A Structural Equation Model of Factors Influencing New Graduates’ Privacy Data Protection Behaviors on Electronic Transactions

Main Article Content

Theerasak Ponepan
Saran Pimthong
Kanchana Pattrawiwat

Abstract

This study aimed to test and develop a structural equation model of the factors influencing personal data protection behaviors in new graduates during electronic transactions. The participants were 418 first-time jobbers living in Bangkok and Perimeter areas. Two-stage cluster sampling was applied to randomize the sample group within the administrative zoning. The theoretical foundations of current study was Protection Motivation Theory and an expanded Technology Acceptance Model. The data were collected using twelve constructs of reliable and valid questionnaires, with alpha coefficients ranging from 0.72 to 0.85. The results showed that the developed structural equation model was well consistent with the empirical data, as measured by the goodness of fit indices: χ2 = 684.99, df = 173, p-value < 0.01, RMSEA = 0.075, SRMR = 0.055, NNFI = 0.96, CFI = 0.97 and GFI = 0.90. The findings revealed that intention had a direct effect on privacy data protection behaviors, while perceived vulnerability, self-efficacy, and subjective norms had the positive indirect effects on privacy data protection behaviors respectively. As a result, before entering social work, education institutes and lecturers should have more practice classes and raise awareness about protecting personal data and digital citizenship security.

Downloads

Download data is not yet available.

Article Details

How to Cite
Ponepan, T., Pimthong, S., & Pattrawiwat, K. (2022). A Structural Equation Model of Factors Influencing New Graduates’ Privacy Data Protection Behaviors on Electronic Transactions. Rajapark Journal, 16(48), 361–382. Retrieved from https://so05.tci-thaijo.org/index.php/RJPJ/article/view/259354
Section
Research Article

References

Aghaei, S., Nematbakhsh, M. A., & Farsani, H. K. (2012). Evolution of the world wide web: From WEB 1.0 TO WEB 4.0. International Journal of Web & Semantic Technology, 3(1), 1-10.

Bandura, A. (1977). Self-Efficacy:Toward a Unifying Theory of Behavioral Change. Psychology. Review, 84, 191-215.

Bank of Thailand. (2018). Annual Report of Mobile Banking Transactions. Bank of Thailand. https://www.bot.or.th/Thai/Statistics/PaymentSystem_Reports/Q2_2560.pdf

Buchanan, T., Paine, C., Joinson, A. N., & Reips, U. D. (2007). Development of measures of online privacy concern and protection for use on the Internet. Journal of the American society for information science and technology, 58(2), 157-165.

Büchi, M., Just, N., & Latzer, M. (2017). Caring is not enough: the importance of Internet skills for online privacy protection. Information, Communication & Society, 20(8), 1261-1278.

Bulgurcu, B., Cavusoglu, H., & Benbasat, I. (2010). Information security policy compliance: an empirical study of rationality-based beliefs and information security awareness. MIS Quarterly, 523-548.

Boerman, S. C., Kruikemeier, S., & Zuiderveen Borgesius, F. J. (2021). Exploring motivations for online privacy protection behavior: Insights from panel data. Communication Research, 48(7), 953-977.

Chellappa, R. K., & Sin, R. G. (2005). Personalization versus privacy: An empirical examination of the online consumer’s dilemma. Information technology and management, 6(2), 181-202.

Chen, H. T., & Chen, W. (2015). Couldn't or wouldn't? The influence of privacy concerns and self-efficacy in privacy management on privacy protection. Cyberpsychology, Behavior, and Social Networking, 18(1), 13-19.

Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 189-211.

Comrey, A. L., & Lee, H. B. (2013). A first course in factor analysis. Psychology.

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

Diamond, P., & Vartiainen, H. (2007). Behavioral economics and its applications. Princeton.

Ernst, C. H. (2015). Privacy Protecting Behavior in Social Network Sites. In Factors driving social network site usage (pp. 57-81). Springer Gabler.

Feng, Y., & Xie, W. (2014). Teens’ concern for privacy when using social networking sites: An analysis of socialization agents and relationships with privacy-protecting behaviors. Computers in Human Behavior, 33, 153-162.

Fishbein, M. & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Addison-Wesley.

Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics.

Freiherr, A. V., & Zeiter, A. (2016). Implementing the EU general data protection regulation: a business perspective. European Data Protection Law Review, 2, 576.

Giovanis, A. N., Binioris, S., & Polychronopoulos, G. (2012). An extension of TAM model with IDT and security/privacy risk in the adoption of internet banking services in Greece. EuroMed Journal of Business, 7, 24-53

Hair, J. F. J., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. (2010). Multivariate data analysis upper saddle river: Pearson Prentice-Hall.

Ifinedo, P. (2012). Understanding information systems security policy compliance: An integration of the theory of planned behavior and the protection motivation theory. Computers & Security, 31(1), 83-95

Jöreskog, K.G., Olsson, U.H., & Wallentin, F.Y. (2016). Multivariate analysis with LISREL. Springer.

Kline, R.B. (2015). Principles and Practice of Structural Equation Modeling. The Guilford.

Lee, Y., & Larsen, K.R. (2009). Threat or coping appraisal: determinants of SMB executives’ decision to adopt anti-malware software. European Journal of Information Systems, 18(2), 177-187.

Malhotra, N.K., Kim, S.S., & Agarwal, J. (2004). Internet users' information privacy concerns (IUIPC): The construct, the scale, and a causal model. Information Systems Research, 15(4), 336-355.

Mehrabian, A. & Russell, J.A. (1974) An Approach to Environmental Psychology. MIT.

Milne, G.R., & Culnan, M.J. (2004). Strategies for reducing online privacy risks: Why consumers read (or don't read) online privacy notices. Journal of Interactive Marketing, 18(3), 15-29.

Milne, G.R., Labrecque, L.I., & Cromer, C. (2009). Toward an understanding of the online consumer's risky behavior and protection practices. Journal of Consumer Affairs, 43(3), 449-473.

Ng, B.Y., Kankanhalli, A., & Xu, Y.C. (2009). Studying users' computer security behavior: A health belief perspective. Decision Support Systems, 46(4), 815-825.

Nunnally, J.C. (1994). Psychometric Theory (3rd ed.). Tata McGraw-Hill Education.

Paine, C., Reips, U.D., Stieger, S., Joinson, A., & Buchanan, T. (2007). Internet users’ perceptions of ‘Privacy Concerns’ and ‘Privacy Actions’. International Journal of Human-Computer Studies, 65(6), 526-536.

Park, C., & Lee, S.W. (2014). A study of the user privacy protection behavior in online environment: Based on protection motivation theory. Journal of Internet Computing and Services, 15(2), 59-71.

Plotnikoff, R.C., Lippke, S., Trinh, L., Courneya, K.S., Birkett, N., & Sigal, R.J. (2010). Protection motivation theory and the prediction of physical activity among adults with type 1 or type 2 diabetes in a large population sample. British Journal of Health Psychology, 15(3), 643-661.

Rogers, R.W. (1983). Cognitive and psychological processes in fear appeals and attitude change: A revised theory of protection motivation. Social psychophysiology: A sourcebook, 153-176.

Rosenstock, I.M. (1974). Historical origins of the health belief model. Health Education Monographs, 2(4), 328-335.

Rovinelli, R.J., & Hambleton, R.K. (1976). On the use of content specialists in the assessment of criterion-referenced test item validity. Tijdschrift Voor Onderwijs Research, 2, 49-60.

Smith, A. D., & Lias, A. R. (2005). Identity theft and e-fraud as critical CRM concerns. International Journal of Enterprise Information Systems (IJEIS), 1(2), 17-36.

Smith, H.J., Milberg, S.J., & Burke, S.J. (1996). Information privacy: Measuring individuals' concerns about organizational practices. MIS Quarterly, 167-196.

The Financial Consumer Protection Center, Bank of Thailand. (2019). Fin-fraud. Bank of Thailand. https://www.1213.or.th/th/finfrauds/OnlineCrime/Pages/OnlineCrime.aspx

Venkatesh, V., & Davis, F.D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481.

Venkatesh, V., & Davis, F.D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.

Yao, M.Z., & Linz, D.G. (2008). Predicting self-protections of online privacy. Cyber Psychology & Behavior, 11(5), 615-617.

Yoon, C., Hwang, J.W., & Kim, R. (2012). Exploring factors that influence students’ behaviors in information security. Journal of Information Systems Education, 23(4), 407-416.