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Leveraging Data Analytics to Optimize Eco-Friendly Transportation and Sustainable Practices in Green Logistics for Carbon Footprint Reduction in Supply Chains
Subject area: Management and Commerce · Area of research: Sustainability, Eco-Transportation
Abstract
The purpose of this research is to explore the applicability of data analysis in line with effective management of environmentally sustainable transport and general environmentally conscious practices in supply chain networks to minimize carbon emissions. To this end, based on a secondary data review, the research presents the impact of analytics in green logistics. With GIS, AI, and IoT technologies it is possible to make real-time decisions which results in a 23% reduction of CO? emissions and 15?20% utilization of vehicles for containerized shipment. The research also looks at how analytics ensures sustainable business operations such as; smart inventory management, efficient storage solutions, and efficient packaging solutions. These practices have positive environmental and economic outcomes including 30 percent energy audit savings in the warehouse and a 20 percent operational waste cut. Nevertheless, some of the issues discussed above, including high implementation costs, lack of access to real-time data, and environmental impacts of the analytics infrastructure are presented as barriers, especially for SMEs. The discussion highlights how policy support, cross-industry supply chain partnerships, and the symbiotic application of analytical techniques with up-and-coming technologies like blockchain and self-driving vehicles have potentially beneficial effects on sustainability performances. The results are compatible with global sustainability paradigms and recommend the strategy for academicians, policymakers, and logisticians who are interested in enhancing environmental supply chain performance. This research establishes data analysis as a crucial component of achieving sustainable logistics, in equal consideration of environmental and operational concerns. Subsequent studies should therefore seek to identify and overcome implementation barriers to extend the scope of adoption to SMEs and incorporate analytics into circular supply chain systems. So, using data solutions, logistics brings a definite high impact on international carbon metrics and leads meaningful change toward sustainable supply chains.
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How to cite this paper
@article{1706778,
author = {Chiagozie Kafidipe},
title = {Leveraging Data Analytics to Optimize Eco-Friendly Transportation and Sustainable Practices in Green Logistics for Carbon Footprint Reduction in Supply Chains},
journal = {Iconic Research And Engineering Journals},
year = {2024},
volume = {8},
number = {6},
pages = {800-811},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1706778.pdf},
abstract = {The purpose of this research is to explore the applicability of data analysis in line with effective management of environmentally sustainable transport and general environmentally conscious practices in supply chain networks to minimize carbon emissions. To this end, based on a secondary data review, the research presents the impact of analytics in green logistics. With GIS, AI, and IoT technologies it is possible to make real-time decisions which results in a 23% reduction of CO? emissions and 15?20% utilization of vehicles for containerized shipment. The research also looks at how analytics ensures sustainable business operations such as; smart inventory management, efficient storage solutions, and efficient packaging solutions. These practices have positive environmental and economic outcomes including 30 percent energy audit savings in the warehouse and a 20 percent operational waste cut. Nevertheless, some of the issues discussed above, including high implementation costs, lack of access to real-time data, and environmental impacts of the analytics infrastructure are presented as barriers, especially for SMEs. The discussion highlights how policy support, cross-industry supply chain partnerships, and the symbiotic application of analytical techniques with up-and-coming technologies like blockchain and self-driving vehicles have potentially beneficial effects on sustainability performances. The results are compatible with global sustainability paradigms and recommend the strategy for academicians, policymakers, and logisticians who are interested in enhancing environmental supply chain performance. This research establishes data analysis as a crucial component of achieving sustainable logistics, in equal consideration of environmental and operational concerns. Subsequent studies should therefore seek to identify and overcome implementation barriers to extend the scope of adoption to SMEs and incorporate analytics into circular supply chain systems. So, using data solutions, logistics brings a definite high impact on international carbon metrics and leads meaningful change toward sustainable supply chains.},
month = {December},
}