Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Fuzzy-logic-based support tools for initial screening of manufacturing reshoring decisions
Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management. Jönköping University, School of Engineering, JTH, Industrial Product Development, Production and Design.ORCID iD: 0000-0002-8305-4412
Jönköping University, School of Engineering, JTH, Industrial Product Development, Production and Design. Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.ORCID iD: 0000-0002-1318-1598
Department of Supply Chain Management, College of Business Administration, University of Tennessee, Knoxville, TN, United States.
2021 (English)In: Industrial management & data systems, ISSN 0263-5577, E-ISSN 1758-5783, Vol. 121, no 5, p. 965-992Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Emerald Group Publishing Limited, 2021. Vol. 121, no 5, p. 965-992
Keywords [en]
Manufacturing reshoring, decision support, initial screening, Fuzzy logic
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:hj:diva-51612DOI: 10.1108/IMDS-05-2020-0290ISI: 000634615100001Scopus ID: 2-s2.0-85103209254Local ID: HOA;intsam;1520774OAI: oai:DiVA.org:hj-51612DiVA, id: diva2:1520774
Available from: 2021-01-21 Created: 2021-01-21 Last updated: 2022-02-10Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Hilletofth, PerSequeira, Movin

Search in DiVA

By author/editor
Hilletofth, PerSequeira, Movin
By organisation
JTH, Supply Chain and Operations ManagementJTH, Industrial Product Development, Production and Design
In the same journal
Industrial management & data systems
Production Engineering, Human Work Science and Ergonomics

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 185 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf