Abstract

Logistics plays a major part in any country's or region's economic success. Logistics performance depends upon the trade between other countries and urbanization. Urbanization has major role in logistics performance. However, being a significant energy user, logistics has negative consequences. As the logistics performance increases, carbon emissions increase as well because of more transportation and urbanization. Logistics performance has positive effects related to trade openness which reduces carbon emissions. As a result, it is necessary to understand function of logistics from both economic and environmental standpoint. Logistics performance is affected by urbanization of any region. The dataset for this research is made up of 10 Asian nations with 550 observations from 2010 to 2018 and is based on the theoretical underpinnings of impact of population affluence and technology (IPAT) and stochastic impacts by regression on population affluence and technology (STIRPAT). After applying various tests like cointegration analysis, unit root test, cross-sectional dependence now long & short-term relation of variables is studied by Cross-sectionally augmented autoregressive distributed lag (CS-ARDL). As indicated by the discoveries, the logistic performance index (LPI) is basically effective on economic growth and carbon emissions, particularly when related to IPAT and STIRPAT. The findings are reviewed, and policy implications are offered, which say that current logistical infrastructure should be transformed to more environmentally friendly operations. Finally, the limits are acknowledged, as well as future research possibilities that should be pursued.

Highlights

  • Logistics is management of acquisition, storage of materials, transportation of components and finished products inventories across companies and marketing platforms [1]

  • We provide effects of logistics performance index (LPI) on the environmental health and economic growth by using modern technique Cross-sectionally augmented autoregressive distributed lag (CS-Autoregressive Distributed Lags (ARDL)) with various other tests

  • Once the data shows the existence of cointegration, CS-ARDL may be used to examine the short and long-run relationships of economic growth and carbon emissions, as well as their drivers, using the theoretical channel outlined previously

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Summary

Introduction

Logistics is management of acquisition, storage of materials, transportation of components and finished products inventories (as well as associated information flow) across companies and marketing platforms [1]. Logistical expansion may help to boost economic growth, but it can have a detrimental influence on environment and green energy. Worldwide acquisition requires a huge interest in transportation and an extended lead time, the two of which contrarily affect environment sustainability [2]. According to the United Nations (2014), transportation is responsible for about 25% of worldwide carbon emissions, which is expected to rise to 55% by 2040 unless environmental safety measures are taken. Since petroleum and fossil fuels account for 96 percent of total energy demand, the transportation sector is heavily reliant on them. Businesses and decision-makers are more concerned about environmental preservation and long-term growth and notion of green logistics (GL) green environment emerges [3]

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