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Spatial Variation of Regional Sustainable Development and its Relationship to the Allocation of Science and Technology Resources

Author

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  • Jian Wu

    (School of Management, Hangzhou Dianzi University, Xiasha, Jianggan District, Hangzhou 310018, China)

  • Guangdong Wu

    (School of Tourism and Urban Management, Jiangxi University of Finance and Economics, Nanchang 330013, China
    These authors contributed equally to this work.)

  • Qing Zhou

    (School of Economics and Management, Beijing University of Technology, Beijing 100022, China
    These authors contributed equally to this work.)

  • Mi Li

    (College of Electro-mechanics Engineering, Jiaxing University, Jiaxing 314000, China
    These authors contributed equally to this work.)

Abstract

With the increasing of labor salaries, the RMB exchange rate, resource product prices and requirements of environmental protection, inexpensive labor and land are no longer the decisive factor of regional competitiveness. From this perspective, China needs to shift from the extensive development mode to the sustainable development mode. Science and technology resources rational allocation is one of the key issues in sustainable development. Based on the counties (districts) data of Zhejiang Province in China, this paper portrays the spatial variation of regional sustainable development level of this area. This paper finds that counties tend to cluster in groups with the same sustainable development level, and this agglomeration trend has been enforced during the past several years. It then testifies to the relationship between the allocation of science and technology resources and local sustainable development, identifies science and technology human resources, financial resources and environmental resource are positively related to local sustainable development, except government financial support. The economic level has a negative relationship with regional sustainable development. This is because the development of the Zhejiang economy grown at the expense of the environment and ecosystem. Some advice is given according to the empirical analysis result.

Suggested Citation

  • Jian Wu & Guangdong Wu & Qing Zhou & Mi Li, 2014. "Spatial Variation of Regional Sustainable Development and its Relationship to the Allocation of Science and Technology Resources," Sustainability, MDPI, vol. 6(9), pages 1-18, September.
    • Handle: RePEc:gam:jsusta:v:6:y:2014:i:9:p:6400-6417:d:40260
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    References listed on IDEAS

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    1. Cairns, Robert D. & Martinet, Vincent, 2014. "An environmental-economic measure of sustainable development," European Economic Review, Elsevier, vol. 69(C), pages 4-17.
    2. Schilling, Markus & Chiang, Lichun, 2011. "The effect of natural resources on a sustainable development policy: The approach of non-sustainable externalities," Energy Policy, Elsevier, vol. 39(2), pages 990-998, February.
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    Cited by:

    1. Sangsung Park & Seung-Joo Lee & Sunghae Jun, 2015. "A Network Analysis Model for Selecting Sustainable Technology," Sustainability, MDPI, vol. 7(10), pages 1-16, September.
    2. Kyung-Young Lee, 2021. "Relationship between Public Service Satisfaction and Intention of Continuous Residence of Younger Generations in Rural Areas: The Case of Jeonbuk, Korea," Land, MDPI, vol. 10(11), pages 1-15, November.
    3. Xuedong Liang & Dongyang Si & Xinli Zhang, 2017. "Regional Sustainable Development Analysis Based on Information Entropy—Sichuan Province as an Example," IJERPH, MDPI, vol. 14(10), pages 1-18, October.
    4. Sheng Zhang & Meng Xu & Yifu Yang & Zeyu Song, 2021. "Technological Innovation, Production Efficiency, and Sustainable Development: A Case Study from Shenzhen in China," Sustainability, MDPI, vol. 13(19), pages 1-12, September.
    5. Lu Zhang & Xiaochao Guo & Zhimei Lei & Ming K. Lim, 2019. "Social Network Analysis of Sustainable Human Resource Management from the Employee Training’s Perspective," Sustainability, MDPI, vol. 11(2), pages 1-20, January.
    6. Sungchul Kim & Dongsik Jang & Sunghae Jun & Sangsung Park, 2015. "A Novel Forecasting Methodology for Sustainable Management of Defense Technology," Sustainability, MDPI, vol. 7(12), pages 1-17, December.

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