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  • Technological proximity and recombinative innovation in the alternative energy field:

    Recombination of knowledge elements has been recognized as important innovation activities. This study aims to develop a new measurement of recombinative innovation and firstly explores its antecedents at the country-dyad level. We analyze 41,007 US alternative energy patents granted between 1976 and 2012. Based on multi-source data and longitudinal design, Quadratic Assignment Procedure (QAP) model results indicate that two countries’ technological proximity (TP) takes an inverted U-shaped relationship with their recombinative innovation (RI), which means that TP could raise the potential of joint recombination, but should not become too high because of great knowledge homogenization. Furthermore, we test two types of distances (i.e., cultural and geographical) as moderators of the relationship between TP and RI. Cultural distance negatively moderates the relationship between TP and RI, but moderating role of geographical distance is not supported in this research. The findings of this study, besides having implications for management and policy, have implications on the research of recombinative innovation, inter-national collaboration and partner selection strategy.

  • Proximity, Knowledge Transfer, and Innovation in Technology-Based M&As:

    M&As; High-technology; knowledge transfer; factors influencing M&As

  • Big Data-IoT: An Analysis of Multidimensional Proximity Implications on Green Innovation Performance—An Empirical Study of the Data from the Chinese Power Industry:

    With the global energy crisis and environmental degradation getting more rigorous, an essential approach is required to attain introverted development through structural optimization, autonomous invention, and technological innovation system. It is an important way to include energy conservation, emission reductions, and the implementation of a low-carbon mode in the power industry, which is a highly polluting sector of the national economy. This article is based on the State Intellectual Property Office of China’s patent search and analysis database. We choose the number of green patents jointly submitted for innovative topics in the power industry from 2016 to 2020. The negative binomial regression is constructed from the standpoint of multidimensional closeness by employing Gephi visual analysis, Ucinet, and the Stata 15 regional model. Furthermore, we investigate the impact of geographical closeness, technological closeness, and institutional closeness, as well as their interaction, on the green innovation performance of inventive organizations in China’s power industry.