Sharing but caring: Location based mobile applications (LBMA) and privacy protection motivation

Abstract

Location based mobile applications (LBMA) are developing rapidly with the increasing adoption of smartphones. These applications advantage userś location to provide products or services based on information obtained from their smart devices. However, implementation and execution of these services may raise userś privacy concerns related to sensitive information being handled. In this context, this paper examines the factors that motivate users and lead them to protect their privacy while using LBMA. It also considers potential benefits they could encounter and thus enable their privacy trade. The model proposed is based on Protection Motivation Theory (PMT) and tested through a variance-based Structural Equations Modelling approach. Data were obtained through an online survey with 820 participants. Findings reveal that perceived severity, perceived vulnerability and self-efficacy exert a positive effect on the intention of privacy protection, which in turn is found to be positively related to the behavior of protecting privacy.