IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v122y2020i1d10.1007_s11192-019-03282-x.html
   My bibliography  Save this article

Does gender structure influence R&D efficiency? A regional perspective

Author

Listed:
  • Mingting Kou

    (University of Sciences and Technology Beijing)

  • Yi Zhang

    (Guangdong Ocean University)

  • Yu Zhang

    (Chinese Academy of Sciences)

  • Kaihua Chen

    (Chinese Academy of Sciences)

  • Jiancheng Guan

    (University of Chinese Academy of Sciences)

  • Senmao Xia

    (Coventry University)

Abstract

The gender structure in research and development (R&D) activities has received more and more attention in terms of its increasing importance in R&D management, but it is still not clear what the R&D efficiency discrepancy between female and male personnel is in the science and technology (S&T) field and whether the gender structure affects the R&D efficiency. Based on the region-level panel dataset of China’s research institutes, this study uses four types of R&D outputs (papers, books, patents and standards) together and individually to measure R&D efficiency score to reveal this topic. When four types of R&D outputs are jointly considered, this paper applies the multi-output stochastic frontier analysis and finds that in general the higher proportion of male R&D personnel produces the higher R&D efficiency. Nevertheless, in terms of S&T papers or S&T books as a single R&D output, we find that the higher proportion of female R&D personnel leads to the higher R&D efficiency. On the contrary, the R&D efficiency is lower with the higher proportion of female R&D personnel when the single R&D output is measured by invention patent applications or national/industrial standards, respectively. Our findings suggest that the female R&D personnel are more effective in conducting scientific research activities, while their counterparts are more effective in doing technology development activities.

Suggested Citation

  • Mingting Kou & Yi Zhang & Yu Zhang & Kaihua Chen & Jiancheng Guan & Senmao Xia, 2020. "Does gender structure influence R&D efficiency? A regional perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 477-501, January.
  • Handle: RePEc:spr:scient:v:122:y:2020:i:1:d:10.1007_s11192-019-03282-x
    DOI: 10.1007/s11192-019-03282-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-019-03282-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11192-019-03282-x?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Alonso-Borrego, Cesar & Arellano, Manuel, 1999. "Symmetrically Normalized Instrumental-Variable Estimation Using Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 36-49, January.
    3. Frietsch, Rainer & Haller, Inna & Funken-Vrohlings, Melanie & Grupp, Hariolf, 2009. "Gender-specific patterns in patenting and publishing," Research Policy, Elsevier, vol. 38(4), pages 590-599, May.
    4. Contini, Dalit & Tommaso, Maria Laura Di & Mendolia, Silvia, 2017. "The gender gap in mathematics achievement: Evidence from Italian data," Economics of Education Review, Elsevier, vol. 58(C), pages 32-42.
    5. Siegel, Donald S. & Waldman, David & Link, Albert, 2003. "Assessing the impact of organizational practices on the relative productivity of university technology transfer offices: an exploratory study," Research Policy, Elsevier, vol. 32(1), pages 27-48, January.
    6. Jane E. Dutton & Robert B. Duncan, 1987. "The influence of the strategic planning process on strategic change," Strategic Management Journal, Wiley Blackwell, vol. 8(2), pages 103-116, March.
    7. Ye, Dezhu & Deng, Jie & Liu, Yi & Szewczyk, Samuel H. & Chen, Xiao, 2019. "Does board gender diversity increase dividend payouts? Analysis of global evidence," Journal of Corporate Finance, Elsevier, vol. 58(C), pages 1-26.
    8. Michael Fritsch & Viktor Slavtchev, 2007. "What determines the efficiency of regional innovation systems?," Jena Economics Research Papers 2007-006, Friedrich-Schiller-University Jena.
    9. Meng, Yu, 2016. "Collaboration patterns and patenting: Exploring gender distinctions," Research Policy, Elsevier, vol. 45(1), pages 56-67.
    10. Fu, Xiaolan & Yang, Qing Gong, 2009. "Exploring the cross-country gap in patenting: A Stochastic Frontier Approach," Research Policy, Elsevier, vol. 38(7), pages 1203-1213, September.
    11. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    12. Hall, Bronwyn H. & Mairesse, Jacques, 1995. "Exploring the relationship between R&D and productivity in French manufacturing firms," Journal of Econometrics, Elsevier, vol. 65(1), pages 263-293, January.
    13. Michael Fritsch & Viktor Slavtchev, 2011. "Determinants of the Efficiency of Regional Innovation Systems," Regional Studies, Taylor & Francis Journals, vol. 45(7), pages 905-918.
    14. Elena Cefis & Orietta Marsili, 2011. "Born to flip. Exit decisions of entrepreneurial firms in high-tech and low-tech industries," Journal of Evolutionary Economics, Springer, vol. 21(3), pages 473-498, August.
    15. Zvi Griliches, 1998. "Issues in Assessing the Contribution of Research and Development to Productivity Growth," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 17-45, National Bureau of Economic Research, Inc.
    16. Roland G. Fryer & Steven D. Levitt, 2010. "An Empirical Analysis of the Gender Gap in Mathematics," American Economic Journal: Applied Economics, American Economic Association, vol. 2(2), pages 210-240, April.
    17. Jaideep Anand & Raffaele Oriani & Roberto S. Vassolo, 2010. "Alliance Activity as a Dynamic Capability in the Face of a Discontinuous Technological Change," Organization Science, INFORMS, vol. 21(6), pages 1213-1232, December.
    18. Guan, JianCheng & Zuo, KaiRui & Chen, KaiHua & Yam, Richard C.M., 2016. "Does country-level R&D efficiency benefit from the collaboration network structure?," Research Policy, Elsevier, vol. 45(4), pages 770-784.
    19. Szu-chia S. Lo, 2010. "Scientific linkage of science research and technology development: a case of genetic engineering research," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 109-120, January.
    20. Hunt, Jennifer & Garant, Jean-Philippe & Herman, Hannah & Munroe, David J., 2013. "Why are women underrepresented amongst patentees?," Research Policy, Elsevier, vol. 42(4), pages 831-843.
    21. Jappelli, Tullio & Nappi, Carmela Anna & Torrini, Roberto, 2017. "Gender effects in research evaluation," Research Policy, Elsevier, vol. 46(5), pages 911-924.
    22. Madjid Tavana & Rashed Khanjani Shiraz & Adel Hatami-Marbini, 2014. "A new chance-constrained DEA model with birandom input and output data," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(12), pages 1824-1839, December.
    23. Melissa A. Schilling & Corey C. Phelps, 2007. "Interfirm Collaboration Networks: The Impact of Large-Scale Network Structure on Firm Innovation," Management Science, INFORMS, vol. 53(7), pages 1113-1126, July.
    24. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    25. Wang, Eric C. & Huang, Weichiao, 2007. "Relative efficiency of R&D activities: A cross-country study accounting for environmental factors in the DEA approach," Research Policy, Elsevier, vol. 36(2), pages 260-273, March.
    26. Tom Broekel, 2015. "Do Cooperative Research and Development (R&D) Subsidies Stimulate Regional Innovation Efficiency? Evidence from Germany," Regional Studies, Taylor & Francis Journals, vol. 49(7), pages 1087-1110, July.
    27. Michael Fritsch & Viktor Slavtchev, 2010. "How does industry specialization affect the efficiency of regional innovation systems?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 45(1), pages 87-108, August.
    28. Siegel, Donald S. & Westhead, Paul & Wright, Mike, 2003. "Assessing the impact of university science parks on research productivity: exploratory firm-level evidence from the United Kingdom," International Journal of Industrial Organization, Elsevier, vol. 21(9), pages 1357-1369, November.
    29. Wullum Nielsen, Mathias & Börjeson, Love, 2019. "Gender diversity in the management field: Does it matter for research outcomes?," Research Policy, Elsevier, vol. 48(7), pages 1617-1632.
    30. Wang, Eric C., 2007. "R&D efficiency and economic performance: A cross-country analysis using the stochastic frontier approach," Journal of Policy Modeling, Elsevier, vol. 29(2), pages 345-360.
    31. Géraldine Henningsen & Arne Henningsen & Uwe Jensen, 2015. "A Monte Carlo study on multiple output stochastic frontiers: a comparison of two approaches," Journal of Productivity Analysis, Springer, vol. 44(3), pages 309-320, December.
    32. Goto, Akira & Suzuki, Kazuyuki, 1989. "R&D Capital, Rate of Return on R&D Investment and Spillover of R&D in Japanese Manufacturing Industries," The Review of Economics and Statistics, MIT Press, vol. 71(4), pages 555-564, November.
    33. Laure Turner, 2009. "Gender diversity and innovative performance," International Journal of Innovation and Sustainable Development, Inderscience Enterprises Ltd, vol. 4(2/3), pages 123-134.
    34. Jung, Taehyun & Ejermo, Olof, 2014. "Demographic patterns and trends in patenting: Gender, age, and education of inventors," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 110-124.
    35. Kaihua Chen & Jiancheng Guan, 2012. "Measuring the Efficiency of China's Regional Innovation Systems: Application of Network Data Envelopment Analysis (DEA)," Regional Studies, Taylor & Francis Journals, vol. 46(3), pages 355-377, April.
    36. Furman, Jeffrey L. & Porter, Michael E. & Stern, Scott, 2002. "The determinants of national innovative capacity," Research Policy, Elsevier, vol. 31(6), pages 899-933, August.
    37. Kim, Bowon & Oh, Heungshik, 2002. "An effective R&D performance measurement system: survey of Korean R&D researchers," Omega, Elsevier, vol. 30(1), pages 19-31, February.
    38. Zhang, Yi & Chen, Kaihua & Fu, Xiaolan, 2019. "Scientific effects of Triple Helix interactions among research institutes, industries and universities," Technovation, Elsevier, vol. 86, pages 33-47.
    39. Lerchenmueller, Marc J. & Sorenson, Olav, 2018. "The gender gap in early career transitions in the life sciences," Research Policy, Elsevier, vol. 47(6), pages 1007-1017.
    40. Tom Broekel, 2012. "Collaboration Intensity and Regional Innovation Efficiency in Germany—A Conditional Efficiency Approach," Industry and Innovation, Taylor & Francis Journals, vol. 19(2), pages 155-179, February.
    41. Li, Xibao, 2009. "China's regional innovation capacity in transition: An empirical approach," Research Policy, Elsevier, vol. 38(2), pages 338-357, March.
    42. TAVANA, Madjid & KHANJANI SHIRAZ, Rashed & HATAMI-MARBINI, Adel, 2014. "A new chance-constrained DEA model with birandom input and output data," LIDAM Reprints CORE 2637, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    43. Yi Zhang & Kaihua Chen & Guilong Zhu & Richard C. M. Yam & Jiancheng Guan, 2016. "Inter-organizational scientific collaborations and policy effects: an ego-network evolutionary perspective of the Chinese Academy of Sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1383-1415, September.
    44. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    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. Meng, Qiaoyu & Li, Yi & Cao, Qinwei, 2024. "The paradox analysis and functional mechanism between R&D efficiency and transformation effect: Evidence from key universities in China," Technovation, Elsevier, vol. 130(C).
    2. Loarne-Lemaire, Séverine Le & Bertrand, Gaël & Razgallah, Meriam & Maalaoui, Adnane & Kallmuenzer, Andreas, 2021. "Women in innovation processes as a solution to climate change: A systematic literature review and an agenda for future research," Technological Forecasting and Social Change, Elsevier, vol. 164(C).
    3. Zhang, Ming-Ze & Wang, Tang-Rong & Lyu, Peng-Hui & Chen, Qi-Mei & Li, Ze-Xia & Ngai, Eric W.T., 2024. "Impact of gender composition of academic teams on disruptive output," Journal of Informetrics, Elsevier, vol. 18(2).
    4. Steven T. Joanis & Vivek H. Patil, 2022. "First-author gender differentials in business journal publishing: top journals versus the rest," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(2), pages 733-761, February.
    5. Mehdi Rhaiem & Nabil Amara, 2020. "Determinants of research efficiency in Canadian business schools: evidence from scholar-level data," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 53-99, October.

    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. Kyriakos Drivas & Claire Economidou & Efthymios G. Tsionas, 2018. "Production of output and ideas: efficiency and growth patterns in the United States," Regional Studies, Taylor & Francis Journals, vol. 52(1), pages 105-118, January.
    2. Jianping Liu & Kai Lu & Shixiong Cheng, 2018. "International R&D Spillovers and Innovation Efficiency," Sustainability, MDPI, vol. 10(11), pages 1-23, October.
    3. Yang, Zhenbing & Shao, Shuai & Li, Chengyu & Yang, Lili, 2020. "Alleviating the misallocation of R&D inputs in China's manufacturing sector: From the perspectives of factor-biased technological innovation and substitution elasticity," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    4. Chen Kaihua & Kou Mingting, 2014. "Staged efficiency and its determinants of regional innovation systems: a two-step analytical procedure," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 52(2), pages 627-657, March.
    5. Chen, Kaihua & Kou, Mingting & Fu, Xiaolan, 2018. "Evaluation of multi-period regional R&D efficiency: An application of dynamic DEA to China's regional R&D systems," Omega, Elsevier, vol. 74(C), pages 103-114.
    6. Cullmann, Astrid & Zloczysti, Petra, 2013. "Towards an Efficient Use of R&D ? Accounting for Heterogeneity in the OECD," CEPR Discussion Papers 9345, C.E.P.R. Discussion Papers.
    7. Xiafei Chen & Zhiying Liu & Chaoliang Ma, 2017. "Chinese innovation-driving factors: regional structure, innovation effect, and economic development—empirical research based on panel data," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 59(1), pages 43-68, July.
    8. Tom Broekel & Nicky Rogge & Thomas Brenner, 2018. "The innovation efficiency of German regions – a shared-input DEA approach," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 38(1), pages 77-109, February.
    9. Cristian Barra & Nazzareno Ruggiero, 2022. "How do dimensions of institutional quality improve Italian regional innovation system efficiency? The Knowledge production function using SFA," Journal of Evolutionary Economics, Springer, vol. 32(2), pages 591-642, April.
    10. Hong, Jin & Feng, Bing & Wu, Yanrui & Wang, Liangbing, 2016. "Do government grants promote innovation efficiency in China's high-tech industries?," Technovation, Elsevier, vol. 57, pages 4-13.
    11. Shi, Xing & Wu, Yanrui & Fu, Dahai, 2020. "Does University-Industry collaboration improve innovation efficiency? Evidence from Chinese Firms⋄," Economic Modelling, Elsevier, vol. 86(C), pages 39-53.
    12. Barra, Cristian & Zotti, Roberto, 2015. "Regional innovation system (in)efficiency and its determinants: an empirical evidence from Italian regions," MPRA Paper 67067, University Library of Munich, Germany.
    13. Stepan Zemtsov & Maxim Kotsemir, 2019. "An assessment of regional innovation system efficiency in Russia: the application of the DEA approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 375-404, August.
    14. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    15. Sabrina Auci & Nicolò Barbieri & Manuela Coromaldi & Donatella Vignani, 2021. "Innovation for climate change adaptation and technical efficiency: an empirical analysis in the European agricultural sector," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(2), pages 597-623, July.
    16. Cristian Barra & Roberto Zotti, 2018. "The contribution of university, private and public sector resources to Italian regional innovation system (in)efficiency," The Journal of Technology Transfer, Springer, vol. 43(2), pages 432-457, April.
    17. Zhang, Anming & Zhang, Yimin & Zhao, Ronald, 2003. "A study of the R&D efficiency and productivity of Chinese firms," Journal of Comparative Economics, Elsevier, vol. 31(3), pages 444-464, September.
    18. Chen, Kaihua & Guan, Jiancheng, 2011. "Mapping the functionality of China's regional innovation systems: A structural approach," China Economic Review, Elsevier, vol. 22(1), pages 11-27, March.
    19. Chen, Xiafei & Liu, Zhiying & Zhu, Qingyuan, 2020. "Reprint of "Performance evaluation of China's high-tech innovation process :Analysis based on the innovation value chain"," Technovation, Elsevier, vol. 94.
    20. 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.

    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:spr:scient:v:122:y:2020:i:1:d:10.1007_s11192-019-03282-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.