A new approach for estimating leagile decoupling point using data envelopment analysis

Arash Shahin, Angappa Gunasekaran, Azam Khalili, Hadi Shirouyehzad

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Purpose - This paper aims to propose a new approach for determining a decoupling point in leagile chain, based on Lean and agile criteria regarding market and customer demands and internal capabilities of the chain with the ultimate goal of fulfilling customer needs and increasing chain profit. Design/methodology/approach - In the new approach, Lean and agile criteria have been defined for assessing the effectiveness and efficiency of supply chain. The efficiency and effectiveness ratios have been calculated for Lean and agile processes using input- and output-oriented Banker, Charnes and Cooper (BCC) methods, respectively. Based on the results, inefficient and ineffective units have been addressed and the decoupling point has been determined. Findings - Findings indicate that the decoupling point can be regarded as a borderline between two strategies of Lean and agile production, and fuzzy decoupling point and lean-agile distance can provide the basis for distinguishing the two strategies. Practical implications - Determining the decoupling point has an important role in dynamic performance of a supply chain. By the proposed approach, managers can estimate the most probable area for the decoupling point. Moreover, by appropriate determination of decoupling point, an organization can increase its public responsibility by appropriate usage of its resources and responding faster to customers' requirements. Originality/value - In this study, in addition to determining a decoupling point in a supply chain with the aim of increasing productivity, the subject of leagile strategy of supply chains has been developed.

Original languageEnglish (US)
Pages (from-to)233-245
Number of pages13
JournalAssembly Automation
Volume36
Issue number3
DOIs
StatePublished - Aug 1 2016

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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