IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0233093.html
   My bibliography  Save this article

Regional technology gap and innovation efficiency trap in Chinese pharmaceutical manufacturing industry

Author

Listed:
  • Hongbo Lai
  • Hao Shi
  • Yang Zhou

Abstract

Objective: There is a huge technology gap between regions in Chinese pharmaceutical manufacturing industry, which is the reality that must be faced. However, most of the available researches on innovation efficiency are based on the logic of a given technology level, ignoring the regional technological gap. This paper will stand from the perspective of technology gap and re-examine the innovation efficiency of pharmaceutical manufacturing industry in different regions of China and its impact on regional industrial competitiveness. Methods: We use the DEA-BCC input-oriented model to measure innovation efficiency of 28 provinces from the data of China's pharmaceutical manufacturing industry. The threshold model is constructed, with technology level as the threshold variable, innovation efficiency as the main explanatory variable, and industrial competitiveness as the dependent variable. In the threshold model, 28 regions are divided into three technical groups, and further, the impact of innovation efficiency on industrial competitiveness in different groups is analyzed and compared. Results: According to the empirical research results, an U-shaped efficiency trap has been found in Chinese pharmaceutical manufacturing industry, and the areas with medium technical level are at the bottom of the trap. The improvement of innovation efficiency does not necessarily promote the improvement of regional industrial competitiveness. Only in high-level and low-level technology groups, innovation efficiency has effectively promoted the improvement of industrial competitiveness. In addition, the intensity of R&D investment has a similar impact on industrial competitiveness. Conclusions: The findings suggest that, regions in the efficiency trap should strive to seek opportunities for industrial transformation and focus on the industrial transformation of new technology, new industry and new opportunities, instead of blindly pursuing R&D investment intensity and superstitious innovation efficiency. So as to free up innovation resources for high-quality technological innovation in other regions. In addition, the Chinese government should make use of its public hospital system to normalize and expand the centralized drug procurement and eliminate the low-quality innovation.

Suggested Citation

  • Hongbo Lai & Hao Shi & Yang Zhou, 2020. "Regional technology gap and innovation efficiency trap in Chinese pharmaceutical manufacturing industry," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-17, May.
  • Handle: RePEc:plo:pone00:0233093
    DOI: 10.1371/journal.pone.0233093
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0233093
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0233093&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0233093?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. repec:fth:harver:1473 is not listed on IDEAS
    2. Hagedoorn, John & Cloodt, Myriam, 2003. "Measuring innovative performance: is there an advantage in using multiple indicators?," Research Policy, Elsevier, vol. 32(8), pages 1365-1379, September.
    3. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    4. Poh Wong & Yuen Ho & Erkko Autio, 2005. "Entrepreneurship, Innovation and Economic Growth: Evidence from GEM data," Small Business Economics, Springer, vol. 24(3), pages 335-350, January.
    5. H.S. Pannu & U. Dinesh Kumar & Jamal A. Farooquie, 2011. "Efficiency and productivity analysis of Indian pharmaceutical industry using data envelopment analysis," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 10(1), pages 121-136.
    6. Bee Yan Aw & Mark J. Roberts & Tor Winston, 2007. "Export Market Participation, Investments in R&D and Worker Training, and the Evolution of Firm Productivity," The World Economy, Wiley Blackwell, vol. 30(1), pages 83-104, January.
    7. Hashimoto, Akihiro & Haneda, Shoko, 2008. "Measuring the change in R&D efficiency of the Japanese pharmaceutical industry," Research Policy, Elsevier, vol. 37(10), pages 1829-1836, December.
    8. Zvi Griliches, 1998. "Patent Statistics as Economic Indicators: A Survey," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 287-343, National Bureau of Economic Research, Inc.
    9. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    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. Yunyao Li & Yanji Ma, 2022. "Research on Industrial Innovation Efficiency and the Influencing Factors of the Old Industrial Base Based on the Lock-In Effect, a Case Study of Jilin Province, China," Sustainability, MDPI, vol. 14(19), pages 1-23, October.
    2. Xueling Guan & Lijiang Chen & Qing Xia & Zhaohui Qin, 2022. "Innovation Efficiency of Chinese Pharmaceutical Manufacturing Industry from the Perspective of Innovation Ecosystem," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    3. Atta Mills, Ebenezer Fiifi Emire & Zeng, Kailin & Fangbiao, Liu & Fangyan, Li, 2021. "Modeling innovation efficiency, its micro-level drivers, and its impact on stock returns," Chaos, Solitons & Fractals, Elsevier, vol. 152(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. Duk Hee Lee & Il Won Seo & Ho Chull Choe & Hee Dae Kim, 2012. "Collaboration network patterns and research performance: the case of Korean public research institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(3), pages 925-942, June.
    2. Stiebale, Joel, 2016. "Cross-border M&As and innovative activity of acquiring and target firms," Journal of International Economics, Elsevier, vol. 99(C), pages 1-15.
    3. Varun Mahajan & D. K. Nauriyal & S. P. Singh, 2020. "Domestic market competitiveness of Indian drug and pharmaceutical industry," Review of Managerial Science, Springer, vol. 14(3), pages 519-559, June.
    4. Guan, Jiancheng & Chen, Kaihua, 2012. "Modeling the relative efficiency of national innovation systems," Research Policy, Elsevier, vol. 41(1), pages 102-115.
    5. Halkos, George & Tzeremes, Nickolaos, 2011. "The effect of national culture on countries’ innovation efficiency," MPRA Paper 30100, University Library of Munich, Germany.
    6. Sandro Mendonca & Hugo Confraria & Manuel Mira Godinho, 2021. "Appropriating the returns of patent statistics: Take-up and development in the wake of Zvi Griliches," SPRU Working Paper Series 2021-07, SPRU - Science Policy Research Unit, University of Sussex Business School.
    7. Jung Ho Park & Kwangsoo Shin, 2018. "Efficiency of Government-Sponsored R&D Projects: A Metafrontier DEA Approach," Sustainability, MDPI, vol. 10(7), pages 1-17, July.
    8. Jaswinder Singh & Parminder Singh, 2017. "Does TRIPS Drive to Productivity Growth in Indian Pharmaceutical Industry," Paradigm, , vol. 21(2), pages 211-228, December.
    9. Varun Mahajan & D. K. Nauriyal & S. P. Singh, 2018. "Efficiency and Its Determinants: Panel Data Evidence from the Indian Pharmaceutical Industry," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 12(1), pages 19-40, February.
    10. Nguyen, Quoc Phu & Vo, Duc Hong, 2022. "Artificial intelligence and unemployment:An international evidence," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 40-55.
    11. Hsu, Fang-Ming & Hsueh, Chao-Chih, 2009. "Measuring relative efficiency of government-sponsored R&D projects: A three-stage approach," Evaluation and Program Planning, Elsevier, vol. 32(2), pages 178-186, May.
    12. Wang, Qunwei & Hang, Ye & Sun, Licheng & Zhao, Zengyao, 2016. "Two-stage innovation efficiency of new energy enterprises in China: A non-radial DEA approach," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 254-261.
    13. Kontolaimou, Alexandra & Giotopoulos, Ioannis & Tsakanikas, Aggelos, 2016. "A typology of European countries based on innovation efficiency and technology gaps: The role of early-stage entrepreneurship," Economic Modelling, Elsevier, vol. 52(PB), pages 477-484.
    14. Su, Hsin-Ning & Moaniba, Igam M., 2017. "Investigating the dynamics of interdisciplinary evolution in technology developments," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 12-23.
    15. Carlino, Gerald & Kerr, William R., 2015. "Agglomeration and Innovation," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 349-404, Elsevier.
    16. Jianyu Han & Min He & Honglin Xie & Tao Ding, 2022. "The Impact of Scientific and Technological Innovation on High-Quality Economic Development in the Yangtze River Delta Region," Sustainability, MDPI, vol. 14(21), pages 1-19, November.
    17. Jianghua Zhou & Rui Wu & Jizhen Li, 2019. "More ties the merrier? Different social ties and firm innovation performance," Asia Pacific Journal of Management, Springer, vol. 36(2), pages 445-471, June.
    18. Michael K. Fung, 2019. "Fraudulent Financial Reporting and Technological Capability in the Information Technology Sector: A Resource-Based Perspective," Journal of Business Ethics, Springer, vol. 156(2), pages 577-589, May.
    19. Noailly, Joëlle, 2012. "Improving the energy efficiency of buildings: The impact of environmental policy on technological innovation," Energy Economics, Elsevier, vol. 34(3), pages 795-806.
    20. Dziallas, Marisa & Blind, Knut, 2019. "Innovation indicators throughout the innovation process: An extensive literature analysis," Technovation, Elsevier, vol. 80, pages 3-29.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0233093. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.