The Algorithmic Transparency Paradox How Algorithmic Control And Job Demands Drive Turnover Intention Among Digital Platform Workers

Abstract

The growing penetration of digital work platforms in non-metropolitan Indonesian cities raises critical questions about the impact of algorithmic management on worker well-being and retention. This study examines the effects of algorithmic control and job demands on turnover intention, as well as the moderating role of algorithmic transparency, among digital platform workers in Kepanjen, Malang Regency. Grounded in Job Demands-Resources (JD-R) Theory and Algorithmic Management Theory, this study employs an explanatory quantitative approach with a cross-sectional design. Data were collected from 80 active platform workers and analyzed using Moderated Regression Analysis (MRA). Results indicate that algorithmic control had no significant effect on turnover intention (β = 0.231, p = 0.163), suggesting algorithmic accommodation driven by limited employment alternatives in non-metropolitan cities (H1 not supported). Job demands significantly and positively predicted turnover intention (β = 0.579, p < 0.001), emerging as the strongest predictor (H2 supported). Algorithmic transparency did not moderate the algorithmic control–turnover intention relationship (H3 not supported). However, the job demands×algorithmic transparency interaction was significant yet counter-directional (β = +0.262, p = 0.041), revealing a transparency paradox whereby greater clarity about algorithmic demands sharpens rather than reduces exit intentions (H4 not supported directionally). The full model explained 41.5% of variance (R² = 0.415, p < 0.001). Theoretically, this study extends JD-R Theory into algorithmic work contexts in developing economies and introduces the algorithmic transparency paradox as an original contribution to Algorithmic Management Theory a condition in which greater algorithmic transparency exacerbates exit intentions when job demands are high. Practically, findings recommend that digital platform operators design transparency mechanisms coupled with genuine worker agency, including formal appeal channels and algorithmic target calibration that accounts for local infrastructure conditions. For labor regulators, results support the urgency of regulations that mandate algorithmic accountability standards and periodic audits of platform algorithmic systems in Indonesia.