IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i22p14941-d971491.html
   My bibliography  Save this article

Analysis on the Spatio-Temporal Evolution Characteristics of the Impact of China’s Digitalization Process on Green Total Factor Productivity

Author

Listed:
  • Junwei Zhao

    (College of Management Science, Chengdu University of Technology, Chengdu 610059, China)

  • Yuxiang Zhang

    (College of Management Science, Chengdu University of Technology, Chengdu 610059, China)

  • Anhang Chen

    (College of Management Science, Chengdu University of Technology, Chengdu 610059, China)

  • Huiqin Zhang

    (College of Management Science, Chengdu University of Technology, Chengdu 610059, China)

Abstract

Green production is an inevitable choice for China’s high-quality economic development. With the rise of the digital technology revolution, China’s digital transformation may play an integral and important role in increasing green total factor productivity (GTFP). Based on the panel data of 30 Chinese provinces from 2014–2020, the impact of digitization on GTFP was explored using the model of geographically and temporally weighted regression (GTWR), and the spatial and temporal distribution characteristics and development trends of such effects were further explored. The main findings are as follows: (1) China’s digitalization level and GTFP has significant spatial autocorrelation and similar spatial distribution characteristics. (2) Digitalization has a significant positive impact on GTFP, but this impact decreases yearly, and there are noticeable regional differences. Digitalization in the eastern and central regions has a more significant impact on GTFP than in the west. (3) The region where China’s digital development has extensively promoted GTFP has shifted from China’s southern coastal region to the northwest and northeast regions. (4) The time-series fluctuations of the regression coefficients of the digitization level in each province in China also show agglomeration characteristics. That is, the regression coefficients of neighboring provinces have similar time-series fluctuations.

Suggested Citation

  • Junwei Zhao & Yuxiang Zhang & Anhang Chen & Huiqin Zhang, 2022. "Analysis on the Spatio-Temporal Evolution Characteristics of the Impact of China’s Digitalization Process on Green Total Factor Productivity," IJERPH, MDPI, vol. 19(22), pages 1-21, November.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:22:p:14941-:d:971491
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/22/14941/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/22/14941/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liu, Zuankuo & Xin, Li, 2019. "Has China's Belt and Road Initiative promoted its green total factor productivity？——Evidence from primary provinces along the route," Energy Policy, Elsevier, vol. 129(C), pages 360-369.
    2. Kong, Qunxi & Peng, Dan & Ni, Yehui & Jiang, Xinyue & Wang, Ziqi, 2021. "Trade openness and economic growth quality of China: Empirical analysis using ARDL model," Finance Research Letters, Elsevier, vol. 38(C).
    3. Dong-hyun Oh, 2010. "A global Malmquist-Luenberger productivity index," Journal of Productivity Analysis, Springer, vol. 34(3), pages 183-197, December.
    4. Rolf Färe & Shawna Grosskopf & Carl A Pasurka, Jr., 2001. "Accounting for Air Pollution Emissions in Measures of State Manufacturing Productivity Growth," Journal of Regional Science, Wiley Blackwell, vol. 41(3), pages 381-409, August.
    5. Pan, Wenrong & Xie, Tao & Wang, Zhuwang & Ma, Lisha, 2022. "Digital economy: An innovation driver for total factor productivity," Journal of Business Research, Elsevier, vol. 139(C), pages 303-311.
    6. Li, Ke & Lin, Boqiang, 2017. "Economic growth model, structural transformation, and green productivity in China," Applied Energy, Elsevier, vol. 187(C), pages 489-500.
    7. Juan Lin & Zhou Yu & Yehua Dennis Wei & Mingfeng Wang, 2017. "Internet Access, Spillover and Regional Development in China," Sustainability, MDPI, vol. 9(6), pages 1-18, June.
    8. Wang, En-Ze & Lee, Chien-Chiang & Li, Yaya, 2022. "Assessing the impact of industrial robots on manufacturing energy intensity in 38 countries," Energy Economics, Elsevier, vol. 105(C).
    9. Teece, David J., 2018. "Profiting from innovation in the digital economy: Enabling technologies, standards, and licensing models in the wireless world," Research Policy, Elsevier, vol. 47(8), pages 1367-1387.
    10. Peng, Jiaying & Xie, Rui & Ma, Chunbo & Fu, Yang, 2021. "Market-based environmental regulation and total factor productivity: Evidence from Chinese enterprises," Economic Modelling, Elsevier, vol. 95(C), pages 394-407.
    11. Yang Liu & Yanlin Yang & Huihui Li & Kaiyang Zhong, 2022. "Digital Economy Development, Industrial Structure Upgrading and Green Total Factor Productivity: Empirical Evidence from China’s Cities," IJERPH, MDPI, vol. 19(4), pages 1-23, February.
    12. Rui Xie & Siling Yao & Feng Han & Jiayu Fang, 2019. "Land Finance, Producer Services Agglomeration, and Green Total Factor Productivity," International Regional Science Review, , vol. 42(5-6), pages 550-579, September.
    13. Shuai Wang & Cunyi Yang & Zhenghui Li, 2021. "Spatio-Temporal Evolution Characteristics and Spatial Interaction Spillover Effects of New-Urbanization and Green Land Utilization Efficiency," Land, MDPI, vol. 10(10), pages 1-26, October.
    14. Si Luo & Miaochao Chen, 2022. "Digital Finance Development and the Digital Transformation of Enterprises: Based on the Perspective of Financing Constraint and Innovation Drive," Journal of Mathematics, Hindawi, vol. 2022, pages 1-10, March.
    15. Gustavo Cattelan Nobre & Elaine Tavares, 2017. "Scientific literature analysis on big data and internet of things applications on circular economy: a bibliometric study," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 463-492, April.
    16. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    17. Yaya Su & Zhenghui Li & Cunyi Yang, 2021. "Spatial Interaction Spillover Effects between Digital Financial Technology and Urban Ecological Efficiency in China: An Empirical Study Based on Spatial Simultaneous Equations," IJERPH, MDPI, vol. 18(16), pages 1-27, August.
    18. Bai, Chong-En & Ma, Hong & Pan, Wenqing, 2012. "Spatial spillover and regional economic growth in China," China Economic Review, Elsevier, vol. 23(4), pages 982-990.
    19. Guangqin Li & Shiyu Lu & Shuai Shao & Lili Yang & Ke Zhang, 2021. "Do environmental regulations hamper small enterprises' market entry? Evidence from China," Business Strategy and the Environment, Wiley Blackwell, vol. 30(1), pages 252-266, January.
    20. Peter Jones & Martin Wynn, 2021. "The Leading Digital Technology Companies and Their Approach to Sustainable Development," Sustainability, MDPI, vol. 13(12), pages 1-12, June.
    21. Susheng Wang & Gang Chen & Xue Han, 2021. "An Analysis of the Impact of the Emissions Trading System on the Green Total Factor Productivity Based on the Spatial Difference-in-Differences Approach: The Case of China," IJERPH, MDPI, vol. 18(17), pages 1-18, August.
    22. Song, Malin & Du, Juntao & Tan, Kim Hua, 2018. "Impact of fiscal decentralization on green total factor productivity," International Journal of Production Economics, Elsevier, vol. 205(C), pages 359-367.
    23. Wu, Haitao & Hao, Yu & Ren, Siyu & Yang, Xiaodong & Xie, Guo, 2021. "Does internet development improve green total factor energy efficiency? Evidence from China," Energy Policy, Elsevier, vol. 153(C).
    24. Pittman, Russell W, 1983. "Multilateral Productivity Comparisons with Undesirable Outputs," Economic Journal, Royal Economic Society, vol. 93(372), pages 883-891, December.
    25. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mingwen XU & Yang CHEN & Farhan ALI & Oleksii LYULYOV & Tetyana PIMONENKO, 2024. "Efficiency of Green Total Factor Production: Exploring Core Determinants," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 102-119, October.
    2. Long Qian & Yunjie Zhou & Ying Sun, 2023. "Regional Differences, Distribution Dynamics, and Convergence of the Green Total Factor Productivity of China’s Cities under the Dual Carbon Targets," Sustainability, MDPI, vol. 15(17), pages 1-26, August.
    3. Chunhua Luo & Dianlong Wei & Wunhong Su & Jinjing Lu, 2023. "Association between Regional Digitalization and High-Quality Economic Development," Sustainability, MDPI, vol. 15(3), pages 1-19, January.

    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. Lv, Chengchao & Song, Jie & Lee, Chien-Chiang, 2022. "Can digital finance narrow the regional disparities in the quality of economic growth? Evidence from China," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 502-521.
    2. Liu, Zuankuo & Xin, Li, 2019. "Has China's Belt and Road Initiative promoted its green total factor productivity？——Evidence from primary provinces along the route," Energy Policy, Elsevier, vol. 129(C), pages 360-369.
    3. Shuai Wang & Cunyi Yang & Zhenghui Li, 2022. "Green Total Factor Productivity Growth: Policy-Guided or Market-Driven?," IJERPH, MDPI, vol. 19(17), pages 1-19, August.
    4. Razzaq, Asif & Yang, Xiaodong, 2023. "Digital finance and green growth in China: Appraising inclusive digital finance using web crawler technology and big data," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    5. Ma, Dan & Zhu, Qing, 2022. "Innovation in emerging economies: Research on the digital economy driving high-quality green development," Journal of Business Research, Elsevier, vol. 145(C), pages 801-813.
    6. Lee, Chien-Chiang & He, Zhi-Wen & Yuan, Zihao, 2023. "A pathway to sustainable development: Digitization and green productivity," Energy Economics, Elsevier, vol. 124(C).
    7. Lin Zhu & Xiaoming Li & Yao Huang & Fangyuan Liu & Chengji Yang & Dongyang Li & Hongpeng Bai, 2023. "Digital Technology and Green Development in Manufacturing: Evidence from China and 20 Other Asian Countries," Sustainability, MDPI, vol. 15(17), pages 1-20, August.
    8. Chunhua Xin & Xiufeng Lai, 2022. "Does the Environmental Information Disclosure Promote the High-Quality Development of China’s Resource-Based Cities?," Sustainability, MDPI, vol. 14(11), pages 1-26, May.
    9. Ruomeng Zhou & Yunsheng Zhang, 2023. "Measurement of Urban Green Total Factor Productivity and Analysis of Its Temporal and Spatial Evolution in China," Sustainability, MDPI, vol. 15(12), pages 1-32, June.
    10. Mingyue Chen & Shuting Wang & Xiaowen Wang, 2024. "How Does Artificial Intelligence Impact Green Development? Evidence from China," Sustainability, MDPI, vol. 16(3), pages 1-23, February.
    11. Can Cheng & Xiuwen Yu & Heng Hu & Zitian Su & Shangfeng Zhang, 2022. "Measurement of China’s Green Total Factor Productivity Introducing Human Capital Composition," IJERPH, MDPI, vol. 19(20), pages 1-19, October.
    12. Xi Zhang & Rui Li & Jinglei Zhang, 2022. "Understanding the Green Total Factor Productivity of Manufacturing Industry in China: Analysis Based on the Super-SBM Model with Undesirable Outputs," Sustainability, MDPI, vol. 14(15), pages 1-16, July.
    13. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali, 2015. "A new slacks-based measure of Malmquist–Luenberger index in the presence of undesirable outputs," Omega, Elsevier, vol. 51(C), pages 29-37.
    14. Shuming Ren & Lianqing Li & Yueqi Han & Yu Hao & Haitao Wu, 2022. "The emerging driving force of inclusive green growth: Does digital economy agglomeration work?," Business Strategy and the Environment, Wiley Blackwell, vol. 31(4), pages 1656-1678, May.
    15. Meiling Wang & Silu Pang & Ikram Hmani & Ilham Hmani & Cunfang Li & Zhengxia He, 2021. "Towards sustainable development: How does technological innovation drive the increase in green total factor productivity?," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(1), pages 217-227, January.
    16. Wu, Ge & Baležentis, Tomas & Sun, Chuanwang & Xu, Shuhua, 2019. "Source control or end-of-pipe control: Mitigating air pollution at the regional level from the perspective of the Total Factor Productivity change decomposition," Energy Policy, Elsevier, vol. 129(C), pages 1227-1239.
    17. Chen, Xiang & Chen, Yong & Huang, Wenli & Zhang, Xuping, 2023. "A new Malmquist-type green total factor productivity measure: An application to China," Energy Economics, Elsevier, vol. 117(C).
    18. Song, Malin & Zhu, Shuai & Wang, Jianlin & Zhao, Jiajia, 2020. "Share green growth: Regional evaluation of green output performance in China," International Journal of Production Economics, Elsevier, vol. 219(C), pages 152-163.
    19. Ruomei Xu & Yanrui Wu & Chen Chen, 2022. "Agricultural green efficiency and productivity incorporating waste recycling," Australian Economic Papers, Wiley Blackwell, vol. 61(3), pages 635-660, September.
    20. Dan Pan & Yi Yu & Fanbin Kong, 2023. "Quantifying the Effectiveness of Environmental Regulations on Green Total Factor Productivity: Evidence Based on China’s Environmental Protection Interview Program," IJERPH, MDPI, vol. 20(4), pages 1-20, February.

    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:jijerp:v:19:y:2022:i:22:p:14941-:d:971491. 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.