Criteria Considered in a Manufacturing Reshoring Decision – A Multiple Case Study

Sequeira, Movin; Hilletofth, Per; Eriksson, David

doi:10.3233/atde200200

Cited by 2 publications

(3 citation statements)

References 31 publications

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“…Using competitive priorities is one of the ways to test the model; furthermore, it has been proposed as a relevant group of criteria for relocation decisions (Hilletofth et al 2021;Sequeira et al 2021). Other groups of criteria that could be considered are risks, resources, global dynamics and contexts (Benstead et al 2017;Sequeira et al 2020).…”

Section: Proposed Model For Generation Of Scenarios and Evaluation Of...mentioning

confidence: 99%

A hybrid fuzzy-AHP-TOPSIS model for evaluation of manufacturing relocation decisions

2022

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Manufacturing relocation decisions are complex because they involve combinations of location modes like offshoring or reshoring, and governance modes like insourcing or outsourcing. Furthermore, the uncertainty involved in the decision-making process makes it challenging to reach a right-shoring decision. This study presents a hybrid fuzzy-AHP-TOPSIS model to support generic relocation decisions. Industry experts were involved in a pairwise comparison of the competitive priorities’ decision criteria. A meta-synthesis of empirical studies is used to generate theoretical relocation scenarios. The presented hybrid model is used to rank the relocation scenarios in order to identify the most pertinent alternative. The resiliency of the solution is presented through a sensitivity analysis. The results indicate that the proposed hybrid model can simultaneously handle all the main relocation options involving governance modes. Based on the input data in this study, the competitive priorities criteria quality, time and cost are shown to have a strong impact, whereas the sustainability criterion has a weak impact on the choice of relocation option. The research presented in this paper contributes to the research field of manufacturing relocation by demonstrating the suitability of the hybrid fuzzy-AHP-TOPSIS model for relocation decisions and the resilience of the results. Furthermore, the research contributes to practice by providing managers with a generic relocation decision-support model that is capable of simultaneously handling and evaluating various relocation alternatives.

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Section: Proposed Model For Generation Of Scenarios and Evaluation Of...mentioning

confidence: 99%

A hybrid fuzzy-AHP-TOPSIS model for evaluation of manufacturing relocation decisions

2022

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“…Several decision criteria influence the reshoring decision and among them include drivers, enablers and barriers. Drivers are those decision criteria that cause a reshoring action [13]. The more common groups of drivers include manufacturing cost, product or process quality, company strategies, availability and proximity to resources, and global conditions [13].…”

Section: Reshoring Driversmentioning

confidence: 99%

“…Drivers are those decision criteria that cause a reshoring action [13]. The more common groups of drivers include manufacturing cost, product or process quality, company strategies, availability and proximity to resources, and global conditions [13]. Drivers can be categorised into different theoretical frameworks, however, not all of the drivers clearly fit into these frameworks [12].…”

Section: Reshoring Driversmentioning

confidence: 99%

Critical Operations Capabilities and Reshoring Drivers in a High-Cost Environment

Sansone¹,

Sequeira²

2021

Advances in Transdisciplinary Engineering

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Reshoring of manufacturing to high-cost environments has been gaining attention. Several drivers are usually involved in the reshoring process. This process also requires manufacturing companies to assess their capabilities in relationship to the reshoring drivers. However, the connection between the reshoring drivers and the capabilities that the manufacturing companies have in high-cost environments has received little attention. The purpose of this study is to investigate the connection between the reshoring drivers and critical capabilities, through a transdisciplinary approach. This study was conducted through a literature review. The first step included the investigation of existing literature related to operations capabilities. The second step included the investigation of existing literature related to reshoring drivers. The third step included an investigation of the link between the critical operations capabilities and the reshoring drivers derived from the literature. Both sets of critical operations capabilities and reshoring drivers were linked based on their respective definitions. The findings revealed that there is a connection between operations capabilities and reshoring drivers. This study contributes to the development of both reshoring and operations capabilities research streams, and to practice by identifying the specific operations capabilities that can drive reshoring.

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Criteria Considered in a Manufacturing Reshoring Decision – A Multiple Case Study

Cited by 2 publications

References 31 publications

A hybrid fuzzy-AHP-TOPSIS model for evaluation of manufacturing relocation decisions

A hybrid fuzzy-AHP-TOPSIS model for evaluation of manufacturing relocation decisions

Critical Operations Capabilities and Reshoring Drivers in a High-Cost Environment

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