The evolution of the industrial value chain in China's high-speed rail driven by innovation policies: A patent analysis
Xiaodong Yuan and
Technological Forecasting and Social Change, 2021, vol. 172, issue C
High-speed Rail (HSR) is one of the most technological breakthroughs in passenger transportation over the last decades. The rapid development of China's High-speed Rail (CRH) is astonishing. However, it seems to be a “black box” how China has achieved great success in the CRH industry for many organizations or scholars. The paper proposes a novel approach to identify the critical components of an industry value chain and then gains insight into why systemic policies can drive significant breakthroughs in the CRH industry. Our findings highlight that both large companies and universities have played a vital function in the process of technology innovation. Besides, the incentive policies induce many innovators to carry out competition and cooperation, which results in forming and perfecting the industrial value chain. Innovation policies facilitate the evolution of the industrial value chain though there is a time lag of incentive effect. In contrast, the perfect industry value chain contributes to achieving the success of technology innovation. The paper provides insight into the incentive effect of public policies on technology innovation that falls into the scope of Schumpeter Mark II, which can help policymakers perfect incentive policies and managers implement appropriate patent strategies for developing new emerging technologies.
Keywords: Innovation policy; Patent analysis; High-speed rail; Industrial value chain; Revealed technological advantage (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:172:y:2021:i:c:s0040162521004868
Access Statistics for this article
Technological Forecasting and Social Change is currently edited by Fred Phillips
More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().