3D Printer Rentals: Technical Service Design and Pricing for Customers of Varying Expertise

Problem definition: Businesses with short-term production needs can rent equipment (e.g., 3D printer) from a manufacturer or distributor (hereafter, OEM) or use a manufacturing-services firm (e.g., print farm). Those who rent may vary in their expertise and therefore in their cost of attaining quality. Those who use a print farm benefit from the expertise of print-farm technicians. An OEM that offers rentals has an incentive to provide technical service to improve customer expertise so as to make renting attractive. Methodology/results: We analytically study the rental-and-technical-service-design problem for an OEM, accounting for the heterogeneity in customer expertise and the choice of utility-maximizing customers to rent or to use a print farm. We consider both a setting where the OEM provides the same menu of offerings to all customers (population-based strategy) and a setting where it customizes the offerings to each customer (user-based strategy). We also study an extension where the print farm actively competes and one where the OEM owns the print farm. We characterize the optimal offering for the OEM, the resulting profit, the value of customization (difference in profits under user-based and population-based strategies), and the impact of expertise distribution on these terms. Our problem is related to vertical quality differentiation but leads to several contrasting insights, including that offering a single quality level can be optimal, that the deadweight loss can be lower for a more heterogeneous customer population, and that upward (instead of the classic downward) distortion occurs. Managerial implications: We provide guidance on when technical service should be bundled with the rental and when it should be offered as an optional upgrade. Our findings highlight when rental markets with higher heterogeneity are more or less attractive. Conventional wisdom suggests that higher customer heterogeneity should increase the value of customization. We prove that this wisdom is not always correct.

Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2024.1563.