EXAMINING THE RELATIONSHIP BETWEEN INTENTION TO ADOPT MOBILE COMMERCE AND BEHAVIOR OF MOBILE COMMERCE ADOPTION IN CONSUMER ELECTRONIC PRODUCTS
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Published:
Aug 3, 2021
Keywords:
M-commerce, Mobile Commerce, Theory of Planned Behavior, Tpb, Consumer Electronic Product, Electronic Product
Main Article Content
Abstract
The objective of this research is to investigate the adoption of mobile commerce (m-commerce) in consumer electronic products by using the theory of planned behavior (TPB). The data were obtained by questionnaire surveys from 386 respondents in Bangkok, Thailand. the results from the partial least squares (PLS-SEM) regression analysis demonstrated that attitude toward behavior and the subjective norm was positively related to intention to adopt m-commerce and intention was found to be a mediator between those two antecedents in predicting the behavior of m-commerce adoption.
Article Details
How to Cite
Suthatorn, P. (2021). EXAMINING THE RELATIONSHIP BETWEEN INTENTION TO ADOPT MOBILE COMMERCE AND BEHAVIOR OF MOBILE COMMERCE ADOPTION IN CONSUMER ELECTRONIC PRODUCTS. Dusit Thani College Journal, 15(2), 280–296. Retrieved from https://so01.tci-thaijo.org/index.php/journaldtc/article/view/249350
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Research Article
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References
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Suthatorn, P. (2019). M-commerce: Examining the Adoption of Mobile Commerce in Bangkok, Thailand: The Moderating Effect of Education Level. Dusit Thani College Journal, 13(2), 307-329.
Tiwari, R., & Buse, S. (2007). The mobile commerce prospects: A strategic analysis of opportunities in the banking sector: Hamburg University Press.
Troise, C., O'Driscoll, A., Tani, M., & Prisco, A. (2021). Online food delivery services and behavioural intention – a test of an integrated TAM and TPB framework. British Food Journal, 123(2), 664-683. doi: 10.1108/BFJ-05-2020-0418
Wan, C., Shen, G. Q., & Choi, S. (2017). Experiential and instrumental attitudes: Interaction effect of attitude and subjective norm on recycling intention. Journal of Environmental Psychology, 50, 69-79. doi: https://doi.org/10.1016/j.jenvp.2017.02.006
Yang, S., Li, L., & Zhang, J. (2018). Understanding consumers’ sustainable consumption intention at china’s double-11 online shopping festival: An extended theory of planned behavior model. Sustainability, 10(6), 1801. doi: https://doi.org/10.3390/su10061801
AlSondos, I., & Salameh, A. (2020). The effect of system quality and service quality toward using m-commerce service, based on consumer perspective. Management Science Letters, 10(11), 2589-2596. doi: 10.5267/j.msl.2020.3.035
Brislin, R. W. (1970). Back-translation for cross-cultural research. Journal of cross-cultural psychology, 1(3), 185-216.
Changchit, C., Cutshall, R., Lonkani, R., Pholwan, K., & Pongwiritthon, R. (2019). Determinants of online shopping influencing thai consumer’s buying choices. Journal of internet Commerce, 18(1), 1-23. doi: 10.1080/15332861.2018.1496391
Chhonker, M. S., Verma, D., Kar, A. K., & Grover, P. (2018). m-commerce technology adoption. The Bottom Line. doi: 10.1108/BL-04-2018-0020
Cui, Y., Mou, J., Cohen, J., Liu, Y., & Kurcz, K. (2020). Understanding consumer intentions toward cross-border m-commerce usage: A psychological distance and commitment-trust perspective. Electronic Commerce Research and Applications, 39, 100920.
Farrar, D. E., & Glauber, R. R. (1967). Multicollinearity in regression analysis: the problem revisited. The Review of Economic and Statistics, 92-107.
Fornell, C., & Larker, D. (1981). Structural equation modeling and regression: guidelines for research practice. Journal of Marketing Research, 18(1), 39-50.
Frolick, M. N., & Chen, L.-D. (2004). Assessing M-Commerce Opportunities. Information Systems Management, 21(2), 53-61. doi: 10.1201/1078/44118.21.2.20040301/80422.8
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the academy of marketing science, 40(3), 414-433. doi: https://doi.org/10.1007/s11747-011-0261-6
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43(1), 115-135. doi: https://doi.org/10.1108/APJBA-05-2019-0109
Kock, N., & Lynn, G. (2012a). Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations. Journal of the Association for Information Systems, 13(7).
Krairit, D. (2018). The new face of Internet user typology: the case of Thailand. Journal of theoretical and applied electronic commerce research, 13(2), 58-79. doi: 10.4067/S0718-18762018000200106
Liang, T.-P., & Wei, C.-P. (2004). Introduction to the special issue: Mobile commerce applications. International journal of electronic commerce, 8(3), 7-17. doi: 10.1080/10864415.2004.11044303
Liu, S. (2020). Consumer electronics - Statistics & Facts. Retrieved 9 May 2021, from https://www.statista.com/topics/4408/consumer-electronics/
NBTC. (2021). Internet Users in Thailand. Retrieved on 31 May 2021. From http://webstats.nbtc.go.th/netnbtc/INTERNETUSERS.php
Ngai, E. W., & Gunasekaran, A. (2007). A review for mobile commerce research and applications. Decision support systems, 43(1), 3-15. doi: 10.1016/j.dss.2005.05.003
Nunnally, J. (1978). Psychometric methods: New York: McGraw-Hill.
Pandey, S., & Chawla, D. (2020). Exploring Factors That Drive Adoption of Various Categories of M-commerce: An Emerging Market Study. Global Business Review, 21(2), 526-546.
Piazza, A. J., Knowlden, A. P., Hibberd, E., Leeper, J., Paschal, A. M., & Usdan, S. (2019). Mobile device use while crossing the street: Utilizing the theory of planned behavior. Accident Analysis & Prevention, 127, 9-18. doi: https://doi.org/10.1016/j.aap.2019.02.006
Preacher, K. J., & Leonardelli, G. J. (2001). Calculation for the Sobel test: An interactive calculation tool for mediation tests.
Ringle, C. M., Sarstedt, M., Mitchell, R., & Gudergan, S. P. (2020). Partial least squares structural equation modeling in HRM research. The International Journal of Human Resource Management, 31(12), 1617-1643. doi: https://doi.org/10.1080/09585192.2017.1416655
Siau, K., Lim, E.-P., & Shen, Z. (2001). Mobile commerce: Promises, challenges and research agenda. Journal of Database Management (JDM), 12(3), 4-13. doi: 10.4018/jdm.2001070101
Singh, S., & Srivastava, S. (2020). Exploring the moderating role of product type in Indian m-commerce fashion and electronics market. International Journal of Logistics Systems and Management, 36(1), 61-91. doi: 10.1504/IJLSM.2020.107227
Suthatorn, P. (2019). M-commerce: Examining the Adoption of Mobile Commerce in Bangkok, Thailand: The Moderating Effect of Education Level. Dusit Thani College Journal, 13(2), 307-329.
Tiwari, R., & Buse, S. (2007). The mobile commerce prospects: A strategic analysis of opportunities in the banking sector: Hamburg University Press.
Troise, C., O'Driscoll, A., Tani, M., & Prisco, A. (2021). Online food delivery services and behavioural intention – a test of an integrated TAM and TPB framework. British Food Journal, 123(2), 664-683. doi: 10.1108/BFJ-05-2020-0418
Wan, C., Shen, G. Q., & Choi, S. (2017). Experiential and instrumental attitudes: Interaction effect of attitude and subjective norm on recycling intention. Journal of Environmental Psychology, 50, 69-79. doi: https://doi.org/10.1016/j.jenvp.2017.02.006
Yang, S., Li, L., & Zhang, J. (2018). Understanding consumers’ sustainable consumption intention at china’s double-11 online shopping festival: An extended theory of planned behavior model. Sustainability, 10(6), 1801. doi: https://doi.org/10.3390/su10061801