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Challenges to competitive manufacturing in high-cost environments: checklist and insights from Swedish manufacturing firms

Author

Listed:
  • Nina Edh Mirzaei

    (Jönköping University)

  • Per Hilletofth

    (Jönköping University
    University of Gävle)

  • Rudrajeet Pal

    (Swedish School of Textiles, University of Borås)

Abstract

Research on competitive manufacturing (CM) in high-cost environments has earlier indicated that firms struggle to remain competitive and that manufacturing operations often have been offshored to low-cost environments. The purpose of this research is to explore and create a compounded view of challenges related to both internal and external environments of firms when operating in high-cost environments. This issue has been investigated through a qualitative case study involving five manufacturing firms in Sweden. This research has empirically derived the challenges associated with sustaining CM in high-cost environments and developed a prescriptive checklist. Seven main categories of challenges have been identified, ranging from a micro level related to product characteristics and employee involvement, to a macro level related to supply chain collaborations and industry systems. This research contributes to the existing literature on CM in high-cost locations by explaining and detailing what constitutes challenges in this kind of environment.

Suggested Citation

  • Nina Edh Mirzaei & Per Hilletofth & Rudrajeet Pal, 2021. "Challenges to competitive manufacturing in high-cost environments: checklist and insights from Swedish manufacturing firms," Operations Management Research, Springer, vol. 14(3), pages 272-292, December.
    • Handle: RePEc:spr:opmare:v:14:y:2021:i:3:d:10.1007_s12063-021-00193-0
    DOI: 10.1007/s12063-021-00193-0
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    References listed on IDEAS

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    Cited by:

    1. Federica Costa & Matthias Thürer & Alberto Portioli-Staudacher, 2023. "Heterogeneous worker multi-functionality and efficiency in dual resource constrained manufacturing lines: an assessment by simulation," Operations Management Research, Springer, vol. 16(3), pages 1476-1489, September.
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    3. Chenxiang Zhang & Fengrui Zhang & Ningyan Chen & Huizhen Long, 2022. "RETRACTED ARTICLE: Application of artificial intelligence technology in financial data inspection and manufacturing bond default prediction in small and medium-sized enterprises (SMEs)," Operations Management Research, Springer, vol. 15(3), pages 941-952, December.

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