Work

Make-or-buy strategies in a multi-stage manufacturing process and the role of learning effect in relocation decisions

Year: 2023

Type: article

Abstract: Current global problems like the pandemic or the war in Ukraine have raised new aspects of make-or-buy decisions. Many companies consider shortening their supply chains or even reshore production. We are modelling the cost-related consequences of possible strategies, jointly considering the effect of productivity knowledge and interdependencies of consecutive production stages in the manufacturing process, assuming varying learning rates based on task complexity. The dynamic optimization problem enables us to investigate the role of learning effect in both outsourcing and insourcing (reshoring) decisions. In general, we find that firms should stick to or insource production processes where learning potential is high; however, keeping activities with low learning potential but higher interdependencies may also be beneficial as they can contribute to increase productivity at other stages. Optimal decisions might dynamically change from one period to the other. Reasons include that it might be reasonable to keep a production stage in-house until its cross-stage learning effect sufficiently contributes to decrease production costs at other stages. Accordingly, if a firm partly re-establishes its in-house manufacturing, the rest of the production stages may also be brought back over time thanks to the accumulated productivity knowledge. This may provide further implications for industrial policies that foster reshoring: pursuing activities with considerable learning potential or possible interdependencies with other corporate functions would trigger further relocation decisions and may result in upgrading in the value chain. We show numerical examples to illustrate the rationale behind different strategies, highlighting the key role of cross-stage learning.

Source: Computers & Industrial Engineering

DOI: 10.1016/j.cie.2023.109259

Authors: Dóra Longauer, Zsuzsanna Hauck, Tamás Vasvári

Institution: University of Pecs

Language: English

Topic: Outsourcing and Supply Chain Management

Subfield: Management Information Systems

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $3,310