IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i11p4424-d364607.html
   My bibliography  Save this article

A Framework for Assessing Green Capacity Utilization Considering CO 2 Emissions in China’s High-Tech Manufacturing Industry

Author

Listed:
  • Ya Wang

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
    School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Jiaofeng Pan

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
    School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Ruimin Pei

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
    School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Guoliang Yang

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
    School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Bowen Yi

    (School of Economics & Management, Beihang University, Beijing 100191, China)

Abstract

China’s high-tech manufacturing industry has become the mainstay of the country’s domestic industrial transformation and upgrading. However, in recent years, the industry has experienced huge blind expansion under policy stimulus, which is not good for long-term industrial development. Therefore, this article attempts to explore the extent to which such an important and critical industry in China utilizes its production capacity and provides a basis for future policymaking. Coupled with the country’s increasing emphasis on the green and low-carbon development of the industry, this article extends the green and low-carbon thinking based on capacity utilization, namely green capacity utilization (CU). On this basis, the study empirically investigates the green CU of the high-tech manufacturing industry in 28 provinces in mainland China from 2010 to 2015. In performing the investigation, the inputs were divided into (quasi-)fixed and variable inputs, and an assessment framework was established based on the data envelopment analysis (DEA) method. Moreover, optimal variable inputs are also available as by-products within the assessment framework. The results were as follows: First, China’s high-tech manufacturing industry showed an excellent overall performance in green CU. Moreover, half of the provinces were at fully utilized capacity, and half were under-utilized. On average, there was a slight deterioration in green CU. Second, the results showed regional differences. The western region had the highest green CU followed by the middle and northeastern regions, and the eastern region had the lowest green CU. Third, regarding the optimal variables inputs, the total amount of labor in China’s high-tech manufacturing industry met the demand, but the distribution was uneven. Fourth, the scale of traditional energy consumption needs to be reduced both in individual provinces and in general. These conclusions have implications for the formulation of policies to promote the green development of China’s high-tech manufacturing industry.

Suggested Citation

  • Ya Wang & Jiaofeng Pan & Ruimin Pei & Guoliang Yang & Bowen Yi, 2020. "A Framework for Assessing Green Capacity Utilization Considering CO 2 Emissions in China’s High-Tech Manufacturing Industry," Sustainability, MDPI, vol. 12(11), pages 1-25, May.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:11:p:4424-:d:364607
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/11/4424/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/11/4424/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ray, Subhash C., 2015. "Nonparametric measures of scale economies and capacity utilization: An application to U.S. manufacturing," European Journal of Operational Research, Elsevier, vol. 245(2), pages 602-611.
    2. Wang, Ya & Pan, Jiao-feng & Pei, Rui-min & Yi, Bo-Wen & Yang, Guo-liang, 2020. "Assessing the technological innovation efficiency of China's high-tech industries with a two-stage network DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    3. Wang, Chun-Hsien & Lu, Yung-Hsiang & Huang, Chin-Wei & Lee, Jun-Yen, 2013. "R&D, productivity, and market value: An empirical study from high-technology firms," Omega, Elsevier, vol. 41(1), pages 143-155.
    4. Zhu Liu & Dabo Guan & Wei Wei & Steven J. Davis & Philippe Ciais & Jin Bai & Shushi Peng & Qiang Zhang & Klaus Hubacek & Gregg Marland & Robert J. Andres & Douglas Crawford-Brown & Jintai Lin & Hongya, 2015. "Reduced carbon emission estimates from fossil fuel combustion and cement production in China," Nature, Nature, vol. 524(7565), pages 335-338, August.
    5. Li, Lan-bing & Liu, Bing-lian & Liu, Wei-lin & Chiu, Yung-Ho, 2017. "Efficiency evaluation of the regional high-tech industry in China: A new framework based on meta-frontier dynamic DEA analysis," Socio-Economic Planning Sciences, Elsevier, vol. 60(C), pages 24-33.
    6. Fare, Rolf & Grosskopf, Shawna & Kokkelenberg, Edward C, 1989. "Measuring Plant Capacity, Utilization and Technical Change: A Nonparametric Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(3), pages 655-666, August.
    7. Bronzini, Raffaello & Piselli, Paolo, 2016. "The impact of R&D subsidies on firm innovation," Research Policy, Elsevier, vol. 45(2), pages 442-457.
    8. Segerson, Kathleen & Squires, Dale, 1990. "On the measurement of economic capacity utilization for multi-product industries," Journal of Econometrics, Elsevier, vol. 44(3), pages 347-361, June.
    9. Zhang, Linyan & Chen, Kun, 2019. "Hierarchical network systems: An application to high-technology industry in China," Omega, Elsevier, vol. 82(C), pages 118-131.
    10. J. M. Cassels, 1937. "Excess Capacity and Monopolistic Competition," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 51(3), pages 426-443.
    11. Chen, Zhenling & Zhang, Xiaoling & Ni, Guohua, 2020. "Decomposing capacity utilization under carbon dioxide emissions reduction constraints in data envelopment analysis: An application to Chinese regions," Energy Policy, Elsevier, vol. 139(C).
    12. Chien-Hsun Chen & Hui-Tzu Shih, 2005. "High-Tech Industries in China," Books, Edward Elgar Publishing, number 3710.
    13. Roxani Karagiannis, 2015. "A system-of-equations two-stage DEA approach for explaining capacity utilization and technical efficiency," Annals of Operations Research, Springer, vol. 227(1), pages 25-43, April.
    14. Lindebo, Erik & Hoff, Ayoe & Vestergaard, Niels, 2007. "Revenue-based capacity utilisation measures and decomposition: The case of Danish North Sea trawlers," European Journal of Operational Research, Elsevier, vol. 180(1), pages 215-227, July.
    15. Chen, Xiafei & Liu, Zhiying & Zhu, Qingyuan, 2018. "Performance evaluation of China's high-tech innovation process: Analysis based on the innovation value chain," Technovation, Elsevier, vol. 74, pages 42-53.
    16. Shan, Yuli & Liu, Jianghua & Liu, Zhu & Xu, Xinwanghao & Shao, Shuai & Wang, Peng & Guan, Dabo, 2016. "New provincial CO2 emission inventories in China based on apparent energy consumption data and updated emission factors," Applied Energy, Elsevier, vol. 184(C), pages 742-750.
    17. Sheng-Hsiung Chiu & Tzu-Yu Lin & Hai-Lan Yang, 2020. "Measuring Energy Performance for Regional Sustainable Development in China: A New Framework based on a Dynamic Two-Stage SBM Approach," Sustainability, MDPI, vol. 12(7), pages 1-15, April.
    18. An Zhou & Shenhan Wu & Zhujie Chu & Wei-Chiao Huang, 2019. "Regional Differences in Municipal Solid Waste Collection Quantities in China," Sustainability, MDPI, vol. 11(15), pages 1-12, July.
    19. Tseng, Fang-Mei & Chiu, Yu-Jing & Chen, Ja-Shen, 2009. "Measuring business performance in the high-tech manufacturing industry: A case study of Taiwan's large-sized TFT-LCD panel companies," Omega, Elsevier, vol. 37(3), pages 686-697, June.
    20. Yang, Guo-liang & Fukuyama, Hirofumi, 2018. "Measuring the Chinese regional production potential using a generalized capacity utilization indicator," Omega, Elsevier, vol. 76(C), pages 112-127.
    21. Ji Guo & Dongdong Zhu & Xianhua Wu & Yaozhen Yan, 2017. "Study on Environment Performance Evaluation and Regional Differences of Strictly-Environmental-Monitored Cities in China," Sustainability, MDPI, vol. 9(12), pages 1-20, December.
    22. Berndt, Ernst R & Morrison, Catherine J, 1981. "Capacity Utilization Measures: Underlying Economic Theory and an Alternative Approach," American Economic Review, American Economic Association, vol. 71(2), pages 48-52, May.
    23. Yu, Ming-Miin & Chang, Yu-Chun & Chen, Li-Hsueh, 2016. "Measurement of airlines’ capacity utilization and cost gap: Evidence from low-cost carriers," Journal of Air Transport Management, Elsevier, vol. 53(C), pages 186-198.
    24. Sahoo, Biresh K. & Tone, Kaoru, 2009. "Decomposing capacity utilization in data envelopment analysis: An application to banks in India," European Journal of Operational Research, Elsevier, vol. 195(2), pages 575-594, June.
    25. Emrouznejad, Ali & Yang, Guo-liang, 2016. "CO2 emissions reduction of Chinese light manufacturing industries: A novel RAM-based global Malmquist–Luenberger productivity index," Energy Policy, Elsevier, vol. 96(C), pages 397-410.
    26. Zhuo-wan Liu & Tomas Balezentis & Yao-yao Song & Guo-liang Yang, 2019. "Estimating Capacity Utilization of Chinese State Farms," Sustainability, MDPI, vol. 11(18), pages 1-29, September.
    27. Yang, Guo-liang & Fukuyama, Hirofumi & Song, Yao-yao, 2019. "Estimating capacity utilization of Chinese manufacturing industries," Socio-Economic Planning Sciences, Elsevier, vol. 67(C), pages 94-110.
    28. Morrison, Catherine J, 1985. "Primal and Dual Capacity Utilization: An Application to Productivity Measurement in the U.S. Automobile Industry," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(4), pages 312-324, October.
    29. Wang, Feng & Wei, Xianjin & Liu, Juan & He, Lingyun & Gao, Mengnan, 2019. "Impact of high-speed rail on population mobility and urbanisation: A case study on Yangtze River Delta urban agglomeration, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 99-114.
    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. Zhang, Jingxiao & Jin, Weixing & Yang, Guo-liang & Li, Hui & Ke, Yongjian & Philbin, Simon Patrick, 2021. "Optimizing regional allocation of CO2 emissions considering output under overall efficiency," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).

    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. Yang, Guo-liang & Fukuyama, Hirofumi & Song, Yao-yao, 2019. "Estimating capacity utilization of Chinese manufacturing industries," Socio-Economic Planning Sciences, Elsevier, vol. 67(C), pages 94-110.
    2. Yao-yao Song & Xian-tong Ren & Guo-liang Yang, 2023. "Capacity utilization change over time," Journal of Productivity Analysis, Springer, vol. 59(1), pages 61-78, February.
    3. Yang, Guo-liang & Fukuyama, Hirofumi, 2018. "Measuring the Chinese regional production potential using a generalized capacity utilization indicator," Omega, Elsevier, vol. 76(C), pages 112-127.
    4. Chen, Zhenling & Zhang, Xiaoling & Ni, Guohua, 2020. "Decomposing capacity utilization under carbon dioxide emissions reduction constraints in data envelopment analysis: An application to Chinese regions," Energy Policy, Elsevier, vol. 139(C).
    5. Mohieddine Rahmouni, 2021. "Determinants of capacity utilisation by firms in developing countries: evidence from Tunisia," International Journal of Technological Learning, Innovation and Development, Inderscience Enterprises Ltd, vol. 13(3), pages 212-245.
    6. Ray, Subhash C. & Walden, John & Chen, Lei, 2021. "Economic measures of capacity utilization: A nonparametric short-run cost function analysis," European Journal of Operational Research, Elsevier, vol. 293(1), pages 375-387.
    7. Wang, Miao & Feng, Chao, 2023. "Measuring capacity utilization under the constraints of energy consumption and CO2 emissions using meta-frontier DEA: A case of China's non-ferrous metal industries," Resources Policy, Elsevier, vol. 80(C).
    8. Zhuo-wan Liu & Tomas Balezentis & Yao-yao Song & Guo-liang Yang, 2019. "Estimating Capacity Utilization of Chinese State Farms," Sustainability, MDPI, vol. 11(18), pages 1-29, September.
    9. Dale Squires & Kathleen Segerson, 2022. "Capacity and Capacity Utilization in Production Economics," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 24, pages 1001-1037, Springer.
    10. Fukuyama, Hirofumi & Song, Yao-yao & Ren, Xian-tong & Yang, Guo-liang, 2022. "Using a novel DEA-based model to investigate capacity utilization of Chinese firms," Omega, Elsevier, vol. 106(C).
    11. Ray, Subhash C., 2015. "Nonparametric measures of scale economies and capacity utilization: An application to U.S. manufacturing," European Journal of Operational Research, Elsevier, vol. 245(2), pages 602-611.
    12. Kerstens, Kristiaan & Sadeghi, Jafar & Van de Woestyne, Ignace, 2019. "Convex and nonconvex input-oriented technical and economic capacity measures: An empirical comparison," European Journal of Operational Research, Elsevier, vol. 276(2), pages 699-709.
    13. Bruno De Borger & Kristiaan Kerstens & Diego Prior & Ignace Van de Woestyne, 2013. "Static efficiency decompositions and capacity utilization: integrating economic and technical capacity notions," Applied Economics, Taylor & Francis Journals, vol. 45(24), pages 3529-3529, August.
    14. Giovanni Cesaroni & Kristiaan Kerstens & Ignace Van de Woestyne, 2017. "A New Input-Oriented Plant Capacity Notion: Definition and Empirical Comparison," Pacific Economic Review, Wiley Blackwell, vol. 22(4), pages 720-739, October.
    15. Wang, Ya & Pan, Jiao-feng & Pei, Rui-min & Yi, Bo-Wen & Yang, Guo-liang, 2020. "Assessing the technological innovation efficiency of China's high-tech industries with a two-stage network DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    16. Xiaoqing Chen & Kristiaan Kerstens, 2022. "Evaluating horizontal mergers in Swedish district courts using plant capacity concepts: with a focus on nonconvexity," Post-Print halshs-03924994, HAL.
    17. Sahoo, Biresh K. & Tone, Kaoru, 2009. "Decomposing capacity utilization in data envelopment analysis: An application to banks in India," European Journal of Operational Research, Elsevier, vol. 195(2), pages 575-594, June.
    18. Kristiaan Kerstens & Jafar Sadeghi & Ignace Van de Woestyne, 2020. "Plant capacity notions in a non-parametric framework: a brief review and new graph or non-oriented plant capacities," Annals of Operations Research, Springer, vol. 288(2), pages 837-860, May.
    19. E. Grifell-Tatjé & C. Lovell, 2014. "Productivity, price recovery, capacity constraints and their financial consequences," Journal of Productivity Analysis, Springer, vol. 41(1), pages 3-17, February.
    20. James Kirkley & Catherine Morrison Paul & Dale Squires, 2002. "Capacity and Capacity Utilization in Common-pool Resource Industries," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 22(1), pages 71-97, June.

    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:jsusta:v:12:y:2020:i:11:p:4424-:d:364607. 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.