Choose clean energy or green technology? Empirical evidence from global ships

On January 1st, 2020, the International Maritime Organization (IMO) implemented a new regulation for a 0.50% global sulphur cap for marine fuels, which was a dramatic decrease from the previous emissions cap of 3.5%. The new regulation will have an enormous impact on the shipping market. At present, there are different feasible schemes for reducing sulphur emissions from ships. Shipowners need to consider the economic cost, energy feasibility, and other relevant factors of different schemes before making decisions. This paper empirically explores the factors that affect shipowners' energy choices. Based on the new emerging individual ship dynamic data, Automatic Identification System (AIS), and other relevant databases, the authors apply various data mining methods and a threshold discrete choice model combined with an oversampling technique to conduct quantitative measurements and statistical analyses of factors for each ship type that affect the shipowners' choices. Three groups of indicators, including ship characteristics, shipowner characteristics, and market conditions, are considered in this analysis. In the model, the authors also address the heterogeneity of the carriers towards environmental awareness. This study provides important practical implications for responding to the new emissions regulations among maritime and maritime-related industries and policymakers.

• Record URL:
  https://doi.org/10.1016/j.tre.2021.102364
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1366554521001320
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13665545
• Supplemental Notes:
  • © 2021 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Bai, Xiwen
  • Hou, Yao
  • Yang, Dong
• Publication Date: 2021-7

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Serial:
  • Transportation Research Part E: Logistics and Transportation Review
  • Volume: 151
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1366-5545
  • Serial URL: http://www.sciencedirect.com/science/journal/13665545

Subject/Index Terms

• TRT Terms: Choice models; Data mining; Identification systems; Markets; Pollutants; Regulations; Shipping; Ships; Sulfur; Sustainable transportation
• Subject Areas: Energy; Environment; Marine Transportation; Planning and Forecasting;

Filing Info

• Accession Number: 01774049
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 11 2021 2:36PM