DIGITAL SKILLS AND TECHNOLOGY ACCEPTANCE INFLUENCING THE APPLICATION OF ARTIFICIAL INTELLIGENCE AMONG EMPLOYEES IN PRIVATE COMPANIES IN BANGKOK

Authors

  • Patthamaporn Samutpraput Faculty of Business Administration, Ramkhamhaeng University
  • Sompon Thungwa Faculty of Business Administration, Ramkhamhaeng University

Keywords:

Digital Skills, Technology Acceptance, Artificial Intelligence Application

Abstract

The aim of this study was to investigate the influence of digital skills and technology acceptance on the application of artificial intelligence (AI) among employees of private companies in the Bangkok metropolitan area. The sample group consisted of 385 employees who were selected using the convenience sampling method. The data was collected using a structured questionnaire and analyzed using descriptive statistics, including frequency, percentage, mean and standard deviation, and multiple regression analysis to test the hypotheses.

The research results showed that the perceived usefulness of the technology had the greatest influence on the use of AI, followed by perceived ease of use and finally the problem-solving and development skills of AI. These three variables together explained 98.5% of the variance in the use of AI in the workplace, with statistical significance at the .05 level. Therefore, private organizations should promote awareness of the benefits of AI, develop user-friendly systems and develop the digital skills of their employees to support the effective and sustainable integration of AI into work processes.

References

มณีรัศมิ์ พัฒนสมบัติสุข. (2564). การตรวจสอบคุณภาพเครื่องมือวิจัยทางการพยาบาลและสังคมศาสตร์. วารสารเครือข่ายวิทยาลัยพยาบาลและการสาธารณสุขภาคใต้, 8(2), 329-343.

Afroogh, S., Akbari, A., Malone, E., Kargar, M., & Alambeigi, H. (2024). Trust in AI: progress, challenges, and future directions. Humanities and Social Sciences Communications, 11(1), 1-30.

Babashahi, L., Barbosa, C. E., Lima, Y., Lyra, A., Salazar, H., Argôlo, M., ... & Souza, J. M. D. (2024). AI in the workplace: A systematic review of skill transformation in the industry. Administrative Sciences, 14(6), 127. https://doi.org/10.3390/admsci14060127

Calitz, A. P., Poisat, P., & Cullen, M. (2017). The future African workplace: The use of collaborative robots in manufacturing. SA Journal of Human Resource Management, 15(1), 1-11.

Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial Intelligence trends in education: a narrative overview. Procedia computer science, 136, 16-24. https://doi.org/10.1016/j.procs.2018.08.233

Cochran, W. G. (1977). Sampling techniques (3rd ed.). John Wiley & Sons.

Cronbach, L. J. (1970). Essentials of psychological test (5th ed.). Harper Collins.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 13(3), 319-340.

DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information systems research, 3(1), 60-95.

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(4), 9-30.

Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... & Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International journal of information management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002

Goodfellow, I., Bengio, Y., Courville, A., & Bengio, Y. (2016). Deep learning (Vol. 1, No. 2). MIT press.

Ikhsan, R. B., Fernando, Y., Prabowo, H., Gui, A., & Kuncoro, E. A. (2025). An empirical study on the use of artificial intelligence in the banking sector of Indonesia by extending the TAM model and the moderating effect of perceived trust. Digital Business, 5(1), 100103. https://doi.org/10.1016/j.digbus.2024.100103

Lee, C. P. (2024). Design, development, and deployment of context-adaptive AI systems for enhanced user adoption. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1-5). Honolulu, HI.

Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-16). Honolulu, HI.

Marangunić, N., & Granić, A. (2015). Technology acceptance model: a literature review from 1986 to 2013. Universal access in the information society, 14, 81-95. https://doi.org/10.1007/s10209-014-0348-1

Mikeladze, T., Meijer, P. C., & Verhoeff, R. P. (2024). A comprehensive exploration of artificial intelligence competence frameworks for educators: A critical review. European Journal of Education, 59(3), e12663. https://doi.org/10.1111/ejed.12663

Misra, S. K., Sharma, S. K., Gupta, S., & Das, S. (2023). A framework to overcome challenges to the adoption of artificial intelligence in Indian Government Organizations. Technological Forecasting and Social Change, 194, 122721. https://doi.org/10.1016/j.techfore.2023.122721

Russell, S., & Norvig, P. (2020). Artificial intelligence: A modern approach (4th ed.). Pearson.

Shrestha, Y. R., Krishna, V., & von Krogh, G. (2021). Augmenting organizational decision-making with deep learning algorithms: Principles, promises, and challenges. Journal of Business Research, 123, 588-603. https://doi.org/10.1016/j.jbusres.2020.09.068

Wang, Y., Kung, L., Wang, W. Y. C., & Cegielski, C. G. (2018). An integrated big data analytics-enabled transformation model: Application to health care. Information & Management, 55(1), 64-79. https://doi.org/10.1016/j.im.2017.04.001

Zhang, C., & Lu, Y. (2021). Study on artificial intelligence: The state of the art and future prospects. Journal of Industrial Information Integration, 23, 100224. https://doi.org/10.1016/j.jii.2021.100224

Downloads

Published

2025-06-30

How to Cite

Samutpraput, P. ., & Thungwa, S. . (2025). DIGITAL SKILLS AND TECHNOLOGY ACCEPTANCE INFLUENCING THE APPLICATION OF ARTIFICIAL INTELLIGENCE AMONG EMPLOYEES IN PRIVATE COMPANIES IN BANGKOK . Journal of Value Chain Management and Business Strategy, 4(2), 106–119. retrieved from https://so08.tci-thaijo.org/index.php/VCMBS/article/view/4926

Issue

Section

Research Articles