IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i7p3008-d343261.html
   My bibliography  Save this article

Sustainable Innovation Governance: An Analysis of Regional Innovation with a Super Efficiency Slack-Based Measure Model

Author

Listed:
  • Kai Xu

    (School of Economics and Management, Tongji University, Shanghai 200092, China)

  • Lawrence Loh

    (Centre for Governance, Institutions and Organisations, NUS Business School, National University of Singapore, 1 Business Link, Singapore 117592, Singapore)

  • Qiang Chen

    (School of Economics and Management, Tongji University, Shanghai 200092, China)

Abstract

As China is undergoing economic transformation and facing increasing energy and environmental problems, it is essential to pay special attention to sustainable innovation governance. This research took industrial waste and total energy consumption into consideration and uses a super efficiency slack-based measure (SBM) model to empirically evaluate the regional innovation efficiency of Chinese provinces. The results showed that the efficiency of China’s regional sustainable innovation has not changed significantly over recent years. In addition, the results also showed large and varying degrees of innovation efficiency across different provinces. Eastern China, in comparison to central and western China, showed higher innovation efficiency. In addition, we found a slightly increasing trend in terms of innovation efficiency disparities between the three areas. On the basis of these findings, the reasons for the innovation efficiency gap between different regions were analyzed. The impacts of influential factors on sustainable innovation efficiency were further explored. We found that technology market maturity affected sustainable innovation efficiency positively, while government funding had a negative impact on sustainable innovation efficiency. Industrial structure and environmental regulations had no significant effect on sustainable innovation efficiency. Finally, some implications for improving governance performance in terms of sustainable innovation were provided.

Suggested Citation

  • Kai Xu & Lawrence Loh & Qiang Chen, 2020. "Sustainable Innovation Governance: An Analysis of Regional Innovation with a Super Efficiency Slack-Based Measure Model," Sustainability, MDPI, vol. 12(7), pages 1-19, April.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:7:p:3008-:d:343261
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/7/3008/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/7/3008/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chien-Ming Chen & Magali A. Delmas & Marvin B. Lieberman, 2015. "Production frontier methodologies and efficiency as a performance measure in strategic management research," Strategic Management Journal, Wiley Blackwell, vol. 36(1), pages 19-36, January.
    2. Stefan Ambec & Mark A. Cohen & Stewart Elgie & Paul Lanoie, 2013. "The Porter Hypothesis at 20: Can Environmental Regulation Enhance Innovation and Competitiveness?," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 7(1), pages 2-22, January.
    3. Chaofan Chen & Jing Han & Peilei Fan, 2016. "Measuring the Level of Industrial Green Development and Exploring Its Influencing Factors: Empirical Evidence from China’s 30 Provinces," Sustainability, MDPI, vol. 8(2), pages 1-20, February.
    4. Emrouznejad, Ali & Yang, Guo-liang, 2018. "A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 4-8.
    5. Howell, Anthony, 2015. "‘Indigenous’ innovation with heterogeneous risk and new firm survival in a transitioning Chinese economy," Research Policy, Elsevier, vol. 44(10), pages 1866-1876.
    6. Cooke, Philip & Gomez Uranga, Mikel & Etxebarria, Goio, 1997. "Regional innovation systems: Institutional and organisational dimensions," Research Policy, Elsevier, vol. 26(4-5), pages 475-491, December.
    7. Li, Huanan & Mu, Hailin & Zhang, Ming & Gui, Shusen, 2012. "Analysis of regional difference on impact factors of China’s energy – Related CO2 emissions," Energy, Elsevier, vol. 39(1), pages 319-326.
    8. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    9. 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.
    10. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    11. Giuseppe Ioppolo & Stefano Cucurachi & Roberta Salomone & Giuseppe Saija & Lei Shi, 2016. "Sustainable Local Development and Environmental Governance: A Strategic Planning Experience," Sustainability, MDPI, vol. 8(2), pages 1-16, February.
    12. Yam, Richard C. M. & Guan, Jian Cheng & Pun, Kit Fai & Tang, Esther P. Y., 2004. "An audit of technological innovation capabilities in chinese firms: some empirical findings in Beijing, China," Research Policy, Elsevier, vol. 33(8), pages 1123-1140, October.
    13. McDonald, John, 2009. "Using least squares and tobit in second stage DEA efficiency analyses," European Journal of Operational Research, Elsevier, vol. 197(2), pages 792-798, September.
    14. Chakraborty, Pavel & Chatterjee, Chirantan, 2017. "Does environmental regulation indirectly induce upstream innovation? New evidence from India," Research Policy, Elsevier, vol. 46(5), pages 939-955.
    15. Klaus Rennings & Christian Rammer, 2011. "The Impact of Regulation-Driven Environmental Innovation on Innovation Success and Firm Performance," Industry and Innovation, Taylor & Francis Journals, vol. 18(3), pages 255-283.
    16. Holley, Cameron & Lecavalier, Emma, 2017. "Energy governance, energy security and environmental sustainability: A case study from Hong Kong," Energy Policy, Elsevier, vol. 108(C), pages 379-389.
    17. Zoltan J. Acs & Luc Anselin & Attila Varga, 2008. "Patents and Innovation Counts as Measures of Regional Production of New Knowledge," Chapters, in: Entrepreneurship, Growth and Public Policy, chapter 11, pages 135-151, Edward Elgar Publishing.
    18. Jaeho Shin & Changhee Kim & Hongsuk Yang, 2018. "The Effect of Sustainability as Innovation Objectives on Innovation Efficiency," Sustainability, MDPI, vol. 10(6), pages 1-13, June.
    19. 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.
    20. Seiford, Lawrence M. & Zhu, Joe, 2005. "A response to comments on modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 161(2), pages 579-581, March.
    21. Evgeniya Lupova-Henry & Nicola Francesco Dotti, 2019. "Governance of sustainable innovation: Moving beyond the hierarchy-market-network trichotomy? A systematic literature review using the ‘who-how-what’ framework," ULB Institutional Repository 2013/283521, ULB -- Universite Libre de Bruxelles.
    22. Hall, Bronwyn H & Griliches, Zvi & Hausman, Jerry A, 1986. "Patents and R and D: Is There a Lag?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 27(2), pages 265-283, June.
    23. Ke Li & Malin Song, 2016. "Green Development Performance in China: A Metafrontier Non-Radial Approach," Sustainability, MDPI, vol. 8(3), pages 1-21, March.
    24. Xinbao Tian & Jiguang Wang, 2018. "Research on Spatial Correlation in Regional Innovation Spillover in China Based on Patents," Sustainability, MDPI, vol. 10(9), pages 1-14, August.
    25. Xiao Dai & Jian Wu & Liang Yan, 2018. "A Spatial Evolutionary Study of Technological Innovation Talents’ Sticky Wages and Technological Innovation Efficiency Based on the Perspective of Sustainable Development," Sustainability, MDPI, vol. 10(11), pages 1-19, November.
    26. Fare, Rolf & Grosskopf, Shawna, 2004. "Modeling undesirable factors in efficiency evaluation: Comment," European Journal of Operational Research, Elsevier, vol. 157(1), pages 242-245, August.
    27. Daniela M. Salvioni & Francesca Gennari & Luisa Bosetti, 2016. "Sustainability and Convergence: The Future of Corporate Governance Systems?," Sustainability, MDPI, vol. 8(11), pages 1-25, November.
    28. Wei, Yi-Ming & Chen, Hao & Chyong, Chi Kong & Kang, Jia-Ning & Liao, Hua & Tang, Bao-Jun, 2018. "Economic dispatch savings in the coal-fired power sector: An empirical study of China," Energy Economics, Elsevier, vol. 74(C), pages 330-342.
    29. 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.
    30. Samuel Wicki & Erik G. Hansen, 2019. "Green technology innovation: Anatomy of exploration processes from a learning perspective," Business Strategy and the Environment, Wiley Blackwell, vol. 28(6), pages 970-988, September.
    31. Zhang, Yue-Jun & Peng, Yu-Lu & Ma, Chao-Qun & Shen, Bo, 2017. "Can environmental innovation facilitate carbon emissions reduction? Evidence from China," Energy Policy, Elsevier, vol. 100(C), pages 18-28.
    32. Seema Sharma & V. J. Thomas, 2008. "Inter-country R&D efficiency analysis: An application of data envelopment analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(3), pages 483-501, September.
    33. Junhong Bai, 2013. "On Regional Innovation Efficiency: Evidence from Panel Data of China's Different Provinces," Regional Studies, Taylor & Francis Journals, vol. 47(5), pages 773-788, May.
    34. Nahra, Tammie A. & Mendez, David & Alexander, Jeffrey A., 2009. "Employing super-efficiency analysis as an alternative to DEA: An application in outpatient substance abuse treatment," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1097-1106, August.
    35. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    36. Nazim Hussain & Ugo Rigoni & René P. Orij, 2018. "Corporate Governance and Sustainability Performance: Analysis of Triple Bottom Line Performance," Journal of Business Ethics, Springer, vol. 149(2), pages 411-432, May.
    37. Xiaoqing Wang & Qiuming Wu & Salman Majeed & Donghao Sun, 2018. "Fujian’s Industrial Eco-Efficiency: Evaluation Based on SBM and the Empirical Analysis of lnfluencing Factors," Sustainability, MDPI, vol. 10(9), pages 1-18, September.
    38. Wang, Ke & Wei, Yi-Ming & Zhang, Xian, 2013. "Energy and emissions efficiency patterns of Chinese regions: A multi-directional efficiency analysis," Applied Energy, Elsevier, vol. 104(C), pages 105-116.
    39. Baocheng He & Jiawei Wang & Jiaoyang Wang & Kun Wang, 2018. "The Impact of Government Competition on Regional R&D Efficiency: Does Legal Environment Matter in China’s Innovation System?," Sustainability, MDPI, vol. 10(12), pages 1-18, November.
    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. Nill, Jan & Kemp, Ren, 2009. "Evolutionary approaches for sustainable innovation policies: From niche to paradigm?," Research Policy, Elsevier, vol. 38(4), pages 668-680, May.
    42. Henry Junior Anderson & Jan Stejskal, 2019. "Diffusion Efficiency of Innovation among EU Member States: A Data Envelopment Analysis," Economies, MDPI, vol. 7(2), pages 1-19, April.
    43. Wang, Ke & Wei, Yi-Ming & Zhang, Xian, 2012. "A comparative analysis of China’s regional energy and emission performance: Which is the better way to deal with undesirable outputs?," Energy Policy, Elsevier, vol. 46(C), pages 574-584.
    44. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    45. Song, Malin & Wang, Shuhong & Sun, Jing, 2018. "Environmental regulations, staff quality, green technology, R&D efficiency, and profit in manufacturing," Technological Forecasting and Social Change, Elsevier, vol. 133(C), pages 1-14.
    46. Yu, Yanni & Qian, Tao & Du, Limin, 2017. "Carbon productivity growth, technological innovation, and technology gap change of coal-fired power plants in China," Energy Policy, Elsevier, vol. 109(C), pages 479-487.
    47. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, 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. 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. Jaeho Shin & Yeongjun Kim & Changhee Kim, 2021. "The Perception of Occupational Safety and Health (OSH) Regulation and Innovation Efficiency in the Construction Industry: Evidence from South Korea," IJERPH, MDPI, vol. 18(5), pages 1-14, February.
    3. Keyan Zheng & Fagang Hu & Yaliu Yang, 2023. "Data-Driven Evaluation and Recommendations for Regional Synergy Innovation Capability," Sustainability, MDPI, vol. 15(14), pages 1-21, July.
    4. Yaliu Yang & Yuan Wang & Yingyan Zhang & Conghu Liu, 2022. "Data-Driven Coupling Coordination Development of Regional Innovation EROB Composite System: An Integrated Model Perspective," Mathematics, MDPI, vol. 10(13), pages 1-25, June.
    5. Liyan Sun & Zhuoying Wang & Li Yang, 2023. "Research on the Dynamic Coupling and Coordination of Science and Technology Innovation and Sustainable Development in Anhui Province," Sustainability, MDPI, vol. 15(4), pages 1-22, February.
    6. Rui Wang & Bing Xia & Suocheng Dong & Yu Li & Zehong Li & Duoxun Ba & Wenbiao Zhang, 2020. "Research on the Spatial Differentiation and Driving Forces of Eco-Efficiency of Regional Tourism in China," Sustainability, MDPI, vol. 13(1), pages 1-23, December.

    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. Kai Xu & Bart Bossink & Qiang Chen, 2019. "Efficiency Evaluation of Regional Sustainable Innovation in China: A Slack-Based Measure (SBM) Model with Undesirable Outputs," Sustainability, MDPI, vol. 12(1), pages 1-21, December.
    2. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2018. "Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envelopment analysis based materials balance approach," European Journal of Operational Research, Elsevier, vol. 269(1), pages 35-50.
    3. Ke Wang & Yi-Ming Wei & Zhimin Huang, 2017. "Environmental efficiency and abatement efficiency measurements of China¡¯s thermal power industry: A data envelopment analysis based materials balance approach," CEEP-BIT Working Papers 108, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    4. Afzalinejad, Mohammad, 2020. "Reverse efficiency measures for environmental assessment in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    5. Atkinson, Scott E. & Tsionas, Mike G., 2021. "Generalized estimation of productivity with multiple bad outputs: The importance of materials balance constraints," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1165-1186.
    6. Li Liang & Kai Xu, 2023. "Convergence analysis of regional sustainable innovation efficiency in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(3), pages 2758-2776, March.
    7. 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.
    8. Kangjuan Lv & Yu Cheng & Yousen Wang, 2021. "Does regional innovation system efficiency facilitate energy-related carbon dioxide intensity reduction in China?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(1), pages 789-813, January.
    9. Chiu, Yung-Ho & Lee, Jen-Hui & Lu, Ching-Cheng & Shyu, Ming-Kuang & Luo, Zhengying, 2012. "The technology gap and efficiency measure in WEC countries: Application of the hybrid meta frontier model," Energy Policy, Elsevier, vol. 51(C), pages 349-357.
    10. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    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. Özkara, Yücel & Atak, Mehmet, 2015. "Regional total-factor energy efficiency and electricity saving potential of manufacturing industry in Turkey," Energy, Elsevier, vol. 93(P1), pages 495-510.
    13. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    14. 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.
    15. Fang, Tao & Fang, Debin & Yu, Bolin, 2022. "Carbon emission efficiency of thermal power generation in China: Empirical evidence from the micro-perspective of power plants," Energy Policy, Elsevier, vol. 165(C).
    16. Pérez, Karen & González-Araya, Marcela C. & Iriarte, Alfredo, 2017. "Energy and GHG emission efficiency in the Chilean manufacturing industry: Sectoral and regional analysis by DEA and Malmquist indexes," Energy Economics, Elsevier, vol. 66(C), pages 290-302.
    17. George Halkos & Nickolaos Tzeremes, 2014. "Measuring the effect of Kyoto protocol agreement on countries’ environmental efficiency in CO 2 emissions: an application of conditional full frontiers," Journal of Productivity Analysis, Springer, vol. 41(3), pages 367-382, June.
    18. Jiang, Lei & Zhou, Haifeng & He, Shixiong, 2021. "Does energy efficiency increase at the expense of output performance: Evidence from manufacturing firms in Jiangsu province, China," Energy, Elsevier, vol. 220(C).
    19. 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).
    20. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "Measuring environmental performance under different environmental DEA technologies," Energy Economics, Elsevier, vol. 30(1), pages 1-14, January.

    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:7:p:3008-:d:343261. 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.