When Shared Manufacturing Meets the Digital Platform: Exploring the Operating Modes and Optimal Matching Policy

The advent of shared manufacturing, driven by digital technologies, has significantly impacted the utilization of social manufacturing resources, leading to the expansion of the sharing economy into the industrial domain. Manufacturing sharing platforms generally adopt one of three operating modes: transaction (TR), supplier‐matching (SM), and requester‐matching (RM). In TR mode, the platform compensates suppliers and resells capacity to requesters; in SM mode, the platform charges requesters for matching services; and in RM mode, it collects a commission from suppliers. This study develops an analytical model of a platform that connects requesters with suppliers exhibiting heterogeneous capacity utilization and incurring different capacity‐sharing costs under each operating mode. Driven by the interaction between the platform's commission target (supplier vs. requester) and the sequence of pricing decisions in capacity sharing, we find that the RM mode maximizes platform profit, the SM mode achieves the highest capacity utilization, and the TR mode leads to the highest gross merchandise volume (GMV). Furthermore, we establish the optimality of a matching policy that prioritizes suppliers with greater capacity slack in the supply queue and requesters with larger capacity shortages in the demand queue. Numerical analyses show that, compared to a first‐come‐first‐served (FCFS) policy, priority‐based matching substantially improves average financial performance, social welfare, and consumer surplus. Overall, this research provides valuable insights into selecting operating modes and designing matching policies for manufacturing sharing platforms, with significant implications for industry practices and social welfare.