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  1. Detecting and Visualizing the Communities of Innovation in Beijing-Tianjin-Hebei Urban Agglomeration Based on the Patent Cooperation Network.Fang Zhou & Bo Zhang - 2021 - Complexity 2021:1-14.
    For a deep understanding of Beijing-Tianjin-Hebei collaborative innovation, we detected and visualized the communities of innovation in BTH Urban Agglomeration based on the patent cooperation network. China Patent Database was connected with Business Registration Database and the Tianyan Check to achieve the geographical information of organizational innovators. Spinglass algorithm was applied and ultimately 12 communities of innovation were detected. Based on the different structure characteristics, we further clustered the 12 communities into four typical structures that are hierarchical, single-center, polycentric, and (...)
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  • The Impact of Chair–Team Sociodemographic Dissimilarity on the Relation Between Chair Power and Entrepreneurial Ventures’ R&D Intensity: Evidence From China.Yaoyi Zheng, Shufen Dai, Yueting Li & Yi Su - 2021 - Frontiers in Psychology 11.
    Contemplating the actual leaders of entrepreneurial firms and socio demographic dissimilarity between leaders and their teams, this study adopts panel data on the entrepreneurial firms of the China’s Growth Enterprise Market and empirically examines the influence of chair power on research and development intensity of entrepreneurial firms from the perspective of social identity. The results indicate that chair power positively affects entrepreneurial firms’ R&D intensity. The chair–team sociodemographic dissimilarity moderates the relationship in such a way that chair power is negatively (...)
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  • How Do Innovation Network Structures Affect Knowledge Sharing? A Simulation Analysis of Complex Networks.Lupeng Zhang & Wenbo Chen - 2021 - Complexity 2021:1-17.
    Knowledge has become an important resource that can help enterprises gain a competitive advantage in the market. In this regard, knowledge sharing in the process of cooperative innovation provides an important way to acquire knowledge. With the development of innovation, the innovation network has become an important carrier of knowledge sharing, which can also have an influence on knowledge sharing. Based on knowledge management theory and complex network theory, this study constructed a multilayer network environment for knowledge sharing. It then (...)
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  • Evolutionary Game Analysis of Firms’ Technological Strategic Choices: A Perspective of the Behavioral Biases.Yingqing Zhang, Ruguo Fan, Ming Luo, Mingman Chen & Jiaqin Sun - 2021 - Complexity 2021:1-17.
    To reveal the mechanisms of firms’ technological strategic choices between innovation and imitation, an evolutionary game model is proposed from the perspective of the behavioral biases. First, behavioral biases such as reference point dependence, loss aversion, and probability weighting can be defined and modeled based on the prospect theory. Second, according to the firm theory, a Cournot or Stackelberg game modeled with a technology spillover effect and intellectual property protection is applied to portray the interaction between firms. Third, an improved (...)
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  • China’s Auto Industry Upgrade Process Based on Aging Chain and Coflow Model.Baojian Zhang, Pengli Li, Huaguo Zhou & Xiaohang Yue - 2021 - Complexity 2021:1-12.
    To protect energy resources and alleviate environmental pollution, many countries attach great importance to the transformation of traditional industries into clean energy industries. In this paper, fuel vehicles, hybrid vehicles, and electric vehicles are included in the research. Then, based on the aging chain and coflow theory of SDs, we construct a dynamic matching model of the auto industry upgrade process and its energy consumption attributes. The simulation results of China’s auto industry show that the upgrading of the auto industry (...)
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  • Fractal Characteristics of Discontinuous Growth of Digital Company: An Entrepreneurial Bricolage Perspective.Xiaoyu Yu, Jiangyong Lu, Xiaomin Liu, Yihan Wang & Yilin Jia - 2021 - Complexity 2021:1-9.
    Digital companies exhibit discontinuous growth in the process of shifting from their existing core business to a newer and less familiar business. This pattern of growth often ends in failure mainly because companies invest most of their resources in maintaining the value network of their existing core business, which ultimately results in a “lock-in” effect. The fractal theory assumes that there are similarities among fractals within companies. These similarities may reduce the threats posed by the value network lock-in effect and (...)
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  • How Could Policies Facilitate Digital Transformation of Innovation Ecosystem: A Multiagent Model.Wei Yang, Jian Liu, Lingfei Li, Qing Zhou & Lixia Ji - 2021 - Complexity 2021:1-19.
    The digital transformation of the innovation ecosystem is not only an inevitable direction of innovation activities in the era of digital economy but also a highly complex and uncertain process. The way to facilitate transformation with policies has become a topic of common concern of academia and policymakers. This paper builds a multiagent model and studies the impacts of supply-side policies, demand-side policies, and environmental policies on enterprises’ transformation willingness, digital level, and income level as well as the proportion of (...)
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  • Reverse Knowledge Transfer in Cross-Border Mergers and Acquisitions in the Chinese High-Tech Industry under Government Intervention.Yi Su, Wen Guo & Zaoli Yang - 2021 - Complexity 2021:1-18.
    The high-tech industry is the main force promoting the development of China’s national economy. As its industrial economic strength grows, China’s high-tech industry is increasingly using cross-border mergers and acquisitions as an important way to “go out.” To explore the rules governing the process and operation mechanism of reverse knowledge transfer through the CBM&A of China’s high-tech industry under government intervention, a tripartite evolutionary game model of the government, the parent company, and the subsidiary as the main subjects is constructed (...)
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  • Member Selection for the Collaborative New Product Innovation Teams Integrating Individual and Collaborative Attributions.Jiafu Su, Fengting Zhang, Shan Chen, Na Zhang, Huilin Wang & Jie Jian - 2021 - Complexity 2021:1-14.
    As the first stage of the formation of a collaborative new product innovation team, member selection is crucial for the effective operation of the CNPI team and the achievement of new product innovation goals. Considering comprehensively the individual and collaborative attributions, the individual knowledge competence, knowledge complementarity, and collaborative performance among candidates are chosen as the criteria to select CNPI team members in this paper. Moreover, using the fuzzy set and social network analysis method, the quantitative methods of the above (...)
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  • Winning and Losing Relationship: A New Method of University Ranking in the Case of Countries along the Belt and Road.Jin Liu, Songyue Lin, Manling Wu & Wenjing Lyu - 2021 - Complexity 2021:1-13.
    From the perspective of the complex system, university ranking is a complex system that involves multiagent actors, which evolve over time. Yet, current major university rankings fail to reflect the system dynamics of the university innovation system. In this paper, we apply the complex system model in the field of the university innovation system in the context of university ranking in the countries along the Belt and Road, which is a long-term overlooked field. We introduce a new method of university (...)
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  • Evolution of a Technology Standard Alliance Based on an Echo Model Developed through Complex Adaptive System Theory.Hong Jiang, Chen Chen, Shukuan Zhao & Yuhao Wu - 2020 - Complexity 2020:1-15.
    The evolution of the technology standard alliance is examined using complex adaptive system theory. Taking TSA as a dynamic CAS, an echo model is constructed to depict the mechanism of its evolution, and a model is simulated on the NetLogo platform. The echo model includes a basic model, an extended model, and a three-layer echo model. The adhesive aggregation of agents is explained, and the three evolutionary stages of agents’ entry, migration, and exit are analyzed. Moreover, the adaptability of agents (...)
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  • Research on the Coordination Mechanism of Value Cocreation of Innovation Ecosystems: Evidence from a Chinese Artificial Intelligence Enterprise.Yu Chen, Yantai Chen, Yanlin Guo & Yanfei Xu - 2021 - Complexity 2021:1-16.
    This paper models the game process of the value cocreation of enterprises based on evolutionary game theory. The factors influencing value cocreation are found through mathematical analysis. Taking iFLYTEK as an example, a representative enterprise of artificial intelligence in China, six factors affecting value cocreation are verified, which are the excess return rate, the distribution coefficient of the excess return rate, coordination costs in the system, the cost-sharing coefficient, imitation costs, and penalties. These six factors have a profound impact on (...)
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