Hierarchical modeling of retailers' issues for lean dairy supply chain: a data-driven decision-making approach

Upendra Kumar, Bishal Dey Sarkar and Sandeep Jagtap

International Journal of Productivity and Performance Management, 2026, vol. 75, issue 11, 267-294

Abstract: PurposeThis research identifies key retailer-related issues causing inefficiencies in the Indian Dairy Supply Chain (DSC) and develops a hierarchical model aimed at guiding decision-makers towards a leaner and more productive DSC. The study addresses a significant gap in the lean DSC literature, focusing on the challenges retailers face in emerging markets such as India.Design/methodology/approachThe study employs a mixed-method approach, beginning with a comprehensive literature review and expert consultations to identify 15 critical retailer issues. A structured questionnaire was administered to industry professionals and academics, resulting in 290 valid responses. Exploratory Factor Analysis (EFA) was applied to uncover underlying constructs, followed by Total Interpretive Structural Modeling (TISM) to map relationships among these issues. The model was statistically validated using a one-sample t-test, and MICMAC analysis classified issues by their driving power and dependence.FindingsThe study categorizes the identified retailer issues into four constructs: strategic, tactical, operational, and performance. Strategic issues (lack of top management commitment, insufficient financial support, and lack of assured long-term contracts) emerged as the most powerful drivers, underscoring their fundamental role in addressing other retailers' concerns. Tactical issues, including inadequate cold storage and ICT infrastructure, significantly influenced operational efficiency. Performance issues, such as retailer dissatisfaction, were the most dependent and were strongly influenced by strategic and tactical factors.Research limitations/implicationsThe study specifically focuses on the Indian DSC, limiting generalizability to other geographical or sectoral contexts. Additionally, the findings depend heavily on expert input, which may introduce subjectivity. Future research could validate these findings through broader empirical studies and comparative analysis in other regions or industries to enhance generalizability and robustness.Practical implicationsThe hierarchical model developed in this research provides clear prioritization guidelines for decision-makers and policymakers in the dairy industry. Strategic issues, notably management commitment and financial support, must be addressed first to resolve tactical and operational inefficiencies. Policymakers can use these insights to formulate targeted policies, invest strategically, and develop training and infrastructure programs that significantly enhance retailer performance and supply chain efficiency.Originality/valueThis study contributes to the lean DSC literature by systematically identifying and modeling retailer-level barriers and by integrating EFA, TISM, and MICMAC into a data-driven hierarchical framework. The findings extend existing knowledge on supply chain performance management by demonstrating how strategic-level factors shape tactical and operational outcomes at the retail node of dairy supply chains. The developed model provides a structured decision-support mechanism to improve operational performance, reduce waste, and strengthen performance management practices within the DSC.

Keywords: Dairy Supply Chain (DSC); Lean; Exploratory Factor Analysis (EFA); Total Interpretative Structural Modeling (TISM); Data driven decision making (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eme:ijppmp:ijppm-07-2025-0733

DOI: 10.1108/IJPPM-07-2025-0733

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