Assessing Carbon Footprint Reduction Strategies for Last-Mile Delivery in Emerging Economies: An INTERPRETIVE STRUCTURAL MODELLING (ISM) Approach

Abstract

In a world of urbanization and rapid e-commerce growth, we have increased the carbon footprint of last-mile delivery. Particularly in emerging economies, where a lack of regulatory frameworks and infrastructure deprivation play challenging roles. This study mainly addresses the need to show and execute effective carbon footprint reduction strategies in this context. To identify and analyze the interdependencies among the key strategies, most of which are given by experts for sustainable urban logistics, Interpretive Structural Modelling (ISM) has been utilized. The purpose of this study is to identify ten core strategies and to rank and evaluate them by using Interpretive Structural Modelling (ISM) to build a hierarchical model that visualizes their relationships. After analyzing, a clear hierarchical structure has been shown. Such as Public-Private Partnerships (PPPs) and the integration of Green Supply Chain Management (GSCM), which were found to be the primary drivers. These strategies create the essential policy and collaborative environment necessary for other strategies to succeed. Other strategies that can be called linkage strategies are load optimization, collaborative logistics, and parcel lockers. These strategies mainly serve a dual role by enabling advanced solutions and giving foundational support. Some solutions, including fleet electrification, micro-mobility, and urban micro-hubs, emerged as dependent strategies, as their successful implementation relies heavily on the lower-level enablers. To conclude the study, policymakers and industry experts should categorize and prioritize efficiencies and strengthen the foundational structure before investing in any high-tech solutions. The purpose of this research study is to show the insights into different perspectives on how important green logistics are in developing nations, and for this, the contribution of various environmental, economic, and operational factors is important.