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A Spatial Evolutionary Study of Technological Innovation Talents’ Sticky Wages and Technological Innovation Efficiency Based on the Perspective of Sustainable Development

Author

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  • Xiao Dai

    (School of Economics and Management, China University of Geosciences, Wuhan 430074, China)

  • Jian Wu

    (School of Economics and Management, China University of Geosciences, Wuhan 430074, China)

  • Liang Yan

    (School of Economics and Management, China University of Geosciences, Wuhan 430074, China)

Abstract

In China, with the deepening of the reform of industrial structures, the improvement of technological innovation has become a key issue. This is not only related to whether the strategic development of Chinese science and technology can be achieved, but also whether the Chinese economy and high-quality human capital can develop sustainably. Based on the theoretical boundary of sustainable development—free transfer of information—we see that sticky wages are the embodiment of information dissemination. Under the dual effects of profit-seeking behavior and information barriers, the relationship between the sticky wages of technological innovation talents (TIT), as the most profitable labor force, and technological innovation efficiency (TIE) has become more complex, and so far we still have a limited understanding of it. We explore this issue in an empirical study by using a two-stage chain Data Envelopment Analysis (DEA) of TIE followed by modifying the wages of TIT; finally, we build a collaborative evolution model with spatial effects on a large dataset (from 2007 to 2016). The results show that the overall Chinese TIE is relatively low, and in the central and western regions the TIE has been seriously reversed; there are also divergences in the TIE at different stages in the regions we focus on. As the output of technological innovation, except for initial results (such as patents), the more important value is whether it has an ability to transform the initial results into production, and the core of it is whether it can match the market environment and technology transfer system (for example, market mechanism, transformation incentive mechanism, and institutional mechanism). So, considering these aspects, the central and west of China are obviously insufficient, while the east has obvious advantages; this can also explain the results of spatial diffusion, namely, in the eastern region it is higher than in other areas, but the gap between them is gradually narrowing; lastly, from the perspective of synergy, the wage stickiness of TIT in the central region is larger than that of the eastern and western regions, and the evolutionary relationship in the former is “extruding” while in the latter it is “cooperative.” Mainly due to the popularity of the eastern innovation network and the initial state of the west, the barriers of information transmission are relatively low, while the central part is undergoing economic transformation, so its extreme demand for TIT has pushed up the cost of information transmission.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:11:p:4201-:d:182828
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    1. Chang Liu & Hui-Lin Xiao, 2022. "The Impact of Ambidextrous Innovation Human Capital on the Technological Innovation Efficiency and Stage Efficiency of Big Data Enterprises," Sustainability, MDPI, vol. 14(24), pages 1-21, December.
    2. 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.
    3. Xiao Dai & Liang Yan & Liu Jianping & JianWu, 2022. "A research on the threshold effect of human capital structure upgrading and industrial structure upgrading—based on the perspective of path dependence," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2645-2674, August.
    4. Yuxin Meng & Lu Liu & Qiying Ran, 2022. "Can Urban Green Transformation Reduce the Urban–Rural Income Gap? Empirical Evidence Based on Spatial Durbin Model and Mediation Effect Model," Sustainability, MDPI, vol. 14(24), pages 1-24, December.

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