Transportation Research Part D: Transport and Environment
Call for Papers for a Virtual Special Issue in Transportation Research Part D on “Decarbonizing the Maritime Industry with Analytics”
摘要截稿:
全文截稿: 2020-07-01
影响因子: 4.577
期刊难度:
CCF分类: 无
中科院JCR分区:
• 大类 : 工程技术 - 2区
• 小类 : 环境研究 - 2区
• 小类 : 交通运输 - 2区
• 小类 : 运输科技 - 3区
Overview
With 80-90% of world trade carried by sea, the maritime industry has witnessed an increasingly loud call to contribute to the global trend towards environmentally sustainable practices in recent years. In fact, the International Maritime Organization (IMO) – an agency of the United Nations responsible for regulating ocean shipping – has set the ambitious goal to reduce the greenhouse gas (GHG) emissions from shipping by at least 50% by 2050, compared to levels in 2008. To achieve such dramatic reductions, it is critical to explore every single solution, from the use of alternative fuels to technological innovations. The goal of the proposed special issue is making a timely contribution towards the decarbonization trend, focusing on the use of analytics.
In the current era of ubiquitous data, analytics has become key in (providing tools for) extracting meaningful insights from them. With the above trend of maritime shipping decarbonization evolving within this era, it presents numerous opportunities for analytics to contribute to the maritime industry’s decarbonization efforts. In fact, various studies have already appeared in the literature that have demonstrated how analytics can lead to meaningful reductions in GHG emissions. This special issue seeks to bring together the latest research in this emerging area. We are looking for high quality submissions that clearly demonstrate the impact analytics can have on the decarbonization efforts in the maritime shipping industry. Submissions can draw from any analytical technique from descriptive, predictive to prescriptive analytics. The focus of the research can be empirical. Or, alternatively, we also welcome more theoretical research, particularly those on mathematical modeling, analysis and optimization.
Topics covered by this special issue include, but are not limited to: