Improving Driver Engagement in Delivery and Rideshare Services

Abstract

Due to driver autonomy, delivery and rideshare platforms in the sharing economy (SE) face uncertainty in service capacity planning. This study investigates how the alignment between the technical and social subsystems within the overall socio-technical system of SE platforms influences driver engagement. Drawing on socio-technical systems theory, we conceptualize SE platforms as systems defined by the organizational design constructs of centralization, formalization, and complexity. Using a discrete choice experiment with 100 experienced SE drivers, we examine how platform design attributes affect drivers' utility and engagement probability. Our findings reveal that drivers value flexibility, preferring platforms that offer direct task allocation and single-task acceptance features. Contrary to expectations, drivers generally favor base pay–oriented remuneration over promotion-oriented structures. Individual driver characteristics such as SE income dependency and multi-apping tendencies significantly influence platform preferences. The findings contribute to logistics research by empirically establishing the relationship between platform structure and driver utility and by extending the application of organizational design theory to digital labor platforms. Our results provide insights into how firms can reduce capacity uncertainty by engaging SE drivers within their networks, highlighting the importance of aligning platform design with the preferences of a heterogeneous driver population.