The Main Factors Influencing E-Business Technology Adoption of Entrepreneurs in WOW Project Songkhla, Thailand
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Published:
Dec 20, 2019
Keywords:
E-Business Technology Adoption UTAUT model SMEs
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Abstract
This study aims to determine the factors that influence the adoption of E-business technology among SMEs in Songkhla, Thailand. The Unified Theory of Acceptance and Use of Technology model (UTAUT) was used to test the adoption and usage of the e-business technology. Questionnaires were distributed and quantitative method was utilized. The organizations with more than ten employees in Songkhla were chosen using database version. Moreover, the SmartPLS program was used to analyze the collected data. Based on the results, performance expectancy was the main reason for the use of technology in the future. In addition, effort expectance and perceived credibility have positive impact on the intention to use future technology. Voluntariness, on the other hand, does not affect this decision. The implications of this study reveal the important to understand why some companies choose to use technology. The study recommends the local companies in maximizing the E-business opportunities in order to gain competitive advantage.
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บทความวิจัย (Research Article)
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References
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Cao, Y., Ajjan, H., Hong, P., & Le, T. (2018). Using social media for competitive business outcomes: An empirical study of companies in China. Journal of Advances in Management Research, 15(2), 211-235.
Dulle, F. W., & Minishi-Majanja, M. K. (2011). The suitability of the Unified Theory of Acceptance and Use of Technology (UTAUT) model in open access adoption studies. Information Development, 27(1), 32-45.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Frambach, R. T., & Schillewaert, N. (2002). Organizational innovation adoption: A multi-level framework of determinants and opportunities for future research. Journal of Business Research, 55(2), 163-176.
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Hart, P., & Saunders, C. (1997). Power and trust: Critical factors in the adoption and use of electronic data interchange. Organization Science, 8(1), 23-42.
Hock, C., Ringle, C. M., & Sarstedt, M. (2010). Management of multi-purpose stadiums: Importance and performance measurement of service interfaces. International Journal of Services Technology and Management, 14(2-3), 188-207.
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Oliveira, T., & Martins, M. F. (2010). Understanding e-business adoption across industries in European countries. Industrial Management & Data Systems, 110(9), 1337-1354.
San Martín, H., &Herrero, Á. (2012). Influence of the user’s psychological factors on the online purchase intention in rural tourism: Integrating innovativeness to the UTAUT framework. Tourism Management, 33(2), 341-350.
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Venkatesh, V., Davis, F. D., & Morris, M. G. (2007). Dead or alive?The development, trajectory and future of technology adoption research. Journal of the Association for Information Systems, 8(4), 267-286.
Venkatesh, V., Morris, M.G., Davis, F.D., and Davis, G.B. (2003).“User Acceptance of Information Technology: Toward a Unified View,” MIS Quarterly, 27, 425-478.
Venkatesh, V., & Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 115-139.
Williams, M. D., Rana, N. P., & Dwivedi, Y. K. (2015). The unified theory of acceptance and use of technology (UTAUT):
a literature review. Journal of Enterprise Information Management, 28(3), 443-488.
Yu, C. S. (2012). Factors Affecting Individuals to Adopt Mobile Banking: Empirical Evidence from the UTAUT Model. Journal of Electronic Commerce Research, 13(2), 104-121.
Zainab, B., Awais Bhatti, M., & Alshagawi, M. (2017). Factors affecting e-training adoption: an examination of perceived cost, computer self-efficacy and the technology acceptance model. Behaviour & Information Technology, 36(12), 1261-1273.
Zhu, K., & Kraemer, K. L. (2005). Post-adoption variations in usage and value of e-business by organizations: cross-country evidence from the retail industry. Information Systems Research, 16(1), 61-84.
Ajao, B. F., Oyebisi, T. O., & Aderemi, H. O. (2018). Factors influencing the implementation of e-commerce innovations: The case of the Nigerian informal sector. African Journal of Science, Technology, Innovation and Development, 10(4), 473-481.
AlAwadhi, S., & Morris, A. (2008). The use of the UTAUT Model in the adoption of e-government services in Kuwait. In Hawaii International Conference on System Sciences, Proceedings of the 41st Annual (pp. 219-219). IEEE.
Alkhunaizan, A., & Love, S. (2012). What drives mobile commerce? An empirical evaluation of the revised UTAUT model. International Journal of Management and Marketing Academy, 2(1), 82-99.
Cao, Y., Ajjan, H., Hong, P., & Le, T. (2018). Using social media for competitive business outcomes: An empirical study of companies in China. Journal of Advances in Management Research, 15(2), 211-235.
Dulle, F. W., & Minishi-Majanja, M. K. (2011). The suitability of the Unified Theory of Acceptance and Use of Technology (UTAUT) model in open access adoption studies. Information Development, 27(1), 32-45.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Frambach, R. T., & Schillewaert, N. (2002). Organizational innovation adoption: A multi-level framework of determinants and opportunities for future research. Journal of Business Research, 55(2), 163-176.
Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications.
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.
Hart, P., & Saunders, C. (1997). Power and trust: Critical factors in the adoption and use of electronic data interchange. Organization Science, 8(1), 23-42.
Hock, C., Ringle, C. M., & Sarstedt, M. (2010). Management of multi-purpose stadiums: Importance and performance measurement of service interfaces. International Journal of Services Technology and Management, 14(2-3), 188-207.
Kfouri, G., & Skyrius, R. (2016). Factors influencing the implementation of business intelligence among small and medium enterprises in Lebanon. Informacijos Mokslai, 76, 96-110.
Khemthong, S., & Roberts, L. M. (2006). Adoption of Internet and web technology for hotel marketing: a study of hotels in Thailand. Journal of Business Systems, Governance, and Ethics, 1(2), 47-60.
Kumar, S., Luthra, S., & Haleem, A. (2015). Benchmarking supply chains by analyzingtechnology transfer critical barriers using AHP approach. Benchmarking: An International Journal, 22(4), 538-558.
Legris, P., Ingham, J., &Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40(3), 191-204.
Lu, J., Yu, C. S., Liu, C., & Yao, J. E. (2003). Technology acceptance model for wireless internet. Internet Research,13(3), 206-222.
Mathieson, K., Peacock, E., & Chin, W. W. (2001). Extending the technology acceptance model: The influence of perceived user resources. ACM SigMIS Database, 32(3), 86-112.
Oliveira, T., & Martins, M. F. (2010). Understanding e-business adoption across industries in European countries. Industrial Management & Data Systems, 110(9), 1337-1354.
San Martín, H., &Herrero, Á. (2012). Influence of the user’s psychological factors on the online purchase intention in rural tourism: Integrating innovativeness to the UTAUT framework. Tourism Management, 33(2), 341-350.
Saekow, A., & Samson, D. (2011). E-learning Readiness of Thailand's Universities Comparing to the USA's Cases. International Journal of e-Education, e-Business, e-Management and e-Learning, 1(2), 126.
Shaharuddin, N. A., Rahman, A. A., Aziz, Y. A., & Kassim, S. (2018). An assessment of web technologies & e-business adoption among SMEs travel agencies in Malaysia. Journal of Academia UiTMNegeri Sembilan Vol, 6(1), 89-96.
Sin T. K., Choy C. S., Lin, B., & Cyril E. U. (2009). Internet-based ICT adoption: Evidence from Malaysian SMEs. Industrial Management & Data Systems, 109(2), 224-244.
Surbakti, F. P. S., Wang, W., Indulska, M., & Sadiq, S. (2019). Factors influencing effective use of big data: A research framework. Information & Management.
Vatanasakdakul, S., Tibben, W., & Cooper, J. (2004). What prevent B2B eCommerce adoption in developing countries?: a socio-cultural perspective. 17th Bled eCommerce Conference on eGlobal (pp. 1-15).
Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365.
Venkatesh, V., Davis, F. D., & Morris, M. G. (2007). Dead or alive?The development, trajectory and future of technology adoption research. Journal of the Association for Information Systems, 8(4), 267-286.
Venkatesh, V., Morris, M.G., Davis, F.D., and Davis, G.B. (2003).“User Acceptance of Information Technology: Toward a Unified View,” MIS Quarterly, 27, 425-478.
Venkatesh, V., & Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 115-139.
Williams, M. D., Rana, N. P., & Dwivedi, Y. K. (2015). The unified theory of acceptance and use of technology (UTAUT):
a literature review. Journal of Enterprise Information Management, 28(3), 443-488.
Yu, C. S. (2012). Factors Affecting Individuals to Adopt Mobile Banking: Empirical Evidence from the UTAUT Model. Journal of Electronic Commerce Research, 13(2), 104-121.
Zainab, B., Awais Bhatti, M., & Alshagawi, M. (2017). Factors affecting e-training adoption: an examination of perceived cost, computer self-efficacy and the technology acceptance model. Behaviour & Information Technology, 36(12), 1261-1273.
Zhu, K., & Kraemer, K. L. (2005). Post-adoption variations in usage and value of e-business by organizations: cross-country evidence from the retail industry. Information Systems Research, 16(1), 61-84.