Purchase or rent? Optimal pricing for 3D printing capacity sharing platforms

Luoyi Sun, Guowei Hua, T. C.E. Cheng, Ruud H. Teunter, Jingxin Dong, Yixiao Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)


Online sharing platforms have attracted considerable research and management attention across a number of industries, including travel, real estate, and cloud computing. They also have great potential for the 3D printing (3DP) industry, offering users the choice between owning or renting 3DP capacity. For matching supply and demand, capacity pricing is crucial. In this paper we consider two fundamental questions concerning pricing: (i) What is the optimal pricing strategy for a 3DP capacity sharing platform? (ii) How do usage level and printer heterogeneity affect consumers’ choice between in-house printing (owning) and outsourcing (renting)? Using queuing analysis, we derive the structural properties of the solutions to the problems. Furthermore, we conduct numerical studies using real-world data to generate managerial insights from the analytical findings. A key finding is that governments should focus on encouraging technological progress to lower the printers’ prices in order to improve the well-being of the industry. When considering two types of printers, we find that it is more beneficial for the platform if the high capacity printer dominates the market, as the platform then retains the prominent role in “redistributing” the 3DP capacity.

Original languageEnglish
JournalEuropean Journal of Operational Research
Publication statusAccepted/In press - 2022


  • 3D printing platform
  • Capacity sharing
  • Manufacturing
  • Pricing strategy

ASJC Scopus subject areas

  • General Computer Science
  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management
  • Industrial and Manufacturing Engineering


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