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Impact of Digital Economy on the Provision Efficiency for Public Health Services: Empirical Study of 31 Provinces in China

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Listed:
  • Yuwen Lyu

    (School of Economics and Statistics, Guangzhou University, Guangzhou 511400, China)

  • Yuqing Peng

    (School of Journalism and Communication, Guangzhou University, Guangzhou 511400, China
    Institude of Communication Studies, Communication University of China, Beijing 100024, China)

  • Hejian Liu

    (School of Education, Guangzhou University, Guangzhou 511400, China)

  • Ji-Jen Hwang

    (School of Policy and Government, George Mason University, Arlington, VA 20301, USA
    Institute for Global Public Affairs Research, Bethesda, MD 20817, USA)

Abstract

The digital economy is booming in China and has become the world’s largest after the United States’. Since China entered the era of the digital economy, its digital technology has radiated into various fields. This study is to examine the impact of China’s digital economy on the provision efficiency of public health institutions and the mechanism of action between them. Specifically, it measures the development level of China’s digital economy, and the provision efficiency of public health institutions from 2009 to 2018. The research also explores the relationship between China’s digital economy and its provision efficiency, through the Tobit-DEA model. An analysis of the regional heterogeneity indicated that the performance of China’s digital economy in the eastern region has a significant positive effect on improving the efficiency of the public health sector. This further confirms that the digital economy has strengthened China’s ability to deal with public health crises during the COVID-19 pandemic. A further mediation effect analysis showed that China’s digital economy optimizes the efficiency of public health provision by improving governmental performance and regulatory quality. This shows that the development of the digital economy promotes the construction of digital government, and thus improves the quality of governmental supervision and governmental performance, which has a significant positive effect on the efficiency of the supply of public health services. During the COVID-19 pandemic especially, government delivery of public health services was critical in addressing public health crises. Therefore, based on the results of our empirical analysis, this study provides policy suggestions for improving the efficiency of public health service provision in the era of the digital economy.

Suggested Citation

  • Yuwen Lyu & Yuqing Peng & Hejian Liu & Ji-Jen Hwang, 2022. "Impact of Digital Economy on the Provision Efficiency for Public Health Services: Empirical Study of 31 Provinces in China," IJERPH, MDPI, vol. 19(10), pages 1-17, May.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:10:p:5978-:d:815688
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    References listed on IDEAS

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    1. Douglass C. North, 1990. "A Transaction Cost Theory of Politics," Journal of Theoretical Politics, , vol. 2(4), pages 355-367, October.
    2. José França & João Figueiredo & Jair Lapa, 2010. "A DEA methodology to evaluate the impact of information asymmetry on the efficiency of not-for-profit organizations with an application to higher education in Brazil," Annals of Operations Research, Springer, vol. 173(1), pages 39-56, January.
    3. Touhami Abdelkhalek & Aziz Ajbilou & Mohamed Benayad & Dorothée Boccanfuso & Luc Savard, 2021. "How Can the Digital Economy Benefit Morocco and All Moroccans?," Working Papers 1503, Economic Research Forum, revised 20 Nov 2021.
    4. Yiru Guo & Yan Hu & Ke Shi & Yuriy Bilan, 2020. "Valuation of Water Resource Green Efficiency Based on SBM–TOBIT Panel Model: Case Study from Henan Province, China," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
    5. Carlsson, Bo, 2004. "The Digital Economy: what is new and what is not?," Structural Change and Economic Dynamics, Elsevier, vol. 15(3), pages 245-264, September.
    6. Aarthi Raghavan & Mehmet Akif Demircioglu & Araz Taeihagh, 2021. "Public Health Innovation through Cloud Adoption: A Comparative Analysis of Drivers and Barriers in Japan, South Korea, and Singapore," IJERPH, MDPI, vol. 18(1), pages 1-30, January.
    7. Mann, Stefan & Wüstemann, Henry, 2010. "Public governance of information asymmetries--The gap between reality and economic theory," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 39(2), pages 278-285, April.
    8. Rongen, Gunnar, 1995. "Efficiency in the provision of local public goods in Norway," European Journal of Political Economy, Elsevier, vol. 11(2), pages 253-264, June.
    9. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, December.
    Full references (including those not matched with items on IDEAS)

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