What is it about?

This article examines the association between green logistics operations, social, environmental and economic indicators of SAARC (South Asian Association for Regional Cooperation) countries. The research used GMM (Generalized Method of Moments) and FGLS (Feasible Generalized Least Squares) two methods to tackle the problems of heterogeneity, serial correlation and heteroskedasticity.

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Why is it important?

The findings show that fossil fuel consumption is at the heart of logistics operations; the more fossil fuel and non-green energy resources that are used, the more negative effects on society and environmental sustainability result from this. A lower quality of transport-related infrastructure and logistics services is negatively correlated with fossil fuel usage, carbon emissions, health expenditure, greenhouse gas emissions and political instability of SAARC countries. Conversely, efficient customs procedures and greater information sharing among supply chain partners increase trade opportunities and also improve environmental sustainability in terms of minimum carbon emissions due to the shorter waiting and queue times involved. Further, the application of green energy resources and green practices can mitigate negative effects on social and environmental sustainability due to better logistics operations while improving financial performance in terms of higher GDP per capita, trade openness and greater export opportunities around the globe. As there is very limited research using green practices relationship with macro-level indicators in current literature, this research will assist both practitioners and policymakers to understand the roles of green supply chain and green logistics in enhancing environmental sustainability, social improvement and economic growth for a better future.

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This page is a summary of: Environmental, Social and Economic Growth Indicators Spur Logistics Performance: From the Perspective of South Asian Association for Regional Cooperation Countries, Journal of Cleaner Production, January 2019, Elsevier,
DOI: 10.1016/j.jclepro.2018.12.322.
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