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Data-Driven Evaluation and Recommendations for Regional Synergy Innovation Capability

Author

Listed:
  • Keyan Zheng

    (School of Foreign Studies, Suzhou University, Suzhou 234000, China)

  • Fagang Hu

    (Business School, Suzhou University, Suzhou 234000, China)

  • Yaliu Yang

    (Business School, Suzhou University, Suzhou 234000, China)

Abstract

Regional synergy innovation capability is an important driving force in promoting the sustainable and high-quality development of the regional economy. Taking the regional innovation development panel data of the Yangtze River Delta integration region from 2010 to 2019 as a sample, this study constructs an evaluation index system of regional synergy innovation capability, weights the index using the entropy weight method, and measures the capability of the Yangtze River Delta integration region (three provinces and one city) using the composite system synergy degree model. The empirical results show that the synergy of regional synergy innovation in the Yangtze River Delta integration has increased steadily, but there is still much room for improvement. Anhui has great potential for synergy innovation with Jiangsu, Zhejiang, and Shanghai. Therefore, this study proposes countermeasures and suggestions for the high-quality development of Anhui’s synergy innovation capability under the integration of the Yangtze River Delta. This study provides theoretical and methodological support for enhancing regional synergy innovation capability and provides decision support for the sustainable and high-quality development of the regional economy.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11143-:d:1196060
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    as
    1. Fei Fan & Huan Lian & Song Wang, 2020. "Can regional collaborative innovation improve innovation efficiency? An empirical study of Chinese cities," Growth and Change, Wiley Blackwell, vol. 51(1), pages 440-463, March.
    2. Marta Gasparin & Martin Quinn, 2021. "Designing regional innovation systems in transitional economies: A creative ecosystem approach," Growth and Change, Wiley Blackwell, vol. 52(2), pages 621-640, June.
    3. Xumei Yuan & Cuicui Zheng, 2022. "Improved Intuitionistic Fuzzy Entropy and Its Application in the Evaluation of Regional Collaborative Innovation Capability," Sustainability, MDPI, vol. 14(5), pages 1-14, March.
    4. Shu Yu & Shuangshuang Zhang & Takaya Yuizono, 2021. "Exploring the Influences of Innovation Climate and Resource Endowments through Two Types of University–Industry Collaborative Activities on Regional Sustainable Development," Sustainability, MDPI, vol. 13(14), pages 1-20, July.
    5. Tero Rantala & Juhani Ukko, 2019. "Performance evaluation to support European regional development – A university–industry perspective," European Planning Studies, Taylor & Francis Journals, vol. 27(5), pages 974-994, May.
    6. Leal Filho, Walter & Wall, Tony & Rui Mucova, Serafino Afonso & Nagy, Gustavo J. & Balogun, Abdul-Lateef & Luetz, Johannes M. & Ng, Artie W. & Kovaleva, Marina & Safiul Azam, Fardous Mohammad & Alves,, 2022. "Deploying artificial intelligence for climate change adaptation," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    7. Elvira Uyarra & Barbara Ribeiro & Lisa Dale-Clough, 2019. "Exploring the normative turn in regional innovation policy: responsibility and the quest for public value," European Planning Studies, Taylor & Francis Journals, vol. 27(12), pages 2359-2375, December.
    8. Heindl, Anna-Barbara & Liefner, Ingo, 2019. "The Analytic Hierarchy Process as a methodological contribution to improve regional innovation system research: Explored through comparative research in China," Technology in Society, Elsevier, vol. 59(C).
    9. Aytekin, Ahmet & Ecer, Fatih & Korucuk, Selçuk & Karamaşa, Çağlar, 2022. "Global innovation efficiency assessment of EU member and candidate countries via DEA-EATWIOS multi-criteria methodology," Technology in Society, Elsevier, vol. 68(C).
    10. Yaliu Yang & Yuan Wang & Cui Wang & Yingyan Zhang & Cuixia Zhang, 2022. "Temporal and Spatial Evolution of the Science and Technology Innovative Efficiency of Regional Industrial Enterprises: A Data-Driven Perspective," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
    11. Hugo Pinto & João Guerreiro, 2010. "Innovation regional planning and latent dimensions: the case of the Algarve region," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 44(2), pages 315-329, April.
    12. Xinbao Tian & Jiguang Wang, 2018. "Research on the Disequilibrium Development of Output of Regional Innovation Based on R&D Personnel," Sustainability, MDPI, vol. 10(8), pages 1-14, August.
    13. Yi Su & Dezhi Liang & Wen Guo, 2020. "Application of Multiattribute Decision-Making for Evaluating Regional Innovation Capacity," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-20, September.
    14. Yingkai Tang & Yaozhi Chen & Kun Wang & He Xu & Xiaoqi Yi, 2020. "An Analysis on the Spatial Effect of Absorptive Capacity on Regional Innovation Ability Based on Empirical Research in China," Sustainability, MDPI, vol. 12(7), pages 1-23, April.
    15. Jianzhong Xu & Jiaqi Zhai, 2020. "Research on the Evaluation of Green Innovation Capability of Manufacturing Enterprises in Innovation Network," Sustainability, MDPI, vol. 12(3), pages 1-20, January.
    16. Ganau, Roberto & Grandinetti, Roberto, 2021. "Disentangling regional innovation capability: what really matters?," LSE Research Online Documents on Economics 114921, London School of Economics and Political Science, LSE Library.
    17. Malik, Ashish & Sharma, Piyush & Pereira, Vijay & Temouri, Yama, 2021. "From regional innovation systems to global innovation hubs: Evidence of a Quadruple Helix from an emerging economy," Journal of Business Research, Elsevier, vol. 128(C), pages 587-598.
    18. Song Wang & Jiexin Wang & Chenqi Wei & Xueli Wang & Fei Fan, 2021. "Collaborative innovation efficiency: From within cities to between cities—Empirical analysis based on innovative cities in China," Growth and Change, Wiley Blackwell, vol. 52(3), pages 1330-1360, September.
    19. Asheim, Bjorn T & Isaksen, Arne, 2002. "Regional Innovation Systems: The Integration of Local 'Sticky' and Global 'Ubiquitous' Knowledge," The Journal of Technology Transfer, Springer, vol. 27(1), pages 77-86, January.
    20. Miao, Cheng-lin & Duan, Meng-meng & Zuo, Yang & Wu, Xin-yu, 2021. "Spatial heterogeneity and evolution trend of regional green innovation efficiency--an empirical study based on panel data of industrial enterprises in China's provinces," Energy Policy, Elsevier, vol. 156(C).
    21. Christopher R Esposito & David L Rigby, 2019. "Buzz and pipelines: the costs and benefits of local and nonlocal interaction," Journal of Economic Geography, Oxford University Press, vol. 19(3), pages 753-773.
    22. Zhao, S.L. & Cacciolatti, L. & Lee, S.H. & Song, W., 2015. "Regional collaborations and indigenous innovation capabilities in China: A multivariate method for the analysis of regional innovation systems," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 202-220.
    23. 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.
    24. 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.
    25. Liu, Zhi & Li, Kevin W. & Tang, Juan & Gong, Bengang & Huang, Jun, 2021. "Optimal operations of a closed-loop supply chain under a dual regulation," International Journal of Production Economics, Elsevier, vol. 233(C).
    26. 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.
    27. Sleuwaegen, Leo & Boiardi, Priscilla, 2014. "Creativity and regional innovation: Evidence from EU regions," Research Policy, Elsevier, vol. 43(9), pages 1508-1522.
    28. Mariangela Piazza & Erica Mazzola & Lorenzo Abbate & Giovanni Perrone, 2019. "Network position and innovation capability in the regional innovation network," European Planning Studies, Taylor & Francis Journals, vol. 27(9), pages 1857-1878, September.
    29. Ai, Hongshan & Wang, Mengyuan & Zhang, Yue-Jun & Zhu, Tian-Tian, 2022. "How does air pollution affect urban innovation capability? Evidence from 281 cities in China," Structural Change and Economic Dynamics, Elsevier, vol. 61(C), pages 166-178.
    30. Jon Zabala-Iturriagagoitia & Peter Voigt & Antonio Gutierrez-Gracia & Fernando Jimenez-Saez, 2007. "Regional Innovation Systems: How to Assess Performance," Regional Studies, Taylor & Francis Journals, vol. 41(5), pages 661-672.
    31. Roberto Ganau & Roberto Grandinetti, 2021. "Disentangling regional innovation capability: what really matters?," Industry and Innovation, Taylor & Francis Journals, vol. 28(6), pages 749-772, July.
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