Examining the performance of on-demand platforms through three lenses: worker, store, and customer

Abstract

Online service platforms have gained traction over the past decade. These platforms connect waiting time-sensitive customers to independent service providers. Among the plethora of online and on-demand service platforms, the online grocery delivery market in particular, has shown rapid growth and is projected to reach US$786.6bn in 2024. Despite its growing popularity, online service-based platforms pose operational challenges, such as the mismatch between demand for, and supply of available services. To add to the complexity, most on-demand platforms operate on a gig-contractor model, where the workers can self-schedule, thereby increasing the uncertainty of workers’ availability. As more customers are getting accustomed to the idea of ordering groceries online, the demand for online delivery services has increased, and so has the competition among the service providers. Furthermore, often there exists a cost-quality trade-off when performing decisions regarding whether to own company-managed dark stores’ to have more control over picking times and service quality, or to pick from retail stores alongside other customers, at no additional cost, but at the expense of slower turnaround times and uncertain service quality resulting from in-store stockouts. Lastly, there is the issue of customers switching to other stores, or to other online grocery platforms owing to lucrative promotions & offers, and low switching costs. All these factors make on-demand grocery retail platforms a growing, yet challenging business, which poses interesting research questions. The purpose of my research is to examine how inherent behaviors of gig workers, and external factors specific to the grocery store, and the end-consumer, could affect the performance and survival of the online grocery platforms. In the first chapter, I discuss factors affecting the productivity and service quality of gig workers who can self-schedule, and how such information could be used to better allocate tasks. For the second chapter, I examine how online grocery platforms could improve order picking efficiency from retail stores by scheduling tasks based on store traffic, and urgency of the order delivery. Lastly, in the third chapter, I explore the effect of online purchase value, service quality, and customers’ online shopping experience on the store-switching and platform-exit (churn) probability of online shoppers.