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| Fine-grained Delineation of Technology Proximity and Its Dynamic Impact on Inter-organizational Technology Transfer |
| Wang Limei1,Luo Qi2 |
| (1.Faculty of Materials and Manufacturing, Beijing University of Technology;2. College of Economics and Management, Beijing University of Technology, Beijing 100124, China) |
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Abstract Technology transfer can boost collaborative innovation in regional science and technology organizations. The problem of low transaction rates in China's technology market still remains serious and it is vital to study on the drivers of inter-organizational technology transfer to promote the technology market development . Technology proximity, as an internal and external factor of technology transactions, is a necessary condition for promoting technology knowledge transfer and a decisive factor for partner selection. However, there is no consensus on the impact of technology proximity on technology transfer, and various theories such as the facilitation theory, inhibition theory and inverted U theory have been formed. Meanwhile, the previous studies have paid little attention to a fine-grained discussion about the connotation definition and quantitative measurement of technology proximity, which makes it hard to illustrate the intrinsic mechanism of the impact of technology proximity on technology transfer. Therefore, this paper makes a fine-grained delineation of technology proximity and explores its microscopic impact on technology transfer to reveal the inner driving mechanism of technology transfer and promote the matching of supply and demand entities as well as technology transactions.#br#The absorptive capacity attributes of technology transfer organizations, the structural proximity of technology content among organizations, and the location and relational proximity of organizations in the technology transfer network are comprehensively considered to fine-grain the technology proximity into 3 dimensions of technology absorption capacity proximity, technology content structure proximity and technology transaction network proximity, with a total of 11 indicators. Then QAP analysis methods, Spearman's rank correlation and time series models are used to construct a model of the influence of multidimensional technology proximity on patent technology transfer, including (1) testing the influence of multidimensional technology proximity on technology transfer by QAP regression analysis; (2) testing the dynamic influence of node centrality on technology transfer by Spearman rank correlation; (3) testing the dynamic influence of technology transaction proximity on technology transfer by QAP correlation.#br#On the basis of an empirical study of Beijing-Tianjin-Hebei regional invention patent transfer data from 2011-2018, the paper investigates the impact of multidimensional technological proximity on patent technology transfer and concludes that (1) on the dimension of technology absorption capacity proximity, technology reserve proximity positively promotes technology transfer; and technology strength proximity negatively affects technology transfer; (2) on the dimension of technology content structure proximity, the proximity of the technology foundation influences technology transfer in an inverted U-shape, the proximity of technology investment negatively influences technology transfer, and the proximity of technology complementarity positively promotes technology transfer; (3) on the dimension of technology transaction network structure proximity, network structure proximity positively promotes technology transfer, and the role of network openness proximity is not significant;network node degree centrality and proximity centrality positively promote technology transfer, and the role of betweenness centrality is not strong, indicating that the effects of merit link and proximity link in the network are significant; the positive impact of technology transaction proximity on technology transfer is "inverted U-shaped", and the path-dependent effect is significant; (4) three extended indicators exert an important effect on patent technology transfer, and their effects are robust in the time series model, i.e. network distance proximity has the strongest promoting effect, followed by technology complementarity proximity, which indicates that organizations prefer to choose others with short network distance and strong technology complementarity for patent technology transfer; while technology investment proximity has the strongest inhibiting effect, which means that organizations with similar demands tend to compete, and it's difficult to carry out patent technology transfer; (5) among the other dimensions of proximity, geographic proximity has a non-significant contribution to technology transfer, while institutional proximity and social proximity have a positive effect on technology transfer.#br#Addressing the above issues, it is advised to (1) promote the construction of a big data platform for technology transactions, dynamically measure the multidimensional proximity between entities, and improve the model of matching technology supply and demand and transaction recommendation on the existing platform; (2) reduce the cost of technology transactions among cross-regional organizations, explore diversified technology transfer models among organizations, and enhance the activity of technology transaction networks; (3) promote the construction of a national technology market, and give full play to the technology spillover effect of backbone organizations in the national market.#br#
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Received: 21 September 2022
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