Iranian Journal of Trade Studies

Iranian Journal of Trade Studies

Customer Resistance to Online Purchase of Tourism Products: A Systematic Review Approach

Document Type : Research Paper

Authors
zohreh Dehdashti Shahrokh 1
Vahid Naeshifar 2
Esmail Ghaderi 3
Mahnaz Lari 4
1 Professor of Business Administration Department, Faculty of Management & Accounting, Allameh Tabataba’i University, Iran (Corresponding Author)
2 Associated Professor of Business Administration Department, Faculty of Management & Accounting, Allameh Tabataba’i University, Iran.
3 Associated Professor of Tourism Management Department, Faculty of Management & Accounting, Allameh Tabataba’i University, Iran
4 PHD student in Business Administration, Faculty of Management & Accounting, Allameh Tabataba’i University, Iran
10.22034/ijts.2024.2034825.4014
Abstract
Nowadays, online businesses have experienced exponential growth, impacting all industries, including the tourism sector. Despite the numerous websites offering online tourism services, statistics indicate that there are still customers who, for various reasons, resist online purchases and prefer to buy in person from travel agencies. Customer resistance is a practical topic in the field of consumer behavior, which is examined in this study concerning online purchases of tourism products. The aim of this research is to develop a model that includes the antecedents and consequences of customer resistance to online purchases of tourism products through a systematic review approach, utilizing both meta-analysis and meta-synthesis methods. The research sample comprised 42 previous studies on customer resistance in the tourism industry from the related databases, including 12 quantitative and 10 qualitative articles. The quantitative studies were analyzed using the meta-analysis method through the CMA2 software by calculating the effect size. The qualitative studies were analyzed using the meta-synthesis method through a three-stage coding analysis, including open, axial, and selective coding. Ultimately, from the combination of both methods, the antecedents and consequences of customer resistance were extracted from the previous literature. According to the results, factors such as functional barriers, psychological barriers, customer characteristics, and website features are the antecedents of the customer resistance model. Additionally, purchase intention and social influence are considered consequences of customer resistance, and managing these factors can help in handling resistant customers and reducing their resistance to online purchase.
Keywords
Consumer Behavior / Functional Barriers / Psychological Barriers / Meta
Analysis / Meta
Synthesis

Subjects

 
Abbas, M. Shahid Nawaz, M. Ahmad, J. & Ashraf, M.(2017). The effect of innovation and consumer related factors on consumer resistance to innovation. Cogent Business & Management.4.1-23. https://doi.org/10.1080/23311975.2017.1312058
Armanfar, M. and Eslamifar, M. (2017). Investigating the impact of attracting foreign tourists on employment and predicting employment trends until 2028 (case study: Iran). 35-66, No. 87, Summer.13 [In Persian]. https://dorl.net/dor/20.1001.1.17350794.1397.22.87.2.3
Baklouti.F & Boukamcha.F.(2024). Consumer resistance to internet banking services: implications for the innovation resistance theory. Journal of Financial Services Marketing.29. 364–376. https://doi.org/10.1057/s41264-023-00210-2
Barani.M, Bagheri,M & Nikbakht,A.(2024). Study and Analysis of Tourism Branding in Shiraz City Using The Strategic Management Model of the Destination Brand. Journal of Brand Management.11(1).103-142 [In Persian]. https://dorl.net/dor/10.22051/BMR.2023.40626.2353
Benur, A. M. & Bramwell, B.(2015). Tourism product development and product diversification in destinations. Tourism Management. 50. 213-224. https://doi.org/10.1016/j.tourman.2015.02.005
Danaii, A, Moeini Rastegar, Sh, and Moghimi, Gh. (2023). Research article: Developing a model for the impact of marketing ethics of female online influencers on the sales of digital products. Journal of Business Research, No. 109, Volume 2, 177-201.[In Persian] https://doi.org/10.22034/IJTS.2024.2014787.3917
Divandari,A, Keimasi,M & Mottaghi.S.(2023). Identification and Classification of the Advertising Texts Features with the Focusing on Consumer Engagement Behavior: A Metasynthesis Approach. Journal of Business Management.15(3).481-505 [In Perisan]. https://doi.org/10.22059/JIBM.2023.348146.4441
Dehdashti Shahrokhi, Zahra. (2020). Research methods and techniques in social sciences. Bazargani Publishing and Printing Company. Tehran.[In Persian]
Dwikesumasari, P. R. & Ervianty, R. M.(2017).Customer Loyalty Analysis of Online Travel Agency App with Customer Satisfaction As A Mediation Variable. Advances in Intelligent Systems Research.131. 104-108. https://doi.org/ 10.2991/icoi-17.2017.18
Esmaeili Mahyari.M, Ghaffari.M, Irani.H & Ebrahimi.E.(2024). Identifying Touchpoints for Foreign Tourists in the Customer Journey through 5 A’s Approach. Journal of Business Management, 16(1), 114- 136.[In Persian]. https://dorl.net/dor/10.22059/JIBM.2023.359654.4586 .
Fu, S. Zheng, X. & Wong, I. A).2022). The perils of hotel technology: The robot usage resistance model. International Journal of Hospitality Management. 102. 1-11. https://doi.org/10.1016/j.ijhm.2022.103-174. https://doi.org/10.1016/j.ijhm.2022.103174
Ghorbani Zadeh, Vahidollah. (2018). Comprehensive research methodology. Tehran: Baztab Publications [In Persian]
Ghorbanizadeh V, Ghorbani Paji A. Meta-Analysis Study of the Effective Factors in the Application of Information Technology in the Iranian Organizations. Human Information Interaction 2020; 7 (2). https://dorl.net/dor/20.1001.1.24237418.1399.7.2.1.5
Hameed, I. Akram, U. & Ashraf, A.(2023). Consumers’ usage of mobile payment systems: an application of the innovation resistance and coping theory on the tourism sector. Kybernetes, 1-23. https://doi.org/10.1108/K-03-2023-0495 
Hamid, R. A. Albahri, A. S. Alwan, J. K. Al-qaysi, Z. T. Albahr, O. S. Zaidan, A. S, Zaidan, B. B.(2021). How smart is e-tourism? A systematic review of smart tourism recommendation system applying data management. Computer Science Review. 39. 1-18. https://doi.org/10.1016/j.cosrev.2020.100337
Hateftabar, F(2022). Analyzing the adoption of online tourism purchase: effects of perceived tourism value and personal innovativeness. Current Issues in Tourism.1-19. https://doi.org/10.1080/13683500.2022.2071682
Hedayati, Arshad, Dehdashti Shahrokh, Zahra, Mohammadian, Mahoud, and Nashehifar, Vahid. (2022). Research article: Designing a model for the factors influencing cooperation between Iranian private banks and fintechs using the meta-combination method. Journal of Business Research, No. 107, 37-65. [In Persian]. https://doi.org/10.22034/IJTS.2023.1990531.3805
Hossain.Md.(2023).A Modified Innovation Resistance Theory Approach to E-Tourism Resistance Intention in Bangladesh. Journal of Technology Management & Innovation.18(4).59-71. http://dx.doi.org/10.4067/S0718-27242023000400059
Huang, D. Chen, Q. Huang, J. Kong, S. Li, Z. (2021). Customer-robot interactions: Understanding customer experience with service robots. International Journal of Hospitality Management. 99. 1-14. https://doi.org/10.1016/j.ijhm.2021.103078
Huang, D. Coghlan, A. & Jin, X. (2020). Understanding the drivers of Airbnb discontinuance. Annals of Tourism Research80. 1-14. https://doi.org/10.1016/j.annals.2019.102798
Huang, D. Coghlan, A. & Jin, X .(2021) Crossing the chasm: resistance to and adoption of Airbnb by Chinese consumers. Journal of Travel & Tourism Marketing. 38(6). 597-621. https://doi.org/10.1080/10548408.2021.1969315
Huang, D., Jin, X., & Coghlan, A.(2021).  Advances in consumer innovation resistance research: A review and research agenda. Technological Forecasting & Social Change.166. 1-21. https://doi.org/10.1016/j.techfore.2021.120594
Huang, Y. K., Hsieh, C. H., Li, W., Chang, C., & Fan, W. S. (2019). Preliminary Study of Factors Affecting the Spread and Resistance of Consumers’ Use of AI Customer Service. Association for Computing Machinery.1-7 . https://doi.org/10.1145/3375959.3375968
Junsukpum, K & Kettem, S .(2015). Applying Innovation Resistance Theory to Understand Consumer Resistance of Using Online Travel in Thailand.14th International Symposium on Distributed Computing and Applications for Business Engineering and Science139-142. https://doi.org/10.1109/DCABES.2015.42
Khan,S. & Mehmood.Sh.(2024).Factors affecting innovation resistance of fast-food employees’ usage intention of robots: an integrative perspective. Journal of Hospitality and Tourism Insights.7(3).1456-1474. https://doi.org/10.1108/JHTI-08-2023-0515
Kourtesopoulou, A. Theodorou, S. D. Kriemadis, & Papaioannou, A.(2019) The Impact of Online Travel Agencies Web Service Quality on Customer Satisfaction and Purchase Intentions. Smart Tourism as a Driver for Culture and Sustainability.24.343-357. https://doi.org/10.1007/978-3-030-03910-3_24
Kumar, S., Dhiman, N. Kanojia, H. & Joshi, R. (2023). What resists millennials to adopt hotel booking apps? An empirical analysis based on extended innovation resistance theory. National Institute of. 1-16. https://doi.org/10.1108/FS-10-2021-0209
Kumar.A, Shankar.A, Kumar Tiwari.A & Hong.H. (2023).Understanding dark side of online community engagement: an innovation resistance theory perspective. Information Systems and e-Business Management.1-27. https://doi.org/10.1007/s10257-023-00633-3
Leong, L. Y., Hew, T. S., Ooi, K. B., & Wei, J. (2020). Predicting mobile wallet resistance: A two-staged structural equation modeling-artificial neural network approach. International Journal of Information Management, 51.1-24. https://doi.org/10.1016/j.ijinfomgt.2019.102047
Mani, Z  &Chouk, I.(2018). Consumer Resistance to Innovation in Services: Challenges and Barriers in the Internet of things era. Journal of Product Innovation Management. 1-65. https://doi.org/10.1111/jpim.12463
Mou, Y. Xu, T. & Hu, Y. (2023). Uniqueness neglect on consumer resistance to AI. Marketing Intelligence & Planning. 41(6). 669-689. https://doi.org/10.1108/MIP-11-2022-0505
Nel, J. & Boshoff, c.(2020). Status quo bias and shoppers’ mobile website purchasing resistance. European Journal of Marketing. 54(6). 1433-1466. https://doi.org/10.1108/EJM-02-2018-0144
Ram, S & Sheth, J. N.(1989). Consumer Resistance to Innovations: The Marketing problem and its Solution. The Journal OF Consumer Marketing. 6(2). 5-14. https://doi.org/10.1108/EUM0000000002542
Rasheed, H. M. He, Y. Usman Khizar, H. M & Abbas, H. S. (2023). Exploring Consumer-Robot interaction in the hospitality sector: Unpacking the reasons for adoption (or resistance) to artificial intelligence. Technological Forecasting & Social Change. 192. 1-8. https://doi.org/10.1016/j.techfore.2023.122555
Rezaeemanesh.B & Abbaspour.J.(2015). Meta-Analysis relationship between Quality of Work Life and Organizational Commitment. Journal of Management Studies in Development and Evolution. 24(78).65-88. https://dorl.net/dor/20.1001.1.22518037.1394.24.78.4.6
Sánchez, I. R. Williams, A. M & Andreu, H. G. (2019).Customer Resistance to Tourism Innovations: Entrepreneurs’ Understanding and Management Strategies. Journal of Travel Research.1-15. https://doi.org/10.1177/0047287519843188
San-Martin, S. Jimenez, N&  Cabanillas, F.(2020).Tourism value VS barriers to booking trips online. Journal of Retailing and Consumer Services50. 1-11. https://doi.org/10.1016/j.jretconser.2019.101957
Syed Naghavi, Mir Ali, and Jamaal Abad, Ghadir. (2013). Effective factors on tourists’ trust in electronic tourism. Journal of Tourism Management Studies, 8(21), 1-27. [In Persian]. https://dorl.net/dor/20.1001.1.23223294.1392.8.21.1.8   
Smith, S. L. (1994). The Tourist Product. Annals of Tourism Research. 21(3). 582-595. https://doi.org/10.1016/0160-7383(94)90121-X
Sun, Y. (2021). Case based models of the relationship between consumer resistance to innovation and customer churn. Journal of Retailing and Consumer Services61. 1-6. https://doi.org/10.1016/j.jretconser.2021.102530
Talwar, S. Dhir, A. Kaur, P & Mantimaki, M. (2020). Barriers toward purchasing from online travel agencies. International Journal of Hospitality Management.89. 1-11. https://doi.org/10.1016/j.ijhm.2020.102593
Talwar, S. Dhir, A. Scutto, V & Kaur, P.(2021). Barriers and paradoxical recommendation behaviour in online to offline (O2O) services. A convergent mixed-method study. Journal of Business Research. 131. 25-39. https://doi.org/10.1016/j.jbusres.2021.03.049
Wang, X. Zhang, Z. Huang, D & Li, Z. (2023). Consumer resistance to service robots at the hotel front desk: A mixed-methods research. Tourism Management Perspectives...46. 1-14. https://doi.org/10.1016/j.tmp.2023.101074
Xu, J. B.(2010).Perceptions of tourism products. Tourism Management. 31. 607-610. https://doi.org/10.1016/j.tourman.2009.06.011
Yang, H. S  & Park, J. W.(2019). A study of the acceptance and resistance of airline mobile application services: with an emphasis on user characteristics. International Journal of Mobile Communications. 17(1). 24-43. https://doi.org/10.1504/IJMC.2019.096514
 
 
 

  • Receive Date 08 July 2024
  • Revise Date 17 October 2024
  • Accept Date 26 October 2024