Employee Control over Personal Data and Acceptance of Workforce Analytics: A Systematic Review of Privacy, Transparency and Organisational Trust

Abstract

Background: Workforce analytics, electronic performance monitoring and algorithmic management increasingly transform employee data into managerial information. Their technical capabilities have advanced faster than evidence on the conditions under which employees regard such systems as legitimate. This systematic review synthesised empirical research on how employee control over personal data, monitoring intrusiveness, transparency, procedural fairness and organisational trust shape acceptance of workforce analytics and related surveillance technologies.

Methods: Structured searches were conducted to 29 July 2026 across PubMed-indexed records and publisher-hosted databases and indexes, supplemented by backward citation chaining from major reviews. Eligible studies were peer-reviewed empirical investigations involving employees or workers exposed to electronic monitoring, people analytics, workforce tracking or algorithmic management and reporting at least one outcome concerning privacy, control, transparency, fairness, trust or acceptance. Eighteen studies were included and appraised using design-appropriate Mixed Methods Appraisal Tool principles.

Results: Across laboratory experiments, factorial-vignette studies, field surveys and mixed-method designs, three findings were consistent. First, invasiveness and collection of data beyond task-relevant purposes were associated with stronger privacy concerns and lower acceptance. Second, meaningful control-participation in monitoring design, access to collected data, relevance restrictions and opportunities for voice-was more reliably associated with legitimacy than disclosure alone. Third, privacy invasion and perceived unfairness frequently operated through organisational trust, with lower trust linked to stress, resistance, lower job attractiveness and turnover intentions. Transparency had conditional effects: it supported fairness or psychological contracts when surveillance scope was limited, but could be ineffective when extensive monitoring itself was viewed as unacceptable.

Conclusions: Employee acceptance of workforce analytics is best understood as a relational governance problem rather than a simple technology-adoption problem. Systems are more likely to be accepted when organisations minimise data scope, make purposes specific, provide employee access and voice, constrain secondary uses, and retain accountable human oversight. These findings support scenario-based experimental work that manipulates employee data control and transparency while treating organisational trust as a central mediating mechanism.