THE ROLE OF ATTITUDE TOWARDS INTERNET OF THINGS (IOT) IN RELATION TO TECHNOLOGY ACCEPTANCE MODEL IN THAILAND
DOI:
https://doi.org/10.20319/pijss.2019.52.7792Keywords:
Perceived Ease of Use, Perceived Usefulness, Attitude towards Internet of Things, Continuance Intention to Use, Technology Acceptance ModelAbstract
The objectives of this study is to investigate the Technology Acceptance Model (TAM) which derives from following factors: Perceived Ease of Use, Perceived Usefulness, Attitude towards Internet of Things, and Continuance intention to use who use products from Internet of Things in Thailand. The researchers applied the quantitative method to 272 users who bought products from Internet of Things and analyzed in term of frequency, mean and Structural Equation Model (SEM) analysis by AMOS. The research findings indicated that Perceived Ease of Use, Perceived Usefulness, Attitude towards Internet of Things had significantly positive influence to Continuance intention to use (p < .05).References
Agarwal, R., Karahanna, E., 2000. Time flies when you're having fun: cognitive absorption and beliefs about information technology usage. MIS Q. 665–694. https://doi.org/10.2307/3250951
Ahmad, S. N., & Laroche, M. (2016). Analyzing electronic word of mouth: A social commerce construct. International Journal of Information Management: 1-12.
Ajzen, I. (1991), “The theory of planned behavior”, Organizational Behaviors and Human Decision Processes, Vol. 50 No. 2, pp. 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
Ajzen, I. and Fishbein, M. (1980), Understanding Attitudes and Predicting Social Behavior, Prentice Hall, Englewood Cliffs, NJ.
Bandyopadhyay, S., Balamuralidhar, P., & Pal, A. (2013). Interoperation among IoT standards. Journal of ICT Standardization, 1, 253-270. https://doi.org/10.13052/jicts2245-800X.12a9
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370. https://doi.org/10.2307/3250921
Carniels, M. C. J., Lenaerts, H. K. L., & Gelderman, C. J. (2014). Explaining the internet usage of SMEs, The impact of market orientation, behavioral norms, motivation and technology acceptance. Internet Research, 25(3): 358-377. https://doi.org/10.1108/IntR-12-2013-0266
Cheng, S-I., Chen, S-C., & Yen, D. C. (2015). Continuance intention of E-portfolio system: A confirmatory and multigroup invariance analysis of technology acceptance model. Computer Standards & Interfaces, 42: 17-23. https://doi.org/10.1016/j.csi.2015.03.002
Chen, S-C., Yen, D-C., & Peng, S-C. (2018). Assessing the impact of determinants in e-magazines acceptance: An empirical study. Computer Standards & Interfaces, 57:49-58. https://doi.org/10.1016/j.csi.2017.11.004
Choi, J., Lee, H. J., Sajjad, F., & Lee, H. (2014). The influence of national culture on the attitude towards mobile recommender systems. Technological Forecasting & Social Change, 86 :65-79. https://doi.org/10.1016/j.techfore.2013.08.012
Chui, M., Markus, L., & Roger, R. (2010). The Internet of things. McKinsey Quarterly, 2: 1-9.
Davis, F.D., 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quart. 13: 319-340. https://doi.org/10.2307/249008
Fayad, R. & Paper, D. (2015). The Technology Acceptance Model E-Commerce Extension: A Conceptual Framework. Procedia Economics and Finance, 26:1000-1006. https://doi.org/10.1016/S2212-5671(15)00922-3
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and Behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Giusto, D., Iera, A., Morabito, G. and Atzori, L. (Eds) (2010), The Internet of Things, ISBN: 978-1-4419-1673-0, Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1674-7
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. Upper Saddle River, NJ: Prentice-Hall. https://doi.org/10.1016/j.jmva.2009.12.014
Hsu, C-L. & Lin, J. C-C. (2016). An empirical examination of consumer adoption of Internet of Things service: Network externalities and concern for information privacy perspectives. Computer in Human Behavior, 62: 516-527. https://doi.org/10.1016/j.chb.2016.04.023
Hsu, C. L., & Lu, H. P. (2004). Why do people play on-line games? an extended TAM with social influences and flow experience. Information & Management, 41(7), 853-868. https://doi.org/10.1016/j.im.2003.08.014
Kim, J. (2015). An extended technology acceptance model in behavioral intention towards hotel tablet apps with moderating effects of gender and age. International Journal of Contemporary Hospitably, 28 (8): 1535-1553. https://doi.org/10.1108/IJCHM-06-2015-0289
Kim, Y. G., & Woo, E. (2016). Consumer acceptance of a quick response (QR) code for the food traceability system: Application of an extended technology acceptance model (TAM). Food Research International, 85:266-272. https://doi.org/10.1016/j.foodres.2016.05.002
Lai, V. S., Li, H. (2005). Technology acceptance model for internet banking: an invariance analysis. Information & Management, 42: 373-386. https://doi.org/10.1016/j.im.2004.01.007
Limayem, M., Hirt, S., & Cheung, C. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 31(4), 705–737. https://doi.org/10.2307/25148817
Lin, C. A., & Kim, T. (2016). Predicting user response to sponsored advertising on social media via the technology acceptance model. Computer in Human Behavior, 64:710-718. https://doi.org/10.1016/j.chb.2016.07.027
Lin, C. P., & Bhattacherjee, A. (2008). Elucidating individual intention to use interactive information technologies: the role of network externalities. International Journal of Electronic Commerce, 13: 85-108. https://doi.org/10.2753/JEC1086-4415130103
Lin, K-Y. & Lu, H-P. (2011). Why people use social networking sites: An empirical study integrating network externalities and motivation theory. Computers in Human Behavior, 27: 1152-1161. https://doi.org/10.1016/j.chb.2010.12.009
Narakorn, P., & Seesupan, T. (2018). The influence of social network site identity, active control, flow, trust in members and customer loyalty of Facebooks users. Silpakorn University Journal, 38 (2), 121-145.
Narakorn, P., & Seesupan, T. (2018). Trust in Seller Catalyst Social Commerce Construct to Continuance Intention. Journal of Business Administration, 41 (159), 24-44.
Narakorn, P., & Seesupan, T. (2019). Social Commerce Constructs and Buyer-Seller Relationship Quality. Modern Applied Science, 13 (2), 169-176. https://doi.org/10.5539/mas.v13n2p169
Nunnally, J. (1978). Psychometric Theory, McGraw-Hill, New York, NY.
Muk, A. & Chung, C. (2015). Applying the technology acceptance model in a two-country study of SMS advertising. Journal of Business Research, 68:1-6. https://doi.org/10.1016/j.jbusres.2014.06.001
Oliver, R. (1999) .Whence consumer loyalty?. Journal of marketing, 63:33-44. https://doi.org/10.2307/1252099
Read, W., Robertson, N., & McQuilken, L. (2011). A novel romance: The Technology Acceptance Model with emotional attachment. Australasian Marketing Journal, 19: 223-229. https://doi.org/10.1016/j.ausmj.2011.07.004
Rese, A., Schreiber, S., & Baier, D. (2014). Technology acceptance modeling of augmented reality at the point of scale: Can surveys be replaced by an analysis of online reviews?. Journal of Retailing and Consumer Service, 21:869-876. https://doi.org/10.1016/j.jretconser.2014.02.011
Sharifzadeh, M. S., Damalas, C. A., Abdollahzadeh, G., & Ahmadi-Gorgi, H. (2017). Predicting adoption of biological control among Iranian rice farmers: An application of the extended technology acceptance model (TAM2). Crop Protection, 96: 88-96. https://doi.org/10.1016/j.cropro.2017.01.014
Shen, C.C., Chiou, J.S., 2010. The impact of perceived ease of use on internet service adoption: the moderating effects of temporal distance and perceived risk. Compute. Hum. Behav. 26 (1), 42–50. https://doi.org/10.1016/j.chb.2009.07.003
Wallance, L. G., & Sheetz, S. D. (2014). The adoption of software measures: A technology acceptance model (TAM) perspective. Information & Management, 51: 249-259 https://doi.org/10.1016/j.im.2013.12.003
Yoo, H-Y. (2016). User Acceptance of Mobile Library Applications in Academic Libraries: An Application of the Technology Acceptance Model. The Journal of Academic Librarianship, 42: 687-693. https://doi.org/10.1016/j.acalib.2016.08.003
Zancul, E. d. S., Takey, M. S., Barquet, A. P. B., Kuwabara, L. H., Miguel, P. A. C., & Rozenfeld, H. (2015). Business process support for IoT based Products-Service System (PSS). Business Process Management Journal, 22 (2), 2016. https://doi.org/10.1108/BPMJ-05-2015-0078
Zhou, T. (2015). The effect of network externality on mobile social network site continuance. Program electronic library and information systems, 49 (3):289-304. https://doi.org/10.1108/PROG-10-2014-0078
Zhou, T. & Lu, Y. (2011). Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience. Computer in Human Behavior, 27: 883-889. https://doi.org/10.1016/j.chb.2010.11.013
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