Choice Urgency in Finite Recommender Services: The Role of Intra-Batch Diversity and Inter-Batch Growth

Sharing economy platforms have adopted Context-Aware Finite Recommender Services (FRS) to cater to time-sensitive service demands. Presenting users with a reduced set of matched recommendations in batches, FRS is devised to induce users’ choice urgency and avoid choice delay. However, there is a dearth of research that attempts to unravel the effects of batch presentation on choice urgency. Anchored on Goal-Setting Theory, we scrutinize the role of intra-batch diversity and inter-batch growth in generating choice urgency through FRS by analyzing a massive dataset of historical order recommendation records from a leading sharing economy platform. Preliminary analysis reveals that intra-batch diversity induces choice urgency while inter-batch diversity discourages choice urgency. Findings from this study contribute to extant literature on recommender services by unraveling how the design of FRS impacts user behavior.