IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2023i1p157-d1308827.html
   My bibliography  Save this article

The Effects and Driving Factors of Low-Carbon Transition of International Oil Companies: Evidence from a Super-SBM Model

Author

Listed:
  • Xuwei Tang

    (School of Economics and Management, China University of Petroleum-Beijing, Beijing 102249, China
    CNPC Economics and Technology Research Institute, Beijing 100120, China)

  • Qi Zhang

    (School of Economics and Management, China University of Petroleum-Beijing, Beijing 102249, China
    Tianshan Research Institute, Xinjiang 834000, China)

  • Chunxin Li

    (CNPC Economics and Technology Research Institute, Beijing 100120, China)

  • Haitao Zhang

    (CNPC Managers Training Institute, Beijing 100096, China)

  • Haiyun Xu

    (Petrochina Natural Gas Marketing Company, Beijing 100007, China)

Abstract

As the main source of energy supply and carbon emissions, the oil and gas industry has entered the comprehensive low-carbon transition stage driven by various factors. Since different oil companies possess distinct understandings of transition paths, the effect of low carbon transition varies greatly. Obviously, it is necessary to evaluate the performance of low-carbon transitions within the oil and gas industry. Therefore, in this paper, 10 major international oil companies are taken as examples, and a super-efficiency slack-based measurement (super-SBM) model is applied in the present study to analyze the efficiency of low-carbon transitions. Furthermore, the logarithmic mean Divisia index (LMDI) is used to decompose the driving factors of carbon emissions and analyze their impact on the low-carbon transition of international oil companies. The obtained results reveal that although major oil companies have taken different measures in low-carbon transition and achieved a year-on-year reduction in carbon emissions, from the perspective of the efficiency of the entire production and operation process, these oil companies are inefficient in carbon emissions and need to adopt more effective low-carbon transition strategies; Moreover, after the further decomposition of the carbon emission driving factors of the 10 companies, it is found that improving the energy consumption intensity and development level of oil companies can effectively improve the effect of low-carbon transition of international oil companies. Drawing on the above findings, this paper puts forward suggestions for the low-carbon transition of energy companies, thus providing theoretical support and guidance for energy companies in different countries to implement low-carbon transition and green development strategies.

Suggested Citation

  • Xuwei Tang & Qi Zhang & Chunxin Li & Haitao Zhang & Haiyun Xu, 2023. "The Effects and Driving Factors of Low-Carbon Transition of International Oil Companies: Evidence from a Super-SBM Model," Energies, MDPI, vol. 17(1), pages 1-19, December.
    • Handle: RePEc:gam:jeners:v:17:y:2023:i:1:p:157-:d:1308827
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/1/157/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/1/157/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Li, Zhengbing & Liang, Yongtu & Ni, Weilong & Liao, Qi & Xu, Ning & Li, Lichao & Zheng, Jianqin & Zhang, Haoran, 2022. "Pipesharing: economic-environmental benefits from transporting biofuels through multiproduct pipelines," Applied Energy, Elsevier, vol. 311(C).
    2. Mohammad S. Masnadi & Adam R. Brandt, 2017. "Climate impacts of oil extraction increase significantly with oilfield age," Nature Climate Change, Nature, vol. 7(8), pages 551-556, August.
    3. Tan, Sieting & Yang, Jin & Yan, Jinyue & Lee, Chewtin & Hashim, Haslenda & Chen, Bin, 2017. "A holistic low carbon city indicator framework for sustainable development," Applied Energy, Elsevier, vol. 185(P2), pages 1919-1930.
    Full references (including those not matched with items on IDEAS)

    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.
    1. Schlör, Holger & Venghaus, Sandra & Hake, Jürgen-Friedrich, 2018. "The FEW-Nexus city index – Measuring urban resilience," Applied Energy, Elsevier, vol. 210(C), pages 382-392.
    2. Yanxiao Jiang & Zhou Huang, 2024. "Impact of urban vitality on carbon emission—an analysis of 222 Chinese cities based on the spatial Durbin model," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    3. Du, Xiaoyun & Meng, Conghui & Guo, Zhenhua & Yan, Hang, 2023. "An improved approach for measuring the efficiency of low carbon city practice in China," Energy, Elsevier, vol. 268(C).
    4. Lin, Boqiang & Zhu, Junpeng, 2019. "Impact of energy saving and emission reduction policy on urban sustainable development: Empirical evidence from China," Applied Energy, Elsevier, vol. 239(C), pages 12-22.
    5. Guorong Chen & Changyan Liu, 2023. "Can Low–Carbon City Development Stimulate Population Growth? Insights from China’s Low–Carbon Pilot Program," Sustainability, MDPI, vol. 15(20), pages 1-22, October.
    6. Hongtao Jiang & Jian Yin & Yuanhong Qiu & Bin Zhang & Yi Ding & Ruici Xia, 2022. "Industrial Carbon Emission Efficiency of Cities in the Pearl River Basin: Spatiotemporal Dynamics and Driving Forces," Land, MDPI, vol. 11(8), pages 1-22, July.
    7. Longyu Shi & Xueqin Xiang & Wei Zhu & Lijie Gao, 2018. "Standardization of the Evaluation Index System for Low-Carbon Cities in China: A Case Study of Xiamen," Sustainability, MDPI, vol. 10(10), pages 1-20, October.
    8. Xiwen Fu & Shuxin Wang, 2022. "How to Promote Low-Carbon Cities with Blockchain Technology? A Blockchain-Based Low-Carbon Development Model for Chinese Cities," Sustainability, MDPI, vol. 14(20), pages 1-17, October.
    9. Tu, Renfu & Jiao, Yingqi & Qiu, Rui & Liao, Qi & Xu, Ning & Du, Jian & Liang, Yongtu, 2023. "Energy saving and consumption reduction in the transportation of petroleum products: A pipeline pricing optimization perspective," Applied Energy, Elsevier, vol. 342(C).
    10. Xing Zhang, 2018. "Short-Term Load Forecasting for Electric Bus Charging Stations Based on Fuzzy Clustering and Least Squares Support Vector Machine Optimized by Wolf Pack Algorithm," Energies, MDPI, vol. 11(6), pages 1-18, June.
    11. Rasool, Samma Faiz & Zaman, Shah & Jehan, Noor & Chin, Tachia & Khan, Saleem & Zaman, Qamar uz, 2022. "Investigating the role of the tech industry, renewable energy, and urbanization in sustainable environment: Policy directions in the context of developing economies," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    12. Francesco Pinna & Valeria Saiu, 2021. "Greenways as Integrated Systems: A Proposal for Planning and Design Guidelines Based on Case Studies Evaluation," Sustainability, MDPI, vol. 13(20), pages 1-17, October.
    13. Garafutdinova Daniya & Decai Tang, 2024. "Green Finance and Industrial Low-Carbon Transition: A Case Study on Green Economy Policy in Kazakhstan," Sustainability, MDPI, vol. 16(17), pages 1-23, September.
    14. Jiang, Hongdian & Dong, Xiucheng & Jiang, Qingzhe & Dong, Kangyin, 2020. "What drives China's natural gas consumption? Analysis of national and regional estimates," Energy Economics, Elsevier, vol. 87(C).
    15. González-López, Rafael & Giampietro, Mario, 2018. "Relational analysis of the oil and gas sector of Mexico: Implications for Mexico's energy reform," Energy, Elsevier, vol. 154(C), pages 403-414.
    16. Mageswaran Rengasamy & Sivasankar Gangatharan & Rajvikram Madurai Elavarasan & Lucian Mihet-Popa, 2020. "The Motivation for Incorporation of Microgrid Technology in Rooftop Solar Photovoltaic Deployment to Enhance Energy Economics," Sustainability, MDPI, vol. 12(24), pages 1-27, December.
    17. Huang, Ying & Liao, Cuiping & Zhang, Jingjing & Guo, Hongxu & Zhou, Nan & Zhao, Daiqing, 2019. "Exploring potential pathways towards urban greenhouse gas peaks: A case study of Guangzhou, China," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    18. Renaud Coulomb & Fanny Henriet & Léo Reitzmann, 2021. "'Bad' Oil, 'Worse' Oil and Carbon Misallocation," Working Papers halshs-03244647, HAL.
    19. Qingduo Mao & Ben Ma & Hongshuai Wang & Qi Bian, 2019. "Investigating Policy Instrument Adoption in Low-Carbon City Development: A Case Study from China," Energies, MDPI, vol. 12(18), pages 1-17, September.
    20. Liu, Jiahong & Wang, Jia & Ding, Xiangyi & Shao, Weiwei & Mei, Chao & Li, Zejin & Wang, Kaibo, 2020. "Assessing the mitigation of greenhouse gas emissions from a green infrastructure-based urban drainage system," Applied Energy, Elsevier, vol. 278(C).

    Corrections

    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:gam:jeners:v:17:y:2023:i:1:p:157-:d:1308827. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.