Behavioral intention in social networking sites ethical dilemmas: an extended model based on Theory of Planned Behavior

• Main Authors: Jafarkarimi, H., Saadatdoost, R., Sim, A. T. H., Hee, J. M.
• Format: Article
• Published: Elsevier Ltd 2016
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/72134/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-84964308177&doi=10.1016%2fj.chb.2016.04.024&partnerID=40&md5=895c46e994b60042d47d05863ced2323

The expanding use of social networking sites (SNSs) and their flexible functionalities allow individuals to use these sites in unexpected and unethical ways. SNS users face ethical dilemmas each day and they need to decide how to behave in these cases. The aim of this study was to identify the influential factors that have an impact on individuals' ethical decision-making and propose a model of the factors that are significant in the ethical decision-making process in the SNS context. This study employed the Theory of Planned Behavior (TPB) and included personal normative beliefs, moral intensity, perceived threat of legal punishment to the main constructs of TPB namely attitude, subjective norms, perceived behavioral control to predict the behavioral intention using a scenario based questionnaire. The moderating effects of several factors, including age, gender, level of income, ego strength, locus of control and religion, were investigated for the probable effect on the proposed model. Derived from a designed procedure, several scenarios were constructed, of which four were selected to be embedded in the survey instrument. With 441 returned questionnaires in hand, the collected data were analyzed using the partial least squares-structural equation modeling technique. The results showed attitude to be the most influential factor, followed by subjective norms, perceived behavioral control, personal normative beliefs, and moral intensity. Level of education, age, and scenario also showed a significant effect on the relation between predictors and behavioral intention.