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Economies of collaboration in build-to-model operations

Hedenstierna, Carl Philip T., Disney, Stephen M. ORCID: https://orcid.org/0000-0003-2505-9271, Eyers, Daniel R. ORCID: https://orcid.org/0000-0001-5499-0116, Holmstrom, Jan, Syntetos, Aris A. ORCID: https://orcid.org/0000-0003-4639-0756 and Wang, Xun ORCID: https://orcid.org/0000-0001-7800-726X 2019. Economies of collaboration in build-to-model operations. Journal of Operations Management 65 (8) , pp. 753-773. 10.1002/joom.1014

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Abstract

The direct‐from‐model and tool‐less manufacturing process of 3D printing (3DP) embodies a general‐purpose technology, facilitating capacity sharing and outsourcing. Starting from a case study of a 3DP company (Shapeways) and a new market entrant (Panalpina), we develop dynamic practices for partial outsourcing in build‐to‐model manufacturing. We propose a new outsourcing scheme, bidirectional partial outsourcing (BPO), where 3D printers share capacity by alternating between the role of outsourcer and subcontractor based on need. Coupled with order book smoothing (OBS), where orders are released gradually to production, this provides 3D printers with two distinct ways to manage demand variability. By combining demand and cost field data with an analytical model, we find that BPO improves 3DP cost efficiency and delivery performance as the number of 3DP firms in the network increases. OBS is sufficient for an established 3D printer when alternatives to in‐house manufacturing are few, or of limited capacity. Nevertheless, OBS comes at the cost of reduced responsiveness, whereas BPO shifts the cost and delivery performance frontier. Our analysis shows how BPO combined with OBS makes 3DP companies more resilient to downward movements in both demand and price levels.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Additional Information: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Publisher: Elsevier
ISSN: 0272-6963
Date of First Compliant Deposit: 4 February 2019
Date of Acceptance: 26 January 2019
Last Modified: 06 May 2023 11:37
URI: https://orca.cardiff.ac.uk/id/eprint/119184

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