Job Satisfaction and Turnover Intentions during Technology Transition: The Role of User Involvement, Core Self-Evaluations, and Computer Self-Efficacy

Job Satisfaction and Turnover Intentions during Technology Transition: The Role of User Involvement, Core Self-Evaluations, and Computer Self-Efficacy

Richard D. Johnson (Department of Management, University at Albany, Albany, NY, USA) and Regina Yanson (Francis Marion University, Florence, SC, USA)
Copyright: © 2015 |Pages: 14
DOI: 10.4018/IRMJ.2015100103
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Abstract

Using data from 52 employees, this study investigated the relations among user involvement, core self-evaluations, computer self-efficacy, employee stress, job satisfaction, and intention to leave the organization during the implementation of a new barcode scanning system. The results revealed that core self-evaluations and user involvement were positively related to computer self-efficacy. In addition, core self-evaluations was negatively related to job stress, but user involvement was not. The results further showed that job stress was negatively related to job satisfaction. Finally, job stress and job satisfaction were each negatively related to intentions to leave the organization. Implications for theory and managers are discussed.
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Introduction

The implementation of a new technology represents a fundamental change to organizational structures, workflows, and employee relationships (Mikkelsen, Øgaard, Lindøe, & Olsen, 2002; Zuboff, 1988). The basic structures of jobs can be changed and employees must adapt to new roles and learn new routines (Maier, Laumer, Eckhardt, & Weitzel, 2013; Liang, Saraf, Hu, & Xue, 2007). This can increase role conflict and affect how employees perceive their jobs. The ambiguity associated with a technology change can increase stress, reduce job satisfaction, and even lead to turnover (Schaubroeck, Cotton, & Jennings, 1989; Ayyagari, Grover, & Purvis, 2011).

However, only limited information systems (IS) research has focused on these outcomes, and few of these studies have theoretically tied such outcomes to factors related to the implementation itself. For example, Maier et al. (2013) found that user attitudes were related to job satisfaction and turnover intentions. In addition, Morris and Venkatesh (2010) found that the implementation of an ERP affected job satisfaction. Finally, Korunka and Vitouch (1999) found that the implementation of new technology was associated with increased job stress. But, more research is needed to systematically explore how the implementation of new technology can affect outcomes “such as employee productivity, satisfaction and turnover.” (Brown, Massey, Montoya-Weiss, & Burkman, 2002, p. 293). In addition, there is value in drawing on fuller theoretical models of job satisfaction.

One such approach is to focus on job stress. Morris and Venkatesh (2010) argue that researchers need to better understand the role of stress during the implementation of new technology. Not everyone will respond to the stress of a technology and organizational change in the same way. For example, research has found that individuals with higher self-efficacy exhibited less stress during organizational change than individuals with lower self-efficacy (Jimmieson, Terry, & Callan, 2004). Research has also found that personality traits such as core self-evaluations (Best, Stapleton, & Downey, 2005; Alarcon, Eschleman, & Bowling, 2009) were related to job stress and burnout. Finally, research has found that involving employees in the change process can reduce stress (Bond & Bunce, 2001).

Thus, the goal of this study was to investigate the relations between core self-evaluations, user involvement, computer self-efficacy (CSE), job stress, and the employee outcomes of job satisfaction and turnover intention. Our work is informed by the work of Schaubroeck et al. (1989) who developed a model of role and job stress and its impacts on job satisfaction and turnover. Previous meta-analytic work (Podsakoff, LePine & LePine, 2007) has found that this model is effective in explaining job stress, its antecedents, and relations with job satisfaction and turnover. But, our model differs from these previous studies in that it focuses on factors of particular importance in the implementation of a new technology (e.g. user involvement, user personality, and CSE). A stronger understanding of these relations can help organizations develop more effective interventions during technology implementation to reduce stress and better utilize organizational human resources.

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