Explaining normative behavior in information technology use

The purpose of this paper is to identify a model that provides explanations for normative behavior in information technology (IT) use, and to test the model across two different types of normative behavior (i.e. green information technology (GIT), and digital piracy (DP)).

The proposed model is based on the norm activation model (NAM) and the unified theory of acceptance and use of technology model (UTAUT). A total of 374 and 360 usable responses were obtained for GIT and DP, respectively. The authors use the SEM technique in order to test the proposed model on the two sub-samples.

Findings from the proposed model show that DP users’ personal norm (PN) negatively impacts behavioral intention and actual behavior. These findings indicate that users of IT who indulge in DP understand that use of pirated software may not be a socially approved behavior but they still indulge in it because their PNs are not aligned with social expectations. GIT users’ PN positively impacts behavioral intention and actual behavior, and the relationship is stronger for behavioral intention than for actual behavior.

The sample consists of college students and working professionals based in India who may be savvy with respect to internet use. Future work may evaluate whether the pattern of results that the authors report for normative behavior does hold across other types of normative behavior.

These findings hint at a gap between the moral compass and the final “action” taken by DP users. What managers need to do is to create awareness among their customers about the implementation of DP/GIT and help users engage in normative behavior.

This research contributes to the literature by integrating the UTAUT and the NAM to explain normative behavior of IT use. The authors propose and test a model that identifies cognitive as well as social-psychological motivations to explain normative behavior in IT use, which have been sparingly studied in extant literature, and provides a holistic understanding of the phenomenon. As such, this research contributes to the existing knowledge of understanding of normative IT behavior.