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Energy supply chain efficiency in the digital era: Evidence from China's listed companies

Shuke Fu, Yingchen Ge, Yu Hao, Jiachao Peng and Jiali Tian

Energy Economics, 2024, vol. 134, issue C

Abstract: With the widespread adoption of cutting-edge digital technologies, including big data, blockchain, artificial intelligence (AI), and cloud computing, the development and digitalization of the supply chain are experiencing significant integration. According to China's Fourteenth Five-Year Plan for a Modern Energy System, the country has embarked on a new phase of constructing a modern energy system. An accelerating trend in the digital upgrading of energy businesses marks a period of innovation and upgrading for the modern energy industry. Although policy documents highlight the role of digital technology in advancing the digital transformation of energy businesses, the underlying relationships and transmission mechanisms have yet to be fully explored, underscoring the necessity for targeted policy development. This study examines the link between enterprise digital transformation and energy supply chain efficiency, utilizing a bidirectional fixed-effects framework and analyzing data from 112 listed companies in the energy sector from 2011 to 2019. Employing a three-stage DEA model and text analysis to measure the primary indicators, findings suggest that digital transformation enhances energy supply chain efficiency by fostering technological innovation, leveraging government subsidies, and increasing openness levels. Moreover, the positive impact is more pronounced in large and private enterprises, especially in the eastern and northeastern regions. This study offers empirical support for the policy framework mentioned, advocating for the advancement of business digital transformation, the establishment and enhancement of digital supply chain systems, and the integration of supply chain enterprise resources upstream and downstream.

Keywords: Enterprise digital transformation; Energy supply chain efficiency; Bidirectional fixed effect model; Text analysis; Three-stage DEA model (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:134:y:2024:i:c:s0140988324003050

DOI: 10.1016/j.eneco.2024.107597

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Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

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