TY - JOUR
T1 - A multi-stage exponential production model for the assessment of China’s regional electric power supply chain efficiency
T2 - Does digital innovation matter?
AU - Li, Jingyun
AU - Shen, Zhiyang
AU - Vardanyan, Michael
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
PY - 2024
Y1 - 2024
N2 - China’s electric utility industry is among the country’s main polluters. Increasing the efficiency of China’s power supply chain is therefore essential to promote more environmentally sustainable power generation. This paper assesses the performance of China’s regional power supply chains that include electric utilities and power grid companies. We rely on the notion of sustainable supply chains to propose a multi-stage model that accounts for negative externalities such as harmful emissions, power transmission line loss, and increased mortality caused by pollution. Different from the existing studies of power supply chains, our approach is based on the exponential directional distance function defined with respect to a multiplicative production technology that can help mitigate the impact of data outliers. We use a panel of 30 Chinese provinces covering the period 2008–2018 to measure the efficiency improvement potential within regional supply chains and assess the efficiency-enhancing role of digital innovation. Our results provide evidence of considerable regional disparities and suggest that China’s eastern provinces outperform other regions due to the relatively advanced state of their technology. Furthermore, we demonstrate that the efficiency improvement potential from better management or technological innovation remains significant across the majority of provinces. Finally, our results provide evidence of a significant role of digitalization in promoting the efficiency of power supply chains. Our findings offer important perspectives on the strategies policymakers can use to promote sustainable performance of electric utilities and power grid companies.
AB - China’s electric utility industry is among the country’s main polluters. Increasing the efficiency of China’s power supply chain is therefore essential to promote more environmentally sustainable power generation. This paper assesses the performance of China’s regional power supply chains that include electric utilities and power grid companies. We rely on the notion of sustainable supply chains to propose a multi-stage model that accounts for negative externalities such as harmful emissions, power transmission line loss, and increased mortality caused by pollution. Different from the existing studies of power supply chains, our approach is based on the exponential directional distance function defined with respect to a multiplicative production technology that can help mitigate the impact of data outliers. We use a panel of 30 Chinese provinces covering the period 2008–2018 to measure the efficiency improvement potential within regional supply chains and assess the efficiency-enhancing role of digital innovation. Our results provide evidence of considerable regional disparities and suggest that China’s eastern provinces outperform other regions due to the relatively advanced state of their technology. Furthermore, we demonstrate that the efficiency improvement potential from better management or technological innovation remains significant across the majority of provinces. Finally, our results provide evidence of a significant role of digitalization in promoting the efficiency of power supply chains. Our findings offer important perspectives on the strategies policymakers can use to promote sustainable performance of electric utilities and power grid companies.
KW - Data envelopment analysis
KW - Digitalization
KW - Exponential production technology
KW - Power supply chain efficiency
UR - http://www.scopus.com/inward/record.url?scp=85199264723&partnerID=8YFLogxK
U2 - 10.1007/s10479-024-06152-9
DO - 10.1007/s10479-024-06152-9
M3 - Article
AN - SCOPUS:85199264723
SN - 0254-5330
JO - Annals of Operations Research
JF - Annals of Operations Research
ER -