Journal of Hospitality and Tourism Management

Journal of Hospitality and Tourism Management 57 (2023) 61–71 68 tourists were more willing to embark on a journey that is congruent with their character strengths. While prior literature mostly focused on developing character strengths of individuals in non tourism settings, this study shows tourism offers a unique opportunity for people to cultivate their strengths. More than two-thirds of MMEs were associated with character strengths of participants. Most of the study participants indicated willingness to develop their strengths even though these may not be their signature strengths. The dominance of moderate strengths over signature strenghts might be due to two factors. Firstly, the participants might not be familiar with the character strengths terminology. For example, “curiosity” might be easily confused with “love of learning”. Secondly, most of the journeys reported were group activities, which might not resonate with the core signature strengths of the participant. Curiosity (openness to new experiences) accounted for one of the most frequently used strengths in this study. The other four most used strengths reported in this study were: the appreciation of beauty and excellence, gratitude, teamwork and perseverance. Literature on strengths (Martínez-Martí et al., 2016) recognised three aspects of the appreciation of beauty and excellence strength: beauty, moral excellence, non-moral excellence. Beauty is a subjective experience that involves perceiving and appreciating what is beautiful and excellent in the physical and social worlds. Moral excellence, on the other hand, is the ability to perceive and appreciate moral goodness or virtue in the world. Non-moral excellence refers to the ability to perceive and appreciate talent or skills in the physical and social worlds. Probably, nudging tourists to participate in cultural tourism which entails moral excellence (e.g., visiting the Anne Frank House) as well as non-moral excellence (e.g., visiting art museums) may increase the appeal of their future travel experiences. Tourists who have a stronger ability to appreciate beauty and excellence tend to be more empathic and altruistic (Martínez-Martí et al., 2016), which in turn enhances their sense of gratitude and teamwork (the other strengths identified in this study). Developing gratitude can help release stress and alleviate depression (Wood et al., 2009). As outlined in other tourism studies (Glover & Filep, 2015), gratitude inducing activities are related to novel and unique experiences (e.g., waiting for a sunrise), and experiences of trust (e.g., in hospitality settings). Teamwork accounted for the fourth most used strength in this study, probably because tourism often involves travel companions and other social actors (e.g. a tour guide). The participants reported many instances of experiences of Table 5 List of the values gained. No. Value gained P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 Freq.a Pct.b 1 Knowledge 1 1 1 2 1 1 1 2 1 1 12 23.5 2 Friendship 1 – 1 2 1 2 1 1 1 1 11 21.6 3 Personal growth 1 – – 2 1 1 3 1 1 1 11 21.6 4 Harmony 1 3 1 – 1 2 – – 1 1 10 19.6 5 Meaning and purpose in life 1 – – 1 – 2 1 2 1 – 8 15.7 6 Excitement – – 3 – – 1 – – 1 2 7 13.7 7 Better world and society 1 1 – – 1 – 1 – 1 1 6 11.8 8 Courage – – – – – – 1 – 1 2 4 7.8 9 Wisdom 1 1 – 1 – 1 – – – – 4 7.8 10 Autonomy 1 1 – – – – – – – 1 3 5.9 11 Kinship – 1 – 1 – – – 1 – – 3 5.9 12 Sense of mastery – – – – 1 – – – 1 – 2 3.9 13 Health – – 2 – – – – – – – 2 3.9 14 Self-acceptance 1 – – – – – – – 1 – 2 3.9 15 Social recognition – – – 1 – – – – – – 1 2 16 Prosperity – – – – – – – – – – 0 0 17 Justice – – – – – – – – – – 0 0 a Each MME entry can attribute a maximum of two values. b Percentage is calculated based on total number of entry (N = 51). Fig. 4. The participants’ responses regarding their attitudes towards future trip planning. Notes: 1: Values gained (M = 4.93, SD = 0.26, SEM = 0.02, n = 131), strengths used (M = 4.74, SD = 0.45, SEM = 0.04, n = 107), travel with the same travel mate(s) (M = 4.06, SD = 1.14, SEM = 0.10, n = 131), do the same activity (M = 4.04, SD = 1.33, SEM = 0.12, n = 51), and visit the same place (M = 3.39, SD = 1.5, SEM = 0.13, n = 51). 2: Error bars represent standard errors across the participants’ responses. C.K.B. Wan et al.

Journal of Hospitality and Tourism Management 57 (2023) 61–71 69 co-creation over their journeys. Some of these experiences were unexpected (e.g., encountered by accident), while others required collective efforts. Lastly, the strength of perseverance was identified in physical activities (e.g., hiking) in this study. Perseverance is strongly associated with grit and prosociality (Disabato et al., 2018), especially in the context of pursuing intrinsic goals and autotelic activities. Tourism literature (Zhao & Agyeiwaah, 2023) reveals that perseverance is conducive to transformative tourism experiences, especially when overcoming emotional, physical and mental challenges. The data collection process itself deserves some further discussion. The design of the journaling platform exemplified principles of reflective informatics (Baumer, 2015), such as breaking down important moments in life by asking participants to provide images and texts related to their MMEs. This process allowed participants to scutinise the travel experiences from different perspectives. Asking participants to disclose their internal psychological factors provided a moment of inquiry that allowed reflection and introspection to take place. Features were created to facilitate expressions of these implicit dimensions by allowing participants to elaborate from a list of provided items. Nevertheless, the inquiry process itself was found to be challenging amongst some participants because they seldom previously reflected on their travel experiences in such great depth. The reflection section of the platform capitalised on the implicit dimensions of the MMEs by providing a dashboard that charted top strengths used. Overall, the study showed that participants were willing to plan their future journeys based on their strengths. 5.2. Theoretical implications This study showed that tourists would gain a deeper understanding of their MMEs when connecting their experiences with their character strengths and thereby drives future behavioural intentions. Reminiscing allows tourists to recollect and re-live important episodes of their journeys (Tung & Ritchie, 2011; Yan & Halpenny, 2021). Recent studies (Miyakawa et al., 2022; Teoh et al., 2023) found reminiscing on one’s travel journey can help tourists build knowledge about the locals and places they visited and lead to transformative experience. This study provides new insights into reminiscence of tourist experiences by understanding their character strengths. This helps build new knowledge and inspires tourists to strive towards self-development in their future trips. By making the implicit psychological dimensions of MMEs explicit, tourists are more likely to choose future journeys to be congruent with their character strengths and values rather than visiting the same place. A new conceptual model is therefore proposed based on this study (Fig. 5) which links post-trip reminiscence of MMEs with the benefits of strengths-based reminiscing and the subsequent behavioural intentions for future trips. 5.3. Practical implications The results contribute to the design of smart tourism platforms and informatics systems (e.g., recommender system). For instance, a tourist may be able to search for a destination not only based on geographical locations but based on their character strengths. Character strengths can be integrated into tourism experience design and delivery by tour guides. For instance, a museum might consider integrating several guided tours that correspond to the travellers’ different character strengths. The study also has some practical implications related to the use of the journaling platform. The journaling platform helps users organise their digital footprints and document moments that are valuable and significant to them. This practical narrative process guides users to find connections between explicit tourism activities and implicit psychological dimensions. Making the implicit explicit helps user to gain deeper insights into their travel experiences. Users can apply the filter, use the dashboard, and employ insight cards to find behavioural and mental patterns of past journeys. The process may facilitate transformative experiences (Zhao & Agyeiwaah, 2023) inspiring users to develop themselves and pursue their personal future travel goals. 6. Conclusions, limitations, future research Meaningful and memorable travel experience research is gaining traction in tourism research (Camara ˆ et al., 2023; Zhao & Agyeiwaah, 2023). However, designing such experiences is challenging because every tourist has its own values and motives for self-development (Sheldon, 2020). The experience may not always be pleasant and enjoyable. The strengths-based interactive journaling platform presented in this study facilitates tourists to narrate memorable and meaningful events and, by so doing, supports them to build a greater awareness of their implicit values. The platform connects travel events with tourists’ character strengths. The study contributes to positive Fig. 5. A conceptual framework of reminiscing about memorable and meaningful tourism experiences with character strengths (Adapted from Bryant & Veroff, 2007; Niemiec, 2017). C.K.B. Wan et al.

Journal of Hospitality and Tourism Management 57 (2023) 61–71 70 tourism research (Filep et al., 2016) using strengths-based approaches and guided journaling to facilitate self-discovery and reflections. The results inform the future use of positive psychology interventions and technology-mediated reflections in tourism experiences. Future tourism researchers could explore how to support meaningful tourism activities in the planning and on-site stages of the journey that incorporate one’s psychological dimensions. The study has a few key limitations. First, the MMEs provided by the participants were based on their past journeys. Future studies can invite tourists to create MME entries in-situ, during their actual trips so that more vivid emotions, memories, and opinions can be captured. Second, our modest budget made the journaling platform limited to photos and text entries. Future studies may add videos and animations. Third, future research can examine the well-being benefits derived from journaling in an explicit manner. Future research can opt for longitudinal studies so that the well-being changes can be observed over a long period. Fourth, further in-depth qualitative research is needed to validate our initial conclusions in this study, especially the results of the thematic analysis which was based on short online interviews. Lastly, increasing the sample size in future studies could help future researchers understand the complexity of MMEs more thoroughly as MMEs are typically very diverse in nature. More empirical studies are needed to understand the connections between character strengths and tourism activities. Lastly, the study was conducted during the COVID-19 period when travel restrictions were imposed on travellers. The entries were created based on participants’ past journeys in the pre-pandemic period. The platform should be deployed to collect new data in the post pandemic period. Future research will allow for further in-depth explorations of the complexities of memorable and meaningful tourism experiences. Author statement Bruce Wan: Conceptualization, Methodology, Investigation, Data Curation, Writing – Original Draft, Visualization. Cees de Bont: Supervision, Writing – Review & Editing. Paul Hekkert: Supervision. Sebastian Filep: Writing – Review & Editing Kenny Chow: Supervision, Writing – Review & Editing. Declaration of competing interest The authors have no conflicts of interest to declare. All co-authors have seen and agree with the contents of the manuscript, and there is no financial interest to report. We certify that the submission is original work and is not under review at any other publications. Funding Acknowledgements This work was partially supported by the research office at Hong Kong Polytechnic University [grant number: G-YBTW], and the General Research Fund at the Research Grants Council Hong Kong [grant number:15500019]. 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Journal of Hospitality and Tourism Management 57 (2023) 97–101 Available online 16 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. Leveraging IPA gap scores to predict intent to travel B. Bynum Boley a,* , Evan Jordan b a Parks, Recreation, and Tourism Management, Warnell School of Forestry and Natural Resources, 180 East Green Street, University of Georgia, Athens, GA, 30602- 2152, USA b Department of Recreation, Parks, and Tourism Studies, School of Public Health, Indiana University, 1025 E. 7th Street, Suite 111, Bloomington, IN, 47405, USA ARTICLE INFO Keywords: Importance performance analysis Gap scores Destination competitiveness Destination choice Expectancy disconfirmation paradigm ABSTRACT While the tourism literature has extended Importance Performance Analysis (IPA) in many ways, there has been little use of the gap scores associated with the differences between a destination’s perceived performance on salient destination-level attributes and the importance tourists place on these attributes to see how these positive or negative disconfirmations influence intent to travel. With this gap in mind, we walk readers through how gaps scores associated with IPA can be calculated and subsequently used as independent variables within multiple regression analyses to identify destination-level attributes that influence intent to travel. 21 destination-level attributes were administered to 1653 international travelers from each of the U.S.’ top five markets. Results revealed the gap scores associated with safety, price, national parks, food, scenery, and transportation were significant predictors of intent to travel demonstrating the value of leveraging IPA scores so that DMOs can better spend their marketing dollars on attributes that are shown to drive visitation rather than just focusing on the managerial prescriptions of “Keep Up the Good Work” or “Concentrate Here.” 1. Introduction Global competition to attract tourists is fierce and destination marketing organizations (DMOs) are increasingly looking for new ways to drive visitation. In this research note, we propose that destinations can increase their competitiveness by extending the age-old tool of Importance Performance Analysis (IPA) by calculating gap scores associated with the differences between a destination’s perceived performance on salient destination-level attributes and the importance tourists place on these attributes, and subsequently, using these positive or negative disconfirmations as independent variables in multiple regression equations to see which ones influence intent to travel. IPA was first designed by Martilla and James (1977) as a tool to help firms such as car dealerships identify the importance of attributes associated with purchasing cars and how well car dealerships were performing on these same attributes. By asking customers to rate both importance and performance on the same five-point scale, Martilla and James (1977) were able to graph attributes into one of four managerially relevant categories including “Keep Up The Good Work,” “Concentrate Here,” “Potential Overkill,” and “Low Priority.” The clear managerial implications associated with IPA have resulted in IPA being one of the most ubiquitous research tools within the hospitality and tourism industry to help destinations and firms identify where they are doing well and what they need to concentrate on to satisfy customers (Boley et al., 2017; Chen, Murphy, & Knecht, 2016; Lai & Hitchcock, 2015; Taplin, 2012; Ye et al., 2016). While the hospitality and tourism literature has extended IPA in many ways such as revising where one should place the crosshairs (Oh, 2001) and suggesting variations such as Impact Range Satisfaction Analysis, Impact Asymmetry Analysis, and Importance Performance Competitor Analysis (Albayrak et al., 2018; Karimi & Boley, 2022, pp. 1–25), there has been little use of gap scores associated with the differences between perceived performance and importance perceptions to see how these positive and negative disconfirmations influence intent to travel. These gap scores are measurements of how well destinations within one’s destination selection set perform on salient destination competitiveness attributes. For example, an ecotourist planning a vacation may be scanning different destinations for the important attributes of national parks, price, unique culture, and something social media worthy. In this example, destinations that are perceived to perform better on these important attributes (i.e., positive disconfirmations) would be more likely to be chosen as the final destination than those that underperform on those important attributes. With this gap in mind, this research note walks readers through how * Corresponding author. E-mail addresses: [email protected] (B.B. Boley), [email protected] (E. Jordan). 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.2023.09.006 Received 23 May 2023; Received in revised form 2 August 2023; Accepted 10 September 2023

Journal of Hospitality and Tourism Management 57 (2023) 97–101 98 gap scores associated with IPA can be calculated and subsequently used as independent variables within multiple regression analyses to identify destination attributes that influence intent to travel. The theoretical backing for the use of IPA gap scores comes from Oliver’s (1980) expectancy disconfirmation which states satisfaction is the result of performance exceeding expectations. While ‘importance’ is not synonymous with ‘expectations’ and ‘performance’ in this case is ‘perceived performance’ of the destination rather than actual performance, the theoretical rationale holds as these concepts are similar. Essentially, travelers scan their consideration set to see how different destinations perform across a range of important attributes of choice and choose destinations that perform well on the functional and symbolic attributes that are important to them (Boley & Woosnam, 2021). Thus, Oliver’s (1980) expectancy disconfirmation logic can be extended to suggest that if one perceives the performance of a destination attribute such as ‘friendly residents’ as being above the level of importance they place on that attribute, it is implied that there would be a positive disconfirmation for that attribute and thus, one would be more likely to visit that destination. However, if one perceives a destination attribute such as ‘price’ as underperforming in relation to its importance, Oliver’s (1980) expectancy disconfirmation paradigm would suggest that this negative disconfirmation would turn one off from traveling to that destination. While others have calculated these gap scores (P–I) associated with IPA (Tseng, 2020), there has been little use of these gap scores as predictors of intent to travel. Using gap scores as independent variables extends IPA beyond a mere visual depiction of where destinations are doing well or where they need to concentrate. Gap scores can identify which attributes are influencing tourism behavior providing DMOs with an extra layer of information that the traditional IPA quadrants lack. In this research note, we analyze data collected from individuals living in the United States of America’s (U.S.) top five international travel markets including how they rate the importance of 21 attributes of the travel experience and how they perceive the U.S. performs on those same 21 attributes. Having both measures of importance and performance provide the opportunity to calculate a gap score which is then used in a multiple regression equation to see how positive and negative disconfirmations with these attributes drive intent to visit the United States. 2. Methods The IPA consisted of 21 destination-level attributes chosen from a combination of the destination competitiveness literature (Chen, Lai, et al., 2016; Enright & Newton, 2004; Lee & Lee, 2009; Mustafa et al., 2020) and the research team’s expertise. Importance questions were Fig. 1. IPA from overall sample’s perceptions of the importance of 21 destination level attributes and the U.S.‘s performance on those attributes. Table 1 Mean importance and performance scores between overall sample and top 5 U.S. markets. Label Site Attribute Total(n = 1653) Canada(n = 316) China(n = 320) Japan(n = 320) Mexico(n = 349) U.K.(n = 348) Ia Pb P–Ic I P P–I I P P–I I P P–I I P P–I I P P–I A Safety 4.58 3.49 − 1.09 4.45 3.32 − 1.13 4.68 3.35 − 1.33 4.62 3.00 − 1.62 4.69 4.01 − 0.68 4.45 3.69 − 0.76 B Shopping opportunities 3.77 4.09 0.32 3.43 4.01 0.58 3.96 4.08 0.12 3.80 3.85 0.05 4.05 4.28 0.23 3.60 4.20 0.60 C Nightlife & entertainment 3.62 3.98 0.36 3.33 3.85 0.52 3.78 3.97 0.19 3.33 3.87 0.54 3.94 4.12 0.18 3.68 4.04 0.36 D National Parks 3.87 4.08 0.21 3.69 4.03 0.34 3.98 4.12 0.14 3.57 3.93 0.36 4.17 4.24 0.07 3.92 4.08 0.16 E Notable history 3.98 3.80 − 0.18 3.84 3.88 0.04 4.16 3.72 − 0.44 3.82 3.53 − 0.29 4.20 4.01 − 0.19 3.89 3.82 − 0.07 F Material for social media posts 3.28 3.83 0.55 2.90 3.69 0.79 3.66 3.73 0.07 2.83 3.69 0.86 3.82 4.09 0.27 3.16 3.92 0.76 G Price 4.04 3.52 − 0.52 4.17 3.47 − 0.70 3.68 3.55 − 0.13 4.14 3.16 − 0.98 4.15 3.84 − 0.31 4.06 3.57 − 0.49 H Interesting small towns/rural countryside 3.89 3.60 − 0.29 3.92 3.64 − 0.28 4.07 3.58 − 0.49 3.50 3.32 − 0.18 3.95 3.73 − 0.22 4.01 3.70 − 0.31 I Friendly people 4.20 3.51 − 0.69 4.18 3.43 − 0.75 4.29 3.47 − 0.82 4.00 3.29 − 0.71 4.32 3.57 − 0.75 4.21 3.76 − 0.45 J Quality of accommodations 4.34 3.93 − 0.41 4.30 3.88 − 0.42 4.40 3.96 − 0.44 4.31 3.64 − 0.67 4.43 4.10 − 0.33 4.28 4.03 − 0.25 K Quality food 4.42 3.79 − 0.63 4.36 3.87 − 0.49 4.36 3.83 − 0.53 4.48 3.36 − 1.12 4.48 3.94 − 0.54 4.42 3.93 − 0.49 L Outstanding scenery 4.38 4.02 − 0.36 4.29 3.89 − 0.40 4.47 4.05 − 0.42 4.43 3.83 − 0.60 4.48 4.19 − 0.29 4.22 4.11 − 0.11 M Inexpensive travel to the country 3.89 3.36 − 0.53 3.91 3.47 − 0.44 3.80 3.41 − 0.39 4.09 3.02 − 1.07 3.85 3.50 − 0.35 3.78 3.38 − 0.40 N Inexpensive travel within the country 3.84 3.37 − 0.47 3.91 3.44 − 0.47 3.71 3.38 − 0.33 4.00 3.05 − 0.95 3.81 3.46 − 0.35 3.79 3.50 − 0.29 O Availability of pre-trip information 4.19 3.99 − 0.20 4.09 3.90 − 0.19 4.06 3.84 − 0.22 4.27 3.96 − 0.31 4.42 4.14 − 0.28 4.09 4.07 − 0.02 P Availability of in-country information 4.20 3.99 − 0.21 4.09 3.96 − 0.13 4.16 3.90 − 0.26 4.20 3.85 − 0.35 4.44 4.15 − 0.29 4.09 4.06 − 0.03 Q Transportation infrastructure 4.22 3.96 − 0.26 4.01 3.89 − 0.12 4.31 3.92 − 0.39 4.30 3.72 − 0.58 4.38 4.28 − 0.10 4.10 3.98 − 0.12 R Sporting events 3.23 3.89 0.66 3.11 3.94 0.83 3.42 3.87 0.45 2.83 3.70 0.87 3.56 4.03 0.47 3.23 3.90 0.67 S Wineries 3.38 3.62 0.24 3.25 3.72 0.47 3.56 3.50 − 0.06 2.91 3.23 0.32 3.68 3.84 0.16 3.44 3.78 0.34 T Breweries 3.31 3.60 0.29 3.21 3.69 0.48 3.42 3.54 0.12 2.83 3.23 0.40 3.67 3.81 0.14 3.36 3.70 0.34 U Cosmopolitan cities 3.89 4.11 0.22 3.62 3.91 0.29 4.04 4.11 0.07 3.74 4.14 0.40 4.17 4.27 0.10 3.82 4.11 0.29 a Importace was measured on a 1–5 Likert scale with 1 representing “Not at All Important” and 5 representing “Extremely Important”. b Performance was measured on a 1–5 Likert scale with 1 representing “Very Poor” and 5 representing “Excellent”. c P–I is the gap score calculated by subtracting importance from perceived performance of the USA on that attribute. B.B. Boley and E. Jordan

Journal of Hospitality and Tourism Management 57 (2023) 97–101 99 asked as “When you consider travel destinations, how important are the following attributes?” and performance questions were asked as “Based on your image of the USA as a travel destination, how does it perform on the following attributes?” Qualtrics was hired to acquire panels of frequent international travelers from each of the U.S.’ top five markets (U.K., Canada, Mexico, Japan, and China). To be included in the sample, respondents had to have traveled internationally within the last two years and make a combined annual household income of US$50,000 since these thresholds have been shown to help ensure the sample has the financial means and interest to travel internationally (Boley & Woosnam, 2021; Beall et al., 2021). Combined, these markets represent 78% of international tourism arrivals to the U.S. before the pandemic (U. S, Travel, 2020). Overall, 1653 respondents completed the survey with country-level samples ranging from 316 to 349 (Canada = 316; China = 320; Japan = 320; Mexico = 349; U.K. = 348). Intent to visit was broken down into three separate time periods to account for the possibility of the COVID-19 pandemic preventing people from traveling as the data was collected in June of 2020. Each time period was measured with a single question stating “How likely are you to travel to the U.S. within the next …. (12 months, 3 years, or 5 years). Each of the constructs was translated from English into the language of the country (e.g., Spanish, Chinese, and Japanese) following Malhotra et al., 1996 guidelines of using native speakers to ensure functional and conceptual equivalence. Gap scores were calculated by subtracting the mean importance scores on a 1–5 Likert scale from the mean performance scores on a 1–5 Likert Scale (Performance-Importance) for each of the 21 destination-level attributes. Gap scores were saved as new variables and included as independent variables in three multiple regressions to predict intent to visit the U.S. across three-time horizons (12 months, 3 years or 5 years). 3. Results The traditional IPA graphs show many similarities in the U.S.‘s competitive position amongst its top markets (Fig. 1, Tables 1 and 2). The attributes of E) Notable History, J) Quality Accommodations, K) Quality Food), L) Outstanding Scenery, O/P) the Availability of Information, and Q) Transportation Infrastructure were generally deemed as areas to “Keep up the Good Work.” Areas to “Concentrate On” were A) Safety, G) Price, and J) Friendly People. Attributes that fell into the “Low Priority” category were H) Interesting Small Towns, M/N) expense of travel to and within the U.S.A., and the U.S.A.‘s S) Wineries and T) Breweries. Areas where the U.S.A. was deemed at overperforming relative to importance were B) Shopping Opportunities, C) Nightlife, D) National Parks, F) Material for social media, and R) Sporting Events. The traditional use of IPA would stop here and provide managerial recommendations based on attribute quadrant placement. However, this research note seeks to highlight the value of leveraging the gap scores associated with IPA to see how positive and negative disconfirmations with attributes drive intent to travel. The multiple regression analyses provided in Table 3 revealed the gap score associated with safety was the best predictor of intent to travel across all three time horizons and market segments cementing the point that perceptions of safety are paramount to travelers’ intent to travel. Following safety, price was the second-best predictor of intent to travel. This was followed by national parks, food, scenery, and transportation. While Table 3 provides many interesting results that could be mentioned, a couple of interesting findings at the country level include U.K. travelers being more influenced to travel in years 3 and 5 by U.S. national parks and Chinese residents being more influenced to travel by the positive gap score associate with the U.S. cosmopolitan cities. 4. Discussion This research note focuses on the value of pairing IPA gap scores with traditional IPA graphs to add an extra layer of interpretation for marketers seeking to improve their destination’s image among their top target markets. An example of the extra value of including IPA gap scores can be seen in the attribute “Friendly People”. “Friendly People” landed in the “Concentrate Here” quadrant but was not a significant Table 2 Attribute quadrant placement for overall sample as well as each market segment. Label Site Attribute Overall Canada(n = 316) China(n = 320) Japan(n = 320) Mexico(n = 349) U.K.(n = 348) Agreement Between Countries A Safety Q2: Concentrate Here Q2: Q2: Q2: Q1: Q2: 4/5 B Shopping opportunities Q4: Possible Overkill Q4: Q4: Q4: Q4: Q4: 5/5 C Nightlife & entertainment Q4: Possible Overkill Q4: Q4: Q4: Q4: Q4: 5/5 D National Parks Q4: Possible Overkill Q4: Q4: Q4: Q1: Q1: 3/5 E Notable history Q1: Keep up the Good Work Q1: Q2: Q2: Q1: Q2: 3/5 F Material for social media posts Q4: Possible Overkill Q3: Q3: Q4: Q4: Q4: 3/5 G Price Q2: Concentrate Here Q2: Q3: Q2: Q2: Q2: 4/5 H Interesting small towns/rural countryside Q3: Low Priority Q2: Q2: Q3: Q3: Q2: 3/5 I Friendly people Q2: Concentrate Here Q2: Q2: Q2: Q2: Q2: 5/5 J Quality of accommodations Q1: Keep up the Good Work Q1: Q1: Q1: Q1: Q1: 5/5 K Quality food Q1: Keep up the Good Work Q1: Q1: Q2: Q2: Q1: 3/5 L Outstanding scenery Q1: Keep up the Good Work Q1: Q1: Q1: Q1: Q1: 5/5 M Inexpensive travel to the country Q3: Low Priority Q2: Q3: Q2: Q3: Q3: 3/5 N Inexpensive travel within the country Q3: Low Priority Q2: Q3: Q2: Q3: Q3: 3/5 O Availability of pre-trip information Q1: Keep up the Good Work Q1: Q1: Q1: Q1: Q1: 5/5 P Availability of in-country information Q1: Keep up the Good Work Q1: Q1: Q1: Q1: Q1: 5/5 Q Transportation infrastructure Q1: Keep up the Good Work Q1: Q1: Q1: Q1: Q1: 5/5 R Sporting events Q4: Possible Overkill Q4: Q4: Q4: Q4: Q4: 5/5 S Wineries Q3: Low Priority Q3: Q3: Q3: Q3: Q3: 5/5 T Breweries Q3: Low Priority Q3: Q3: Q3: Q3: Q3: 5/5 U Cosmopolitan cities Q4: Possible Overkill Q4: Q1: Q4: Q1: Q4: 3/5 B.B. Boley and E. Jordan

10Table 3 Regression of intent to travel to the U.S. using gap scores from the IPAs. Overall (N = 1653) Canadab (N = 316) China (N = 320) Japan (N = 320) Mexico (N = 349) U.K. (N = 348) YR 1 YR 3 YR 5 YR 1 YR 3 YR 1 YR 3 YR 5 YR 1 YR 3 YR 5 YR 1 YR 3 YR 5 YR 1 YR 3 YR 5 R2 = .27 R2 = .16 R2 = .17 R2 = .17 R2 = .12 R2 = .40 R2 = .31 R2 = .35 R2 = .21 R2 = .17 R2 = .14 R2 = .13 R2 = .07 R2 = .05 R2 = .37 R2 = .22 R2 = .20 Betaa Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta A GAP safety 0.27** 0.16** 0.12** .286** .080 .215** .073 .010 .248** .167* .096 .119 − .005 − .033 .237** .203** .136* B GAP shopping opportunities − 0.03 0.05 0.07* .000 .091 − .028 .116* .057 − .022 − .098 − .071 − .035 − .060 − .042 − .202** − .051 .064 C GAP nightlife − 0.05 − 0.05 − 0.04 .015 .006 − .028 − .047 .029 .006 .045 .031 − .064 − .024 .042 − .048 − .066 − .053 D GAP National parks − 0.02 0.07** 0.08** − .143 .018 .005 .048 .152* .056 .092 .074 .018 .026 − .036 .047 .188* .196* E GAP history 0.03 0.03 − 0.02 .092 .133 .074 .086 .083 − .113 − .094 − .041 − .008 .014 − .007 .053 .019 .017 F GAP material for social media − 0.11** − 0.06* − 0.07* − .124 − .042 − .008 − .012 − .015 − .056 − .001 − .020 − .015 .022 .044 − .157* − .089 .013 G GAP price 0.11** 0.07** 0.07* .207* .121 .084 .078 .033 .101 .088 .053 .096 .037 − .037 .078 − .036 − .030 H GAP small towns 0.00 − 0.04 − 0.06* .053 .057 .020 − .025 − .065 − .042 − .042 − .046 .012 − .019 − .026 .018 − .020 − .008 I GAP friendly people 0.04 − 0.02 − 0.03 .110 .081 .276** .233** .121 .006 .037 .003 .030 − .036 − .049 .061 − .025 .098 JGAPaccommodations004004001−004−011−002−033−070024−003010084144*090062045−025B.B. Boley and E. Jordan

Journal of Hospitality and Tourism Management 57 (2023) 97–101 00 J GAP accommodations 0.04 0.04 0.01 − .004 − .011 − .002 − .033 − .070 .024 − .003 .010 .084 .144 .090 .062 .045 − .025 K GAP food 0.04 0.06* 0.10** .067 .064 .099 .079 .115* − .030 .056 .059 − .084 − .052 .003 .076 − .011 .086 L GAP scenery 0.06* 0.05* 0.07** .024 − .018 .043 .073 .055 .037 .016 .063 .109 .056 .045 .038 .070 .047 M GAP inexpensive travel to country 0.06* 0.07* 0.07 − .140 − .135 .122* .034 .017 .072 .042 .045 .008 .103 − .044 .081 .073 .052 N GAP inexpensive travel within country 0.01 0.05 0.10** − .116 − .032 − .062 .015 .035 .030 .090 .120 .112 − .002 .173* .038 .175* .153* O GAP pre trip information 0.01 0.01 0.06 − .108 − .055 .076 .009 .162* − .014 .039 .072 .014 .079 .011 .076 − .031 .028 P GAP in country information 0.00 0.01 0.01 .034 − .005 .052 .019 − .012 .035 .038 .004 .033 − .082 .062 .016 .089 .012 Q GAP transportation infrastructure 0.06* 0.07** 0.03 .082 .121 − .070 − .021 .051 .098 .071 .067 .056 .069 − .042 − .025 .034 − .097 R GAP sporting events − 0.06* − 0.04 − 0.02 .056 − .034 − .100 − .030 .014 − .177* − .101 − .056 .049 .134* .079 − .097 − .095 − .062 S GAP wineries 0.02 0.01 0.02 − .109 − .126 .018 .043 .104 − .005 − .042 − .093 .071 − .002 .054 .022 .080 .016 T GAP breweries − 0.07* − 0.03 − 0.04 − .085 − .013 − .046 .031 − .035 − .016 − .008 .021 − .105 − .060 − .121 .019 .066 .089 U GAP cosmopolitan cities − 0.05 0.00 0.02 .022 .020 .018 .168* .170* − .063 .014 .038 − .058 − .065 − .033 − .103 − .030 − .010 * Denotes significance at the 0.05 level. ** Denotes significance at the 0.001 level. a Standardized regression coefficients. b Canadians were not asked about intent to visit in year 5.

Journal of Hospitality and Tourism Management 57 (2023) 97–101 101 predictor of intent to travel for the overall sample. This would imply that managers should take not only quadrant placement into account when making decisions but also the gap scores and how these gap scores influence intent to travel so that they do not waste resources on attributes that do not drive visitation. On the flip side, “Transportation Infrastructure” was located in the “Keep Up the Good Work” quadrant suggesting managers do not need to worry about it. However, its gap score was found to be a significant driver of intent to visit, thus, warranting attention for destination marketers. Based on this finding, marketers may want to highlight the U.S. excellent transportation network to help convince certain markets to visit. Results varied substantially by target market which shows the practical value of pairing IPA with market segmentation. For example, the Chinese market’s intention to visit in year 5 was significantly influenced by “Food” and “Cosmopolitan Cites” indicating that they might be more interested in gastronomy tourism while other markets such as the U.K. were more influenced by the U.S.’ national parks indicating that they be more interested in ecotourism. This shows the utility of using IPA gap scores to better understand target markets and provide them with different promotional materials based on the destination level attributes that are most likely to influence their intent to travel. More implications could be drawn from country-level comparisons, but the point is to highlight the value of calculating gap scores with IPA and including them within regression models so that DMOs have an extra layer of information for making marketing decisions. Essentially, when marketers just use traditional IPAs, they are leaving valuable information on the table that could help them improve their marketing material. While including IPA gap scores shows some promise to DMOs, there are certain limitations that need to be mentioned. First, the data was collected during the height of the pandemic, and this could have influenced people’s intent to visit the U.S. Another limitation is asking travelers to evaluate a destination as big as the U.S. While many international travelers think of destinations at the country level, the U.S. is very large, and it may be worth applying the same methods at the state level or in regards to a smaller destination that potential tourists can more easily evaluate. A last limitation worth mentioning is the potential multicollinearity among destination attributes that could suppress the regression coefficients of other attributes. Future use of IPA gap scores with regression models may want to factor analyses attributes to consolidate similar attributes into like categories before including them in the model. In conclusion, with the ubiquitous nature of IPA within the tourism literature, this research note sought to demonstrate the value of leveraging IPA scores so that DMOs can better spend their marketing dollars on attributes that are shown to drive visitation rather than just focusing on the managerial prescriptions of “Keep Up the Good Work” or “Concentrate Here.” Funding No external sponsors funded this study. Declaration of competing interest None. References Albayrak, T., Caber, M., Gonz´ alez-Rodríguez, M. R., & Aksu, A. (2018). Analysis of destination competitiveness by IPA and IPCA methods: The case of Costa Brava, Spain against Antalya, Turkey. Tourism Management Perspectives, 28, 53–61. 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. Boley, B. B., McGehee, N. G., & Hammett, A. T. (2017). Importance-performance analysis (IPA) of sustainable tourism initiatives: The resident perspective. Tourism Management, 58, 66–77. Boley, B. B., & Woosnam, K. M. (2021). Going global or going local? Why travelers choose franchise and independent accommodations. Journal of Travel Research, 60 (2), 354–369. Chen, C. C., Lai, Y. H. R., Petrick, J. F., & Lin, Y. H. (2016). Tourism between divided nations: An examination of stereotyping on destination image. Tourism Management, 55, 25–36. Chen, M. M., Murphy, H. C., & Knecht, S. (2016). An importance performance analysis of smartphone applications for hotel chains. Journal of Hospitality and Tourism Management, 29, 69–79. Enright, M. J., & Newton, J. (2004). Tourism destination competitiveness: A quantitative approach. Tourism Management, 25(6), 777–788. Karimi, A., & Boley, B. (2022). Service quality assessments of cultural heritage sites by residents and tourists: Application of four complementary IPA techniques. Tourism Planning & Development. Lai, I. K. W., & Hitchcock, M. (2015). Importance performance analysis in tourism: A framework for researchers. Tourism Management, 48, 242–267. Lee, G., & Lee, C. K. (2009). Cross-cultural comparison of the image of Guam perceived by Korean and Japanese leisure travelers: Importance–performance analysis. Tourism Management, 30(6), 922–931. Malhotra, N. K., Agarwal, J., & Peterson, M. (1996). Methodological issues in crosscultural marketing research: A state-of-the-art review. International Marketing Review. Martilla, J. A., & James, J. C. (1977). Importance-performance analysis. Journal of Marketing, 41(1), 77–79. Oh, H. (2001). Revisiting importance performance analysis. Tourism Management, 22(6), 617–627. Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 460–469. Taplin, R. H. (2012). Competitive importance-performance analysis of an Australian wildlife park. Tourism Management, 33(1), 29e37. Tseng, C. C. (2020). An IPA-Kano model for classifying and diagnosing airport service attributes. Research in Transportation Business & Management, 37, Article 100499. Ye, B., Fu, H., & Law, R. (2016). Use of impact-range performance and asymmetry analyses to improve OTA website quality. Journal of Hospitality and Tourism Management, 26, 9–17. B.B. Boley and E. Jordan

Journal of Hospitality and Tourism Management 57 (2023) 284–302 Available online 3 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. Mapping progress in hospitality CSR research: A bibliometric review from 2006 to 2023 Xuerong Peng a , Hong Wang a , Pei Fang a , Wenhao Song b,* , Dan Zhou c a School of Tourism and Urban-rural Planning, Zhejiang Gongshang University, Hangzhou, 310018, China b School of Economics & Management, Shanghai Maritime University, Shanghai, 201306, China c School of Business Administration, Zhejiang University of Finance & Economics, Hangzhou, 310018, China ARTICLE INFO Keywords: Corporate social responsibility Corporate social performance CSR CSP Hotel Hospitality Review ABSTRACT Corporate social responsibility (CSR) challenges the conventional wisdom of profit-centric hospitality operations. This study offers a comprehensive assessment of CSR within the hospitality industry (HCSR), a field characterized by richness yet fragmentation. We conducted a thorough review using bibliometric and thematic content analyses of 765 peer-reviewed articles in English. Our analysis reveals three key research themes: firm-level HCSR research, employee-level HCSR research, and customer-level HCSR research. The firm-level HCSR research delves into four distinct subthemes: HCSR dimensions and forms, HCSR predictors, the interrelation between HCSR and corporate financial performance (CFP), as well as the interplay of HCSR and COVID-19 context. Employee-level and customer-level HCSR research concentrates on elucidating the impact of HCSR on individual in-role and extra-role behaviors, as well as its impact on the quality of relationships between individuals and hospitality firms. Our work contributes to a comprehensive understanding of the HCSR landscape and complements market-focused strategies in hospitality operations. 1. Introduction Corporate social responsibility (CSR) is commonly recognized as a set of actions aimed at maximizing positive impacts or spillovers while minimizing negative impacts on various stakeholders or society at large (Campbell, 2007; Lantos, 2001). In recent decades, CSR has become a crucial determinant for hospitality firms to attain competitive edges (Lopez-Gamero et al., 2023; Nguyen et al., 2019; Sowamber et al., 2017, pp. 384–396). This shift can be primarily attributed to two key factors. First, stakeholders such as customers, employees, and governments hold increasing expectations for hospitality firms to prioritize CSR activities (D’Acunto et al., 2020). They use corporate social performance (CSP) as an evaluative tool to assess the credibility and desirability of these firms and their offerings (Ahn, 2019; Guix & Font, 2020). Second, intensified competition within the hospitality industry has stimulated a shift towards CSR as a novel avenue for firms to attain competitive advantages (Martinez et al., 2014). As a complementary strategy to traditional market-centered approaches (e.g., excellent service quality, product innovation, and cost leadership) (Huang et al., 2017), CSR has become an integral element of overall corporate strategies (Porter & Kramer, 2006; Porter & Van der Linde, 1995; Sowamber et al., 2017, pp. 384–396). Its positive effects on various indicators of firm performance have received substantial support in empirical studies (Gonzalez-Rodriguez et al., 2021; Lee & Park, 2009). The inception of the modern CSR theory in general management can be traced back to the 1950s, marked by Bowen’s seminal work (Bowen, 1953), whereas the study of CSR within the hospitality industry (HCSR) has witnessed notable expansion only in the last decade (Font & Lynes, 2018). The rapid proliferation of HCSR practices has resulted in a substantial body of research, calling for a comprehensive examination of HCSR studies. While existing reviews on HCSR (Farrington et al., 2017; Guzzo et al., 2020a; Iyer & Jarvis, 2019; Rhou & Singal, 2020) have made valuable contributions, there are still opportunities to address methodological biases and limitations, and capture emerging trends in the field. Firstly, these reviews have predominantly relied on data extracted from prominent tourism and hospitality journals, neglecting important HCSR literature published in general management journals such as the Journal of Business Ethics, Academy of Management Review, Academy of Management Journal, and Journal of Marketing. Consequently, the number of articles considered in these reviews has been relatively small, comprising less than 200 pieces of literature. For instance, Farrington * Corresponding author. E-mail addresses: [email protected] (X. Peng), [email protected] (W. Song). 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.2023.09.003 Received 15 April 2023; Received in revised form 31 August 2023; Accepted 4 September 2023

Journal of Hospitality and Tourism Management 57 (2023) 284–302 285 et al. (2017) examined 81 articles, Guzzo et al. (2020a) analyzed 158 articles, and Rhou and Singal (2020) surveyed 170 articles. Furthermore, the recent two to three years have witnessed a significant surge in HCSR research, contributing to the substantial disparity in the volume of literature between previous reviews and the current study. Secondly, some previous reviews have incorporated keywords beyond CSR during the literature search, such as “sustainable development” (Guzzo et al., 2020a), which subjectively assumed the scope of HCSR research and led to biased search results. Additionally, the literature search did not adequately account for variations in singular and plural forms or consider synonyms of search keywords associated with the hospitality context (e.g., hotel(s), hospitality, lodging, accommodation, and restaurant(s)), resulting in the omission of relevant literature. Moreover, it is noteworthy that previous review articles have predominantly focused on systematic reviews, overlooking the utilization of bibliometric analysis techniques. These techniques can handle larger volumes of literature data and provide more objective insights into research themes. To address the limitations of previous reviews and capture recent advancements in HCSR research, this review employs a combined approach of bibliometric analysis and content analysis. The primary objectives of this review are to address the following research questions (RQs): RQ1: What is the literature profile of HCSR, including publication trends, key contributors, and influential works? RQ2: What are the primary themes and subthemes have emerged from the HCSR literature? By utilizing automated bibliometric analysis tools (e.g., VOSviewer) in conjunction with manual coding for thematic content analysis, our scrutiny of 765 articles unveiled three pivotal research streams/themes: firm-level HCSR research, employee-level HCSR research, and customerlevel HCSR research. This study provides a comprehensive understanding of HCSR research and offers insights for future directions. 2. Methods 2.1. Data collection We gathered data for our review from the Social Science Citation Index (SSCI), a subdatabase within the Web of Science (WOS) Core Collection. For a comprehensive understanding of recent advancements in the field of HCSR, we set the year 2000 as the starting point for our search (Hanelt et al., 2021). In order to ensure comprehensive coverage, we conducted a keyword search across the title, abstract, and author keywords in the subject area. To mitigate bias, we employed the keywords “corporate social responsibilit*1 " or “CSR” in conjunction with terms related to the hospitality context, such as “hotel(s)", “hospitality”, “lodging”, “accommodation”, and “restaurant(s)" . To implement this search strategy effectively, we made use of the “Advanced Search” function provided by WOS. The advanced search code used was [(TS= (“corporate social responsibilit*" OR “CSR")) AND (TS= (“hotel” OR “hotels” OR “hospitality” OR “lodging” OR “accommodation” OR “restaurant” OR “restaurants"))]. We refined the search results by selecting articles and review articles published in English-language journals, excluding conference papers and book reviews. Our search yielded 765 peer-reviewed articles that met these criteria and were published between 2006 and 2023. Notably, most of these articles (536 pieces, accounting for 70%) were published after 2018, indicating a significant increase in attention towards HCSR in recent years, particularly following the onset of the COVID-19 outbreak (refer to Fig. 1). 2.2. Data analysis The purpose of literature reviews is to map and assess the body of literature to determine research gaps and knowledge bases (Tranfield et al., 2003). Most review studies of HCSR rely on qualitative content analysis, but this method is inefficient when dealing with large amounts of literature (e.g., over 300 pieces) (Wong et al., 2021). In this situation, bibliometric analysis proves to be more efficient. However, a challenge researchers face is how to provide insights into the results of bibliometric software analyses (Donthu et al., 2021a). According to previous studies (Khanra et al., 2021a, 2021b), an effective strategy is to identify research themes through automated co-occurrence analysis using bibliometric software and then interpret those themes via content analysis. Therefore, in this review study, we employ bibliometric analysis along with content analysis to assess HCSR literature. The supporting software utilized in this study is VOSviewer with Excel and EndNote as supplements. VOSviewer is a reliable tool for efficiently evaluating and analyzing bibliometric data (Donthu et al., 2021b). Five types of analysis are available in VOSviewer: co-authorship, citation, co-citation, bibliographic coupling, and co-occurrence. Our data analysis comprised three steps. First, descriptive statistics are performed to obtain the literature profile, including top productivity entities, co-authorship analysis, citation analysis, and co-citation analysis. Second, a co-occurrence/co-word analysis based on index keywords (co-words appear in titles, abstracts, and author keywords) (Fahimnia et al., 2015) is conducted to obtain clustered themes in the area of HCSR. The third step involves the identification of subthemes within clustered themes based on a content analysis of the corresponding keywords and high-quality/high-impact articles in each theme. 3. Descriptive analysis results 3.1. Top productivity entities A total of 765 articles on HCSR were published in 123 journals. Table 1 reveals the top 15 journals ranked by publication volume, with International Journal of Hospitality Management occupying the first place (123 articles), followed by Sustainability (92 articles), and International Journal of Contemporary Hospitality Management (84 articles). These findings provide a comprehensive overview of the HCSR research landscape and highlight the key journals shaping the academic discourse. The HCSR literature involves more than 1700 authors affiliated with 878 institutions across 77 countries. Tables 2–4 present rankings of top 15 authors, institutions, and countries based on the number of publications, providing valuable insights into the key contributors shaping the field. 3.2. Citation analysis Citation analysis is a widely used method to evaluate a publication’s influence by counting the times it has been cited in subsequent works (Cronin & Ding, 2011). Tables 5–8 present the top 10 most cited articles, authors, and institutions in the field of HCSR. Notably, Martinez and del Bosque (2013), Inoue and Lee (2011), and Kang et al. (2010) emerge as the most widely cited articles, as shown in Table 5. Table 6 reveals that Seoki Lee holds the highest cited authors in the HCSR literature, followed by Kyung Ho Kang, and Xavier Font. In terms of institutions, Table 7 highlights Temple University, Hong Kong Polytechnic University, and Pennsylvania State University as the top three most cited institutions. Furthermore, Table 8 indicates that the United States, China, and England are the most frequently cited countries in HCSR research. 1 The asterisk (*) represents different word endings or variations. X. Peng et al.

Journal of Hospitality and Tourism Management 57 (2023) 284–302 286 3.3. Co-citation analysis Co-citation refers to the occurrence of two publications being cited together in the reference lists of other documents, indicating a connection between them (Fahimnia et al., 2015). An advantageous aspect of employing co-citation analysis is its ability to identify influential publications (Donthu et al., 2021a). In this study, 765 articles on HCSR research yielded a dataset of 37,520 references from over 10,000 sources involving more than 23,000 authors. This dataset is the foundation for conducting co-citation analysis, enabling an exploration of the influential contributions and connections within the HCSR research literature. Tables 9–11 provide insights into the top 10 most co-cited references, co-cited authors, and co-cited journals. In Table 9, the leading three most frequently co-cited references are Fornell and Larcker (1981), Kang et al. (2010), and de Grosbois (2011). In Table 10, the three most prominently co-cited authors are Joseph F. Hair, Heesup Han, and Seoki Lee. In Table 11, the three most frequently co-cited journals are International Journal of Hospitality Management, Journal of Business Fig. 1. HCSR Annual Publication Volume (2006–2023) Note: The data for the year 2023 includes publications made up to June 15, 2023. Table 1 Top 15 journals based on the number of publications. # Journals Articles↓ % Citations ACC 1 International Journal of Hospitality Management 123 16.1% 7184 58 2 Sustainability 92 12.0% 923 10 3 International Journal of Contemporary Hospitality Management 84 11.0% 2868 34 4 Journal of Sustainable Tourism 49 6.4% 1706 35 5 Tourism Management 35 4.6% 2272 65 6 Journal of Hospitality and Tourism Management 28 3.7% 643 23 7 Corporate Social Responsibility and Environmental Management 27 3.5% 814 30 8 Journal of Hospitality Marketing & Management 25 3.3% 606 24 9 Current Issues in Tourism 22 2.9% 548 25 10 Tourism Economics 17 2.2% 164 10 11 Cornell Hospitality Quarterly 16 2.1% 581 36 12 Journal of Hospitality & Tourism Research 15 2.0% 181 12 13 Journal of Business Ethics 11 1.4% 523 48 14 Frontiers in Psychology 11 1.4% 49 4 15 Tourism Management Perspectives 10 1.3% 226 23 Total 565 73.9% – Note: ACC = Average citation count. Table 2 Top 15 authors based on the number of publications. # Authors Articles↓ Citations Total Link Strength 1 Lee, Seoki 33 2505 66 2 Mattila, Anna S. 18 579 34 3 Han, Heesup 18 518 62 4 Koseoglu, Mehmet Ali 10 250 30 5 Font, Xavier 9 865 16 6 Hur, Won-Moo 9 338 18 7 Perez, Andrea 8 394 14 8 Uyar, Ali 8 138 25 9 Kim, Seongseop (Sam) 8 79 21 10 Kang, Kyung Ho 7 972 15 11 Martinez, Patricia 7 763 13 12 Gao, Yixing Lisa 7 403 12 13 Zhang, Lu 7 205 14 14 Karaman, Abdullah S. 7 134 22 15 Wong, Antony King Fung 7 79 16 Note: Data in Tables 2–4 were generated by co-authorship analysis with VOSviewer. The total link strength attribute represents the total strength of the links of a given item with other items. In co-authorship analysis with VOSviewer, “Total Link Strength” refers to a measure that quantifies the strength or intensity of collaboration between authors. Table 3 Top 15 institutions based on the number of publications. # Institutions Articles↓ Citations Total Link Strength 1 Pennsylvania State University 48 1409 69 2 Hong Kong Polytechnic University 40 1475 55 3 Sejong University 23 560 63 4 University of Central Florida 18 571 33 5 Kyung Hee University 16 724 28 6 University of Surrey 15 400 24 7 Temple University 14 1728 20 8 University of Cantabria 14 958 7 9 University of Johannesburg 14 502 47 10 University of Nevada 14 481 24 11 Sun Yat-Sen University 14 433 22 12 Washington State University 13 558 31 13 Griffith University 13 452 17 14 University of Houston 12 418 18 15 Inha University 11 227 17 X. Peng et al.

Journal of Hospitality and Tourism Management 57 (2023) 284–302 287 Ethics, and International Journal of Contemporary Hospitality Management. 3.4. Co-occurrence analysis for theme identification Using the word co-occurrence/co-word analysis technique, we can determine how co-occurrence words relate to each other and construct a conceptual structure (Callon et al., 1983). The co-occurrence analysis of index keywords has revealed three clusters of research themes in the field of HCSR: “Firm-level HCSR research " (Cluster #1), “Employee-level HCSR research " (Cluster #2), and “Customer-level HCSR research” (Cluster #3), as visually represented in Fig. 2. Moreover, Fig. 3 presents a temporal perspective by demonstrating the evolution of index keywords over time, indicating shifts in research interests. Since 2020, HCSR research has focused on corporate sustainable innovation (e.g., eco-innovation), waste management, employee engagement in Table 4 Top 15 countries/regions based on the number of publications. # Countries/ Regions Articles*↓ % Citations Total Link Strength 1 USA 219 29.0% 8416 161 2 China 191 25.3% 5750 189 3 Spain 105 13.9% 2896 64 4 England 88 11.6% 2900 113 5 South Korea 85 11.2% 2553 89 6 Pakistan 58 7.7% 1177 112 7 Australia 56 7.4% 1425 58 8 Turkey 34 4.5% 655 34 9 Italy 29 3.8% 826 46 10 Malaysia 29 3.8% 711 45 11 Saudi Arabia 26 3.4% 537 57 12 France 20 2.6% 604 32 13 South Africa 19 2.5% 728 43 14 Canada 15 2.0% 908 15 15 Scotland 15 2.0% 566 14 Note: *Co-authors from multiple countries and regions in a single article may lead to duplicate calculations in the publication counts of different countries and regions. Table 5 Top 10 most cited articles based on citation analysis. # Articles WOS Citations↓ Local Citation Links 1 Martinez and del Bosque (2013) 483 94 2 Inoue and Lee (2011) 405 97 3 Kang et al. (2010) 371 129 4 Kang et al. (2012) 368 66 5 Kim et al. (2019) 367 42 6 de Grosbois (2012) 276 118 7 Garay and Font (2012) 270 68 8 Pham et al. (2019) 253 34 9 Lee and Park (2009) 228 86 10 Chou (2014) 207 27 Table 6 Top 10 most cited authors based on citation analysis. # Authors Articles Citations↓ Total Link Strength 1 Lee, Seoki 33 2505 2524 2 Kang, Kyung Ho 7 972 944 3 Font, Xavier 9 865 836 4 Rodriguez-del-Bosque, Ignacio 6 825 602 5 Martinez, Patricia 7 763 593 6 Mattila, Anna S. 18 579 632 7 Heo, Cindy Yoonjoung 3 529 415 8 Zientara, Piotr 6 527 512 9 Singal, Manisha 6 523 786 10 Han, Heesup 18 518 660 Table 7 Top 10 most cited institutions/organizations based on citation analysis. # Organization Articles Citations↓ Total Link Strength 1 Temple University 14 1728 1150 2 Hong Kong Polytechnic University 40 1475 1699 3 Pennsylvania State University 48 1409 1430 4 University of Cantabria 14 958 657 5 Leeds Metropolitan University (now known as Leeds Beckett University) 5 737 398 6 Kyung Hee University 16 724 683 7 Florida State University 9 593 284 8 Macau University of Science and Technology 7 584 364 9 University of Central Florida 18 571 619 10 Sejong University 23 560 614 Table 8 Top 10 most cited countries based on citation analysis. # Countries/Regions Documents Citations↓ Total Link Strength 1 USA 219 8416 4159 2 China 191 5750 3647 3 England 88 2900 1847 4 Spain 105 2896 2127 5 South Korea 85 2553 1851 6 Australia 56 1425 888 7 Pakistan 58 1177 1167 8 Canada 15 908 559 9 Italy 29 826 675 10 South Africa 19 728 443 Table 9 Top 10 most co-cited references from the co-citation analysis. # Co-cited references Focuses Citations Total Link Strength↓ 1 Fornell and Larcker (1981) Validity and reliability 199 18676 2 Kang et al. (2010) HCSR 128 11657 3 de Grosbois (2011) HCSR 116 11294 4 Podsakoff et al. (2003) CMB of self-report data 112 11369 5 Hair et al. (2014)* Data analysis 110 10514 6 Martinez and del Bosque (2013) HCSR 93 9209 7 Inoue and Lee (2011) HCSR 93 8422 8 Sen and Bhattacharya (2001) Strategic CSR 95 8239 9 Carroll (1979) Dimensions of CSR 87 7637 10 Lee and Park (2009) HCSR 85 7574 Note: * This book is available in multiple editions. CMB = Common Method Biases. Table 10 Top 10 most co-cited authors from the co-citation analysis. # Co-cited authors Citations Total Link Strength↓ 1 Hair, Joseph F. 310 30342 2 Han, Heesup 305 29480 3 Lee, Seoki 303 27990 4 Carroll, Archie B. 293 25863 5 Bohdanowicz, Paulina 245 22709 6 Fornell, Claes 231 21645 7 Kang, Kyung Ho 219 20359 8 Font, Xavier 214 20088 9 Podsakoff, Philip M. 199 19996 10 Martinez, Patricia 187 18287 Note: Web of Science data includes only the first author of a cited document. Other authors are not considered in a co-citation analysis of cited authors. X. Peng et al.

Journal of Hospitality and Tourism Management 57 (2023) 284–302 288 green/pro-environmental behaviors and value cocreation behaviors, and the connections between HCSR and the COVID-19 pandemic. 4. Thematic content analysis of co-occurrence clustering 4.1. Cluster #1: Firm-level HCSR research Investigating HCSR at the firm level is essential for comprehending this phenomenon, as firms hold a pivotal position in executing such initiatives. This research stream centers on the dimensions and forms of HCSR observed in empirical studies and reality, the antecedents of HCSR, the link between HCSR and corporate financial performance (CFP), and the interplay between HCSR and the COVID-19 pandemic. 4.1.1. HCSR dimensions and forms CSR is widely recognized as a multidimensional construct in empirical research, with its classification varying based on different criteria, such as contents (responsible for what) and stakeholders (responsible for whom). In HCSR empirical studies, CSR dimensions are commonly classified using four approaches.2 One approach, grounded in Carroll’s CSR pyramid, classifies HCSR into economic, legal, ethical, and philanthropic dimensions (Chen et al., 2021a; Choi & Choi, 2021; Kim et al., 2018). In some cases, the environmental dimension is also added to this classification (Ghaderi et al., 2019). Another frequently employed categorization is rooted in the triple bottom line (TBL) framework of sustainable development, which classifies HCSR into environmental, social, and economic dimensions (Gursoy et al., 2019; Shim et al., 2021). The third approach classifies HCSR into external CSR and internal CSR (Hur et al., 2019; Yoon & Chung, 2018). External CSR primarily addresses the environmental and social concerns of external stakeholders, such as customers, governments, and local communities, while internal CSR focuses on enhancing the well-being of employees. Furthermore, the fourth classification categorizes HCSR into positive CSR and negative CSR (Kang et al., 2010, 2016; Park et al., 2017), or CSR and corporate social irresponsibility (CSIR) (Volgger & Huang, 2019; Youn et al., 2015). This distinction highlights the broad spectrum of CSR actions in hospitality firms, spanning from negative (doing bad things) to positive (doing good things). Moreover, in some other studies, the classification of HCSR does not differentiate or match the contents with the corresponding stakeholders (e.g., Inoue & Lee, 2011; Paek et al., 2013; Singal, 2014a). Additionally, our data analysis reveals the predominant forms of HCSR at the organizational level research, which are environmental/ green (management) practices (e.g., environmental management system Table 11 Top 10 most co-cited journals from the co-citation analysis. # Co-cited journals Citations Total Link Strength↓ 1 International Journal of Hospitality Management 4668 347378 2 Journal of Business Ethics 3057 211599 3 International Journal of Contemporary Hospitality Management 2414 198591 4 Tourism Management 1944 157180 5 Journal of Sustainable Tourism 1394 106618 6 Journal of Business Research 1266 100711 7 Journal of Cleaner Production 1035 85350 8 Journal of Marketing 1087 77694 9 Cornell Hospitality Quarterly 909 76878 10 Academy of Management Review 931 66822 Note: The minimum citation threshold for a journal is set at 10. Fig. 2. Density diagram of index keywords (Threshold = 15 co-occurrences, Items = 100). Notes: Keywords with similar or interchangeable meanings have been consolidated using a VOSviewer thesaurus file. It is important to note that some keywords with potential overlap may not be readily discernible in the figure. Please consult the appendix table for a comprehensive list of keywords associated with each cooccurrence cluster. 2 The classification of HCSR does not differ significantly among the studies within the three thematic clusters. However, distinctions arise in the forms of HCSR within each cluster. X. Peng et al.

Journal of Hospitality and Tourism Management 57 (2023) 284–302 289 (EMS) adoption, and environmental certification), sustainable innovation (e.g., eco-innovation, green innovation, and environmental innovation), ethics, sustainable/green supply chain management, quality management, and waste management. 4.1.2. HCSR predictors The predictors of HCSR initiatives can be categorized into environmental/institutional, organizational, and managerial (individual and group-level) drivers. The first group pertains to external predictors outside the focal hospitality firm, while the latter two encompass internal drivers within the firm. Prior research has indicated that internal motivation is the primary driving force behind CSR activities (Graafland & Van de Ven, 2006), although in some cases, external motivations may outweigh internal ones (Fehr et al., 1997). Managerial predictors. The managerial predictors of HCSR that have already been examined by empirical studies include gender diversity of top management teams (TMTs) (e.g., female directors) (Gerged et al., 2023; Quintana-Garcia et al., 2018; Uyar et al., 2020), CEO’s narcissism (Ahn et al., 2020), top managers’ leadership styles (e. g., ethical leadership and environmental leadership) (Jang et al., 2017; Zhu et al., 2014), top managers’ environmental values (Jang et al., 2017), managers’ sustainability attitude (Koch et al., 2020), CEOs’ compensation3 (Park et al., 2019), and network embeddedness such as CEO network centrality (Chen et al., 2021b), managerial political tie (Gu et al., 2013), and board interlock centrality (Vaughan & Koh, 2022). The central arguments of this research camp suggest that executives’ cognitive patterns, influenced by their psychological traits, past experiences, and demographics, along with their perceived discretion rooted in their possessed resources and capabilities, play a significant role in shaping their HCSR decisions. The underlying theories supporting this proposition encompass the upper echelons theory, agency theory, the theory of planned behavior (TPB), and social capital theory. Notably, among these theories, the upper echelons theory (Hambrick, 2007; Hambrick & Mason, 1984) takes the forefront as the primary perspective for understanding how managerial predictors influence HCSR decisions. According to this theory, executives function as information filters in the corporate strategic decision-making process, and thus, their mindsets and cognitive patterns profoundly impact organizational strategies and performance. Empirical studies frequently operationalize executives’ mindsets using observed past experiences and demographics (Finkelstein et al., 2009). It’s important to note that demographics, including factors like age, gender, education, race, nationality, religion, occupation, and income, also reflect past experiences to some extent. Additionally, the degree to which executives influence organizational outcomes depends on managerial discretion, which arises in the absence of constraints and in situations characterized by a high degree of ambiguity about means and ends (Hambrick, 2007). Managerial discretion can stem from various sources, including managerial, organizational, and environmental factors. For instance, CEO narcissism can affect their perception of the discretion level and their efforts to enhance it (Tang et al., 2018). Organizational predictors. The organizational predictors of HCSR center on RPV (resources-processes-values) dimensions.4 Predictors linked to resources (and capabilities) highlight financial/slack resources (Choi & Lee, 2018; Moneva et al., 2020; Pereira-Moliner et al., 2012; Singal, 2014b; Vaughan et al., 2023), dynamic capabilities (which primarily include adaptive capability, absorptive capacity, and innovative capability (Wang & Ahmed, 2007) and their indicators explored in HCSR literature focus on innovativeness, agility and green ambidexterity (Koch et al., 2020; Lopez-Gamero et al., 2023; Ubeda-Garcia et al., 2022)), and sustainable intangible capital (Zaragoza-Saez et al., 2023). These studies are grounded in the necessity for essential resources and capabilities within hospitality firms to engage in CSR, primarily from the perspective of the resource-based view (Barney, 1991) and dynamic capabilities theory (Teece et al., 1997). Processes or structures predictors of HCSR emphasize corporate governance (e.g., ownership structures like institutional/managerial ownership, board gender diversity, board size, independent director-toFig. 3. Overlay visualization diagram of index keywords. 3 Executive compensation reflects corporate governance and can also be considered a predictor at the firm level. 4 The RPV (Resources-Processes-Values) framework was proposed by Christensen (2013) to illustrate that successfully implementing disruptive innovation requires changes in firm capabilities in three key aspects, with capabilities being a broader concept in this context. X. Peng et al.

Journal of Hospitality and Tourism Management 57 (2023) 284–302 290 total director ratio, and TMTs’ compensation) (Chen & Lin, 2015; Paek et al., 2013; Park et al., 2019; Qasem et al., 2023; Uyar et al., 2020) and formal management procedures or policies (e.g., (total) quality management) (Benavides-Velasco et al., 2014; Pereira-Moliner et al., 2021; Quintana-Garcia et al., 2018). In terms of corporate governance predictors, drawing on principal-agent theory or agency theory, prior research posits that corporate governance can either moderate or exacerbate executives’ opportunistic behaviors associated with HCSR, as corporate governance aims to address agency problems and ensure that executive actions align with shareholder interests (Eisenhardt, 1989). Specifically, diverse governance structures exhibit differing capabilities in monitoring TMTs and yield varying preferences for CSR among shareholders, despite their primary pursuit being profit maximization. Moreover, CSR initiatives can give rise to conflicting interests between shareholders and managers, particularly over different time frames (long-term and short-term). For instance, certain HCSR activities (e.g., donations) might be beneficial for managers in the short term yet not as favorable for shareholders (Park et al., 2019), whereas the scenario could be reversed for other cases like eco-innovation. Regarding management procedures predictors, the rationale lies in mutual reinforcement between quality management and HCSR, as product quality is a vital component of customer-centered HCSR (Inoue & Lee, 2011), and HCSR is an integral aspect of total quality management (TQM) (Quintana-Garcia et al., 2018; Zhu et al., 2014). Accordingly, the application of quality management or TQM practices leads to a positive impact on HCSR initiatives and performance (Benavides-Velasco et al., 2014; Pereira-Moliner et al., 2021; Quintana-Garcia et al., 2018). Organizational values predictors of HCSR highlight various corporate cultures (e.g., green culture, long-term-oriented culture, and ethical value) (Asadi et al., 2020; Gonzalez-Rodriguez et al., 2019; Kim & Pennington-Gray, 2017; Yang et al., 2023) and strategic orientations (e. g., market orientation) (Qu, 2007). Corporate values provide standards for executives and employees to make prioritization decisions (Christensen, 2013), such as giving HCSR priority when allocating resources. They can also be viewed as intangible organizational resources (Klein, 2011) that have the potential to facilitate HCSR actions. Additionally, extensive research has investigated other organizational-level predictors of HCSR, including strategies (determined by RPV) and firm characteristics, particularly the unique features of hospitality firms. Corporate strategies, such as competitive strategies (i.e., cost leadership and differentiation) (Uyar et al., 2022) and green innovation strategy (Asadi et al., 2020), impact HCSR due to the mutual influence between market strategy and CSR strategy, or simply the principle that “CSR strategy guides CSR actions”. Furthermore, firm characteristics such as company size, hotel class, chain affiliation (e.g., chain vs. independent), market structure (e.g., a high ratio of business tourists), hotel location (e.g., urban vs. non-urban), and reputation (based on online reviews) also influence HCSR (Chen, 2019a; Mzembe et al., 2019; Yang et al., 2023). For instance, compared to small firms, larger companies have greater resource availability and visibility, leading to increased external pressures to engage in CSR (Mzembe et al., 2019). Likewise, in comparison to independent hotels, chain hotels demonstrate higher levels of CSR performance, primarily attributed to stringent regulations imposed by management companies (Chen, 2019a). Environmental predictors. Unexpectedly, this stream of CSR research in the hospitality industry is limited in contrast to extensive research on this direction in the manufacturing industry (Aguinis & Glavas, 2012). Empirically examined HCSR predictors associated with environmental factors include three classical institutional pressures: coercive pressures from government-enacted laws, rules, and sanctions, normative pressures from social values and norms of accreditations and certifications awarded by standard-setting entities, and mimetic pressures from shared cultural-cognitive understanding with peers (e.g., national culture) (de Grosbois & Fennell, 2022; Ibrahim et al., 2023; Mzembe et al., 2019; Ng & Sia, 2023; Ouyang et al., 2019). Indeed, institutional pressures align closely with stakeholder pressures, as they inherently reflect expectations and/or (negative or positive) incentives associated with CSR and CSIR from various stakeholders (Yan et al., 2023; Zailani et al., 2012), such as governments, customers, competitors, and local communities. The salience of stakeholders depends on their power, legitimacy, and urgency of their claim (Mitchell et al., 1997), which significantly impacts external HCSR (Ibrahim et al., 2023). The core idea of CSR is that business has an implicit social contract with a society that consists of various dominant stakeholders (Chiu & Sharfman, 2009; Wartick & Cochran, 1985). This social contract sets up rights and obligations for firms, and firms should have social legitimacy by meeting the expectations of society or critical stakeholders (Waldman et al., 2006; Wartick & Cochran, 1985). This idea is reflected to varying degrees in theories that emphasize the impact of the external environment on firm behaviors, including institutional theory, stakeholder theory, and resource dependence theory, as highlighted in HCSR literature. For instance, according to institutional theory (DiMaggio & Powell, 1983; Meyer & Rowan, 1977), CSR is an effort undertaken by enterprises to address institutional isomorphic pressures from critical stakeholders, intending to establish or maintain legitimacy in the eyes of these stakeholders (Chiu & Sharfman, 2011). This pursuit, in turn, enables them to attain resources controlled by these stakeholders, given that legitimacy serves as a leveraged resource (Zimmerman & Zeitz, 2002). Notably, the institutional pillars of isomorphic pressures can be formal (based on regulations) and informal (arising from social-cultural embeddedness). In addition, several studies have delved into the influence of environmental characteristics (e.g., munificence and turbulence) on the promotion of HCSR initiatives (De Clercq et al., 2018; Fatima & Elbanna, 2023). Grounded in resource dependence theory, the rationale of this line of inquiry is that diverse environmental characteristics signify distinct opportunities, risks, and available resources, thereby eliciting diverse HCSR responses from businesses. This impact is contingent upon the managerial interpretation of external stimuli. Moderation and mediation models. Research on the antecedents of HCSR constructs theoretical models that mostly involve moderators or mediators from distinct levels. In typical moderation models, the emphasis is on the interaction between institutional/managerial and organizational predictors (Ahn et al., 2020; Chen et al., 2021b; Ouyang et al., 2019), and between organizational predictors (Vaughan & Koh, 2022). The underlying logic suggests that the synergy of executive cognitive preferences or (negative/positive) incentives for the focal firm (and its executives) and the availability of resources (and capabilities) is essential for effectively promoting HCSR. Regarding mediation models, previous studies primarily focus on exploring how organizational or managerial factors mediate the impact of environmental factors on HCSR (Ibrahim et al., 2023) and mutual meditating effects among same-level predictors (Boronat-Navarro & Garcia-Joerger, 2019). Barriers of HCSR. Despite hospitality firms’ growing interest in CSR initiatives, implementing such practices faces various obstacles. These barriers include inadequate understanding of the concept (G´ azquez-Abad et al., 2015; Sheldon & Park, 2011), limited environmental awareness among business stakeholders (Luo et al., 2021), constrained tangible and intangible resources (Garay & Font, 2012; Luo et al., 2021; Mzembe et al., 2019; Wells et al., 2016), expensive costs (Cantele & Cassia, 2020; Luo et al., 2021), technical and managerial obstacles (Bohdanowicz et al., 2011; Luo et al., 2021), poor communication (Bohdanowicz et al., 2011), difficulties in performance measurement (Bohdanowicz et al., 2011), time limitations (Khatter et al., 2021), old property (Khatter et al., 2021), obstacles tied to stakeholders (e.g., property owners) (Khatter et al., 2021) and the absence of clear government policies and regulations (Cantele & Cassia, 2020; Khatter et al., 2021; Luo et al., 2021). Addressing these barriers is essential for accelerating the diffusion of CSR initiatives among hospitality firms. X. Peng et al.

Journal of Hospitality and Tourism Management 57 (2023) 284–302 291 4.1.3. HCSR-CFP link HCSR-CFP direct link. The connection between CSR and CFP has ignited extensive discussions in general management field since the 1960s (see reviews: Cochran & Wood, 1984; Orlitzky et al., 2003; van Beurden & Gossling, 2008), while research into the CSR-CFP link within the hospitality industry has surged in the past two decades (Inoue & Lee, 2011; Kang et al., 2010; Lee & Park, 2009; Nazir et al., 2021). Empirical findings concerning the direct association between HCSR and CFP, similar to those in the manufacturing sector, yield mixed results (see a review: Lee et al., 2022), encompassing positive effects (Lee & Park, 2009; Moneva et al., 2019), negative impacts (Shin et al., 2021), and a U-shape relationship (Franco et al., 2020). One evident explanation for this disparity emerges from the diverse operationalization of CSR (employing various dimensions such as internal CSR and external CSR, as well as utilizing different measurements like direct scale measures and proxy measures) and CFP (encompassing objective and subjective CFP, the indicators range from short-term metrics like ROA, ROE, ROS, ADR, OCC, and RevPAR to long-term metrics like Tobin’s Q),5 and different research settings (e.g., developed countries and developing countries; luxury hotels and budget hotels) involved in empirical studies (Lee et al., 2022). Another vital cause lies in model misspecification (Surroca et al., 2010), such as the absence of essential controls, mediators, and moderators. Consequently, recent investigations into the HCSR-CFP link have shifted from direct relationship analysis to identifying moderators and mediators, aiming to unravel these intricate connections. Moderators. Moderators in the HCSR-CFP link suggest that the impact of HCSR on CFP depends on how well it is absorbed by the external environment and within the organizations themselves. Moderators impacting external absorptive capacity for HCSR include stakeholders’ CSR awareness (Rhou et al., 2016), macroeconomic conditions (Lee et al., 2013b), CSR communication (Kim & Kim, 2019), franchising strategy (which elevates CSR importance due to more stakeholder involvement) (Kim & Lee, 2020), chain affiliation (where CSR in chain-affiliated hotels is less visible and recognizable) (Mao et al., 2022), hotel class (with higher-end hotels having guests more willing to pay for eco-friendly programs) (Mao et al., 2022), and business type (with different stakeholder CSR expectations and rewards between fast-food and full-service restaurants) (Youn et al., 2016). Moderators affecting internal absorptive capacity for HCSR encompass firm size (larger firms have more resources and influence for implementing CSR initiatives) (Youn et al., 2015), quality management (which may be incompatible with CSR) (Franco et al., 2020), and family involvement (reducing CSR-related agency costs) (Yeon et al., 2021). Mediators.6 The impact of HCSR on CFP is mainly mediated by intangible organizational resources and capabilities, which are core indicators of operational performance, such as reputation (Becerra-Vicario et al., 2022; Gonzalez-Rodriguez et al., 2019, 2021; Zhu et al., 2014), customer satisfaction (which has been studied at the organizational level) (Cantele & Cassia, 2020; Lee & Heo, 2009; Qu, 2014), competitiveness/competitive advantage (Cantele & Cassia, 2020; Pereira-Moliner et al., 2021), demand and productivity effects (Chen, 2019b), growth opportunities (Babajee et al., 2022), organizational resilience during crises (Marco-Lajara et al., 2022), innovation capabilities (Wang, 2014; Yoo et al., 2022), sustainability performance (the improvement of stakeholders’ well-being, such as CSP and corporate environmental performance [CEP]) (Shi & Tsai, 2020). Three mechanisms account for these mediating effects. First, engaging in HCSR initiatives can be viewed as an investment in reputation insurance, serving as a risk buffer to mitigate the adverse effects of unpredictable negative events on CFP (Godfrey et al., 2009; Luo et al., 2018; Marco-Lajara et al., 2022). Second, HCSR initiatives enable firms to establish social networks (Chang & Chen, 2012) and maintain social legitimacy (Lin et al., 2021) by satisfying the CSR expectations of salient stakeholders. These impacts facilitate a direct increase in customer demand or market competitiveness (Cantele & Cassia, 2020; Pereira-Moliner et al., 2021) and the acquisition of valuable resources and capabilities necessary for implementing growth strategies, such as innovation (Wang, 2014; Yoo et al., 2022). Third, HCSR serves as a significant source of Porter’s two competitive strategies, leading to potential cost reduction (e.g., through the adoption of green energy-saving technology) and increased sales revenue via product differentiation (as evidenced by products displaying eco-certifications) (Lee et al., 2010; Lopez-Gamero et al., 2023). This function is particularly true for strategic CSR initiatives (e.g., eco-innovation), where CSR initiatives are closely integrated with the corporate core business, carrying a win-win potential that benefits both the firm and social welfare for society at large (Porter & Van der Linde, 1995). In such cases, HCSR acts as a necessary input for achieving high CFP. Other outcomes of HCSR. Numerous studies conducted at organizational or individual levels have explored non-CFP consequences without investigating their mediating role in the HCSR-CFP link. These non-CFP outcomes, in addition to the previously mentioned mediators between the HCSR-CFP link, include the firm’s ability to attract institutional equity capital providers (Lyssimachou & Bilinski, 2022), image (Latif et al., 2020), positive stakeholder behaviors (Gao & Mattila, 2014; Tian & Robertson, 2019), stakeholder relationship quality (Martinez & del Bosque, 2013), and specific indicators of sustainability performance associated with stakeholders, such as basic need satisfaction (Bibi et al., 2021), increased quality of life (Kim et al., 2018), self-efficacy (Sung & Lee, 2023), self-esteem (Bibi et al., 2021), personal prestige, and personal pride (Hur et al., 2018). An implicit assumption in these studies is that the favorable non-CFP outcomes resulting from HCSR initiatives can ultimately contribute to enhancing CFP. In the subsequent two cluster analyses, based on individual-level research, we will provide comprehensive examinations and discussions of the non-CFP outcomes of HCSR related to two key stakeholders: employees and customers. 4.1.4. HCSR and COVID-19 The COVID-19 pandemic, which started in December 2019, has gained significant attention in the HCSR literature over the past three years (Lee, 2022). This global public health crisis has had extensive economic repercussions, particularly impacting industries such as hospitality and tourism (Baber et al., 2022; Chi et al., 2022; Lee, 2022). The connection between HCSR and COVID-19 has been explored through three specified research avenues. The first avenue explores the mutual influence between HCSR and COVID-19. On the one hand, it has been observed that CSR practices impact the response of hospitality firms to the pandemic (Marco-Lajara et al., 2022). On the other hand, COVID-19 has also influenced HCSR actions. It has elevated the role of CSR as a crisis management tool for hospitality firms to cope with the public health emergency posed by COVID-19 and other consequential challenges spanning social, environmental, and economic realms (Lee, 2022). Additionally, it has provided hospitality firms with an opportunity to explore new CSR activities (e.g., COVID-19-oriented CSR) (Sun et al., 2022), particularly in transitioning from traditional CSR (e.g., philanthropy) to more strategic CSR (e.g., social innovation and entrepreneurship targeting the creation of shared value) approaches (Lee, 2022). The second avenue focuses on understanding stakeholder responses to HCSR efforts during the pandemic. Previous studies have indicated that HCSR initiatives, particularly those related to COVID-19, receive 5 ROA = Return on Assets; ROE = Return on Equity; ROS=Return on Sales; ADR = Average Daily Rate; OCC=Occupancy Rate; RevPAR=Revenue per Available Room (calculated as OCC multiplied by ADR); Tobin’s Q = Market Value of a Company/Replacement Cost of its Assets = Market Value/Book Value. 6 Some constructs linking independent variables and HCSR lack corresponding hypotheses regarding their mediation roles and have not been tested for their mediating effects. X. Peng et al.

Journal of Hospitality and Tourism Management 57 (2023) 284–302 292 positive reactions from various stakeholders. Employees, for instance, exhibit enhanced psychological capital (Mao et al., 2021), improved safety behaviors (Zhang et al., 2021a), reduced job insecurity, and increased job performance (Vo-Thanh et al., 2021). Likewise, customers manifest favorable reactions to COVID-19-related HCSR, as evidenced by their purchase and visit intentions and/or behaviors (Chi et al., 2022; Tong et al., 2021). Moreover, investors react positively to HCSR initiatives, as studies suggest that HCSR endeavors alleviate the adverse impact of COVID-19 on stock market performance (Clark et al., 2021; Qiu et al., 2021). The third avenue examines the moderating role of CSR in the relationship between the pandemic and CFP, focusing on the risk-buffering insurance effect of CSR during crises. Findings indicate that CSR enhances organizational resilience during the pandemic, enabling them to better withstand and adapt to challenges (Li et al., 2021; Marco-Lajara et al., 2022). 4.2. Cluster #2: Employee-level HCSR research Employees are not only beneficiaries but also the key implementers of HCSR practices. Research at the employee level of HCSR emphasizes HCSR actions related to sustainable/green/socially responsible human resource management (HRM), diversity, work-life balance, fair and equal opportunities, workplace safety and health, training, competitive salaries, and employee assistance programs. This strand of research centers on examining the effects of HCSR on employees’ in-role and extra-role performance and its impact on the quality of the employeecompany relationship. 4.2.1. HCSR and employee in-role job performance Research indicates that HCSR actions have both direct and indirect positive effects on employees’ overall job performance (He et al., 2019, 2021; Hur et al., 2021; Kim et al., 2022; Nazir et al., 2021; Vo-Thanh et al., 2021; Yu et al., 2022), as well as on specific task performance (e. g., creativity, green creativity, innovative work behavior, and safety behavior) (Al-Ghazali & Afsar, 2021; Hur et al., 2018; Oh et al., 2022; Zhang et al., 2021a). These effects stem from three core mechanisms: organizational identification and compassion at work, self-identification and passion for work, and empowerment. First, given its potential to empower a focal company to stand out amidst its counterparts by contributing to the well-being of employees and other stakeholders (Heikkurinen, 2010), HCSR can instill a sense of organizational pride (due to perceived external prestige) and identification among employees (representing the process by which employees make sense of their affiliations) (Gurlek & Tuna, 2019; Kim et al., 2020a; Tian & Robertson, 2019). This, in turn, bolsters employee relations and evokes emotions of compassion, empathy, gratitude, and reciprocity within employees (Nazir & Ul Islam, 2020a). These favorable relationships subsequently serve as motivators for employees to elevate their work/organization engagement and embrace collaborative behaviors that safeguard the collective reputation and image—essentially, the social identity—associated with their prestigious companies (Guzzo et al., 2020b; Hur et al., 2018; Kim & Kim, 2021; Nazir & Ul Islam, 2020b; Zhang et al., 2021a). Second, when HCSR initiatives align with employees’ interests and values (e.g., precisely cater to the expectations of employees interested in participating in socially responsible projects), they experience a deep sense of work meaningfulness (Nazir & Ul Islam, 2020a; Raub & Blunschi, 2014), personal prestige and self-identification that ignites their passion and dedication toward their work (reflecting the process by which employees make sense of themselves) (Cho & Yoo, 2021; Raub & Blunschi, 2014), ultimately resulting in elevated work engagement and job performance (Hur et al., 2018; Nazir et al., 2021). Lastly, employee-centered HCSR initiatives, such as diversity recruitment and health and safety programs (Paek et al., 2013), can directly improve the well-being of employees, benefiting their physical and mental state (Ahmed et al., 2020b) and equip them with necessary skills and competences. This empowerment contributes to their excellence in job roles and leads to elevated job performance (Kim et al., 2017; Luu, 2021). Conversely, CSIR actions within hospitality firms, such as sexual harassment, bullying, and violence, can harm employee engagement (Ram, 2018). Notably, the decline in HCSR may stem from external factors beyond a company’s control, rendering its impact on employee performance complex. The COVID-19 pandemic illustrates the effects of such a decline caused by non-corporate control factors. Several studies have reported that layoffs and mergers resulting from the pandemic have hurt employee job performance (De Clercq et al., 2017). However, the findings of Vo-Thanh et al. (2021) suggest that employees appear to demonstrate an increased dedication to their companies during such periods, using this as a strategic approach to maintain employment. The authors also argue that HCSR initiatives that are well-suited to address the health-related challenges posed by COVID-19 can help mitigate job insecurity and sustain employee performance (Vo-Thanh et al., 2021). Thus, this research highlights the need to consider the specific context and circumstances surrounding a decline in HCSR to fully understand its impact on employee performance. 4.2.2. HCSR and employee extra-role performance In addition to in-role job performance, HCSR initiatives can also influence employees’ extra-role discretionary behaviors (Afridi et al., 2023; Raub & Blunschi, 2014), such as organizational citizenship behaviors (OCBs), green/pro-environmental behaviors (PEBs) and other pro-social (responsible) behaviors. OCBs refer to voluntary actions taken by employees that support their working companies and goals but are not part of their formal job requirements, such as helping co-workers, collaborating on tasks, and finding better ways to achieve goals (Kim et al., 2017). PEBs can be viewed as OCBs for the environment (OCBEs) (Luu, 2017, 2019). Numerous studies have shown a positive relationship between HCSR actions (e.g., green/sustainable HRM) and employees’ OCBs (Bogan & Dedeoglu, 2020; Fu et al., 2014; Kim et al., 2017). Conversely, CSIR among hospitality firms has been linked to reduced employees’ identification with the firms (Kim et al., 2017) and a decline in their OCBs (Appelbaum & Roy-Girard, 2007). The three core mechanisms underpinning HCSR’s impact on employees’ in-role job performance are likewise applicable to understanding its effects on employees’ OCBs (Ahmed et al., 2020b; Ali et al., 2023; Cheema et al., 2020; Su & Swanson, 2019; Tian & Robertson, 2019). Additionally, we have recognized a distinct mechanism termed “CSR mimic/cultural isomorphism,” which underscores employees’ adoption of OCBs to align with the CSR culture, climate, values, and philosophy of hospitality firms (Al-Swidi et al., 2021; Shao et al., 2021; Zientara & Zamojska, 2018). These shared HCSR cultural cognitions yield mimic pressures for employees within the organizational context to engage in OCBs. Moreover, given that employees’ OCBs also serve as a manifestation of CSR at the individual level, the HCSR literature encompasses a range of studies that delve into the antecedents of employees’ OCBs. Apart from HCSR, other highly investigated predictors of employees’ OCBs concentrate on leadership styles (e.g., ethical leadership, servant leadership, responsible leadership, transformational leadership) (Aboramadan et al., 2021; He et al., 2021; Tosun et al., 2022; Wood et al., 2021), organizational green culture (Al-Swidi et al., 2021; Yesiltas et al., 2022) or climate (Aboramadan et al., 2021; Zientara & Zamojska, 2018) and employee’s CSR motive attributions (e.g., substantive or symbolic) (Afridi et al., 2023; Vila-Vazquez et al., 2023). 4.2.3. HCSR and employment relationship quality The impact of HCSR on employee in-role and extra-role performance is heavily mediated by the quality of the employee-employer relationship, leading to extensive research on the effects of HCSR on employment relationship quality. Relationship quality, lacking a consistent definition (Gottfredson et al., 2022), can be regarded as a metaconstruct X. Peng et al.

Journal of Hospitality and Tourism Management 57 (2023) 284–302 293 comprising various interrelated components that reflect the overall nature of relationships (e.g., cooperative versus conflict; long-term orientation versus opportunism) between interconnected parties (such as employees and employers, or buyers and sellers) (Alejandro et al., 2011; Hennig-Thurau et al., 2002; Qian et al., 2021). The outcomes of HCSR associated with employment relationship quality, as examined in empirical studies, include identification (Cheema et al., 2020; Chen et al., 2023; Gurlek & Tuna, 2019; Kim et al., 2020b; Shah et al., 2021), commitment (Fu et al., 2014; Kim et al., 2021; Yoon et al., 2016), trust (Lee et al., 2012; Su & Swanson, 2019; Yoon et al., 2016), satisfaction (Appiah, 2019; Farmaki et al., 2022; Lee et al., 2012), compassion at work (Guzzo et al., 2020b; Hur et al., 2018; Nazir & Ul Islam, 2020a), gratitude (Guzzo et al., 2020b), organizational pride (Farooq & Salam, 2020; Raza et al., 2021), (external) prestige (Bogan & Dedeoglu, 2020; Gurlek & Tuna, 2019), organizational/work engagement (Gurlek & Tuna, 2019; Nazir & Ul Islam, 2020a; Raza et al., 2021), turnover intention (Gonzalez-De-la-Rosa et al., 2023), job pursuit intentions (Guzzo et al., 2022) and organizational attraction (Guzzo et al., 2023). Among them, trust, commitment, and satisfaction are wellestablished components of relationship quality in the management literature (Athanasopoulou, 2009; Hennig-Thurau et al., 2002; Rauyruen & Miller, 2007). Bhattacharya et al. (2009) further incorporated identification as a critical component of quality relationships. They contend that the four components represent varying degrees of relationship quality, with identification being the strongest (referring to individuals’ perceived oneness with their affiliated entities), followed by commitment (which signifies people’s enduring desire to uphold a valued relationship), trust (indicating one’s confidence in the reliability and integrity of tied partners, not only for partners’ past actions but also for their anticipated future actions), and finally, satisfaction being the weakest (relating to the overall evaluation of individuals’ experience with connected entities). Furthermore, some indicators hold significant importance in HCSR literature, such as compassion at work and gratitude, highlighting the reciprocal nature of positive relationships. Additionally, some indicators (e.g., (electric) word-of-mouth/(e)WOM, engagement, turnover intention, loyalty, job pursuit intentions, and organizational attraction) are regarded by some researchers in general management (Athanasopoulou, 2009; Hennig-Thurau et al., 2002; Rauyruen & Miller, 2007) and hospitality management (Lee et al., 2012) fields as indications of relationship outcomes, rather than constituting dimensions of relationship quality themselves. Moreover, other scholars emphasize the interconnected nature of these components, suggesting the existence of inherent causal relationships among them (Hennig-Thurau et al., 2002; Rauyruen & Miller, 2007). This perspective is supported by extensive research that investigates the mutual mediating or moderating effects among dimensions of relationship quality beyond examining the direct impact of HCSR on these dimensions. For instance, a typical mediation model suggests that HCSR influences employees’ organizational identification, subsequently affecting their organizational commitment or turnover intention (Kim et al., 2023). The dominant rationale through which HCSR influences the quality of employee relationships is by providing employees a wide range of benefits (Bhattacharya et al., 2009). These benefits manifest in diverse forms: direct (e.g., increased employees’ well-being via employee-focused HCSR) and indirect (e.g., enhancing employee organizational prestige via improved well-being for others) (Kim et al., 2018) aspects, along with functional (e.g., enhanced life quality) (Gonzalez-De-la-Rosa et al., 2023) and psychological (e.g., fostering feelings of pride, prestige, self-efficacy, and job security) (Farooq & Salam, 2020; Mao et al., 2021) gains. 4.3. Cluster #3: Customer-level HCSR research Customer-level HCSR research primarily focuses on examining the impact of HCSR on customer intentions/behaviors and the quality of customer-company relationships. In this research stream, several customer-centered HCSR initiatives are frequently discussed, such as CSR communication (e.g., Line et al., 2016; Perez et al., 2019), CSR/green/sustainable marketing (e.g., Zhang et al., 2021b), corporate environmental responsibility (CER)/environmental CSR (e.g., Parsa et al., 2015), green hotels (e.g., Gao & Mattila, 2014), philanthropy/charity/giving/donation (e.g., Bae, 2023), and food health management (e.g., Kim & Ham, 2016). These frequently mentioned terms underscore the diverse ways in which HCSR can influence customer relations, perceptions, attitudes, intentions, choices, and actions. 4.3.1. HCSR and customer behavioral intentions and actions HCSR plays a significant role in shaping customers’ decision-making processes, behavioral intentions, and actual behaviors, encompassing intentions/actions related to both in-role (buying and consuming) and extra-role (voluntary) aspects of being consumers. Regarding in-role consumption behaviors, HCSR exerts an impact on consumers’ intentions to purchase (Lee et al., 2016) or to (re)visit (Ahn, 2020; Hu & Dang-Van, 2023) and willingness to pay premiums for green products (Kang et al., 2012). This effect arises from two key rationales: First, CSR actions (e.g., green hotels and products with eco-labels) function as valuable competitive strategies to differentiate the focal firm from its competitors within the fiercely competitive hospitality industry (Heikkurinen, 2010), thus enhancing the focal firm’s attractiveness to customers within this industry. Second, CSR acts as a signal or indicator of product quality and corporate/brand reputation or overall image for customers (Ahn, 2019; Han et al., 2019; Liu et al., 2014), reducing in perceived risks inherent in customers’ purchasing decisions, especially with uncertain intangible hospitality offerings (Nicolau, 2008). This active role of CSR nurtures trust and facilitates exchange relationships between buyers and hospitality sellers. HCSR can also impact customers’ voluntary behaviors beyond their expected roles, such as value co-creation behaviors (Raza et al., 2020; Sung & Lee, 2023; Yen et al., 2020), (green) customer citizenship behaviors (e.g., advocacy, feedback, helping, and tolerance) (Aljarah, 2020; Nguyen & Chiu, 2023) and customer donations (Huang & Liu, 2020). This impact occurs because CSR helps hospitality businesses build collaborative relationships with customers, possibly due to customers’ improved organizational identification and self-efficacy (Raza et al., 2020; Sung & Lee, 2023). These mechanisms share similarities with those underlying HCSR’s influence on employee behaviors. It’s worth noting that the scope of value co-creation behaviors is broader, encompassing both customer citizenship behaviors and customer participation behaviors (e.g., information seeking, information sharing, personal interactions with service providers and other customers) (Alqayed et al., 2022; Carvalho & Alves, 2023). Moreover, certain customer voluntary behaviors (e.g., PEBs and customer donations) are components of micro-CSR. Additionally, despite the increased efforts of many hospitality firms to adopt green practices in response to customer demand for environmental protection (Afifah & Asnan, 2015), customers remain skeptical about the sincerity of these efforts (Zhang & Hanks, 2017). This skepticism has led to accusations of “greenwashing” and customers often question whether the corporate primary motive behind HCSR initiatives is genuinely altruistic or driven by self-interest (i.e., CSR motive attributions). The skepticism and self-interest attributions of CSR motives have reduced customer engagement in hospitality green programs (Chen & Petersen, 2022), brand advocacy (Aljarah et al., 2022), and decreased the likelihood of repeat visits to hospitality firms (Rahman et al., 2015). 4.3.2. HCSR and customer-company relationship quality Besides directly examining the relationship between HCSR and customer consumption behaviors, extensive research has also investigated the impact of HCSR on customer relationship quality, which serves as a significant antecedent of customers’ in-role and extra-role behavioral intentions or actions. Existing literature has examined the influence X. Peng et al.

Journal of Hospitality and Tourism Management 57 (2023) 284–302 294 of HCSR on various dimensions of customer relationship quality, with many of these being the same indicators employed to evaluate the quality of employment relationships. The identical indicators mainly include (organizational/brand) identification (Huang et al., 2017; Martinez & del Bosque, 2013), commitment (Ahmed et al., 2020a; de Leaniz & del Bosque, 2015), trust (Martinez & del Bosque, 2013), satisfaction (Lee et al., 2020; Lee & Heo, 2009; Prayag et al., 2019), feelings of gratitude (Nguyen & Chiu, 2023), compassion (Hughes & Scheyvens, 2021), (brand) prestige (Han et al., 2020), (green hotel) pride (Lin et al., 2023) and engagement (Bilro et al., 2018, 2019; Yen et al., 2020). Additionally, some indicators receive substantial emphasis in the evaluation of customer relationship quality, such as loyalty (Huang et al., 2017; Latif et al., 2020; Martinez & del Bosque, 2013), attitudes (attitudinal loyalty) (Line et al., 2016; Xu & Gursoy, 2015), (e) WOM (Ali et al., 2021; Jalilvand et al., 2017; Lee et al., 2016; Su et al., 2017), emotional (brand) attachment (Nguyen & Chiu, 2023; Sung & Lee, 2023) and delight (i.e., the progression of satisfaction) (Ramkissoon et al., 2020). As mentioned earlier, relationship quality components are interrelated instead of independent. Therefore, extensive research examining the impact of HCSR on dimensions of customer relationship quality further investigates the mutual mediation among these dimensions. The representative causal pathway, HCSR → identification/trust/satisfaction/commitment → loyalty (de Leaniz & del Bosque, 2015; Swimberghe & Wooldridge, 2014), highlights how HCSR initiatives foster customer loyalty by increasing customers’ identification with the brand, building trust in the company, enhancing satisfaction, or strengthening commitment with the seller. Furthermore, previous studies have investigated additional causal relationships among identification, trust, satisfaction, and commitment (de Leaniz & del Bosque, 2015; Fatma & Rahman, 2017; Su et al., 2017). For instance, Martinez and del Bosque (2013) established a causal chain: HCSR → identification → trust → satisfaction → loyalty. They argue that HCSR initiatives promote customer identification with the company, subsequently building trust. This trust, in turn, fosters higher customer satisfaction, ultimately resulting in heightened customer loyalty. This logical progression highlights how HCSR can impact various dimensions of customer relationship quality in a sequential manner. 5. Discussion and conclusions 5.1. Integrated framework By employing bibliometric and content analysis on a dataset of 765 articles focusing on HCSR, this study sheds light on the accomplishments and trends within this research domain. Our work identifies three prominent research streams within the HCSR domain: firm-level HCSR research, employee-level HCSR research, and customer-level research. The firm-level research stream encompasses four subthemes: HCSR dimensions and forms, HCSR predictors, and the HCSR-CFP link, alongside an examination of HCSR within the context of COVID-19. Employeelevel and customer-level HCSR research concentrates on delineating the impact of HCSR on employee/customer in-role and extra-role behaviors or behavioral intentions and on the quality of relationships between employees/customers and hospitality firms. We have developed an integrated framework for HCSR research based on our findings, as illustrated in Fig. 4. This framework emphasizes that the focal points of this field are the antecedents and consequences of HCSR, as well as the clarification of its classification and operationalization, which form the foundation for empirical studies. More specifically, research on HCSR antecedents highlights the predictive role of external incentives (linked to institutional or stakeholder pressures and the task environment) and internal “RPV”: resources (including capabilities), processes (and structures), and values, primarily shaped by managerial cognitions. In addition, our framework suggests that CSR characteristics, highly associated with its Fig. 4. Integrated framework of HCSR research Notes: asterisks (*) and dashed arrows denote underexplored areas in current research and point towards potential future research directions. Text in red font signifies areas of paramount importance for future research. X. Peng et al.

Journal of Hospitality and Tourism Management 57 (2023) 284–302 295 classifications and forms, significantly influence its diffusion among hospitality firms. For instance, CSR initiatives, such as donations, energy conservation, and green hotels, which exhibit higher levels of visibility, appropriability (the potential to extract economic benefits from CSR projects), and centrality (the degree to which CSR aligns with the corporate mission or vision) (Burke & Logsdon, 1996; Husted & Allen, 2009), are more likely to be embraced by hospitality firms compared to those with lower visibility, appropriability, and centrality. Regarding research on HCSR consequences, our framework suggests that HCSR can impact CFP both directly and indirectly. The indirect impact occurs through enhancing sustainability performance (e.g., CSP and CEP) and improving operational performance (with a focus on nurturing resources and capabilities). Sustainability performance, primarily reflected in improving the psychological and physical well-being of natural and social stakeholders, can strengthen stakeholder relations, subsequently leading to positive in-role and extra-role behaviors among stakeholders. These behaviors, in turn, contribute to improvements in sustainability performance, operational performance, and CFP. Our work significantly contributes to the scholarship on HCSR by deepening the understanding of its overall landscape and central themes. Our study also provides practical insights for practitioners, guiding the formulation of effective CSR strategies and policies that align CSR efforts with the needs of various stakeholders. This alignment enhances sustainability performance, optimizes the returns on CSR investments, and fosters sustainable corporate growth. 5.2. Overall assessment of HCSR research In light of our findings, it is evident that previous research generally demonstrates the following characteristics: First, existing research has focused on exploring the antecedents and outcomes of HCSR, yet it has paid limited attention to HCSR implementation strategies. The prevailing cause-and-effect research primarily addresses the question of whether to engage in CSR, often with a focus on CSR adoption decisions. However, contemporary hospitality enterprises are undergoing a paradigm shift, moving from deliberations on whether to adopt CSR practices to the more intricate considerations of how to implement CSR effectively and enhance the returns on CSR investments. Second, over two-thirds of HCSR studies concentrate on the microindividual level, which sharply contrasts with the CSR research profile in the general management field, where organizational-level CSR research is more prevalent. This disparity may stem from the significant role of micro-level customer and employee engagement in achieving firm-level CSR objectives in the hospitality service industry, where production and consumption occur simultaneously. However, it’s worth noting that individual-level HCSR research designs often exhibit a degree of convergence. For instance, numerous studies have focused on the impact of HCSR on the four key dimensions of business stakeholder relationship quality. Additionally, individual-level research primarily focuses on general customer and employee responses to HCSR, with limited attention given to responses and CSR expectations from other stakeholders. Third, HCSR research, particularly when investigating HCSR antecedents, often falls short of capturing the distinctive features of the hospitality sector. For example, the existing literature identifies very few HCSR predictors that reflect the hospitality context’s uniqueness. In fact, many of these identified factors have been confirmed in general management (e.g., three institutional pressures, slack resources, CEO’s narcissism), which raises the concern that much of the research on HCSR may be stuck in a “reinventing the wheel” situation. Fourth, research on HCSR impacts lacks extensive dialogue across levels. For instance, firm-level research mainly focuses on the effects of HCSR on CFP with limited attention to stakeholder outcomes. In contrast, individual-level research primarily investigates the impacts of HCSR on stakeholder outcomes related to their well-being, improved relationships, and behaviors without considering their ultimate effects on CFP. This separation fails to address whether and how stakeholderlevel consequences influence organizational-level outcomes. However, it’s important to note that some stakeholder in-role behaviors, such as employee job performance and customer purchasing behavior, directly contribute to CFP and do not necessitate further exploration. 5.3. Future directions Fig. 4 also presents future research directions marked with asterisks (*) and dashed arrows, with a specific emphasis on the following areas (highlighted in red font in the figure): (1) HCSR theories that reflect the uniqueness of the hospitality context. Using HCSR antecedent research as an illustration, it is worth noting that property owners represent a crucial stakeholder group with significant influence on HCSR decisions (Khatter et al., 2021), yet they have received limited attention in previous studies. Future research should delve into the intricate dynamics of how conflicting pressures stemming from property owners and hotel management companies shape the HCSR decisions made by hotel general managers. Specifically, property owners may prioritize cost control over CSR, whereas mimic pressures from peer hotels operating under the same management company may compel general managers to align their CSR investments with those of their peer establishments. Another promising direction for further research is examining whether the high proportion of international visitors exerts influence on HCSR investments, as international travelers are more likely to rely on CSR reputations to mitigate perceived risks associated with their international accommodation choices. Furthermore, future research should also devote more attention to the unique features of the hospitality context at both the organizational level (e.g., business operational models, hotel company rankings based on room numbers, and hotel locations) and the managerial level (e. g., travel experiences) and explore their impacts on HCSR. Such inquiries could greatly enhance our understanding of CSR decisions in the hospitality context. (2) Exploring implementing strategies to maximize the return on HCSR investment. The societal and environmental benefits of CSR are evident, making the enhancement of its value for businesses a crucial step toward achieving a win-win situation. This, in turn, can foster greater corporate engagement in CSR. Accordingly, future research should prioritize investigating implementing strategies to maximize HCSR returns. While existing research suggests that effective HCSR communication strategies may contribute to boosting HCSR returns (Kim & Kim, 2019; Perez et al., 2019; Vinzenz et al., 2019), this alone is insufficient. Several CSR studies within general management may offer valuable insights. For instance, Husted and Allen (2007, 2009) have established a significant correlation between CSR’s visibility, centrality, specificity/appropriability, and the business value creation of CSR. Additionally, drawing on absorptive capacity perspective, Tang et al. (2012) have identified that firms experience more benefits when they employ CSR engagement strategies characterized by consistency, relatedness, and path with an internal CSR starting point. Furthermore, Madsen and Rodgers (2015) have uncovered that disaster relief CSR initiatives, which are executed more promptly (urgency), involve partner NGOs (legitimacy), and include in-kind contributions (enactment), are more effective in capturing stakeholder attention and consequently enhancing CFP. In the future, HCSR research can build upon these insights to explore implementing strategies for augmenting HCSR returns, thereby deepening our understanding of how CSR can be mutually beneficial for both corporations and society. X. Peng et al.

Journal of Hospitality and Tourism Management 57 (2023) 284–302 296 (3) Expanding HCSR research to encompass a broader range of stakeholders and incorporate insights from multiple perspectives and levels. In future research, greater attention should be given to the expectations and feedback on HCSR from stakeholders beyond typical customers and employees. The underrepresented stakeholders include property owners and hotel management companies mentioned earlier, as well as tour guides, local residents, and vulnerable groups. For instance, vulnerable groups like ethnic minorities, the LGBT community, and individuals with disabilities are more prone to encountering discrimination and bias. Hence, future studies should delve into the perspectives of these marginalized groups regarding HCSR policies and contribute to developing more inclusive HCSR strategies. In addition, future studies should integrate diverse theories and investigate across levels to directly examine the intricate mechanisms through which elevated sustainability performance and the enhanced social welfare of stakeholders, resulting from HCSR, impact firm performance over both shortterm and long-term timeframes. Financial disclosure statement The authors declare that they have no financial interests or relationships that may be relevant to the research presented in this paper. Declaration of competing interest The authors declare that there is no conflict of interest to disclose in relation to this research. Appendix Table 12 The results of co-occurrence analysis for theme identification Cluster Index Keywords Occurrences↓ Links Total link strength Firm-level HCSR research CSR 711 99 4987 CFP 338 99 2556 sust./resp. practices 198 96 1523 hotels 192 96 1430 hospitality 167 99 1293 mgt. 153 97 1187 envir. mgt./practices 129 95 1016 firms 112 94 830 (eco/tech/ …) inno. 76 94 604 strategies/strategic mgt. 74 88 549 risk mgt. 46 77 307 perspectives 40 76 300 inst. pressure/logics 39 75 282 compet. advantage 37 73 330 COVID-19 37 65 234 ethics 37 74 251 (CSR/eco-/strategic) orient. 36 71 285 TMT. 35 67 264 China 33 70 253 governance 32 56 205 supply chain mgt. 32 68 281 stakeholder theory 30 62 239 capabilities. 28 68 215 frameworks 25 64 188 (slack) resources/rbv 23 64 195 (stakeholder) collab. 22 59 157 empirical analysis 22 59 183 (task) environment 21 65 175 developing countries 20 56 153 international. 19 46 113 literature review 19 49 148 (CSR) stakeholders 17 47 132 ownership 16 34 85 SME 16 43 124 quality mgt. 15 50 116 waste mgt. 15 43 115 Employee-level HCSR research OCB(E) 97 89 873 mediators 95 95 837 (envir./SR) commitment 90 92 772 employees 70 84 569 moderators 70 92 551 (ethical/ …) leadership 64 82 532 (green/SR) hrm 64 77 533 org. identi. 64 83 520 employee satisf. 56 84 467 (CSR) engage. 55 86 441 identification 52 85 454 green behaviors 50 76 444 work 43 67 335 envir. performance 38 59 329 org. support 27 66 234 (continued on next page) X. Peng et al.

Journal of Hospitality and Tourism Management 57 (2023) 284–302 297 Table 12 (continued ) Cluster Index Keywords Occurrences↓ Links Total link strength envir. cognitions 26 69 221 job performance 25 52 205 SEM 25 73 223 values 23 70 175 employee (dis)engage. 22 57 183 (csr/green) culture/climate 21 56 192 (employee) well-being 17 51 141 CSR perceptions 16 50 150 meaningfulness 16 49 138 turnover (intent.) 16 53 142 Customer-level HCSR research impacts 218 99 1695 cus. satisf. 148 94 1247 antecedents 122 97 1004 (CSR) communication 115 88 793 cus. loyalty 94 90 815 (purch./visit) intent. 92 91 746 restaurants 85 88 627 (service) quality 81 89 617 customers 68 81 522 models 68 89 532 behaviors 67 88 509 trust 64 79 519 (green) image 54 76 428 attitudes 54 81 408 reputation 54 78 463 decision. 42 75 276 guest (purch.) behaviors 41 74 297 (CSR/sust.) marketing 39 71 256 consequences 39 79 328 (e)WOM 36 69 272 CER 31 73 265 green hotels 30 72 253 TPB 28 66 219 charity. 27 60 174 emotions 26 68 212 knowledge mgt. 26 71 216 service 26 69 201 value (co)creation 24 62 185 (brand) equity 23 60 173 experiences 23 61 183 responses 22 60 171 attributions 21 62 170 brand/cus. identi. 20 46 182 guest perceptions 20 58 160 guest engage. 19 46 135 self 17 51 135 (un)ethical/green consum. 16 53 128 health/healthy food 16 45 100 scale dev. 15 52 122 References Aboramadan, M., et al. (2021). Examining the effects of environmentally-specific servant leadership on green work outcomes among hotel employees: The mediating role of climate for green creativity. Journal of Hospitality Marketing & Management, 30(8), 929–956. Afifah, N., & Asnan, A. (2015). The impact of corporate social responsibility, service experience and intercultural competence on customer company identification, customer satisfaction and customer loyalty (case study: PDAM Tirta Khatulistiwa Pontianak West Kalimantan). Procedia-Social and Behavioral Sciences, 211, 277–284. Aguinis, H., & Glavas, A. (2012). What we know and don’t know about corporate social responsibility: A review and research agenda. Journal of Management, 38(4), 932–968. Afridi, S. A., et al. (2023). Impact of corporate social responsibility attributions on employee’s extra-role behaviors: Moderating role of ethical corporate identity and interpersonal trust. Corporate Social Responsibility and Environmental Management. Ahmed, I., et al. (2020a). Investing in CSR pays you back in many ways! The case of perceptual, attitudinal and behavioral outcomes of customers. Sustainability, 12(3). Ahmed, M., et al. (2020b). Impact of CSR and environmental triggers on employee green behavior: The mediating effect of employee well-being. Corporate Social Responsibility and Environmental Management, 27(5), 2225–2239. Ahn, J. (2019). Corporate social responsibility signaling, evaluation, identification, and revisit intention among cruise customers. Journal of Sustainable Tourism, 27(11), 1634–1647. Ahn, J. (2020). Understanding the role of perceived satisfaction with autonomy, competence, and relatedness in the CSR context. Journal of Sustainable Tourism, 28 (12), 2027–2043. Ahn, J. S., et al. (2020). Narcissistic CEOs and corporate social responsibility: Does the role of an outside board of directors matter? International Journal of Hospitality Management, 85, 8. Al-Ghazali, B. M., & Afsar, B. (2021). Green human resource management and employees’ green creativity: The roles of green behavioral intention and individual green values. Corporate Social Responsibility and Environmental Management, 28(1). Al-Swidi, A. K., et al. (2021). The joint impact of green human resource management, leadership and organizational culture on employees’ green behaviour and organisational environmental performance. Journal of Cleaner Production, 316. Alejandro, T. B., et al. (2011). The outcome of company and account manager relationship quality on loyalty, relationship value and performance. Industrial Marketing Management, 40(1), 36–43. Ali, W., et al. (2021). Corporate social responsibility and customer loyalty in food chainsmediating role of customer satisfaction and corporate reputation. Sustainability, 13 (16). Ali, M. A., et al. (2023). How does environmental corporate social responsibility contribute to the development of a green corporate image? The sequential mediating roles of employees’ environmental passion and pro-environmental behavior. Business Ethics the Environment & Responsibility. Aljarah, A. (2020). The nexus between corporate social responsibility and target-based customer citizenship behavior. Journal of Sustainable Tourism, 28(12), 2044–2063. X. Peng et al.

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