Högskolan i Skövde

Background

Algorithmic management (AM) has rapidly impacted the nature of work in the economy, especially in sectors such as food delivery. While AM offers many benefits in terms of optimizing business models, it also raises many concerns, one of which is the reduction of worker autonomy, an essential psychological need as defined by Self-Determination Theory (SDT). Most existing research on AM has been conducted in a Western context, leaving a gap in understanding how AM operates in different cultural contexts, such as Vietnam.

Purpose

This study investigates the relationship between the core dimensions of algorithmic management: direction, evaluation, and discipline and the perceived job autonomy of food delivery drivers in Vietnam. By situating the research within a high power distance culture and applying SDT as a theoretical framework, the study aims to examine whether AM constrains or enables worker autonomy.

Method

A quantitative survey was conducted with 189 active food delivery drivers across Vietnam. Standardized scales were used to measure the three dimensions of algorithmic management and perceived job autonomy. The data were analyzed using reliability tests, exploratory factor analysis, Pearson correlation, and multiple regression analysis to test the hypothesized relationships.

Conclusion

Contrary to common assumptions, the findings reveal that all three AM dimensions are positively associated with perceived job autonomy. In particular, algorithmic evaluation emerged as the strongest predictor of autonomy, followed by discipline and direction. These results suggest that, in the Vietnamese context, AM may function as a supportive structure rather than a controlling force. Cultural acceptance of hierarchical systems and the perception of algorithmic processes as impartial may contribute to this outcome. The study highlights the importance of local context in shaping the effects of digital management technologies and calls for more culturally sensitive approaches to platform labor policy and design.