Journal of Hospitality and Tourism Management

Journal of Hospitality and Tourism Management 57 (2023) 143–144 144 discussions throughout the book. This chapter also draws in-depth conclusions about research gaps and problems. This book signifies a crux of the tourism formation that focuses on two important components, which are: 1) lack of labor laws that allow tourists and/or 2) employees who serve tourists to work in substandard conditions. The second component consists of various cases related to family violence. This is an important yet under-researched topic in the tourism and events literature that will attract researchers and practitioners in this topic, as well as the examination of family violence, social work, health, and law. Eliyunus Waruwu* , Delipiter Lase, Maria Magdalena Bate’e Department of Management at Faculty of Economics and Business, Nias University, Indonesia * Corresponding reviewer. E-mail addresses: [email protected] (E. Waruwu), [email protected] (D. Lase), [email protected], [email protected] (M.M. Bate’e). Book review

Journal of Hospitality and Tourism Management 57 (2023) 130–132 Available online 22 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. Book Review Entrepreneurship in Indonesia From Artisan and Tourism to Technology-based Business Growth, First Edition (Edited by Vanessa Ratten), ISBN 9781032035253. This book is interesting because it examines the growth of entrepreneurship in Indonesia, ranging from handicraft and cultural businesses to technology-based forms of digital entrepreneurship. This book also emphasizes the importance of focusing on categories such as crafts, tourism, and sustainability to facilitate the growth of digital-based startups. This book aims to explain how Indonesia became a dominant world power through its entrepreneurial endeavors. In addition, the focus on the tourism sector indicates an awareness of the economic potential associated with the tourism industry in Indonesia. In the digital era, digital platforms and information technology can play an essential role in promoting Indonesian tourist destinations and increasing accessibility for tourists. The importance of sustainability is also highlighted in this book. In an entrepreneurial context, sustainability can refer to a socially and environmentally responsible business approach. This book discusses how digital-based startups can adopt sustainable business practices and positively contribute to society and the environment. Before reviewing each chapter, we’ll talk a little about the author of this book, Vanessa Ratten. He is a distinguished scholar in the fields of entrepreneurship and management education. She has contributed to various research fields, including entrepreneurship education, women entrepreneurship, craftsman entrepreneurship, cultural entrepreneurship, sustainable entrepreneurship, collective entrepreneurship in developing countries, and the impact of COVID-19 on entrepreneurship. Vanessa Ratten’s research contributions have provided valuable insights into various aspects of entrepreneurship, contributing to understanding entrepreneurship in different contexts and informing future research directions. The first chapter of the book "Indonesian Entrepreneurship: Origins, Conceptualization, and Practice" reviews entrepreneurship in Indonesia and highlights the need for further research in this field. This chapter emphasizes the importance of studying entrepreneurship in the Indonesian context separately from other countries, as Indonesia is undergoing rapid change and has unique cultural, political, and environmental factors. This chapter also examines the diverse nature of entrepreneurship in Indonesia, including business ventures and discovery opportunities. It is noted that the digitization of business transactions has shaped the entrepreneurial landscape in Indonesia and requires a deeper understanding of the contextual factors that drive individuals to pursue entrepreneurial opportunities. Furthermore, this chapter examines the role of the individual entrepreneur, organizations, and networks in Indonesian entrepreneurship. It emphasizes the cultural element in Indonesian entrepreneurship because cultural institutions and values influence the type and number of entrepreneurs. This chapter also mentions the long tradition of entrepreneurship in Indonesia, particularly in inter-island trade and local customs and traditions. This chapter acknowledges the limited research on Indonesian entrepreneurship compared to North America and Europe, despite Indonesia’s fast economic growth and emphasis on entrepreneurship, particularly in inter-island trade and local customs and traditions. This chapter acknowledges the limited research on Indonesian entrepreneurship compared to North America and Europe, despite Indonesia’s fast economic growth and emphasis on entrepreneurship, particularly in interisland trade and local customs and traditions. This chapter acknowledges the limited research on Indonesian entrepreneurship compared to North America and Europe, despite Indonesia’s fast economic growth and emphasis on entrepreneurship. The second chapter, "Artisan Entrepreneurship in Indonesia," explores the concept of artisan entrepreneurship in Indonesia. This chapter highlights the importance of the handicraft industry in preserving cultural traditions and contributing to economic development. But apart from this, some things could be improved in this chapter. First, this chapter tends to provide an overly optimistic picture of artisanal entrepreneurship in Indonesia without providing an in-depth analysis of the challenges and obstacles faced by artisanal entrepreneurs. Although it is stated that they have adapted to digital technology, it is not explained in detail how they overcome obstacles such as technological accessibility and limited resources. Second, This chapter also needs a balanced perspective between cultural and business aspects of artisanal entrepreneurship. While it is important to maintain cultural heritage through producing artisanal goods, it needs to explain in detail how artisanal entrepreneurs manage business aspects such as marketing, operational management, and financial sustainability. In addition, this chapter also needs to describe the role of government and policies that support the development of artisanal entrepreneurship in Indonesia. The government has an essential role in creating a conducive environment for artisanal entrepreneurs through education, training, and market access policies. In this case, this chapter can be enriched with further research that digs deeper into the challenges and obstacles faced by artisanal entrepreneurs. The third chapter, "Food Artisan Entrepreneurship in Indonesia," explores the entrepreneurial concept of food artisans in Indonesia. This chapter focuses on the role of food in Indonesian culture and the relationship between art and culinary traditions. It highlights the diversity of Indonesian cuisine, which is influenced by the country’s colonial, immigrant, and indigenous history. This third chapter provides exciting insight into the role of artisanal entrepreneurship in the Indonesian food industry. However, there are some criticisms of this chapter. First, this chapter gives an overly generalized picture of artisanal entrepreneurship in the food industry in Indonesia. There needs to be an in-depth analysis of the challenges and obstacles faced by artisanal food entrepreneurs, such as market competition, licensing, or limited market access. Second, This chapter must provide a balanced perspective between 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.2023.08.022 Received 29 July 2023; Received in revised form 28 August 2023; Accepted 30 August 2023

Journal of Hospitality and Tourism Management 57 (2023) 130–132 131 cultural and business aspects of artisanal food entrepreneurship. While it is important to maintain cultural heritage through artisan food production, it does not explain in detail how artisan food entrepreneurs manage business aspects such as marketing, operational management, and financial sustainability. In addition, this chapter also needs to describe the role of government and policies that support the development of artisanal food entrepreneurship in Indonesia. The government has an essential role in creating a conducive environment for artisanal food entrepreneurs, including through education, training, and market access policies. The fourth chapter, "Knowledge Management and Artisan Entrepreneurship in Indonesia," explores the relationship between knowledge management and craftsman entrepreneurship. There have been several criticisms of this chapter. First, this chapter gives an overly general picture of knowledge management in Indonesia’s artisanal entrepreneurship context. There needs to be an in-depth analysis of how artisan entrepreneurs manage their knowledge, such as collecting, storing, and sharing their expertise in producing and marketing artisanal products. Second, this chapter needs to provide concrete examples or case studies that illustrate the application of knowledge management in artisanal entrepreneurship in Indonesia. Specific examples will help readers understand how knowledge is applied in everyday business practice. In addition, this chapter needs to describe the impact of knowledge management in improving the performance and sustainability of artisanal entrepreneurship in Indonesia. There needs to be a discussion of how knowledge management can help artisanal entrepreneurs meet challenges and take advantage of opportunities in the artisanal food industry. In this regard, this chapter can be enriched with further research that digs deeper into the practice and benefits of knowledge management in artisanal entrepreneurship in Indonesia and concrete examples illustrating its application. In conclusion, although this chapter provides an overview of knowledge management in artisanal entrepreneurship in Indonesia, there needs to be more in-depth analysis, concrete examples, and an understanding of impact. Further research is required to enrich knowledge management experience in the context of artisanal entrepreneurship in Indonesia. The fifth chapter, "Indonesian Migrant Entrepreneurs: A Comparison of Two Cohorts in Malaysia," comprehensively analyzes Indonesian migrant entrepreneurs in Malaysia. Some of the comments from this chapter are: First, this chapter tends to give an overly general description of Indonesian migrant entrepreneurs in Malaysia. There is no indepth analysis of the factors that influence the success or failure of Indonesian migrant entrepreneurs, such as skills, capital, or social networks. Second, this chapter lacks an in-depth comparison between the two cohorts of Indonesian migrant entrepreneurs in Malaysia. Neither analysis compared the two cohorts’ background, experience, or business strategy differences. Besides that, this chapter also lacks a description of the impact of Indonesian migrant entrepreneurship on the Malaysian and Indonesian economies. There is no discussion of the economic contribution of Indonesian migrant entrepreneurs in Malaysia or the effect of repatriating the capital and knowledge they bring back to Indonesia. In this regard, this chapter could be enriched by further research that digs deeper into the factors influencing the success of Indonesian migrant entrepreneurs in Malaysia, a more in-depth comparison between migrant entrepreneur cohorts, and the economic impact of Indonesian migrant entrepreneurship. The book’s sixth chapter focuses on "Technology Entrepreneurship in Indonesia." This chapter explores the role of digital technology in shaping Indonesian entrepreneurship and discusses the various types of startups that have sprung up in the country. This highlights the growing interest in entrepreneurship among Indonesian entrepreneurs seeking new strategies to respond to market needs and develop alternative income-generating activities. In addition, there are several reviews of this chapter. First, this chapter gives an overly generalized picture of technology entrepreneurship in Indonesia. There is no in-depth analysis of the factors influencing the success or failure of tech startups in Indonesia, such as access to capital, technical skills, or government support. Second, This chapter needs to provide concrete examples or case studies illustrating developments and challenges in technology entrepreneurship in Indonesia. Specific examples will help readers understand how technology startups in Indonesia deal with market changes, competition, and regulations. In addition, this chapter needs to broadly describe technology entrepreneurship’s impact on the Indonesian economy and society. There is no discussion of how technology startups contribute to job creation, increased productivity, or solutions to social and environmental problems in Indonesia. In this regard, this chapter can be enriched with further research that digs deeper into the factors that influence the success of technology startups in Indonesia. The book’s seventh chapter presents a “cross-sectional study conducted from 2013 to 2016 to identify the factors that influence entrepreneurship in Indonesia.” This study uses data from the Global Entrepreneurship Monitor (GEM) database, a comprehensive observatory on entrepreneurship worldwide. There have been several criticisms of this chapter. First, this chapter is limited to a relatively short period, namely 2013–2016. This may limit our understanding of the factors influencing entrepreneurship in Indonesia. Studies involving a more extended period can provide a more comprehensive picture of changes and trends in entrepreneurship in the country. Second, This chapter needs to provide an in-depth analysis of the factors influencing entrepreneurship in Indonesia. The information provided is limited to social, perceptual, and economic variables without a detailed explanation of how these variables interact and influence each other. In addition, this chapter needs to describe the methodology used in this study. There needs to be an explanation of how the data was collected, how the sample was selected, or how the statistical analysis was carried out. This information is essential to ensure the validity and reliability of the findings in this study. In this regard, this chapter could be enriched with more in-depth research and detailed methodology. The eighth chapter of the book explores the topic of "rural entrepreneurship and social innovation in Indonesia." This chapter highlights the importance of the agricultural sector in Indonesia and examines the role of rural industry in driving economic growth and competitiveness. There have been several critical reviews of this chapter. First, this chapter gives an overly general picture of Indonesia’s rural entrepreneurship and social innovation. There needs to be an in-depth analysis of the factors influencing the success or failure of rural entrepreneurship or how social invention can be effectively implemented in rural settings. Second, this chapter needs concrete examples or case studies illustrating developments and challenges in Indonesia’s rural entrepreneurship and social innovation. Specific examples will help the reader understand how rural entrepreneurship and social innovation can provide real solutions to social and economic problems in rural areas. In addition, this chapter needs to broadly describe rural entrepreneurship and social innovation’s impact on rural communities. There is no discussion of how rural entrepreneurship and social innovation can improve the welfare of rural communities, create jobs, or strengthen local communities. In this regard, this chapter can be enriched with further research that digs deeper into the factors that influence the success of rural entrepreneurship, concrete examples that illustrate developments and challenges in rural entrepreneurship and social innovation. The book’s ninth chapter discusses "Indonesian Entrepreneurship: Future Directions." This chapter acknowledges the limited research on Indonesian entrepreneurship and highlights the need to explore this topic further. It emphasizes the importance of understanding the unique context of Indonesian entrepreneurship and its implications for entrepreneurial behavior. Some reviews of this chapter. First, this chapter gives an overly general picture of the direction of entrepreneurship development in Indonesia. There is no in-depth analysis of the factors that will affect entrepreneurship in the future, such as changes in technology, government policies, or market trends. Second, this chapter needs to provide concrete examples or case studies that illustrate the direction of entrepreneurship development in Indonesia. Specific Book Review

Journal of Hospitality and Tourism Management 57 (2023) 130–132 132 examples will help readers understand how entrepreneurship in Indonesia might develop in different contexts, such as technology-based entrepreneurship, social entrepreneurship, or rural entrepreneurship. In addition, this chapter also needs to describe the practical implications of the direction of entrepreneurship development in Indonesia. There needs to be a discussion of how this development direction might influence government policy, entrepreneurship education, or support for entrepreneurs. In this regard, this chapter can be enriched with further research that digs deeper into the factors that will influence entrepreneurship in the future. These concrete examples illustrate the direction of entrepreneurship development in Indonesia and the practical implications of this direction of growth. After reviewing each chapter, we get the strengths of this book, which is a comprehensive exploration. This book explores various aspects of entrepreneurship in Indonesia, from craft and cultural businesses to forms of digital entrepreneurship. This provides a deep understanding of the multiple forms of entrepreneurship that exist in Indonesia. Then, there is an emphasis on cultural and institutional factors. This book highlights the importance of understanding Indonesia’s cultural and institutional context in developing entrepreneurship. This helps the reader to understand the factors influencing the growth and development of entrepreneurship in this country. Another advantage is focusing on relevant categories. This book emphasizes the importance of focusing on categories such as crafts, tourism, and sustainability in facilitating the growth of digital-based startups. It provides insight into the opportunities and challenges that exist within these sectors. There is also an understanding of the role of entrepreneurship in economic development. This book explains how entrepreneurship is essential for Indonesia’s economic growth. This provides inspiration and motivation for readers who are interested in getting involved in the world of entrepreneurship. The global context is relevant. This book also highlights how Indonesia became a dominant world power through its entrepreneurial endeavors. This provides a perspective that is relevant to current global economic developments. Overall, this book offers valuable insight into the dynamics of entrepreneurship in Indonesia, spanning a variety of factors and contexts. Funding The Lembaga Pengelola Dana Pendidikan (LPDP) supports this article’s publication. Irfan Wildzan Muafaa,* , Dewi Putri Anjar Wulanb a Faculty of Economics and Business, Musamus University, Indonesia b Faculty of Economics and Business, Airlangga University, Indonesia * Corresponding reviewer. E-mail addresses: [email protected] (I.W. Muafa), dewi.putri. [email protected] (D.P.A. Wulan). Book Review

Journal of Hospitality and Tourism Management 57 (2023) 72–73 Available online 10 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. Book review Entrepreneurship in Indonesia From Artisan and Tourism to Technology-based Business Growth (Edited By Vanessa Ratten), ISBN 9781032035253 Book Link : https://www.routledge.com/Entrepreneurship-inIndonesia-From-Artisan-and-Tourism-to-Technologybased/Ratten/p/book/9781032035253. This book “Entrepreneurship in Indonesia From Artisan and Tourism to Technology-based Business Growth” consists of nine chapters. In this book, there is an in-depth exploration of the reality of entrepreneurship in Indonesia, highlighting the uniqueness and dynamics that underlie the country’s economic development. While other countries in Asia such as China and India have become the main focus of research in the entrepreneurship domain, Indonesia is emerging as a significant entity in the context of global economic growth. Although not widely known in the literature. The first chapter substantially discusses important aspects of understanding entrepreneurship in Indonesia. By focusing on three different levels of analysis (individual, organizational and network), this chapter provides a rich and comprehensive view of the dynamics of entrepreneurship in the Indonesian context. In addition, this chapter provides a solid initial understanding of the importance of understanding entrepreneurship in an emerging market context. This helps open new views of how entrepreneurship operates in an emerging economic environment, which has unique dynamics. Then the second chapter, provides an in-depth explanation of what craftsman entrepreneurship is, how the craftsmen work, and how the craftsmen’s products have their own unique characteristics. This provides a clear understanding of the essence of craftsman entrepreneurship. In addition, this chapter introduces the concept of artisan entrepreneurship as a form of culture-centered entrepreneurship. This allows artisans to incorporate cultural and economic values into their business endeavors. The third chapter, this chapter is still related to the previous chapter on artisans in Indonesia. This chapter places a strong emphasis on the concept of entrepreneurship in the context of crafts, particularly in the food industry in Indonesia. This helps open up insight into how culture, innovation and tradition play a role in the development of craft businesses. In addition, this chapter highlights the importance of local products in supporting the local economy, cultural preservation, and quality of life. Local handicraft products are attractive because of their high quality and their relation to tradition. Then chapter four, this chapter is interesting because readers are invited to explore the entrepreneurial world of craftsmen who are rich in culture and knowledge. This chapter describes the important role of the artisan entrepreneur in connecting culture with profitable business practices. Craft entrepreneurs are not only product creators, but also community glues and agents of change in society. By combining anthropological, sociological and entrepreneurial perspectives, this chapter creates interdisciplinarity that reveals the diversity and depth of the issues discussed. The hallmark of this chapter is the insight the author presents on how knowledge and culture can be managed effectively in a craftsman entrepreneurial environment, creating valuable insights for readers interested in the worlds of business and culture. Chapter five discusses the results of research from Hamizah Abd Hamid on the role of technology entrepreneurship by comparing Indonesia and Malaysia. The subjects of this study were 5 respondents who migrated to Malaysia in the range 1969–1990. It was found that one main reason for these respondents leaving Indonesia was the financial crisis. Thus, entrepreneurs migrate to Malaysia to develop and operate their businesses. Malaysia was chosen as the destination country due to cultural and geographical proximity between the two and having a large population to serve as future entrepreneurial opportunities for entrepreneurs between the two countries. The qualitative research methods used in this chapter provide in-depth and comprehensive insight into the experiences and views of IMEs. Through interviews with key informants related to social and economic associations, this research was able to unravel the complex nuances in the embeddedness and dynamics of IMEs. Furthermore, the sixth chapter, in this sixth chapter, discusses technology entrepreneurship in Indonesia. This chapter provides an overview of how digital economic growth based on knowledge and technology can change the economic paradigm in Indonesia. This transformation not only creates new business opportunities, but also changes the face of the economy as a whole. By providing concrete examples of how technological innovation is changing the business landscape, this chapter illustrates the important role entrepreneurship plays in driving progress and change in the digital age. The seventh chapter, in this chapter the author reviews in depth the characteristics, influences, and determining factors that also influence the presence and growth of entrepreneurship in Indonesia. Within this framework, the presentation of this report aims to provide in-depth insight into the important elements driving entrepreneurial activity in Indonesia during the intended time period. That the very vital role of entrepreneurship in the economic context has been revealed very clearly, adding to the urgency to understand how the direction of its development, which depends on a number of various decisions in various sectors, especially in encouraging the promotion of entrepreneurship in various fields and segments, through the implementation of various economic policies and diverse social. The results of research conducted between 2013 and 2016 explored the impact of various variables, such as age, education level, gender, and social and economic influences, which turned out to have a significant influence on entrepreneurship in Indonesia. Turning to the eighth chapter, the author explains the importance of the agricultural sector in Indonesia. In this realm, rural industries play a crucial role in driving growth and increasing competitiveness. The focus on forming entrepreneurial farmers who continue to innovate in agriculture is very relevant, because this is considered an important foundation for making a better 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.2023.09.002 Received 17 August 2023; Accepted 4 September 2023

Journal of Hospitality and Tourism Management 57 (2023) 72–73 73 contribution to the national economy. In this case, the research conducted may reveal how entrepreneurial scenarios occur in rural areas of Indonesia and the use of social innovation in dealing with various social challenges, while creating positive social impacts in the region. This research may also track the various strategies, practices and initiatives adopted by rural entrepreneurs and social innovators to drive economic growth, create opportunities and improve the welfare of rural communities in Indonesia. As such, this research sheds light on the fundamental role of entrepreneurship and social innovation as agents of change in the context of rural development, creating sustainable sources of livelihoods, and embracing social transformation in the Indonesian reality. The ninth chapter, as the concluding chapter, carefully explores and discusses the direction and potential developments in the field of entrepreneurship in Indonesia. By observing the current state of entrepreneurship in Indonesia and identifying new trends, challenges and opportunities that might shape the future direction of entrepreneurship in the country, this research provides insights that are rich in meaning. The purpose of this research is to provide valuable insights and recommendations for policy makers, business actors, and other parties involved to encourage and support the entrepreneurial ecosystem in this country going forward. In addition, it is also possible to explore various innovative strategies and cutting-edge technologies that have the potential to play an important role in shaping the future of entrepreneurship in Indonesia, by contributing to economic growth and the development of society as a whole. The conclusion in this book is that this book is able to explain comprehensively the potential development of entrepreneurship in Indonesia. This book is a call to understand that Indonesia has become a more prominent player in the global entrepreneurial arena. In realizing its goal of becoming a major world power through entrepreneurial endeavors, Indonesia is able to generate energy that shapes new directions on the global stage. With a unique foundation of creativity, innovation and entrepreneurial spirit, Indonesia has gone beyond its role as a beneficiary of the global economy and has turned into a creator of change that can shape a more dynamic and inclusive global economic paradigm. Acknowledgement Funding: This article is sponsored by the Lembaga Pengelola Dana Pendidikan (LPDP), The Ministry of Finance of the Republic of Indonesia. Mutiya Oktariani* Training and Education, Musamus University, Indonesia Adrianus Aprilius Faculty of Economics and Business, Airlangga University, Indonesia E-mail address: [email protected]. Prima Lestari Situmorang Training and Education, Musamus University, Indonesia E-mail address: [email protected]. * Corresponding author. E-mail address: [email protected] (M. Oktariani). Book review

Journal of Hospitality and Tourism Management 57 (2023) 145–147 Available online 6 October 2023 1447-6770/© 2023 The Authors. Published by Elsevier Ltd. on behalf of CAUTHE - COUNCIL FOR AUSTRALASIAN TOURISM AND HOSPITALITY EDUCATION. All rights reserved. Book review Heritage entrepreneurship cultural and creative pursuits in business management, Edited by Vanessa Ratten, Palgrave Macmillan Singapore, 2023, XIVþ169 pp, DOI: https://doi.org/10.1007/978-981-19-5149-7, ISBN 9789811951497, EUR 149.99. In recent years, Increasing attention has been focused on the critical role of cultural heritage in entrepreneurial contexts. This also includes maintaining regional economic stability (Muˇstra, Peri´c, & Pivˇcevi´c, 2023) As the impact of globalization and technological developments continue to change the business landscape, entrepreneurs are increasingly seeking innovation from cultural heritage and the creative arts to develop unique and sustainable business models (Petrescu, Namin, & Richard, 2023; Szromek, 2022; Wang, Li, Ruan, Zhang, & Li, 2023). The adaptive use of cultural heritage can increase positive externalities, such as community convenience, public goods and social interaction (Kee, 2019). This book collects 9 articles to provide readers with a comprehensive understanding of tourism development with a cultural heritage concept, both theoretically and in practical management. Moreover, this book can provide valuable guidance for governments, practitioners, communities, and the general public interested in combining cultural and creative elements in business strategy. The author began the book by explaining the importance of new theories related to Heritage entrepreneurship in the first chapter. Heritage entrepreneurship is a unique field that aims to understand and solve social issues. It is shaped by external forces such as technological advances and increased interest in culture. It requires additional research to become a recognized subfield of entrepreneurship studies. Heritage entrepreneurship scholars can integrate how heritage shapes and is shaped by entrepreneurship by building on the work of scholars in other disciplines. After discussing the significance of literacy concerning to the new theory of heritage entrepreneurship, the primary purpose of this unique field of entrepreneurship is to describe and predict various ways heritage can be used in business practices. Chapter 2 explores social entrepreneurship in Thailand, which has been a significant player in the social enterprise ecosystem, with the government actively establishing the Pracharath Rak Samakee (PRS) scheme. PRSs with high public awareness must appropriately manage public and private tensions. They should approach the opposites through impact measurement, connecting, a third space, and dialogue to do this. It is critical to establish a third space for political just measurement practice. PRSs and related social enterprises in Thailand should embrace just measurement, providing stakeholder rights to objective measurement and stakeholder rights to be objectively measured. Interestingly, the authors in this book pay close attention to the development of the heritage tourism business by making the promotional aspect one of the methods to increase awareness of all parties. Thus, this is explored in more depth in the third chapter regarding the role of trust and support in promoting social innovations in tourism destinations. Trust is crucial for guiding local actors’ behaviors and enabling the mobilization of resources. Trust and support are mutually dependent, since they facilitate the connection and utilization of resources within a relationship characterized by confidence. The local environment, which encompasses elements such as culture, customs, people, territory, and intangible values, plays a crucial role in promoting active and collaborative engagement. Leads to the generation of innovation and the co-production of value. Nevertheless, the chapter acknowledges certain constraints, notably the absence of empirical investigation. Future research could explore the relationship between trust and support, potentially mediating the relationship and promoting sustainability issues. The chapter also emphasizes the importance of policymakers and local entrepreneurs in triggering social innovation processes within the entrepreneurial ecosystem. Promoting innovation and growth can positively impact local entrepreneurship, the entrepreneurial ecosystem, and the entire local territory. In Chapter 4, the authors proceed to examine a series of empirical studies that have delved into the investigation of 18 family enterprises in Indonesia. These studies have employed a qualitative technique to gather and analyze data. Four distinct innovation techniques were developed, namely: driven innovators employing a deferred strategy, let-it-flow innovators employing a survival strategy, ad-hoc innovators employing an emergent strategy, and experienced innovators employing a systematic strategy. These techniques have the potential to offer a more comprehensive framework for innovation initiatives in family businesses, particularly in cases where the nature of the business is distinct and contingent upon certain contextual factors. Nevertheless, the research fails to distinguish between several sectors within family enterprises, such as service-oriented firms as opposed to manufacturing firms, or knowledge-intensive firms vs those that are not knowledgeintensive. In order to enhance the existing body of research on family business and innovation, it is imperative for future studies to take into account the following factors. In addition, Chapter 5 delves into the correlation between legacy entrepreneurship, informal entrepreneurship, and the entrepreneurial environment, conducting an analysis of more than 400 documents spanning the years 1991–2021. The study identified three primary clusters: green, associated with informal and formal institutions, institutional theory, entrepreneurial ecosystems, and unproductive entrepreneurship; red, encompassing aspects of informality and entrepreneurial ecosystems such as culture, gender equality, social capital, emerging economies, social entrepreneurship, entrepreneurial intention, resilience, entrepreneurial universities, and small firms; and blue, consisting of elements related to informal and formal entrepreneurship, institutional credibility migration, and youth. The salient subjects that establish a connection between informal heritage entrepreneurship and the entrepreneurial ecosystem encompass ethnic diversity, ethnic heritages, market relationships, entrepreneurship in South-Asian nations, and entrepreneurs during socialist periods, as well as their implementation from social and educational standpoints. 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.2023.09.010 Received 9 September 2023; Accepted 21 September 2023

Journal of Hospitality and Tourism Management 57 (2023) 145–147 146 The preceding chapter explored worldwide academic research about informal and heritage entrepreneurship within various documented literature sources accessible through the ISI Web of Science database spanning 31 years (1991–2021), employing bibliometric and content analysis methodologies. Subsequently, in the ensuing four chapters, the discussion revolves around the manifestations of heritage entrepreneurship in several countries across the globe. For instance, in Chapter 6, researchers elucidate the ramifications of the Covid-19 pandemic on the tourism sector within the Alpine Mountain region of Switzerland. Tourism is a pivotal factor within the economic sector (Jaggi, ¨ 2022). The Swiss Alpine Mountains have remained a globally renowned tourist destination, albeit experiencing a decline in visitor numbers. The Swiss government is actively addressing this issue by fostering growth within the hospitality industry. Encouragingly, the authors provide several solutions, including the convergence of tourism and work, the reduction of innovation gaps within micro, small, and medium-sized enterprises (SMEs) in the tourism sector, the significance of governmental and political support, and the importance of a multi-local lifestyle. Ultimately, the authors underscore the necessity for the tourism sector, particularly Alpine destinations, to adopt a customer-centric approach to optimize services and positively impact regional tourism. Understanding customer-centricity is pivotal for various future innovations (Madsen, 2020). In Chapter 7, the authors focus on Italy as a host of “world heritage sites,” where the tourism sector is intimately intertwined with culture and history. Among these sites are Monte San Giorgio, which harbors a significant number of marine fossils primarily from the Triassic period; The Aeolian Islands; Venice; Val d’Orcia; The Sassi; Urbino; Piedmont Langhe-Roero and Monferrato; Syracuse and its Necropolis; Villa Romana del Casale; Villa Adriana; the Sacred Mountains of Piedmont and Lombardy; the Amalfi Coast; Christian Monuments of Ravenna; the Dolomites; the Arab-Norman Palermo and the Cathedral Churches of Cefalù; the Archaeological Areas of Pompeii, Herculaneum, and Torre Annunziata; the Church and Dominican Convent of Santa Maria delle Grazie; the Cilento and Vallo in Diano National Park; the Certosa; the Orto Botanico; the Archaeological Area and Patriarchal Basilica of Aquileia; the Royal House of Savoy; Assisi, the Basilica of San Francesco, and Franciscan Sites; the Royal Palace of Caserta; and the City of Verona. Importantly, the authors succinctly convey the locations and significant histories behind these heritage tourism destinations. Italy holds a crucial position as a world cultural tourism destination, which significantly impacts its economic and social development. Moving to the more detail analysis about this topic, in chapter 8 the authors elucidate that the United States, like Italy as previously discussed in the preceding chapter, is also home to World Heritage Sites (WHS). Therefore, in this section, the exploration focuses on heritage tourism destinations located on the American continent, with particular attention to the United States as a compelling subject for research in the realms of tourism and entrepreneurship development (Rashid & Ratten, 2022). There are indeed at least 24 properties in the United States that are designated as World Heritage Sites (WHS), as detailed in this chapter. These sites encompass a wide range of cultural and natural significance, as recognized by UNESCO. The United States stands out as a unique country in terms of its heritage sites. Each WHS holds a distinct allure for individuals, stemming from its unique cultural and natural attributes. Therefore, the development of the tourism sector is of paramount importance when viewed from a personal perspective, considering the diverse heritage that exists within the country. Chapter 9 serves as both the conclusion and the culmination of this book, where the author delves into future trends related to heritage entrepreneurship. The uniqueness of heritage endeavors, which integrate heritage and business goals, offers opportunities for the market to continually innovate and address various challenges. This underscores the critical importance of understanding heritage entrepreneurship. The author presents a heritage entrepreneurship model that takes into account influencing factors such as location, history, management structure, stakeholder involvement, and competitive dynamics. This model highlights various future challenges, including market competition, resource availability, time constraints, and entrepreneurial thinking patterns. Heritage entrepreneurship has far-reaching impacts on society, socio-economic aspects, and stakeholders. Building an entrepreneurial ecosystem is crucial within heritage entrepreneurship, but the author introduces a novel idea: the necessity of cross-sector collaboration, supported by strong leadership as a driving force. The author also suggests intriguing research avenues that warrant further exploration in the realm of heritage entrepreneurship. Heritage is inherently complex, considering its multifaceted nature, encompassing socio-cultural, human and non-human, geographical and digital elements, innovation acceleration, cross-disciplinary studies, and the analysis of both positive and negative impacts of heritage entrepreneurship. The author provides valuable insights regarding the potential development of heritage entrepreneurship, making it an essential area for academic inquiry in this chapter. This book provides a wealth of crucial information concerning the potential and significance of contemporary heritage entrepreneurship development. It offers an intensive exposition complemented by supporting analyses. Readers can readily comprehend a spectrum of subjects, starting from the theory of heritage entrepreneurship, its relationship with government, innovation, and strategies, to the mapping of existing research and how an individual’s personal interest in heritage sites in a specific country can underscore the importance of heritage entrepreneurship. Notably, the concluding section of this book serves as a veritable “treasure trove,” particularly for academics, as it identifies numerous prospective research themes related to heritage entrepreneurship that remain ripe for comprehensive examination. Overall, this book is recommended for a diverse readership, encompassing entrepreneurs, governmental authorities, policymakers, academics, as well as enthusiasts of history, nature, and culture across various global organizations. Its explications are comprehensible, concise, and effectively present key points. Nevertheless, it is imperative to heed the author’s concluding message, which underscores that heritage entrepreneurship is a unique and intricate entrepreneurial domain, thus warranting multifaceted investigations that continue to hold substantial potential for in-depth examination. Acknowledgments The authors wish to express their gratitude to the Lembaga Pengelola Dana Pendidikan (LPDP) Indonesia for their financial support during the publication process and for facilitating the dissemination of this paper. References J¨ aggi, C. J. (2022). Economic importance of tourism. In C. J. Jaggi ¨ (Ed.), Tourism before, during and after corona: Economic and social perspectives (pp. 27–46). Springer Fachmedien. https://doi.org/10.1007/978-3-658-39182-9_3. Kee, T. (2019). Sustainable adaptive reuse – economic impact of cultural heritage. Journal of Cultural Heritage Management and Sustainable Development, 9(2), 165–183. https://doi.org/10.1108/JCHMSD-06-2018-0044 Madsen, S. M. (2020). Gaining customer centric understanding of retail displays for future innovations. International Journal of Retail & Distribution Management, 49(4), 491–513. https://doi.org/10.1108/IJRDM-08-2019-0280 Muˇstra, V., Peri´c, B.S., ˇ & Pivˇcevi´c, S. (2023). Cultural heritage sites, tourism and regional economic resilience. Papers in Regional Science, 102(3), 465–482. https://doi.org/ 10.1111/PIRS.12731 Petrescu, M., Namin, A., & Richard, M. O. (2023). Technology within cultures: Segmenting the wired consumers in Canada, France, and the USA. Journal of Business Research, 164(April), Article 113972. https://doi.org/10.1016/j. jbusres.2023.113972 Rashid, S., & Ratten, V. (2022). Subsistence small business entrepreneurs in Pakistan. Small Enterprise Research, 29(2), 109–137. Szromek, A. R. (2022). Value propositions in heritage tourism site business models in the context of open innovation knowledge transfer. Journal of Open Innovation: Technology, Market, and Complexity, 8(3), 161. https://doi.org/10.3390/joitmc8030161 Wang, M. Y., Li, Y. Q., Ruan, W. Q., Zhang, S. N., & Li, R. (2023). Influencing factors and formation process of cultural inheritance-based innovation at heritage tourism destinations, 2024 Tourism Management, 100, Article 104799. https://doi.org/10.1016/ j.tourman.2023.104799. Book review

Journal of Hospitality and Tourism Management 57 (2023) 145–147 147 Mohammad Rofiuddin* Doctoral of Economics Program, Airlangga University, Surabaya, East Java, Indonesia Rodame Monitorir Napitupulu Doctoral of Islamic Economics Program, Airlangga University, Surabaya, East Java, Indonesia E-mail address: [email protected]. Ega Rusanti Department of Islamic Economics, Airlangga University, Surabaya, East Java, Indonesia E-mail address: [email protected]. * Corresponding reviewer. E-mail address: [email protected] (M. Rofiuddin). Book review

Journal of Hospitality and Tourism Management 57 (2023) 258–259 Available online 2 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. Book Review Towards sustainable and resilient tourism futures: Insights from the International Competence Network of Tourism Research and Education (ICNT) (Edited by Anne Kochling, ¨ Sabrina Seeler, Peet van der Merwe, Albert Postma) ISBN 9783503211951, DOI: https://doi. org/10.37307/b.978-3-503-21195-1, 2023, 252 pp. In an increasingly globalized world, the tourism industry ranks as the third-largest industry after the chemical and fuel industries, generating 1.7 trillion US Dollars (USD) (Amin & Taghizadeh-Hesary, 2023). This serves as evidence that tourism must be preserved. On the other hand, the COVID-19 pandemic has led to a significant decline in visitors as a result of government policies such as regional quarantine and border closures (Prayag, 2023). Dodds Toronto and Butler (2010) depict the necessity of studying the implementation of tourism policies to achieve sustainable tourism. Therefore, this book is highly suitable for providing reference and recommendations for crafting a resilient and sustainable tourism industry policy. This book discusses “Towards Sustainable and Resilient Tourism Futures.” Within the book, there are four main topics: First, it covers sustainability: the attitude and behavior of selected tourist groups, which consists of 3 chapters; second, it explains the management of wildlife protection with 2 chapters; third, it comprises the management of sustainability aspects by industry stakeholders, consisting of 3 chapters; and finally, it discusses “Towards Sustainable and Resilient Tourism Futures: Strategies to Overcome COVID-19 Induced Issues,” which includes 4 chapters. In the discussion of Part 1 of the book, in the first chapter, the author highlights the significant level of consumer interest in the sustainability options introduced by tour operators. The author emphasizes that travelers want vacation packages to align with sustainability standards. Therefore, tour operators are key to introducing sustainable practices into their offerings. Sustainability in the next chapter revolves around the importance of volunteers in the workforce and in realizing sustainable tourism. However, there were doubts about volunteer tourists’ involvement in sustainable tourism development. In the end, those from Germany, Austria, and Switzerland who are interested in volunteer tourism tend to be more inclined towards engaging in resilient and sustainable travel in the future. The more complex discussion presented in the third chapter pertains to the environmental impacts and sustainable development in relation to tourism. The author explains that the high cost of travel is seen as a barrier to the growth of tourism, as some travelers are deterred from visiting Antarctica. This is because only individuals with good income and social status can afford to go. Not only is the travel expensive, but also some environmentally unaware tourists pose a threat to Antarctic wildlife by potentially exacerbating global warming. However, the distinctive features and uniqueness of Antarctic tourism cannot deter tourists from visiting as long as they promote Antarctica’s protection, and some of them dedicate themselves to its conservation. In this case, the professionalism of the expedition team is crucial in establishing strict regulations and environmental education to ensure the preservation of Antarctica’s environment and sustainable development. Moving on to Part 2, it discusses the management of wildlife protection. The research findings in the first chapter reveal that the sense of responsibility held by tourists is crucial in preserving the habits of Hawaiian green sea turtles while sunbathing on the beach. Consequently, this supports two strategies that can be implemented in Ho’okipa Beach Park in the future: providing a dedicated area for visitors to observe sunbathing turtles and introducing a fee that visitors must pay, which will be used for maintenance costs. In the second chapter, the author explains that what is needed in the whale-watching industry is industry regulation. This is because unregulated activities can worsen the condition of individual cetaceans, populations, and habitats, potentially harming the tourism industry. The results indicate that there are still shortcomings in the tourism industry in achieving sustainability. The author suggests that there is a gap due to the absence of clear LAC (Limits of Acceptable Change) criteria. Therefore, four recommendations will be implemented, including: (i) establishing clear LAC criteria and evaluation period; (ii) strengthening social science research; (iii) enhancing monitoring and law enforcement; (iv) improving knowledge exchange among different stakeholders. Part 3 focuses on the management of sustainable aspects by industry stakeholders. In the first chapter, the author observes Finnish tourists who booked travel during the COVID-19 pandemic. The pandemic has brought attention to the importance of realizing the impact of travel on global warming, making it crucial and necessary. Consequently, travel intermediaries are attempting to explore opportunities within the travel sector to create value for their customers. The method employed involves collecting questionnaires from consumers of the Association of Finnish Travel Industry (SMAL). This research indicates a shift in the thinking of Finnish tourists towards greater responsibility when traveling abroad. These findings also contribute to the understanding of changes in tourist behavior regarding awareness of responsibility and sustainability. Moving on to the second chapter, it discusses Circular Economics (CE) in tourism and services from a Nordic perspective. This chapter explains that the role of the public sector is also significant concerning regulations, incentives, and infrastructure to develop CE structures. Market participants should be aware that the solutions they implement must be tied to sustainability to increase the number of consumers who are increasingly mindful of their responsibilities regarding consumption and travel. In the final chapter, the ease of access to tourism education for the future of tourism from the perspective of educators and caregivers for people with disabilities is discussed. From the literature the author obtained, tourism education fails to reflect the abilities and knowledge required to address people with disabilities in the tourism industry. At the same time, traditional tourism still faces challenges in preparing 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.2023.09.011 Received 29 August 2023; Accepted 21 September 2023

Journal of Hospitality and Tourism Management 57 (2023) 258–259 259 individuals to serve people with disabilities within the tourism sector. Participants also agreed on the importance of understanding that people with disabilities are also essential in the tourism industry. Based on the findings of this research, it is recommended to establish a new framework for tourism education that will contribute to improving accessibility in the future. Part 4 is the concluding section of the book. In the first chapter, the author attempts to categorize market segmentation, profiles, and travel motivations of scuba diving tourists in Ponta do Ouro, Mozambique. The author has successfully identified five market segment clusters for the scuba diving market in Ponta do Ouro, namely socializers, novice enthusiasts, casuals, advanced fanatic divers, and novice fanatic divers. This information is expected to be used by scuba diving operators in Ponta do Ouro to enhance their products and develop better marketing strategies, especially in the post-COVID-19 era. In the second chapter, the author observes the impact of COVID-19 on ecotourism and the local community in Wadi El Gemal National Park (TNWG), Egypt. Like other locations worldwide, TNWG has also been affected by the COVID-19 pandemic, resulting in a decrease in ecotourism visitors. To address the COVID-19 shock, stakeholders of the national park and beneficiaries of ecotourism have collaborated to design and implement a COVID-19 Crisis Management Plan to mitigate its impact. The findings from this research can assist policymakers in formulating strategies to ensure the long-term management of community-based ecotourism initiatives within an evolving operational environment caused by the pandemic. Tourism researchers need to respond to the influence of the COVID19 pandemic on family vacation behavior. Widely recognized quarantine and social distancing policies during the pandemic created an opportunity window for “Quaran-cation,” referring to quarantine vacations. This is the focus of discussion in the third chapter. Traveling by motorhome provided the possibility for Chinese families living in New Zealand to undertake travel during/post COVID-19. The proposed conceptual framework indicates opportunities for tourism authorities and marketers to identify comprehensive factors for the promotion and enhancement of a more sustainable and resilient future tourism postCOVID-19. The final chapter discusses the impact of the COVID-19 pandemic on domestic tourism in the Sub-Saharan Africa (SSA) region. Using a retrospective approach to explain the paradoxes related to domestic tourism in this region, this chapter presents constraints on promoting domestic tourism as a vector for the tourism sector. Relevant cases and policy documents will provide recommendations to mitigate the pandemic’s impact and constraints to ensure a more sustainable and resilient future for domestic tourism post-pandemic. After the COVID-19 pandemic ends, the revival of the tourism sector must be carried out promptly. The impact of tourism resilience and sustainability can also affect the country’s economic conditions. Therefore, this book is worth reading because it provides guidance for academics, stakeholders, government officials, and tourism managers that can be used as policy-making materials to ensure the resilience and sustainability of tourism are maintained. Acknowledgments The authors of scholarship recipients would like to thank for Lembaga Pengelola Dana Pendidikan (LPDP) for supporting us in the process of publishing this paper. References Amin, S. B., & Taghizadeh-Hesary, F. (2023). Tourism, sustainability, and the economy in Bangladesh: The innovation connection amidst Covid-19. Economic Analysis and Policy, 79, 153–167. https://doi.org/10.1016/j.eap.2023.06.018 Dodds Toronto, R., & Butler, R. W. (2010). Barriers to implementing sustainable tourism policy in mass tourism destinations. Tourismos: An International Multidisciplinary Journal of Tourism, 5(1), 35–53. Prayag, G. (2023). Tourism resilience in the ‘new normal’: Beyond jingle and jangle fallacies? Journal of Hospitality and Tourism Management, 54, 513–520. https://doi. org/10.1016/j.jhtm.2023.02.006 Moh. Amru* Department of Economics, Airlangga University, Surabaya, Indonesia Moh. Nur Khaqiqi Department of Economics, Airlangga University, Surabaya, Indonesia E-mail address: [email protected]. Linda Rahmawati Department of Management, Gadjah Mada University, Yogyakarta, Indonesia E-mail address: [email protected]. * Corresponding reviewer. E-mail address: [email protected] (Moh. Amru). Book Review

Journal of Hospitality and Tourism Management 57 (2023) 40–47 Available online 8 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. Bridging the gap of bibliometric analysis: The evolution, current state, and future directions of tourism research using ChatGPT Hakseung Shin a , Juhyun Kang b,* a School of Tourism, College of Social Science, Hanyang University, 222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Republic of Korea b Department of Tourism Management, Jeju National University, Jeju-Daehakro 102, Jeju-Si, 63243, Republic of Korea ARTICLE INFO Keywords: Generative artificial intelligence (GAI) ChatGPT Bibliometric analysis Tourism research Knowledge structure Research agenda ABSTRACT ChatGPT can generate coherent text with unprecedented fluency by processing massive amounts of text data. Given the chatbot’s remarkable accuracy in responses to a wide range of topics, this research aims to examine the evolution, present status, and future directions of tourism research using ChatGPT. A total of 15 interview questions were developed and semi-structured interviews were conducted with ChatGPT. The responses were qualitatively analyzed to identify the main themes associated with the issues of tourism research, such as key topics of previous research, forces to influence the evolution, achievement and limitations of research, and under examined areas of research. The use of ChatGPT provided valuable insights into the latest progressions within tourism research. For example, unlike the widely held view adopted by most tourism studies, ChatGPT indicates that the interdisciplinary nature of tourism research strongly contributes to the development of other academic fields, suggesting the maturity of tourism research. 1. Introduction ChatGPT is an AI-based generative language model developed by OpenAI to generate high-quality human-like text by predicting the next word based on context (Radford et al., 2019). ChatGPT is exposed to a wide-ranging and extensive amount of data obtained from publicly accessible internet sources, including websites, books, articles, blogs, and forums. This exposure enables the model to generate responses on a diverse array of topics (Brown et al., 2020, pp. 1–25). During pre-training, the model learns to predict the next word in a sentence based on the context of the preceding words, allowing it to understand grammar, semantics, and context (Radford et al., 2019). The training data includes scholarly materials, along with other types of publicly accessible text. However, the model does not differentiate between the types of sources or have access to proprietary databases (Hill-Yardin et al., 2023). The training data used in ChatGPT is fixed at a certain point in time, and the model does not automatically update with new data. Instead, any updates or improvements typically come from the fine-tuning process, where the pre-trained model is further trained on specific tasks or datasets to make it more useful or tailored for particular applications (Brown et al., 2020, pp. 1–25; Radford et al., 2019). While the primary objective of ChatGPT is to promote the development of AI in a secure and beneficial manner (OpenAI, 2021), its usage has substantial impacts on society because of its innovative and revolutionary functions to process large volumes of data, identify patterns of previous and present trends, analyze complex phenomena, and predict the future by analyzing previous events (Dogru et al., 2023; Lund & Wang, 2023). In addition, ChatGPT is likely to transform the operation processes of tourism and hospitality businesses, including service delivery, human resource management, back-of-house operations, employee training, and management decision-making (Ali, 2023; Carvalho & Ivanov, 2023; Dogru et al., 2023). ChatGPT can be used for various purposes owing to its innovative design and functions to understand and interpret user requests and complete complex tasks. After having conversations with ChatGPT on several issues regarding the future of jobs, businesses, and technologies, Karakas (2022) argues that ChatGPT can be used to generate new ideas, forecast, and develop strategies for the future. In addition, ChatGPT can be used for academic purposes. Lund and Wang (2023) argue that ChatGPT can help scholars find answers to domain-specific academic questions associated with the intellectual structure, evolution, and future research direction of a certain scholarly domain. In addition, * Corresponding author. E-mail addresses: [email protected] (H. Shin), [email protected] (J. Kang). 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.2023.09.001 Received 28 March 2023; Received in revised form 31 August 2023; Accepted 3 September 2023

Journal of Hospitality and Tourism Management 57 (2023) 40–47 41 Iskender (2023) interviewed ChatGPT to understand the impact of ChatGPT on higher education, academic work, and hospitality and tourism industries. The results concluded that ChatGPT may aid academic work, but it cannot replace human creativity and originality due to its lack of novelty in generated outputs. Recently, one of the primary concerns of tourism researchers has been to systematically analyze the intellectual structure of tourism research to further develop tourism knowledge (Kim et al., 2018; Sigala et al., 2021). In line with this research trend, a large body of bibliometric tourism studies has been published to diagnose the progress of overall tourism and hospitality literature (e.g., Guzeller & Celiker, 2019; Kim et al., 2018; Leong et al., 2021; Sigala et al., 2021), in addition to examining the evolution of certain research topics, such as corporate social responsibility (Coles et al., 2013), knowledge management (Abdollahi et al., 2023), tourism development (Bianchi, 2018), gender (Small et al., 2017), innovation (Shin & Perdue, 2022), and smart tourism (Mehraliyev et al., 2020). Furthermore, a body of tourism research has critically reviewed the evolution of tourism research methods (Fong et al., 2016; Rasoolimanesh et al., 2021). While the aforementioned studies have contributed to understanding the evolution of tourism research, most bibliometric tools adopted in such research have limitations associated with restricted databases and subjectivity in the interpretation of analyses (Koseoglu et al., 2022; Leong et al., 2021). This research aims to bridge this gap in existing literature by examining the evolution of tourism research, the current state of tourism research, and future directions of tourism research using the ChatGPT chatbot. In non-academic contexts, some attempts have been made to forecast the future using ChatGPT (e.g., Karakas, 2022; Mearian, 2023). Recently, a growing body of research has provided academic insights by interviewing ChatGPT or other AI-enabled tools (Iskender, 2023). Since academic research is relatively easier to analyze through well-established citation networks of scholarly data and the intensity of certain research topics (Yan & Ding, 2012), ChatGPT is an effective tool for analyzing scholarly data that is more refined and interconnected than other text data (Yan & Ding, 2012). Although this study assumes that ChatGPT is an effective tool to assess the progress of tourism research, it is important to emphasize that the validity of the results generated via ChatGPT requires further investigation. In fact, ChatGPT can generate false or misleading information (Carvalho & Ivanov, 2023; Dwivedi et al., 2023). For this reason, Iskender (2023) argued that outputs generated by ChatGPT or other AI tools should not be seen as a substitute for academic works performed by researchers. In addition, AI-based natural language processing, such as ChatGPT, can result in bias and unreliable information (Zhuo et al., 2023). Thus, the results of this study should never be considered as an “ultimate truth” while the study will only demonstrate how the most innovative AI technology evaluates the scientific progress of tourism research. The findings of the current study can help to complement the limitations of most bibliometric analyses associated with difficulties in processing large amounts of data and exposure to subjective bias. While most recent tourism research focuses only on the influence of ChatGPT or AI-enabled tools on tourism and hospitality education or overall research processes (Ali, 2023; Ivanov & Soliman, 2023; Skavronskaya et al., 2023), this research will be one of the initial tourism studies that adopts ChatGPT as a methodological tool for bibliometric purposes. 2. Methods 2.1. Research process Unlike traditional bibliometric reviews that depend on the identification and analysis of scholarly data, this research attempts to gain bibliometric insights into the scholarly progress of tourism research by conducting multiple semi-structured interviews with the ChatGPT-3.5 chatbot. Semi-structured interviews are a form of qualitative research in which participants are interviewed using open-ended questions, allowing for follow-up questions and discussions (Patton et al., 2015). Given that the quality of answers provided by ChatGPT is dependent upon the type of input (Montti, 2022), additional questions were asked to improve clarification and elaboration of the initial response, further explore issues, and gain a deeper understanding of the research topic. The responses comprised 12,342 words. 2.2. Development of the interview questions To develop questions regarding the evolution of tourism research, current state of tourism research, and future directions of tourism research, extensive reviews of bibliometric studies on tourism were conducted (e.g., Guzeller & Celiker, 2019; Kim et al., 2018). Subsequently, a set of questions to understand the progress of tourism research was identified through discussions with tourism researchers, including eight professors and seven Ph.D. researchers in the USA, China, and South Korea. Initially, 34 questions were developed and the importance of each question was evaluated. Some questions capturing similar content were combined. Finally, a set of 15 questions (five questions for each stage) was developed, as shown in Table 1. 2.3. Interview and data analysis A thematic analysis of the answers to each question was conducted to identify the key themes, patterns, or relationships in the data (Braun & Clarke, 2006). Specifically, a multi-order categorization analysis was performed to organize the response data according to the level of abstraction or specificity (Guest et al., 2012). While this method is useful Table 1 List of questions to ask ChatGPT. Evolution Questions Evolution of tourism research How do you think and evaluate the evolution of tourism research? What topics have been studied importantly in the development process of tourism research? What are the internal and external factors that have had a significant impact on the development of tourism research? What are the important achievements and limitations in the development of tourism research? How has research methodology evolved in the development of tourism research? Current state of tourism research How do you see tourism research standing compared to other academic fields? Do you think tourism knowledge is sufficiently accumulated through tourism research? Why? What are the similarities and differences between current tourism research and other academic fields? What are the most important topics in tourism research today? What are the limitations of recent tourism research and what are needed to supplement them? Future directions of tourism research What are the topics that tourism research needs to address in the future? What kind of efforts are needed to further develop tourism research in the future? What efforts should researchers make to supplement the limitations of tourism research and promote continuous development in the future? How do you think the research methodology of future tourism research should be developed? What should researchers pay particular attention to in order for tourism studies to continue to develop in the future? H. Shin and J. Kang

Journal of Hospitality and Tourism Management 57 (2023) 40–47 42 for analyzing interview transcripts with multiple dimensions and levels of meaning, it was especially helpful in developing a more nuanced understanding of the responses provided by ChatGPT. Table 2 is a summary of the thematic analysis, and Fig. 1 depicts the interview and data analysis processes adopted in the study. 2.4. Ethics in data collection and analyses As ChatGPT is an AI-based tool, ethical considerations were carefully considered for bibliometric data collection and analyses (Lund et al., 2023; Zhuo et al., 2023). These considerations encompassed issues such as data consistency and result validation. Table 2 A summary of thematic analysis results. Progress Themes Sub-themes Key findings Evolution of tourism research Nature of tourism research Interdisciplinary nature Focuses on analytical and interdisciplinary approaches Incorporation of new technologies and data sources Key topics Tourism planning and development Tourist behavior and psychology Tourism impacts Tourism marketing and management Tourism education and training Tourism technology Sustainable tourism Forces to influence the evolution Internal forces The emergence of new destinations, Advances in research methods Interdisciplinary collaboration External forces Technological advances Environmental issues Process of tourism research Achievements The impacts of tourism on host communities and destinations The identification of factors that influence tourist behavior The exploration of sustainable tourism practices that promote environmental conservation Limitations The lack of a unified theory of tourism The limited availability of reliable data The underrepresentation of the perspectives of local communities and stakeholders A need for greater engagement with industry stakeholders Methodological evolution Nature Qualitative and quantitative analyses The emergence of new methods Limitations Over-reliance on quantitative methods Limited generalizability Bias in data collection Current state of tourism research The current position of tourism research Impacts Effective in understanding the complex nature of society Contribute to the development of other academic fields Key topics Sustainable tourism Tourism and technology Tourism and the sharing economy Tourism and cultural heritage Tourism and economic development Tourism and destination management Under examined areas of research The impact of tourism on local communities The economic benefits and costs of tourism The impact of technology on the tourism industry Comparisons with other disciplines Similarities Interdisciplinary nature A focus on quantitative research methods Differences Applied nature of research issues A more holistic approach Limitations in current tourism research Limitations Lack of diversity in research perspectives Limited attention to emerging tourism markets Methods to overcome limitations Greater focus on community engagement Greater attention to emerging tourism markets Future directions of tourism research Tourism research development Promising research topics Tourism and health Tourism and social justice Tourism and climate change Tourism governance and policy Ways to improve research quality Collaboration and networking to develop innovative research The use of new technology to collect and analyze data more efficiently Knowledge transfer by interacting with the wider public Ways to improve research methodologies Participatory action research Mixed-methods systematic reviews Future research agenda about ChatGPT and tourism Destination management Tourism content assessment Sustainable tourism Tourism marketing and promotion Customer service in tourism Real-time travel recommendations Travel behavior Market forecasting. H. Shin and J. Kang

Journal of Hospitality and Tourism Management 57 (2023) 40–47 43 Initially, the researchers posed identical interview questions on multiple occasions to guarantee the coherence and uniformity of the collected data. The interviews were performed in February 2023, and the same questions were asked again two weeks after the initial interviews to compare the answers. While most answers were highly similar to the original answers, some minor differences were observed in the answers, which were included in the data analysis. Next, to improve the result validity and reduce subjective bias, two independent coders performed a thematic analysis and compared their findings. Any discrepancies in the analysis results were discussed until a consensus was reached. Additionally, to ensure further robustness, the final outcomes of the thematic analysis were reviewed by an expert in qualitative research who has published over three academic research papers in leading tourism journals based on qualitative data. Importantly, the expert was unaware that the interviews were conducted using ChatGPT, thereby minimizing the chance of a subjective bias towards AI-generated content. 3. Results 3.1. Evolution of tourism research Analytical and interdisciplinary nature of tourism research: According to ChatGPT’s responses, tourism research has moved towards analytical and interdisciplinary methodologies, aligning with the findings of the literature reviews conducted by Ruhanen et al. (2019) and Guzeller and Celiker (2019). In addition, the incorporation of new technologies and data sources have also had significant impacts on the evolution of tourism research, which supports the views of most tourism researchers (Darbellay & Stock, 2012; Xiang, 2018). There has been an increasing focus on interdisciplinary research, as tourism is a complex and multifaceted phenomenon that intersects with various fields such as economics, sociology, geography, psychology, and environmental science. Moreover, the rise of technology has also impacted tourism research, with the emergence of new data sources, such as social media and online review data. Key topics of previous tourism research: Seven key topics of previous tourism research were identified by ChatGPT, including tourism planning and development, tourist behavior and psychology, tourism impacts, tourism marketing and management, tourism education and training, tourism technology, and sustainable tourism. This discovery corroborates the outcomes of the bibliometric analyses performed by Guzeller and Celiker (2019) and Leong et al. (2021), who identified tourism motivation, travel behavior, tourism marketing, and online tourism as significant topics in earlier tourism research. Interestingly, ChatGPT has proposed the topic of tourism education and training, which has not been commonly regarded as a significant subject in the bibliometric research mentioned earlier. It was assumed that this outcome is related to the importance of human resource management in the tourism industry, including hiring, training, and retaining employees. Influential factors in the evolution of tourism research: ChatGPT identified several internal and external factors that influenced the evolution of tourism research. While it is relatively straightforward to pinpoint internal factors such as the discovery of new destinations, the development of research techniques, and collaborative efforts across different fields, external factors such as advancements in technology and environmental concerns are closely related to significant areas of research in tourism. These include sustainability and information technologies, which have received increased attention in previous studies (Gossling, ¨ 2017; Ritchie & Jiang, 2019). Technological advances: Technological advances, such as the Internet, social media, and mobile devices, have had a significant impact on the tourism industry, prompting researchers to explore the impact of these technologies on tourist behavior, marketing, and management. Environmental issues: Environmental issues, such as climate change, pollution, and resource depletion, have had a significant impact on the tourism industry and have prompted researchers to explore the role of tourism in environmental conservation and sustainable development. Achievements and limitations of tourism research: ChatGPT provided interesting answers regarding the achievements and limitations of previous tourism research. Regarding achievements, it suggests that tourism research allows us to better understand the impact of tourism on destinations, tourist behaviors, and sustainable tourism practices. There are several achievements of tourism studies. First, the development of theoretical frameworks that explain the impacts of tourism on host communities and destinations. Second, the identification of factors that influence tourist behavior, such as motivation, perception, and attitudes, which have helped tourism managers and policymakers to develop effective marketing and management strategies. Third, the exploration of sustainable tourism practices that promote environmental conservation, social responsibility, and economic benefits, which have helped to mitigate the negative impacts of tourism on the environment and local communities. ChatGPT has put forward the absence of a cohesive theory of tourism as a significant drawback of tourism studies, which reinforces the viewpoint presented in the literature review conducted by Ruhanen et al. (2019). The findings support the argument put forth by Stergiou and Airey (2018) that the advancement of the interdisciplinary field of tourism research can be impeded by the lack of original theories and tourist-centered data. In addition, the limited availability of reliable and comprehensive data, and the underrepresentation of the perspectives of local communities and stakeholders were also suggested. ChatGPT mentioned that further engagement with industry stakeholders and the wider public is necessary. Despite these achievements, there are also some limitations to the development process of tourism research, including the lack of a unified theory of tourism that can explain the complex and multifaceted nature of tourism. Another challenge is the limited availability of reliable and comprehensive data on tourism, particularly in developing countries and niche tourism markets. In addition, the underrepresentation of the perspectives of local communities and stakeholders in tourism research can lead to a narrow Fig. 1. Interview and data analysis processes. H. Shin and J. Kang

Journal of Hospitality and Tourism Management 57 (2023) 40–47 44 understanding of the impacts of tourism on these groups. Finally, there is a need for greater engagement with industry stakeholders and the wider public to ensure that tourism research is relevant and useful. The evolution of tourism research methods: ChatGPT stated that tourism research methodology has evolved significantly, with researchers adopting new techniques and tools to collect and analyze data more effectively. This discovery is consistent with the bibliometric analysis conducted by Shin and Perdue (2022), which found that the utilization of diverse research methods, including both qualitative and quantitative analyses, as well as innovative techniques like big data analysis and geographic information systems (GIS), has contributed to the reliability and accuracy of research findings in the field of tourism. In addition, ChatGPT pointed out some limitations of research methods adopted in tourism research, such as over-reliance on quantitative methods, limited generalizability, and bias in data collection. It is important to note that bias in data collection has not been widely discussed in the field of tourism. Over-reliance on quantitative methods: While quantitative methods have their strengths, an over-reliance on these methods can lead to a neglect of qualitative data, which can provide rich insights into the subjective experiences of tourists and other stakeholders. Limited generalizability: Tourism research often focuses on specific locations or populations, which can limit the generalizability of the findings to other contexts. Bias in data collection: Data collection in tourism research can be biased if it is conducted by researchers who have preconceived notions about the destination or population being studied. 3.2. Current state of tourism research Tourism research as a rapidly growing and dynamic field: ChatGPT stated that although tourism research is a relatively young academic field, it has made a significant impact on society and the economy. It was also mentioned that tourism research can be effective in understanding the complex nature of society owing to its interdisciplinary nature. Interestingly, ChatGPT stated that tourism research has contributed to the development of other academic fields as well. While the majority of tourism research tends to acknowledge the impact of other fields on its development (Benckendorff & Zehrer, 2013; Laws & Scott, 2015), ChatGPT’s response suggests a distinct perspective that tourism research has also influenced the development of other academic disciplines. This perspective has not been suggested in earlier literature review studies on tourism (Guzeller & Celiker, 2019; Kim et al., 2018; Leong et al., 2021). While tourism research may not be as established as some other academic fields, it is a rapidly growing and dynamic field that has a significant impact on various aspects of society and the economy. In addition, the interdisciplinary approach of tourism research allows tourism research to make valuable contributions to understanding the complex relationships between tourists, destinations, and the broader social, economic, and environmental contexts in which tourism operates. Tourism research also contributes significantly to the development of other academic fields such as urban planning, cultural studies, and environmental studies, among others. Unbalanced accumulation of tourism knowledge: Although ChatGPT stated that tourism research has contributed significantly to the accumulation of knowledge and understanding of the tourism industry, some areas still need further attention, such as the impact of tourism on local communities, the economic benefits and costs of tourism, and the impact of technology on the tourism industry. This response suggests that the accumulation of tourism knowledge focuses only on a few topics. Tourism research has produced a wealth of knowledge that has informed policy and practice in the tourism industry. For example, tourism research has led to the development of sustainable tourism practices, the promotion of responsible tourism behavior, and the identification of new tourism markets. However, there are still areas where more research is needed. For example, there is a need for more research on the impact of tourism on local communities and cultures, the economic benefits and costs of tourism, and the impact of technology on the tourism industry. Comparisons with other disciplines: ChatGPT clearly explained both the similarities and differences between tourism and other relevant research fields. While the similarities include an interdisciplinary nature and a focus on quantitative research methods, the differences are delineated in terms of research focus and scope. Specifically, tourism research puts more emphasis on practical issues and adopts a more holistic approach compared to other research fields. The discovery highlights the fact that while tourism research can effectively address practical issues, it is deficient in terms of theoretical advancements, as noted by Stergiou and Airey (2018). Focus of research: While other academic fields often have a more theoretical focus, tourism research tends to be more applied in nature, with a focus on addressing practical issues faced by the tourism industry. Research scope: Tourism research often takes a more holistic approach, examining the interactions between the tourism industry, tourists, and the local environment and communities, while other academic fields may have a more narrow focus. Important topics of tourism research: ChatGPT summarized several important research topics in current tourism research, such as sustainable tourism, tourism and technology, tourism and the sharing economy, tourism and economic development, and destination management. As Ruhanen et al. (2019) suggested, forthcoming research should embrace broader perspectives to encompass a comprehensive range of sustainability issues, including the sociocultural, economic, and political dimensions of sustainability in tourism. Sustainable tourism: This includes research on how to develop and promote tourism in a way that is environmentally and socially sustainable, and that benefits local communities. Tourism and technology: This includes research on the impact of technology on the tourism industry, such as the use of social media and online booking platforms. Tourism and the sharing economy: This includes research on the impact of sharing economy platforms, such as Airbnb and Uber, on the tourism industry and local communities. Tourism and cultural heritage: This includes research on how to preserve and promote cultural heritage through tourism, while also ensuring that local communities benefit from tourism activities. Tourism and economic development: This includes research on the economic benefits and costs of tourism, as well as research on how to maximize the economic benefits of tourism for local communities. Tourism and destination management: This includes research on how to manage and develop tourism destinations in a sustainable and responsible manner, while also balancing the needs of tourists and local communities. Limitations of current tourism research: ChatGPT suggested a lack of diversity in research perspectives and limited attention to emerging tourism markets as the main limitations of current tourism research. These limitations indicate that tourism research does not address tourists’ broader perspectives. Thus, further attention needs to be paid to emerging trends in the tourism industry, such as senior and medical tourism. Lack of diversity in research perspectives: There is a need for more research that considers a range of perspectives, including those of local communities, marginalized groups, and small and medium-sized tourism enterprises. Limited attention to emerging tourism markets: There is a need for more research on emerging tourism markets, such as senior tourism and medical tourism. Several methods to overcome these limitations have also been proposed by ChatGPT, such as a greater focus on engagement with local communities and the involvement of more stakeholders in tourism research. In addition, tourism research must be responsive to changes in the industry and address emerging travel trends. H. Shin and J. Kang

Journal of Hospitality and Tourism Management 57 (2023) 40–47 45 Greater focus on community engagement: Tourism research could benefit from greater engagement with local communities and other stakeholders to ensure that research is relevant and responsive to local needs and concerns. Greater attention to emerging tourism markets: Tourism research could benefit from greater attention to emerging tourism markets to ensure that research is responsive to changes in the industry and emerging trends. 3.3. Future directions of tourism research Promising research topics in the future: ChatGPT pointed out several topics that need to be addressed in the future to comprehensively examine the changes and challenges faced by the tourism industry. While the topics of sustainable tourism, technology, and economic impacts overlap with those identified as significant in recent tourism literature review research by Kim et al. (2018) and Ruhanen et al. (2019), several other topics, such as tourism and social justice, tourism and climate change, and tourism governance and policy, need to be addressed in future tourism research. In particular, Ruhanen et al. (2019) have also suggested that climate change is a crucial field for future tourism research. Tourism and health: The COVID-19 pandemic has highlighted the importance of health and safety in the tourism industry. Research needs to examine how tourism can be managed to minimize the risk of disease transmission and promote health and wellness. Tourism and social justice: Tourism has the potential to create social and economic inequalities in destinations, and research needs to explore how tourism can be managed to promote social justice and equity. Tourism and climate change: Climate change is a significant threat to the tourism industry, and research needs to examine how the industry can adapt to changing weather patterns and mitigate its impact on the environment. Tourism governance and policy: Tourism is a complex industry that involves multiple stakeholders, including governments, businesses, and communities. Researchers should pay attention to ways to improve tourism governance and policy, such as through the development of sustainable tourism policies, public-private partnerships, and stakeholder engagement. Ways to improve the quality of tourism research: ChatGPT has suggested several ways to further develop the quality of tourism research in the future. First, collaborations among researchers, universities, and tourism organizations are essential for developing innovative research. Second, using new technologies in data collection and analysis can enable researchers to gain new insights into consumer behavior, market trends, and economic impacts. Third, researchers must transfer research knowledge by interacting with the wider public, including industry practitioners and policymakers. This indicates that tourism research needs to be designed to heighten awareness among sector representatives, stakeholders, and decision-makers so that they can take necessary preventive measures to address the issue (Guzeller & Celiker, 2019). Collaboration and networking: Collaboration among researchers, universities, and tourism organizations is essential for developing innovative research in the field. By working together, researchers can share ideas, resources, and data to enhance the quality and relevance of their research. Technological innovations: The use of technology can help researchers to collect and analyze data more efficiently and accurately. New technological innovations, such as big data analytics, artificial intelligence, and machine learning, can enhance the quality and efficiency of tourism research. Knowledge transfer: Knowledge transfer is critical to ensuring that tourism research findings are disseminated to industry practitioners and policymakers. Tourism researchers need to communicate their findings in a clear and concise manner, using formats that are accessible to a broad audience. Ways to improve methodologies of tourism research: ChatGPT proposed specific ways to improve tourism research methodologies in the future. While previous tourism research has frequently referred to methodological approaches such as mixed methods, longitudinal analysis, and big data analysis (Nunkoo, 2018), this study has introduced innovative methods like participatory action research and mixed-method systematic reviews. Participatory action research: Participatory action research involves engaging with communities and stakeholders to identify research questions and to develop and implement research projects. This approach can provide a more inclusive and collaborative approach to tourism research. Mixed-methods systematic reviews: Systematic reviews should be conducted to provide a comprehensive overview of the literature on specific tourism topics. Key tourism research agenda for ChatGPT: Another query was directed to ChatGPT to seek insight into how ChatGPT or AI-enabled tools might impact the advancement of tourism research. In response, ChatGPT highlighted several significant research domains and potential applications associated with destination management, tourism content assessment, sustainable tourism, tourism marketing and promotion, customer service in tourism, real-time travel recommendations, travel behavior, market forecasting, and tourist perceptions, preferences, and sentiments. Destination Recommendation Systems: Investigate the application of AI language models like ChatGPT in developing more personalized and contextaware destination recommendation systems to cater to individual tourists’ preferences and interests. Assessing Bias in AI-Generated Tourism Content: Examine the potential biases present in AI-generated content, including travel articles, reviews, and destination descriptions, and explore strategies to mitigate such biases for fair and balanced tourism information. Sustainable Tourism: Explore how AI language models can contribute to sustainable tourism practices, such as optimizing transportation routes, minimizing environmental impact, and encouraging responsible tourism behaviors. Tourism Marketing and Promotion: Examine the effectiveness of AIgenerated content in tourism marketing campaigns, including social media posts, advertisements, and website content, and assess tourists’ perceptions of AI-driven promotional materials. Customer Service in Tourism: Assess the impact of AI chatbots and virtual assistants on customer service in the tourism industry, evaluating customer satisfaction, preferences, and concerns. Real-Time Travel Recommendations: Investigate the feasibility of using AI language models to deliver real-time travel recommendations, considering factors like weather conditions, crowd density, and personalized preferences. Understanding Tourist Behavior: Utilize AI language models to analyze large-scale social media data, online reviews, and other digital footprints to gain insights into tourist behavior, preferences, and motivations. Tourism Market Forecasting: Investigate the potential of AI language models in predicting tourism trends, market demand, and future tourist preferences, aiding policymakers and businesses in strategic planning. Tourist Perceptions, Preferences, and Sentiments: Researchers can apply ChatGPT for content analysis and sentiment analysis of large volumes of textual data, enabling them to gain insights into tourist perceptions, preferences, and sentiments. 4. Conclusion 4.1. Summary of findings and contributions The results of the current study indicate that ChatGPT supports the findings of existing bibliometric tourism studies in terms of the nature and key topics of previous tourism research. In addition, ChatGPT clearly demonstrates the limitations of tourism research, such as a lack of unified theories, less engagement with industry stakeholders in research design, and limited availability of reliable data on underrepresented groups and stakeholders. In addition, overdependence on quantitative methods and limited efforts for generalizing study findings have been proposed as methodological limitations, which may lead to a lack of theoretical development in future tourism research. H. Shin and J. Kang

Journal of Hospitality and Tourism Management 57 (2023) 40–47 46 Unlike the widely held view adopted by most tourism studies (Benckendorff & Zehrer, 2013; Laws & Scott, 2015), ChatGPT indicates that the interdisciplinary nature of tourism research strongly contributes to the development of other academic fields, suggesting the maturity of tourism research. In addition, ChatGPT explains the nature of tourism research in terms of applied social science, with a high dependence on practical issues. This finding indicates that current tourism research focuses more on practical research problems than on theoretical and conceptual problems. Regarding the future of tourism research, ChatGPT offers a set of promising topics, such as health, social justice, climate change, and governance/policy issues. To further develop the quality of tourism research, there should be increased collaboration among industry and external stakeholders to develop innovative research ideas and make efforts to disseminate research knowledge as widely as possible. In terms of methodologies, ChatGPT proposed novel methods, such as participatory action research and mixed-method systematic reviews, which are not commonly used in current tourism research. The findings of this study contribute to the existing literature in several ways. Unlike previous tourism-related bibliometric research that relies primarily on descriptive analysis of scholarly data or quantitative citation analyses (e.g., co-citation analysis, bibliocoupling analysis, network analysis) (e.g., Pahlevan-Sharif et al., 2019; Ritchie & Jiang, 2019; Shin & Perdue, 2022), the current study attempts to examine the progress and future directions of tourism research by using the AI-based chatbot ChatGPT. This approach offered valuable insights into recent advancements in tourism research by uncovering significant patterns in research, the organization of scholarly content, and the principal research agendas for future research in an effective and comprehensive manner. By employing ChatGPT, the most advanced AI-based language model, this study addresses the shortcomings of traditional bibliometric studies in tourism associated with restricted databases and subjectivity in the interpretation of analyses (Leong et al., 2021). ChatGPT can enhance the efficiency of tourism researchers using bibliometric methods through its ability to quickly retrieve relevant information from bibliographic databases, providing assistance in identifying pertinent papers and trends. Additionally, it serves as a preliminary tool by generating summaries and insights from large datasets, giving researchers a comprehensive overview and guiding their further analysis. The model also automates certain repetitive tasks such as data extraction and keyword identification, allowing researchers to allocate more time to higher-level analysis. Lastly, while the results of traditional bibliometric analyses are interpreted by researchers, ChatGPT objectively analyzes academic literature without biases or preconceptions. ChatGPT or other generative AI tools can be a useful tool for information retrieval and effective text analysis in bibliometric studies. However, ChatGPT is not inherently superior to human researchers when conducting bibliometric analyses. Bibliometric analysis involves analyzing patterns, relationships, and trends in academic literature, which requires not only understanding the content of the publications but also domain expertise, critical thinking, and context-awareness, which are areas where human researchers excel. Thus, tourism researchers need to use AI tools like ChatGPT as aids rather than replacements, integrating them into their workflow to enhance efficiency and complement their own domain expertise. 4.2. Limitations and future research directions Although the present study reveals important findings, it has some limitations. First, caution should be exercised in interpreting the results because ChatGPT is based on a large dataset of text, which may include some unreliable information (Lund & Wang, 2023). Thus, the study results should never be regarded as “truth” and further tests need to be performed to analyze the reliability of content generated by ChatGPT or other similar AI-based natural language processing models (Iskender, 2023; Zhuo et al., 2023). Second, although this study conducted interviews with ChatGPT multiple times to improve the reliability of the data, future research needs to use multiple AI-based software similar to ChatGPT to further improve the quality of interview data generated by AI. Finally, this study relied only on data generated by ChatGPT to understand the progress of tourism research. Future research may adopt a mixed-methods systematic review approach, as suggested by ChatGPT, by employing both AI-based tools and traditional bibliometric methods to gain deeper insight into the evolution and development of tourism research. Disclosure statement None. Declaration of competing interest None. References Abdollahi, A., Ghaderi, Z., B´eal, L., & Cooper, C. (2023). The intersection between knowledge management and organizational learning in tourism and hospitality: A bibliometric analysis. Journal of Hospitality and Tourism Management, 55, 11–28. Ali, F. (2023). Let the devil speak for itself: Should ChatGPT be allowed or banned in hospitality and tourism schools? Journal of Global Hospitality and Tourism, 2(1), 1–6. Benckendorff, P., & Zehrer, A. (2013). A network analysis of tourism research. Annals of Tourism Research, 43, 121–149. Bianchi, R. (2018). The political economy of tourism development: A critical review. Annals of Tourism Research, 70, 88–102. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., … Amodei, D. (2020). Language models are few-shot learners. arXiv preprint arXiv:2005.14165. Carvalho, I., & Ivanov, S. (2023). ChatGPT for tourism: Applications, benefits and risks. Tourism Review, 1, 1–14. Coles, T., Fenclova, E., & Dinan, C. (2013). Tourism and corporate social responsibility: A critical review and research agenda. Tourism Management Perspectives, 6, 122–141. Darbellay, F., & Stock, M. (2012). Tourism as complex interdisciplinary research object. Annals of Tourism Research, 39(1), 441–458. Dogru, T., Line, N., Mody, M., Hanks, L., Abbott, J. A., Acikgoz, F., … Zhang, T. (2023). Generative artificial intelligence in the hospitality and tourism industry: Developing a framework for future research. Journal of Hospitality & Tourism Research, Article 10963480231188663. Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., … Wright, R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, Article 102642. Fong, L. H. N., Law, R., Tang, C. M. F., & Yap, M. H. T. (2016). Experimental research in hospitality and tourism: A critical review. International Journal of Contemporary Hospitality Management, 28(2), 246–266. Gossling, ¨ S. (2017). Tourism, information technologies and sustainability: An exploratory review. Journal of Sustainable Tourism, 25(7), 1024–1041. Guest, G., MacQueen, K. M., & Namey, E. E. (2012). Applied thematic analysis. Sage publications. Guzeller, C. O., & Celiker, N. (2019). Bibliometrical analysis of Asia Pacific journal of tourism research. Asia Pacific Journal of Tourism Research, 24(1), 108–120. Hill-Yardin, E. L., Hutchinson, M. R., Laycock, R., & Spencer, S. J. (2023). A Chat (GPT) about the future of scientific publishing. Brain, Behavior, and Immunity, 110, 152–154. Iskender, A. (2023). Holy or unholy? Interview with open AI’s ChatGPT. European Journal of Tourism Research, 34, 3414. -3414. Ivanov, S., & Soliman, M. (2023). Game of algorithms: ChatGPT implications for the future of tourism education and research. Journal of Tourism Futures, 9(2), 214–221. Karakas, F. (2022). I asked ChatGPT 10 questions about 2030: Here are the Wonderfully exciting responses it gave me!. Retrieved from https://medium.com/predict/i-asked-ch atgpt-10-questions-about-2030-here-are-the-wonderfully-exciting-responses-it-gaveme-cc70e899d999 (2023.3). Kim, C. S., Bai, B. H., Kim, P. B., & Chon, K. (2018). Review of reviews: A systematic analysis of review papers in the hospitality and tourism literature. International Journal of Hospitality Management, 70, 49–58. Koseoglu, M. A., Yick, M. Y. Y., King, B., & Arici, H. E. (2022). Relational bibliometrics for hospitality and tourism research: A best practice guide. Journal of Hospitality and Tourism Management, 52, 316–330. Laws, E., & Scott, N. (2015). Tourism research: Building from other disciplines. Tourism Recreation Research, 40(1), 48–58. Leong, L. Y., Hew, T. S., Tan, G. W. H., Ooi, K. B., & Lee, V. H. (2021). Tourism research progress–a bibliometric analysis of tourism review publications. Tourism Review, 76 (1), 1–26. H. Shin and J. Kang

Journal of Hospitality and Tourism Management 57 (2023) 40–47 47 Lund, B. D., & Wang, T. (2023). Chatting about ChatGPT: How may AI and GPT impact academia and libraries? Library Hi Tech News. Lund, B. D., Wang, T., Mannuru, N. R., Nie, B., Shimray, S., & Wang, Z. (2023). ChatGPT and a new academic reality: Artificial Intelligence-written research papers and the ethics of the large language models in scholarly publishing. Journal of the Association for Information Science and Technology, 74(5), 570–581. Mearian, L. (2023). Q&A: Chat GPT isn’t sentient, it’s a next-world prediction engine. Retrieved from https://www.computerworld.com/article/3688934/chatgpt-is-notsentient-it-s-a-next-word-prediction-engine.html, 2023.3. Mehraliyev, F., Chan, I. C. C., Choi, Y., Koseoglu, M. A., & Law, R. (2020). A state-of-theart review of smart tourism research. Journal of Travel & Tourism Marketing, 37(1), 78–91. Montti, R. (2022). What is ChatGPT and how can you use it?. Retrieved from https://www. searchenginejournal.com/what-is-chatgpt/473664/#close, 2023.3. Nunkoo, R. (2018). The state of research methods in tourism and hospitality. In Handbook of research methods for tourism and hospitality management (pp. 3–23). Edward Elgar Publishing. OpenAI. (2021). About OpenAI. Retrieved from https://openai.com/about/. Pahlevan-Sharif, S., Mura, P., & Wijesinghe, S. N. (2019). A systematic review of systematic reviews in tourism. Journal of Hospitality and Tourism Management, 39, 158–165. Patton, C. V., Sawicki, D. S., & Clark, J. J. (2015). Basic methods of policy analysis and planning. Routledge. Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., & Sutskever, I. (2019). Language models are unsupervised multitask learners. OpenAI blog, 1(8), 9–13. Rasoolimanesh, S. M., Wang, M., Mikuli´c, J., & Kunasekaran, P. (2021). A critical review of moderation analysis in tourism and hospitality research toward robust guidelines. International Journal of Contemporary Hospitality Management, 33(12), 4311–4333. Ritchie, B. W., & Jiang, Y. (2019). A review of research on tourism risk, crisis and disaster management: Launching the annals of tourism research curated collection on tourism risk, crisis and disaster management. Annals of Tourism Research, 79, Article 102812, 1-15. Ruhanen, L., Moyle, C. L., & Moyle, B. (2019). New directions in sustainable tourism research. Tourism Review, 74(2), 138–149. Shin, H., & Perdue, R. R. (2022). Hospitality and tourism service innovation: A bibliometric review and future research agenda. International Journal of Hospitality Management, 102, Article 103176. Sigala, M., Kumar, S., Donthu, N., Sureka, R., & Joshi, Y. (2021). A bibliometric overview of the journal of hospitality and tourism management: Research contributions and influence. Journal of Hospitality and Tourism Management, 47, 273–288. Skavronskaya, L., Hadinejad, A., & Cotterell, D. (2023). Reversing the threat of artificial intelligence to opportunity: A discussion of ChatGPT in tourism education. Journal of Teaching in Travel & Tourism, 23(2), 253–258. Small, J., Harris, C., & Wilson, E. (2017). Gender on the agenda? The position of gender in tourism’s high ranking journals. Journal of Hospitality and Tourism Management, 31, 114–117. Stergiou, D. P., & Airey, D. (2018). Understandings of tourism theory. Tourism Review, 73 (2), 156–168. Xiang, Z. (2018). From digitization to the age of acceleration: On information technology and tourism. Tourism Management Perspectives, 25, 147–150. Yan, E., & Ding, Y. (2012). Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other. Journal of the American Society for Information Science and Technology, 63(7), 1313–1326. Zhuo, T. Y., Huang, Y., Chen, C., & Xing, Z. (2023). Exploring ai ethics of chatgpt: A diagnostic analysis. arXiv preprint arXiv:2301.12867. 1-17. H. Shin and J. Kang

Journal of Hospitality and Tourism Management 57 (2023) 84–96 Available online 15 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. Cooperation in rural tourism routes: Evidence and insights Helena de Lima Krauss Leite a , Erlaine Binotto b,* , Ana Claudia ´ Machado Padilha c , Paulo Henrique de Oliveira Hoeckel b a Federal University of Grande Dourados, Rodovia Dourados- Itahum KM 12, CEP: 79800000, Dourados, MS, Brazil b Federal University of Grande Dourados, Faculty of Business, Accounting and Economics, Rodovia Dourados- Itahum KM 12, CEP: 79800000, Dourados, MS, Brazil c University of Passo Fundo, School of Agricultural Sciences, Innovation and Business, Campus I, Sao ˜ Jos´e, CEP: 99001970, Passo Fundo, RS, Brazil ARTICLE INFO Keywords: Systematic review Tourism development Rural tourism Synergy experience ABSTRACT Cooperation serves as an effective strategy for fostering economic development in underdeveloped regions through tourism routes. The objective of this study is to identify the key components of cooperation process in rural tourism routes, drawing upon existing literature. A systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) protocol. Two databases were utilized, resulting in the selection of 18 relevant studies. This study identifies the key components (factors, elements, and instruments) necessary for fostering cooperation in rural tourism routes. Additionally, it underscores their significance in generating synergies to benefit destinations, promote sustainable development, and enhance the experiences of tourists. The identified factors encompass tourist attractions (36%), tourist services (30%), public services (15%), basic infrastructure (6%), management (8%), brand image (2%), and price (2%). The pivotal elements for cooperation include stakeholder interaction, active community participation, support from the public sector, trust, shared goals, planning, structuring, financing, product development, mutual benefits, communication, learning, and self-assessment. Moreover, various instruments support cooperation, including agreements, projects, plans, partnerships, programs, inter-cooperation, associations, sub-projects, regulations, letters of intent, alliances, mission statements, bylaws, and barter. These instruments facilitate the formalization and enhancement of cooperative arrangements within rural tourism routes, ensuring long-term sustainability and promoting effective implementation. Furthermore, the study indicates the necessity of conducting further indepth exploration into the essential elements for cooperation in rural tourism routes. 1. Introduction Cooperation is essential for the survival of many organisms (Raihani & Modarelli, 2020). From an evolutionary perspective, cooperation arises when individual benefits increase through collective action (Hamilton, 1964). Consequently, it enhances the survival and development of enterprises in rural areas. Moreover, cooperation fosters reciprocal benefits between partners, promoting social relationships (Trivers, 1971; Axerold & Hamilton, 1981). In tourism, cooperation also plays a crucial role, especially concerning tourist routes. For decades, trails and routes have formed the basis of tourist mobility patterns, contributing to recreational activities, a plethora of travel plans, and tourism progress worldwide (Anuar & Marzuki, 2022). The concept of a tourist route is based on geographical approaches, logically aligned from a geographical standpoint and thematically connected to the development of tourism infrastructure and the monitoring of tourist flows (Zyrianov & Zyrianova, 2021). The development of tourism routes offers opportunities for the formation of local development partnerships, as well as arrangements for cooperative planning and relationships among different localities, enabling them to compete collectively as tourist destinations (Rogerson, 2007). However, the cooperation is not merely a friendship, a voluntary collaborative action that requires lasting commitment based on structured relationships with frequent interactions (Axelrod, 2006). Cooperation encompasses attitudes, behaviors, and outcomes that arise from pursuing agreed-upon goals (Castaner ˜ & Oliveira, 2020). It can manifest in various social activities, for examples, assuming regional leadership roles, engaging in product development, improving access * Corresponding author. E-mail addresses: [email protected] (H.L.K. Leite), [email protected] (E. Binotto), [email protected] (A.C.M. Padilha), paulohoeckel@ufgd. edu.br (P.H.O. Hoeckel). URL: http://www.ufgd.edu.br (E. Binotto), http://upf.br (A.C.M. Padilha). 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.2023.09.005 Received 20 January 2023; Received in revised form 17 August 2023; Accepted 10 September 2023

Journal of Hospitality and Tourism Management 57 (2023) 84–96 85 infrastructure, fostering community participation, promoting innovation among micro-entrepreneurs, sharing knowledge and information, and, most importantly, contributing to the development of tourism destinations (Meyer, 2004, pp. 1–31). In simple terms, rural tourism refers to tourism that occurs in the countryside. However, it is important to note that not all tourism in rural areas strictly adheres to this definition; diverse manifestations of rural tourism have evolved in various regions, contributing to the complexity of rural areas’ ongoing changes. For these reasons, rural tourism constitutes a multifaceted and intricate activity (Lane, 1994). In this article, rural tourism is encompasses any form of tourism that highlights rural life, art, culture, and heritage within rural settings (Fang & Fang, 2020). Among the various methods of promoting rural tourism, tourism routes play a significant role. These routes can be described as predetermined itineraries followed by travelers who appreciate the available tourist offerings along a specific course or direction (Lourens, 2007; Meyer, 2004, pp. 1–31). Route tourism is a market-driven approach for tourism destination development, and its terminology is used to describe the concept often varies in different parts of the world, with use of the notions of ‘themed routes’, ‘trails’, ‘scenic by-ways’ and so forth (Rogerson, 2007). Routes seem to be a particularly good opportunity for the development of less mature areas with high cultural resources that appeal to special interest tourists who often not only stay longer but also spend more to pursue their particular interest (Meyer, 2004, pp. 1–31). The essence of a route is a chosen journey or progression among a series of elements, a strategy toward one or a series of objectives, a course of action, not an immediate and isolated activity (Moulin & Boniface, 2001). In the context of tourism networks, the absence of cooperation leads to social conflicts, mistrust among members involved, and price wars (Pilving et al., 2019). Moreover, the lack of cooperation hampers tourism development, particularly in fostering innovation among members. However, cooperation can assist members in overcoming the challenges posed by the highly competitive and globalized contemporary market, facilitating better practices, improved performance, and increased profitability for all stakeholders (Baggio et al., 2010). To address the future challenges of developing tourism routes, further research needs to understand their motivations, limitations, and future requirements. Cooperation among key stakeholders can help overcome several challenges (Olsen, 2003). The importance of testing the life cycle of tourism partnerships in different environments to gain a better understanding of the factors influencing their development at different stages and impact on partnership sustainability (Pilving et al., 2019). Analyzing cooperation in the context of tourism routes becomes more complex, which serve as mechanisms for heritage conservation, cultural preservation, and tourism. Regarding their potential to generate impacts on socioeconomic development, fostering cooperation and adequate communication between stakeholders are crucial (Moulin & Boniface, 2001). Planning tourist routes involves more than a government strategy encompassing attractions, services, marketing, financing, and the most important is the management processes (Meyer, 2004, pp. 1–31). In addition to the requirement for local government to implement tourism-related development projects is need to enhance further rural tourism activities in order to foster the growth of the local economy (Yang et al., 2021). It requires the involvement of various enterprises that can contribute to enhancing the competitiveness of cooperative arrangements over time. Significant challenges in rural tourism development often extend beyond the direct influence of communities (Johnson, 2010). Cooperation can be a vital stimulus for achieving sustainable tourism (World Bank, 2010), particularly in rural areas. Moreover, cooperation can contribute to meeting the expectations of consumers seeking quality products and services (Correia et al., 2014) offered in rural tourism. Furthermore, studies should focus on analyzing the factors contributing to the development of analytical tools and systems that support decision-making in these environments (Tikunov et al., 2018). Future research should delve deeper into analyzing stakeholders involved in rural tourism, such as tourism enterprises, government entities, and residents (Peng et al., 2016). This analysis is crucial because cooperative relationships in tourism are highly complex due to the constant inflow and outflow of partners (Jesus & Franco, 2016). Additionally, there are significant regional disparities among the intersections of tourism destinations along the routes, including variations in resource endowment, location, accessibility, infrastructure allocation, and the level of market development. These disparities may hinder the coordinated development of these destinations, requiring specific studies to address these issues (Peng et al., 2016). Therefore, a comprehensive understanding of the subject under analysis is essential to obtain meaningful results from theoretical and practical perspectives (Baggio et al., 2010). Thus, this study address the following research question: What does the existing literature present regarding cooperation in rural tourism routes? Moreover, this study aims to identify the key components of cooperation process in rural tourism routes, drawing upon existing literature. Although there are systematic reviews on cooperation (Castaner ˜ & Oliveira, 2020) and rural tourism (Rosalina et al., 2021), the lack of studies specifically addressing rural tourism routes justifies the significance of this study. By contributing to the discussion on this topic, the study can identify elements related to cooperation that will enable future comparisons regarding the potential of different routes and support decision-making processes (Tikunov et al., 2018). Wang et al. (2022) reviewed studies on social entrepreneurship research in tourism, identifying limited studies exploring tourism social entrepreneurship, revealing certain gaps and limitations in this area, and providing practical implications for social entrepreneurs and local authorities. These findings reinforce the importance of conducting systematic reviews. The study contributes by providing elements related to cooperation that can be comparable in future research to assess the potential of establishing tourist routes. The development of rural tourism relies on the entrepreneurs’ ability to sustainable utilize the local physical space and non-material resources (Yachin & Ioannides, 2020). It is worth noting that the processes and mechanisms of internal interaction among stakeholders play a crucial role in fostering cooperation (Ma et al., 2020). Taking into account that a study regards the perception of local residents as the most crucial factor to be taken into consideration for models development (Mathew & Sreejesh, 2017), cooperative behavior within tourist routes enables member enterprises to access novel sources of knowledge, thereby facilitating organizational learning and fostering the ongoing enhancement of their dynamic capabilities (Wilke et al., 2019). Cooperation among entrepreneurs in the sector is fundamental aspect for tourism development (Komppula, 2014), particularly on tourist routes. Furthermore, it contributes to the analysis of problems related to the internal resources of enterprises within rural destinations, especially in developing countries (Rosalina et al., 2021). The study’s contribution lies in providing insights for discussing cooperation in rural tourism routes from a theoretical standpoint. Furthermore, the empirical contribution provides elements for enterprises to develop cooperation in a more organized manner. Lastly, from a practical perspective, this study provides guidance for public authorities to develop effective public policies for the rural tourism sector. Considering the diversity of studies on tourist routes, a comprehensive perspective encompassing the key components of the cooperation process in rural tourism routes has yet to be established. This study seeks to address knowledge gaps in understanding, identifying, and determining critical elements from cooperative perspectives for the development of tourist routes. The primary rationale for this research revolves around the endeavor to comprehend these gaps and establish crucial aspects for a potential landscape. H.L.K. Leite et al.

Journal of Hospitality and Tourism Management 57 (2023) 84–96 86 2. Materials and methods The search was conducted in March 2022 using the Web of Science and Scopus databases. The following keywords were included in the study topic: (cooperation OR co-operation) AND (tourism OR rural tourism OR agritourism OR agrotourism) AND (route). The systematic review was developed following the PRISMA protocol (Page et al., 2020) (see APPENDIX I). No period limitation was applied as a screening filter; instead, we searched for studies in English language. As a result of this step, 78 studies were identified. The first analysis involved checking the ranking of journals in the Journal Citation Report (JCR). Studies ranked in the Q1 and Q2 quartiles based on the Journal Citation Indicator (JCI) or Journal Impact Factor (JCF) in 2020 (latest ranking) were included, resulting in a selection of 40 studies. In the next step, 13 duplicate studies were excluded. Subsequently, after reading the abstracts, others nine additional studies because they did not align with the research scope, specifically in terms of mentioning cooperation in rural tourism routes. Thus, as a result 18 studies were selected for the systematic review, following a PRISMA flowchart (see Fig. 1) after checklist (APPENDIX I). The 18 selected studies were thoroughly read, analyzed, and synthesized. The selection of this sample (18 articles) is appropriate given the specific nature of the subject and adherence to the complete PRISMA Protocol, which helps minimize potential biases selection (Shamseer et al., 2015). The utilization of comprehensive Databases for the searches, inclusion of well-indexed journals, and the fact that all articles underwent peer review are evident. The decision not to filter based on specific areas was deliberate to prevent restricting the research within a particular domain. The belief is that cross-disciplinary research can collaboratively enhance the progression of rural tourism as a subject (Rosalina et al., 2021). Given the increasing significance and impact of multidisciplinary research in the wider realm of tourism, embracing multidisciplinary perspective can significantly broaden horizons and contribute to accessing novel frontiers of knowledge (Singala et al., 2021). To identify the key components of cooperation in rural tourism routes, we explored: the frequency of studies were published per year, rural tourism routes’ themes, the factors impacting the development of tourism potential in regions and rural tourism routes, elements that impact on cooperation process, instruments that assist cooperation. Finally, a co-occurrence analysis of the keywords was performed using the VOSviewer software, analyzing a total of 210 keywords. The cooccurrence analysis was performed with 18 studies included in this systematic review (see APPENDIX II) using the VOSviewer software. The next section will present the results, discussion, and conclusions. 3. Results This section presents the synthesis of the 18 reviewed studies and the co-occurrence analysis. The geographical distribution of routes surveyed in the selected studies: Europe (58%), Asia (26%), Africa (11%), and Oceania (5%). Among them, six are cross-border routes: four in Europe, one in Asia, and one in Africa. Our findings reveal that studies focused on the development of cooperation in rural tourism routes have been under-explored in the literature. However, there has been a noticeable growth in these studies over the past three years (see Fig. 2). The systematic review has identified key components (factors, elements, and instruments) for developing and enhancing cooperation in rural tourism routes. 3.1. Factors that impact in rural tourism routes The analyzed studies encompass tourist routes that traverse rural areas and encompass diverse themes (see Fig. 3). The routes presented in the studies are geographically situated in rural areas, each with its own uniqueness. All the analyzed studies showcase rural tourism routes whose themes are connected to the factors present in the respective locations, making them attractive and distinctive. This observation is reinforced when comparing Fig. 3 and Table 1. The factors identified in the rural destinations (Table 1) significantly influence the development of tourism potential in rural regions, thereby impacting rural tourism routes and the cooperation existing within them. For instance, cycling routes not only appeal to sports enthusiasts but also attract visitors with their scenic landscapes, directly contributing to the revitalization of rural areas and the retention of young people in these regions (Vujko & Gajic, 2014). According to Stepanova (2017), the factors that affect in rural tourism routes can be geographic, geopolitical, economic, and institutional. Table 1 highlights the importance of leveraging local history, resources, and existing potential in destinations to foster sustainable development of rural tourism in these regions, thereby creating economic synergies through cooperation. Fig. 1. The PRISMA flowchart. H.L.K. Leite et al.

Journal of Hospitality and Tourism Management 57 (2023) 84–96 87 We identified 100 aspects, and some of them cited more than one time. A total was 163 times (n) across the reviewed studies. These aspects were grouped into seven factors divided into 22 sub-factors, inspired in Leask (2010; 2016) and Ignarra (2013). Notably, the most frequently mentioned aspects include cultural and historical heritage/monuments (4.30%), areas of pristine nature (2.45%), trains (2.45%), dissemination (trading, production, and development of websites and information materials in multiple languages) (2.45%), tourist offices/centers (2.45%), transportation offerings (both internal and external) (2.45%), site protection (2.45%), and accessibility (2.45%). Collectively, these aspects constitute 21.47% of the total. Stakeholders rely on these aspects to identify the potential attractions of their regions and, consequently, develop their rural tourist routes. Moreover, we observed that certain sub-factors hold greater significance in rural destinations, and are commonly considered when selecting the theme for rural tourist routes. The most frequently mentioned sub-factors include cultural attractions (22%), natural attractions (15%), tours (9%), and quality (9%). Among the seven identified factors, some are cited more frequently than others: tourist attractions (36%), tourist services (30%), public services (15%), basic infrastructure (6%), management (8%), brand image (2%), and price (2%). Tourist attractions emerge as the most significant factor, encompassing sub-factors related to cultural and natural attractions. This factor’s prominence stems from the presence of heritage/historical sites and areas of pristine natural beauty. 3.2. Elements that shape and explain the cooperation process in rural tourism routes In addition to the factors, we have identified elements that shape and explain the cooperation process in rural tourism routes (Fig. 4). The systematic review allowed us to extract from the studies the cooperation elements developed in rural tourism routes. We found that cooperation depends on the interaction of stakeholders, including Fig. 2. Number of studies published over the years. Fig. 3. Rural tourism routes’ themes. H.L.K. Leite et al.

Journal of Hospitality and Tourism Management 57 (2023) 84–96 88 Table 1 Factors that impact in rural tourism routes. Factors Subfactors Aspects (n = 100) (n = 163)a Authors Tourist Attractions (n = 59) Naturals (n = 24) Good environmental conditions/balance 3 Tikunov et al. (2018), Khalil et al. (2021), Severino et al. (2021) Wild Nature Areas 4 Li and Hu (2019), Frost and Shanka (2001), Rainero and Modarelli (2020), Severino et al. (2021) Nature Reserves and Parks; 3 Severino et al. (2021), Revilla and Moure (2021), Kolodziejczyk (2020) Location 2 Peng et al. (2016), Rainero and Modarelli (2020) Rational use of tourism and recreational resources 1 Tikunov et al. (2018) Rivers 1 Li and Hu (2019) Conservation of endangered animals 1 Briedenhann and Wickens (2004) Thermal waters for therapeutic tourism 2 Severino et al. (2021), Kolodziejczyk (2020) Balance in terms of implementing economic, environmental, social, and cultural objectives 1 Tikunov et al. (2018) Scenery/Landscape 1 Revilla and Moure (2021) Unique and untapped resources 1 Briedenhann and Wickens (2004) Rurality/landscape 1 Rainero and Modarelli (2020) Mountain areas 2 Li and Hu (2019), Kolodziejczyk (2020) Agricultural Areas 1 Li and Hu (2019) Cultural (n = 35) Prehistoric cave paintings 1 Briedenhann and Wickens (2004) Sites included on the UNESCO World Heritage List 3 Bogacz-Wojtanowska et al. (2019), Stepanova (2017), Revilla and Moure (2021) Cultural/Historical Centers 2 Bogacz-Wojtanowska et al. (2019), Rainero and Modarelli (2020) Archeological Sites 2 Revilla and Moure (2021), Sipos et al. (2021) Cultural relics (including ancient sites, tombs, caves, temples, and churches) 1 Li and Hu (2019) Cultural and Historical Heritage/Monument 7 Stepanova (2017), Naramski and Szromek (2019), Severino et al. (2021), Revilla and Moure (2021), Sipos et al. (2021), Bogacz-Wojtanowska et al. (2019), Rainero and Modarelli (2020) Industrial culture real estate properties 1 Bogacz-Wojtanowska et al. (2019) Local traditions (culture/history) 2 Revilla and Moure (2021), Sipos et al. (2021) Availability of residents 1 Stepanova (2017) Complementary experiences 1 Revilla and Moure (2021) Architectural value of the properties 1 Revilla and Moure (2021) National and local characteristics 1 Severino et al. (2021) Historical lack of technological and economic breakthroughs 1 Li and Hu (2019) Contact with the local population 1 Sipos et al. (2021) Authenticity/natural life 1 Rainero and Modarelli (2020) Sense of family/affective component 1 Rainero and Modarelli (2020) Cultural and geographical unity (identity) 2 Li and Hu (2019), Naramski and Szromek (2019) Myths, folklore, magic, legends 1 Rainero and Modarelli (2020) Typical multi-ethnic area (existence of different ethnicities) 1 Li and Hu (2019) Traditional Buildings 1 Li and Hu (2019) Missionary cities and stations 1 Briedenhann and Wickens (2004) Geological and mining heritage, old mines, operating smelters and mines, garnet fields, mining museums, ruins 1 Stepanova (2017) Cultural villages 1 Briedenhann and Wickens (2004) Tourist Services (n = 49) Lodging (n = 5) Hotels 3 Severino et al. (2021), Tikunov et al. (2018), Vujko and Gajic (2014) Camping parks 1 Vujko and Gajic (2014) Inns, Hostel 1 Tikunov et al. (2018) Food (n = 5) Theme restaurants 1 Briedenhann and Wickens (2004) Gastronomy 3 Revilla and Moure (2021), Rainero and Modarelli (2020), Naramski and Szromek (2019) Coffees 1 Stepanova (2017) Agency business (n = 1) Tourism preferences 1 Peng et al. (2016) Tourist Transportation (n = 5) Trains 4 Severino et al. (2021), Kolodziejczyk (2020), Li et al. (2020), Frost and Shanka (2001) Transfers and excursions 1 Severino et al. (2021), Events (n = 7) Festivals 3 Rainero and Modarelli (2020), Naramski and Szromek (2019), Sipos et al. (2021) Cultural Events 2 Sipos et al. (2021), Bogacz-Wojtanowska et al. (2019) Trade Shows and Parties 1 Revilla and Moure (2021) Courses 1 Revilla and Moure (2021) Entertainment (n = 2) Entertainment 2 Severino et al. (2021), Li and Hu (2019) Tourist Information (n = 8) Dissemination (trading, production, and development of websites and information materials in several languages) 4 Vujko and Gajic (2014), Stepanova (2017), Severino et al. (2021), Kolodziejczyk (2020) (continued on next page) H.L.K. Leite et al.

Journal of Hospitality and Tourism Management 57 (2023) 84–96 89 enterprise owners, tourists, investors, public authorities, and other individuals and organizations involved (Severino et al., 2021). This involvement extends to the private sector (Frost & Shanka, 2001; Rainero & Modarelli, 2020) and tour operators (Bogacz-Wojtanowska et al., 2019). Common roots and a sense of identity and belonging create a cooperation network that brings stakeholders together (Bogacz-Wojtanowska et al., 2019). This interaction requires significant community participation, along with the support of public authorities, mainly in terms of providing safety and security (Briedenhann & Wickens, 2004). Public authorities also play a crucial role in ensuring commitment to the route (Rainero & Modarelli, 2020; Sipos et al., 2021) and assisting in its financing (Stepanova, 2017). Commitment (Bogacz-Wojtanowska et al., 2019) and trust among stakeholders are factors in maintaining a proper balance between cooperation and competition within a network (Naramski & Szromek, 2019). Trust influences cooperation (Naramski & Szromek, 2019), fostering a sense of community and strengthening it (Bogacz-Wojtanowska et al., 2019). Voluntary partnerships (Briedenhann & Wickens, 2004; Sipos et al., 2021) and barter (Frost & Shanka, 2001) can Table 1 (continued ) Factors Subfactors Aspects (n = 100) (n = 163)a Authors Tourist office/center 4 Stepanova (2017), Peng et al. (2016), Sipos et al. (2021), Kolodziejczyk (2020) Tours (n = 14) Cycling 3 Stepanova (2017), Stoffelen (2018), Vujko and Gajic (2014) Ski Center 1 Kolodziejczyk (2020) Spa town 1 Severino et al. (2021) Bilingual guided tours 2 Revilla and Moure (2021), Stepanova (2017) Breweries 1 Naramski and Szromek (2019) Public bathrooms 1 Stepanova (2017) Wineries 1 Revilla and Moure (2021) Unique, natural, and man-made tourist attractions 2 Stepanova (2017), Revilla and Moure (2021) Quiet resting places 1 Severino et al. (2021) Active recreation venues 1 Severino et al. (2021) Tourist Trade (n = 2) Stores 1 Stepanova (2017) General Services 1 Severino et al. (2021) Public Services (n = 25) Transportation (n = 5) Transportation offer (internal and external) 4 Li et al. (2020), Kolodziejczyk (2020), Stepanova (2017), Li and Hu (2019) Gas station 1 Stepanova (2017), Health (n = 2) Health and beauty tourism 1 Revilla and Moure (2021) Health care and emergency service 1 Stoffelen (2018) Safety (n = 13) Site protection 4 Briedenhann and Wickens (2004), Vujko and Gajic (2014), Severino et al. (2021), Khalil et al. (2021) Administrative limit 1 Peng et al. (2016) Of the highway 2 Olsen (2003), Vujko and Gajic (2014) Of the railroad 1 Severino et al. (2021) Political stability 2 Stoffelen (2018), Frost and Shanka (2001) Weather shelters 1 Stepanova (2017) Tourist autonomy 1 Vujko and Gajic (2014) Strengthening of customs and cross-border infrastructure (including the opening of new checkpoints and simplification of visa formalities) 1 Stepanova (2017) Information (n = 4) Road and site signs 1 Stepanova (2017) Signaling system: maps, guides, accommodation, and food signaling capacity, marked by difficulty weight, and all grades of natural and cultural resources; reading boards and audio guides 3 Vujko and Gajic (2014), Stepanova (2017), Rainero and Modarelli (2020) Driver Support (n = 1) Driver safety 1 Olsen (2003) Basic Infrastructure (n = 10) Access points (n = 7) Accessibility 4 Stepanova (2017), Stoffelen (2018), Kolodziejczyk (2020), Peng et al. (2016) Travel duration/time 1 Severino et al. (2021) Of potentially interesting locations (present and future) 2 Stepanova (2017), Severino et al. (2021) Urban Circulation Routes (n = 2) Traffic-related facilities and services 1 Peng et al. (2016) Spatial structure 1 Peng et al. (2016) Human Services Training (n = 1) Qualified human resources 1 Sipos et al. (2021) Management (n = 14) Qualitya (n = 14) Of the product 1 Revilla and Moure (2021) Of the destination 1 Revilla and Moure (2021) Of the services 3 Vujko and Gajic (2014), Severino et al. (2021), Naramski and Szromek (2019) Of the facilities 2 Revilla and Moure (2021), Rainero and Modarelli (2020) Of the accommodation (comfort) 2 Sipos et al. (2021), Severino et al. (2021) Of the highway 2 Olsen (2003), Vujko and Gajic (2014) Of the transportation 1 Kolodziejczyk (2020) Of the railroad 1 Severino et al. (2021) of the trip/route 1 Severino et al. (2021) Brand Image (n = 3) Advertisinga (n = 3) Social media applications and media in general (marketing) 2 Khalil et al. (2021), Kolodziejczyk (2020) Feedback/posting from users on social media (internet) 1 Tikunov et al. (2018) Price (n = 3) Price (n = 3) Tours or tickets 1 Severino et al. (2021) Promotional prices or free entrance table 1 Naramski and Szromek (2019) Pricing and Fee Policy 1 Severino et al. (2021) a Note: number of authors that cited the factors. H.L.K. Leite et al.

Journal of Hospitality and Tourism Management 57 (2023) 84–96 90 stimulate the maintenance and strengthening of cooperative relationships among actors involved in rural tourism routes (Li et al., 2020). Usually, there are mediators who play a role in these arrangements. They are individuals who enjoy the most trust from other participants in the network. Their role includes conflict resolution (Naramski & Szromek, 2019) or serving on an advisory board (Bogacz-Wojtanowska et al., 2019). Establishing organized and structured cooperation is important not only from the perspective of a single enterprise struggling to survive in a highly competitive market but also from the perspective of an entire tourism region (Naramski & Szromek, 2019). Cooperative (Stoffelen, 2018) and realistic planning (Frost & Shanka, 2001) become necessary. An organizational structure for management should be in place (Li & Hu, 2019), considering community perceptions regarding social, economic, cultural, and environmental factors (Khalil et al., 2021). In other words, a holistic and immersive approach should be adopted (Rainero & Modarelli, 2020). Furthermore, the impacts of the actions should be evaluated (Stoffelen, 2018), and risk management of the project should be implemented (Severino et al., 2021; Sipos et al., 2021). Uncertainty factors of different categories should be analyzed (Severino et al., 2021), and mechanisms for formalizing competition mechanisms and analyzing their efficiency should be considered (Severino et al., 2021), along with having a strategic vision, particularly in the long term, to combine local efforts (Stoffelen, 2018) and develop a route development plan (Bogacz-Wojtanowska et al., 2019). When planning, the forms of ownership and individual management models of the enterprises must also be considered (Naramski & Szromek, 2019). Moreover, the sustainability and carrying capacity of the land must be considered to ensure that it remains within the region’s capacity. Otherwise, the tourism industry will be negatively impacted by the loss of authenticity of the destinations, which often occurs due to overcrowding (Revilla & Moure, 2021). Seasonal periods should also be considered, including the development of an internal work plan to enable implementation even in unfavorable weather conditions (Sipos et al., 2021). Efforts should be made to ensure that the destination is not forgotten outside of the peak season (Kolodziejczyk, 2020). Revilla and Moure (2021) suggest allocating resources to both the busiest and off-peak months to increase the number of visits and achieve sustained growth throughout the year. The different actors involved need to organize themselves for this structuring and must have clear objectives (Li & Hu, 2019; Stoffelen, 2018), which may be tangible and/or intangible, integrated and known, or unknown to the network participants (Bogacz-Wojtanowska et al., 2019). Moreover, there must be an open and inclusive decision-making network (Stoffelen, 2018) or inter-organizational networks (a developed form of cooperation) (Naramski & Szromek, 2019). Additionally, the members must have specific tasks (Bogacz-Wojtanowska et al., 2019; Li & Hu, 2019). The cooperation must also be formalized and can be structured through various instruments (refer to Table 2 in Section 3.2). Furthermore, the organization of the route should preferably be Fig. 4. Elements of cooperation in rural tourism routes. Table 2 Instruments that formalize the cooperation. Instruments Frequency (n = 35) Author(s) 1-Agreements 6 Severino et al. (2021), Stoffelen (2018), Stepanova (2017), Frost and Shanka (2001), Naramski and Szromek (2019), Kołodziejczyk (2020) 2-Projects 6 Briedenhann and Wickens (2004), Bogacz-Wojtanowska et al. (2019), Stoffelen (2018), Sipos et al. (2021), Stepanova (2017), Khalil et al. (2021) 3-Plans 5 Stoffelen (2018), Khalil et al. (2021), Sipos et al. (2021), Revilla and Moure (2021), Bogacz-Wojtanowska et al. (2019) 4-Partnerships 4 Briedenhann and Wickens (2004), Sipos et al. (2021), Li et al. (2020), Naramski and Szromek (2019) 5-Programs 3 Stepanova (2017), Kołodziejczyk (2020), Olsen (2003) 6-Intercooperation 2 Stoffelen (2018), Naramski and Szromek (2019) 9-Association 2 Stepanova (2017), Revilla and Moure (2021) 8-Sub-Project 1 Khalil et al. (2021) 9-Regulations 1 Bogacz-Wojtanowska et al. (2019) 10-Letter of Intent 1 Bogacz-Wojtanowska et al. (2019) 11-Alliance 1 Briedenhann and Wickens (2004) 12-Mission Statement 1 Bogacz-Wojtanowska et al. (2019) 13-Bylaws 1 Bogacz-Wojtanowska et al. (2019) 14-Barter 1 Frost and Shanka (2001) Note: Research Data. Name and frequency of instruments and the authors who cited them. H.L.K. Leite et al.

Journal of Hospitality and Tourism Management 57 (2023) 84–96 91 institutionally embedded in a broader regional organization (Stoffelen, 2018). For Vujko and Gajic (2014), there must be standardization of services at multiple levels, such as categorizing the accommodation facilities to indicate whether they are adapted for cycling tourists or other types of sports and recreational tourists, and implementing pricing and fee policies (Severino et al., 2021; Stepanova, 2017). To implement planning, the reviewed studies emphasize the importance of controlling the route’s finances (Li & Hu, 2019) and establishing a stable financial organization with clear, long-term financial agreements (Stoffelen, 2018). These agreements can take the form of sponsorships (Naramski & Szromek, 2019) or other forms of support. Financing the establishment of a route can be problematic and hinder development (Briedenhann & Wickens, 2004). Therefore, cooperation plays a crucial role in securing financing and/or co-financing (Stoffelen, 2018), assisting in obtaining modern technologies (Li & Hu, 2019) and in disseminating, and promoting the route through strategic marketing actions (Peng et al., 2016; Rainero & Modarelli, 2020; Severino et al., 2021; Stoffelen, 2018). This promotion is primarily achieved through joint actions (Bogacz-Wojtanowska et al., 2019; Kolodziejczyk, 2020; Naramski & Szromek, 2019; Revilla & Moure, 2021), the creation of joint events and festivals, and the distribution of route maps (Rainero & Modarelli, 2020) and other way of dissemination materials. To effective tap into the tourism market and its growing demand, regions need to provide information to potential visitors before their departure, as this is the stage where travelers plan their destination and trip (Olsen, 2003). For example, both large and small cities in inland and remote areas are developing the capacity to organize events and festivals to attract tourists and achieve positive results and returns for the territory (Rainero & Modarelli, 2020). In terms of finance, various investments should be made (Sipos et al., 2021), in infrastructure (Frost & Shanka, 2001), particularly in transportation (Kolodziejczyk, 2020). Transportation is a crucial factor in the economic integration of countries and regions, international cooperation, and a tourist’s choice of travel (Severino et al., 2021). Therefore, it is important to emphasize that the availability of tourism infrastructure, especially in terms of transport accessibility, is highlighted in Table 1, presented in Section 3.1. An example of the importance of transportation infrastructure is the need to connect railway tracks with existing cycle lanes, which can enhance route stability in the absence of a cross-border management structure (Stoffelen, 2018). Olsen (2003) indicated that people in the short-trip tourism market often prefer to travel close to home, but the radius for most travelers can extend to approximately 800 km. This rapidly growing market represents a significant opportunity for regional areas and specific thematic routes that cater to holiday preferences, highlighting the need for statewide and regional transportation and infrastructure provisions. The impact on regional development is limited by the ability of tourism and transportation professionals to facilitate visitor travel through the road network safely and efficiently. This is where tourismthemed routes can play a crucial role in the country’s future road infrastructure planning. Thus, road safety becomes essential for tourism and transportation planners, and it requires coordination and improvement (Olsen, 2003). In addition to investments in transportation infrastructure, attention should be given to regional infrastructure development (Khalil et al., 2021). Although it may seem initially focused on rural tourism, it ultimately promotes the growth of agricultural production, generating employment opportunities in rural areas and contributing to the development of the rural economy. This impact encompasses economic benefits such as earning opportunities, employment, trade, and other financial advantages for residents. The benefits of cooperation are diverse and interdisciplinary, as listed below. Cooperation in rural tourism routes is maintained and reinforced through communication (Frost & Shanka, 2001; Stepanova, 2017), including the sharing of experiences (Bogacz-Wojtanowska et al., 2019; Naramski & Szromek, 2019; Stepanova, 2017; Tikunov et al., 2018) and learning facilitated by companies that provide information and support knowledge formation (Stepanova, 2017). This learning process involves competent personnel and the employment of a qualified labor force through education. Moreover, cooperation is sustained and strengthened through selfassessment, which involves ongoing qualitative reflections on crossborder cooperation, management, and stakeholder participation experiences (particularly in the case of cross-border routes), rather than relying solely on quantitative outcome indicators (Stoffelen, 2018). Measuring visitor satisfaction is important (Stoffelen, 2018), with special attention given to identifying weaknesses and threats that can serve as crucial tools for future improvement (Rainero & Modarelli, 2020). Regarding learning, the analyzed studies indicate the involvement of educational institutions in cooperation in rural tourism routes. Hiring qualified human resources is essential, and one possible solution is to train professionals and provide continuous internships through close cooperation with universities (Sipos et al., 2021). The literature also highlights the need for companies to take the initiative in providing information and support for knowledge-building among tourism companies, investors, and educators in the regions involved (Stepanova, 2017). This support is made possible through strategic alliances with institutions such as boards, universities (offering short courses and mentoring programs), foundations, and park development organizations (Briedenhann & Wickens, 2004). Furthermore, higher education institutions can play a significant role in organizing, planning, and implementing tourism routes, given their geographical proximity and regional integration (Sipos et al., 2021), thereby encouraging project implementation and research (Stepanova, 2017). All these efforts combine to create long-term, stable, and attractive tourism products (Naramski & Szromek, 2019; Peng et al., 2016; Stoffelen, 2018) that are authentic, original, and unique (Bogacz-Wojtanowska et al., 2019). In other words, they foster joint tourism products within the route (Naramski & Szromek, 2019). Revilla and Moure (2021) propose that the territory can determine the product. Similarly, Naramski and Szromek (2019) suggest that one territory can create network products based on the route’s theme and the products of individual or geographically close establishments. It is important to note that the quality and social responsibility of a regional tourism product are determined not by a single organization but by its collective result as a self-organization. Gastronomy, culture, and tourism can be associated with a single activity to create a perfect symbiosis in a global product, which helps drive regional development and assists the local economy through the circular flow of income (Revilla & Moure, 2021). The importance of factors impacting the development of the tourism potential of regions and rural tourism routes (Tables 1 and in Section 3.1) is reiterated. Therefore, cooperation in rural tourism routes will lead to the fulfillment of the stated goals and generate several benefits. • It develops trust, a sense of justice, and dignity (restoring the right to access or not to be forgotten) (Bogacz-Wojtanowska et al., 2019). • It facilitates politics between neighboring regions (Kolodziejczyk, 2020; Li & Hu, 2019). • It creates long-term stability by facilitating the establishment of adaptive management, which provides financial and organizational stability in coping with unforeseen complexities and establishes a shared mindset among the stakeholders involved (Stoffelen, 2018). • It protects natural resources (Li & Hu, 2019). • It assists in implementing sustainable tourism for rural areas by integrating agricultural aspects and traditions (Rainero & Modarelli, 2020). • It promotes regional tourism (Li & Hu, 2019). H.L.K. Leite et al.

Journal of Hospitality and Tourism Management 57 (2023) 84–96 92 • It contributes to the equal distribution of regional economic benefits, improving the level of social cohesion (Li & Hu, 2019). • It generates competitive advantages (Stepanova, 2017) by reducing costs and creating value for customers (Naramski & Szromek, 2019), combining resources (Peng et al., 2016), or jointly using natural and cultural heritage as one of the mechanisms to increase attractiveness (Stepanova, 2017). • It reduces the effects of tourism seasonality (Naramski & Szromek, 2019). • It minimizes the loss of local cultural and regional identity while including sustainable development practices and heritage preservation for future generations (Naramski & Szromek, 2019). • It fosters the growth of organizational learning and knowledge sharing (Naramski & Szromek, 2019). • It generates potential synergies (Bogacz-Wojtanowska et al., 2019; Frost & Shanka, 2001; Naramski & Szromek, 2019; Rainero & Modarelli, 2020; Revilla & Moure, 2021; Sipos et al., 2021). • It promotes profitability/profits (Severino et al., 2021). • It generates indirect benefits for other individuals/sectors in the location (Khalil, 2021). On the other hand, not developing cooperation can present barriers for all those involved. For example, Briedenhann and Wickens (2004) clarify that if the different layers of government and the private sector do not resolve territorial wars and conflicts, they will not succeed. These conflicts manifest themselves between policymakers and the private industry, resulting in negative synergy that leads to a high degree of private sector negativism, local infighting, the presence of politicians uninterested in community well-being, unilateral actions, uncoordinated programs, inadequate promotional funding, duplicated effort, and waste of available resources. In addition to these barriers, some aspects hinder a quality experience, such as a lack of education, deficiencies in basic literacy, problems with access to training, and inadequacy of the programs offered (Briedenhann & Wickens, 2004). According to the same authors, this is due to the common lack of understanding and the inability of government officials to take responsibility, the lack of leadership and understanding of the private sector in its role to be developed, and the lack of understanding of the integrated nature of tourism and government. Specifically, regarding rural tourism routes connected by high-speed rail, this format has benefited peripheral regions. However, there has been a clear tendency for cooperation to disperse, with a significant weakening trend towards medium and long distances (Li et al., 2020). 3.3. Instruments that assist cooperation in rural tourism routes The analyzed studies present instruments that assist in formalizing and encouraging cooperation. The data points out that formalizing cooperation is relevant for the operation of rural tourism routes. This becomes evident when we observe that 72% of the studies explicitly present some instrument, with variations according to stakeholders’ expectations (Table 2), which encompass different institutional levels and formats. The most commonly used instruments include agreements (17%), projects (17%), and plans (14%). These instruments are elaborated with different objectives, such as financial agreements, financing, or cofinancing. They are related to sustainability and the environment, emergency health services on the route, inter-organizational coordination, actions related to opening borders, short or long-term transportation, and defining objectives or functions of local authorities, among others. Formalizing cooperation in the routes does not imply that the terms of the instruments should be rigid. For example, Bogacz-Wojtanowska et al. (2019) show that the degree of close community (cooperative) relationships between people and organizations on the routes varies. In their work, cooperation was greater when the degree of formalization of relationships between the manager and the objects of the route was lower. Interpersonal relationships are based on friendship, willingness to help one another (genuine involvement), and informal relationships. Cooperation is developed outside organizational structures (Bogacz-Wojtanowska et al., 2019), and community participation is the most important factor for its development (Bogacz-Wojtanowska et al., 2019; Briedenhann & Wickens, 2004). Therefore, a formal instrument that establishes and describes some of its terms is important. If tourism routes develop without minimum standards, planning, and comprehensive coordination, the fundamental premise of assurance and reliability that makes them attractive to the market may be undermined (Olsen, 2003). 3.4. Co-occurrence analysis The co-occurrence analysis of the keywords (Fig. 5) in the reviewed studies showed that the most frequently repeated terms include, in descending order, those related to rural tourism, agrotourism, destination, management, cooperation, community, typology (theme), innovation, policies, strategies, collaboration, networks, among others. The size of the circle and the word represents its occurrence frequency. The colors represent different clusters, and the length and thickness of the lines indicate their connections and proximity relationships. Fig. 5 corroborates these results, demonstrating the important role of cooperation in tourism routes for managing and integrating rural destinations with the community. Furthermore, it highlights the significance of factors present in the destinations (typology/theme) as a strategy for innovation. Finally, it reveals that the reviewed studies address "sustainable development" without connection to other terms, relating to one of the study’s central terms: "rural tourism". In other words, rural tourism serves to achieve sustainable development, with cooperation being the key to sustainability and simultaneously dependent on it, thus constituting the central point. 4. Discussion The data revealed that each region has its own peculiarities, resulting in different themes for rural tourism routes. The themes depicted in Fig. 3 emerge from the exploitation and improvement of existing factors in the destination, thereby enhancing the tourism potential of rural areas. The more these factors are refined, the more enriching the experience of rural tourism routes becomes. As suggested by Cruz-Ruiz et al. (2020), during the systematic review, we identified factors that impact the development of tourism potential in regions and, consequently, rural tourism routes (Table 1 and Fig. 6). Certain aspects are recurrent in the quotes and deserve highlighting. One major aspect is historical-cultural heritage or monuments (4.30%). This factor currently constitutes one of the pillars of sustainable development (Bogacz-Wojtanowska et al., 2019). These factors can encompass the unique characteristics of each community (McGehee et al., 2015). Enterprises participating in rural tourism routes can explore and improve these factors to increase tourist flow and, consequently, their income from tourism. By doing so, they can provide visitors with more engaging and memorable tourism experiences, thereby encouraging repeat visits to the rural tourism destination. The data presented 100 aspects, cited 163 times (n) in the reviewed studies. These aspects were categorized into seven factors and 22 subfactors, some of which were cited more frequently than others. These factors aid in identifying the themes of the routes and developing tourism products through cooperation. We identified the elements of cooperation in rural tourism routes (Fig. 4). These elements can serve as a checklist for stakeholders involved in the routes, facilitating better organization, financial security, balance, and stability. These elements contribute to the development and maintenance of cooperation in rural tourism routes, playing a H.L.K. Leite et al.

Journal of Hospitality and Tourism Management 57 (2023) 84–96 93 significant role in structuring the process. This study supports Foletto et al. (2018) by providing additional elements that address the challenges of implementing shared guidelines among different route members. The cooperation elements, supported by the factors present in rural tourism destinations, create a synergy that enhances the success of the tourism product, generating benefits and helping stakeholders achieve their objectives. It is important to note that this synergy is crucial for the sustainable development of rural tourism destinations. Fig. 5 verifies these findings, shedding light on potential interventions for policymakers and tourism planners. These underscores the role of responsible tourism as a sustainable framework for destination management (Mathew & Sreejesh, 2017). The data demonstrate that cooperation is essential for the economic development of rural tourism routes and that there are key instruments (Table 2 and Fig. 6) available to assist in formalizing cooperation, improving the terms of cooperation in rural tourism routes, enabling long-term maintenance, and promoting its practice. It is essential to emphasize that the choice of instruments will depend on the specific needs of the stakeholders. We found that these key components (factors, elements, and instruments) (Fig. 6) are necessary for the effective functioning of rural tourism routes and the success of their cooperation. As suggested by McGehee et al. (2015), the leaders of these routes can leverage these factors and elements to facilitate their success and invest in their further development. Fig. 7 illustrates the interaction of all the findings from the systematic review. This summary of the results provides in this systematic review, enabling readers to visualize the importance of each discussed section and the synergy between them. The roles of the key components have been observed: The key factors present in rural destinations facilitate the development of tourism potential in regions and contribute to the creation of tourism products. The key elements of cooperation enable its understanding and development, supported by the key instruments of formalization. The combination of factors and elements of cooperation allows for the development of tourism products, leading to benefits that align with the agreed-upon objectives of the stakeholders. The findings of McGehee et al. (2015) regarding the leadership of rural communities, including skills, experience, and personal values that foster social capital, connection, resource maximization, trust, reciprocity, and cooperation, align with the findings of this study. Each rural community adopts unique combinations of social capital and leadership approaches to facilitate its success. These results support Chuang (2010) in emphasizing the socio-psychological aspects of interactions between residents and tourists. These interactions influence residents’ attitudes Fig. 5. Co-occurrence analysis of the keywords. Fig. 6. Key Components that influencing cooperation in rural tourism routes. H.L.K. Leite et al.

Journal of Hospitality and Tourism Management 57 (2023) 84–96 94 and create synergies that benefit destinations, their sustainable development, and tourist experiences. Thus, this study addresses the theoretical gap concerning cooperation in rural tourism routes by introducing new elements for discussion, such as stakeholder interaction, meaningful community participation, supported from the public sector, trust, common purpose, planning, structure, finance, products, benefits, communication, learning, and self-assessment. Future research from different perspectives can further explore these key factors and key instruments. 5. Conclusions The research successfully achieved its objective and made significant advancements, providing answers to the research question and objective, as depicted in Figs. 6 and 7. Additionally, it identified the elements of cooperation in rural tourism routes (Fig. 4) and shed light on the outcomes resulting from their synergy. The results make valuable contributions to the academic debate by innovatively demonstrating the relationship between the key components (factors, elements, and instruments) necessary for fostering cooperation in rural tourism routes. Moreover, the results highlight their importance in generating synergies that benefit destinations, promote sustainable development, and enhance tourists’ experiences. Ultimately, our contribution lies in establishing a connection between the literature on cooperative strategies and the reality of rural tourism routes. This study also reveals the need for further research in rural tourism. As emphasized by Briedenhann and Wickens (2004), the potential of tourism routes has long been recognized in developed countries like Brazil. The scarcity of published research on this topic underscores the necessity and effort required to raise awareness of other initiatives from a discussion perspective. The significance of collective action in rural tourism enterprises becomes evident as they cannot operate in isolation. In certain situations, organizing tourism routes relies on collective and social actions. This expansion of the theme extends beyond the theoretical field and can encourage further empirical studies. The academic challenge in rural tourism research lies in advancing paradigms through rigorous theoretical and methodological approaches, thus fostering progress and opening new possibilities for interdisciplinary studies. The results offer stakeholders a checklist to effectively manage routes and plan their development. The identified benefits lead to the conclusion that cooperation in rural tourism routes enables the diversification of peripheral areas and contributes to their regeneration. Similar to the Wang et al. (2022) study, the selection of eligible articles followed the explicit procedures of PRISMA, enabling future review research possible and replicable, and brought some limitations. Concerning the inclusion and exclusion criteria used in the protocol, which may have resulted in the omission of content from studies not included in the analysis. For instance, just studies meeting the criteria for Q1 and Q2 quartiles were included, and nowadays some of them has the quality questioned. We recommend selecting journals focused on tourism with a strong tradition in this field. Other limitations were the terms used to identify articles might have excluded relevant papers, and the categorization and interpretation of data, being a revision can have subjectivity to some extent. Despite these limitations, several key findings emerged in this paper. Our results suggest a need for more in-depth discussions on the importance of cooperation elements in tourism studies. Our study used Web of Science and Scopus, and future studies can use multiple databases to include more articles for explorative analysis (Esfandiar et al., 2022). As suggestions for future research, we propose mapping the influence of different cooperation elements on cooperation in rural tourism routes, investigating the functioning of cooperation in rural tourism routes in the context of Covid-19 and the war in Ukraine, and further exploring the extent to which instruments facilitating formalized cooperation enhance interaction among stakeholders in rural tourism routes. Additionally, comparisons between cooperation in rural tourism in developed and less developed areas can be made, geographic perspectives can be utilized to examine the differences between eastern and western paradigms, and future studies can focus on destination or intelligent destination concepts and their impact on visitors. Authors statements Helena de Lima Krauss Leite: Conceptualization, Formal analysis, Investigation, Data Curation and Writing - Original Draft. Erlaine Binotto: Conceptualization, Validation, Supervision and Project administration. Ana Claudia ´ Machado Padilha: Conceptualization, Validation and Supervision. Paulo Henrique de Oliveira Hoeckel: Review. Conceptualization Ideas; formulation or evolution of overarching research goals and aims. Methodology: Using PRISMA Protocol. Software: Using EXCEL, WORD and VOSviewer software. Validation: Verification, whether as a part of the activity or separate, of the overall replication/reproducibility of results/experiments and other research outputs. Fig. 7. Summary of cooperation process in rural tourism routes. H.L.K. Leite et al.

Journal of Hospitality and Tourism Management 57 (2023) 84–96 95 Funding acquisition: National Council for Scientific and Technological Development – CNPq, Coordination of Superior Level Staff Improvement, Foundation for Supporting the Development of Education, Science and Technology of the State of Mato Grosso do Sul, Federal University of Grande Dourados. Declaration of competing interest No potential conflict of interest was reported by the authors. Acknowledgement The second author to the National Council for Scientific and Technological Development – CNPq, Brazil for the research grant number 312225/2020–2. Resources from CNPq, Process 421523/2018–2, Foundation for Supporting the Development of Education, Science and Technology of the State of Mato Grosso do Sul - Fundect Process: 71/ 032.723/2022, Federal University of Grande Dourados, Postgraduate Program in Agribusiness and PROAP/Coordination of Superior Level Staff Improvement –CAPES supported this research, Brazil. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.jhtm.2023.09.005. References Anuar, M. A. K., & Marzuki, A. (2022). Critical elements in determining tourism routes: A systematic literature review. Geografie, 127, 319–340. https://doi.org/10.37040/ geografie.2022.010 Axerold, R. (2006). The evolution of cooperation (Revised Edition). Basic Books. Axerold, R., & Hamilton, W. D. (1981). The evolution of cooperation. Science, 211, 1390–1396. http://www.jstor.org/stable/1685895. Baggio, R., Scott, N., & Cooper, C. (2010). A review focused on tourism (Vol. 1). Network Science. https://arxiv.org/abs/1002.4766. Bogacz-Wojtanowska, E., Goral, ´ A., & Bugdol, M. (2019). The role of trust in sustainable heritage management networks. Case study of selected cultural routes in Poland. Sustainability, 11(10). https://doi.org/10.3390/su11102844 Briedenhann, J., & Wickens, E. (2004). Tourism routes as a tool for the economic development of rural areas-vibrant hope or impossible dream? Tourism Management, 25(1), 71–79. https://doi.org/10.1016/S0261-5177(03)00063-3 Castaner, ˜ X., & Oliveira, N. (2020). Collaboration, coordination, and cooperation among organizations: Establishing the distinctive meanings of these terms through a systematic literature review. Journal of Management, 46(6), 965–1001. https://doi. org/10.1177/0149206320901565 Chuang, S. (2010). Rural tourism: Perspectives from social exchange theory. Social Behavior and Personality, 38(10), 1313–1322. https://doi.org/10.2224/ sbp.2010.38.10.1313 Correia, A., Vaughan, R., Edwards, J., & Silva, G. (2014). O Potential para a Cooperaçao ˜ entre Empresas de Turismo e Produç˜ ao de Vinho na Oferta De Experiˆencias Turísticas: O Caso da Regi˜ ao do Douro, em Portugal. RPER, (36), 43–55. https://doi. org/10.59072/rper.vi36.421 Cruz-Ruiz, E., Zamarreno-Aramendia, ˜ G., & De La Cruz, E. R. R. (2020). Key elements for the design of a wine route. The case of la axarquía in M´ alaga (Spain). Sustainability, 12(21), 1–19. https://doi.org/10.3390/su12219242 Esfandiar, K., Pearce, J., Dowling, R., & Goh, E. (2022). Pro-environmental behaviours in protected areas: A systematic literature review and future research directions. Tourism Management Perspectives, 41. https://doi.org/10.1016/j.tmp.2022.100943. Article 100943. Fang, W. T., & Fang, W. T. (2020). Rural tourism. Tourism in emerging economies: The way we green (pp. 103–129). Sustainable, and Healthy. https://doi.org/10.1007/978- 981-15-2463-9 Foletto, S., Thom´e-Ortiz, H., Santos, E. O., & Gonz´ alez, N. A. A. (2018). Fatores que interferem no desenvolvimento do turismo sustentavel ´ no espaço rural do roteiro turístico Vale dos Vinhedos, de Bento Gonçalves, Rio Grande do Sul, Brasil. Estudios Latinoamericanos, 35, 115–131. https://doi.org/10.25112/rgd.v15i2.1252 Frost, F. A., & Shanka, T. (2001). Cape to Cairo - Can the dream be realised? Journal of Vacation Marketing, 7(3), 235–244. https://doi.org/10.1177/135676670100700304 Hamilton, W. D. (1964). The genetical evolution of social behavior I and II. Journal of Theoretical Biology, 7, 1–52. https://doi.org/10.1016/0022-5193(64)90038-4 Ignarra, L. R. (2013). Fundamentos do turismo (Vol. 3). Editora Senac. Jesus, C., & Franco, M. (2016). Cooperation networks in tourism: A study of hotels and rural tourism establishments in an inland region of Portugal. Journal of Hospitality and Tourism Management, 29, 165–175. https://doi.org/10.1016/j.jhtm.2016.07.005 Johnson, P. A. (2010). Realizing rural community based tourism development: Prospects for social-economy enterprises. Journal of Rural and Community Development, 5(1), 150–162. https://journals.brandonu.ca/jrcd/article/view/349. Khalil, I. U., Hena, S., Ghani, U., Ullah, R., Jan, I., Rauf, A., & Jingdong, L. (2021). Development and sustainability of rural economy of Pakistan through local community support for CPEC. Sustainability, 13(2), 1–17. https://doi.org/10.3390/ su13020686 Kolodziejczyk, K. (2020). Cross-border public transport between Poland and Czechia and the development of the tourism functions of the region. Geographia Polonica, 93(2), 261–285. https://doi.org/10.7163/GPol.0173 Komppula, R. (2014). The role of individual entrepreneurs in the development of competitiveness for a rural tourism destination–A case study. Tourism Management, 40, 361–371. https://doi.org/10.1016/j.tourman.2013.07.007 Lane, B. (1994). What is rural tourism? Journal of Sustainable Tourism, 2, 1–2. https://doi. org/10.1080/09669589409510680 Leask, A. (2010). Progress in visitor attraction research: Towards more effective management. Tourism Management, 31(2), 155–166. https://doi.org/10.1016/j. tourman.2009.09.004 Leask, A. (2016). Visitor attraction management: A critical review of research 2009–2014. Tourism Management, 57, 334–361. https://doi.org/10.1016/j. tourman.2016.06.015 Li, G., & Hu, W. (2019). A network-based approach for landscape integration of traditional settlements: A case study in the wuling mountain area, southwestern China. Land Use Policy, 83, 105–112. https://doi.org/10.1016/j. landusepol.2019.01.043 Li, L., Lu, L., Xu, Y., & Sun, X. (2020). Influence of high-speed rail on tourist flow network in typical tourist cities: An empirical study based on the hefei–fuzhou high-speed rail in China. Asia Pacific Journal of Tourism Research, 25(11), 1215–1231. https://doi. org/10.1080/10941665.2020.1821387 Lourens, M. (2007). Route tourism: A roadmap for successful destinations and local economic development. Development Southern Africa, 24(3), 475–490. https://doi. org/10.1080/03768350701445574 Ma, X. L., Dai, M. L., & Fab, D. X. F. (2020). Cooperation or confrontation? Exploring stakeholder relationships in rural tourism land expropriation. Journal of Sustainable Tourism, 28(11), 1841–1859. https://doi.org/10.1080/09669582.2020.1762622 Mathew, P. V., & Sreejesh, S. (2017). Impact of responsible tourism on destination sustainability and quality of life of community in tourism destinations. Journal of Hospitality and Tourism Management, 31, 83–89. https://doi.org/10.1016/j. jhtm.2016.10.001 McGehee, N., Knollenberg, W., & Komorowski, A. (2015). The central role of leadership in rural tourism development: A theoretical framework and case studies. Journal of Sustainable Tourism, 23(8–9), 1277–1297. https://doi.org/10.1080/ 09669582.2015.1019514 Meyer, D. (2004). Tourism routes and gateways: Key issues for the development of tourism routes and gateways and their potential for pro-poor tourism. ODI discussion paper. Moulin, C., & Boniface, P. (2001). Routeing heritage for tourism: Making heritage and cultural tourism networks for socio-economic development. International Journal of Heritage Studies, 7(3), 237–248. https://doi.org/10.1080/13527250120079411 Naramski, M., & Szromek, A. R. (2019). Configuring a trust-based inter-organizational cooperation network for post-industrial tourist organizations on a tourist route. Sustainability, 11(13), 3542. https://doi.org/10.3390/su11133542 Olsen, M. (2003). Tourism themed routes: A queensland perspective. Journal of Vacation Marketing, 9(4), 331–341. https://doi.org/10.1177/135676670300900403 Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., … Moher, D. (2020). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 2021(71). https://doi.org/10.1136/bmj.n71 Peng, H., Zhang, J., Liu, Z., Lu, L., & Yang, L. (2016). Network analysis of tourist flows: A cross-provincial boundary perspective. Tourism Geographies, 18(5), 561–586. https://doi.org/10.1080/14616688.2016.1221443 Pilving, T., Kull, T., Suˇskevics, M., & Viira, A. H. (2019). The tourism partnership life cycle in Estonia: Striving towards sustainable multisectoral rural tourism collaboration. Tourism Management Perspectives, 31, 219–230. https://doi.org/ 10.1016/j.tmp.2019.05.001 Raihani, N. (2021). The social instinc-how cooperation shaped the world. Penguin Random House. Rainero, C., & Modarelli, G. (2020). The attractive power of rural destinations and a synergistic community cooperative approach: A “tourismability” case. Sustainability, 12(17), 7233. https://doi.org/10.3390/su12177233 Revilla, M. R. G., & Moure, O. M. (2021). Wine as a tourist resource: New manifestations and consequences of a quality product from the perspective of sustainability. Case analysis of the province of malaga. ´ Sustainability, 13(23), Article 13003. https://doi. org/10.3390/su132313003 Rogerson, C. M. (2007). Tourism routes as vehicles for local economic development in South Africa: The example of the magaliesberg meander. Urban Forum, 18, 49–68. https://doi.org/10.1007/s12132-007-9006-5, 2007. Rosalina, P. D., Dupre, K., & Wang, Y. (2021). Rural tourism: A systematic literature review on definitions and challenges. Journal of Hospitality and Tourism Management, 47(March), 134–149. https://doi.org/10.1016/j.jhtm.2021.03.001 Severino, A., Martseniuk, L., Curto, S., & Neduzha, L. (2021). Routes planning models for railway transport systems in relation to passengers’ demand. Sustainability, 13(16), 8686. https://doi.org/10.3390/su13168686 Shamseer, L., Moher, D., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., & Stewart, L. (2015). Preferred reporting items for systematic review and metaanalysis protocols (PRISMA-P) 2015: Elaboration and explanation. Research Methods & Reporting, 349, g7647. https://doi.org/10.1136/bmj.g7647 H.L.K. Leite et al.

Journal of Hospitality and Tourism Management 57 (2023) 84–96 96 Singala, M., Kumar, S., Donthu, N., Sureka, R., & Joshi, Y. (2021). A bibliometric overview of the journal of hospitality and tourism management: Research contributions and influence. Journal of Hospitality and Tourism Management, 47, 273–288. https://doi.org/10.1016/j.jhtm.2021.04.005 Sipos, N., Pap, N., Gonda, T., & Jarjabka, A. ´ (2021). Feasibility and sustainability challenges of the süleyman’s türbe cultural-tourism centre project in Szigetv´ ar, Hungary. Sustainability, 13(10), 5337. https://doi.org/10.3390/su13105337 Stepanova, S. V. (2017). Cross-border tourist routes: The potential of Russia’s northwest. Baltic Region, 9(4), 97–112. https://doi.org/10.5922/2079-8555-2017-4-7 Stoffelen, A. (2018). Tourism trails as tools for cross-border integration: A best practice case study of the vennbahn cycling route. Annals of Tourism Research, 73, 91–102. https://doi.org/10.1016/j.annals.2018.09.008 Tikunov, V. S., Belozerov, V. S., Panin, A. N., & Antipov, S. (2018). Geoinformation monitoring of key queries of search engines, and geotagging photos in the NorthCaucasian segment of the tourist route ‘Great Silk Road’. Annals of GIS, 24(4), 255–260. https://doi.org/10.1080/19475683.2018.1501606 Trivers, R. L. (1971). The evolution of reciprocal altruism. The Quarterly Review of Biology, 46, 35–57. http://www.jstor.org/stable/2822435. Vujko, A., & Gajic, T. (2014). Opportunities for tourism development and cooperation in the region by improving the quality of tourism services – the ‘Danube Cycle Route’ case study. Economic Research-Ekonomska Istrazivanja, 27(1), 847–860. https://doi. org/10.1080/1331677X.2014.975517 Wang, M., Rasoolimanesh, S. M., & Kunasekaran, P. (2022). A review of social entrepreneurship research in tourism: Knowledge map, operational experiences, and roadmaps. Journal of Sustainable Tourism, 30(8), 1777–1798. https://doi.org/ 10.1080/09669582.2021.2007255 Wilke, E. P., Costa, B. K., Freire, O. B. de L., & Ferreira, M. P. (2019). Interorganizational cooperation in tourist destination: Building performance in the hotel industry. Tourism Management, 72, 340–351. https://doi.org/10.1016/j.tourman.2018.12.015 World Bank. (2010). Sustainable tourism and cultural heritage: A review of development assistance and its potential to promote sustainability. https://documents.worldbank. org/pt/publication/documents-reports/documentdetail/551751468176048723/sus tainable-tourism-and-cultural-heritage-a-review-of-development-assistance-and-its -potential-to-promote-sustainability. Yachin, J. M., & Ioannides, D. (2020). “Making do” in rural tourism: The resourcing behaviour of tourism micro-firms. Journal of Sustainable Tourism, 28(7), 1003–1021. https://doi.org/10.1080/09669582.2020.1715993 Yang, J., Yang, R., Chen, M. H., Su, C. H. J., Zhi, Y., & Xi, J. (2021). Effects of rural revitalization on rural tourism. Journal of Hospitality and Tourism Management, 47, 35–45. https://doi.org/10.1016/j.jhtm.2021.02.008 Zyrianov, A., & Zyrianova, I. (2021). Planning of the interregional tourist route in the urals. Quaestiones Geographicae, 40(2), 109–118. https://doi.org/10.2478/quageo2021-0018 H.L.K. Leite et al.

Journal of Hospitality and Tourism Management 57 (2023) 48–60 Available online 9 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. Deconstructing consumers’ low-carbon tourism promotion preference and its consequences: A heuristic-systematic model Aiping Zhang a , Wei Xi b , Feng Zeng Xu b,c,d,* , Ruiyi Wu b a School of Business, Shandong Management University, Jinan, Shandong, 250357, China b School of Management, Shandong University, Jinan, Shandong, 250100, China c Institute of State Governance, Shandong University, Jinan, Shandong, 250100, China d Center for Service Strategy and Service Management, Shandong University, Jinan, Shandong, 250100, China ARTICLE INFO Keywords: Low-carbon tour promotion Consumer preference Heuristic systematic model Tourism experience Perceived travel agency image Low-carbon tourism behavior intention ABSTRACT In the context of low-carbon tour promotion, consumers lack the motivation to translate environmental awareness into practical action; moreover, it is unclear which form of promotion is the most effective for travel agencies. Thus, this study considers consumers’ preference for low-carbon promotion as an entry point and adopts the best-worst scaling method to analyze their preference characteristics. In addition, it introduces a heuristic-systematic model to analyze the influence of consumer preferences on travel agency image and lowcarbon tourism behavior intention. The results show that consumer preferences are deconstructed into different types of tourism experiences according to heuristic and systematic paths, such that they create a positive effect on image evaluation and behavioral intentions. This study reveals the significance of consumer preference in low-carbon tour promotion scenarios, which helps break the promotion deadlock and promote tourism enterprises to optimize their service design. 1. Introduction The tourism industry is generally carbon-intensive (Lenzen et al., 2018). All aspects of tourism, such as transportation, hotel accommodations, destinations, travel agencies, and restaurants, consume energy and produce carbon emissions. To reduce this negative impact, low-carbon tourism has gained attention as a new form of promoting sustainable development (Becken, 2017; Fakfare & Wattanacharoensil, 2022; Zhang & Zhang, 2020a, 2020b). However, there has always been a marketing impasse in low-carbon tourism: many tourists, even if they are aware of the potential environmental impact of tourism, are reluctant to change their behavior because they perceive it as a threat to their personal freedom to travel (Steiger et al., 2019). Additionally, many tourism companies generally believe that the provision of low-carbon products and services will destroy the tourist experience and intentionally fail to fully communicate sustainable development practices (Font et al., 2017). Any commitment to reducing carbon emissions must be implemented by enterprises and consumers (Gossling ¨ et al., 2023). Although consumers are not obliged to reduce carbon emissions on an individual level, their consumption patterns are highly correlated with carbon emission growth. A previous study has found that consumers enjoy the professional services and trust the advice provided by travel agencies (Law et al., 2015). Therefore, the role of travel agencies in promoting low-carbon consumption and green purchasing should not be underestimated (Font et al., 2021; Hsiao et al., 2021). However, few studies have considered how to break the marketing deadlock and encourage tourism enterprises to carry out low-carbon promotion actively (Zhang & Zhang, 2021). Although mandatory measures such as carbon taxes and higher prices for tourism products can achieve carbon reduction in the short term, they are also more likely to pit enterprises and consumers against each other. Promoting shared value between the two parties seems more sustainable than considering one party’s interests alone (Font et al., 2021; Font & McCabe, 2017). Consumers’ preference for sustainable activities has been found to significantly affect their subsequent engagement, loyalty, and behavior (Tao et al., 2022; Wehrli et al., 2017). Therefore, when providing and marketing low-carbon tourism products, tourism enterprises should evaluate their effectiveness and suitability from the tourist perspective (Juvan & Dolnicar, 2014). However, it is unclear which form of marketing promotion is more effective in low-carbon tourism, and the impact of consumer preferences * Corresponding author. School of Management, Shandong University, Jinan, Shandong, 250100, China E-mail addresses: [email protected] (A. Zhang), [email protected] (W. Xi), [email protected] (F.Z. Xu), [email protected] (R. Wu). 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.2023.08.020 Received 23 November 2022; Received in revised form 12 June 2023; Accepted 29 August 2023

Journal of Hospitality and Tourism Management 57 (2023) 48–60 49 remains to be explored (Hsiao et al., 2021). Accordingly, we proposed two research questions as follows: (1) What are the characteristics of consumers’ preference for low-carbon tour promotion by travel agencies? (2) How does this preference bring about follow-on effects, such as positive travel agency image or low-carbon tourism behavior intention? To answer these questions, we adopted the best-worst scaling (BWS) approach (Lee et al., 2008; Louviere et al., 2013) to measure and rank consumers’ preferences for low-carbon promotion. To further analyze the subsequent impact of preferences, we used the heuristic-systematic model (HSM; Chaiken, 1980) to consider how consumers deconstruct preferences based on heuristic and systematic paths and ultimately achieve beneficial personal and organizational outcomes. In the marketing process, the tourism experience is an important factor affecting tourists’ follow-up intention and behavior (Lee & Jan 2019). Although sustainable practices require some sacrifice and adaptation, this does not mean low-carbon tourism runs counter to a high-quality tourism experience (Manthiou et al., 2022). Therefore, we used different types of tourism experiences as mediating variables to explore how preferences are deconstructed, so as to understand what customers expect and optimize service design from the source. The study included two phases. First, we used the BWS method to measure consumers’ preferences and summarized the main characteristics. Then, taking the preference score as the starting point of the second phase, we measured the influence of preference on perceived travel agency image and low-carbon tourism behavior intention. The research contributes to forming a value-sharing mechanism between consumers and enterprises and promotes the carbon reduction to be embedded in a positive feedback loop, enriching the findings in the sustainable tourism marketing field. Our conclusions also reveal ways to motivate carbon reduction stakeholders and provide implications for what kind of experiences are effective in low-carbon promotion. 2. Theoretical framework and hypothesis development 2.1. Heuristic systematic model The HSM is an effective theoretical framework for explaining individual information processing, evaluation, and decision-making (Chaiken, 1980). It holds that there are the following two parallel paths when people analyze and process information cues: One is the heuristic path, in which people make less cognitive effort and make more irrational evaluations based on external, explicit, and formal cues; the other is the systematic path, in which people try to thoroughly understand the available information through careful attention, deep thinking, and intense reasoning, mainly based on central clues and internal characteristics of the information (Chen & Chaiken, 1999). The HSM assumes that heuristic and systematic processing can occur simultaneously and significantly influence the results, called the additive effect. More importantly, the two paths interact with each other. When the heuristic path plays a dominant role, the role of the systematic path is weakened, and vice versa. This is defined as the attenuation effect (Zhang et al., 2014). The HSM is widely used in information processing and decisionmaking situations (Chang & Wu, 2015; Fu et al., 2020; Siddiqi et al., 2020) and has many applications in the tourism decision-making context (Ham et al., 2019; Kim et al., 2017; Shi et al., 2021). For low-carbon tourism products, because of heterogeneity and intangibility, consumers rely primarily on the acquired characteristics and clues to form judgments and make decisions. Among them, as organizers, the marketing promotion information of travel agencies is an important source of clues and has a crucial impact on shaping consumers’ subsequent attitudes and behavioral intentions (Hsiao et al., 2021). Therefore, in this study, we used the HSM to analyze how consumer preferences and the experiences they cause affect the final image perception and behavioral intentions. 2.2. Low-carbon tourism and tourism experience Low-carbon tourism is a concrete form of environmentally responsible behavior (Liu et al., 2022), and its typical feature is that tourists consider the possible negative impact on the environment and try to reduce carbon emissions during tourism activities (Becken, 2017). To reduce their carbon footprint, tourists can change different aspects, such as food, lodging, shopping, and entertainment. For example, Lumsdon and McGrath (2011) suggest that using low-carbon means of transportation, such as walking and cycling, can effectively reduce its negative impact on the local environment. Additionally, staying longer at the destination (Dickinson et al., 2011), using eco-friendly products provided by travel agencies (Hsiao et al., 2021), and choosing foods with a low-carbon footprint (Liu et al., 2022) are all feasible ways to reduce carbon emissions, as the calculation of the carbon footprint of tourism is based on industry and specific tourism activities (Lee & Jan 2019). Low-carbon tourism contributes to a sense of meaningfulness. Changes in usual travel activities, forms, and objectives can also help relieve boredom, bring excitement and surprise, and produce novel experiences (Lee & Crompton, 1992; Wu et al., 2022). Moreover, according to the low-carbon tourism experience scale developed by Lee and Jan (2019), hedonic elements, such as pleasure, comfort, and excitement, are important components. Therefore, we chose meaningfulness, novelty, and hedonism as typical experience representatives to explore how tourists’ promotion preferences are deconstructed. To control for the possible effects of the demographic variables, we added gender, age, and education as control variables to the model. Fig. 1 illustrates the conceptual framework of the study. In this study, we regarded hedonic and novelty experiences as heuristic factors and meaningful experiences as systematic factors. Generally, external cues and dominant characteristics are seen as heuristics in the HSM, whereas central cues and intrinsic characteristics are viewed as systematic (Todorov et al., 2002). Perceiving novelty is a relatively simple process of utilizing external or formally available cues, which consumes relatively few cognitive resources (Encinar & Munoz, 2006; Watts & Zhang, 2008). Hedonic experience is mainly based on the subjective judgment of emotion, with strong irrational colors (Siddiqui et al., 2018; Watts & Zhang, 2008). Therefore, the two can be seen as a heuristic way to interpret clues. Conversely, the perception of meaningfulness requires more cognitive resources. It is a process of gaining a thorough understanding of information through deep thinking and intensive reasoning (Todorov et al., 2002). Therefore, it should be considered systematic. 2.3. Impacts of tourist experiences on performance 2.3.1. Additivity effect between heuristic and systematic processing A novelty experience is defined as the experience of something new that is different from the usual experience and is widely considered a pleasant factor in tourism (Lee & Crompton, 1992; Mitas & Bastiaansen, 2018). Previous studies have mentioned novelty seeking as an important travel motivation (Lee & Crompton, 1992; Li & Cai, 2012). Oh et al. (2016) point out that one of the motivations and goals for people to carry out sustainable practice is to seek novel experiences through new places and people and to obtain feelings of excitement and surprise. Therefore, novelty is an important factor in the decision-making process for low-carbon tourism. Novelty experiences also inspire environmentally responsible behavior among visitors (Sthapit et al., 2022). Perceived novelty is an important component of customer satisfaction in the context of service innovation and has a positive impact on subsequent behavioral intentions (Truong et al., 2020). Additionally, novel experiences can trigger positive emotions such as pleasure (Mitas & Bastiaansen, 2018). It is also an important link to maintaining the relationship between enterprises and customers (Siu et al., 2013), which helps form a positive attitude and evaluation of enterprises (Blomstervik & Olsen, 2022). Therefore, we proposed the following hypotheses: A. Zhang et al.

Journal of Hospitality and Tourism Management 57 (2023) 48–60 50 Hypothesis 1a. Novelty experience is positively related to perceived travel agency image. Hypothesis 1b. Novelty experience is positively related to low-carbon tourism behavior intentions. Hedonic experience is a subjectively pleasing emotional response, including inner emotional satisfaction and feelings of comfort and relaxation (Bender et al., 2022). Hedonism in the travel experience has always been something that cannot be ignored, even in the context of low-carbon tourism. Moore (2012) claims that when people choose to contribute to environmental sustainability, it is often accompanied by a quest for personal well-being. Similarly, Strzelecka et al. (2018) find that volunteers hope to contribute to nature conservation, and if they can obtain hedonic experiences, their commitment can be strengthened further. Based on the above findings, we explored the impact of hedonic experiences on low-carbon tourism promotion. Regarding behavioral intentions, previous studies have repeatedly confirmed the role of hedonic experiences (Ryu et al., 2010; Yang & Mattila, 2016). The same is true in the green tourism context (Jiang & Kim, 2015; Strzelecka et al., 2018). This is because once consumers experience hedonism stemming from activities, they are more likely to show a tendency to expect the same experience again (Dedeoglu et al., 2018). Perceived image is subjective knowledge and attitude, which is the overall impression of the enterprise formed in consumers’ minds (Hussein et al., 2018). Image formation is the process of transformation through ideas, feelings, and experiences. Hedonic experience is closely related to a positive emotional state, making it easier for consumers to form positive evaluations and judgments (Ladhari, 2007; Oliver, 1993). Therefore, we proposed the following hypotheses: Hypothesis 2a. Hedonic experience is positively related to perceived travel agency image. Hypothesis 2b. Hedonic experience is positively related to lowcarbon tourism behavior intentions. Meaningfulness embodies an individual’s inherent need to find fulfilling meaning for their actions to bring about a sense of accomplishment, which often includes imparting social impact and contributing to others (Rejikumar et al., 2021). The establishment of meaningfulness requires individuals to be able to evaluate the sense of value brought about by travel and understand its transformative effect on personal development (Jose et al., 2022). Rejikumar et al. (2021) examine the positive relationship between perceived meaning, destination image, and behavioral intention. Meaningful experiences can positively influence customer satisfaction, sustainable consumption (Minton et al., 2018), and behavioral intentions (Truong et al., 2020) and are also considered an important indicator of the value of travel provider services (Busser & Shulga, 2018). According to the additive effect, the systematic process affects an individual’s judgment and decisions. Therefore, we proposed the following hypotheses: Hypothesis 3a. Meaningful experience is positively related to perceived travel agency image. Hypothesis 3b. Meaningful experience is positively related to lowcarbon tourism behavior intentions. 2.3.2. Attenuation effect between heuristic and systematic processing According to the theoretical assumption, when the heuristic path dominates the decision-making process, the utility of the systematic path diminishes, and vice versa (Chaiken et al., 1989; Chen & Chaiken, 1999; Zhang et al., 2014). Under the low-carbon promotion scenario, consumers who expect novel and hedonic experiences pay attention to formal features and external cues and use readily available, significant, and tractable cues for decision-making (Chaiken, 1980). In this case, their judgments and decisions are irrational and emotional and have a positive impact on image evaluation and attitude formation (Prayag et al., 2015). Therefore, we argue that compared with the positive utility brought by meaningful experience, novelty and hedonic experience will have a more pronounced impact on perceived travel agency image because of the characteristics of stimulation and pleasure (Bender et al., 2022; Blomstervik & Olsen, 2022). Correspondingly, consumers who expect meaningful experiences focus on internal features and central clues and spend cognitive resources to analyze content and value. They focus on clues that are relevant, critical, and typical of the event itself (Chaiken, 1980). In this case, their judgments and decisions are subject to a high degree of rational analysis and deep thinking (Chaiken et al., 1989). We proposed that in terms of low-carbon tourism behavior intention, given the high degree of participation and the time and energy investment, consumers are likely to develop a strong motivation for in-depth evaluation and systematic thinking (Chaiken et al., 1989; Zhang et al., 2014). As a result, the influence of the systematic path represented by meaningful experience will be more significant than the heuristic path. Therefore, we proposed the following hypotheses: Hypothesis 4a. Compared with meaningful experience, the novelty and hedonic experiences of a tourist will exert a stronger influence on perceived travel agency image. Hypothesis 4b. Compared with novelty and hedonic experiences, the meaningful experience of a tourist will exert a stronger influence on lowcarbon tourism behavior intentions. 2.4. Low-carbon tour promotion preference and tourist experience Travel purchases are experiential and personalized, and consumers’ Fig. 1. Conceptual research framework. A. Zhang et al.

Journal of Hospitality and Tourism Management 57 (2023) 48–60 51 pre-purchase evaluations involve different decision paths (Tsaur & Wang, 2009). Therefore, low-carbon tour promotion by travel agencies should consider consumers’ preferences and decisions (Ma et al., 2021). The individual preference of consumers is an important signal that helps enterprises understand what customers expect (Chatterjee & Mandal, 2020; Jarvis et al., 2017). In interpreting clues, the expected experiences are often manifested in different degrees of valence and arousal because of personal experience, personality characteristics, needs, and purposes. Therefore, the deconstruction of acquired clues varies from person to person (Knobloch et al., 2017). For example, an individual’s criteria for judging novelty are subjective or based on preference (Lepp & Gibson, 2003). For some tourists, novelty is positive, preferred, and intense; however, for others, the same cues may evoke different expectations and feelings (Petrick, 2002). Therefore, exploring the relationship between customer preferences and experience (Lee, 2018; Shen, 2014) is necessary. The essence of tourism is to obtain an ideal experience (Knobloch et al., 2017). Previous studies have emphasized the involvement of consumers in service design, which helps induce a positive impact on purchase intention (Robinson et al., 2012) and promotes value sharing between customers and enterprises (Font et al., 2021). If travel agencies want to mainstream the consumption of sustainable products, they should focus on the value consumers can obtain from sustainable actions (Font et al., 2021). Especially in fierce market competition, promoting low-carbon tourism products can only attract customers’ attention and bring practical utility if they meet the needs and preferences of customers (Jarvis et al., 2017). Travel agencies need to understand the deconstruction of consumer preferences to advance a reasonable experience design. Therefore, we proposed the following hypotheses: Hypothesis 5a. Tourists’ low-carbon tour promotion preference is positively related to novelty. Hypothesis 5b. Tourists’ low-carbon tour promotion preference is positively related to hedonism. Hypothesis 5c. Tourists’ low-carbon tour promotion preference is positively related to meaningfulness. 2.5. The mediating role of tourist experience 2.5.1. Heuristic processing: the mediating role of novelty experience and hedonic experience Identifying the differences among multiple mediation paths is important for mining the relationship between low-carbon tour promotion preference and its performance outcomes. According to the HSM and related literature on tourism experience, there are four specific indirect paths of heuristic processing in the multi-mediation model proposed in this paper: (1) low-carbon tour promotion preference → novelty experience → perceived image of tourism agency sequence; (2) lowcarbon tour promotion preference → novelty experience → behavior intention sequence; (3) low-carbon tour promotion preference → hedonic experience → perceived image of tourism agency sequence; and (4) low-carbon tour promotion preference → hedonic experience → behavior intention sequence. According to the theoretical framework of the HSM, heuristic processing can be regarded as relatively automatic; that is, it can occur when people are not motivated and able to consciously think about a topic (Ruiz-Mafe et al., 2018). When consumers receive information about low-carbon tourism promotions, their heuristic processing facilitates easy noticing of those easy-to-understand clues, that is, to invoke the heuristic perception of the hedonic and novel experiences that low-carbon tourism may bring and subsequently form a cognitive image of travel agencies and promote the subsequent intention or behavior (Qiu et al., 2022). Therefore, we proposed the following hypotheses: Hypothesis 6a. Novelty experience mediates the relationship between a tourist’s low-carbon tour promotion preference and their perceived travel agency image. Hypothesis 6b. Novelty experience mediates the relationship between a tourist’s low-carbon tour promotion preference and their low-carbon tourism behavior intentions. Hypothesis 7a. Hedonic experience mediates the relationship between a tourist’s low-carbon tour promotion preference and their perceived travel agency image. Hypothesis 7b. Hedonic experience mediates the relationship between a tourist’s low-carbon tour promotion preference and their lowcarbon tourism behavior intentions. 2.5.2. Systematic processing: the mediating role of meaningful experience As mentioned above, it is a systematic process for tourists to experience the significance of low-carbon tourism. Two specific indirect paths in the multi-mediation model are systematic processing: (1) lowcarbon tour promotion preference → meaningful experience → perceived image of tourism agency sequence; (2) low-carbon tour promotion preference → meaningful experience → behavior intention sequence. The HSM suggests that individuals tend to process information heuristically unless they are both motivated and able to engage in diligent systematic processing (Ma et al., 2021). Considering the meaningful experience induced by low-carbon tourism, it is as such a systematic process (Rejikumar et al., 2021). The role of systematic processing in influencing attitudes and behaviors is confirmed due to its association with competence and motivation(Qahri-Saremi & Montazemi, 2019). When tourists receive information about low-carbon tourism promotion, they pay attention to clues related to low-carbon and environmental protection through systematic processing. In this process, tourists are more likely to systematically perceive the meaningful experience that low-carbon tourism may bring, thus forming a cognitive image of travel agencies and promoting their subsequent behavior intentions. Therefore, we developed the following hypotheses: Hypothesis 8a. Meaningful experience mediates the relationship between a tourist’s low-carbon tour promotion preference and their perceived travel agency image. Hypothesis 8b. Meaningful experience mediates the relationship between a tourist’s low-carbon tour promotion preference and their lowcarbon tourism behavior intentions. 3. Methodology 3.1. Development of low-carbon tour promotion items We chose China as the study scenario because of its typicality; on the one hand, in terms of carbon emission reduction, China has committed to reducing greenhouse gas emissions by 65% by 2030 (Climate Action Tracker, 2021). Achieving this task requires the joint effort of enterprises and consumers. On the other hand, China’s tourism industry is still dominated by mass tourism, and the continuous expansion of the tourism scale has led to a sustained increase in carbon emissions (Luo et al., 2018). It is unwise to regulate carbon emissions by simply reducing the scale of tourism. In this case, China has significant potential and motivation to achieve its targets by strengthening the promotion of low-carbon tourism. We initially derived the low-carbon tour promotion items from the relevant literature (Anauate et al., 2020; Chang et al., 2019; Hsiao et al., 2021; Hsiao, 2016). To better fit the situation in China and improve the initial item design, we visited the official websites of tourism enterprises, focusing on the low-carbon tour promotion methods adopted. In addition, to further supplement information, we used convenience sampling to recruit participants with specific tourism experiences and then conducted simple focus group interviews with seven tourists. A. Zhang et al.

Journal of Hospitality and Tourism Management 57 (2023) 48–60 52 Combined with the literature review results and interviews, we formed a selection set containing 22 items. Two researchers reviewed the preliminary items; some were modified or merged if necessary. Following the classification dimension of Anauate et al. (2020), we positioned the items along the following two axes: benefits for tourists (i. e., immediate vs. future) and relevance to products (i.e., high vs. low), resulting in a set of 13 items distributed in four quadrants (Fig. 2). It is worth noting that these items are set for subsequent BWS analyses. Therefore, the criteria for item determination are not exhaustive but typical and representative to discover preference characteristics systematically and accurately. To ensure the practical feasibility of these items, we invited two tourism experts to further evaluate their feasibility and value. See Appendix A for the specific contents of each item. 3.2. Preference score for low-carbon tour promotion Unlike the Likert scale, we adopted the BWS method to analyze the preference for low-carbon tour promotion. Studies have demonstrated that consumers are easily influenced by social expectations and moral factors in questionnaire surveys, resulting in inaccurate and biased results (Auger et al., 2010). This is particularly evident regarding issues such as public welfare and environmental protection. Therefore, we refer to the BWS method proposed by Lee et al. (2008). This method could overcome the problem of over-scoring all items and has wide applications in marketing surveys (Louviere et al., 2013). Most BWS methods adopt a balanced incomplete block design, which requires each option to appear alone or in pairs with others at the same frequency and take order effects into account, ensuring that all items have appeared in different locations. In this study, we generated a total of 13 efficiently designed choice sets using original items, each with four items. Each item appears four times, and each pair of items appears once (see Table 1). Participants were required to select the most and least preferred item in each choice set. Through repeated comparisons, their preferences for each item could be inferred. In terms of preference calculation, the best-worst scores of all respondents could be analyzed as a whole, forming a ranking list of all 13 promotion items. To further analyze differences at the individual level, we used the R package of BWS tools developed by White (2021) to estimate individuals’ preference scores and then incorporated the scores into a structural equation model. Bayesian hierarchical modeling is the most used method when estimating the preference score for each participant in BWS. According to existing research, it is appropriate and feasible to use the individual preference scores calculated for subsequent structural equation estimation (Jarvis et al., 2017; O’Brien et al., 2020). 3.3. Questionnaire design The questionnaire consisted of three parts. The first was demographic data; the second used the simulation scenario method to measure whether the research model and hypotheses were valid; the third part measured consumers’ preference for items using the BWS method. The scenario-based survey method has been widely used in consumer decision-making behavior analysis. It could effectively shield the interference of irrelevant factors and accurately reflect the relationships among variables (Jun & Vogt, 2013). After reading the definitions, respondents were asked to select items that were not low-carbon tourism to check their comprehension. If the screening question was wrong, the questionnaire would end directly. Afterward, participants would read a list containing 13 low-carbon tour promotion items. They were required to stay on this page for at least 20 seconds to fully understand the details of each item. Subsequently, participants were randomly assigned to different scenarios. Travel modes included “alone” or “with friends”. The 13 promotion methods appeared with almost equal probability in questionnaire scenarios. The description was as follows: “Imagine that you are planning to go alone/with friends to a Creative Farm for a lowcarbon tourism campaign. Here is how a travel agency promotes it”. After reading a given scenario, participants were required to answer two questions to test the validity of the setting: “How realistic do you think the above scenario is?” and “According to this scenario, are you traveling with friends?” After understanding the situation, respondents were asked to answer follow-up questions based on the given scenario. All measures were derived from well-established scales used in previous studies. The expected experiences of novelty and hedonism were derived from the scale developed by Kim et al. (2012). The meaningful experience scale mainly referred to Kim et al. (2012) and Nazir et al. (2021). To measure the perceived image of travel agency, we adopted the scale used by Mody et al. (2017), whereas the measurement of low-carbon tourism behavior intention employed items used in the research of Kuo and Dai (2012). Items presented in the questionnaire were shuffled to avoid order effects. Finally, respondents were asked to complete the third part about item preferences. 3.4. Sample, data collection and analysis We collected data using an online research platform in China (http s://www.credamo.com,n.d.). Credamo has millions of registered users and supports the setting of random simulation scenario questionnaires. Previous studies have also utilized this platform to complete data collection (Su et al., 2021). We followed Brislin’s (1980) back-translation procedure to translate the English scale into Chinese and then translated the Chinese scale back into English, discussing and resolving the differences between the two English versions. After we Fig. 2. Low-carbon tour promotion items. completed the questionnaire design, 30 questionnaires were distributed Table 1 Balanced incomplete block design for the BWS method. Choice set Items 1 1 2 4 10 2 2 3 5 11 3 3 4 6 12 4 4 5 7 13 5 5 6 8 1 6 6 7 9 2 7 7 8 10 3 8 8 9 11 4 9 9 10 12 5 10 10 11 13 6 11 11 12 1 7 12 12 13 2 8 13 13 1 3 9 A. Zhang et al.

Journal of Hospitality and Tourism Management 57 (2023) 48–60 53 on the platform for a simple pretest, focusing on whether participants could effectively understand the scene and whether there were flaws in the logical sequence and meaning expression. We conducted formal data collection in April 2022, collecting 259 valid questionnaires. All participants were fully informed and voluntarily participated in this survey. To improve the quality of the online questionnaire, we set eligibility requirements for participants: the credit score on the platform must be higher than 90 points, and the historical acceptance rate must be above 90%. Of the 259 samples, 127 were randomly assigned to the “traveling with friends” scenario and 132 were “traveling alone”. In terms of promotion items, each contains approximately 18–21 samples, ensuring the adequacy of sampling in different scenarios. According to the results, the average score of evaluation on scenario authenticity is 5.6 points, indicating that the scenario setting of this study is relatively effective. Table 2 shows the respondent profile. As mentioned, we mainly used the R language package developed by White (2021) to calculate the overall best-worst score and perform preference ranking. In addition, we applied a Bayesian hierarchical algorithm to calculate individual scores. According to the specific scenario they were assigned, we screened out the corresponding preference score and used the score in subsequent structural equation modeling analyses. We used the partial least squares (PLS) approach (SmartPLS version 3.0) to analyze data. This method met our research requirements, mainly as follows: (1) PLS does not have strict requirements on data distribution and is suitable for exploratory research; (2) PLS can test complex models with moderating variables, but the requirements for sample size are not very high. 4. Results 4.1. Low-carbon tour promotion preference score In the BWS method, each respondent was required to select the best and worst option from a set of four items, and the process was repeated 13 times. Using R language tools, we counted how many times each item was selected as the best or the worst. If an item was selected as the best, it was counted as 1. If an item was selected as the worst, it was counted as − 1. Based on the difference in scores, we determined the preference ranking of 259 participants for 13 items (see Table 3). According to the results, the top five popular items are product innovation, low-carbon options, discount incentives, quality assurance, and promotional gifts in sequence. Some of them are related to the development and innovation of low-carbon products, whereas others highlight the immediate benefits distributed to consumers. The number of best and worst choices for carbon offsetting, personal certification, and channel promotion items is roughly equal, signaling that participants’ preferences for those items are comparatively different and thus do not exhibit a clear trend. The remaining items (e.g., sufficient information, social sharing, authoritative certification, convenience purchase, educational guidance) are chosen as the worst considerably more often than as the best, demonstrating that these items are not highly attractive to participants. This may be because conventional promotion methods have become basic hygiene factors in a low-carbon scenario and fail to arouse the resonance of consumers. An obvious limitation of a simple BWS score analysis is that averages may conceal potential differences among individuals. We adopted a Bayesian hierarchical algorithm to calculate individuals’ preference utility scores, which were used in subsequent structural equation model estimation. Compared with questionnaires, this method could effectively avoid possible social expectation bias and conduct accurate measurements of consumer preferences (Louviere et al., 2013). 4.2. Evaluation of the measurement model We first used Harman’s one-factor analysis to test for common method bias. All measures were simultaneously included in the principal component analysis. Without factor rotation, the extracted first principal component explained 44.63% of the total variance, less than the critical criterion of 50%. To further rule out possible biases, we added a theory-independent marker variable (i.e., a formative construct) to the model, following the practice of Ylitalo (2009). The conclusions of all hypotheses did not change after adding the marker variable, proving the robustness of the results. Therefore, we concluded that common method bias was not a problem. Subsequently, we tested convergent and discriminant validity. In Smartpls 3.0, relevant criteria included that the item loadings were greater than 0.6, average variance extracted was higher than 0.5, and composite reliability was above 0.7. As shown in Table 4, except for two hedonic measurement items that were removed for not meeting requirements, all other items were retained and showed good convergent validity. Discriminant validity requires that the square root of each construct’s average variance extracted value (i.e., the diagonal entries in each column) is greater than its correlation with other constructs (Chin, 1998). As shown in Table 5, all constructs exhibit good discriminant validity. We then checked for collinearity. If the variance inflation factor was less than 5, there was no severe multicollinearity. According to the analysis, the variance inflation factor values of all independent variables Table 2 Sample profile. Category Total number % Gender Male 119 45.9 Female 140 54.1 Age 18–26 112 43.2 27–35 122 47.1 36–44 16 6.2 45–53 5 1.9 ≥54 4 1.5 Education Junior high school or below 1 0.4 High school or technical secondary school 3 1.2 Bachelor’s or senior college 207 79.9 Postgraduate or above 48 18.5 Travel frequency Once a month 11 4.2 Once every three months 110 42.5 Once half a year 96 37.1 Once a year 33 12.7 Once every few years 9 3.5 Monthly discretionary income 500–1000 RMB 2 0.8 1001–2000 RMB 38 14.7 2001–3000 RMB 33 12.7 3001–4000 RMB 37 14.3 ≥4001 RMB 149 57.5 Table 3 Rank order of consumers’ promotion preferences. Low-carbon tour promotion items Total best Total worst B–W Rank Product innovation 560 105 455 1 Low-carbon options 420 62 358 2 Discount incentives 421 176 245 3 Quality assurance 324 148 176 4 Promotional gifts 341 210 131 5 Carbon offset 265 201 64 6 Personal certification 315 261 54 7 Channel promotion 196 248 − 52 8 Sufficient information 103 274 − 171 9 Social sharing 133 383 − 250 10 Authoritative certification 106 381 − 275 11 Convenience purchase 101 378 − 277 12 Educational guidance 82 540 − 458 13 A. Zhang et al.

Journal of Hospitality and Tourism Management 57 (2023) 48–60 54 ranged from 1 to 2.355, thus excluding the threat of multicollinearity. 4.3. Evaluation of the structural model Fig. 3 illustrates the path analysis results of the structural model. Different experience types directly and significantly affect perceived travel agency image and low-carbon tourism behavior intention, confirming the additive effect of the HSM. Specifically, novelty experience is positively correlated with perceived travel agency image (β = 0.303, p < .001) and low-carbon tourism behavior intention (β = 0.191, p < .05), supporting Hypotheses 1a and 1b. Hedonic experience demonstrates a significant impact on perceived travel agency image (β = 0.311, p < .01) and low-carbon tourism behavior intention (β = 0.313,p < .001), indicating that Hypotheses 2a and 2b are supported. Meaningful experience significantly influences perceived travel agency image (β = 0.179, p < .05) and low-carbon tourism behavior intention (β = 0.228, p < .01), validating Hypotheses 3a and 3b. Additionally, the results reveal that heuristic routes have a greater impact on the perceived travel agency image than systematic routes, supporting Hypothesis 4a. In terms of lowcarbon tourism behavior intention, hedonic experience has the greatest influence, followed by meaningful and novelty experiences, which partially supports Hypothesis 4b. Regarding the influence of consumers’ promotion preference on experience, preference is positively correlated with novelty (β = 0.257, p < .001) and hedonic experiences (β = 0.384, p < .001), respectively; thus, Hypotheses 5a and 5b are confirmed. However, the effect of preference on meaningful experience (β = 0.100, p > .10) is not significant; therefore, Hypothesis 5c is rejected. It is worth noting that although the linear relationship is not confirmed, the quadratic effect between preference and meaningful experience is significant (β = − 0.192, p < .01), implying an inverted U-shaped relationship between the two. Control variables (i.e., age, gender, education) have no significant impact on outcome variables. The R2 values indicate that the model explains sufficient variances in perceived travel agency image (54.8%) and low-carbon tourism behavior intention (45.4%), demonstrating good practical value. We examined the mediation path using the bootstrap method (Table 6). For heuristic routes, novelty mediates the relationship between preference and perceived image (β = 0.078, p < .01), whereas the mediation effect by novelty between preference and behavior intention (β = 0.049, p > .05) is not significant. Thus, Hypothesis 6a is supported, and Hypothesis 6b is rejected. Both mediation pathways, promotion preference → hedonic experience → perceived image (β = 0.119, p < .05) and promotion preference → hedonic experience → behavior intention (β = 0.120, p < .01), are confirmed, supporting Hypotheses 7a and 7b. For the systematic route represented by meaningful experiences, Hypotheses 8a and 8b are both rejected because no mediating effect was found. Nonetheless, the quadratic effect of preference would be transmitted through the mediation of meaningful experience, which significantly affects low-carbon tourism behavior intention (β = − 0.044, p < .05). This finding affirms that the mediating effect of the systematic route is also supported. Table 4 Reliability and convergent validity. Constructs and items Factor loading T-statistic CR AVE Cronbach’s alpha Novelty experience NE1 0.742 19.378*** 0.876 0.639 0.812 NE2 0.816 28.159*** NE3 0.811 33.642*** NE4 0.827 25.874*** Hedonic experience HE1 0.894 55.997*** 0.891 0.804 0.756 HE2 0.899 48.802*** Meaningful experience ME1 0.869 39.812*** 0.909 0.769 0.850 ME2 0.866 40.988*** ME3 0.896 50.666*** Perceived travel agency image PI1 0.714 17.231*** 0.855 0.596 0.773 PI2 0.760 19.855*** PI3 0.799 25.290*** PI4 0.812 28.099*** Low-carbon tourism behavior intention BI1 0.845 35.866*** 0.836 0.630 0.710 BI2 0.773 18.722*** BI3 0.761 14.705*** Marker variable MV1 0.782 5.138*** _ _ _ MV2 0.877 7.147*** Note: CR = composite reliability; AVE = average variance extracted. ***p < .001. Table 5 Correlations of latent variables. HE LTBI ME NE PTAI Hedonic experience (HE) 0.897 Low-carbon tourism behavior intention (LTBI) 0.600 0.794 Meaningful experience (ME) 0.594 0.557 0.877 Novelty experience (NE) 0.692 0.576 0.637 0.799 Perceived travel agency image (PTAI) 0.657 0.619 0.582 0.662 0.772 Note: Diagonal elements are the square root of the average variance extracted for each construct, and nondiagonal elements are correlations between constructs. Fig. 3. Results of structural equation modeling. Note: *p < .05, **p < .01, ***p < .001. A. Zhang et al.

Journal of Hospitality and Tourism Management 57 (2023) 48–60 55 5. Discussions In this study, we measured and ranked the preferences for different low-carbon tour promotion methods and deconstructed how such preferences affect subsequent outcomes. Regarding the utility of heuristic and systematic routes, novelty, hedonic, and meaningful experiences directly and notably affect the perceived image of travel agencies and low-carbon behavior intention; therefore, the additivity effect is verified. For the attenuation effect, when heuristic routes (i.e., hedonic experience, novelty experience) play a dominant role, the influence of the systematic route (i.e., meaningful experience) weakens. In contrast to our expectation, it is only partially confirmed that heuristic routes are weakened when systematic route dominates. Specifically, referring to the influence on behavioral intention, hedonic experience > meaningful experience > novelty experience may be due to the obvious hedonic characteristics of the tourism situation we studied. Previous research has also found that hedonic motives have a significantly higher impact than normative motives on tourists’ water-saving behaviors in hotels during vacations (Casado-Díaz et al., 2022). This shows that consumers’ decision-making is influenced not only by the value it brings but also by the context in which the decision is made (Steg et al., 2014). In a low-carbon tourism scenario, consumers are driven by social norms to protect the environment and expect a relaxing and hedonic experience. Pelletier et al. (1998) emphasize that when people derive happiness and satisfaction from eco-friendly behavior, they are more likely to engage in it. Therefore, it is not difficult to understand why hedonic experience has the most significant impact on low-carbon behavior intention (β = 0.313, p < .001), whereas meaningful experience (β = 0.228, p < .01) does not play a dominant role. We have confirmed the positive and significant effects of low-carbon tour promotion preference on novelty and hedonic experience. Because tourism services are intangible, it is difficult for consumers to accurately assess their quality when making decisions. The low-carbon tour promotion methods adopted by travel agencies as a significant external clue (Hsiao et al., 2021; Tsaur & Wang, 2009) have become an important factor in shaping subsequent experience expectations. Through analysis, we not only clarify what kind of promotion is attractive to tourists, but also deconstruct the way tourists interpret external cues, so as to clarify what tourists are looking for in sustainable tourism practices (Font et al., 2021; Hsiao et al., 2021). The linear relationship with meaningful experience is not supported. An interesting finding is that, contrary to our common belief that the pursuit of meaningful experience is more important in sustainable scenarios, preference and meaningful experience show an inverted U-shaped relationship. That is, the impact of preference on meaningful experience is more positive at low levels than at high levels. This illustrates that in the process of preference deconstruction, consumers’ sensory pursuit of hedonism and novelty is intertwined with their rational pursuit for meaningfulness (Malone et al., 2014), and at a higher level, there is a diminishing marginal utility between preferences and meaningfulness. The mediation effect is confirmed in both heuristic and systematic routes. According to our results, both paths with hedonic experience as a mediating variable are significantly supported, which echoes Malone et al.’s (2014) emphasis on hedonic value in the context of ethical tourism. For meaningfulness, because the linear relationship with preference is not significant, neither of the two mediating paths is established. However, the quadratic effect of preference would significantly affect low-carbon behavior intention through meaningfulness, indicating that meaningful experience could demonstrate a significant conduction effect in scenarios with high participation or long duration (Jose et al., 2022; Siu et al., 2013). Concerning novelty experience, the mediating path of preference → novelty → perceived image is established, whereas the mediating effect of preference → novelty → low-carbon behavior intention is not significant. The reason may be that the novelty experience itself has an obvious dual effect. On the one hand, it may “change from routine, thrill, boredom alleviation, and surprise” (Lee & Crompton, 1992, p. 739), stimulating tourists to travel (Caber & Albayrak, 2016; Petrick, 2002); on the other hand, it is naturally antithetical to familiarity, associated with higher risk, and would therefore have a diminishing effect on tourists’ intention (Zhang et al., 2020). For tourists who are keen on novelty experiences, “another” will always be the best choice. Their willingness to repeatedly participate in the same type of activity or revisit the same destination would be significantly affected (Assaker et al., 2011). 6. Conclusion Researchers have repeatedly mentioned the challenge of decarbonization that the tourism industry faces (Gossling ¨ & Higham, 2021; Scott & Gossling, ¨ 2022b). Most studies assigned the responsibility of mitigation and the pressure of emission reduction to government agencies (Becken et al., 2020; Gossling ¨ et al., 2023). At the micro level, as the actual executors, tourism enterprises and consumers are inseparable from carbon reduction efforts. How can all parties be motivated to form a sustainable cooperation framework? This study focused on the promotion stage of low-carbon tourism. We adopted the BWS method to measure consumers’ preferences and deconstructed how such preferences affect subsequent novelty, hedonic and meaningful experiences, leading to favorable individual and organizational outcomes. In terms of preference ranking, items related to product innovations or immediate benefits are more popular. Our research also confirmed that low-carbon tour promotion that aligns with consumer preferences not only helps promote the perceived travel agency image, but also contributes to sustainable consumer behavior. This shared value approach helps bring carbon reduction efforts into a positive feedback loop. Our findings provide several theoretical contributions and meaningful implications. Table 6 Mediating effect analysis. IV Mediator DV Estimate Standard deviation 95% CI Lower Upper Low-carbon tour promotion preference Novelty experience PTAI 0.078** 0.030 0.026 0.142 LTBI 0.049 0.032 0.001 0.122 Hedonic experience PTAI 0.119* 0.048 0.035 0.220 LTBI 0.120** 0.043 0.040 0.206 Meaningful experience PTAI 0.018 0.017 − 0.008 0.058 LTBI 0.023 0.019 − 0.009 0.066 Quadratic effects of preference PTAI − 0.034 0.020 − 0.083 − 0.003 LTBI − 0.044* 0.021 − 0.089 − 0.008 Note: IV = independent variable; DV = dependent variable; CI = confidence interval; PTAI = Perceived travel agency image; LTBI = Low-carbon tourism behavior intention. *p < .05, **p < .01. A. Zhang et al.

Journal of Hospitality and Tourism Management 57 (2023) 48–60 56 6.1. Theoretical implications First, based on the HSM, this study verified the mediating mechanism from promotion preference to image perception and behavioral intention, thus providing further empirical evidence for exploring sustainable practices’ promotion mode and service design (Font et al., 2021; Hsiao et al., 2021). Both the additivity and attenuation effects of the HSM were confirmed in a low-carbon tourism scenario. This echoes the research by Liu et al. (2022) that the variables of central and peripheral cues influence pro-environmental behavior. This confirms the applicability of the HSM in explaining low-carbon tourism issues and provides new analytical ideas for exploring how to motivate sustainable behavior changes among tourists (Budeanu, 2007). This study effectively combines the BWS method and structural equation modeling to systematically analyze customer preferences and their consequences, thereby enriching research findings in sustainable tourism marketing. Second, we did not simply explore differences in preferences based on factors such as gender, age, experience, and resource characteristics (Crouch et al., 2016; Tsai & Chen, 2019), instead using a bottom-up approach, taking preference measures as a starting point for analysis. This conforms to user-centered service design thinking (Baldassarre et al., 2017) and helps tourism enterprises optimize service supply from the source (Coghlan, 2015; Font et al., 2021). This would be conducive to breaking the marketing deadlock for low-carbon tourism (Font et al., 2017, 2021). This study also addresses how to design the best campaigns for low-carbon tourism at a practical level (Becken, 2017), thus providing an effective model for designing marketing and communication in sustainable tourism practices (Grimmer & Woolley, 2014). Third, this study introduced three constructs of novelty, hedonic, and meaningful experience to further deconstruct consumer promotion preferences and predict outcome variables. The value of the three experience types in explaining customer satisfaction, loyalty, and behavioral intentions has been confirmed in existing tourism literature (Blomstervik & Olsen, 2022; Jose et al., 2022; Strzelecka et al., 2018). In addition to validating these findings in new scenarios, our study further leads to some interesting conclusions: hedonic experience has the most significant value in the low-carbon tourism scenario, suggesting that consumers expect to do meaningful things but do not want to sacrifice the experience they deserve in typical hedonic consumption (Malone et al., 2014; Strzelecka et al., 2018). Moreover, the quadratic effect of preference and meaningfulness is significant, which indicates that it is not sufficient to focus only on the supply of meaningful experience. Consumers want their experiences to be novel and meaningful (Siu et al., 2013), doing meaningful things while having fun (Malone et al., 2014). These results further enrich the theoretical findings of tourism experience research in sustainable scenarios, turning the conflicting focus of whether to convey sustainable characteristics in marketing into the question of creating what kind of experience. 6.2. Managerial implications In this study, we demonstrated how governments and tourism enterprises can contribute to low-carbon tourism practices (Becken, 2017; Rastegar & Ruhanen, 2023; Scott & Gossling, ¨ 2022a). Our findings echo the view proposed by Gossling ¨ et al. (2023) that “governments can implement policies, but mitigation efforts will ultimately rest with producers or consumers” (p.8). Countries, destinations, and enterprises need to form a common action framework to achieve the goal of carbon emission reduction, but the established goal of decarbonization often runs counter to the enterprises’ pursuit for economic interests (Zhang & Zhang, 2018). Our research reveals a new direction for the government to complete the carbon reduction work: in addition to mandatory means such as taxation and task allocation, encouraging enterprises to innovate low-carbon promotion methods by setting rewards or establishing advanced models is also an effective way. Compared with the income loss of tourism enterprises caused by price regulation, the promotion based on consumer preferences incorporates tourists into the responsible subjects of carbon emission reduction and encourages them to practice low-carbon environmental protection behaviors voluntarily and consciously, which is conducive to the formation of a sustainable multi-party shared value model. To some extent, this helps mitigate potential risks in the transition to a net-zero economy (Scott & Gossling, ¨ 2022b). Tourism marketers should focus on the kind of promotion consumers prefer and the kind of experience they expect. Although consumers often show preferences for certain types of promotions, not all preferences translate into responsible behaviors such as purchasing responsible travel products, choosing eco-friendly transportation, or taking ecofriendly actions at a destination (Budeanu, 2007). The promotion of low-carbon tourism should enable tourists to update their intended travel experiences with effective clues, thus fully justifying their choice and participation. Tourism marketers should also regularly pay attention to the changing trend in promotion preferences and further amplify the positive effect of clues in combination with current events and popular trends. For example, when providing characteristic low-carbon options, we could enhance consumers’ expectations through blind box choices, stimulate their desire to explore new places and activities, and guide them to discover the fun of low-carbon tourism. Finally, service designers must pay attention to the specific mechanisms of novelty, hedonic, and meaningful experiences. When more time investment or engagement is involved, a systematic route represented by meaningfulness can be activated. Consumers are more focused on the meaning of activities, which helps generate a high level of loyalty and behavioral intention. In situations that do not require in-depth thinking and rely more on individual subjective feelings and emotions, positive attitudes and evaluations can be promoted by activating heuristic routes represented by novelty or hedonism (Blomstervik & Olsen, 2022; Coghlan, 2015). For example, when designing low-carbon cycling activities, displaying the novelty and fun of cycling equipment and highlighting the enjoyment of cycling scenery or the stimulation of activities will significantly contribute to the positive evaluation of the travel agency’s image. 6.3. Limitations and future research directions Although this study has drawn some useful conclusions, it has some limitations. First, we used samples from China as the survey subjects, which makes the conclusions not generalizable, and whether our findings are valid in other regions or cultural contexts needs to be examined further. Our sample group was dominated by young people aged 18 to 35, limiting the applicability of conclusions to middle-aged and older adults to a certain extent. Although we found that demographic factors such as age and education did not have a significant impact on outcome variables and the youth group is the main target group for emerging sustainable tourism practices, it is still important to be aware of a possible discrepancy between age groups. Our research questionnaire had many items and a high degree of difficulty. The respondents were relatively young and generally considered to have quick thinking and a better understanding of the questions, which significantly contributed to the survey’s overall quality. However, the lack of research on middleaged and older adults may affect the generalization of conclusions. In the future, researchers should issue questionnaires specifically to those groups to form a more comprehensive understanding. Second, concerning our research methods, we adopted a simulation scenario design, asking participants to choose from 13 promotion items. Although researchers have widely used this method to examine decision-making behaviors (Shi et al., 2021), the scenario setting may not fully reflect the actual situation. Therefore, it is necessary to further test whether our conclusions are valid in real consumption scenarios. Third, regarding research content, we only discussed the role of novelty, hedonic, and meaningful experiences. To obtain a systematic understanding, it is necessary to further examine the possible impact of other experiences A. Zhang et al.

Journal of Hospitality and Tourism Management 57 (2023) 48–60 57 under low-carbon tourism scenarios. Funding This research received financial support from the Ministry of Education of the People’s Republic of China Humanities and Social Sciences Youth Foundation [Grant number: 21YJC790155], National Social Science Fund of China [Grant number: 22AJY010], Shandong Social Science Foundation of China [Grant number: 22BGLJ03], Humanities and Sciences Project of Shandong University of China [Grant number: 22RWZX09], and Research Fund of the Institute of State Governance, Shandong University of China [Grant number: 23Z04]. Appendix A Contents of low-carbon tour promotion items. Items Content Item 1 Low-carbon options Offer low-carbon consumption options in tourism products (e.g., low-carbon transportation, eco-friendly/green restaurants) Item 2 Product innovation Launch specialized and attractive low-carbon tourism products (e.g., low-carbon cycling tours) Item 3 Quality assurance Guarantee the quality of low-carbon tourism products through standard formulation and other means, and clarify that it will not be at the expense of tourist experience Item 4 Authoritative certification Sell low-carbon tourism products with government and industry certification marks Item 5 Carbon offset Donate on behalf of tourists to promote environmental protection, or offset carbon emissions through activities such as planting trees Item 6 Personal certification Launch low-carbon tourism passports, and holders can enjoy preferential treatment Item 7 Discount incentives Offer cash discounts and coupons when buying low-carbon products Item 8 Educational guidance Promote low-carbon tourism knowledge through lectures or websites, highlighting the value and importance of low-carbon tourism Item 9 Promotional gifts In promotion activities, give away shopping bags, toothbrush sets and other eco-friendly gifts, and remind customers to carry them when traveling Item 10 Sufficient information Travel agencies clearly label low-carbon tourism products on their websites and truthfully inform relevant information Item 11 Convenience purchase Set up a specialized search column and provide customized services Item 12 Social sharing Publish low-carbon tourism-related topics on media platforms and provide channels for sharing and discussion Item 13 Channel promotion Implement a variety of online and offline promotion activities to fully expose tourists to low-carbon tourism Appendix B Constructs and measurement items. Constructs Measurement items Novelty experience This kind of promotion makes me feel I would (have) … NE1 Once-in-a-lifetime experience NE2 Unique experience NE3 Different from previous experiences NE4 Experience something new Hedonic experience This kind of promotion makes me feel I would (be/have) … HE1 Thrilled about having a new experience HE2 Exciting experience Meaningful experience This kind of promotion makes me feel I would … ME1 Do something meaningful ME2 Do something important ME3 Do something valuable If the travel agency adopts the promotion method in the above situation, please rate the following statements according to the degree of agreement. Perceived travel agency image I feel this travel agency … PI1 Provides good customer service PI2 Provides a reliable travel product PI3 Provides a good quality travel product PI4 Provides good value for money Low-carbon tourism behavior intention BI1 From now on, I am willing to plan in a way that aligns with low-carbon tourism during my next tour BI2 From now on, I am willing to tell my friends and family to engage in low-carbon tourism BI3 If conditions permit, the possibility for me to participate in low-carbon tourism in the near future would be (0%; 1–10%; 11–30%; 31–50%; 51–70%; 71–90%; Above 90%) Appendix C Descriptive statistics of the variables. A. Zhang et al.

Journal of Hospitality and Tourism Management 57 (2023) 48–60 58 Number of cases Mean Std. error mean Median Standard deviation Skewness Std. error skewness Kurtosis Std. error kurtosis Novelty experience NE1 259 5.16 0.076 5 1.218 − 0.670 0.151 0.299 0.302 NE2 259 5.41 0.071 5 1.149 − 0.841 0.151 1.106 0.302 NE3 259 5.43 0.075 6 1.210 − 0.867 0.151 0.901 0.302 NE4 259 5.86 0.063 6 1.008 − 1.281 0.151 2.986 0.302 Hedonic experience HE1 259 5.49 0.068 6 1.094 − 0.960 0.151 1.125 0.302 HE2 259 5.38 0.072 6 1.160 − 1.242 0.151 2.817 0.302 Meaningful experience ME1 259 5.91 0.068 6 1.087 − 1.227 0.151 1.784 0.302 ME2 259 5.35 0.070 5 1.129 − 1.009 0.151 2.210 0.302 ME3 259 5.85 0.063 6 1.021 − 1.278 0.151 2.493 0.302 Perceived travel agency image PI1 259 5.48 0.052 6 0.841 − 0.594 0.151 0.894 0.302 PI2 259 5.64 0.062 6 0.999 − 0.993 0.151 2.024 0.302 PI3 259 5.54 0.063 6 1.016 − 0.759 0.151 1.533 0.302 PI4 259 5.29 0.069 5 1.116 − 0.642 0.151 0.772 0.302 Low-carbon tourism behavior intention BI1 259 5.83 0.052 6 0.830 − 1.073 0.151 2.800 0.302 BI2 259 5.63 0.061 6 0.977 − 0.542 0.151 0.921 0.302 BI3 259 5.46 0.066 5 1.068 − 1.009 0.151 2.613 0.302 Low-carbon tour promotion preference PP1 259 0.18 0.044 0.170 0.710 − 0.234 0.151 − 0.716 0.302 Marker variable MV1 259 3.31 0.054 3 0.875 − 0.585 0.151 0.142 0.302 MV2 259 4.13 0.072 5 1.161 − 0.948 0.151 − 0.597 0.302 References Anauate, P. M., Isabella, G., & Ramos, C. (2020). Promotions in action: Classifying promotional activities under the perception of consumers. REMark, 19(3), 515–539. Assaker, G., Vinzi, V. E., & O’Connor, P. (2011). Examining the effect of novelty seeking, satisfaction, and destination image on tourists’ return pattern: A two factor, nonlinear latent growth model. Tourism Management, 32(4), 890–901. Auger, P., Devinney, T. M., Louviere, J. J., & Burke, P. F. (2010). The importance of social product attributes in consumer purchasing decisions: A multi-country comparative study. International Business Review, 19(2), 140–159. Baldassarre, B., Calabretta, G., Bocken, N., & Jaskiewicz, T. (2017). Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design. Journal of Cleaner Production, 147, 175–186. Becken, S. (2017). Evidence of a low-carbon tourism paradigm? Journal of Sustainable Tourism, 25(6), 832–850. Becken, S., Whittlesea, E., Loehr, J., & Scott, D. (2020). Tourism and climate change: Evaluating the extent of policy integration. Journal of Sustainable Tourism, 28(10), 1603–1624. Bender, A. C., Guerreiro, M., Sequeira, B. D., & Mendes, J. (2022). Hedonic experiences at heritage attractions: The visitor’s perspective. International Journal of Culture, Tourism and Hospitality Research, 16(1), 138–151. Blomstervik, I. H., & Olsen, S. O. (2022). Progress on novelty in tourism: An integration of personality, attitudinal and emotional theoretical foundations. Tourism Management, 93. Article 104574. Brislin, R. W. (1980). Translation and content analysis of oral and written material. In H. C. Triandis, & J. W. Berry (Eds.), Handbook of cross-cultural psychology: Methodology (pp. 389–444). Allyn & Bacon. Budeanu, A. (2007). Sustainable tourist behaviour—a discussion of opportunities for change. International Journal of Consumer Studies, 31(5), 499–508. Busser, J. A., & Shulga, L. V. (2018). Co-created value: Multidimensional scale and nomological network. Tourism Management, 65, 69–86. Caber, M., & Albayrak, T. (2016). Push or pull? Identifying rock climbing tourists’ motivations. Tourism Management, 55, 74–84. Casado-Díaz, A. B., Sancho-Esper, F., Rodriguez-Sanchez, C., & Sellers-Rubio, R. (2022). Tourists’ water conservation behavior in hotels: The role of gender. Journal of Sustainable Tourism, 30(7), 1518–1538. Chaiken, S. (1980). Heuristic versus systematic information processing and the use of source versus message cues in persuasion. Journal of Personality and Social Psychology, 39(5), 752–766. Chaiken, S., Liberman, A. M., & Eagly, A. H. (1989). Heuristic and systematic information processing within and beyond the persuasion context. In J. S. Uleman, & J. A. Bargh (Eds.), Unintended thought (pp. 212–252). The Guilford Press. Chang, K. C., Hsu, C. L., Hsu, Y. T., & Chen, M. C. (2019). How green marketing, perceived motives and incentives influence behavioral intentions. Journal of Retailing and Consumer Services, 49, 336–345. Chang, M. C., & Wu, C. C. (2015). The effect of message framing on pro-environmental behavior intentions: An information processing view. British Food Journal, 117(1), 339–357. Chatterjee, S., & Mandal, P. (2020). Traveler preferences from online reviews: Role of travel goals, class and culture. Tourism Management, 80. Article 104108. Chen, S., & Chaiken, S. (1999). The heuristic-systematic model in its broader context. In S. Chaiken, & Y. Trope (Eds.), Dual-process theories in social psychology (pp. 73–96). The Guilford Press. Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295–336. Climate Action Tracker. (2021). China. Retrieved from https://climateactiontracker. org/countries/china/. Coghlan, A. (2015). Tourism and health: Using positive psychology principles to maximise participants’ wellbeing outcomes—a design concept for charity challenge tourism. Journal of Sustainable Tourism, 23(3), 382–400. Crouch, G. I., Huybers, T., & Oppewal, H. (2016). Inferring future vacation experience preference from past vacation choice: A latent class analysis. Journal of Travel Research, 55(5), 574–587. Dedeoglu, B. B., Bilgihan, A., Ye, B. H., Buonincontri, P., & Okumus, F. (2018). The impact of servicescape on hedonic value and behavioral intentions: The importance of previous experience. International Journal of Hospitality Management, 72, 10–20. Dickinson, J. E., Lumsdon, L. M., & Robbins, D. (2011). Slow travel: Issues for tourism and climate change. Journal of Sustainable Tourism, 19(3), 281–300. Encinar, M. I., & Munoz, F. F. (2006). On novelty and economics: Schumpeter’s paradox. Journal of Evolutionary Economics, 16(3), 255–277. Fakfare, P., & Wattanacharoensil, W. (2022). Low-carbon tourism: Determining domestic tourist perception from Thailand: Tourism Agenda 2030. Tourism Review, 78(2), 496–516. Font, X., Elgammal, I., & Lamond, I. (2017). Greenhushing: The deliberate under communicating of sustainability practices by tourism businesses. Journal of Sustainable Tourism, 25(7), 1007–1023. Font, X., English, R., Gkritzali, A., & Tian, W. S. (2021). Value co-creation in sustainable tourism: A service-dominant logic approach. Tourism Management, 82. Article 104200. Font, X., & McCabe, S. (2017). Sustainability and marketing in tourism: Its contexts, paradoxes, approaches, challenges and potential. Journal of Sustainable Tourism, 25 (7), 869–883. Fu, J. R., Lu, I. W., Chen, J. H. F., & Farn, C. K. (2020). Investigating consumers’ online social shopping intention: An information processing perspective. International Journal of Information Management, 54. Article 102189. Gossling, ¨ S., Balas, M., Mayer, M., & Sun, Y. Y. (2023). A review of tourism and climate change mitigation: The scales, scopes, stakeholders and strategies of carbon management. Tourism Management, 95. Article 104681. Gossling, ¨ S., & Higham, J. (2021). The low-carbon imperative: Destination management under urgent climate change. Journal of Travel Research, 60(6), 1167–1179. Grimmer, M., & Woolley, M. (2014). Green marketing messages and consumers’ purchase intentions: Promoting personal versus environmental benefits. Journal of Marketing Communications, 20(4), 231–250. Ham, J., Lee, K., Kim, T., & Koo, C. (2019). Subjective perception patterns of online reviews: A comparison of utilitarian and hedonic values. Information Processing & Management, 56(4), 1439–1456. Hsiao, T. Y. (2016). Developing a dual-perspective low-carbon tourism evaluation index system for travel agencies. Journal of Sustainable Tourism, 24(12), 1604–1623. A. Zhang et al.

Journal of Hospitality and Tourism Management 57 (2023) 48–60 59 Hsiao, T. Y., Sung, P. L., Tsai, H. Y., Wang, T. S., & Liang, A. R. D. (2021). Establishing a model of low-carbon tour promotion for use by travel agencies from the perspective of shared value theory. Tourism Management Perspectives, 37. Article 100787. Hussein, A. S., Hapsari, R. D. V., & Yulianti, I. (2018). Experience quality and hotel boutique customer loyalty: Mediating role of hotel image and perceived value. Journal of Quality Assurance in Hospitality & Tourism, 19(4), 442–459. Jarvis, W., Ouschan, R., Burton, H. J., Soutar, G., & O’Brien, I. M. (2017). Customer engagement in CSR: A utility theory model with moderating variables. Journal of Service Theory and Practice, 27(4), 833–853. Jiang, Y., & Kim, Y. (2015). Developing multi-dimensional green value: Extending social exchange theory to explore customers’ purchase intention in green hotels–Evidence from Korea. International Journal of Contemporary Hospitality Management, 27(2), 308–334. Jose, A., Rejikumar, G., Asokan Ajitha, A., Mathew, S., & Chakraborty, U. (2022). Destination image and perceived meaningfulness for visitor loyalty: A strategic positioning of Indian destinations. Tourism Recreation Research, 1–20. https://doi. org/10.1080/02508281.2022.2040294 Jun, S. H., & Vogt, C. (2013). Travel information processing applying a dual-process model. Annals of Tourism Research, 40, 191–212. Juvan, E., & Dolnicar, S. (2014). Can tourists easily choose a low carbon footprint vacation? Journal of Sustainable Tourism, 22(2), 175–194. Kim, S. E., Lee, K. Y., Shin, S. I., & Yang, S. B. (2017). Effects of tourism information quality in social media on destination image formation: The case of Sina Weibo. Information & Management, 54(6), 687–702. Kim, J.-H., Ritchie, J. R. B., & McCormick, B. (2012). Development of a scale to measure memorable tourism experiences. Journal of Travel Research, 51(1), 12–25. Knobloch, U., Robertson, K., & Aitken, R. (2017). Experience, emotion, and eudaimonia: A consideration of tourist experiences and well-being. Journal of Travel Research, 56 (5), 651–662. Kuo, N. W., & Dai, Y. Y. (2012). Applying the theory of planned behavior to predict lowcarbon tourism behavior: A modified model from Taiwan. International Journal of Technology and Human Interaction, 8(4), 45–62. Ladhari, R. (2007). The movie experience: A revised approach to determinants of satisfaction. Journal of Business Research, 60(5), 454–462. Law, R., Leung, R., Lo, A., Leung, D., & Fong, L. H. N. (2015). Distribution channel in hospitality and tourism: Revisiting disintermediation from the perspectives of hotels and travel agencies. International Journal of Contemporary Hospitality Management, 27 (3), 431–452. Lee, S. A. (2018). M-servicescape: Effects of the hotel mobile app servicescape preferences on customer response. Journal of Hospitality and Tourism Technology, 9 (2), 172–187. Lee, T. H., & Crompton, J. (1992). Measuring novelty seeking in tourism. Annals of Tourism Research, 19(4), 732–751. Lee, T. H., & Jan, F. H. (2019). The low-carbon tourism experience: A multidimensional scale development. Journal of Hospitality & Tourism Research, 43(6), 890–918. Lee, J. A., Soutar, G., & Louviere, J. (2008). The best–worst scaling approach: An alternative to Schwartz’s values survey. Journal of Personality Assessment, 90(4), 335–347. Lenzen, M., Sun, Y. Y., Faturay, F., Ting, Y. P., Geschke, A., & Malik, A. (2018). The carbon footprint of global tourism. Nature Climate Change, 8(6), 522–528. Lepp, A., & Gibson, H. (2003). Tourist roles, perceived risk and international tourism. Annals of Tourism Research, 30(3), 606–624. Li, M., & Cai, L. A. (2012). The effects of personal values on travel motivation and behavioral intention. Journal of Travel Research, 51(4), 473–487. Liu, P., Segovia, M., Tse, E. C. Y., & Nayga, R. M. (2022). Become an environmentally responsible customer by choosing low-carbon footprint products at restaurants: Integrating the elaboration likelihood model (ELM) and the theory of planned behavior (TPB). Journal of Hospitality and Tourism Management, 52, 346–355. Louviere, J., Lings, I., Islam, T., Gudergan, S., & Flynn, T. (2013). An introduction to the application of (case 1) best–worst scaling in marketing research. International Journal of Research in Marketing, 30(3), 292–303. Lumsdon, L. M., & McGrath, P. (2011). Developing a conceptual framework for slow travel: A grounded theory approach. Journal of Sustainable Tourism, 19(3), 265–279. Luo, F., Becken, S., & Zhong, Y. (2018). Changing travel patterns in China and ‘carbon footprint’ implications for a domestic tourist destination. Tourism Management, 65, 1–13. Ma, S., He, Y., & Gu, R. (2021). Joint service, pricing and advertising strategies with tourists’ green tourism experience in a tourism supply chain. Journal of Retailing and Consumer Services, 61. Article 102563. Malone, S., McCabe, S., & Smith, A. P. (2014). The role of hedonism in ethical tourism. Annals of Tourism Research, 44, 241–254. Manthiou, A., Klaus, P., & Luong, V. H. (2022). Slow tourism: Conceptualization and interpretation – a travel vloggers’ perspective. Tourism Management, 93. Article 104570. Minton, E. A., Jeffrey Xie, H., Gurel-Atay, E., & Kahle, L. R. (2018). Greening up because of god: The relations among religion, sustainable consumption and subjective wellbeing. International Journal of Consumer Studies, 42(6), 655–663. Mitas, O., & Bastiaansen, M. (2018). Novelty: A mechanism of tourists’ enjoyment. Annals of Tourism Research, 72, 98–108. Mody, M., Day, J., Sydnor, S., Lehto, X., & Jaff´e, W. (2017). Integrating country and brand images: Using the product–country image framework to understand travelers’ loyalty towards responsible tourism operators. Tourism Management Perspectives, 24, 139–150. Moore, K. (2012). On the periphery of pleasure: Hedonics, eudaimonics, and slow travel. In S. Fullagar, K. Markwell, & E. Wilson (Eds.), Slow tourism: Experiences and mobilities (pp. 25–35). Channel View Publications. Nazir, O., Islam, J. U., & Rahman, Z. (2021). Effect of CSR participation on employee sense of purpose and experienced meaningfulness: A self-determination theory perspective. Journal of Hospitality and Tourism Management, 46, 123–133. O’Brien, I. M., Ouschan, R., Jarvis, W., & Soutar, G. N. (2020). Drivers and relationship benefits of customer willingness to engage in CSR initiatives. Journal of Service Theory and Practice, 30(1), 5–29. Oh, H., Assaf, A. G., & Baloglu, S. (2016). Motivations and goals of slow tourism. Journal of Travel Research, 55(2), 205–219. Oliver, R. L. (1993). Cognitive, affective, and attribute bases of the satisfaction response. Journal of Consumer Research, 20(3), 418–430. Pelletier, L. G., Tuson, K. M., Green-Demers, I., Noels, K., & Beaton, A. M. (1998). Why are you doing things for the environment? The motivation toward the environment scale (MTES). Journal of Applied Social Psychology, 28(5), 437–468. Petrick, J. F. (2002). An examination of golf vacationers’ novelty. Annals of Tourism Research, 29(2), 384–400. Prayag, G., Hosany, S., Muskat, B., & Del Chiappa, G. (2015). Understanding the relationships between tourists’ emotional experiences, perceived overall image, satisfaction, and intention to recommend. Journal of Travel Research, 56(1), 41–54. Qahri-Saremi, H., & Montazemi, A. R. (2019). Factors affecting the adoption of an electronic word of mouth message: A meta-analysis. Journal of Management Information Systems, 36(3), 969–1001. Qiu, H., Wang, X., Wu, M. Y., Wei, W., Morrison, A. M., & Kelly, C. (2022). The effect of destination source credibility on tourist environmentally responsible behavior: An application of stimulus-organism-response theory. Journal of Sustainable Tourism, 1–21. https://doi.org/10.1080/09669582.2022.2067167 Rastegar, R., & Ruhanen, L. (2023). Climate change and tourism transition: From cosmopolitan to local justice. Annals of Tourism Research, 100. Article 103565. Rejikumar, G., Ajitha, A. A., Jose, A., & Mathew, S. (2021). Strategic positioning of tourist destinations—analyzing the role of perceived meaningfulness. Journal of Hospitality and Tourism Management, 49, 140–151. Robinson, S. R., Irmak, C., & Jayachandran, S. (2012). Choice of cause in cause-related marketing. Journal of Marketing, 76(4), 126–139. Ruiz-Mafe, C., Chatzipanagiotou, K., & Curras-Perez, R. (2018). The role of emotions and conflicting online reviews on consumers’ purchase intentions. Journal of Business Research, 89, 336–344. Ryu, K., Han, H., & Jang, S. S. (2010). Relationships among hedonic and utilitarian values, satisfaction and behavioral intentions in the fast-casual restaurant industry. International Journal of Contemporary Hospitality Management, 22(3), 416–432. Scott, D., & Gossling, ¨ S. (2022a). A review of research into tourism and climate change — launching the annals of tourism research curated collection on tourism and climate change. Annals of Tourism Research, 95. Article 103409. Scott, D., & Gossling, ¨ S. (2022b). Destination net-zero: What does the international energy agency roadmap mean for tourism? Journal of Sustainable Tourism, 30(1), 14–31. Shen, A. Y. (2014). Recommendations as personalized marketing: Insights from customer experiences. Journal of Services Marketing, 28(5), 414–427. Shi, S., Gong, Y., & Gursoy, D. (2021). Antecedents of trust and adoption intention toward artificially intelligent recommendation systems in travel planning: A heuristic–systematic model. Journal of Travel Research, 60(8), 1714–1734. Siddiqi, U. I., Sun, J., & Akhtar, N. (2020). The role of conflicting online reviews in consumers’ attitude ambivalence. Service Industries Journal, 40(13–14), 1003–1030. Siddiqui, R. A., Monga, A., & Buechel, E. C. (2018). When intertemporal rewards are hedonic, larger units of wait time boost patience. Journal of Consumer Psychology, 28 (4), 612–628. Siu, N. Y. M., Zhang, T. J. F., Dong, P., & Kwan, H. Y. (2013). New service bonds and customer value in customer relationship management: The case of museum visitors. Tourism Management, 36, 293–303. Steg, L., Bolderdijk, J. W., Keizer, K., & Perlaviciute, G. (2014). An integrated framework for encouraging pro-environmental behaviour: The role of values, situational factors and goals. Journal of Environmental Psychology, 38, 104–115. Steiger, R., Scott, D., Abegg, B., Pons, M., & Aall, C. (2019). A critical review of climate change risk for ski tourism. Current Issues in Tourism, 22(11), 1343–1379. Sthapit, E., Bjork, ¨ P., & Coudounaris, D. N. (2022). Memorable nature-based tourism experience, place attachment and tourists’ environmentally responsible behaviour. Journal of Ecotourism, 1–24. https://doi.org/10.1080/14724049.2022.2091581 Strzelecka, M., Woosnam, K. M., & Nisbett, G. S. (2018). Self-efficacy mechanism at work: The context of environmental volunteer travel. Journal of Sustainable Tourism, 26(11), 2002–2020. Su, L., Tang, B., & Nawijn, J. (2021). How tourism activity shapes travel experience sharing: Tourist well-being and social context. Annals of Tourism Research, 91. Article 103316. Tao, R., Wu, J., & Zhao, H. (2022). Do corporate customers prefer socially responsible suppliers? An instrumental stakeholder theory perspective. Journal of Business Ethics, 1–24. https://doi.org/10.1007/s10551-022-05171-5 Todorov, A., Chaiken, S., & Henderson, M. D. (2002). The heuristic-systematic model of social information processing. In J. P. Dillard, & M. Pfau (Eds.), The persuasion handbook: Developments in theory and practice (pp. 195–211). SAGE Publications. Truong, N. T., Dang-Pham, D., McClelland, R. J., & Nkhoma, M. (2020). Service innovation, customer satisfaction and behavioural intentions: A conceptual framework. Journal of Hospitality and Tourism Technology, 11(3), 529–542. Tsai, T. H., & Chen, C. M. (2019). Evaluating tourists’ preferences for attributes of thematic itineraries: Holy folklore statue in Kinmen. Tourism Management Perspectives, 30, 208–219. Tsaur, S. H., & Wang, C. H. (2009). Tip-collection strategies, service guarantees, and consumer evaluations of group package tours. Journal of Travel Research, 47(4), 523–534. A. Zhang et al.

Journal of Hospitality and Tourism Management 57 (2023) 48–60 60 Watts, S. A., & Zhang, W. (2008). Capitalizing on content: Information adoption in two online communities. Journal of the Association for Information Systems, 9(2), 73–94. Wehrli, R., Priskin, J., Demarmels, S., Schaffner, D., Schwarz, J., Truniger, F., & Stettler, J. (2017). How to communicate sustainable tourism products to customers: Results from a choice experiment. Current Issues in Tourism, 20(13), 1375–1394. White, M. H. (2021). BwsTools: An R package for case 1 best-worst scaling. Journal of Choice Modelling, 39. https://doi.org/10.1016/j.jocm.2021.100289 Wu, M. Y., Wu, X., Li, Q. C., Wang, J., & Wang, Y. (2022). Justice and community citizenship behavior for the environment: Small tourism business entrepreneurs’ perspectives. Journal of Sustainable Tourism, 1–18. https://doi.org/10.1080/ 09669582.2022.2122061 Yang, W., & Mattila, A. S. (2016). Why do we buy luxury experiences? Measuring value perceptions of luxury hospitality services. International Journal of Contemporary Hospitality Management, 28(9), 1848–1867. Ylitalo, J. (2009). Controlling for common method variance with partial least squares path modeling: A Monte Carlo study. Research project. Helsinki University of Technology. Zhang, Y., Li, J., Liu, C. H., Shen, Y., & Li, G. (2020). The effect of novelty on travel intention: The mediating effect of brand equity and travel motivation. Management Decision, 59(6), 1271–1290. Zhang, J., & Zhang, Y. (2018). Carbon tax, tourism CO2 emissions and economic welfare. Annals of Tourism Research, 69, 18–30. Zhang, J., & Zhang, Y. (2020a). Assessing the low-carbon tourism in the tourism-based urban destinations. Journal of Cleaner Production, 276. Article 124303. Zhang, J., & Zhang, Y. (2020b). Low-carbon tourism system in an urban destination. Current Issues in Tourism, 23(13), 1688–1704. Zhang, J., & Zhang, Y. (2021). Tourism and low-carbon performance: An fsQCA approach. Asia Pacific Journal of Tourism Research, 26(6), 626–639. Zhang, K. Z. K., Zhao, S. J., Cheung, C. M. K., & Lee, M. K. O. (2014). Examining the influence of online reviews on consumers’ decision-making: A heuristic–systematic model. Decision Support Systems, 67, 78–89. A. Zhang et al.

Journal of Hospitality and Tourism Management 57 (2023) 29–39 Available online 8 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. Does temporary performance matter for word of mouth in museums? Jie Yin a , Huantao Chen b , Yensen Ni c,* a Department of Exhibition Economy and Management, College of Tourism, Huaqiao University, Quanzhou, China b College of Tourism, Huaqiao University, Quanzhou, China c Department of Management Sciences, Tamkang University, New Taipei, Taiwan ARTICLE INFO Keywords: Experience at museums (EAM) Brand image (BI) Attractiveness of museums (AOM) Word of mouth (WOM) Temporary performance (TP) Howard-sheth model ABSTRACT Given the significance of word of mouth (WOM) in influencing other people’s decisions to visit, it is critical to investigate the mechanism and condition configuration of WOM in museums. Using SEM technology and fuzzyset qualitative comparative analysis (fsQCA), this study discovered that experience at museums influences WOM via either brand image or attractiveness of museums, and that temporary experience positively moderates the effect of experience at museums on attractiveness of museums, indicating that visitors with temporary experience may perceive attractiveness of museums to be stronger, which is rarely disclosed in the existing literature. Furthermore, this study revealed that the formation of WOM occurs as a result of a multi-condition configuration, such as the combination of entertainment and aesthetic experiences at museums, which results in WOM. The mechanism and configuration of WOM in museums, as well as the moderating effect of temporary experience as an external factor in the Howard-Sheth model, were discovered in this study, providing a new understanding of this model. 1. Introduction Museums have recently been widely recognized as major tourist attractions in many destinations (He et al., 2018; Jin et al., 2020), playing an important role in the cultural and economic development of cities (Mavragani, 2015). Given the importance of museums and the serious consequences of COVID-19, a significantly profound understanding of visitors has received considerable concern (Luo & Ye, 2020). Museums, in particular, place a high value on customer experience in response to intense competition (Kang et al., 2017), because the museum experience can influence visitors’ behavior, emotion, and psychological state (Fan & Luo, 2022). Visiting museums is one of the most popular activities that tourists do while visiting cities. A growing body of literature has focused on the crucial issue of museum experience (defined as an amalgam of tangible and intangible experience encounters derived from both service providers and museum visitors (Komarac & Ozreti´c Doˇsen, 2021)). Consequently, previous research has not only investigated the antecedents (e. g., services capes including (Bitner, 1992; Conti et al., 2020)) of museum experience (Guo et al., 2021), but also the effects of museum experience (Trunfio et al., 2022; Vesci et al., 2021). Nowacki and Kruczek (2020) revealed that museum experiences can influence visitors’ satisfaction and behavioral intentions, which is consistent with the findings of Forgas-Coll et al. (2017). Previous research has also shown that different types of museum experiences provide different benefits (Komarac & Ozreti´c Doˇsen, 2021). For example, the museum technology experience including interactive technologies (Ponsignon & Derbaix, 2020), 3D virtual simulation technology (Hu et al., 2020), and virtual reality technology (Zou & Arif, 2022) improves satisfaction (Trunfio et al., 2021), revisit intention (Kang et al., 2017), and behavior intention (Yang & Zhang, 2022); a leisure experience at a museum is a benefit for loyalty (Wu, 2017). However, with the increase in the number of museums and the serious consequences of COVID-19, competition for visitors among museums is becoming fiercer, as increasing the number of visitors is an important task for museum operators (Han et al., 2018). As a result, increasing the number of visitors is a pressing concern for museum operators. It should be noted that word of mouth (WOM) is a significant influencer of consumer purchasing decisions and has a significant impact on purchasing decisions (Manna & Palumbo, 2018). Furthermore, it may be the most efficient way of boosting the number of visitors by enhancing the attractiveness of museums. Despite the importance of museum experience, few studies have revealed the process of employing experience at museums to improve the * Corresponding author. Department of Management Sciences, Tamkang University, No.151, Yingzhuan Rd., Tamsui Dist., New Taipei City, 25137, Taiwan. E-mail addresses: [email protected], [email protected] (Y. Ni). 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.2023.08.024 Received 27 February 2023; Received in revised form 16 July 2023; Accepted 30 August 2023

Journal of Hospitality and Tourism Management 57 (2023) 29–39 30 attractiveness and WOM of museums. Moreover, it appears that only a few studies have focused on investigating the effects of different experience configurations, particularly on the critical issue of WOM for museums. This study then focuses on identifying two major concerns according to the research gap recognized by presenting the aforementioned previous research. To better understand how the experience at museums (EAM) affects WOM, we employ a mediation and moderation model in the context of the museum field. Based on individuals’ observation and evaluation of the entire attractiveness (Hu & Ritchie, 2016; Kim & Thapa, 2018; Yin, Ji, & Ni, 2023a, 2023b) and WOM of a museum, this study investigates whether EAM has a direct effect on the brand image (referring to people’s emotions, ideas, and attitudes toward the service or place they experience (Erkmen & Hancer, 2019), attractiveness (referring to people’s perceptions of the place’s worth revisiting (Hu & Ritchie, 2016; Ozdemir et al., 2012), and WOM. Furthermore, this research investigated the mediating effects of brand image (BI) and attractiveness of museums (AOM), as both may not only result from visitors’ experience (Huang & Liu, 2018; Manhas & Tukamushaba, 2015; Mohseni et al., 2016) but also influence consumption decision (Lin et al., 2017; Lohneiss & Hill, 2013) and WOM (Schlesinger et al., 2023; Wirtz et al., 2018). Moreover, taking into account the edutainment aspects of museum experience (Gieling & Ong, 2016; Shaby & Vedder-Weiss, 2021), this study examined whether temporary performance (TP), which refers to a type of short, non-routine performance, would moderate the effect of museum experience on brand image or attractiveness according to the Howard-Sheth theory of buyer behavior (Juan et al., 2017). Museums are concerned with presenting a variety of temporary performances (Anton ´ et al., 2017) to enhance visitors’ experiences by providing a wide range of recreational, educational, and entertaining activities (Cox, 2016; Niblett & Allison, 2016; Yu et al., 2009). This study concludes that visitors may enrich their museum experience after experiencing a temporary performance provided by the museum, which may intensify the effect of the experience on the museum’s brand image and attractiveness. This research thus examines the moderation effect of temporary performance. This study not only focuses on revealing the process by which museum experience influences visitors’ word of mouth via the mediating effect of museum brand image and attractiveness of museums, but it also investigates whether temporary performance moderates the effect of EAM on BI or AOM. Therefore, since the purpose of this study was to uncover the interaction configuration of museum WOM antecedents for the process of how EAM affects WOM, this study sought to ascertain how various antecedents combine and interact to form museum WOM. We then conduct two studies to investigate two critical issues: the mechanism by which EAM influences WOM formation and the condition configuration of WOM formation. This study could add to the existing body of knowledge. First, this study not only disclosed that EAM could directly influence WOM and indirectly influence WOM via the mediating effects of BI and AOM, which is useful for understanding the mechanism of how EAM affects WOM and improving WOM in museums, but it also revealed the condition configuration of antecedents to form WOM. Second, TP positively moderated the effect of EAM on the AOM of visitors, which indicated that temporary performance, the short and non-routine performance in a museum, really works in improving the attractiveness of a museum (AOM). Third, unlike previous studies, this study may broaden the Howard-Sheth model by revealing the moderating role of an external variable (i.e., temporary performance) rather than its direct impacts, as has been explored in previous studies. According to the Howard-Sheth model, an individual’s internal factors (i.e. perception or image) are influenced by either stimuli factors (e.g., service, experience, and price (Juan et al., 2017)) or external variables (e.g., culture and activities). As a result, this study investigated and validated the moderating effect of external factors (TP; activities) on the relationship between stimuli factors (EAM; experience) and internal factors (BI; image), which may shed new light on the traditional Howard-Sheth model. Study 1: The mechanism and process of experience at museums (EAM) affect word of mouth (WOM). 2. Literature review and hypotheses 2.1. Howard-Sheth model There are numerous theoretical frameworks available for analyzing consumers’ purchasing behaviors. Among them, the Howard-Sheth model was the most commonly used (Juan et al., 2017). In 1969, Howard and Sheth proposed the model, which included four major facets, to clarify the process of forming consumer behavior. These facets include stimulating (input) factors such as service, experience, and price, external factors such as culture and personality, internal factors that primarily explain how stimulating and external factors influence psychological perception and thus influence consumer decisions, and reflect (output) factors such as cognitive, emotional, and behavioral response. They also claimed that stimuli and external factors can influence consumer behavior (Sheth & Parvatiyar, 1995). According to the Howard-Sheth model (Fig. 1), consumers may develop a series of internal influences and psychological perceptions in response to stimulus variables. Based on the Howard-Sheth model, this study asserted that experience at museums, as a result of the services and products provided and regulated by the museum, may serve as stimuli. Brand image (denoting the ideas, emotions, or attitudes that customers interact with the place or service they experience (Erkmen & Hancer, 2019)) and attractiveness (denoting that individuals believe that the place is worth visiting again (Hu & Ritchie, 2016; Ozdemir et al., 2012) may act as internal factors in the Howard-Sheth model. Furthermore, word of mouth, which is often recognized as a behavior response (Kumar et al., 2021; Vazquez et al., 2017), may function as a consumer behavior response. Moreover, external factors are advantageous in generating the internal component in the standard Howard-Sheth model. However, in earlier investigations, external factors frequently served as an intervention component (Wong, 2014; Khan & Fatma, 2021; Yin & Ni, 2021; Yin et al., 2023a, 2023b). Thus, unlike the traditional Howard-Sheth model, this research attempted to examine the moderating effect of temporary performance (as an external component). Thus, the research conceptual framework was developed, and several hypotheses were proposed (Fig. 1). 2.2. Experience at museums and word of mouth Concerning the significance of experience and WOM in the service field, the effect of experience on WOM has received considerable attention. According to Lopez ´ and Sicilia (2014), there is a quadratic association between consumer Internet experience and e-WOM. Yadav et al. (2021) contended that national brand experience, comprising sensory, affective, behavioral, and cognitive aspects, influences WOM. The favorable influence of brand experience on WOM has been validated in the field of restaurant studies (Zhang et al., 2021). Consequently, this study hypothesizes that the museum experience can inspire visitors’ WOM. Because stimuli, according to the Howard-Sheth model, elicit consumer behavioral responses, we argued that the museum experience, acting as a stimuli factor, may promote visitors’ behavioral reactions, namely WOM. This study then proposed H1. H1. Experience at museums positively affects WOM. 2.3. Mediation of brand image In prior studies, the experience was often used as a stimulating factor (Jiang, 2020; Kim et al., 2018; Lu et al., 2021). Thus, we treated the J. Yin et al.

Journal of Hospitality and Tourism Management 57 (2023) 29–39 31 museum experience as the stimulating factor in the Howard-Sheth model. Furthermore, brand image, recognized as the organism factor (Mkedder et al., 2021), is treated as the internal factor in the Howard-Sheth model. As such, according to the Howard-Sheth model, the stimulating factor (i.e., experience at museums) may affect the internal factor (i.e. brand image). Moreover, previous studies have confirmed the effects of experience on brand image in various situations. Manhas and Tukamushaba (2015) discovered that in the hospitality industry, the service experience is related to brand image. Huang and Liu (2018) proposed that creative experience has a beneficial effect on brand image among tourists. Following the aforementioned investigation, we offered H2a. H2a. Experience at museums (EAM) positively influences brand image (BI). The positive impacts of brand image on behavior reactions such as revisit intention (Gomez-Rico ´ et al., 2023; Liang & Lai, 2022) and booking intention (Casado-Díaz et al., 2016) have been intensively investigated in the tourism and hospitality field. Nyadzayo et al. (2020) showed that brand image is a crucial antecedent of favorable WOM; a favorable brand image is advantageous for encouraging positive WOM (Schlesinger et al., 2023; Yadav et al., 2021). We then conclude that brand image may be associated with WOM in museums. Furthermore, based on prior research that has frequently treated WOM as a response factor (Kumar et al., 2021; Roy et al., 2019; Vazquez et al., 2017), we argue that, according to the Howard-Sheth model, brand image (i.e., the internal factor) may influence WOM (i.e., the response factor) by providing H2b. H2b. Brand image (BI) positively influences word of mouth (WOM). We conclude from the preceding analysis that EAM may initiate BI. Meanwhile, we suspect that BI will affect WOM. We infer that EAM may result in WOM as a result of the BI effect. According to the Howard-Sheth model, the internal factor acts as a link and mediator between the stimulating factor and the response factor. Based on this, we propose that brand image (i.e., the internal factor) may mediate the influence of museum experience (i.e., the stimulating factor) on WOM (i.e., the response factor). Furthermore, recent research has demonstrated the mediation of brand image (Chen et al., 2018; Lee & Lee, 2018; Ramesh et al., 2019), indicating that it could support the mediator role. We hypothesized that by proposing H2c, BI could serve as a mediator between EAM and WOM. H2c. Brand image (BI) mediates the relationship between EAM and WOM. 2.4. Mediation of attractiveness of museums Previous research has shown that restaurant experience can increase the attractiveness of a tourist destination (Chen et al., 2019); work experience affects the attractiveness of employers (Bellou et al., 2018); experience factors had substantial effects on the perception of attractiveness (Ji & Yang, 2022). We conclude that museum experience may have a significant effect on a museum’s appeal. Since the attractiveness of museums (AOM), viewed as the perception of visitors, has frequently been used as the organism factor in prior research (Briand Decr´e & Cloonan, 2019), we can include that AOM, treated as an internal factor in the Howard-Sheth model, may increase the perception of the museum’s attractiveness by proposing H3a. H3a. Experience at museums positively influences the attractiveness of museums. Recent studies have shown that an individual’s behavior may be influenced by his or her perception of attractiveness (Jeon et al., 2022; Kim & Jung, 2022). Mohammad Shafiee et al. (2021) stated that attractiveness influences word of mouth. The attractiveness of Facebook pages, in particular, has a positive effect on word-of-mouth intention (Wirtz et al., 2018). From the foregoing analysis, we conclude that attractiveness influences word of mouth. According to the Howard-Sheth model, the attractiveness of the museum (i.e., the Fig. 1. Research model. J. Yin et al.

Journal of Hospitality and Tourism Management 57 (2023) 29–39 32 internal factor) may generate a WOM (i.e. the response factor). Therefore, we hypothesize that museum visitors who perceive the attraction of the museum will engage in word-of-mouth marketing. Then, we developed H3b. H3b. Attractiveness of museums (AOM) positively influences the word of mouth (WOM) of museums. Based on the preceding analysis, we not only hypothesize that EAM may generate AOM, but we also investigate the effect of AOM on WOM in museums. According to the Howard-Sheth model, the individual’s response may be triggered by the internal factor resulting from the stimulating factor. Concerning the attributes of EAM (the stimulating factor), AOM (the internal factor), and WOM (the response factor), we infer that AOM acts as a mediator between EAT and WOM, as the mediation effect of AOM has been demonstrated in several disciplines (Dijkstra et al., 2008; Joglekar & Tan, 2022; Sharma et al., 2018; Wang et al., 2019). Thus, we postulated H3c based on the aforementioned role of AOM as a mediator. H3c. Attractiveness of museums (AOM) mediates the relationship between EAM and WOM. 2.5. Serially mediation of brand image and attractiveness of museums Image is the essential precursor of attractiveness (Younis & Hammad, 2020). Specifically, Chapman et al. (2005) stressed that the image of employers positively influences the organization’s attractiveness. In addition, Bankins and Waterhouse (2018) determined that organizational image influences organizational reputation and employer attractiveness. Although the effect of brand image on attraction has not been thoroughly investigated, we can conclude that brand image may influence the attractiveness of museums based on the verified effect of image on attractiveness. Consequently, we offer H4a. H4a. Brand image (BI) positively influences the attractiveness of museums (AOM). Due to the significance of experience, the effect of experience on WOM has been extensively studied. According to previous research, brand image and attractiveness may serve as mediators between experience and WOM. However, Carpentier et al. (2017) discovered that exposing nurses to the hospital’s Facebook page may improve their understanding of the hospital’s brand image and thus increase their job attractiveness. According to Kucherov and Zhiltsova (2020), the corporate brand image resulting from the information available on corporate social media has a positive effect on the corporation’s attractiveness. Both of the aforementioned indicated that Experience at museums may affect AOM via brand image. As such, we further argue that the influence of EAM on WOM may be mediated serially by brand image and attractiveness. Thus, we presented H4b. H4b. The positive impact of experience at museums on word of mouth (WOM) is serially mediated by brand image and attractiveness of museums. 2.6. Moderation of temporary performance The most visible aspect of the museum visit is its educational value. Museums organize a variety of recreational, educational, and entertaining activities (Anton ´ et al., 2017) for visitors by offering a variety of temporary performances to enrich their experience (Cox, 2016; Niblett & Allison, 2016; Yin et al., 2024; Yu et al., 2009). Consequently, temporary performance (TP), a type of brief and non-routine performance, may be one of the most prevalent methods for museums to interact with visitors. According to the Howard-Sheth paradigm, external factors assist develop internal factors in persons. In the context of a museum, temporary performance, as a type of external factor, may enhance the experience of visitors, thereby enhancing the impact of the experience on the brand image and attractiveness of museums. Thus, we hypothesized that stimulating factors (i.e., experience at museums) can activate internal factors (brand image and attractiveness of museums) more smoothly with the assistance of external factors (i.e., temporary performance). As a result, we put forth the following hypotheses: H5a and H5b. H5a. Temporary performance (TP) moderates the effect of experience at museums (EAM) on the brand image (BI). H5b. Temporary performance (TP) moderates the effect of experience at museums (EAM) on the attractiveness of museums (AOM). 3. Materials and method 3.1. Measurement The current validated and reliable multi-item measures were employed to measure the essential terms EAM, BI, AOM, TP, and WOM that were used in this study in Fig. 1. All metrics are taken using anchors from a seven-point Likert scale. This study assessed EAM using sixteen modified items created by Manthiou et al. (2014), which comprised education, entertainment, escapism, and esthetics experience, BI with four items that were modified by Liu et al. (2015), AOM with five items that were referred to organizational attractiveness designed by Highhouse et al. (2003), and WOM with three items that were established by Vesci et al. (2021). Also, TP is with one question (i.e., did you experience the temporary performance in museums?). 3.2. Data collecting and samples This study chose the Xiamen Science & Technology Museum in Fujian province, China, which has five theme pavilions and three special effects cinemas, as the study site because it provides a variety of interactions experiences such as science popularization, education, tourism, and leisure, all of which emphasize the edutainment features of museums. From May 1 to May 3, 2022, a field survey was used to collect data using a convenience sampling method. A well-trained research team distributed questionnaires to visitors who had completed their museum experience at the sites. After providing a brief explanation of the study’s purpose, the field research team distributed the questionnaire to museum visitors who agreed to participate in this survey. Concerning the minimum sample size of 150 samples (Yin et al., 2020), we distributed 400 questionnaires and obtained 312 valid questionnaires after excluding incomplete questionnaires and those with flatline answers (See Table 1)Se. The majority of respondents (65.71%) were males, aged 19–40 years (77.56%), had a college graduate degree (46.47%), and earned $2500–7500 per month (66.99%). Adopting the two stages suggested by Anderson and Gerbing (1988), the SEM method was used to evaluate the succession of dependent relationships and verify cause-and-effect relationships between multiple independent and dependent constructs. We utilized Amos 23 and SPSS 24 to analyze the data. In the initial phase of the research, confirmatory factor analysis (CFA) was used to validate constructs. In the second stage, SPSS Process 3.4 was used to evaluate the structural model, elucidate the relationships between the constructs, and investigate the moderation effect (Hayes, 2013; Yin et al., 2022). In addition, Huertas-Valdivia et al. (2018) asserted that the PROCESS mediation could address some of the Sobel test’s shortcomings by testing the indirect effect in this study. Furthermore, we employed the fsQCA method, the widely used method (Manosuthi et al., 2022; Rasoolimanesh et al., 2021), to verify the conditional combination and configuration of the antecedences of WOM based on verifying the relationship between multiple independent (i.e. EAM, BI, AOM, and TP) and dependent constructs (i.e. WOM). J. Yin et al.

Journal of Hospitality and Tourism Management 57 (2023) 29–39 33 4. Results and analysis 4.1. Common method bias analysis Common method bias is a type of variation influenced by the similarity of data collection methods (Hsiao et al., 2020). The common technique bias was evaluated using the single-factor test proposed by Harman (1976), and the initial factor structure was established using a series of exploratory factor analyses with maximum likelihood estimation. Unrotated factor analysis of all questionnaire items showed the first factor accounted for 49.65% of the variance, which was lower than the 50% standard (Podsakoff et al., 2003), denoting that bias in common methods was not the main issue. 4.2. Measurement model validation We used SPSS 24.0 and Amos 24.0 to analyze descriptive statistical data as well as the scale’s reliability and validity (See Table 2). We started by removing the AOM 2 item because the factor loading is less than 0.5. The construct reliability was confirmed using composite reliability (CR) and Cronbach’s alpha, which revealed that CR far exceeded 0.7 for all factors and Cronbach’s values were all greater than 0.7. Following that, we ran CFA on this study’s constructs. We then displayed the Average variance extracted (AVE) for the constructs employed in this study, which is over 0.5 (i.e., 0.509 to 0.575) (Hayes, 2013), as well as the square root of the AVE values, which is also higher than construct correlations. These results showed high discriminant validity, convergent validity, and internal consistency reliability. In addition, we used confirmatory factor analysis to compare the fitting degree of various nested models after investigating the discriminative validity of the four latent variables. Table 3 showed that the fourfactor model (EAM; BI; AOM; WOM) met satisfactory criteria (Baumgartner & Homburg, 1996; Hu & Bentler, 1999) and represented a good model fit because the results of these statistics (i.e., χ2 = 473.966, df = 281.000, χ2 /df = 1.687, GFI = 0.902, NFI = 0.923, IFI = 0.967, TLI = 0.958, CFI = 0.967, RMSEA = 0.047, SRMR = 0.031) displayed a satisfactory overall fit of the proposed model to the data. Furthermore, Table 4 revealed that there was a significant positive correlation between EAM and BI (α = 0.653, P < 0.05), AOM (α = 0.670, P < 0.05), and WOM (α = 0.632, P < 0.05); BI positively affected AOM (α = 0.631, P < 0.05) and WOM (α = 0.628, P < 0.05); and AOM positively affects WOM (α = 0.651, P < 0.05). These results may offer initial evidence for our proposed hypotheses. 4.3. The direct effects The Process macro in SPSS 24.0 was then used to bootstrap 5000 samples while using bias-corrected confidence intervals. Table 5 revealed that EAM significantly positively affected WOM (Model III: β = 0.196, P < 0.01), supporting H1; EAM significantly positively affected both BI (Model I: β = 0.916, P < 0.01) and AOM (Model II: β = 0.499, P < 0.01), supporting H2a and H3a; and both BI (Model III: β = 0.321, P < 0.01) and AOM (Model III: β = 0.413, P < 0.01) significantly positively affected WOM, supporting H2b and H3b. Additionally, with supporting H4a, BI significantly affected AOM (Model II: β = 0.324, P < 0.01). 4.4. The mediating effects To investigate potential BI and AOM mediations, we used the method of bootstrapping (Zhao et al., 2010) in PROCESS. Based on a 95% confidence level (CI) calculated with 5000 bootstrap samples and the method for measuring the indirect effect (Montoya & Hayes, 2017), we found that EAM had a significantly positive impact on WOM via either BI with a 95% CI of [0.121, 0.433] or AOM with a 95% CI of [0.129, 0.372]. Furthermore, because the 95% CI of [0.020, 0.225] did not include 0, EAM may influence WOM via the serial mediating effect of BI and AOM. According to the results of the above analysis, BI and AOM not only act as mediators but also as serial mediators between EAM and WOM, supporting H2c, H3c, and H4b. 4.5. The moderating effect Furthermore, we used the Process macro to investigate the moderating effect of TP (Hayes, 2013). Table 5 showed that the interaction item, EAM by TP, significantly affected AOM (Model 1: β = 0.125, P < 0.1), but not BI (β = − 0.057, P > 0.5), supporting H5b but not H5a. To gain a better understanding of the moderating effect of TP, we conducted simple slope tests with either experienced temporary performance (ETP) or no experience temporary performance (NETP). Fig. 2 displayed that when visitors experienced temporary performance, it may intensify the positive effect of EAM on WOM, indicating the positive moderation effect of TP. In Fig. 3, we summarize whether our hypotheses are supported (see Fig. 1). Study 2: The condition configuration of word-of-mouth antecedents. 5. Fuzzy-set qualitative comparative analysis (fsQCA) fsQCA, a combination of qualitative and quantitative methods, can be used to investigate the multiple concurrent causal relationships of events. Thus, according to Manthiou et al. (2014), this study used fsQCA to identify all causal conditions combined that may lead to WOM, which is influenced by EAM, such as education experience (EDE), entertainment experience (ENE), escapism experience (ECE), and esthetics experience (ESE), TP, BI, and AOM. Ragin (2009) stated that raw data must be converted into values ranging from 0 to 1 before being used by fsQCA, with 1 representing full membership, 0.5 representing the crossover point, and 0 representing full non-membership. According to Ordanini et al. (2014), prior to variable calibration, one index is calculated for each construct by averaging corresponding indicators. A 5% threshold indicates that the item score was 6, a 50% threshold Table 1 The demographic characteristics of samples. Characteristics of respondents N % Characteristics of respondents N % Gender Males 205 65.71 Age Under 18 26 8.33 Females 107 34.29 19–30 140 44.87 Education Junior high school and below 36 11.54 31–40 102 32.69 Senior high school 119 38.14 41–50 29 9.29 College graduate 145 46.47 51–60 15 4.81 Post-graduate 12 3.85 Over 60 6 1.92 Monthly income Less than ¥2500 66 21.15 Jobs Students 53 16.99 ¥2501-5000 121 38.78 Teachers 42 13.46 ¥5001-7500 88 28.21 Employees 86 27.56 ¥7501-10000 24 7.69 Civil servants 10 3.21 Over¥10,000 13 4.17 Salespersons 12 3.85 Jobs Freelancers 27 8.56 Others 73 23.40 J. Yin et al.