TERTIARY STUDENT INTENTION TO USE BLOCKCHAIN-BASED ACADEMIC RECORDS: A CASE STUDY OF UBON RATCHATHANI PROVINCE, THAILAND

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Charnsak Srisawatsakul
Waransanang Boontarig

บทคัดย่อ

Blockchain-based applications possess the disruption of several industries worldwide. Researchers applied blockchain to transform the educational industry in several approaches, including blockchain-based academic records system. In Thailand, major universities in the capital have applied blockchain-based academic records systems, but it is relatively new in rural areas. Therefore, this study aims to analyze the adoption behavior toward blockchain-based academic records systems of tertiary students in Ubon Ratchathani Province, Thailand. We proposed an integrated research model based on the technology acceptance model and task-technology fit. The data were collected using online and offline questionnaires (Cronbach’s alpha > 0.84). A total of 134 randomly selected participants responded to the questionnaires and the obtained data were analyzed. The partial least square structural equation model was applied for empirically testing of the hypotheses. Every hypothesis was statistically supported. However, the behavioral intention to use blockchain-based academic records was predicted by perceived usefulness and task technology fit with 50.6 percent of the variance. Perceived ease of use was the strongest predictor of perceived usefulness. Perceived privacy risk had a negative impact on perceived usefulness. Task technology fit was confirmed in our study. Finally, the paper discussed and provided the practical implications for stakeholders related to the blockchain-based academic records system.

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References

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.

Almekhlafi, S., & Al-Shaibany, N. (2021). The literature review of blockchain adoption. Asian Journal of Research in Computer Science, 7(2), 29-50.

Arenas, R., & Fernandez, P. (2018). Creedence ledger: A permissioned blockchain for verifiable academic credentials. In 2018 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) (pp. 1-6). IEEE.

Ballarini, P., Guido, R., Mazza, T., & Prandi, D. (1995). Task-technology fit and individual performance. MIS Quarterly, 10(3), 213-236.

Batubara, F. R., Ubacht, J., & Janssen, M. (2018). Challenges of blockchain technology adoption for e-government. In The 19th Annual International Conference on Digital Government Research: Governance in the Data Age (pp. 1-9). Association for Computing Machinery.

Brown, G. M. (2006). Degrees of doubt: Legitimate, real and fake qualifications in a global market. Journal of Higher Education Policy and Management, 28(1), 71-79.

Buasuwan, P., & Jones, M. E. (2016). Asia pacific graduate education. Palgrave Macmillan.

Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Academic press.

Dam, H. N., Phan, D. T., Vu, D. T., & Nguyen, L. T. N. (2020). The determinants of customer’s intention to use international payment services by applying blockchain. Uncertain Supply Chain Management, 8(3), 439-456.

Daraghmi, E. Y., Daraghmi, Y. A., & Yuan, S. M. (2019). Unichain: A design of blockchain-based system for electronic academic records access and permissions management. Applied Sciences (Switzerland), 9(22), 4966.

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

Dijkstra, T. K., & Henseler, J. (2015). Consistent and asymptotically normal PLS estimators for linear structural equations. Computational Statistics and Data Analysis, 81, 10-23.

Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with tasktechnology fit constructs. Information & Management, 36(1), 9-21.

Dujak, D., & Sajter, D. (2019). SMART supply network. Springer, Cham.

Featherman, M. S., Miyazaki, A. D., & Sprott, D. E. (2010). Reducing online privacy risk to facilitate e-service adoption: The influence of perceived ease of use and corporate credibility. Journal of Services Marketing, 24(3), 219-229.

Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451-474.

Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research. Philosophy & Rhetoric, 10(2), 130-132.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.

George, D., & Mallery, P. (2019). IBM SPSS statistics 26 step by step: A simple guide and reference. Routledge.

Grech, A., & Camilleri, A. F. (2017). Blockchain in education. Publications Office of the European Union.

Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial Least Squares Structural Equation Modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106-121.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2018). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.

Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications.

Han, M., Li, Z., He, J., Wu, D., Xie, Y., & Baba, A. (2018). A novel blockchain-based education records verification solution. In The 19th Annual SIG Conference on Information Technology Education (pp. 178-183). Association for Computing Machinery.

Heidari, H. (2019). Evaluating the factors affecting behavioral intention in using blockchain technology capabilities as a financial instrument. Journal of Money and Economy, 13(2), 195-219.

Henseler, J., Ringle, C. M., & Sarstedt, M. (2014). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135.

Hoyle, R. H. (1995). Structural equation modeling: Concepts, issues, and applications. Sage Publications.

Isaac, O., Abdullah, Z., Ramayah, T., & Mutahar, A. M. (2017). Internet usage, user satisfaction, task-technology fit, and performance impact among public sector employees in Yemen. The International Journal of Information and Learning Technology, 34(3), 210-241.

Kamble, S., Gunasekaran, A., & Arha, H. (2019). Understanding the blockchain technology adoption in supply chains-Indian context. International Journal of Production Research, 57(7), 2009-2033.

Kamble, S. S., Gunasekaran, A., Kumar, V., Belhadi, A., & Foropon, C. (2021). A machine learning based approach for predicting blockchain adoption in supply chain. Technological Forecasting and Social Change, 163, 120465.

King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & Management, 43(6), 740-755.

Klopping, I. M., & Mckinney, E. (2004). Extending the technology acceptance model and the task-technology fit model to consumer e-consumer. Information Technology, Learning, and Performance Journal, 22(1), 35-48.

Lee, C. C., Kriscenski, J. C., & Lim, H. S. (2019). An empirical study of behavioral intention to use blockchain technology. Journal of International Business Disciplines, 14(1), 1-21.

Lee, M. C. (2008). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8(3), 130-141.

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.

Lizcano, D., Lara, J. A., White, B., & Aljawarneh, S. (2020). Blockchain-based approach to create a model of trust in open and ubiquitous higher education. Journal of Computing in Higher Education, 32(1), 109-134.

Miraz, M. H., Hasan, M. T., & Masum, M. H. (2020). Factors affecting consumers intention to use Blockchain Based Services (BBS) in the hotel industry. International Journal of Mechanical and Production Engineering Research and Development, 10(3), 8891-8902.

Mitzner, T. L., Boron, J. B., Fausset, C. B., Adams, A. E., Charness, N., Czaja, S. J., Dijkstra, K., Fisk, A. D., Rogers, W. A., & Sharit, J. (2010). Older adults talk technology: Technology usage and attitudes. Computers in Human Behavior, 26(6), 1710-1721.

Mooney, C. Z., Mooney, C. F., Mooney, C. L., Duval, R. D., & Duvall, R. (1993). Bootstrapping: A nonparametric approach to statistical inference. Sage Publications.

Nakamoto, S. (2009). Bitcoin: A peer-to-peer electronic cash system. Bitcoin. http://www.bitcoin.org

Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101-134.

Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152.

Ringle, C. M., Wende, S., & Becker, J. M. (2015). SmartPLS3. SmartPLS. http://www.smartpls.com

Sebastian, S., & Venkatesh, V. (2021). Blockchain, adoption, and financial inclusion in India: Research opportunities. International Journal of Information Management, 52, 101936.

Szabo, N. (1997). Formalizing and securing relationships on public networks. Firstmonday. https://firstmonday.org/ojs/index.php/fm/article/view/548/469

Thai Government. (2019). Personal data protection act. https://drive.google.com/open?id=1MzGNi3kdDPA0E52n8bDybeuDNklM8xJe

Tschorsch, F., & Scheuermann, B. (2016). Bitcoin and beyond: A technical survey on decentralized digital currencies. IEEE Communications Surveys and Tutorials, 18(3), 2084-2123.

Turkanović, M., Hölbl, M., Košič, K., Heričko, M., & Kamišalić, A. (2018). EduCTX: A blockchain-based higher education credit platform. IEEE Access, 6, 5112-5127.

Vinzi, V. E., Chin, W. W., Henseler, J., & Wang, H. (2010). Handbook of Partial Least Squares. Springer.

Wong, K. K. K. (2013). Partial Least Squares Structural Equation Modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1-32.

Wright, A., & De Filippi, P. (2015). Decentralized blockchain technology and the rise of lex cryptographia. SSRN. https://ssrn.com/abstract=2580664

Wu, B., & Chen, X. (2017). Continuance intention to use MOOCS: Integrating the Technology Acceptance Model (TAM) and Task Technology Fit (TTF) Model. Computers in Human Behavior, 67, 221-232.