The Acceptance of Technology and Online Consumer Behavior are Related to Purchasing Decisions Made Through Store Chatbots on Applications

Main Article Content

Siri Cledonyor
Pongsagorn Sothanon
Weerawat Thantikarn
Tosopon Sukhata
Thitatakan Aungsuchawalkit

Abstract

The objectives of this research were to examine technology acceptance factors related to consumers’ purchase decision-making through merchant chatbots on applications, and to investigate online consumer behavior factors related to purchase decision-making through merchant chatbots on applications. This study employed a quantitative research approach. The sample consisted of individuals residing or working in Bangkok who had experience purchasing products via merchant chatbots on applications. The samples were selected using purposive sampling, and the sample size was determined using W.G. Cochran's formula, resulting in a total of 400 respondents. The research instrument was a questionnaire. Data were analyzed using descriptive statistics, including percentages, means, and standard deviations, as well as inferential statistics, including one-way ANOVA and multiple linear regression. The results revealed that: (1) overall technology acceptance related to purchase decision-making through merchant chatbots on applications was at a high level. Perceived ease of use and perceived risk were significantly related to purchase decision-making through merchant chatbots on applications at the 0.05 level of statistical significance. (2) Overall, online consumer behavior related to purchase decision-making through merchant chatbots on applications was also at a high level. Online emotional factors and continuity factors were significantly related to purchase decision-making through merchant chatbots on applications at the 0.05 level of statistical significance.

Article Details

How to Cite
Cledonyor, S., Sothanon, P., Thantikarn, W., Sukhata, T., & Aungsuchawalkit, T. (2026). The Acceptance of Technology and Online Consumer Behavior are Related to Purchasing Decisions Made Through Store Chatbots on Applications. Rajapark Journal, 20(66), 164–178. retrieved from https://so05.tci-thaijo.org/index.php/RJPJ/article/view/286312
Section
Research Article

References

AIGAN. (2021, 20 December). What is a chatbot? An indispensable business assistant in the next normal era. https://aigencorp.com/what-is-chatbot/

Aggelidis, V. P., & Chatzoglou, P. D. (2009). Using a modified technology acceptance model in hospitals. International Journal of Medical Informatics, 78(2), 115-126. https://doi.org/10.1016/j.ijmedinf.2008.06.006

Camarero, C., Antón, C., & Rodríguez-Pinto, J. (2014). Technological and ethical antecedents of e-book piracy and price acceptance: Evidence from the Spanish case. Journal of the Electronic Library, 32(4), 542-566. https://doi.org/10.1108/EL-11-2012-0149

Chan, G., Cheung, C. M. K., Kwong, T., Limayem, M., & Zhu, L. (2003). Online consumer behavior: A review and agenda for future research. In BLED 2003 Proceedings (pp. 194-218). Association for Information Systems. https://aisel.aisnet.org/bled2003/43/

The National Electronics and Computer Technology Center (NECTEC). (2019, June 27). Chatbot…at the right place, at the right time. https://www.nectec.or.th/news/news-pr-news/chatbot-righttime.html

Davis, F. D. (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319-340. https://doi.org/10.2307/249008

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. http://dx.doi.org/10.1287/mnsc.35.8.982

Hassan, A. M., Kunz, M. B., Pearson, A. W., & Mohamed, F. A. (2006). Conceptualization and measurement of perceived risk in online shopping. Marketing Management Journal, 16(1), 138-147. https://www.mmaglobal.org/volume-16-2016

Kotler, P., & Keller, K. L. (2016). Marketing management (15th ed.). Pearson Education.

Kwek, C. L., Tan, H. P., & Lau, T. C. (2010). Investigating the shopping orientations on online purchase intention in the e-commerce environment a Malaysian study. Journal of Internet Banking and Commerce, 15(2), 1-22.

Park, E., & Kim, K. J. (2014). An integrated adoption model of mobile cloud services: Exploration of key determinants and extension of technology acceptance model. Journals of Telematics and Informatics, 31(3), 376-385. https://doi.org/10.1016/j.tele.2013.11.008

Richard, M.-O., & Chebat, J.-C. (2016). Modeling online consumer behavior: Preeminence of emotions and moderating influences of need for cognition and optimal stimulation level. Journal of Business Research, 69(2), 541–553. https://doi.org/10.1016/j.jbusres.2015.05.010

Rogers, E. M. (1983). Diffusion of Innovation (3rd ed.). The Free Press.

Schiffman, L. G., & Kanuk, L. L. (2010). Consumer behavior (10th ed.). Pearson Education.

Solomon, M. R. (2016). Consumer behavior: Buying, having, and being (12th ed.). Pearson.

Tulanon, S. (2019). Accepting technology affects decision to buy online products of elderly[Master’s thesis, Naresuan University]. http://nuir.lib.nu.ac.th/dspace/handle/123456789/1538

Krungsri Plearn Plearn. (2024). Upgrade Your Business with Chatbots. https://www.krungsri.com/th/plearn-plearn/chatbot-for-business

Wuttipappinyo, N. (2021). A study of factors affecting chatbot user’s satisfaction[Master’s thesis, Mahidol University]. https://archive.cm.mahidol.ac.th/handle/123456789/4123