Worker Experience and Donor Heterogeneity: The Impact of Charitable Workers on Donors’ Blood Donation Decisions

Abstract

Problem definition: We ask whether and how a charitable organization’s front-line staff members can be effectively positioned to encourage donors to donate more (in compliance with the eligibility rules) during their in-person interactions. Academic/practical relevance: Specifically, we consider how charitable organizations can use microlevel data on worker-donor interactions to improve donation outcomes, via understanding of workers’ experiences and donors’ characteristics. Methodology: Using a unique data set at the worker-donor interaction level, we analyze the role of nurses’ experiences in driving charitable productivity and explore the downstream effects of the donation volume outcome. Results: We find that the effect of the charitable worker on charitable productivity strongly depends on the worker’s experiences that entail sharing knowledge about a donor’s donation options, rather than the worker’s experiences that are primarily focused on collecting donations. Moreover, worker experience can encourage donors that have lower self-efficacy over performing their donation to choose higher donation volumes. A worker’s experience with donors with lower self-efficacy furthermore benefits charitable productivity when interacting with those donors. Higher donations induced by an experienced worker from the previous session are correlated with higher donation volumes in the focal session if the donor returns to donate. Managerial implications: When taking the insights on staff-donor interactions into account, improved matching between workers and donors can provide economically significant benefits for the blood bank. Understanding worker experience in the staff-donor interactions and leveraging big data in staffing decisions can help charitable organizations improve their productivity simply from the personnel end. Funding: W. Lin acknowledges the support of the Marshall Fellowship at the USC Marshall School of Business. S. F. Lu acknowledges the support of the Gerald Lyles Rising Star fund at Purdue. T. Sun acknowledges the support of an Adobe Data Science Award and an iORB grant at the USC Marshall School of Business. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2023.1198 .