Transfer Decisions in Services: A Multimethod Approach

In many service encounters front-line workers (often referred to as gatekeepers) have the discretion to attempt to resolve a customer request, or to transfer the customer to an expert service provider. We study the gatekeeper’s transfer decision using an integrated approach that consists of a field study, an analytical model, and a behavioral experiment. Drawing on a proprietary dataset of interactions between the customers and call center agents of a mid-size US-based bank, we formulate and solve an analytical model of the gatekeeper’s transfer response to different incentive schemes and to different congestion loads and then test several model predictions experimentally. Our experiments show that human behavior matches the predictions qualitatively, but not always in magnitude. Specifically, transfer rates are disproportionately low in the presence of monetary penalties for transferring, even after controlling for the economic (dis)incentive to transfer, suggesting an overreaction to transfer cost. In contrast, the transfer response to varying congestion shows no systematic bias. Taken together, these results advance our understanding of cognitive capabilities and rationality limits on human server behavior in queueing systems.