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Leagile supply chain: design drivers and business performance implications

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  • Masih Fadaki
  • Shams Rahman
  • Caroline Chan

Abstract

In the context of a dynamic and hypercompetitive business environment, effective supply chain design helps organisations to align resources for improved flow of products and services and satisfy customers’ diverse needs. Scholars have proposed several mutually exclusive supply chain designs such as efficient versus responsive, and lean versus agile. Quantitative testing has revealed that supply chain designs of many firms do not match with what was conceptually expected. To address this mismatch, in this study, a new approach to supply chain leagility is introduced and the impact of uncertainty as the key design driver of supply chains on leagility is investigated. The partial least squares (PLS) was employed to analyse data collected from 299 Australian firms by administering a structured questionnaire. Results indicate that higher performance is achievable on minimising the deviation from a balanced supply chain in which aspects of both leanness and agility are equally embedded. Further, the level of uncertainty directly and positively affects the Deviation from Leagility (DFL) index.

Suggested Citation

  • Masih Fadaki & Shams Rahman & Caroline Chan, 2020. "Leagile supply chain: design drivers and business performance implications," International Journal of Production Research, Taylor & Francis Journals, vol. 58(18), pages 5601-5623, September.
    • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:18:p:5601-5623
    DOI: 10.1080/00207543.2019.1693660
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    Cited by:

    1. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    2. Oliveira-Dias, Diéssica de & Maqueira-Marin, Juan Manuel & Moyano-Fuentes, José & Carvalho, Helena, 2023. "Implications of using Industry 4.0 base technologies for lean and agile supply chains and performance," International Journal of Production Economics, Elsevier, vol. 262(C).
    3. Maria Concetta Carissimi & Lorenzo Bruno Prataviera & Alessandro Creazza & Marco Melacini & Fabrizio Dallari, 2023. "Blurred lines: the timeline of supply chain resilience strategies in the grocery industry in the time of Covid-19," Operations Management Research, Springer, vol. 16(1), pages 80-98, March.
    4. Efpraxia D. Zamani & Conn Smyth & Samrat Gupta & Denis Dennehy, 2023. "Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review," Annals of Operations Research, Springer, vol. 327(2), pages 605-632, August.

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