Effects of patent policy on innovation outputs and commercialization: evidence from universities in China

Gong, Han; Peng, Shan

doi:10.1007/s11192-018-2893-5

Cited by 44 publications

(34 citation statements)

References 22 publications

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“…At present, the number of patent applications in China has risen sharply, and China also has the largest number of patent applications in the world. Although the quantity of patent applications in universities has increased dramatically in recent years, the rate of patent commercialization is much lower than what we expected [1]. According to The State Intellectual Property Office of Patent Statistical Yearbook (2018), the growth rate of invention patents in colleges and universities in China has accelerated significantly, from 1,548 in 2000 to 19,400 in 2018, an increase of more than 125 times.…”

Section: Introductionmentioning

confidence: 91%

“…The purpose of the commercialization of patents in universities is to transform the results of knowledge creation into productivity [18]. Patent commercialization is one of the key processes for the realization of patent value in universities [1]. The focus is using and integrating existing knowledge and technology to create new application products to serve production activities and life.…”

Section: Patent Commercialization Stagementioning

confidence: 99%

“…After Hausmann's test, the negative binomial fixed-effects regression model was applied. There were only control variables in column (1), and knowledge innovation in the past stage was added to column (2). The coefficient was significantly positive, which indicates that there exists a path-dependent effect in the knowledge innovation stage.…”

Section: Realization Process In Upivcmentioning

confidence: 99%

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The innovation value chain of patents: Breakthrough in the patent commercialization trap in Chinese universities

et al. 2020

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The innovation value chain is an effective tool for analysing innovation activities and reflects the process of value creation and increase in innovation activities. From the perspective of innovation value chains, we divided patent innovation activities into three stages: knowledge innovation stage, applied research stage and patent commercialization stage. The panel data from 64 universities directly managed by the Ministry of Education from 2009 to 2017 were used and several conclusions were drawn: 1) In the initial stage of knowledge innovation, the fundamental research fund plays a crucial promoting role, and knowledge innovation achievements are mainly published academic papers. 2) In the applied research stage, the knowledge innovation in the early stage and the fund investment in R&D activities have a significant positive effect on the patent output of universities, but the personnel investment has a negative effect. 3) In the final stage of patent commercialization, preliminary research results have a positive impact on patent commercialization, whose marginal effect depends on the industry-university-research relationship, external competition and reputation of the university. The evidence showed that there is a feedback channel between university patent commercialization and knowledge innovation, and new knowledge generated by the interaction with the outside world in the process of patent commercialization was transmitted to the subject of knowledge innovation through this channel, forming a virtuous dynamic cycle. By analysing the driving factors of the value chain of patent innovation in colleges and universities, we provided empirical evidence for the operation mechanism and policy formulation of college patents in China. PLOS ONEPLOS ONE | https://doi.org/10.1371/journal.pone.

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Section: Introductionmentioning

confidence: 91%

Section: Patent Commercialization Stagementioning

confidence: 99%

Section: Realization Process In Upivcmentioning

confidence: 99%

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The innovation value chain of patents: Breakthrough in the patent commercialization trap in Chinese universities

et al. 2020

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“…The scope of patent commercialization consists of the sales, transfer, or license of patented technologies to industrial firms; founding start-ups that are based on the grounds of licensed patent technologies; or commercializing patented technologies in designs, products, and manufacturing or the service process of licensees [31]. The patents held by firms or universities are, by nature, different [16]. On the one hand, patents held by firms are driven primarily by possible market benefits.…”

Section: Patent Commercialization By Universitiesmentioning

confidence: 99%

“…Therefore, scholars have started to investigate the related issues of patent commercialization by universities, due to the low percentage rate of patents that have been commercialized by universities [16]. Whether university patents can successfully be commercialized is very important for the sustainable economic growth of certain fast-growing economies like that of mainland China.…”

Section: Introductionmentioning

confidence: 99%

A DANP-Based NDEA-MOP Approach to Evaluating the Patent Commercialization Performance of Industry–Academic Collaborations

Huang

Yang

et al. 2021

Mathematics

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The industry–academic collaboration (IAC) in developed and developing countries enables these economies to gain momentum in continuous innovation and, thus, economic growth. Patent commercialization is one major channel of knowledge flow in IAC. However, very few studies consider the flow of knowledge between industrial firms and universities. Moreover, ways that the patent commercialization performance of IACs can be evaluated are rarely discussed. Therefore, defining an analytic framework to evaluate the performance of IAC from the aspect of patent commercialization is critical. Traditionally, data envelopment analysis (DEA) models have widely been adopted in performance evaluation. However, traditional DEA models cannot accurately evaluate the performance of IACs with complex university–industry interconnections, the internal linkages, or linking activities of knowledge-flow within the decision-making units (DMUs), i.e., the IACs. In order to solve the abovementioned problems, this study defines a multiple objective programming (MOP)-based network DEA (NDEA), with weighting derived from the decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process (ANP), or the DANP. The proposed analytic framework can evaluate the efficiency of decision-making units (DMUs) with a network structure (e.g., supply chains, strategic alliances, etc.) based on the weights that have been derived, based on experts’ opinions. An empirical study based on the performance of the patent commercialization of Taiwanese IACs was used to demonstrate the feasibility of the proposed framework. The results of the empirical research can serve as a basis for improving the performance of IAC.

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State‐owned industrial enterprises' non‐R&D innovation and regional total factor productivity: An analysis based on the panel co‐integration method

Wang

et al. 2022

Manage Decis Econ

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State‐owned industrial enterprises' (SOIEs') non‐R&D innovation activities have been ignored by scholars. Using panel data on the regions of China, this paper examines the impact of non‐R&D innovation by SOIEs on regional total factor productivity (TFP) with panel Co‐integration and a panel vector error correction (VEC) model. The results show that SOIEs' non‐R&D innovation is important for economic growth, and different types of non‐R&D innovations have heterogeneous effects on regional TFP. Foreign technology acquisition (FTA) has more positive long‐term and short‐term impacts on regional TFP than do R&D expenditures. Technology assimilation (TA) improves regional TFP, but the effect of R&D expenditures on innovation is higher than that of TA in the eastern region. Domestic technology purchases (DTPs) have no significant impact on regional TFP in the central and western regions and even have a negative effect in the eastern region. Technology transformation (TT) has a stronger long‐term positive effect on regional TFP than R&D expenditures, but R&D innovation has a stronger short‐term positive effect than TT. We examine the impact of SOIEs' non‐R&D innovation on regional economic efficiency and, to a degree, identify the source of its effect on innovation. This study emphasizes the critical function of technology diffusion in fostering economic efficiency.

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Effects of patent policy on innovation outputs and commercialization: evidence from universities in China

Cited by 44 publications

References 22 publications

The innovation value chain of patents: Breakthrough in the patent commercialization trap in Chinese universities

The innovation value chain of patents: Breakthrough in the patent commercialization trap in Chinese universities

A DANP-Based NDEA-MOP Approach to Evaluating the Patent Commercialization Performance of Industry–Academic Collaborations

State‐owned industrial enterprises' non‐R&D innovation and regional total factor productivity: An analysis based on the panel co‐integration method

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