Choose clean energy or green technology? Empirical evidence from global ships
Author
Abstract
Suggested Citation
DOI: 10.1016/j.tre.2021.102364
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Roar Adland & Haiying Jia & Siri P. Strandenes, 2017. "Are AIS-based trade volume estimates reliable? The case of crude oil exports," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(5), pages 657-665, July.
- Dong Yang & Lingxiao Wu & Shuaian Wang & Haiying Jia & Kevin X. Li, 2019. "How big data enriches maritime research – a critical review of Automatic Identification System (AIS) data applications," Transport Reviews, Taylor & Francis Journals, vol. 39(6), pages 755-773, November.
- Zhang, Liye & Meng, Qiang & Fang Fwa, Tien, 2019. "Big AIS data based spatial-temporal analyses of ship traffic in Singapore port waters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 287-304.
- Prochazka, Vít & Adland, Roar & Wolff, François-Charles, 2019.
"Contracting decisions in the crude oil transportation market: Evidence from fixtures matched with AIS data,"
Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 37-53.
- Vít Prochazka & Roar Adland & François-Charles Wolff, 2019. "Contracting decisions in the crude oil transportation market: Evidence from fixtures matched with AIS data," Post-Print hal-03778166, HAL.
- Zhen, Lu & Wu, Yiwei & Wang, Shuaian & Laporte, Gilbert, 2020. "Green technology adoption for fleet deployment in a shipping network," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 388-410.
- Océane Balland & Cecilia Girard & Stein Ove Erikstad & Kjetil Fagerholt, 2015. "Optimized selection of vessel air emission controls--moving beyond cost-efficiency," Maritime Policy & Management, Taylor & Francis Journals, vol. 42(4), pages 362-376, May.
- Øyvind Patricksson & Stein Ove Erikstad, 2017. "A two-stage optimization approach for sulphur emission regulation compliance," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(1), pages 94-111, January.
- Lixian Fan & Bingmei Gu, 2019. "Impacts of the Increasingly Strict Sulfur Limit on Compliance Option Choices: The Case Study of Chinese SECA," Sustainability, MDPI, vol. 12(1), pages 1-20, December.
- Regli, Frederik & Nomikos, Nikos K., 2019. "The eye in the sky – Freight rate effects of tanker supply," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 402-424.
- Mingfeng Lin & Henry C. Lucas & Galit Shmueli, 2013. "Research Commentary ---Too Big to Fail: Large Samples and the p -Value Problem," Information Systems Research, INFORMS, vol. 24(4), pages 906-917, December.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Li, Yiliang & Bai, Xiwen & Wang, Qi & Ma, Zhongjun, 2022. "A big data approach to cargo type prediction and its implications for oil trade estimation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
- Shao, Shuai & Tan, Zhijia & Wang, Tingsong & Liu, Zhiyuan, 2023. "Configuration design of the emission control areas for coastal ships: A Stackelberg game model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 172(C).
- Peng, Wenhao & Bai, Xiwen, 2022. "Prospects for improving shipping companies’ profit margins by quantifying operational strategies and market focus approach through AIS data," Transport Policy, Elsevier, vol. 128(C), pages 138-152.
- Wu, Jie & Liu, Jiaguo & Li, Na, 2024. "The evasion strategy options for competitive ocean carriers under the EU ETS," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
- Li, Huanhuan & Xing, Wenbin & Jiao, Hang & Yang, Zaili & Li, Yan, 2024. "Deep bi-directional information-empowered ship trajectory prediction for maritime autonomous surface ships," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 181(C).
- Li, Huanhuan & Jiao, Hang & Yang, Zaili, 2023. "AIS data-driven ship trajectory prediction modelling and analysis based on machine learning and deep learning methods," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
- Bai, Xiwen & Cheng, Liangqi & Iris, Çağatay, 2022. "Data-driven financial and operational risk management: Empirical evidence from the global tramp shipping industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
- Huang, Xingyu & Zheng, Pengjun & Liu, Guiyun, 2024. "Non-cooperative and Nash-bargaining game of a two-parallel maritime supply chain considering government subsidy and forwarder's CSR strategy: A dynamic perspective," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Li, Yiliang & Bai, Xiwen & Wang, Qi & Ma, Zhongjun, 2022. "A big data approach to cargo type prediction and its implications for oil trade estimation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
- Fuentes, Gabriel, 2021. "Generating bunkering statistics from AIS data: A machine learning approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
- Sugrue, Dennis & Adriaens, Peter, 2021. "A data fusion approach to predict shipping efficiency for bulk carriers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
- Kei Kanamoto & Liwen Murong & Minato Nakashima & Ryuichi Shibasaki, 2021. "Can maritime big data be applied to shipping industry analysis? Focussing on commodities and vessel sizes of dry bulk carriers," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(2), pages 211-236, June.
- Zhang, Jinfen & Liu, Jiongjiong & Hirdaris, Spyros & Zhang, Mingyang & Tian, Wuliu, 2023. "An interpretable knowledge-based decision support method for ship collision avoidance using AIS data," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
- Yang, Dong & Wu, Lingxiao & Wang, Shuaian, 2021. "Can we trust the AIS destination port information for bulk ships?–Implications for shipping policy and practice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
- Xin, Xuri & Liu, Kezhong & Loughney, Sean & Wang, Jin & Li, Huanhuan & Ekere, Nduka & Yang, Zaili, 2023. "Multi-scale collision risk estimation for maritime traffic in complex port waters," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
- Xin, Xuri & Liu, Kezhong & Loughney, Sean & Wang, Jin & Yang, Zaili, 2023. "Maritime traffic clustering to capture high-risk multi-ship encounters in complex waters," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
- Bai, Xiwen & Cheng, Liangqi & Iris, Çağatay, 2022. "Data-driven financial and operational risk management: Empirical evidence from the global tramp shipping industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
- Gong, Xu & Li, Zhi-Chun, 2022. "Determination of subsidy and emission control coverage under competition and cooperation of China-Europe Railway Express and liner shipping," Transport Policy, Elsevier, vol. 125(C), pages 323-335.
- Hsin-Han Chen & Hui-Ling Chen & Yi-Tien Lin & Chaou-Wen Lin & Chien-Chang Ho & Hsueh-Yi Lin & Po-Fu Lee, 2020. "The Associations between Functional Fitness Test Performance and Abdominal Obesity in Healthy Elderly People: Results from the National Physical Fitness Examination Survey in Taiwan," IJERPH, MDPI, vol. 18(1), pages 1-14, December.
- Thomas Görzen, 2019. "Can Experience be Trusted? Investigating the Effect of Experience on Decision Biases in Crowdworking Platforms," Working Papers Dissertations 55, Paderborn University, Faculty of Business Administration and Economics.
- Yi Yang & Kunpeng Zhang & Yangyang Fan, 2023. "sDTM: A Supervised Bayesian Deep Topic Model for Text Analytics," Information Systems Research, INFORMS, vol. 34(1), pages 137-156, March.
- Evangelista, Rui & Ramalho, Esmeralda A. & Andrade e Silva, João, 2020. "On the use of hedonic regression models to measure the effect of energy efficiency on residential property transaction prices: Evidence for Portugal and selected data issues," Energy Economics, Elsevier, vol. 86(C).
- Yen-Chun Chou & Howard Hao-Chun Chuang, 2018. "A predictive investigation of first-time customer retention in online reservation services," Service Business, Springer;Pan-Pacific Business Association, vol. 12(4), pages 685-699, December.
- Tang, Kayu & Parsons, David J. & Jude, Simon, 2019. "Comparison of automatic and guided learning for Bayesian networks to analyse pipe failures in the water distribution system," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 24-36.
- Sujin Park & Ali Tafti & Galit Shmueli, 2024. "Transporting Causal Effects Across Populations Using Structural Causal Modeling: An Illustration to Work-from-Home Productivity," Information Systems Research, INFORMS, vol. 35(2), pages 686-705, June.
- Claire Teunenbroek & René Bekkers & Bianca Beersma, 2021. "They ought to do it too: Understanding effects of social information on donation behavior and mood," International Review on Public and Nonprofit Marketing, Springer;International Association of Public and Non-Profit Marketing, vol. 18(2), pages 229-253, June.
- Haiying Jia & Ove Daae Lampe & Veronika Solteszova & Siri P. Strandenes, 2017. "Norwegian port connectivity and its policy implications," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(8), pages 956-966, November.
- Jiang, Meizhi & Lu, Jing, 2020. "The analysis of maritime piracy occurred in Southeast Asia by using Bayesian network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 139(C).
More about this item
Keywords
IMO emissions regulation; Energy choice; AIS data; Policy formulation; Ship behaviour;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:151:y:2021:i:c:s1366554521001320. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.