IDEAS home Printed from https://ideas.repec.org/a/gam/jecomi/v13y2025i4p90-d1621896.html
   My bibliography  Save this article

Evaluation of Operational Efficiency in China’s Pharmaceutical Industry and Analysis of Environmental Impacts

Author

Listed:
  • Jiaqiang Sun

    (Department of Social Science & Management, Faculty of Humanities, Management & Science, Universiti Putra Malaysia, Bintulu Campus, Nyabau Road, Bintulu 97008, Sarawak, Malaysia
    Strategic Research Center of Chengdu Maidison Pharmaceutical Technology Co., Ltd., No. 733, East Section, Hubin Road, Xinglong Subdistrict, Tianfu New Area, Chengdu 610000, China)

  • Anita Binti Rosli

    (Department of Social Science & Management, Faculty of Humanities, Management & Science, Universiti Putra Malaysia, Bintulu Campus, Nyabau Road, Bintulu 97008, Sarawak, Malaysia)

  • Adrian Daud

    (Department of Social Science & Management, Faculty of Humanities, Management & Science, Universiti Putra Malaysia, Bintulu Campus, Nyabau Road, Bintulu 97008, Sarawak, Malaysia
    Institute of Ecosystem Science Borneo, Universiti Putra Malaysia, Bintulu Sarawak Campus, Nyabau Road, Bintulu 97008, Sarawak, Malaysia)

  • Xia Yan

    (Department of Social Science & Management, Faculty of Humanities, Management & Science, Universiti Putra Malaysia, Bintulu Campus, Nyabau Road, Bintulu 97008, Sarawak, Malaysia)

Abstract

The pharmaceutical industry is a cornerstone of national economies and plays a critical role in public health. However, China’s pharmaceutical industry faces significant challenges, including regional disparities in development. The existing research on operational efficiency evaluation primarily focuses on financial or innovation metrics, lacking a comprehensive approach. Moreover, studies on the environmental impact on operational efficiency often rely on a limited set of indicators, failing to offer a holistic understanding of how environmental factors influence efficiency. This study aims to address these gaps by comprehensively evaluating operational efficiency and analyzing the impact of broader environmental factors on efficiency. To achieve these objectives, the study employs a Three-Stage Data Envelopment Analysis method combined with Principal Component Analysis to evaluate the operational efficiency of the pharmaceutical industry across 31 provinces in China, considering both financial and innovation dimensions.The findings reveal that overall efficiency has improved annually, with regional disparities gradually narrowing. Specifically, innovation capability and innovation environment have a positive impact on operational efficiency, while living standards and openness exhibit a negative correlation. Additionally, the current environmental conditions in the northwestern region are found to be conducive to the development of the pharmaceutical industry. This study is the first to integrate three-stage data envelopment analysis with principal component analysis, constructing a comprehensive framework for analyzing the relationship between environmental factors and operational efficiency. The results provide empirical evidence for policymakers aiming to enhance the efficiency of the pharmaceutical industry.

Suggested Citation

  • Jiaqiang Sun & Anita Binti Rosli & Adrian Daud & Xia Yan, 2025. "Evaluation of Operational Efficiency in China’s Pharmaceutical Industry and Analysis of Environmental Impacts," Economies, MDPI, vol. 13(4), pages 1-35, March.
  • Handle: RePEc:gam:jecomi:v:13:y:2025:i:4:p:90-:d:1621896
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7099/13/4/90/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7099/13/4/90/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fernando Gascón & Jesús Lozano & Borja Ponte & David Fuente, 2017. "Measuring the efficiency of large pharmaceutical companies: an industry analysis," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(5), pages 587-608, June.
    2. Grossman, Sanford J & Stiglitz, Joseph E, 1977. "On Value Maximization and Alternative Objectives of the Firm," Journal of Finance, American Finance Association, vol. 32(2), pages 389-402, May.
    3. Haitovsky, Yoel, 1969. "Multicollinearity in Regression Analysis: Comment," The Review of Economics and Statistics, MIT Press, vol. 51(4), pages 486-489, November.
    4. 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)

    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. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    2. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, October.
    3. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    4. Chen, Ya & Pan, Yongbin & Liu, Haoxiang & Wu, Huaqing & Deng, Guangwei, 2023. "Efficiency analysis of Chinese universities with shared inputs: An aggregated two-stage network DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    5. 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.
    6. Ashrafi, Ali & Seow, Hsin-Vonn & Lee, Lai Soon & Lee, Chew Ging, 2013. "The efficiency of the hotel industry in Singapore," Tourism Management, Elsevier, vol. 37(C), pages 31-34.
    7. Juan Aparicio & Jesus T. Pastor & Jose L. Sainz-Pardo & Fernando Vidal, 2020. "Estimating and decomposing overall inefficiency by determining the least distance to the strongly efficient frontier in data envelopment analysis," Operational Research, Springer, vol. 20(2), pages 747-770, June.
    8. Davtalab-Olyaie, Mostafa & Begen, Mehmet A. & Yang, Zijiang & Asgharian, Masoud, 2024. "Incentivization in centrally managed systems: Inconsistencies resolution," Omega, Elsevier, vol. 129(C).
    9. Qin, Quande & Li, Xin & Li, Li & Zhen, Wei & Wei, Yi-Ming, 2017. "Air emissions perspective on energy efficiency: An empirical analysis of China’s coastal areas," Applied Energy, Elsevier, vol. 185(P1), pages 604-614.
    10. Atris, Amani Mohammed & Goto, Mika, 2019. "Vertical structure and efficiency assessment of the US oil and gas companies," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    11. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    12. Mohammad Nourani & Qian Long Kweh & Evelyn Shyamala Devadason & V.G.R. Chandran, 2020. "A decomposition analysis of managerial efficiency for the insurance companies: A data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(6), pages 885-901, September.
    13. Honma, Satoshi, 2012. "Environmental and economic efficiencies in the Asia-Pacific region," MPRA Paper 43361, University Library of Munich, Germany.
    14. Mohammad Tavassoli & Mahsa Ghandehari & Masoud Taherinia, 2023. "Rang-adjusted measure: modelling and computational aspects from internal and external perspectives for network DEA," Operational Research, Springer, vol. 23(4), pages 1-34, December.
    15. Bao Jiang & Enxin Chi & Jian Li, 2022. "Uncertain Data Envelopment Analysis for Cross Efficiency Evaluation with Imprecise Data," Mathematics, MDPI, vol. 10(13), pages 1-9, June.
    16. Jia Li & Yahong Zheng & Bing Liu & Yanyi Chen & Zhihang Zhong & Chenyu Dong & Chaoqun Wang, 2024. "The Synergistic Relationship between Low-Carbon Development of Road Freight Transport and Its Economic Efficiency—A Case Study of Wuhan, China," Sustainability, MDPI, vol. 16(7), pages 1-21, March.
    17. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    18. Su Yang & Jie Shen & Hongyang Li & Beibei Zhang & Jinchao Ma & Baoquan Cheng, 2023. "Unraveling the U-Shaped Linkage: Population Aging and Carbon Efficiency in the Construction Industry," Sustainability, MDPI, vol. 15(17), pages 1-15, September.
    19. Eder, Andreas, 2024. "The effect of land fragmentation on risk and technical efficiency of crop farms," FORLand Working Papers 31 (2024), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    20. Zhuang Miao & Tomas Baležentis & Zhihua Tian & Shuai Shao & Yong Geng & Rui Wu, 2019. "Environmental Performance and Regulation Effect of China’s Atmospheric Pollutant Emissions: Evidence from “Three Regions and Ten Urban Agglomerations”," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(1), pages 211-242, September.

    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:jecomi:v:13:y:2025:i:4:p:90-:d:1621896. 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.