ALGORITHMIC MANAGEMENT CONTROL ON FINANCIAL WELL-BEING: MODERATION OF FINANCIAL SELF-EFFICACY
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Abstract
This study analyzes the influence of algorithmic management control on the financial well-being of gig workers in Indonesia and examines the moderating role of financial self-efficacy. With the increasing number of gig workers in Indonesia facing unstable incomes, job uncertainty, and algorithm-driven control pressures that can affect their financial well-being. This study uses an explanatory quantitative approach, with primary data collected through a questionnaire survey of 62 gig workers in Indonesia, comprising online motorcycle taxi drivers and marketplace sellers. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS 4. The study's results show that algorithmic management control negatively affects the financial well-being of gig workers. However, financial self-efficacy has not been shown to moderate such relationships. These findings confirm that the pressure of algorithmic control can worsen the financial well-being of gig workers. In contrast, financial self-confidence is not yet strong enough to mitigate its influence. Theoretically, this study expands the literature on management accounting and financial behavior in the context of the gig economy. In practice, the research results can serve as input for digital platforms, the Ministry of Manpower, and financial institutions to design work systems and financial interventions that are more favorable to gig workers.Keywords:
Algorithmic Management Control Financial Well-Being Financial Self-Efficacy Gig Economy Management AccountingReferences
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