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Leveraging industrial-technological innovation to achieve sustainable development: A systems thinking perspective

Author

Listed:
  • Jin Guo
  • Meng Chen
  • Xialing Sun
  • Zhanzhao Wang
  • Jinli Xue

Abstract

Industrial-technological innovation (ITI) has become an important requirement for the sustainable development of China. ITI development requires a comprehensive understanding of the dynamic complexity associated with ITI systems. Previous research into ITI systems is based primarily on static methods that isolate system components, and ignore feedback on adjustments made. Based on systems thinking, this paper develop six archetypes (“Limit to Growth,” “Success to the Successful,” “Tragedy of the Commons,” “Fixes that Fail,” “Accidental Adversaries,” and “Shifting the Burden”) and an ITI system integration model. The model visualizes the ITI system as a whole and identifies bottlenecks that may affect ITI development. This conceptual model provides a more effective method of judgment, which can better explain the operational mechanism of the ITI system and improve the system’s operational characteristics. Finally, we evaluate the ITI system and propose that self-organization is a key lever of a systemic intervention framework for ITI.

Suggested Citation

  • Jin Guo & Meng Chen & Xialing Sun & Zhanzhao Wang & Jinli Xue, 2020. "Leveraging industrial-technological innovation to achieve sustainable development: A systems thinking perspective," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-23, December.
    • Handle: RePEc:plo:pone00:0242981
    DOI: 10.1371/journal.pone.0242981
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    References listed on IDEAS

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    1. J Sylvan Katz, 2016. "What Is a Complex Innovation System?," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-24, June.
    2. Jin Guo & Bingmei Gu & Xialing Sun & Jinli Xue & Baiyun Yuan, 2019. "Communication Barrier, Spillover Effect and Industrial-Technological Innovation," Sustainability, MDPI, vol. 11(18), pages 1-20, September.
    3. Liu, Hongwei & Wu, Jie & Chu, Junfei, 2019. "Environmental efficiency and technological progress of transportation industry-based on large scale data," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 475-482.
    4. Du, Minzhe & Wang, Bing & Zhang, Ning, 2018. "National research funding and energy efficiency: Evidence from the National Science Foundation of China," Energy Policy, Elsevier, vol. 120(C), pages 335-346.
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