Mobile Banking Adoption in Thailand: The Moderating Role of Hedonic and Utilitarian Consumer Types
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Abstract
Mobile banking in Thailand faces challenges in attracting customers that demonstrate different behaviors based on consumer values. This study aimed to understand the adoption of mobile banking in Thailand with the moderating effect of hedonic and utilitarian consumers on the relationship between the determinants and the intention to adopt mobile banking. A survey questionnaire collected data from 1088 Thai mobile banking users and was analyzed with structural equation modeling. The results indicate that perceived usefulness (β = .58, p = .01), perceived ease of use (β = .33, p = .01), mobile banking service quality (β = .54, p =. 01), and reference groups (β = .11, p = .0) significantly affected mobile banking adoption. Moreover, the impact of perceived usefulness was significantly greater among utilitarians (β= .16, p = .00) than hedonists (β= .08, p = .01). Perceived ease of use was also significantly higher among utilitarians (β =.14, p =.01) than among hedonists (β =.01, p =.00). However, the influence of mobile service quality on mobile banking adoption was significantly stronger among hedonists (β = .70, p = .01) than utilitarians (β = .45, p = .01). Reference groups were significant for hedonists (β = .20, p =.01), but not for utilitarians (β = .6, p = .08). This study contributes to behavioral science by first investigating the moderating effects of hedonic and utilitarian consumers on mobile banking adoption. The findings have practical implications for marketers to develop appropriate marketing strategies to fit two distinct types of consumer needs. Future research should be replicated in other countries to increase generalization.
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References
Agyei, J., Sun, S., Abrokwah, E., Penney, E. K., & Ofori-Boafo, R. (2020). Mobile banking adoption: examining the role of personality traits. SAGE Journals, 10, 1-15. https://doi.org/10.1177/2158244020932918
Akdim, K., Casalo, L.V., & Flavian, C. (2022). The role of utilitarian and hedonic aspects in the continuance intention to use social mobile apps. Journal of Retailing and Consumer Services, 66, 102888. https://doi.org/10.1016/j.jretconser.2021.102888.
Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Williams, M. D. (2016). Consumer adoption of mobile banking in Jordan: Examining the role of usefulness, ease of use, perceived risk and self-efficacy. Journal of Enterprise Information Management, 29(1), 118-139. https://doi.org/10.1108/JEIM-04-2015-0035
Alkawaldeh, A. M., Matar, A., & Al-Rdaydeh, M. (2020). Behavioral intentions to use mobile banking services: Extended model, International Journal of Business Information Systems, 1. https://doi.org/10.1504/IJBIS.2020.10025359
American Psychological Association. (2017). Ethical Principles of Psychologists and Code of
Conduct. American Psychological Association. https://www.apa.org/ethics/code/ethics-code-2017.pdf
Arcand, M., PromTep, S., Brun, I., & Rajaobelina, L. (2017). Mobile banking service quality and customer relationships. The International Journal of Bank Marketing, 35, 1068-1089. https://doi.org/10.1108/IJBM-10-2015-0150
Arnold, M. J., & Reynolds, K. E. (2003). Hedonic shopping motivations. Journal of Retailing, 79, 77-95. https://doi.org/10.1016/S0022-4359(03)00007-1
Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 20, 644-656. https://doi.org/10.1086/209376
Bank of Thailand. (2021a). Commercial Banks registered in Thailand’s Deposits Classified by Sizes and Maturity.
https://www.bot.or.th/App/BTWS_STAT/statistics/ReportPage.aspx?reportID=188&language=eng
Bank of Thailand. (2021b). Use of mobile banking and internet banking statistic 2021. https://www.bot.or.th/App/BTWS_STAT/statistics/ReportPage.aspx?reportID=949&language=eng
Batra, R., & Ahtola, O. T. (1991). Measuring the hedonic and utilitarian sources of consumer attitudes. Marketing Letters, 2, 159-170. https://doi.org/10.1007/BF00436035
Bearden, W. O., & Etzel, M. J. (1982). Reference group influence on product and brand purchase decisions. Journal of Consumer Research, 9, 183-194. https://doi.org/10.1086/208911
Childers, T. L., Carr, C. L., Peck, J., &. Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77, 511-535. https://doi.org/10.1016/S0022-4359(01)00056-2
Childers, T. L., & Rao, A. R. (1992). The influence of familial and peer-based reference groups on consumer decisions. Journal of Consumer Research, 19, 198-211. https://doi.org/10.1086/209296
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of Tests. Psychometrika, 16, 297-334. https://doi.org/10.1007/BF02310555
Cronin, J. J., Brady, M.K. & Hult, G. T. (2000). Assessing the effects of quality, value and customer satisfaction on consumer behavioral intentions in service environments. Journal of Retailing, 76, 193-218. https://doi.org/10.1016/S0022-4359(00)00028-2
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology, Management Information Systems Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Delone, W. H., & McLean, E. R. (2003). The Delone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19, 9-30. https://doi.org/10.1080/07421222.2003.11045748
Ding, S., Lin, J., & Zhang, Z. (2020). Influences of reference group on users’ purchase behavioral intentions in network communities: From the perspective of trial purchase and upgrade purchase. Sustainability, 12, 1-19. https://doi.org/10.3390/su122410619
Farah, F. M., Hasni, S. J. M., & Abbas, K. A. (2018) Mobile banking adoption: empirical evidence from the banking sector in Pakistan. The International Journal of Bank Marketing, 36(7), 1386-1413. https://doi.org/10.1108/IJBM-10-2017-0215
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39–50. https://doi.org/10.2307/3151312
Hair, J. F., Anderson, R. E., Babin, B. J., & Black W. C. (2010). Multivariate Data Analysis: A Global Perspective. Pearson Education.
Ho, J. C., Wu, C. G., Lee, C. S., & Pham, T. T. (2020) Factors affecting the behavioral intentions to adopt mobile banking: An international comparison. Technology in Society, 63. https://doi.org/10.1016/j.techsoc.2020.101360
Holbrook, M. B., & Hirschman, E. C. (1982) The experiential aspects of consumption: consumer fantasies, feelings, and fun. Journal of Consumer Research, 9, 132–140. https://doi.org/10.1086/208906
Hoonsopon, D. (2016) Accelerating adoption of new products of Thai consumers: The moderating roles of self-brand concept and reference group. Asia Pacific Journal of Management, 17, 151–172. https://doi.org/10.1080/10599231.2016.1166023
Hoonsopon, D., & Puriwat, W. (2016). The effect of reference groups on purchase behavioral intentions: Evidence in distinct types of shoppers and product involvement. Australasian Marketing Journal, 24, 157-164. https://doi.org/10.1016/j.ausmj.2016.05.001
Huang, E. Y., Lin, S. W., & Fan, Y. C. (2015). M-S-QUAL: Mobile service quality measurement. Electronic Commerce Research and Applications, 14, 126-142. https://doi.org/10.1016/j.elerap.2015.01.003
Kim, D. J., & Hwang, Y. (2012). A study of mobile internet user’s service quality perceptions from a user’s utilitarian and hedonic value tendency perspectives. Information Systems Frontiers, 14, 409-421. https://doi.org/10.1007/s10796-010-9267-8
Kim, K. J., & Shin, D. H. (2015). An acceptance model for smart watches: Implications for the adoption of future wearable technology. Internet Research, 25, 527-541.
https://doi.org/10.1108/IntR-05-2014-0126
Komulainen, H., & Saraniemi, S. (2019). Customer centricity in mobile banking: a customer experience perspective. International Journal of Bank Marketing, 37(5), 2411-1102. https://doi.org/10.1108/ijbm-11-2017-0245
Kumar, R. (2017). A proposed scale of assessing mobile app service quality (MAPPSQL). ELK Asia Pacific Journal of Marketing and Retail Management, 8(1), 1-11.
Kumar, A., Dhingra, S., Batra V., & Purohit, H. (2020). A framework of mobile banking adoption in India. Journal of Open Innovation: Technology, Market, and Complexity, 6, 40. https://doi.org/10.3390/joitmc6020040
Kwateng, K. O., Atiemo, K. A. O., & Appiah, C. (2019). Acceptance and use of mobile banking: An application of UTAUT2. Journal of Enterprise Information Management, 32, 118-152. https://doi.org/10.1108/02652320510584403
Lassar, W. M., Manolis, C., & Lassar, S. S. (2005). The relationship between consumer innovativeness, personal characteristics, and online banking adoption. The International Journal of Bank Marketing, 23, 176-199. https://doi.org/10.1108/02652320510584403.
Makanyeza, C. (2017). Determinants of consumers’ behavioral intentions to adopt mobile banking services in Zimbabwe. International Journal of Bank Marketing., 35, 997-1017. https://doi.org/10.1108/IJBM-07-2016-0099
Malhotra, A., & Kubowicz-Malhotra, C. (2013). Exploring switching behavior of US mobile service customers. 2013, Journal of Services Marketing, 27, 13-24. https://doi.org/10.1108/08876041311296347
Mattila, M., Karjaluoto, H., & Pento,T. (2001). Internet banking adoption factors in Finland. Journal of Internet Banking and Commerce, 6, 129-133.
Parasuraman, A., Zeithaml, V.A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring customer perceptions of service quality. Journal of Retailing, 64, 12-40.
Puriwat, W., & Tripopsakul, S. (2017). Mobile banking adoption in Thailand: An integration of technology acceptance model and mobile service quality. European Research Studies, 200-210. https://doi.org/10.35808/ersj/885
Rafdinal, W., & Senalasari, W. (2021). Predicting the adoption of mobile payment applications during the COVID-19 pandemic. International journal of bank marketing, 39, 984-1002. https://doi.org/10.1108/IJBM-10-2020-0532
Rintamaki,T., Kanto, A., Kuusela, H., & Spence, M.T. (2006). Decomposing the value of department store shopping into utilitarian, hedonic and social dimensions: evidence from Finland. International Journal of Retail & Distribution Management, 34, 6–24. https://doi.org/10.1108/09590550610642792
Saprikis, V., Avlogiaris, G., & Katarachia, A. (2022). A Comparative Study of Users versus Non-Users’ Behavioral Intention towards M-Banking Apps’ Adoption. Information, 13(1), 30. https://doi.org/10.3390/info13010030
Sass, A. D., & Schmitt, A.T. (2013). Testing Measurement and Structural Invariance: Implications for practice. In T. Teo. (Eds.), Handbook of Quantitative Methods for Educational Research (pp. 315-346). Sense Publishers. https://doi.org/10.1007/978-94-6209-404-8_15
Scarpi, D. (2012). Work and fun on the internet: The effects of utilitarianism and hedonism online. Journal of Interactive Marketing, 26, 53–67. https://doi.org/10.1016/j.intmar.2011.08.001
Sener, A., Atesoglu, L., & Coskun, A. (2018). The effect of utilitarian and hedonic shopping values on consumers perceived benefits and risks in online shopping. Journal of Academic Researches and Studies, 10, 12-28. https://doi.org/10.20990/kilisiibfakademik.428589
Sweeney, J.C., & Soutar, G.N. (2001). Consumer perceived value: the development of a multiple item scale. Journal of Retailing, 77, 203–220. https://doi.org/10.1016/S0022-4359(01)00041-0
Tiwari, P., Tiwari, S. K., & Gupta, A. (2021). Examining the impact of customers’ awareness, risk and trust in m-banking adoption. FIIB Business Review, 10(4), 413-423. https://doi.org/10.1177/23197145211019924
Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: development and test, Decision Sciences. 1996, 27, 451–481. https://doi.org/10.1111/j.1540-5915.1996.tb00860.x
Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36, 1, 157–178. https://doi.org/10.2307/41410412
World Bank (2021). Thailand economic monitor: The road to recovery. The World Bank Group.