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Examining personal, organizational and technological factors on job performance: A study on law enforcement officers
Arun Joshi1, Srinivasan Sekar2, Saini Das3
1International School of Business and Media, Pune, Maharashtra, India.
Abstract:
Despite substantial investments in information and communication technologies (ICTs), governments worldwide continue to face challenges in their effective implementation across public service departments. This study examines the personal, organizational, and technological determinants of Crime and Criminal Tracking Network and Systems (CCTNS) usage among police officers and its impact on job performance. Using quantitative survey data collected from 447 police officers across seven districts in Rajasthan, India, the research integrates the Big Five personality traits, the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Task-Technology Fit (TTF) model, employing structural equation modeling and importance-performance analysis. Attitude is modeled as a integrative evaluative construct that mediates the effects of personality and expectancy beliefs on behavioral intention and actual use within an extended UTAUT framework. Results indicate that personality, attitude, and training significantly influence the actual ICTs use. Although performance expectancy and training had no significant direct effects on behavioral intention and actual use in a mandatory-use context, these relationships were fully mediated by attitude and behavioral intention, respectively. The actual ICTs use positively influences job performance, particularly when task-technology fit is high. This article makes three novel contributions. First, this paper studies a relatively unexplored form of ICT, i.e., CCTNS. Second, the unique characteristics and nature of the sample - police personnel. Third, this research observes a sharp deviation from the prior research in the form of a set of counterintuitive findings. This article advances technology adoption literature by integrating three theoretical models and relevant variables, demonstrating superior explanatory power. It offers actionable insights for technology providers, policymakers, training officials, police departments, and governments to enhance technology adoption and job performance by addressing personal, organizational, and technological factors.
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