Configuring lean supply chain performance in Indian millet distribution: A fuzzy-set qualitative comparative analysis approach

Abstract

Background: The Indian millet sector remains fragmented and inefficient, constraining effective supply chain performance. With growing recognition of millets’ role in food security and rural livelihoods, enhancing operational efficiency through lean practices has become crucial.
Objectives: This study identifies and analyses the combinations of conditions that lead to high and low lean supply chain performance (LSCP) in millet distribution across India, addressing key operational challenges in agri-food supply chains.
Method: Using fuzzy-set qualitative comparative analysis (fsQCA), the study evaluates six core conditions: technology integration, farmer coordination, market linkage (ML), inventory control, waste reduction (WR), and standardised processes. Primary data were collected from 132 respondents through structured surveys and field-level expert inputs, and configurations leading to both high and low LSCP were examined based on raw and unique coverage and consistency values.
Results: The analysis reveals multiple sufficient pathways for achieving high LSCP, particularly configurations that combine ML, inventory control, and WR. Technology integration is a sufficient but not a necessary condition, suggesting its effectiveness is context specific. Conversely, the absence of ML, WR, and inventory control consistently contributes to low LSCP.
Conclusion: The fsQCA provides a systematic approach to understanding the configurational dynamics influencing supply chain performance in millet distribution. Operational practices such as ML, inventory control, and WR exert greater influence than standardisation or technology in isolation.
Contribution: The findings offer practical insights for policymakers and supply chain actors, highlighting the need for integrated strategies that strengthen market access, storage infrastructure, and post-harvest efficiency.