| 1. |
- Hilletofth, Per, et al.
(författare)
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Fuzzy-logic-based support tools for initial screening of manufacturing reshoring decisions
- 2021
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Ingår i: Industrial management & data systems. - : Emerald Group Publishing Limited. - 0263-5577 .- 1758-5783. ; 121:5, s. 965-992
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: This paper investigates the suitability of fuzzy-logic-based support tools for initial screening of manufacturing reshoring decisions.Design/methodology/approach: Two fuzzy-logic-based support tools are developed together with experts from a Swedish manufacturing firm. The first uses a complete rule base and the second a reduced rule base. Sixteen inference settings are used in both of the support tools.Findings: The findings show that fuzzy-logic-based support tools are suitable for initial screening of manufacturing reshoring decisions. The developed support tools are capable of suggesting whether a reshoring decision should be further evaluated or not, based on six primary competitiveness criteria. In contrast to existing literature this research shows that it does not matter whether a complete or reduced rule base is used when it comes to accuracy. The developed support tools perform similarly with no statistically significant differences. However, since the interpretability is much higher when a reduced rule base is used and it require fewer resources to develop, the second tool is more preferable for initial screening purposes.Research limitations/implications: The developed support tools are implemented at a primary-criteria level and to make them more applicable, they should also include the sub-criteria level. The support tools should also be expanded to not only consider competitiveness criteria, but also other criteria related to availability of resources and strategic orientation of the firm. This requires further research with regard to multi-stage architecture and automatic generation of fuzzy rules in the manufacturing reshoring domain.Practical implications: The support tools help managers to invest their scarce time on the most promising reshoring projects and to make timely and resilient decisions by taking a holistic perspective on competitiveness. Practitioners are advised to choose the type of support tool based on the available data.Originality/value: There is a general lack of decision support tools in the manufacturing reshoring domain. This paper addresses the gap by developing fuzzy-logic-based support tools for initial screening of manufacturing reshoring decisions.
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| 2. |
- Sansone, Cinzia, et al.
(författare)
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Critical Operations Capabilities and Reshoring Drivers in a High-Cost Environment
- 2021
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Ingår i: Transdisciplinary Engineering for Resilience: Responding to System Disruptions. - Amsterdam : IOS Press. - 9781643682082 - 9781643682099 ; , s. 263-271
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Konferensbidrag (refereegranskat)abstract
- 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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| 3. |
- Sequeira, Movin, et al.
(författare)
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AHP-based support tools for initial screening of manufacturing reshoring decisions
- 2021
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Ingår i: Journal of Global Operations and Strategic Sourcing. - : Emerald Group Publishing Limited. - 2398-5364 .- 2398-5372. ; 14:3, s. 502-527
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Tidskriftsartikel (refereegranskat)abstract
- PurposeThe existing literature expresses a strong need to develop tools that support the manufacturing reshoring decision-making process. This paper aims to examine the suitability of analytical hierarchy process (AHP)-based tools for initial screening of manufacturing reshoring decisions.Design/methodology/approachTwo AHP-based tools for the initial screening of manufacturing reshoring decisions are developed. The first tool is based on traditional AHP, while the second is based on fuzzy-AHP. Six high-level and holistic reshoring criteria based on competitive priorities were identified through a literature review. Next, a panel of experts from a Swedish manufacturing company was involved in the overall comparison of the criteria. Based on this comparison, priority weights of the criteria were obtained through a pairwise analysis. Subsequently, the priority weights were used in a weighted-sum manner to evaluate 20 reshoring scenarios. Afterwards, the outputs from the traditional AHP and fuzzy-AHP tools were compared to the opinions of the experts. Finally, a sensitivity analysis was performed to evaluate the stability of the developed decision support tools.FindingsThe research demonstrates that AHP-based support tools are suitable for the initial screening of manufacturing reshoring decisions. With regard to the presented set of criteria and reshoring scenarios, both traditional AHP and fuzzy-AHP are shown to be consistent with the experts' decisions. Moreover, fuzzy-AHP is shown to be marginally more reliable than traditional AHP. According to the sensitivity analysis, the order of importance of the six criteria is stable for high values of weights of cost and quality criteria.Research limitations/implicationsThe limitation of the developed AHP-based tools is that they currently only include a limited number of high-level decision criteria. Therefore, future research should focus on adding low-level criteria to the tools using a multi-level architecture. The current research contributes to the body of literature on the manufacturing reshoring decision-making process by addressing decision-making issues in general and by demonstrating the suitability of two decision support tools applied to the manufacturing reshoring field in particular.Practical implicationsThis research provides practitioners with two decision support tools for the initial screening of manufacturing reshoring decisions, which will help managers optimize their time and resources on the most promising reshoring alternatives. Given the complex nature of reshoring decisions, the results from the fuzzy-AHP are shown to be slightly closer to those of the experts than traditional AHP for initial screening of manufacturing relocation decisions.Originality/valueThis paper describes two decision support tools that can be applied for the initial screening of manufacturing reshoring decisions while considering six high-level and holistic criteria. Both support tools are applied to evaluate 20 identical manufacturing reshoring scenarios, allowing a comparison of their output. The sensitivity analysis demonstrates the relative importance of the reshoring criteria.
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| 4. |
- Sequeira, Movin
(författare)
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Multi-stage fuzzy-logic model for evaluation of reshoring decisions
- 2021
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Ingår i: Transdisciplinary Engineering for Resilience: Responding to System Disruptions. - Amsterdam : IOS Press. - 9781643682082 - 9781643682099 ; , s. 312-321
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Konferensbidrag (refereegranskat)abstract
- Reshoring decisions are complex due to multiple groups of criteria that have an impact on the decision involved. In order to support this manual decision-making process, more advanced tools need to be developed. The purpose of this paper is to explore a multi-stage fuzzy-logic model to support the reshoring decision-making process through a transdisciplinary approach. Three relevant stages pertaining to reshoring decisions were identified: production resources, production capabilities, and competitive priorities. For each stage, factor loading values were used to create fuzzy rules. The model provides a decision recommendation based on a set of input reshoring scenarios. The research contributes to the reshoring literature providing a multi-stage fuzzy-logic model that simultaneously handles different groups of criteria, and to practitioners by contemplating different key competencies within a company during the reshoring decision process.
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| 5. |
- Sequeira, Movin, et al.
(författare)
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Relocation for production innovation capability : a bibliometric analysis
- 2021
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Ingår i: Proceedings of the 28th Innovation and Product Development Management Conference.
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Konferensbidrag (refereegranskat)abstract
- Due to increasing competition, many manufacturing companies have relocated their production to low-cost countries, through offshoring. Recently, some manufacturing companies have moved their production back to their home country. Innovation has played an important role in allowing companies to add value to their productions and influencing relocation decisions. However, the literature does not provide a clear snapshot that explains how relocations are related to innovation. Therefore, the purpose of this paper is to explore the relationship between innovation and relocation. The paper adopts a quantitative review and a bibliometric analysis with data extracted from Scopus. Next, a content analysis is carried out on a subset of articles. The findings indicate that there is certain consensus on the positive relationship between innovation and offshoring, while limited knowledge on the relationship between innovation and reshoring. Furthermore, the relationship between innovation and relocation can be understood through the theory of dynamic capabilities, which is the boundary for both these topics. This research contributes to the debate on relocations and production innovation.
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