e-Review of Tourism Research (eRTR), Vol. 17, No. 4, 2019 http://ertr.tamu.edu 610 Zhongyi Ma University of South Florida Sarasota-Manatee Katerina Berezina University of Mississippi Cihan Cobanoglu University of South Florida Sarasota-Manatee Predicting Chinese travelers’ intentions to use Airbnb The purpose of this study is to develop and test a model explaining factors influencing customer decision-making regarding Airbnb accommodations in China. This study builds on the theory of planned behavior to develop a model to explain a decision-making process of Chinese consumers when it comes to choosing Airbnb accommodation. The results of the study were based on the analysis of 451 responses collected via WeChat. The findings confirmed behavioral control, subjective norms, and attitude as statistically significant predictors of intentions to book Airbnb by Chinese travelers. Key words: Airbnb, China, decision model, theory of planned behavior, PLS SEM Zhongyi Ma Document Clerk Application Processing Center Beijing Youth Concern International Education Consulting Center Hangzhou Sub-center R409，F4, Yuantong Bldg., 511 Yan'an Rd., Hangzhou, Zhejiang, China Phone:(+86) 15067129790 Email: 1535197285@qq.com Katerina Berezina, PhD, CHTP, CRME, CHIA Department of Nutrition and Hospitality Management The University of Mississippi P.O. Box 1848 216 Lenoir Hall University, MS 38677-1848 U.S.A. Phone: +1 (662) 915-3073 Email: eberezin@olemiss.edu http://ertr.tamu.edu/ mailto:eberezin@olemiss.edu e-Review of Tourism Research (eRTR), Vol. 17, No. 4, 2019 http://ertr.tamu.edu 611 Cihan Cobanoglu, PhD, CHTP College of Hospitality and Tourism Leadership University of South Florida Sarasota-Manatee 8350 N. Tamiami Tr. Sarasota, FL 34243 U.S.A. Phone: 941-359-4200 Email: cihan@usf.edu Zhongyi Ma, M.S., graduated from the University of South Florida Sarasota-Manatee with a master’s degree in Hospitality Management. Upon graduation he worked as an HR Clerk in Intercontinental Hangzhou for 10 months. Currently he is employed as a document clerk in Application Processing Center of Beijing Youth Concern International Education Consulting Center Hangzhou Sub-center. His research interests include sharing economy and brand localization in China. Katerina Berezina, PhD, CHTP, CRME, CHIA, is an Assistant Professor in the Department of Nutrition and Hospitality Management at the University of Mississippi. Her research interests are in the areas of information technology in hospitality and tourism, electronic distribution, and revenue management. Cihan Cobanoglu, PhD, is the McKibbon Endowed Chair Professor of the College of Hospitality & Tourism Leadership at the University of South Florida Sarasota-Manatee, and he also serves as the director of the M3 Center for Hospitality Technology and Innovation and coordinator of International Programs for the College of hospitality & Tourism Leadership. His research involves the use and impact of technology in the hospitality industry. http://ertr.tamu.edu/ mailto:cihan@usf.edu e-Review of Tourism Research (eRTR), Vol. 17, No. 4, 2019 http://ertr.tamu.edu 612 Introduction Airbnb, short for airbed and breakfast, is a peer-to-peer internet platform that offers individuals chances to become local hosts through renting their spare houses and rooms to travelers for a short period of time (Birinci et al., 2018; Zervas et al., 2014). This platform has gained popularity among travelers for an opportunity to experience the local lifestyle with living in the homes of local people. Airbnb was created in the U.S, but later expanded internationally. In this transition, it may encounter some problems, such as unfamiliarity with the market, financial instability and environmental sustainability challenges (Van Paasschen, 2015). Therefore, to become successful in a new market the company should explore local customers’ decision-making model and implement some adaptations based on their culture and society (Zhao, 2016). The purpose of this study is to develop and test a model explaining factors influencing customer decision-making regarding Airbnb accommodations in China. Airbnb officially entered Chinese market on August 19th of 2015, however, did not gain immediate popularity (Bie et al., 2017). Academic research highlighted dilemmas that Airbnb faced in Chinese market, such as unfamiliarity of Chinese customer, keen competition, and lack of trust (Cui, 2015; Qiu et al., 2016). Most of studies concentrate on the in-adaptability and difficulties of Airbnb brand domestication in China rather than exploring Chinese people decision-making process (Cui, 2015, Zhao, 2016). Therefore, the research problem of this study is grounded in the lack of understanding of factors influencing behavior of Chinese travelers when selecting Airbnb accommodations. This study builds on the theory of planned behavior to develop a model to explain a decision-making process of Chinese consumers when it comes to choosing Airbnb accommodation. http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 17, No. 4, 2019 http://ertr.tamu.edu 613 Literature review Airbnb in China Airbnb entered China in 2015, but until 2016, the distribution of Airbnb hosts in China mainly concentrated in Beijing and Shanghai, which indicated slow penetration and differences in people attitudes toward this type of accommodation compared to the United States, where the concept originated. At the same time, it also reflects great potential of the Chinese market that Airbnb still needs to explore (Qiu et al., 2016). Previous studies in China reveal that obstacles and difficulty that Airbnb confronts in China focus on the domestication of Airbnb, the unfamiliarity that Airbnb has on China’s market and Chinese travelers and lower consumers’ awareness on Airbnb slow down the pace of Airbnb’s development in China (Qiu et al., 2016; Zhao, 2016) Previous research mainly concentrated on Western markets and identified various factors that influence travelers’ choice of Airbnb: consumer’s perceived authenticity (Birinci et al., 2018; Grayson & Martinec, 2004; Liang, 2015; Steiner & Reisinger, 2006), price (Chang 1994; Liang, 2015; Moon et al., 2008), online reviews (Ert, & Magen, 2015; Fradkin et al., 2015; Zervas, 2015), availability (Kennedy, & Dawson, 2017; Zervas, 2015; Zuev, 2015), and trust level (Ert 2015; Kim et al., 2008; Lu et al., 2011). These studies provide some guidance for understanding the behavior of Chinese consumers, however, variables that have been identified through previous research should be tested in the new market environment. Theoretical background The theory of planned behavior (TPB) is a theory that combines people believes, http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 17, No. 4, 2019 http://ertr.tamu.edu 614 attitudes and intentions to reveal the decision-making behind a certain behavior. This theory was developed based on the theory of reasoned action by Icek Ajzen (Ajzen, 1991). Currently, it has been widely utilized to analyze human behavior in different fields. The theory of planned behavior suggests that people’s behavior is affected by three main factors: attitude, subjective norm, and perceived behavioral control. The attitude refers to the evaluation that people give to the behavior they may perform (Ajzen, 1985). In the context of this research, attitudes refer to traveler’s evaluation of Airbnb as a potential accommodation option. This research hypothesizes that traveler attitudes toward Airbnb will have an impact on intentions to book this type of accommodation. The subjective norm is the individual’s impression or perception of specific behavior, which will be impacted by critical judgment from other individuals or groups (Ajzen, 1985). Subjective norm includes social comments that individual received from other people when the individual aims to engage in certain behavior. Previous research found that subjective norms may not only be affected by the personal level differences, but also influenced by the cultural and societal values and norms (Hofstede & Hofstede, 2001; Triandis, 1989) because culture norms play a major role on marketing perception and consumer’s behavior (Pookulangara & Koesler, 2011). In the context of this study, subjective norms may be influenced by Chinese collectivist culture (Chen, 2000; Lam et al., 2003). Perceived behavioral control refers to indispensable possession of resources and opportunities that people have to implement a behavior. This variable plays a vital role for individuals to perform particular behaviors because it described the perceived ease or difficulty of performing specific behaviors (Ajzen, 2002a). This study hypothesizes that http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 17, No. 4, 2019 http://ertr.tamu.edu 615 perceived behavioral control may be one of the factors influencing intentions to book Airbnb accommodations for Chinese travelers. Method This study employed a quantitative method to develop and test the proposed research model. The survey instrument was built in English and was translated into Chinese using back translation method (Marin & Marin, 1991; McGorry, 2000). The survey was built using Qualtrics platform and was distributed online. The survey started with a qualifying question where participants were asked whether they have stayed in AirBnB in the last year. The targeted population of this study are Chinese travelers who have stayed in AirBnB accommodations. After the qualifying question, the survey continued with demographics questions, after that, participants received questions about attitudes toward Airbnb, subjective norm, perceived behavioral control, and their intention to stay in Airbnb. The survey items were developed based on existing scales and used five-point Likert-type scale ranging from 1 (disagree) to 5 (strongly agree) and seven-point Likert-type scale ranging from 1 (extremely disagree) to 7 (extremely agree). Prior to main data collection, a pilot test was conducted via Facebook and WeChat to check the clarity of the survey and scale reliability. Findings Sample and Demographics A total of 967 surveys were collected for this study via WeChat. Among these, 451 usable responses were retained for the data analysis stage after excluding those participants who were not familiar with Airbnb and incomplete responses. Majority of respondents were http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 17, No. 4, 2019 http://ertr.tamu.edu 616 female (71%), between 18 and 24 years of age (70%), attending a college or university (67%). Hypotheses Testing Since this study tested the theory of planned behavior in the context of Airbnb in China, partial least squares structural equation modelling (PLS SEM) was applied to test the model (Hair, Ringle, & Sarstedt, 2011). The analysis of the model started with evaluation of the measurement model. Internal consistency and convergent validity were confirmed using Cronbach’s alpha, composite reliability (CR), and average variance extracted (AVE). Discriminant validity of the measurement model was checked and ensured through the examination of the Fornell-Larcker criterion and cross-loadings (Hair et al., 2011). The results of the model testing revealed that all path coefficients were statistically significant. Behavioral control had the highest path coefficient among all variables affecting intentions to book Airbnb accommodations by Chinese travelers. The path between attitudes and intentions to use Airbnb accommodations was marginally significant at p = 0.049. Conclusions The purpose of this study was to understand the decision-making process of Chinese travelers with regard to selecting Airbnb accommodations. The study tested the theory of planned behavior in the context of selecting Airbnb accommodations by Chinese travelers. All hypothesized relationships were found to be statistically significant. This study contributes to the development of the theory of reasoned action by testing the model in the context of Airbnb accommodations in China. Overall, the model demonstrated a http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 17, No. 4, 2019 http://ertr.tamu.edu 617 high level of explanatory power. The same may be said for subjective norm and behavioral control. However, the construct of attitudes should be revisited in future research to include more predictors and improve the amount of variance explained. This study brings practical implications to understanding Chinese consumers’ behavior with regard to selecting Airbnb accommodations. One of the important variables influencing intentions of Chinese travelers to stay in Airbnb was behavioral control. This means that in order to achieve success on Chinese market, Airbnb should make it easy for customers to book travel by providing accommodation options in different places, user-friendly booking interface, and affordable pricing. In addition, in the context of Chinese market social norms seem to outweigh personal attitudes when selecting Airbnb accommodations. This finding highlights the importance of the societal approval in Chinese culture. This means that in order to be successful, Airbnb needs to finds its way to the hearts not only the target consumer, but also to their circles (e.g., parents, siblings, children, friends, etc.). This study validated the theory of planned behavior as a model explaining consumer behavior of Chinese travelers when selecting Airbnb accommodations. This research may be developed further by including additional variables that have been studied about selecting Airbnb on other markets. Such variables may include perceived authenticity (Birinci et al., 2018; Liang, 2015; Wang, 1999), online reviews (Chevalier & Mayzlin, 2006; Duan, Gu, & Whinston, 2008), price (Liang, 2015; Moon et al., 2008) and availability (Qiu et al., 2016; Hawlitschek et al., 2016). References Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 17, No. 4, 2019 http://ertr.tamu.edu 618 decision processes, 50(2), 179-211. Bie, Y., Wang, J., & Wang, J. (2017, July). Airbnb in China: The Impact of Sharing Economy on Chinese Tourism. In International Conference on Applied Human Factors and Ergonomics (pp. 11-19). Springer, Cham. Birinci, H., Berezina, K., & Cobanoglu, C. (2018). Comparing customer perceptions of hotel and peer-to-peer accommodation advantages and disadvantages. International Journal of Contemporary Hospitality Management, 30(2), 1190-1210. Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of marketing research, 43(3), 345–354. Chhabra, D. (2008). Positioning museums on an authenticity continuum. Annals of Tourism Research, 35(2), 427–447. Duan, W., Gu, B., & Whinston, A. B. (2008). Do online reviews matter? - An empirical investigation of panel data. Decision support systems, 45(4), 1007–1016. Ert, E., Fleischer, A., & Magen, N. (2015). Trust and Reputation in the Sharing Economy: The Role of Personal Photos on Airbnb. Available at SSRN 2624181. Retrieved from http://papers.ssrn.com/sol3/Papers.cfm?abstract_id=2624181 Forman, C., Ghose, A., & Wiesenfeld, B. (2008). Examining the relationship between reviews and sales: The role of reviewer identity disclosure in electronic markets. Information Systems Research, 19(3), 291–313 Fradkin, A., Grewal, E., Holtz, D., & Pearson, M. (2015). Bias and reciprocity in online reviews: Evidence from field experiments on airbnb. Proceedings of the Sixteenth ACM Conference on Economics and Computation (P 641–641). ACM. Retrieved from http://dl.acm.org/citation.cfm?id=2764528 Grayson, K., & Martinec, R. (2004). Consumer perceptions of iconicity and indexicality and their influence on assessments of authentic market offerings. Journal of consumer research, 31(2), 296–312. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152. Hawlitschek, F., Teubner, T., & Gimpel, H. (2016). Understanding the Sharing Economy–Drivers and Impediments for Participation in Peer-to-Peer Rental. System Sciences (HICSS), 2016 49th Hawaii International Conference on (P4782–4791). IEEE. Retrieved from http://ieeexplore.ieee.org/abstract/document/7427780 Hofstede, G. H., & Hofstede, G. (2001). Culture’s consequences: Comparing values, behaviors, institutions and organizations across nations. Sage. Retrieved from https://books.google.com/books?hl=en&lr=&id=w6z18LJ_1VsC&oi=fnd&pg=PR15 &dq=culture%27s+consequences+comparing+values&ots=x6hBzbFqg5&sig=Ah4eD v4X_li9LKwPjRvUF_X_VyE Kennedy, R. D., Douglas, O., Stehouwer, L., & Dawson, J. (2017). The availability of smoking-permitted accommodations from Airbnb in 12 Canadian cities. Tobacco Control, tobaccocontrol–2016. Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision support systems, 44(2), 544–564. Liang, L. J. (2015). Understanding repurchase intention of Airbnb consumers: perceived http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 17, No. 4, 2019 http://ertr.tamu.edu 619 authenticity, EWoM and price sensitivity. Retrieved from https://atrium2.lib.uoguelph.ca/xmlui/handle/10214/8813 Marin, G., & Marin, B. (1991). Research with Hispanic Populations. Applied Social Research Methods Series, v23. Newbury Park: Sage Publications McGorry, S. Y. (2000). Measurement in a cross-cultural environment: survey translation issues. Qualitative Market Research: An International Journal, 3(2), 74–81. Moon, J., Chadee, D., & Tikoo, S. (2008). Culture, product type, and price influences on consumer purchase intention to buy personalized products online. Journal of Business Research, 61(1), 31–39. Pookulangara, S., & Koesler, K. (2011). Cultural influence on consumers’ usage of social networks and its’ impact on online purchase intentions. Journal of Retailing and Consumer Services, 18(4), 348–354. Ramkissoon, H., & Uysal, M. S. (2011). The effects of perceived authenticity, information search behaviour, motivation and destination imagery on cultural behavioural intentions of tourists. Current Issues in Tourism, 14(6), 537–562. Qiu Rong, Ou Shuyi, Jiang Jiayin, & Huang Liting. (2016). The Current Situation and Its Countermeasures of Airbnb in China. Value Engineer. (31), 176–178 Triandis, H. C. (1989). The self and social behavior in differing cultural contexts. Psychological review, 96(3), 506. Van Paasschen, Fr. (2015). Globalization from a Business Leader’s Point of View. Brown J. World Aff., 22, 175 Zervas, G., Proserpio, D., & Byers, J. W. (2014). The rise of the sharing economy: Estimating the impact of Airbnb on the hotel industry. Journal of Marketing Research. Retrieved from http://journals.ama.org/doi/abs/10.1509/jmr.15.0204 Wang, N. (1999). Rethinking authenticity in tourism experience. Annals of tourism research, 26(2), 349–370. http://ertr.tamu.edu/ http://journals.ama.org/doi/abs/10.1509/jmr.15.0204 Zhongyi Ma Email: eberezin@olemiss.edu Cihan Cobanoglu, PhD, CHTP College of Hospitality and Tourism Leadership University of South Florida Sarasota-Manatee 8350 N. Tamiami Tr. Sarasota, FL 34243 U.S.A. Phone: 941-359-4200 Email: cihan@usf.edu Katerina Berezina, PhD, CHTP, CRME, CHIA, is an Assistant Professor in the Department of Nutrition and Hospitality Management at the University of Mississippi. Her research interests are in the areas of information technology in hospitality and touris... Cihan Cobanoglu, PhD, is the McKibbon Endowed Chair Professor of the College of Hospitality & Tourism Leadership at the University of South Florida Sarasota-Manatee, and he also serves as the director of the M3 Center for Hospitality Technology and In... Introduction Literature review