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Analysis of enablers for the implementation of leagile supply chain management using an integrated fuzzy QFD approach

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  • A. Noorul Haq

    (National Institute of Technology)

  • Varma Boddu

    (National Institute of Technology)

Abstract

Global competition and market uncertainty has forced organizations to become more responsive and efficient which thereby drives interest in the concept of supply chain leanness and agility. The leagile supply chain management paradigm includes lean and agile principles and has attained greater importance in the current scenario. The objective of this work is to identify the most appropriate leagile enablers for implementation by companies based on the characteristics of the related market by linking competitive bases, leagile attributes and leagile enablers. In this paper, a quality function deployment (QFD) approach integrated with analytical hierarchy process and technique for order preference by similarity to ideal solution is proposed to enhance the leagility of the supply chain. Fuzzy logic is used to deal with linguistic judgments expressing relationships and the correlations required by QFD. The presentation of a case study from the Indian food processing industry illustrates the proposed methodology. This approach will help the management to exploit the most influential enablers in achieving the desired degree of leagility.

Suggested Citation

  • A. Noorul Haq & Varma Boddu, 2017. "Analysis of enablers for the implementation of leagile supply chain management using an integrated fuzzy QFD approach," Journal of Intelligent Manufacturing, Springer, vol. 28(1), pages 1-12, January.
    • Handle: RePEc:spr:joinma:v:28:y:2017:i:1:d:10.1007_s10845-014-0957-9
    DOI: 10.1007/s10845-014-0957-9
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    1. Costa, Luana Bonome Message & Godinho Filho, Moacir & Fredendall, Lawrence D. & Devós Ganga, Gilberto Miller, 2021. "Lean six sigma in the food industry: Construct development and measurement validation," International Journal of Production Economics, Elsevier, vol. 231(C).
    2. Germán González Rodríguez & Jose M. Gonzalez-Cava & Juan Albino Méndez Pérez, 2020. "An intelligent decision support system for production planning based on machine learning," Journal of Intelligent Manufacturing, Springer, vol. 31(5), pages 1257-1273, June.
    3. Yongbo Li & Ali Diabat & Chung-Cheng Lu, 2020. "Leagile supplier selection in Chinese textile industries: a DEMATEL approach," Annals of Operations Research, Springer, vol. 287(1), pages 303-322, April.
    4. Asadabadi, Mehdi Rajabi, 2017. "A customer based supplier selection process that combines quality function deployment, the analytic network process and a Markov chain," European Journal of Operational Research, Elsevier, vol. 263(3), pages 1049-1062.
    5. Seyed Mahmoud Zanjirchi & Mina Rezaeian Abrishami & Negar Jalilian, 2019. "Four decades of fuzzy sets theory in operations management: application of life-cycle, bibliometrics and content analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1289-1309, June.
    6. Habib Zare Ahmadabadi & Fatemeh Zamzam & Farahnaz Rahmani Meybodi & Dalia Streimikiene & Abbas Mardani, 2018. "Developent of a New Sesame Product using QFD and DOE methods: A Case Study of Sesame Product in Yazd," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 14(1), pages 27-44.
    7. Mathiyazhagan, Kaliyan & Agarwal, Vernika & Appolloni, Andrea & Saikouk, Tarik & Gnanavelbabu, A, 2021. "Integrating lean and agile practices for achieving global sustainability goals in Indian manufacturing industries," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    8. Ghazi M. Magableh & Mahmoud Z. Mistarihi, 2023. "Global Supply Chain Nervousness (GSCN)," Sustainability, MDPI, vol. 15(16), pages 1-24, August.

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