The purpose of the study is to understand employees’ proactive behaviors in Bring Your Own Device (BYOD)-enabled environments. Firms to date employ BYOD as a digital transformation strategy aimed to enhance comprehensive enterprise mobility (Bradley et al. 2016; French et al. 2014), as well as meet a growing demand from employees (Harris et al. 2012). With the wide diffusion of BYOD used in organizations, employees are able to interact with enterprise and private technologies that may be leveraged at their work (Niehaves et al. 2013). Many studies suggest that employees would increase job performance if they would choose own software, familiar devices, familiar way of working, and less limitation on own devices (Harris et al. 2012; Lee et al. 2017). These studies have extensively studied BYOD use for employees from management-led perspective, i.e. from a top-down job design process. However, it fails to capture how individuals actually perform their jobs through BYOD use. We attempt to study a bottom-up process where employees proactively reconfigure their IT landscapes that help to approach their work. More specifically, when employees realize that they are unable to complete job tasks, they would either proactively make changes to improve current circumstances or passively accept present conditions (Bateman and Crant 1993). The proactive employees attempt to modify their current work routines or the materiality of the technologies accordingly (Leonardi 2013; Schmitz et al. 2016). This process can be captured by the concept of Job Crafting. Job crafting refers to “the physical and cognitive changes individuals make in the task or relational boundaries of their work” (Wrzesniewski and Dutton 2001, p. 179). It captures employees’ proactive behaviors to reframe their jobs aimed to fulfill their idiosyncratic needs at work (Berg et al. 2013). Drawing on this theoretical lens, we want to understand how BYOD-enabled work environments allow employees to craft their work experiences in ways that are consistent with their individualized needs. In this ERF paper, we propose a conceptual model based on literature review. Moving forward, a mixed-methods research will be employed because to capture a rich understanding of this phenomenon (Venkatesh et al. 2013). First, we will employ an interpretive interview to identify its impact measures through in-depth discussions with BYOD users in an industry-leading biotechnology company. Second, we will revise our proposed conceptual model in accordance with findings from interviews and extended literature review. Then we will conduct empirical instruments to test revised model in a specific context.
|Journal||AMCIS 2018 PROCEEDINGS|