Using the Theory of Interpersonal Behavior to Predict Information Security Policy Compliance
Title | Using the Theory of Interpersonal Behavior to Predict Information Security Policy Compliance |
Publication Type | Conference Paper |
Year of Publication | 2021 |
Authors | Chin, Won Yoon, Chua, Hui Na |
Conference Name | 2021 Eighth International Conference on eDemocracy eGovernment (ICEDEG) |
Keywords | Bibliographies, compliance, data protection, Government, government effectiveness, Information security, information security policy (ISP), information theoretic security, policy-based governance, Predictive models, pubcrawl, Regulation, security policies, theory of interpersonal behavior (TIB) |
Abstract | Employees' compliance with information security policies (ISP) which may minimize the information security threats has always been a major concern for organizations. Numerous research and theoretical models had been investigated in the related field of study to identify factors that influence ISP compliance behavior. The study presented in this paper is the first to apply the Theory of Interpersonal Behavior (TIB) for predicting ISP compliance, despite a few studies suggested its strong explanatory power. Taking on the prior results of the literature review, we adopt the TIB and aim to further the theoretical advancement in this field of study. Besides, previous studies had only focused on individuals as well as organizations in which the role of government, from the aspect of its effectiveness in enforcing data protection regulation, so far has not been tested on its influence on individuals' intention to comply with ISP. Hence, we propose an exploratory study to integrate government effectiveness with TIB to explain ISP compliance in a Malaysian context. Our results show a significant influence of government effectiveness in ISP compliance, and the TIB is a promising model as well as posing strong explanatory power in predicting ISP compliance. |
DOI | 10.1109/ICEDEG52154.2021.9530849 |
Citation Key | chin_using_2021 |