Purpose: Agriculture logistics networks are vulnerable to several disruptions. Disruptions impeding agriculture produce logistical flows often result into distorted food supplies, excessive logistics lead times and higher food prices. The strategies for enabling agriculture produce logistics resilience (APLR) are becoming crucial for managing logistical disturbances. The purpose of this study is to devise strategic implementation framework for APLR managing disruptions.Design/methodology/approach: The factors contributing APLR are identified utilizing literature review and discussions with various stakeholders of agro-logistics sectors. The integrated N-WINGS-ISM approach is developed to explore causal interrelationship among APLR factors. Geographical Indication (GI) tagged Nashik grapes from Nashik, Maharashtra, India have been specifically chosen to demonstrate application of the developed model to devise the strategic framework for managing disruptions.Findings: The study identifies 16 APLR factors imparting logistics resilience. N-WINGS provide categorical clustering of APLR into – Priority, Contingency, Autonomous and Long-term factors. ISM model structures the hierarchy of the implementation strategies highlighting three levels – Depth, Transition and Surface level factors. N-WINGS-ISM combined results are utilized to devise APLR implementation strategies.Originality/value: The study argues that the need for developing proactive resilience systems incorporating resilience culture. Moving beyond technology integration, developing “Human-Technology-Systems” ecosystem is the primary imperative for systemic resilience.

The purpose of this work is to identify and analyze the key important barriers to uptake the compressed biogas (CBG) plants in India for enhancing their role as a sustainable energy source. Initially, the barriers are identified from the past academic literature using literature review process and are then validated through the fuzzy Delphi method with expert opinions. The finalized barriers were then categorized into cause effect relationship and ranked for strategic decision making by policy makers, investors, and industry practitioners. We employed the weighted influence non-linear gauge systems (WINGS) method to find hierarchical relationships and determine the priority of these barriers. The findings provide a strategic roadmap for policymakers, investors, and industry stakeholders to enhance CBG adoption through supply chain improvements, financial incentives, public awareness campaigns, and regulatory streamlining. By systematically identifying, linking, and ranking interrelated barriers, the study develops a structured and data-driven framework that provides actionable strategies for accelerating the adoption of compressed biogas (CBG) plants in India.