Student cheating is a problem that has been plaguing academics globally for decades. With the infiltration of technology, this has taken on a newer more sinister form, termed e-cheating. E-cheating is electronic cheating that encompasses variety of previously known and new practices involving variety of technologies students engage in when breaching academic integrity (AI). This chapter presents the herculean task of compiling and then proposing a comprehensive factor model to pave way for better understanding of antecedents that may influence students' likelihood to e-cheat. This chapter attempts to use interpretive structural modelling (ISM) as a scientific approach towards developing such a proposed model after conducting an extensive content analysis to collate and provide a comprehensive list of factors and models already existing spread across hundreds of academic papers. This chapter is positioned as the first such attempt to provide a model of factors that is of significant benefit to stakeholders such as teachers, students, managements, government, and even employers so that they can develop an understanding of their roles in helping or hindering such behavior in the future.
Interpretive structural modelling of risk sources in a virtual organisation
