Description

As the use of personal mobile computing devices is growing exponentially, many organizations are implementing BYOD programs that allow employees access corporate networks using their mobile devices. Consequently, these devices can become a vehicle to transfer the risky IT behavior of individuals to enterprises. The ubiquitous, multifunctional, and highly-connected nature of mobile devices create a unique context for studying risky use of these devices. Previous IS security research has studied adoption of protective technologies. However, there is a lack of research on measuring different dimensions of risky IT behavior and how they can be influenced by using protective technologies. To address this gap, we develop a survey to identify and measure the individuals’ risky IT behaviors on mobile devices. We will then extend our research to investigate antecedents of users’ risky IT behaviors across different devices.

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Identifying and measuring the dimensions of risky IT behavior

As the use of personal mobile computing devices is growing exponentially, many organizations are implementing BYOD programs that allow employees access corporate networks using their mobile devices. Consequently, these devices can become a vehicle to transfer the risky IT behavior of individuals to enterprises. The ubiquitous, multifunctional, and highly-connected nature of mobile devices create a unique context for studying risky use of these devices. Previous IS security research has studied adoption of protective technologies. However, there is a lack of research on measuring different dimensions of risky IT behavior and how they can be influenced by using protective technologies. To address this gap, we develop a survey to identify and measure the individuals’ risky IT behaviors on mobile devices. We will then extend our research to investigate antecedents of users’ risky IT behaviors across different devices.