Technology Acceptance Model : The Evidence of NodeMCU’s Mushroom House Control System in Thailand

Authors

  • พงศธร ตันตระบัณฑิตย์ คณะการบัญชีและการจัดการ
  • Manirath Wongsim Mahasarakham Business School, Mahasarakham University
  • Olarik Surinta Faculty of Informatics, Mahasarakham University

Keywords:

Technology Acceptance Model, Internet of Things, Mushroom House, Smart Farm

Abstract

The purpose of this study is to (1) To develop the NodeMCU’s mushroom house control system that be able to control by both automatic system and manual system (2) To generate the application (or related online tool) that be able to adjust the suitable humidity and appropriate temperature for each growth stages of mushroom in the mushroom house (3) To determine the perception of the NodeMCU’s users by applying TAM model. “Song Pee Nong” mushroom farm was chosen as a case study to implement the NodeMCU’s system in this study. After installed the NodeMCU’s mushroom house control system and developed the mobile application for the users, the system was able to sustain the most appropriate temperature and humidity in mushroom house by set up the system automatically or by control manually from the users via mobile application. This study also applied technology acceptance model (TAM) to explain the famer’s intention to use the NodeMCU’s mushroom house control system in the future.

References

Aldas-Manzano, J., Ruiz-Mafe, C., & Sanz-Blas, S. (2009). Exploring individual personality factors as drivers of M-shopping acceptance. Industrial Management & Data Systems, 109, 739–757. doi: 10.1108/02635570910968018.

Ashton, K. (2009, June 22). That 'Internet of Things' Thing. RFID Journal. Retrieved from https://www.rfidjournal.com/articles/view?4986

Babin, N. (2017). Internet of Things or connected objects. The Internet of Things. Retrieved from https://www.linkedin.com/pulse/internet-things-connected-objects-nicolas-babin-l-i-o-n-/

Behrend, T. S., Wiebe, E. N., London, J. E., & Johnson, E. C. (2011, March–April). Cloud computing adoption and usage in community colleges. Behaviour & Information Technology, 30(2), 231–240.

Bosnjak, M., Obermeier, D. & Tuten, T.L. (2006). Predicting and explaining the propensity to bid in online auction: a comparison of two action-theoretical models. Journal of Consumer Behavior, 5, 102-116.

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

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.

Department of Agricultural Extension. (2019). Agricultural Statistics Information, Ministry of Agriculture and Cooperatives, Thailand. Retrieved from https://www.doae.go.th/doae/km_list.php?Cat=SXpUVVF0TGdXb0Y1SlRFOVNBdnhqUT09

Ha, I., Yoon, Y., & Choi, M. (2007). Determinants of adoption of mobile games under mobile broadband wireless access environment. Information & Management, 44(3), 276–286.

Jung, Y., Perez-Mira, B., & Wiley-Patton, S. (2009). Consumer adoption of mobile TV: Examining psychological flow and media content. Computers in Human Behavior, 25(1), 123–129.

Kuo, Y. F., & Yen, S. N. (2009). Towards an understanding of the behavioral intention to use 3G mobile value-added services. Computers in Human Behavior, 25(1), 103–110.

Mallat, N., Rossi, M., Tuunainen, V. K., & Oorni, A. (2009). The impact of use context on mobile services acceptance: The case of mobile ticketing. Information & Management, 46(3), 190–195.

Mariampolski, H. (2001). Qualitative market research: A comprehensive guide. Thousand Oaks, CA: Sage Publications.

Rouse, M. & Bernstein, C. (2019, June). Smart Farming. TechTarget. Retrieved from https://internetofthingsagenda.techtarget.com/definition/smart-farming

Rouse, M., Rosencrance, L., Shea, S. & Wigmore, I. (2019, March). Internet of Things (IoT). TechTarget. Retrieved from https://internetofthingsagenda.techtarget.com/definition/Internet-of-Things-IoT

Shih, Y. & Fan, S. (2013). Adoption of instant messaging by travel agency workers in Taiwan: Integrating technology readiness with the theory of planned behavior. International Journal of Business and Information, 8(1), 120-136.

Shin, D. H. (2009). Understanding user acceptance of DMB in South Korea using the modified technology acceptance model. International Journal of Human–Computer Interaction, 25, 173–198.

Venkatesh, V., & Bala, H. (2008, May). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315.

Zhou, T. & Lu, Y. (2011). The effects of personality on user acceptance of mobile commerce. International Journal of Human-Computer Interaction, 27(6), 545-561.

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Published

21-03-2020

How to Cite

ตันตระบัณฑิตย์ พ., Wongsim, M. ., & Surinta, O. . (2020). Technology Acceptance Model : The Evidence of NodeMCU’s Mushroom House Control System in Thailand. Journal of Accountancy and Management, 12(1), 42–54. Retrieved from https://so02.tci-thaijo.org/index.php/mbs/article/view/240475

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Section

Research Articles