing a healthy outlet for frustration. Humour during crisis in addition construct re-presentation of uncertain situations and perform collective sense-making function (Yilmaz & Bilen, 2022). In addition, different types of disaster humour such as irony serve to express certain (typically negative) attitudes towards the issue or target (e.g. authorities) (James, 2014). Additional ‘communicative’ (and overlapping) functions of humour, such as expressiveness, self-disclosure, identification, exposition, clarification, and critique, have also been recognised during crises/disasters (Marone, 2016; Meyer, 2000; Ungor & Verkerke, 2015). This suggest that during COVID-19 pandemics the general functions of humour are adjusted and exhibited as nuanced and more specific varieties that exceed simple releasing of emotional frustrations. As a complex and multifaceted phenomenon, humour has yet to be unambiguously and consistently categorised (Carell, 2008). Humour consists of different components (styles and types), where only some of them may be present and operative during disasters. Such potentially relevant styles are, for instance positive (affiliative and self-enhancing) styles of humour, which differ from negative (aggressive and self-defeating) styles (Dynel & Poppi, 2018; Graham et al., 1992; Martin et al., 2003; Samson & Gross, 2014). Additional styles of humour encompass various ‘comic’ styles (Heintz & Ruch, 2019). Other authors emphasise the importance and role of cognitive processing through humour (Kuiper, 2012; Navarro-Carrillo et al., 2020). These styles in turn overlap with different ‘ways’ (styles and strategies) of coping, such as aggressive (confrontive) coping, regulation of feelings, accepting responsibility, seeking social support, escape-avoidance and planful problem solving (Abel, 2002; Skinner et al., 2003). Finally, specific types (also designated as ‘techniques’) of humour, represent mechanisms that operationalise pursued functions and strategies in specific form. In contemporary media such relevant types are, for instance, exaggeration, sarcasm, irony, personification, comparison, satire, parody, and play (Buijzen & Valkenburg, 2004; Taecharungroj & Nueangjamnong, 2015). Discussed functions, styles and types of humour cannot be easily and consistently taxonomised (Carell, 2008; Speck, 1991), leaving a dearth of more inclusive and purposive typologies to be developed and explored. For the purpose of empirical study, such a holistic yet purposive theoretical framework is proposed (see Fig. 1). It postulates that humour firstly operates as perceptive, (appraisal) ‘lens’, focused on representation and evaluation of stressful issues. Subsequently humour is deployed as coping resource that perform warranted functions, by means of specific styles and types (themselves representing relevant ‘analysable and informative’ components of humour). 3. Research approach, methodology and sample In line with the research goals and nature of proposed theoretical framework, the qualitative and exploratory empirical design is employed, with content (thematic) analysis as main analytical method. Thematic analysis is a versatile and effective tool for unpacking rich material and offering insight into patterns of meaning across it (Braun & Clarke, 2012; Walters, 2016). While principally inductive, it is also amenable to theory-led analysis. Following established phased approach suggested by Gleeson (2012, pp. 314–322) and Braun and Clarke (2012), researchers comprehensively inspected all sampled material (jokes), systematically coded it and subsequently identified emerging and dominant themes. To obtain a representative sample of empirical material, a systematic sampling approach was used by exploring popular online humour websites such as boredpanda.com and knowyourmeme.com, using Google Chrome and acknowledging popularity of websites by means of Google page ranking (Laineste & Voolaid, 2016; Shifman & Lemish, 2010). Visual jokes (memes) were found to be the prevailing format, so the sampling and analysis were narrowed down to visual user-generated contents. A direct search on Google Images was also conducted, using Fig. 1. Theoretical framework of the study. Source: Adapted from: Meyer (2000); Marone (2016); Ungor & Verkerke (2015) Taecharungroj and Nueangjamnong (2015), Buijzen (2004) T. Kolar and W. Wattanacharoensil

Journal of Hospitality and Tourism Management 57 (2023) 112–116 114 keywords such as “Covid,” “travel,” “joke,” “memes,” and “hum(u)or.” Identical and repetitive jokes were eliminated, and popularity indicators (likes, shares) were recorded. This approach resulted in a saturated sample of 180 of the most popular topical jokes, as additional searches did not reveal new jokes. All meme photos were assigned a code for identification. Each photo was carefully analysed using four styles of humour and seven types of humour as preliminary code themes. In this manner, four naturally occurring patterns (themes) and related elements (i.e., stressors and corresponding coping functions, styles, and types of humour) were explored, combining a bottom-up and top-down (theory-driven) approach. One of the researchers and her research assistant separately coded each meme photo using an Excel spreadsheet. The coding results were cross-validated to ensure intercoder reliability, which was over 80 percent. Memes that posed difficulties in interpretation (possibly due to cultural differences) were omitted, resulting in a final set of 174 useable memes. The majority of the coding for each group was used to identify the key theories and functions of humour appearing in each theme. A coding sample and descriptive results is shown in summary Table 1. 4. Findings and discussion As a result of content analysis, four main themes are recognised that serve as a structure for presentation and discussion of empirical findings. First common and prominent theme is termed New travelling realities, comprising the highest share of the collected images. These jokes deal with the identification, perceptions, explanations and “sense-making” of how the travel (world) has changed during the pandemic. The majority of these jokes (somewhat surprisingly) use the positive styles (i.e. affiliative and self-enhancing humour) to express the outlook about the new realities of travel and tourism. Numerous creative jokes are created on this topic, such as the ‘new costume when travel’, the ‘pile of washed dishes’ that is reminiscent of Sydney’s opera or ‘washing machine window’ that resemble airplane window. In a similar vein, apartment plan serves as travel map, where our travelling choices now became either trivial (bedroom vs. living room, or virtual (on google maps and social media). Around one-third of the jokes in this theme employ the negative (aggressive or self-defeating) humour styles. They address the ‘disastrous/monstrous/devastating’ nature of Covid-19. The fact that “virus burned down travel plans” as “the world is closed”, and the “waiting the end of the ban is soooo looong” depicts the new travelling reality as grim, unpleasant and scary. Different humour types are found under this theme, most frequently exaggeration, comparison and sarcasm. Some jokes in addition creatively use pun to playfully point out where “you are not going” during pandemics (e.g. “LonDON’T″) or where can you choose to go (“Los Kitchenas, Porto Gradenas, Costa del Balconia”). Second identified theme is Rising feelings and travel urges as it Table 1 The four themes of humour and descriptive elaborations. Key Themes and Stressors Key Theories & Functions Humour Styles Humour Types Illustrattive Photos Theme 1: New Travel Reality Relief (release tension): Identification (deepening mutual feelings), sense making Incongruity: Clarification (stress on expected norm – stay home) Affiliative 47% Self-enhancing 23% Aggressive 9% Self-defeating 21% Total photos (n) = 101 Exaggeration 31% Comparison 19% Sarcasm 14% Silliness 13% Surprise 2% Pun 10% Personification 12% Code: Affiliation/Comparison • Fear of Corona • Lock Down at Home • Quarantine • Travel Ban • Masks and Protection • Undertourism • Influencers & travel Theme 2: Rising Feelings and Travel Urges Relief (release tension): Identification (deepening mutual feelings), Expressiveness Affiliative 8% Self-enhancing 27% Aggressive 12% Self-defeating 53% Total photos (n) = 26 Exaggeration 50% Comparison 15% Sarcasm 15% Silliness 4% Surprise 4% Pun 4% Personification 8% Code: Self-defeating/ Exaggeration • Missing Travel • Need to Travel • Happy when Travel • Despair that Travel Never Comes Key Themes and Stressors Key Theories & Functions Humour Styles Humour Types Photos Theme 3: Infected People Like to Travel Incongruity: Identification, Enforcement (enforce desirable norms – stay home when being sick), Critique Affiliative 64% Self-enhancing 14% Aggressive 22% Self-defeating 0% Total photos (n) = 36 Exaggeration 17% Comparison 19% Sarcasm 36% Silliness 3% Surprise 0% Pun 3% Personification 22% Code: Affiliation/Comparison and/or Sarcasm • Subtheme is similar to the theme’s name Theme 4: Hypocritical Tourism Providers Superiority: Differentiation (distinguish between individuals from tourism providers), Critique Affiliative 27% Self-enhancing 9% Aggressive 46% Self-defeating 18% Total photos (n) = 11 Exaggeration 0% Comparison 0% Sarcasm 73% Silliness 0% Surprise 0% Pun 0% Personification 27% Code: Aggressive/Sarcasm • Subtheme is similar to the theme’s name *All meme photos are sourced from open-meme repositories and should be considered under “Fair Use” given their use for non-profit educational purposes. T. Kolar and W. Wattanacharoensil

Journal of Hospitality and Tourism Management 57 (2023) 112–116 115 encompass a wide array of emotional responses to Covid-19 lockdown and inability to travel. Most jokes clearly serve for a vent-out, frustration relief and empathy seeking, as the register of expressed feelings is evidently negative, employing aggressive and self-defeating humour styles. More than half of these jokes encompass feelings of sadness (due to the cancellation of long-awaited trip(s), irritation and grumpiness as “no one cares”, bust also anger, anxiety and confusion (as “masks are required but not enforced!?“). Related variety on the topic is also vivid expressions of “how bad I want to travel/how bad I miss the travel” and “how ready I am to travel”. These jokes reflect distorted perceptions or create illusion of travelling. In this regard, amusing examples of “‘seeing’ ship in the piece of cake or in the tear on the leather sofa” are good examples. On the other hand, some jokes under this theme are also expressive and amusing, representing the affiliative (positive) humour styles. Illustrative jokes also demonstrate weird yet empathic behaviour (e.g. talking with suitcases, or realizing that suitcase is ‘devastated’ due to the cancellation of travel). Largest shares of jokes under this theme use humour types of exaggeration and sarcasm. The third main theme revolves around upsetting realisation that Infected people like to travel (instead of staying at home). Jokes that fit into this topic expose paradoxical and nonsensical ‘urge’ of people with COVID-19 to travel around the world, despite the contagious and dangerous nature of the virus. While many jokes read as simple and straightforward identification of this fact, the issue addressed is actually the blatant irresponsibility of the infected individuals. Although affiliation is the common humour style in this theme, some jokes also hammer inconsiderate people in an aggressive way, albeit in a seemingly concealed manner. Only few jokes condemn, degrade, ridicule and “name” those people in an explicit manner (e.g. “Idiots everywhere”, “not being too bright”). A range of humorous techniques and types are found here, namely a comparison (e.g. what “normal” vs. “sick people” do), personification (use animals to imitate human) and sarcasm/using irony which overlaps with nonsense (absurdity) and deviation (eccentricity). While many jokes use comparison as a type of humour type to contrast between two groups of sick people (normal individuals versus those with coronavirus), sarcastic remarks are typically implied and expressed in an allusive and visual manner, where parody is used as a main technique. These jokes often use some popular (pop-cultural) references and persons in order to ‘roast’ irresponsible travellers. The fourth theme, Hypocritical tourism providers is related to the previous one, but still distinctive as it deals with the irresponsible behaviours of other tourism stakeholders - in a different manner. Here, vendors such as airlines and cruise companies are criticised due to their inappropriate commercial interest, being seen as irresponsible and immoral, even their business survivals are at stake. Some jokes cynically expose sales promotion (e.g. cheap tickets), while others disagree with the ‘luring seduction’ of these companies to ‘show the world’ to infected people. Typically, a negative humour style is deployed in this theme, dominated by sarcastic type of humour. These jokes are mostly aggressive, where some overtly ‘demonize’ travel-related companies, and some ridicule the authorities (i.e. police), or address the ignorance and stupidity of politicians. The later uses pun as technique and plays with the term “Corona” (being understood as Mexican beer by president Trump). A lot of jokes under this theme use memetic format (i.e. captioned photos), where some parody commercials - implying that they are not funny at all. 5. Conclusions and implications Findings of this study (summarised in Table 1) illuminate the complex role and versatile, yet constructive functions of dark humour in coping with pandemic stress. Content analysis namely reveals that most prominent (frequently addressed) theme and challenging cause of stress is the ‘new, closed world’, where humour mainly serves cognitive, sensemaking function, coupled with positive, affiliative style, what suggests that at ‘making new reality intelligible’, humour also involves bonding and social approval. Second prominent theme confirms expected function of humour at venting-out diverse emotional tensions and highlights its empathy-seeking role. Here negative styles of humour are deployed for coping with ‘impossible travel’ frustrations, self-defeating style in particular. Next two related themes reveal important social function of humour for condemning irresponsible infected travellers and hypocrite vendors. Here positive and negative styles of humour are more balanced, where affiliative style is more frequent than aggressive. In regard to deployed humour types, exaggeration and comparison are dominant types found across first two themes. This reveals that humorous functions are pursued through overstating and contrasting mechanisms, in order to appraise and re-frame pandemics as ‘comic and absurd’, relativise (reduce) its catastrophic nature and distance from (avoid) it. At third and fourth theme sarcasm is dominant type, revealing that true intent of these jokes is social critique and mocking the immoral stakeholders. Obtained findings provide several theoretical contributions. They affirm functional (positive, adaptive) role of dark humour, itself predicated to be negative and maladaptive (see Kuiper, 2012; Samson & Gross, 2014). In this manner study findings support the need for further conceptual distinctions among related but distinctive kinds of humour such as dark, disaster and sick humour (Chovanec, 2019; Dynel & Poppi, 2018). Humorous functions are, in addition, performed by means of various styles and types of humour, what refutes simplistic and exclusivist assumptions, such as for instance that function of social dominance is limited to (equals) disparaging humour (see Speck, 1991). In this manner proposed integrative theoretical framework (on Fig. 1), is supported and represent an important theoretical contribution. Such purposeful taxonomies provide needed conceptual, experimental and managerial basis for understanding of humorous effects (Speck, 1991). This framework and study findings in addition illuminate the versatile role of humour during the process of coping with stressful life events, where humour seem overlooked resource (see Schwarzer & Schulz, 2003). In more specific terms, dominant identified styles of also complement coping strategies and styles in psychological literature (Abel, 2002; Kuiper, 2012; Skinner et al., 2003). These contributions have significant implications for tourism. Conceptually, our study expands the register of relevant kinds of humour examined, which seem to be in tourism so far biased towards ‘bright’ side of humour, used for promotional and employee’s purposes (see Ge, 2019; Pearce & Pabel, 2015). In similar vein, topic of stress-coping has been so far in tourism examined in more general terms (Jordan et al., 2019; Zhu et al., 2020) and humour as stress-coping resource seems completely overlooked topic in the management of tourism crises and disasters (see Ritchie & Jiang, 2019). Here proposed taxonomical framework yield several practical implications. Initially, humorous user-generated contents (UGC) are useful for informative purposes and “analytic” strategy that deploys social media contents as valuable knowledge resource (Munar, 2011). This assures consumer/tourist-based perspective-taking, where humorous UGC provide rich description of how tourist experience crises-related stressors, but also what they expect in terms of responsible and supportive responses from tourism authorities and vendors (Li et al., 2022). Afterwards humour can be used as coping resource, where tourism stakeholders facilitate sense-making, vent-out and bonding (affiliation) functions by assuring warranted support. A number of tactical tools is available and recommended for this purpose, such as collective sensemaking framework (Yilmaz & Bilen, 2022), and various interventional applications that include programmes and exercises for use of humour in a facilitative manner (Gonot-Schoupinsky & Garip, 2018). Such interventions are relevant for different tourism audiences that experiences stress, including tourists and employees (see Bichler et al., 2021). Practical interventions need to be accompanied by effective promotion and responsive social-media communication, where adequate styles and types of humour need to be selectively deployed in order to be effective (Shin & Larson, 2020). To assure and control efficient use of humour for T. Kolar and W. Wattanacharoensil

Journal of Hospitality and Tourism Management 57 (2023) 112–116 116 promotion, more structured and quantitative research is recommended, that encompass descriptive, comparative and experimental evaluation of different types of humour in terms of their relevance and efficiency (Speck, 1991). In this manner dark humour can provide brighter outlook and fruitful implications for building psychological resilience during hard times. Declaration of competing interest The authors declare no conflict of interest in creating this research note and no financial statement to declare. References Abel, M. H. (2002). Humor, stress, and coping strategies. Humor, 15(4), 365–381. Agarwal, P. (2021). Shattered but smiling: Human resource management and the wellbeing of hotel employees during COVID-19. International Journal of Hospitality Management, 93, Article 102765. Bichler, B. F., Petry, T., & Peters, M. (2021). ‘We did everything we could’: How employees’ made sense of COVID-19 in the tourism and hospitality industry. Current Issues in Tourism. https://doi.org/10.1080/13683500.2021.1985974 Boyle, G. J., & Joss-Reid, J. M. (2004). Relationship of humour to health: A psychometric investigation. British Journal of Health Psychology, 9(1), 51–66. Braun, V., & Clarke, V. (2012). Thematic analysis. American Psychological Association. Buijzen, M., & Valkenburg, P. M. (2004). Developing a typology of humor in audiovisual media. Media Psychology, 6(2), 147–167. Cancelas-Ouvina, ˜ L. P. (2021). Humor in times of COVID-19 in Spain: Viewing coronavirus through memes disseminated via WhatsApp. Frontiers in Psychology, 12, Article 611788. Carbone, F. (2021). Tourism destination management post covid-19 pandemic: A new humanism for a human-centred tourism (tourism 5.0). In L. M. Figueira, & L. Oosterbeek (Eds.), Turismo Mundial, Crise Sanitaria ´ e Futuro: vis˜ oes globais partilhadas World Tourism, Health Crisis and Future: Sharing Perspectives (pp. 43–55). Instituto Politecnico de Tomar: Portugal. Carrell, A. (2008). In V. Raskin (Ed.), Historical views of humor. The primer of humor research (pp. 303–332). USA: de Gruyter Mouton. Cauberghe, V., Van Wesenbeeck, I., De Jans, S., Hudders, L., & Ponnet, K. (2021). How adolescents use social media to cope with feelings of loneliness and anxiety during COVID-19 lockdown. Cyberpsychology, Behavior, and Social Networking, 24(4), 250–257. Cheung, C., Takashima, M., Choi, H., Yang, H., & Tung, V. (2021). The impact of COVID19 pandemic on the psychological needs of tourists: Implications for the travel and tourism industry. Journal of Travel & Tourism Marketing, 38(2), 155–166. Chinery, W. (2007). Alleviating stress with humour: A literature review. Journal of Perioperative Practice, 17(4), 172–182. Chovanec, J. (2019). Early titanic jokes: A disaster for the theory of disaster jokes? Humor, 32(2), 201–225. Crawford, S. A., & Caltabiano, N. J. (2011). Promoting emotional well-being through the use of humour. The Journal of Positive Psychology, 6(3), 237–252. Dynel, M. (2021). COVID-19 memes going viral: On the multiple multimodal voices behind face masks. Discourse & Society, 32(2), 175–195. Dynel, M., & Poppi, F. I. (2018). Tragoedia risus: Analysis of dark humour in postterrorist attack discourse. Discourse & Communication, 12(4), 382–400. Foss, N. J. (2020). Behavioral strategy and the COVID-19 disruption. Journal of Management, 46(8), 1322–1329. Ge, J. (2019). Social media-based visual humour use in tourism marketing. The European Journal of Humour Research, 7(3), 6–25. Gleeson, K. (2012). 21 Polytextual thematic analysis for visual data. Visual methods in psychology: Using and interpreting images in qualitative research. Gonot-Schoupinsky, F. N., & Garip, G. (2018). Laughter and humour interventions for well-being in older adults: A systematic review and intervention classification. Complementary Therapies in Medicine, 38, 85–91. Graham, E. E., Papa, M. J., & Brooks, G. P. (1992). Functions of humor in conversation: Conceptualization and measurement. Western Journal of Communication, 56(2), 161–183. Han, S., Yoon, A., Kim, M. J., & Yoon, J. H. (2022). What influences tourist behaviors during and after the COVID-19 pandemic? Focusing on theories of risk, coping, and resilience. Journal of Hospitality and Tourism Management. https://doi.org/10.1016/j. jhtm.2022.02.024 Heintz, S., & Ruch, W. (2019). From four to nine styles: An update on individual differences in humor. Personality and Individual Differences, 141, 7–12. Hussein, A. T., & Aljamili, L. N. (2020). COVID-19 humor in Jordanian social media: A socio-semiotic approach. Heliyon, 6(12), Article e05696. James, A. B. (2014). Humour as resistance. The European Journal of Humour Research, 2 (3), 28–41. Jordan, E. J., Spencer, D. M., & Prayag, G. (2019). Tourism impacts, emotions and stress. Annals of Tourism Research, 75, 213–226. Kuiper, N. A. (2012). Humor and resiliency: Towards a process model of coping and growth. Europe’s Journal of Psychology, 8(3), 475–491. Laineste, L., & Voolaid, P. (2016). Laughing across borders: Intertextuality of internet memes. The European Journal of Humour Research, 4(4), 26–49. Li, S., Chen, G., Liu, M., Xu, J., Cao, J., & Yang, J. (2022). How does tour guide humor influence tourist citizenship behavior? Journal of Hospitality and Tourism Management, 50, 108–118. M˘ ada, S., & Gomoescu, M. (2020). Quarantine humour as a coping mechanism. A centennial “dialogue”. Bulletin of the Transilvania University of Brasov, Series IV: Philology & Cultural Studies, 13(2), 55–78. Marone, V. (2016). Looping out loud. The European Journal of Humour Research, 4(4), 50–66. Martin, R. A., & Ford, T. (2018). The psychology of humor: An integrative approach. Academic press. Martin, R. A., Puhlik-Doris, P., Larsen, G., Gray, J., & Weir, K. (2003). Individual differences in uses of humor and their relation to psychological well-being: Development of the Humor Styles Questionnaire. Journal of Research in Personality, 37(1), 48–75. Meyer, J. C. (2000). Humor as a double-edged sword: Four functions of humor in communication. Communication Theory, 10(3), 310–331. Miller, E., Bergmeier, H. J., Blewitt, C., O’Connor, A., & Skouteris, H. (2021). A systematic review of humour-based strategies for addressing public health priorities. Australian & New Zealand Journal of Public Health, 45(6), 568–577. Munar, A. M. (2011). Tourist-created content: Rethinking destination branding. International Journal of Culture, Tourism and Hospitality Research, 5(3), 291–305. Navarro-Carrillo, G., Torres-Marín, J., Corbacho-Lobato, J. M., & Carretero-Dios, H. (2020). The effect of humour on nursing professionals’ psychological well-being goes beyond the influence of empathy: A cross-sectional study. Scandinavian Journal of Caring Sciences, 34(2), 474–483. Nicholls, C. (2020). Online humour, cartoons, videos, memes, jokes and laughter in the epoch of the coronavirus. Text matters: A journal of literature, theory and culture, 10, 274–318. Oduor, J. A., & Kodak, B. (2020). Online humour as a coping mechanism in the face of corona virus pandemic: The Kenyan context. East African Scholars Journal of Psychology and Behavioural Sciences, 2(4), 1–8. Olah, A. R., & Ford, T. E. (2021). Humor styles predict emotional and behavioral responses to COVID-19. Humor, 34(2), 177–199. Oliveira, R., Arriaga, P., & Barreiros, J. (2023). The role of humor in social, psychological, and physical well-being. Humor. https://doi.org/10.1515/humor2022-0072, 0. Pearce, P. L., & Pabel, A. (2015). Tourism and humour, 68. Channel View Publications. Ritchie, B. W., & Jiang, Y. (2019). A review of research on tourism risk, crisis and disaster management: Launching the annals of tourism research curated collection on tourism risk, crisis and disaster management. Annals of Tourism Research, 79, Article 102812. Roth-Cohen, O., & Lahav, T. (2021). Cruising to nowhere: Covid-19 crisis discourse in cruise tourism Facebook groups. Current Issues in Tourism. https://doi.org/10.1080/ 13683500.2021.1940106 Samson, A. C., & Gross, J. J. (2014). The dark and light sides of humor. Positive emotion: Integrating the light sides and dark sides. In J. Gruber, & J. T. Moskowitz (Eds.), Positive emotion: Integrating the light sides and dark sides (p. 169). Oxford University Press, 2014. Schwarzer, R., & Schulz, U. (2003). Stressful life events. Handbook of psychology, 9, 29–56. Shifman, L., & Lemish, D. (2010). Between feminism and fun (ny) mism: Analysing gender in popular internet humour. Information, Communication & Society, 13(6), 870–891. Shin, H., & Larson, L. R. (2020). The bright and dark sides of humorous response to online customer complaint. European Journal of Marketing, 54(8), 2013–2047. Sigala, M. (2020). Tourism and COVID-19: Impacts and implications for advancing and resetting industry and research. Journal of Business Research, 117, 312–321. Skinner, E. A., Edge, K., Altman, J., & Sherwood, H. (2003). Searching for the structure of coping: A review and critique of category systems for classifying ways of coping. Psychological Bulletin, 129(2), 216. Speck, P. S. (1991). The humorous message taxonomy: A framework for the study of humorous ads. Current Issues and Research in advertising, 13(1–2), 1–44. Taecharungroj, V., & Nueangjamnong, P. (2015). Humour 2.0: Styles and types of humour and virality of memes on Facebook. Journal of Creative Communications, 10 (3), 288–302. Üngor, ¨ U.Ü., & Verkerke, V. A. (2015). Funny as hell: The functions of humour during and after genocide. The European Journal of Humour Research, 3(2/3), 80–101. Walker, G., & McCabe, T. (2021). Psychological defence mechanisms during the COVID19 pandemic: A case series. The European Journal of Psychiatry, 35(1), 41–45. Walters, T. (2016). Using thematic analysis in tourism research. Tourism Analysis, 21(1), 107–116. Yang, F. X., & Wong, I. A. (2020). The social crisis aftermath: Tourist well-being during the COVID-19 outbreak. Journal of Sustainable Tourism, 29(6), 859–878. Yilmaz, G., & Bilen, M. (2022). Sensemaking in a networked world: COVID-19 vaccine hesitancy in Turkey. Communication Studies, 73(4), 347–363. Zhu, M., Gao, J., Zhang, L., & Jin, S. (2020). Exploring tourists’ stress and coping strategies in leisure travel. Tourism Management, 81, Article 104167. T. Kolar and W. Wattanacharoensil

Journal of Hospitality and Tourism Management 57 (2023) 148–157 Available online 7 October 2023 1447-6770/© 2023 The Authors. Published by Elsevier Ltd. on behalf of CAUTHE - COUNCIL FOR AUSTRALASIAN TOURISM AND HOSPITALITY EDUCATION. All rights reserved. Green intellectual capital and green competitive advantage in hotels: The role of environmental product innovation and green transformational leadership Chong Xin * , Yushi Wang School of Business Administration, Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang, China ARTICLE INFO Keywords: Green intellectual capital Green competitive advantage Environmental product innovation Green transformational leadership ABSTRACT The environmental problems brought about by the rapid development of the hospitality industry can no longer be ignored, and the green transformation of the hospitality industry is imminent. This study aims to investigate the role of the mediating effect of environmental product innovation and the moderating effect of green transformational leadership on the relationship between green intellectual capital (GIC) and green competitive advantage. A questionnaire survey of 400 Spanish hotel employees was conducted, and empirical analysis was carried out using SPSS 27.0 and AMOS 28.0. The results show that GIC makes a positive contribution to green competitive advantage in hotels. The mediating role of environmental product innovation and the moderating role of green transformational leadership were also statistically significant. We contribute to the development of the resource-based view theory through hypothesis testing and explores ideas for green transformation in hotel companies. 1. Introduction Economic growth and social advancement have contributed to a booming tourism industry (Wang, Wang, et al., 2021). In 2019, the GDP share of tourism in Spain was 13%, with 84 million travelers visiting Spain, making it the most visited country in the EU (Martinez-Martinez et al., 2021). Although COVID-19 impacted tourism, it is still one of the pillar industries in Spain (Aguiar-Quintana et al., 2021). With the increasing demand for hotels, the economic benefits are accompanied by a range of environmental issues (Nisar et al., 2021). The rapidly expanding hotel industry is bound to result in high consumption of water, electricity, and disposable resources, generating large amounts of waste and greenhouse gases, which will cause tremendous environmental pressure (Martinez-Martinez et al., 2021). Therefore, the EU has proposed an Action Plan: “Towards Zero Pollution for Air, Water and Soil” (EUR-Lex, 2021), advocating a green transformation of the hospitality industry to eliminate pollution and achieve sustainable development. Because of the high environmental impact of hotel behavior with increasing stakeholder concern and pressure, a green transformation of Spanish hotels is urgently needed (Dang & Wang, 2022). This study aims to provide a solution for hotels in green transformation and obtain a green competitive advantage. Established research has confirmed that using environmentally friendly products, saving energy and resources, reducing pollutant emissions and managing green human resources can enhance the hotel’s environmental performance and build a competitive advantage (Haldorai et al., 2022; Obeidat et al., 2020). Intellectual capital is also a key attribute for hotels to guarantee competitive advantage and can be used to anticipate customer demands and create sustainable value (Liu & Jiang, 2020). By introducing the concept of green into intellectual capital (GIC), Chen (2008) integrates the notion of green into intellectual capital. GIC encompasses all intangible assets at the organizational or individual level, such as talent, knowledge, culture, relationships, collaboration, and so forth. It is of critical importance to business development and value creation (Yong et al., 2019). Studies have demonstrated that GIC supports enterprises in environmental management (Munawar et al., 2022), improves their sustainable performance across economic, environmental and social performance (Yusliza et al., 2020), and facilitates the attainment of competitive advantage (Kuo et al., 2022). Based on the resource-based view (RBV) theory, GIC is a precious, scarce, high imitation cost and irreplaceable resource for hotels. The foundation of the GIC literature is, therefore, profoundly rooted in the logic of RBV (Haldorai et al., 2022). While research on GIC has attracted widespread interest among management researchers (Dang & Wang, 2022), its * Corresponding author. E-mail addresses: [email protected] (C. Xin), [email protected] (Y. Wang). Contents lists available at ScienceDirect Journal of Hospitality and Tourism Management journal homepage: www.elsevier.com/locate/jhtm https://doi.org/10.1016/j.jhtm.2023.10.001 Received 22 February 2023; Received in revised form 1 October 2023; Accepted 1 October 2023

Journal of Hospitality and Tourism Management 57 (2023) 148–157 149 contribution to how it directly or indirectly affects the green competitive advantage of hotels (e.g., environmental product innovation and green transformational leadership) has not been adequately investigated in academic literature. For one, the rapid growth of the hotel industry has resulted in intensified competitive pressure, necessitating hotels to maintain a competitive advantage through product innovation (Liu & Jiang, 2020). Previous studies have shown that achieving a high level of product innovation can yield cost savings and generate economic value (Li et al., 2017). Furthermore, it can reduce risks and mitigate the impact of the external environment on enterprises (Qiu et al., 2020). While environmental product innovation focuses more on environmental protection and green development, creating economic value for enterprises along with enhancing environmental benefits (Huang & Chen, 2022). Importantly, GIC offers a competitive edge for achieving high levels of eco-friendly product innovation (Shehzad et al., 2023). Although environmental product innovation has shown its beneficial role in acquiring competitive advantage for firms (Qiu et al., 2020), surprisingly, no studies in the management literature examine the value of environmental product innovation intermediation GIC for green competitive advantage. Therefore, it is becoming increasingly urgent to identify the essential characteristics of environmental product innovation (Wang, Wang, et al., 2021) and explore how hotels can utilize GIC to significantly enhance the level of environmental product innovation and further strengthen the green competitive advantage. For another, hotel leaders, in comparison to consumers, possess superior expertise in hotel management, sensitivities and a deeper understanding of hotel ecosystem development (Amankwaa et al., 2022). Previous studies mainly focused on the influence of hotel intellectual capital on competitive advantage from the consumer perspective (Cui & Wang, 2022; Liu & Jiang, 2020), and few scholars investigated the relationship between GIC and green competitive advantage from a leadership perspective. Therefore, we introduce the concept of green transformational leadership and examine its role in the relationship between GIC and green competitive advantage. Particularly, green transformational leadership provides new learning opportunities and stimuli for employees, can enhance companies’ utilization of GIC and accelerate product innovation (Cui & Wang, 2022). Additionally, it focuses more on environmental concerns and aims to provide enterprises with new environmental protection ideas and visions to obtain a green competitive advantage (Zhang & Ma, 2021). Therefore, this study assesses how the relationship between GIC, environmental product innovation and green competitive advantage can provide additional significance for the hospitality management literature from a leadership perspective. Table 1 specifically selected a comprehensive literature review concerning all the variables of this study. It highlights the contributions of the current research in comparison to relevant previous studies. This study is the first to incorporate a context-specific experiment with Spanish hotel firms into the research framework to examine the direct impact of GIC on green competitive advantage, which extends the existing literature on intellectual capital and competitive advantage. Then, we explore how environmental product innovation mediates the relationship between GIC and green competitive advantage. It helps business managers rationalize targeted measures to shape environmentally oriented product innovation by increasing the level of GIC, thereby achieving a higher level of competitive advantage. What’s more, it extends the application of green transformational leadership in the area of intellectual capital and competitive advantage by introducing green transformational leadership as a moderating variable. The remainder of the paper begins with a theoretical and literature review, which is a critical step in the construction of the research model for this study. The research methodology and sample, results and discussion follow this. Next, the theoretical contributions and managerial implications of the study findings are discussed. Finally, limitations and avenues for future research are discussed. Table 1 Review of relevant literature. Study Variables (selected) Key findings (selected) Green intellectual capital (GIC) Chen (2008) GIC, Competitive advantage. The relationship between GIC and firms’ competitive advantage is positive. Wang and Juo (2021) GIC, Green innovation, Green performance. GIC has a positive impact on green innovation, green performance, and economic performance, respectively. Dang and Wang (2022) Green innovation strategic orientation, GIC, Competitive advantage. GIC positively mediates the association between strategic green innovation orientation and competitive advantage. Haldorai et al. (2022) GIC, Top management green commitment, Green human resource management, Environmental performance. Both GIC and top management’s green commitment directly influence hotel environmental performance and green human resource management. Environmental product innovation AmoresSalvado ´ et al. (2014) Environmental product innovation, Firm performance. Confirms a positive association between environmental product innovation and firm performance. Qiu et al. (2020) Green product innovation, Competitive advantage. Green product innovation is actively associated with a competitive advantage. Wang, Wang, et al. (2021) Green product innovation, Green process innovation, Firm performance. Green product and process innovation significantly contribute to the firm’s performance. Huang and Chen (2022) Institutional pressure, Green product innovation, Green new product success. Institutional pressure has a positive effect on firms’ participation in green product innovation and the success rate of new green products. Green transformational leadership Chen and Chang (2013) Green transformational leadership, Green creativity, Green product development performance. Green transformational leadership actively impacts green product development performance and green creativity. Riva et al. (2021) Green transformational leadership, Green creativity, Environmental performance. Green creativity partially mediates the positive impact of green transformational leadership on environmental performance. Zhang and Ma (2021) Environmental leadership, Green innovation, Environmental management. Environmental leadership moderates the breadth and depth of environmental management’s impact on green innovation. Pan et al. (2021) Environmental leadership, GIC, Green product innovation. Environmental leadership moderates the relationship between GIC and green product innovation. Green competitive advantage Zameer et al. (2020) Green production, Green creativity, Green brand image, Green competitive advantage. Green brand image partially mediates the relationship between green production and green creativity on green competitive advantage. Kuo et al. (2022) Eco-innovation, Green core competence, Green competitive advantage. Research confirms the direct effect of green core competencies on green competitive advantage, but the direct effect of eco-innovation is insignificant. Muisyo et al. (2022) Green product innovation, Green process innovation, Green competitive advantage. Firms’ green process and product innovation positively affect green competitive advantage. Zameer et al. (2022) Environmental orientation, Green innovation, Green competitive advantage. Environmental orientation impacts green competitive advantage by influencing green innovation. C. Xin and Y. Wang

Journal of Hospitality and Tourism Management 57 (2023) 148–157 150 2. Literature review and research hypothesis 2.1. Resource-based view theory According to the RBV theory, the possession of valuable, rare or irreplaceable resources is the basis for an enterprise’s sustained competitive advantage (Hoskisson et al., 1999). Valuable resources enable an enterprise to plan and implement efficient and effective strategies (Barney, 1991). Resources that only a few competitors possess are considered rare (Haldorai et al., 2022). By transforming these resources into internal advantages and compensating for external weaknesses, the enterprise has the potential to gain a sustained competitive advantage over its core competitors (Haldorai et al., 2022). RBV states that an enterprise’s resources include human, structural and relational capital: (1) human capital refers to the enterprise’s collective knowledge, experience, and capabilities; (2) structural capital is the internal organizational assets, including symbolic assets such as facilities, equipment, and database systems, as well as abstract assets such as corporate culture and organizational norms; and (3) relational capital refers to the enterprise’s internal and external network of relationships, i.e., the network of stakeholder relationships (Sardo et al., 2018). Although enterprises can have a wide range of resources, RBV believes that intellectual capital is one of the most significant resources (Wright et al., 1994). While Chen (2008) divides GIC into three sub-dimensions, which are green human capital (organizational environmentally oriented experience, knowledge, competence and creativity, etc.), green structural capital (environmentally oriented organizational assets, reward and punishment systems, compensation systems, trademarks, copyrights, databases and management systems, etc.) and green relational capital (building relationships with partners, suppliers and customers to implement environmental innovation and gain competitive advantage). Based on RBV, GIC is a crucial resource that enables hotel enterprises to achieve a competitive advantage (Dang & Wang, 2022). This study is built upon the theoretical foundation provided by RBV. GIC, being a valuable and scarce resource for hotel enterprises, serves as a fundamental basis for attaining a green competitive advantage (Dang & Wang, 2022). According to RBV, innovative products are categorized as valuable and irreplaceable resources for hotel enterprises (Wang, Wang, et al., 2021). Consequently, hotels will persist in innovating environmental products to maintain their green competitive advantage. However, environmental product innovation often relies on the support of GIC as a distinctive resource (Haldorai et al., 2022). Meanwhile, according to RBV, leadership is regarded as a crucial resource for the business environment (Singh et al., 2020). In the context of green transformation in the hospitality industry, green transformational leadership is considered a rare resource (Riva et al., 2021). More specifically, green transformational leadership represents a proactive approach that leaders adopt to incorporate GIC into high-level environmental product innovation (Zhang & Ma, 2021). 2.2. Green intellectual capital and green competitive advantage Green competitive advantage is defined as the position an enterprise occupies in the field of environmental management or innovation that competitors cannot imitate or copy, which allows the enterprise to gain sustainable benefits (Muisyo et al., 2022). Green competitive advantage includes the enterprise’s low-cost advantage in environmental management or innovation, its ability to manage and innovate environmentally and provide higher quality environmental products than its major competitors (Chen & Chang, 2013; Zameer et al., 2022). GIC, in its essence, refers to the enterprise’s capacity to effectively address environmental challenges by combining competence, knowledge, and experience (Dang & Wang, 2022). It plays a critical role in hotel operations and development, creating economic benefits and improved environmental performance (Jirakraisiri et al., 2021). In recent years, GIC has gradually become a more critical capital element than conventional resources like money, land, and labor in the Spanish hotel industry, exerting a significant influence on hospitality development (Haldorai et al., 2022). Therefore, in the context of green transformation in the hospitality industry, GIC is a key driver of the competitive advantage for hotel enterprises (Liu & Jiang, 2020). Additionally, based on the RBV theory, GIC is regarded as a scarce, valuable and intangible resource for dealing with environmental issues, helping enterprises reduce pollution and guaranteeing sustainable development, with the role of building sustainable competitive advantage for enterprises (Dang & Wang, 2022). The logic of the RBV theory explains the effect of the three subdimensions of GIC on green competitive advantage. First, green human capital reflects a hospitality enterprise’s environmentally oriented experience, knowledge, capabilities and creativity (Chen, 2008). Human capital is essential for the daily operation and maintenance of a hospitality enterprise, where green competencies such as green R&D and innovation, green production and marketing, and green operations are required on the basis of green human capital (Huang et al., 2021). When a hospitality enterprise is facing environmental issues or trying to improve its environmental performance, its green competencies allow it to have a competitive advantage over its competitors (Obeidat et al., 2020). This is because green human capital allows hospitality employees to utilize green knowledge and competencies for continuous and diverse green activities, environmental management and innovation (Yong et al., 2019). Innovative ideas, concepts and competencies based on environmental protection are frequently rooted in its green human capital, which helps the hospitality enterprise build a unique competitive advantage in the area of environmental management or innovation, i.e., to establish the green competitive advantage for the hospitality enterprise (Yusliza et al., 2020). According to the RBV theory, green human capital should be an irreplaceable resource for a hospitality enterprise and one of its most valuable intangible assets. Second, green structural capital is also an essential resource for hospitality enterprises to build their competitive advantage. Environmentally oriented green organizational culture, green reputation, green information technology and green management systems are intangible assets that are unique and worthwhile to the hospitality enterprise. In contrast, green facilities and green infrastructure are scarce and irreplaceable tangible assets (Chen, 2008). As green structural capital supports green R&D, operations and management in hospitality, various green practices, activities and environmental innovations need to be rooted in green structural capital, i.e., these types of activities are often driven by organizational culture, green technologies, management systems and organizational structures (Wang et al., 2019). Therefore, these green assets enable a hospitality enterprise to build a competitive advantage. When a hospitality enterprise focuses on establishing its green competitive advantage, it is required to develop green business processes, improve its green organizational structure, establish a green organizational culture, utilize green information technology systems and purchase green infrastructure equipment (Dang & Wang, 2022). Therefore, based on RBV, with the establishment and improvement of green structural capital, the hospitality enterprise has a more robust capacity for green activities and environmental innovation compared to its competitors and is more likely to create a green competitive advantage (Yong et al., 2019). Finally, green relational capital is a unique resource for hospitality enterprises to build, maintain and expand their market relationships and improve their market position. It reflects the relationships between a hospitality enterprise and its stakeholders, such as partners, suppliers and customers (Chen, 2008). A hospitality enterprise’s relationship network is created through long-term accumulation. It is unique and complex to be copied or imitated by other competitors because it requires opportunities and is created in a specific time and space (Dang & Wang, 2022). Therefore, green resources acquired from a hospitality enterprise’s relationship network are often unique, valuable and scarce (Yusliza et al., 2020). According to RBV theory, this distinctive green C. Xin and Y. Wang

Journal of Hospitality and Tourism Management 57 (2023) 148–157 151 resource (i.e., green relational capital) can help the hospitality enterprise to build and improve its green capabilities and use them to meet the continuous green demands of its customers, create value and gain a green competitive advantage (Sadiq et al., 2022). Therefore, the following hypothesis is proposed in this paper. H1a. Green human capital is positively associated with the green competitive advantage. H1b. Green structural capital is positively associated with the green competitive advantage. H1c. Green relational capital is positively associated with the green competitive advantage. 2.3. Environmental product innovation Environmental product innovation refers to innovation that reduces environmental impact throughout the product lifecycle to achieve environmentally sustainable goals (Clausen & Fichter, 2019). Environmental product innovation can be achieved through innovations such as decreasing the use of polluting or toxic materials, improving energy and resource efficiency, using biodegradable and environmentally friendly packaging in product production and considering waste recycling and disposal at product end-of-life (Amores-Salvado ´ et al., 2014). Firstly, reducing the use of polluting or toxic materials during product production, which makes the product significantly greener or more environmentally friendly than traditional or competitors’ products, satisfies stakeholders’ environmental needs, and enhances the hospitality enterprise’s green reputation, competitiveness and environmental performance (Wang, Wang, et al., 2021). Secondly, using less energy and fewer resources throughout the product life cycle helps the hospitality enterprise to save energy and reduce emissions, increase energy and resource utilization rates, reduce costs, increase the possibility of entering new markets and establish a competitive advantage (Qiu et al., 2020). Finally, increasing the end-of-life disposal of products provides ideas for hospitality enterprises to turn waste into treasure while adopting environmentally friendly packaging to build a green corporate image and improve sustainable performance (Asadi et al., 2020). It has been shown that when a company is committed to environmental product innovation, its stakeholders’ needs for environmental protection are met, and satisfaction with the company gradually increases (Wang & Juo, 2021). Therefore, when a hospitality enterprise is more innovative in its environmental products, the more efficient its operations and maintenance become, resulting in lower costs and higher sales, thus improving its economic and environmental performance, significantly enhancing competitiveness and gaining a green competitive advantage (Huang & Chen, 2022; Qiu et al., 2020). Based on RBV, a firm’s intangible assets, such as GIC, are more likely to contribute to environmental product innovation (Haldorai et al., 2022). GIC is recognized as a link between corporate knowledge of eco-friendly practices and environmental innovation (Shehzad et al., 2023), enabling corporations to harness their creativity in developing new environmentally oriented products (Zameer et al., 2020). Specifically, organizations and their employees have accumulated and developed environmental knowledge and competencies through prior work experiences, which can contribute to the enhancement of the company’s environmental knowledge. Based on the knowledge and competencies, environmental product innovations are launched to develop new products that are more energy-efficient and environmentally friendly (Mansoor et al., 2021). Consequently, the knowledge and competencies possessed by hotel enterprises significantly influence the extent of their environmental product innovation (Wang & Juo, 2021). Haldorai et al. (2022) and Nisar et al. (2021) have shown that GIC positively influences innovation activities in hospitality enterprises, improving environmental performance and building competitive advantage. Wang and Juo (2021) pointed out that environmental product innovation is rooted in GIC, which directly impacts the efficiency of a firm’s innovation and enables timely responsiveness to consumer demand and market trends. First, human capital is seen as the primary basis for innovation in firms, as the expertise and skills of employees in their functions and roles continuously motivate innovation (Graziano, 1997). Green human capital in a hotel enterprise facilitates the creation of innovation as a source of green competitive advantage (Nisar et al., 2021). When a hotel enterprise has a high-level green human capital, hotel employees have a high level of green competence (Jirakraisiri et al., 2021). They are more conducive to generating innovative ideas that are environmentally friendly and contribute to environmental protection. Therefore, A high-level green human capital enables hotel employees to make product innovations with more consideration for environmental issues to environmental issues to reduce the environmental impact of their products and achieve environmental product innovation, thus improving the green competitive advantage of the hotel enterprise. Second, firms develop structural capital to enhance their learning and innovation capabilities (Jirakraisiri et al., 2021). Green structural capital containing green organizational culture, green information technology and green management systems cultivates firms’ innovation capabilities and thus enhances green competitive advantage (Haldorai et al., 2022). When a hotel enterprise has a high-level green structural capital, the inculcation of a green organizational culture and the use of green technology systems motivate the enterprise to develop new and more environmentally friendly products (Huang & Chen, 2022) to reduce the use and emission of pollutants. Therefore, a high-level green structural capital in hospitality enterprises motivates them to develop environmentally friendly products and conduct environmental product innovation to support obtaining a green competitive advantage. Finally, close relationships between firms and stakeholders such as partners, suppliers and customers allow firms to gain new and diverse perspectives, knowledge and experience to promote product innovation (Sadiq et al., 2022). Green relational capital promotes green knowledge sharing and supports green innovation to gain a green competitive advantage. On the one hand, close relationships between hospitality enterprises and environmentally oriented customers encourage environmental product innovation to meet the green needs of customers (Jirakraisiri et al., 2021). On the other hand, close relationships with green partners and suppliers facilitate green knowledge flow and green technology sharing to support environmental product innovation (Dang & Wang, 2022). Both contribute to improving the green competitive advantage of hospitality enterprises. Therefore, a high-level green relational capital of hospitality enterprises supports the conduct of environmental product innovation and improves their green competitive advantage. Therefore, the following hypothesis is proposed in this paper. H2a. Environmental product innovation mediates the relationship between green human capital and green competitive advantage. H2b. Environmental product innovation mediates the relationship between green structural capital and green competitive advantage. H2c. Environmental product innovation mediates the relationship between green relational capital and green competitive advantage. 2.4. Green transformational leadership as a moderator Transformational leadership achieves the vision of improved corporate performance by creating an innovative climate and motivating employees to innovate (Cui & Wang, 2022). Green transformational leadership, proposed by Chen and Chang (2013), is defined as leadership behaviors that provide employees with green inspiration, motivation, and vision, oriented toward achieving environmental goals. Effective green transformational leadership complies with the goal of environmental greening, pays more attention to the value of the C. Xin and Y. Wang

Journal of Hospitality and Tourism Management 57 (2023) 148–157 152 environment, understands the green needs of stakeholders, and is committed to corporate green change (Zhang & Ma, 2021). Research has shown that green transformational leadership encourages green jobs (Zhang & Ma, 2021), and supports green creativity and green innovation (Singh et al., 2020), to improve green product development performance (Riva et al., 2021). A high level of green transformational leadership leader typically has attitudes, values and behaviors promoting environmental improvement, so when managers of hospitality enterprises are mindful of the environment, the enterprises are more likely to develop their GIC (Cui & Wang, 2022). First, high-level green transformational leadership can raise the environmental awareness of hospitality employees, motivate them to learn new knowledge, lead them to develop new perspectives on environmental concerns (Chen & Chang, 2013), support them to consider innovative solutions to environmental issues, encourage environmentally oriented product innovation, and provide resources and technical support for new products that benefit the environment (Zhang & Ma, 2021). Thus, a higher level of green transformational leadership can enhance the positive relationship between green human capital and environmental product innovation. Second, high-level green transformational leadership can build green values, corporate culture and organizational structure for hospitality enterprises, create an excellent eco-friendly atmosphere (Dang & Wang, 2022), adopt greener information systems and technologies, improve environmental pollution detection systems, support green R&D in hospitality, and find innovative ways to reduce pollution in the product production process (Wang et al., 2019). Thus, a higher level of green transformational leadership can enhance the positive relationship between green structural capital and environmental product innovation. Finally, high-level green transformational leadership can strengthen the level of relationship between hospitality enterprises and stakeholders such as partners, suppliers and customers, promote the learning of environmental knowledge and technology, the sharing of environmental information and resources, and facilitate environmental innovation (Pan et al., 2021). Meanwhile, high-level green transformational leadership pays more attention to stakeholders’ green visions, continuously improves the environmental aspects of products to realize stakeholders’ green demands, and explores innovative solutions for improving products and reducing pollution (Riva et al., 2021). Thus, a higher level of green transformational leadership can enhance the positive relationship between green relational capital and environmental product innovation. Therefore, the following hypothesis is proposed in this paper. H3a. Green transformational leadership moderates the relationship between green human capital and environmental product innovation. H3b. Green transformational leadership moderates the relationship between green structural capital and environmental product innovation. H3c. Green transformational leadership moderates the relationship between green relational capital and environmental product innovation. 2.5. Research model In Fig. 1, the research model presented shows the suggested relationships between constructs. Notably, the independent variable is GIC, the dependent variable is green competitive advantage, the mediating variable is environmental product innovation, and the moderating variable is green transformational leadership in the model. 3. Methodology 3.1. Data collection and sample This study was conducted with working employees in the Spanish hospitality industry. To improve the sample quality and survey collection efficiency, we edited the survey through Qualtrics and distributed it using Mturk (Chen & Eyoun, 2021). Drawing on the study by Chen and Eyoun (2021), three selection items were set at the beginning of the survey to ensure that the respondents were the target audience, including “Which of the following countries are you located in?” “Which of the following industries are you working in?” and “Which of the following is related to your position?” The survey was automatically closed if the criteria were not met. Attention check questions have been added to guarantee survey quality. Before data collection, a pre-test was conducted for this study. 48 valid questionnaires were gathered, analyzed and evaluated to ensure a reliable, readable survey. The formal research was carried out through the Mturk platform, where current employees (non-managers) in the Spanish hospitality industry were precisely invited to fill in questionnaires. 463 questionnaires were returned from October 2022 to November 2022, of which 63 did not pass the attention check question. The total number of valid questionnaires was 400. The sample data were analyzed by SPSS 27.0 and AMOS 28.0. The demographic data are presented in Table 2. Of these, 336 subjects were male (84%), and 64 subjects were female (16%). In terms of age, 278 subjects were 25–34 years old (69.5%), and 96 were 35–44 years old (24%). For the type of hospitality, 174 subjects worked in a four-star hotel/restaurant (43.5%), 130 worked in a five-star hotel/ restaurant (32.5%), and 88 worked in a three-star hotel/restaurant (22%). For hotel size, 250 subjects worked in hotels with 150–300 employees (62.5%), and 126 worked with less than 150 employees (31.5%). Regarding the department, 102 subjects worked in the front office (25.5%), 84 worked in food and beverage (21%), 82 worked in food production (20.5%), and 64 worked in housekeeping (16%). Fig. 1. Research model. C. Xin and Y. Wang

Journal of Hospitality and Tourism Management 57 (2023) 148–157 153 3.2. Measurement scales The survey contains both demographic information and variable measurement components. The variable measure uses a 7-point Likert scale to measure six constructs, including green human capital, green structural capital, green relational capital, environmental product innovation and green competitive advantage. Questionnaire items were adapted from previous studies, with 1 representing strong disagreement and 7 representing strong agreement. Adapted from Chen (2008) and Nisar et al. (2021), five items measure the Green Human Capital scale, eight measure the Green Structural Capital scale, and five measure the Green Relational Capital. Adapted from Huang and Chen (2022), the Environmental Product Innovation scale is measured by five items. Adapted from Chen and Chang (2013) and Cui and Wang (2022), six items measure the Green Transformation Leadership scale. Adapted from Chen and Chang (2013) and Muisyo et al. (2022), six items measure the Green Competitive Advantage scale. Detailed items are listed in Table 3. 4. Results 4.1. Data normality and common method variance As shown in Table 3, all items meet the requirements of normal distribution, i.e., |skewness index| ≤ 0.99 and |kurtosis index| ≤ 0.60 (Wu et al., 2022). In addition, we used Harman’s single-factor analysis to test the effect of common method variance on the experimental results. Results indicated that the first variable explained only 39.818% of the variance (with a threshold of 50%), suggesting that the CMV issue was insignificant (Podsakoff et al., 2003). 4.2. Reliability and validity The reliability and validity of the scale were tested using SPSS 27.0 and AMOS 28.0. The confirmatory factor analysis showed that the model fitted well (χ2/df = 2.969, p ＜ 0.001, GFI = 0.838, RMSEA = 0.07, CFI = 0.944, TLI = 0.936, IFI = 0.944). As shown in Table 3, all Cronbach’s α was higher than 0.8, CR was higher than 0.8, and AVE was higher than 0.6, indicating high reliability, internal consistency and convergent validity of the scales (Yu et al., 2022). Additionally, this study passed the multicollinearity test, with all Variance Inflation Factor (VIF) values in Table 4 ranging from 1.193 to 1.687, less than the threshold value. (Wu et al., 2022). Table 2 Demographic profile (N = 400). Variables N % Variables N % Gender Hotel size Male 336 84% Less than 150 employees 126 31.5% Female 64 16% 150-300 employees 250 62.5% Age More than 300 employees 24 6% ≤25 8 2% Department 25–34 278 69.5% Front Office 102 25.5% 35–44 96 24% Housekeeping 64 16% ≥45 18 4.5% Food and Beverage 84 21% Type of hospitality company Food Production 82 20.5% Five-star hotel/ restaurant 130 32.5% Marketing & Sales 26 6.5% Four-star hotel/ restaurant 174 43.5% Human Resources 26 6.5% Three-star hotel/ restaurant 88 22% Finance 14 3.5% Resort hotel 8 2% Maintenance 2 0.5% Table 3 Confirmatory factor analysis findings. Constructs and items Mean (SD) Skewness Kurtosis Stdloading Green human capital (GHC) (α = 0.934; CR = 0.917; AVE = 0.689) GHC 1: Employees in our hotel always involve a positive productivity and contribution towards environmental protection. 5.26 (1.30) − .68 − .02 .81 GHC 2: Employees in our hotel always have an adequate competence towards environmental protection. 5.24 (1.46) − .78 − .32 .81 GHC 3: Employees in our hotel always provide high product and service qualities towards environmental protection. 5.32 (1.55) − .72 − .49 .87 GHC 4: Our cooperative degree of teamwork towards environmental protection is always performed at high levels. 5.30 (1.41) − .74 − .15 .84 GHC 5: Our managers always fully support our employees to achieve their jobs of environmental protection. 5.18 (1.51) − .85 − .26 .82 Green structural capital (GSC) (α = 0.965; CR = 0.945; AVE = 0.681) GSC 1: Our hotel has a superior management system of environmental protection. 5.24 (1.58) − .78 − .39 .83 GSC 2: Our hotel has a high percentage of environmental management employees. 5.20 (1.52) − .77 − .43 .83 GSC 3: Our hotel always makes an adequate investment in environmental protection facilities. 5.21 (1.58) − .82 − .36 .84 GSC 4: Our overall operation processes towards environmental protection always operate efficiently. 5.31 (1.48) − .94 − .04 .80 GSC 5: Our knowledge management system always facilitates the accumulation and sharing of environmental management knowledge. 5.26 (1.62) − .85 − .33 .84 GSC 6: Our hotel has formed a committee to progress on key issues in environmental protection. 5.14 (1.57) − .77 − .39 .82 GSC 7: Our hotel has established detailed rules and regulations of environmental protection. 5.24 (1.51) − .79 − .25 .82 GSC 8: Our hotel has established a reward system for accomplishing environmental tasks. 5.34 (1.47) − .93 − .07 .82 Green relational capital (GRC) (α = 0.931; CR = 0.922; AVE = 0.703) GRC 1: Our hotel designs products or services are always in line with the environmental desires of our customers. 5.28 (1.34) − .63 − .21 .82 GRC 2: Our hotel designs products or services are always in line with the environmental desires of our customers. 5.24 (1.40) − .89 − .16 .82 GRC 3: Customers are always satisfied with our hotel’s environmental protection. 5.44 (1.48) − .92 .08 .83 GRC 4: Our cooperative relationships with customers towards environmental protection are always stable. 5.31 (1.49) − .83 − .19 .87 GRC 5: Our cooperative relationships with strategic partners towards environmental protection are always stable. 5.30 (1.42) − .91 .19 .85 Environmental product innovation (EPI) (α = 0.912; CR = 0.917; AVE = 0.689) EPI 1: Our hotel always develops environmentally friendly products to replace traditional products. 5.36 (1.46) − .89 .07 .83 (continued on next page) C. Xin and Y. Wang

Journal of Hospitality and Tourism Management 57 (2023) 148–157 154 4.3. Hypotheses testing Table 5 revealed the results of direct and mediating effects analyzed using AMOS 28.0. H1a was supported by the fact that green human capital was significantly positively associated with green competitive advantage (β = 0.180, p < 0.01). The positive effects of green structural capital on green competitive advantage (β = 0.260, p < 0.001) and of green relational capital on green competitive advantage (β = 0.203, p < 0.01) were significant. Therefore, H1b and H1c were supported. The indirect effect of green human capital on green competitive advantage through environmental product innovation was significant (β = 0.039, p < 0.01). 95% confidence interval (CI) [0.006, 0.099] without 0, supporting H2a. Moreover, the indirect effects of green structural capital (β = 0.039, p < 0.01) and green relational capital (β = 0.041, p < 0.05) on green competitive advantage through environmental product innovation were significant and 95% confidence interval without 0. Therefore, H2b and H2c were supported. The results of moderating effects (H3a-c) are shown in Table 6. Model 3 showed a significant positive effect of the interaction coefficient of GHC*GTL on environmental product innovation (β = 0.180, p < 0.001), and the moderating effect of green transformational leadership in model 5 significantly affected the relationship between green structural capital and environmental product innovation (β = 0.217, p < 0.001), and the moderating effect of green transformational leadership in model 7 (β = 0.199, p < 0.001) was equally significant. A simple slope analysis was conducted and plotted to verify moderating effects further, as shown in Fig. 2, where H3a-c was supported. 5. Discussion and conclusion 5.1. Conclusion This study clearly examined the complex theoretical associations between essential factors, namely GIC (including green human capital, green structural capital, and green relational capital) and environmental product innovation, and green competitive advantage in Spanish hotels. Based on the RBV theory, we further identified the role of green transformational leadership in facilitating GIC on green competitive advantage. Significantly, our results were consistent with the hypotheses but Table 3 (continued ) Constructs and items Mean (SD) Skewness Kurtosis Stdloading EPI 2: Our hotel always develops new products using less or non-polluting materials. 5.37 (1.39) − .73 − .20 .83 EPI 3: Our hotel always develops new products reduce the consumption of materials or energy. 5.44 (1.33) − .92 .43 .81 EPI 4: Our hotel always develops new products use environmentally friendly packaging. 5.45 (1.31) − .77 − .12 .86 EPI 5: Our hotel always develops new products consider recycling and disposal at the end-of-life. 5.44 (1.32) − .99 .49 .82 Green transformation leadership (GTL) (α = 0.958; CR = 0.943; AVE = 0.734) GTL 1: Our managers always inspire employees with environmental plans. 5.11 (1.36) − .57 − .30 .81 GTL 2: Our managers always provide a clear environmental vision for employees. 5.27 (1.50) − .81 − .26 .85 GTL 3: Our managers always engage employees to work together to achieve the same environmental goals. 5.21 (1.61) − .72 − .60 .87 GTL 4: Our managers always encourage employees to achieve environmental goals beyond expectations. 5.25 (1.59) − .79 − .49 .87 GTL 5: Our managers always consider employees’ environmental beliefs in their actions. 5.25 (1.45) − .85 − .12 .86 GTL 6: Our managers always stimulate employees to create green ideas. 5.25 (1.57) − .76 − .48 .88 Green competitive advantage (GCA) (α = 0.971; CR = 0.953; AVE = 0.772) GCA 1: Our hotel always has the competitive advantage of low environmental innovation costs compared to its major competitors. 5.25 (1.74) − .78 − .57 .89 GCA 2: The quality of the environmental products offered by our hotel is always better than that of its major competitors. 5.30 (1.62) − .87 − .22 .88 GCA 3: Our hotel is always more capable of green R&D and innovation than its major competitors. 5.35 (1.71) − .84 − .45 .87 GCA 4: Our hotel is always more capable of environmental management than its major competitors. 5.24 (1.69) − .78 − .48 .89 GCA 5: Major competitors always fail to imitate the environmental products of our hotels. 5.24 (1.65) − .87 − .27 .85 GCA 6: Major competitors always fail to replace the unique position of our hotel on environmental management and innovation. 5.28 (1.73) − .82 − .46 .89 Notes: SD = Standard deviation; α = Cronbach’s alpha; CR = Composite reliability; AVE = Average variance extracted. Table 4 Correlation matrix and covariance matrix. Constructs Mean SD VIF 1 2 3 4 5 6 1. GHC 5.261 1.285 1.402 .890 .522 .456 .575 .756 2. GSC 5.242 1.382 1.687 .501** .754 .525 .892 .960 3. GRC 5.312 1.263 1.298 .322** .432** .407 .574 .700 4. EPI 5.413 1.174 1.193 .302** .324** .275** .466 .622 5. GTL 5.224 1.378 1.350 .325** .468** .330** .288** .873 6. GCA 5.275 1.581 .372** .439** .351** .335** .400** Notes: GHC = Green human capital; GSC = Green structural capital; GRC = Green relational capital; EPI = Environmental product innovation; GTL = Green transformation leadership; GCA = Green competitive advantage; VIF = Variance inflation factor. The correlation matrix is below the diagonal. **p < 0.01. The covariance matrix is above the diagonal. Table 5 Direct effects and mediating effects. Hypothesis Path Standardized estimates LL UL Decision H1a GHC→GCA .180** .026 .343 Supported H1b GSC→GCA .260*** .108 .441 Supported H1c GRC→GCA .203** .032 .370 Supported H2a GHC→EPI→GCA .039** .006 .099 Supported H2b GSC→EPI→GCA .039** .008 .096 Supported H2c GRC→EPI→GCA .041* .006 .107 Supported Notes: ***p < 0.001, **p < 0.01, *p < 0.05; LL = lower limit, UL = upper limit. C. Xin and Y. Wang

Journal of Hospitality and Tourism Management 57 (2023) 148–157 155 generated novel results that differed from previous research. The findings showed that the impact of GIC (including green human capital, green structural capital, and green relational capital) on green competitive advantage in Spanish hotels exists, and green transformational leadership has a moderating effect. First, the results revealed that green human capital (βGHC→GCA = 0.180, p < 0.01, MeanGHC = 5.261), green structural capital (βGSC→GCA = 0.260, p < 0.001, MeanGSC = 5.242) and green relational capital (βGRC→GCA = 0.203, p < 0.001, MeanGRC = 5.312) had a positive influence on the green competitive advantage of hotel firms (MeanGCA = 5.275), confirming the positive relationship between GIC of hotel firms and green competitive advantage. Consistent with a previous study (Dang & Wang, 2022), which found that GIC motivates hotel staff and leads to benefits, our results demonstrate that a hotel’s GIC advantage enhances its green competitive advantage. Second, we found that GIC positively influenced the capacity and creativity of hotel employees to innovate environmentally friendly products, resulting in a green competitive advantage (βGHC→EPI→GCA = 0.039, p ＜0.01; βGSC→EPI→GCA = 0.039, p ＜0.01; βGRC→EPI→GCA = 0.041, p ＜0.05). Indicating a strong positive relationship between environmental product innovation mediating GIC and green competitive advantage. We revealed that GIC plays a crucial role in fostering environmental innovation among employees and inspiring eco-friendly behaviors while enhancing the hotel’s competitiveness, which aligns with Alkhatib and Valeri’s (2022) study. Finally, the results indicated a strong effect of green transformational leadership on the relationship between GIC and environmental product innovation, confirming the moderating effect of green transformational leadership (βGHC*GTL = 0.180, p < 0.001; βGSC*GTL = 0.217, p < 0.001; βGRC*GTL = 0.199, p < 0.001). In conclusion, hospitality leaders’ high level of green transformational leadership motivates staff to leverage GIC for innovating high-level environmental products. This finding supports the research by Singh et al. (2020), demonstrating that green transformational leadership strengthens the association between GIC and green innovation. 5.2. Theoretical implications Our paper has the following theoretical contributions. First, this study enriches the existing hospitality management literature and GIC literature by exploring how GIC enhances the green competitive advantage of hospitality enterprises. While prior research has highlighted the role of green human resource management in improving firms’ environmental impacts and competitive advantage (Muisyo et al., 2022; Munawar et al., 2022). These studies often focused on specific aspects of GIC (Dang & Wang, 2022), and few studies adopted a GIC perspective and emphasized the overall role of GIC in environmental management (Haldorai et al., 2022; Huang et al., 2021; Munawar et al., 2022). In contrast, this study emphasizes the comprehensive role of GIC in hotel firms’ green competitive advantage and expands the scope of GIC research, differentiating itself from prior studies. Second, through rigorous theoretical and data analysis, we confirm the positive relationship between GIC and green competitive advantage. While the existing literature has suggested that intellectual capital is associated with a firm’s competitive advantage (Dang & Wang, 2022), green-oriented research is still in its infancy (Muisyo et al., 2022). This study fills the research gap regarding the impact of GIC on green competitive advantage in hotel enterprises and holds significance in the context of green transformation in the hospitality industry, particularly for the more fragile hospitality and tourism sector (Yu et al., 2022). Third, our finding confirms the position of previous studies (Alkhatib & Valeri, 2022; Rehman et al., 2022). As mentioned above, GIC in hotels Table 6 Moderating effects of green transformational leadership. Variables EPI Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Gender − .018 − .050 − .036 − .049 − .043 − .033 − .012 Age .077 .064 .060 .061 .062 .059 .056 Hotel type − .020 − .010 − .005 .009 .014 .004 .014 Hotel size − .145** − .094 − .087 − .097* − .099* − .096 − .101* Department .068 .061 .065 .066 .070 .076 .071 GHC .218*** .255*** GSC .228*** .283*** GRC .186*** .237*** GTL .211*** .251*** .176*** .220*** .220*** .255*** GHC*GTL .180*** GSC*GTL .217*** GRC*GTL .199*** R2 .029 .148 .176 .145 .185 .136 .170 Adj-R2 .017 .132 .159 .130 .168 .121 .153 ΔR2 .029 .118 .028 .116 .040 .107 .034 F 2.359* 9.693*** 10.419*** 9.512*** 11.072*** 8.814*** 10.022*** Notes: ***p < 0.001, **p < 0.01, *p < 0.05. Fig. 2. Moderating results of green transformational leadership. C. Xin and Y. Wang

Journal of Hospitality and Tourism Management 57 (2023) 148–157 156 continues to support the development of the sector, especially in Spain (Martinez-Martinez et al., 2021). However, the majority of the research on the impact mechanisms of environmental product innovation has focused on the manufacturing sector (Qiu et al., 2020). Only a few existing hotel-related studies, including Asadi et al. (2020), have explored the dimension of environmental product innovation. This study integrates environmental product innovation into the research framework of the Spanish hospitality industry, contributing to a better understanding of the impact mechanisms between GIC and green competitive advantage. We expand the existing literature on GIC from the perspective of the hospitality industry, which distinguishes this research from previous work. Finally, previous literature has examined the direct effects of green transformational leadership on firm performance (Zhang & Ma, 2021) and competitive advantage (Riva et al., 2021). However, few studies have investigated the moderation effect of differences in the level of green transformational leadership possessed by leaders on the relationship between GIC and environmental product innovation in a hospitality context (Singh et al., 2020). Moreover, most previous research on hotels has been discussed from a consumer perspective, paying less attention to the advantages of leadership (Cui & Wang, 2022). This study aims to address the call for examining factors related to green transformational leadership (Amankwaa et al., 2022) by investigating the impact of varying levels of green transformational leadership in Spanish hotel enterprises. We make a significant contribution to GIC literature by providing insights into the variations in the utilization of GIC for environmental product innovation among Spanish hospitality enterprises with different levels of green transformational leadership. 5.3. Managerial implications In practice, increasing the competitive advantage of hotel companies and capturing a larger market share has been a central issue in the hospitality industry, especially in Spain (Martinez-Martinez et al., 2021). The results of our study help to provide Spanish hotel companies with a management approach to gain a competitive advantage. To conclude, Spanish hotels should embrace a comprehensive green transformation that takes into account and incorporates green from the entire perspective of hotel operations. This entails training and selecting employees who exhibit eco-friendly behaviors and promoting environmental awareness through specific plans. Additionally, implementing green-oriented regulations can effectively regulate polluting behaviors while fostering a culture of environmental consciousness among employees. At the same time, we recommend that hotel enterprises attach importance to GIC in production and operation and strive to continuously improve the level of environmental product innovation to meet environmental challenges and improve the competitive advantage of hotels (Munawar et al., 2022). Hotel managers should play a pivotal role in encouraging and incentivizing their employees’ green behaviors and creativity. In addition, hotel managers should also actively establish a green management system for hotel enterprises and build green partnerships. For example, establish close cooperation with green clients and suppliers, and participate in green innovation plans with green partners. Hotel companies can also improve their GIC levels by investing in green equipment and facilities, developing an eco-friendly organizational culture and operating system, and refining the green organizational structure. Focusing on GIC will promote environmental protection innovation in hotel enterprises, and enterprises will gradually gain green competitive advantages. Furthermore, we encourage hospitality companies to focus on environmentally oriented leadership development and the development of employees who may have green transformational leadership behaviors in order to improve the level of GIC and increase the alignment of the green vision of hospitality company employees with the organizational vision (Amankwaa et al., 2022). For instance, a hospitality enterprise could initiate a formal green education project to impart green knowledge and ideas to its employees. This project could include specialized training and education sessions focused on green knowledge and competencies. During this program, emphasis is placed on developing green leadership behaviors among employees and uncovering potential green leadership. 5.4. Limitations and future research Although we have provided new evidence on the relationship between GIC and green competitive advantage in hotels, some limitations still need to be further explored in future research. First, the data in our study were all sourced from practitioners in the Spanish hospitality industry. As different countries or regions have different levels of development in the hospitality industry and place various levels of emphasis on the environment (Liu & Jiang, 2020), future research may consider replicating this model in similar situations in other countries or across countries to validate the observations and generalize this study’s findings. Second, online surveys and self-reports have unavoidable common method variance (Yu et al., 2022). Despite the rigorous experimental controls and data validation methods used in this study to reduce its influence, future research could incorporate contextual experiments and in-depth interviews to obtain more rigorous data. Finally, we only explored the mediating effects of environmental product innovation and the moderating effects of green transformational leadership. Nevertheless, alternative variables, like brand equity and environmental commitment, may also influence the relationship between GIC and green competitive advantage in hotels. Therefore, future research could explore this relationship’s internal mechanisms and boundary conditions more. Declaration of competing interest The authors report there are no competing interests to declare. Acknowledgements This work was supported by the National Natural Science Foundation of China (Grant number: 72072028) and the Fundamental Research Funds for the Central Universities (N2206006). References Aguiar-Quintana, T., Nguyen, T. H. H., Araujo-Cabrera, Y., & Sanabria-Díaz, J. M. (2021). Do job insecurity, anxiety and depression caused by the COVID-19 pandemic influence hotel employees’ self-rated task performance? The moderating role of employee resilience. International Journal of Hospitality Management, 94(3), Article 102868. Alkhatib, A. W., & Valeri, M. (2022). Can intellectual capital promote the competitive advantage? Service innovation and big data analytics capabilities in a moderated mediation model. European Journal of Innovation Management. https://doi.org/ 10.1108/EJIM-04-2022-0186 Amankwaa, A., Seet, P. S., & Susomrith, P. (2022). Tackling hotel employees’ turnover: A moderated-mediation analysis of transformational leadership, organisational embeddedness, and community embeddedness. Journal of Hospitality and Tourism Management, 51(2), 67–78. Amores-Salvado, ´ J., Castro, G. M. D., & Navas-Lopez, ´ J. E. (2014). Green corporate image: Moderating the connection between environmental product innovation and firm performance. Journal of Cleaner Production, 83(22), 356–365. Asadi, S., Pourhashemi, S. O., Nilashi, M., Abdullah, R., Samad, S., Yadegaridehkordi, E., Aljojo, N., & Razali, N. S. (2020). Investigating influence of green innovation on sustainability performance: A case on Malaysian hotel industry. Journal of Cleaner Production, 258(17), Article 120860. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. Chen, Y. S. (2008). The positive effect of green intellectual capital on competitive advantages of firms. Journal of Business Ethics, 77(3), 271–286. Chen, Y., & Chang, C. (2013). The determinants of green product development performance: Green dynamic capabilities, green transformational leadership, and green creativity. Journal of Business Ethics, 116(1), 107–119. Chen, H., & Eyoun, K. (2021). Do mindfulness and perceived organizational support work? Fear of COVID-19 on restaurant frontline employees’ job insecurity and C. Xin and Y. Wang

Journal of Hospitality and Tourism Management 57 (2023) 148–157 157 emotional exhaustion. International Journal of Hospitality Management, 94(3), Article 102850. Clausen, J., & Fichter, K. (2019). The diffusion of environmental product and service innovations: Driving and inhibiting factors. Environmental Innovation and Societal Transitions, 31(2), 64–95. Cui, R., & Wang, J. (2022). Shaping sustainable development: External environmental pressure, exploratory green learning, and radical green innovation. Corporate Social Responsibility and Environmental Management, 29(3), 481–495. Dang, V. T., & Wang, J. (2022). Building competitive advantage for hospitality companies: The roles of green innovation strategic orientation and green intellectual capital. International Journal of Hospitality Management, 102(3), Article 103161. EUR-Lex. (2021). EU action plan: “Towards Zero pollution for Air, water and Soil”. Retrieved from https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX% 3A52021DC0400. (Accessed 19 November 2022). Graziano, K. A. (1997). Innovation: Leadership strategies for the competitive edge - Kuczmarski, TD. Journal of Product Innovation Management, 14(2), 142–143. Haldorai, K., Kim, W. G., & Garcia, R. L. F. (2022). Top management green commitment and green intellectual capital as enablers of hotel environmental performance: The mediating role of green human resource management. Tourism Management, 88(1), Article 104431. Hoskisson, R. E., Hitt, M. A., Wan, W. P., & Yiu, D. (1999). Theory and research in strategic management: Swings of a pendulum. Journal of Management, 25(3), 417–456. Huang, Y. C., & Chen, C. T. (2022). Exploring institutional pressures, firm green slack, green product innovation and green new product success: Evidence from Taiwan’s high-tech industries. Technological Forecasting and Social Change, 174(1), Article 121196. Huang, S., Yu, Z., Shao, Y., Yu, M., & Li, Z. (2021). Relative effects of human capital, social capital and psychological capital on hotel employees’ job performance. International Journal of Contemporary Hospitality Management, 33(2), 448–466. Jirakraisiri, J., Badir, Y. F., & Frank, B. (2021). Translating green strategic intent into green process innovation performance: The role of green intellectual capital. Journal of Intellectual Capital, 22(7), 43–67. Kuo, F. I., Fang, W. T., & Lepage, B. A. (2022). Proactive environmental strategies in the hotel industry: Eco-innovation, green competitive advantage, and green core competence. Journal of Sustainable Tourism, 30(6), 1240–1261. Liu, C. H., & Jiang, J. F. (2020). Assessing the moderating roles of brand equity, intellectual capital and social capital in Chinese luxury hotels. Journal of Hospitality and Tourism Management, 43(2), 139–148. Li, D., Zheng, M., Cao, C., Chen, X., Ren, S., & Huang, M. (2017). The impact of legitimacy pressure and corporate profitability on green innovation: Evidence from China top 100. Journal of Cleaner Production, 141, 41–49. Mansoor, A., Jahan, S., & Riaz, M. (2021). Does green intellectual capital spur corporate environmental performance through green workforce? Journal of Intellectual Capital, 22(5), 823–839. Martinez-Martinez, A., Cegarra-Navarro, J. G., Garcia-Perez, A., & Vicentini, F. (2021). Extending structural capital through pro-environmental behaviour intention capital: An outlook on Spanish hotel industry. Journal of Intellectual Capital, 22(3), 633–652. Muisyo, P., Su, Q., Ho, T. H., Julius, M. M., & Usmani, M. S. (2022). Implications of green HRM on the firm’s green competitive advantage: The mediating role of enablers of green culture. Journal of Manufacturing Technology Management, 33(2), 308–333. Munawar, S., Yousaf, D. H. Q., Ahmed, M., & Rehman, D. S. (2022). Effects of green human resource management on green innovation through green human capital, environmental knowledge, and managerial environmental concern. Journal of Hospitality and Tourism Management, 52(3), 141–150. Nisar, Q. A., Haider, S., Ali, F., Jamshed, S., Ryu, K., & Gill, S. S. (2021). Green human resource management practices and environmental performance in Malaysian green hotels: The role of green intellectual capital and pro-environmental behavior. Journal of Cleaner Production, 311(34), Article 127504. Obeidat, S. M., Al Bakri, A. A., & Elbanna, S. (2020). Leveraging "green" human resource practices to enable environmental and organizational performance: Evidence from the qatari oil and gas industry. Journal of Business Ethics, 164(2), 371–388. Pan, C., Jiang, Y., Wang, M., Xu, S., Xu, M., & Dong, Y. (2021). How can agricultural corporate build sustainable competitive advantage through green intellectual capital? A new environmental management approach to green agriculture. International Journal of Environmental Research and Public Health, 18(15), 7900. Podsakoff, P. M., Mackenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. Qiu, L., Jie, X., Wang, Y., & Zhao, M. (2020). Green product innovation, green dynamic capability, and competitive advantage: Evidence from Chinese manufacturing enterprises. Corporate Social Responsibility and Environmental Management, 27(1), 146–165. Rehman, S. U., Bresciani, S., Ashfaq, K., & Alam, G. M. (2022). Intellectual capital, knowledge management and competitive advantage: A resource orchestration perspective. Journal of Knowledge Management, 26(7), 1705–1731. Riva, F., Magrizos, S., & Rubel, M. R. B. (2021). Investigating the link between managers’ green knowledge and leadership style, and their firms’ environmental performance: The mediation role of green creativity. Business Strategy and the Environment, 30(7), 3228–3240. Sadiq, M., Adil, M., & Paul, J. (2022). Eco-friendly hotel stay and environmental attitude: A value-attitude-behaviour perspective. International Journal of Hospitality Management, 100(1), Article 103094. Sardo, F., Serrasqueiro, Z., & Alves, H. (2018). On the relationship between intellectual capital and financial performance: A panel data analysis on SME hotels. International Journal of Hospitality Management, 75(8), 67–74. Shehzad, M. U., Zhang, J., Dost, M., Ahmad, M. S., & Alam, S. (2023). Linking green intellectual capital, ambidextrous green innovation and firms green performance: Evidence from Pakistani manufacturing firms. Journal of Intellectual Capital, 24(4), 974–1001. Singh, S. K., Del, G. M., Chierici, R., & Graziano, D. (2020). Green innovation and environmental performance: The role of green transformational leadership and green human resource management. Technological Forecasting and Social Change, 150 (1), Article 119762. Wang, C. H., & Juo, W. (2021). An environmental policy of green intellectual capital: Green innovation strategy for performance sustainability. Business Strategy and the Environment, 30(7), 3241–3254. Wang, M., Li, Y., Li, J., & Wang, Z. (2021). Green process innovation, green product innovation and its economic performance improvement paths: A survey and structural model. Journal of Environmental Management, 297(21), Article 113282. Wang, Y., Su, X., Wang, H., & Zou, R. (2019). Intellectual capital and technological dynamic capability: Evidence from Chinese enterprises. Journal of Intellectual Capital, 20(4), 453–471. Wang, J., Wang, S., Wang, H., Zhang, Z., & Ru, X. (2021). Examining when and how perceived sustainability-related climate influences pro-environmental behaviors of tourism destination residents in China. Journal of Hospitality and Tourism Management, 48(3), 357–367. Wright, P. M., Mcmahan, G. C., & Mcwilliams, A. (1994). Human resources and sustained competitive advantage: A resource-based perspective. International Journal of Human Resource Management, 5(2), 301–326. Wu, J., Wu, H. C., Hsieh, C. M., & Ramkissoon, H. (2022). Face consciousness, personal norms, and environmentally responsible behavior of Chinese tourists: Evidence from a lake tourism site. Journal of Hospitality and Tourism Management, 50(1), 148–158. Yong, J. Y., Yusliza, M. Y., Ramayah, T., & Fawehinmi, O. (2019). Nexus between green intellectual capital and green human resource management. Journal of Cleaner Production, 215(10), 364–374. Yusliza, M. Y., Yong, J. Y., Tanveer, M. I., Ramayah, T., Noor Faezah, J., & Muhammad, Z. (2020). A structural model of the impact of green intellectual capital on sustainable performance. Journal of Cleaner Production, 249(8), Article 119334. Yu, J., Xie, C., & Huang, S. (2022). Effect of perceived job risk on organizational conflict in tourism organizations: Examining the roles of employee responsible behavior and employee silence. Journal of Hospitality and Tourism Management, 53(4), 21–31. Zameer, H., Wang, Y., & Yasmeen, H. (2020). Reinforcing green competitive advantage through green production, creativity and green brand image: Implications for cleaner production in China. Journal of Cleaner Production, 247(6), Article 119119. Zameer, H., Wang, Y., Yasmeen, H., & Mubarak, S. (2022). Green innovation as a mediator in the impact of business analytics and environmental orientation on green competitive advantage. Management Decision, 60(2), 488–507. Zhang, Q., & Ma, Y. (2021). The impact of environmental management on firm economic performance: The mediating effect of green innovation and the moderating effect of environmental leadership. Journal of Cleaner Production, 292(15), Article 126057. C. Xin and Y. Wang

Journal of Hospitality and Tourism Management 57 (2023) 225–235 Available online 20 October 2023 1447-6770/© 2023 The Authors. Published by Elsevier Ltd. on behalf of CAUTHE - COUNCIL FOR AUSTRALASIAN TOURISM AND HOSPITALITY EDUCATION. All rights reserved. Hotel digital capability: Dimensionality and measurement Lingling Fan a , Chaowu Xie a,* , Jiangchi Zhang a , Songshan (Sam) Huang b , Xuequn (Alex) Wang c a College of Tourism, Huaqiao University, Quanzhou, 362021, Fujian, China b Tourism and Services Marketing, School of Business and Law, Edith Cowan University, Australia c School of Business and Law, Edith Cowan University, Australia ARTICLE INFO Keywords: Digital capability Hotel Dimensionality Scale development ABSTRACT While the significance of Hotel Digital Capability (HDC) has been acknowledged in the literature, limited attention has been given to its measurement. This study endeavors to identify the dimensions of HDC and construct a reliable measurement scale. A combined approach of qualitative and quantitative methods across three studies was employed to achieve the research objectives. Study 1, grounded in interviews, delineated HDC as a multidimensional construct encompassing digital basic capability, digital integration capability, digital application capability, and digital optimization capability. Building on the four-factor model identified in Study 1, Study 2 formulated an 18-item scale with robust measurement properties. Additionally, the second-order structure, incorporating four first-order factors, received empirical support. Subsequently, Study 3 sought to validate the scale and ascertain its nomological validity. The developed HDC scale lays the groundwork for future investigations into digital capability and transformation within the hotel industry. 1. Introduction The advent of digital technology has fundamentally changed how hotels operate, ushering in a new era of value creation (Sigala, 2018). For instance, tools like business analytics have empowered hotels to glean invaluable insights and craft strategic direction for their operations. This shift has been especially pronounced since the onset of the COVID-19 pandemic, with consumers increasingly demanding digitally-enabled services like contactless interactions, self-service options, and remote work capabilities (Lau, 2020). In response, hotel managers are facing mounting pressure to seamlessly integrate digital technology into their operations to meet these evolving consumer expectations. In this challenging environment shaped by the pandemic, the pivotal role of digital capability, fueled by technological advances, has emerged as the linchpin for hotels to adapt and thrive (Lau, 2020). Thus, it becomes imperative for hotel managers to grasp the concept of Hotel Digital Capability (HDC) and understand how to cultivate this vital capacity. While existing literature has delved into the impact of digital technology in the hotel industry from various perspectives, there is a noticeable gap in understanding its implications at the business level, particularly regarding service innovation and strategic positioning (Busulwa et al., 2022). Often, studies have predominantly approached digital technology in hospitality from a technological lens, inadvertently overlooking its profound influence on business strategy and service innovation. Recognizing the fundamental role of digital technology in hotel management is crucial (Shin et al., 2019). In the realm of digital transformation, hotels require specific digital capabilities to effectively implement and leverage digital technologies (Gong et al., 2023). These capabilities involve orchestrating seamless technology integration, evaluating and deploying requisite functional systems, and aligning system feedback with present and future needs. Moreover, these digital capabilities are reshaping the value proposition and strategic conduct of companies, emerging as a pivotal source of competitive advantage (Braun & Sydow, 2019). The existing research on Hotel Digital Capability (HDC) has notable shortcomings. Firstly, there is a lack of consensus on HDC’s dimensional structure, with studies proposing varying dimensions. The literature has shown studies suggesting one, two, three, or even four dimensions (Hou & Liu, 2022; Junior & Maçada, 2020; Khin & Ho, 2018; Lenka et al., 2017). Hotels, as customer-centric ‘high-touch’ service providers, face unique challenges in effectively applying digital technologies, necessitating a tailored understanding of digital capabilities in this context (Piccoli et al., 2017). Secondly, existing research tends to overlook the dynamic nature of HDC, often focusing on static capabilities. However, the hotel industry is * Corresponding author. E-mail address: [email protected] (C. Xie). Contents lists available at ScienceDirect Journal of Hospitality and Tourism Management journal homepage: www.elsevier.com/locate/jhtm https://doi.org/10.1016/j.jhtm.2023.10.010 Received 12 June 2023; Received in revised form 12 October 2023; Accepted 14 October 2023

Journal of Hospitality and Tourism Management 57 (2023) 225–235 226 inherently dynamic, reflected in consumer value and business model shifts. Hotel digital capabilities continuously evolve to align with market changes and customer needs, emphasizing the importance of considering HDC from a dynamic capability perspective (S´ anchez-Fernandez ´ et al., 2020). Thirdly, there is a lack of a suitable measurement scale for HDC, with existing ones primarily tailored to manufacturing or internet companies. These scales may not fully capture the unique focus of the hospitality industry, which centers on customer experiences. It is crucial to address these structural barriers and develop a scale specifically designed for HDC to integrate ‘high-touch’ hotel services with high-tech needs (He et al., 2019; Heredia et al., 2022; Li et al., 2022). To address these gaps, this study aims to identify the dimensional structure of HDC and develop a rigorously validated measurement scale. This contribution will serve as the foundation for future HDC-related research. Through three studies, we employed in-depth interviews (Study 1), developed the measurement scale (Study 2), and validated the scale’s nomological validity (Study 3). The results strongly support the proposed dimensional structure of HDC and demonstrate the scale’s reliability and validity. This research provides a comprehensive understanding of HDC and a reliable tool for its measurement. 2. Literature review 2.1. The concept of digital capability The concept of digital capability encompasses four key perspectives: resource, technology, capability, and value. From a resource standpoint, it refers to a company’s digital infrastructure, platform, and data (Coreynen et al., 2020). In terms of technology, it signifies a company’s proficiency in leveraging digital tools (Yoo et al., 2012). Regarding capability, it empowers companies to effectively utilize their resources and generate value (Junior et al., 2020; Tams et al., 2014). From a value perspective, it enables organizations to sift through, analyze, and evaluate data, ultimately leading to value creation (Lenka et al., 2017). Drawing from the literature, our study frames Hotel Digital Capability (HDC) through a capability lens, viewing digital technology as the bedrock and data resources as the nucleus for hotels to drive digital transformation in customer services, business processes, and management decision-making. This, in turn, bolsters hotels’ capacity to generate value. This conceptualization of HDC acknowledges the distinctive and vital attributes of the hotel industry. It also aligns with dynamic capability theory, asserting that digital capability integrates enterprise digital assets and business resources to advance organizational interests through product, service, and management innovation (Annarelli et al., 2021). 2.2. Dimensional structure of digital capability Studies on digital capability have employed various dimensional structures. Some conceptualize it as a single dimension (Khin & Ho, 2018), while others adopt a multi-dimensional approach. For instance, Hou and Liu (2022) assessed digital capability with two dimensions: digital synergy and digital diffusion. Lenka et al. (2017) proposed a three-dimensional structure comprising intelligence, connection, and analysis. Junior et al. (2020) introduced a four-dimensional structure encompassing sensing, responsiveness, process scanning, and ecosystem connectivity. These studies offer valuable insights for defining dimensions and creating scales for Hotel Digital Capability (HDC). However, it’s crucial to acknowledge the dynamic nature of the hotel industry (Sanchez-Fern ´ andez ´ et al., 2020; Seo et al., 2021). The aforementioned studies predominantly focus on measuring the dimensional structure of digital capability from a static standpoint, which may not effectively capture the dynamic processes in hotels as they employ digital technology to enhance customer service. This highlights the necessity for developing a digital capability scale tailored specifically to the unique context of the hotel industry. 2.3. Hotel digital capability Hotel digital capability (HDC) refers to a hotel’s agile utilization of digital technology to adapt to market changes in production and business activities. It empowers hotels to attain competitive edges and sustainable growth amidst complexity and turbulence (Liu & Yang, 2021; Mandal & Dubey, 2020). Developing HDC is a dynamic and multifaceted endeavor. Merely investing in digital infrastructure yields short-term advantages, easily replicated. Hence, sustained competitive advantages stem from integrating digital technology into operations, culture, and strategy (Hua, 2020; Iranmanesh et al., 2022). HDC progression typically starts at a basic technological level and evolves into a sophisticated business-oriented level. Soh and Markus (1995) hierarchical classification theory of dynamic capabilities and the IT business value process model serve as foundational theories. Dynamic capabilities in enterprises can be categorized hierarchically, encompassing zero-order (ensuring basic survival in the market), first-order (coping with change), and second-order (adapting to long-term shifts) capabilities (Winter, 2003). HDC development mirrors this evolutionary process, advancing from handling digital technology infrastructure to integrating it with business processes. The IT business value process model elucidates how and why a company’s IT investment enhances organizational performance. It involves IT spending, IT assets, IT impact, and organizational performance, as well as IT conversion, IT usage, and IT competition processes. IT spending covers hardware and software investments, forming the digital basis capability. IT assets pertain to utilizing implemented IT for resource aggregation and capital accumulation, corresponding to the digital integration capability. This includes linking digital technology with hotel operations and consumer data collection. IT impact refers to the effects of adept IT use on an organization, representing digital application capabilities. This involves extracting and analyzing accumulated data to support business operations. Organizational performance signifies favorable outcomes from effective IT use in a competitive setting. While IT usage generates impacts, external factors may impede improved performance. In this study, organizational performance is linked to digital optimization capabilities, spotlighting how hotels leverage digital tools for enhanced operational value in enabling environments. This study posits that the development of digital capabilities in hotels (see Fig. 1) can be outlined as follows. 1) Conversion process: Hotels invest in digital technology and upgrade technical resources. Although this initial investment in digital software and hardware infrastructure doesn’t directly yield dynamic capabilities, it enhances the efficiency and effectiveness of data acquisition, forming the groundwork for building digital capability in hotels (Iranmanesh et al., 2022). 2) Use Process: Hotels employ digital resources in their business activities, integrating digital technology into organizational management. This involves utilizing digital technology to support data accumulation, integrate resource information, enable departmental resource sharing, and achieve data/system integration (Han et al., 2021). Simultaneously, by integrating digital resources, hotels extract valuable customer information through thorough analysis for effective data resource utilization (Melian-Gonz ´ alez ´ & Bulchand-Gidumal, 2016). 3) Competition Process: Hotels leverage digital technology to adapt to internal and external changes, sustaining and enhancing their competitive edge (Liu & Yang, 2021). These processes focus on transformational effects driven by digital empowerment, culminating in competitive advantages achieved through meeting user needs, refining business processes, and optimizing strategic goals. This evolutionary approach aligns with hotels’ pursuit of business and value objectives via digital empowerment. Drawing from this framework, our study conceptualizes HDC through four dimensions: basic capability, integration capability, application capability, and L. Fan et al.

Journal of Hospitality and Tourism Management 57 (2023) 225–235 227 optimization capability. 2.3.1. Digital basic capability Digital basic capability refers to an enterprise’s capacity to utilize digital technology for fundamental operations, primarily through investing in digital infrastructure. This encompasses elements like artificial intelligence, data center platforms, and the Internet of Things. Within hotels, this forms the bedrock for Hotel Digital Capability (HDC), including both software (e.g., front desk management, central reservation, customer management, revenue management systems) and hardware (e.g., construction equipment monitoring, video surveillance, security alarm devices) components (Kim et al., 2020). This digital infrastructure enables real-time collection of customer data, setting the stage for future processing and analysis. In sum, digital basic capabilities enable hotels to execute online business processes, fostering process reengineering and capability enhancement. 2.3.2. Digital integration capability Digital integration capability refers to an enterprise’s proficiency in merging digital resources built upon a solid digital infrastructure. With advanced digital infrastructure bolstered by data-driven intelligent technology, hotels can efficiently gather and synchronize data from various sources. This empowers them to offer streamlined services (e.g., online booking, contactless check-in/out), and monitor production and operational activities. It facilitates seamless integration of front-end services with back-end systems, ensuring a smooth customer experience. 2.3.3. Digital application capability This pertains to an enterprise’s ability to deploy digital technology in products, services, business activities, and management. It encompasses both customer-facing and managerial aspects. On the customer side, digital technology enables hotels to provide services such as digital marketing, online reviews, and intelligent service experiences to consumers. For instance, social media has reinforced relationships between hotels and consumers, allowing for swift identification of customer profiles and tailored service provision (Morosan & DeFranco, 2019). On the managerial side, it addresses hotel business management (e.g., human resource management, guest services), employee perceptions, acceptance of digital technology, and electronic security issues (e.g., biometric technology) (Gibbs et al., 2015; Kim et al., 2010). By leveraging digital technology, hotels can enhance business processes, operational efficiency, innovate business models, and ultimately reap economic benefits (Sahadev & Islam, 2005). 2.3.4. Digital optimization capability This refers to an enterprise’s ability to utilize digital technology to meet user needs, enhance performance, and promote sustainability. The core of this capability involves transforming the relationship between users (consumers and employees) and technology. For hotels to effectively cater to consumer needs, it’s crucial to proactively anticipate and promptly address their digital requirements. This transformation is vital in shifting consumers from passive service recipients to active cocreators of value within a technology-driven experiential setting (Han et al., 2021; Sarmah et al., 2017). Additionally, hotels should utilize digital technology to enhance service quality, deliver personalized consumer experiences, optimize workflows for frontline employees, and provide resources to match information processing requirements with capabilities (Jeong et al., 2016; Piccoli et al., 2017). Managers must enhance their capacity to transform data into valuable insights and actionable knowledge, utilizing digital technology for intelligent decision-making, efficient business management, and operations (Lamest & Brady, 2019; Melian-Gonz ´ alez ´ & Bulchand-Gidumal, 2016). To maximize overall value, hotels must comprehensively consider the interests of consumers, frontline employees, and managers in their digital optimization capability. 3. Research design Our research employs the scale development framework outlined by MacKenzie et al. (2011) to create a measurement scale for Hotel Digital Fig. 1. Conceptual framework for the evolution and development of hotel digital capability. L. Fan et al.

Journal of Hospitality and Tourism Management 57 (2023) 225–235 228 Capability (HDC). This process involves defining the concept, identifying dimensions, constructing the scale, refining it, and ultimately verifying its effectiveness. We conducted three comprehensive studies, utilizing both qualitative and quantitative analyses. 4. Study 1: the dimensional structure of HDC 4.1. Methods Study 1 utilized semi-structured interviews to discern the concept and dimensional structure of HDC, employing the process of open coding, selective coding, and theoretical coding. Data was gathered through semi-structured in-depth interviews, offering flexibility to capture the respondent’s perspective effectively (Copeland et al., 1976). The collected data was then coded using NVivo 11.0 software to extract themes and concepts. The interview guide, jointly developed by two professors and four PhD researchers, included the following key open-ended questions: What digital technologies are available at the hotel? What kind of digital experience can hotels offer consumers? What digital technologies are involved in hotel employees’ work? What digital management methods are used by hotel managers? What is the impact of digital adoption in hotels? Nineteen respondents (comprising 17 hoteliers and 2 academics with expertise in hotel digitization) participated in one-on-one semi-structured in-depth interviews (see Table A.1). These respondents met specific criteria: they should possess knowledge of how digital technology is utilized in hotel operations, understand its impact on hotel work, and be familiar with providing digital services to hotel customers. The entire interview process adhered to transparency guidelines and did not involve any proprietary information. Additionally, the interviews were approved by the research institution and the human resources department of the hotel under investigation. The average interview duration was approximately 50 min, generating transcripts exceeding 270,000 words. 4.2. Data coding and results In the initial open coding phase, two researchers independently coded the data to ensure the organic emergence of HDC-related concepts. Any disparities in coding were addressed through discussion and feedback, resulting in an agreement level exceeding 90% (Xie et al., 2022). The coded data was then compared, classified, and merged by two researchers, ultimately identifying 484 primary concepts (see Table A.2). To further ensure the reliability and validity of the coding results, the research team scrutinized the classification. In the subsequent selective coding phase, systematic analysis led to the extraction of sub-categories and core categories. The initial 484 concepts were refined, consolidated, and categorized, yielding 13 subcategories of HDC. These sub-categories were then further organized and combined to form four core categories. Moving to the theoretical coding stage, the researchers engaged in a comparative analysis of the relationships among sub-categories. This analysis culminated in the development of a conceptual model of HDC, comprising four core categories: digital basic capability, digital integration capability, digital application capability, and digital optimization capability (see Fig. 2). Digital Basic Capability pertains to hotels’ foundational operational proficiency in carrying out digital activities. It encompasses the presence of necessary hardware and software infrastructure for digital operations. Hardware includes information or intelligent equipment, while software involves information systems and networks supporting hotel business processes. Digital Integration Capability concerns hotels’ capacity to collect, transform, analyze, and manage data using digital infrastructure. It encompasses data integration (enabling business data accumulation or transmission), process integration (automating hotel business processes based on predefined parameters), and management integration (enabling system-based management and control). Fig. 2. Data structure diagram. L. Fan et al.

Journal of Hospitality and Tourism Management 57 (2023) 225–235 229 Digital Application Capability relates to hotels’ ability to apply digital technology to various facets of hotel business processes, including marketing, customer services, and backend management. It aims to establish a digital business environment with digital information at its core. This capability involves integrating technology with business, digitalizing key business activities, and developing pivotal digital business scenarios. Digital Optimization Capability refers to hotels’ ability to empower stakeholders and optimize business objectives through the utilization of data resources and digital technology. This capability centers on enhancing the performance of hotel stakeholders and fine-tuning business objectives based on the insights gleaned from data and digital tools. 5. Study 2: scale development 5.1. Measurement item generation Following the outcomes of Study 1 and relevant literature on digital capability, we initially compiled a list of 43 measurement items for HDC. We rigorously ensured content validity through multiple steps. Four doctoral and two master’s students specializing in tourism management assessed the items, refining or removing those with unclear meanings or inconsistent content, resulting in 34 retained items. Subsequently two professors and two lecturers specializing in tourism management further reviewed and revised these items for accuracy and appropriateness. Feedback from hotel employees led to additional refinements, leading to the final set of 26 items measuring four HDC dimensions (seeTable B.1. in Appendix B). 5.2. Pilot test We conducted a pilot test, administering all items using a 7-point Likert scale (1 = “Completely disagree”, 7 = “Completely agree”). Using the online survey platform Wenjuanxing (www.wjx.cn), we collected 178 valid responses. Initially, we assessed reliability, resulting in the removal of item AC5 due to a low item-to-total correlation. Cronbach’s alpha values demonstrated good internal consistency for basic capability, integration capability, application capability, and optimization capability (0.86, 0.91, 0.83, and 0.92 respectively). Next, an Exploratory factor analysis (EFA) with promax rotation was conducted. Items were evaluated based on factor loadings, communalities, and cross-loading criteria (Hair et al., 2010). While the KMO was 0.93 and Bartlett’s test was significant, some items required revision. For instance, BC6 was dropped, and others were adjusted (e.g., IC2, IC3, AC6, AC7), resulting in a final set of 24 items (see Table B.2 in Appendix B). 5.3. Exploratory factor analysis In April 2022, 14 mid-to high-end hotels in China, known for offering advanced digital services, were selected for the initial questionnaire survey. These hotels are equipped with cutting-edge digital technologies, such as delivery robots and 5G, and they are mainly located in provinces with robust digital infrastructure. The staff in these hotels are adept at using these technologies to provide personalized services. Questionnaires were distributed electronically, complying with epidemic regulations. We secured hotel support, ensuring questionnaires reached employees in various departments and positions. An attention check and assurance of no right or wrong answers were included in the questionnaire. Out of 280 distributed questionnaires, 204 valid responses were received, yielding a response rate of 72.8%. The demographic information of participants is detailed in Table 1. The data distribution was deemed normal based on skewness and kurtosis values meeting established standards (Kline, 2011). We began by assessing the reliability of the measures. The Cronbach’s alpha coefficients for the four dimensions were as follows: 0.87 for basic capacity, 0.87 for integration capacity, 0.89 for application capacity, and 0.93 for optimization capacity. These results indicate strong internal consistency and reliability across all dimensions. Next, we conducted a principal axis factoring with promax rotation. During this process, it was observed that BC1 (0.32), IC3 (0.40), IC4 (0.44), and AC7 (0.37) had communalities below 0.50, and therefore, these items were removed from further analysis. Following this, an exploratory factor analysis (EFA) was performed on the remaining 20 items. The Kaiser-Meyer-Olkin (KMO) measure, which assesses the sampling adequacy for factor analysis, was calculated to be 0.92. Additionally, the Bartlett sphericity test yielded a significant result (χ2 = 2940.48, df = 190, p < 0.001), indicating that the data was suitable for factor analysis. The Cronbach’s alpha coefficients for all factors exceeded the acceptable threshold of 0.70. Furthermore, the factor loadings of the remaining items ranged from 0.58 to 0.88, all surpassing the recommended threshold of 0.50 (see Table 2). These outcomes collectively affirm the validity of the four-factor structure we proposed. 6. Study 3: scale validation 6.1. Confirmatory factor analysis In Study 3, we conducted confirmatory factor analysis (CFA) to further validate the items, following the approach outlined by Fokkema and Greiff (2017). Data for this round was collected through two methods: electronic questionnaires, using a similar approach as in Study 2, and paper questionnaires distributed and collected at the hotels. To ensure a representative sample, we selected 34 mid-to-high-end hotels in the provinces of Jiangxi, Anhui, Fujian, Zhejiang, Jiangsu, and Guangdong in China, known for their high levels of digitization. Data collection took place from May to July 2022. Out of 680 distributed questionnaires, we received 491 valid responses, yielding a valid response rate of 72.2%. Participants’ demographic information is presented in Table 1. To assess the validity and reliability of the scale, we conducted the CFA. The results indicated reasonably good model-fit indices after removing OC5 and OC6 due to loadings below 0.5: χ2 = 245.29, df = 129, χ2 /df = 1.90, SRMR = 0.03, RMSEA = 0.04, NFI = 0.94, RFI = 0.93, IFI = 0.97, TLI = 0.96, CFI = 0.97, GFI = 0.95, AGFI = 0.93, PNFI = 0.79. The composite reliabilities for all dimensions exceeded 0.80. Although the Average Variance Extracted (AVE) for the application capability dimension fell below the threshold of 0.50, this was deemed acceptable due to the high composite reliability (CR) value of the dimensions (Gottschalk et al., 2022). Additionally, Cronbach’s alphas for all dimensions exceeded 0.70, and the standard factor loadings of all items ranged from 0.61 to 0.81 (see Table 3). In summary, the four-dimensional structure of HDC received robust support. 6.2. Convergent and discriminant validity To assess the discriminant validity of the scale, we employed both the Fornell-Larcker criterion and the heterotrait-monotrait ratio (HTMT) (Grace et al., 2020). The results indicated that the average variance extracted (AVE) values for the four factors were 0.53, 0.52, 0.46, and 0.53, respectively (Table 3). While the AVE of the application capability was slightly below 0.50, it was still considered acceptable, in line with the criteria outlined by Gottschalk et al. (2022). As presented in Table 4, the square root of AVE for each dimension was lower than the correlations between that dimension and the others. Additionally, the correlations between dimensions ranged from 0.50 to 0.66, all below the threshold of 0.85. Moreover, the HTMT results (Table 5) demonstrated that the HTMT values between any two variables were below the established threshold of 0.9 (Henseler et al., 2015). These results strongly support the discriminant validity of the scale. L. Fan et al.