  The 8th edition of the Xixian Innovation Cloud Forum, co-organised by the Ministry of Education, the IIDPF under the Ministry of Science and Technology and the Centre for Science and Technology Strategy and Policy Research, was held online on 30 December 2021 from 11:00-13:00. Professor Tang Chaoying from the School of Economics and Management of the University of Chinese Academy of Sciences (UCAS) gave a talk on "The Impact of Knowledge Base and Knowledge Network on Research Creativity". The forum was hosted by Professor Zeng Jingjing, Director of the Center for Science and Technology Strategy and Policy Research, and more than 100 students and faculty from Tsinghua University, University of Chinese Academy of Sciences, Wuhan University, Renmin University of China, Huazhong University of Science and Technology, and Zhongnan University of Economics and Law attended the forum online.
  1. Creativity research moves from psychology to management
  Amabile et al. propose the theory of the elements of creativity, in which the formation of individual creativity depends on three complementary rather than alternative factors: work motivation, professionally relevant knowledge and creativity-related skills. Thus, introducing the study of creativity into the field of management.
  2. A phenomenon to be studied: scientific creativity
  Scientific creativity is reflected in the results of patents, new products, etc. and is not exactly the same as innovation. There are two types of scientific creativity: incremental and breakthrough. Breakthrough scientific creativity is an uncontrollable process, where scientific creativity is a breakthrough in existing scientific knowledge. Scientific creativity is the product of the interaction between the individual and the innovation system.
  There are several main behavioral measures of creativity: Consensus assessment technique (Amabile, 1996); scales: Zhou & George (2001) AMJ, Oldham & Cummings (1996) AMJ, Tierney et al. 1999) Personnel Psychology; other assessment + multi-temporal design; progressive versus breakthrough creativity (e.g., Madjar, Greenberg, & Chen, 2011); objective: patents, papers, new products.
  3. The origins of the relationship between knowledge and creativity
  The generative-exploratory model sees two main cognitive processes in creative activity: the generative process and the exploratory process. The generative process is the construction of initial mental representations in incomplete form; whereas the exploratory process is the refinement, processing and iterative modification of the representations developed in the primary process in response to the creative demands of the task. The cognitive theory of creativity (Ward, T. B.), the earlier knowledge is stored the less likely it is to be applied over time.
  Emotions are an important antecedent variable of creativity. Professor Tang explored the social function of individual positive emotions at the team level acting on team creativity through tacit knowledge sharing. Knowledge sharing and positive emotions are necessary to promote a positive link between value diversity and creativity; otherwise, diversity can have a negative impact on creativity. Therefore, value diversity, emotions and knowledge sharing need to be considered in team formation, training and performance evaluation. Analysis of paired data from 207 R&D staff from seven R&D units found that: external knowledge acquisition intensity had no direct effect on innovation performance, knowledge digestion had a significant positive effect on innovation performance, and the effect of external knowledge acquisition intensity on innovation performance was moderated by knowledge digestion ability.
  How can external heterogeneous technological knowledge acquired by companies with weak technological capabilities be transformed into team breakthrough creativity? The R&D team's analysis of data on 279 R&D members and corresponding team leaders from 70 R&D teams in 17 high-tech SMEs found that the external heterogeneous knowledge acquired by the R&D teams acts on the breakthrough creativity of the R&D teams through team-based exploratory activities, and that this path of action only exists when problem clarity is high.
  4. Knowledge networks: collaborative networks and knowledge factor networks
  The relationship between social networks and creativity has become a hot topic of research in recent years, due to the inherently social nature of creativity. What makes Silicon Valley a world-renowned innovation region is the unique socio-human environment, where the close interaction of heterogeneous groups brings about heterogeneous pollination and co-created innovations. At the heart of the resource network is the knowledge network. Knowledge networks include networks of collaboration and networks of knowledge elements.
  Relational characteristics in knowledge networks refer to the strength of ties, i.e. the frequency, duration and emotional attachment between subjects. 1) Strong ties: trust, facilitating knowledge flow (especially tacit knowledge) enhances creativity. Strong ties reduce individuals' adherence to their own unique perspectives and increase the likelihood of acquiring redundant homogeneous knowledge, showing an inverted U-shaped relationship with innovation performance (Perry-smith, 2006). Excessive network density tends to make network members more dependent on knowledge or information within the network, leading to cognitive inertia (Hansen, Mors, & Løvås, 2005). 2) Weak ties lead to heterogeneous knowledge (Perry-smith, 2006), while Zhou, Shin, Brass, Choi, and Zhang (2009) found that weak ties are also inversely related to employee creativity. (2009) also found an inverted U-shaped relationship between weak ties and employee creativity. Subjects in the structural hole position in an inventor's collaborative network have an information advantage and knowledge control, which facilitates knowledge creation (Hirst, Van, Zhou, Quintane, & Zhu, 2015). However, subjects in the structural hole position need time and energy to process the huge amount of information and face information overload, thus showing an inverted U-shaped relationship with creativity (Paruchuri, 2010). Four types of intermediaries (gatekeepers, coordinators, consultants, and liaisons (Gould & Fernandez (1989) Structural hole* connection strength (Tang, Zhang & Naumann, 2017).3) Centerer cost and speed advantages (Wang, Rodan, Fruin, & Xu, 2014) , status-sustaining psychology (Hemphä lä & Magnusson, 2012), and reduced willingness to search across borders (Wang et al, 2014).
  5. The impact of knowledge networks on research creativity
  What kind of observations do social networks offer us for studying creativity? In the case of knowledge networks, for example, there are three pathways in general: access to resources, motivation to create, and creative cognition. The first pathway is the effect on access to creative resources. Having more heterogeneous subjects, having more weakly connected social relations, being on the edge of the network structure, and being in a network with more open, factions, all facilitate access to heterogeneous knowledge and are conducive to creativity. The second path is the influence of network characteristics on the willingness to create. The creative process is full of risks and unknowns, and only a willing subject will engage in it. Subjects in a central position, or with a high density of networks and strong inter-subject ties, tend to maintain their central position and may be less likely to develop new knowledge, absorb new knowledge, and be less innovative, but more efficient in executing their creative solutions. The third pathway is the influence of network characteristics on the cognitive propensity to be creative. Knowledge creation requires a new understanding of existing knowledge from a new perspective and a new combination of relationships between existing knowledge. When knowledge networks are open, have low overall centrality and are relatively loose, subjects are more likely to hold autonomy and to remain sensitive to heterogeneous knowledge, which contributes to creative cognition.
  Accessed knowledge is an important component of managing the creativity of R&D employees. Professor Tang's findings suggest that the reliability of accessed knowledge moderates the relationship between the diversity of accessed knowledge and the centrality of the knowledge network within the team. Such centrality, in turn, increases employee creativity. The results of an empirical study based on 211 researchers and 257 technology developers show that external knowledge search increases employee creativity in the area of technology development, but not in the area of scientific research. Furthermore, the centrality of employees in the team's internal problem-solving network moderated the relationship between external knowledge search and creativity in the field of scientific research.
  Knowledge creation (especially exploratory creation) is an important mission of R&D teams in innovative companies. Professor Tang proposed that the relationship between the knowledge base of R&D teams and knowledge creation is influenced by the position of R&D teams in the corporate knowledge factor network and the position in the inventor collaboration network. Both the structural hole mean of the R&D team in the prior corporate knowledge factor network and the degree centrality mean in the corporate inventor collaboration network negatively moderate the relationship between the R&D team's knowledge base and knowledge creation.
  Internal knowledge portfolio is an important antecedent of corporate knowledge innovation. The consistency and diversity of an enterprise's knowledge base positively affects knowledge innovation, the density of an enterprise's internal cooperation network negatively regulates the relationship between the consistency and diversity of an enterprise's knowledge base and knowledge innovation, and the network degree central potential positively regulates the relationship between the consistency of the knowledge base and knowledge innovation. Corporate knowledge base is one of the important prerequisites for corporate innovation. Based on the patent data of 76 global 3d printing, ICT, wind energy and lithium battery industries from 1993-2013, the analysis results show that the consistency of corporate knowledge base positively moderates the relationship between corporate knowledge base diversity and corporate innovation. In addition, the concentration of industry knowledge networks and the consistency of firms' knowledge base enhance the positive relationship between knowledge diversification and firm innovation.
  The dichotomous innovation balance refers to a company engaging in both exploratory and tapping innovation. Exploratory innovation is a guarantee of long-term competitiveness, while tapping innovation is a guarantee of profitability from current technology, and achieving the dichotomous innovation balance is important for the survival and growth of a company. Efficient learning facilitates discovery innovation, while diverse knowledge facilitates exploration innovation, and the organisation of the R&D workforce will affect the ability of a company to achieve both efficient learning and diverse knowledge acquisition. Based on the analysis of patent data from 76 firms in four high-tech industries, it is found that the stability of R&D staff cooperation contributes to the dichotomous innovation equilibrium; the central tendency of the degree of cooperation network within a firm negatively moderates the relationship between professional heterogeneity of R&D staff and the dichotomous equilibrium.
  How to retain the knowledge of existing R&D staff and benefit from the knowledge brought by new R&D staff to enhance firm creativity. Empirical results based on invention patents of Chinese ICT firms suggest that co-invention networks of highly connected firms weaken the damage of outward mobility of R&D employees to firm creativity. In addition, the low centrality of firms in industrial co-invention networks reduces the contribution of inward mobility of R&D staff to firm creativity, and the low centrality of firms in industrial co-invention networks facilitates firms to benefit from the inward mobility of R&D staff.
  Among the changes in the key R&D intermediary roles are three types of intermediary roles that link internal and external organisations (contact, consultant, gatekeeper) and two types of intermediary roles that involve only internal organisations (coordinator, bridge). The analysis of 10,216 invention patent applications from 17 AI firms in the Derwent Innovation Index database for the period 2002-2019 revealed that changes in key developer contacts, consultants, gatekeepers and bridgers all positively influenced firms' exploratory innovation, and that the diversity of firms' knowledge base and the stability of R&D staff partnerships had a positive impact on key developer The relationship between changes in gatekeepers, bridgers and exploratory innovation is positively moderated by the diversity of the firm's knowledge base and the stability of the R&D partnership.
  6. Research Implications
  In the context of a new type of great power relationship, China is facing new challenges of technological "necking". To this end, the following research insights are proposed: Chinese enterprises attach great importance to organisational learning; use theories of organisational behaviour to guide corporate knowledge sharing; make knowledge management the underlying foundation of R&D innovation; focus on and build knowledge networks and cooperation networks at the industrial and regional levels; and explore new external sources of knowledge.
  Professor Tang shared her entire research journey, from how she discovered the problem to the step-by-step advancement of her research, which started with an interest and curiosity that drove her to conduct research on research creativity, followed by decades of persistence and dozens of publications in this field, which brought us a lot of inspiration and reflection. Professor Tang concluded by calling on everyone to join the team of big data analysis methods, to jointly study the relationship between knowledge and creativity, and to explore the path from organisational learning and knowledge network management to research creativity in Chinese enterprises under the current new pattern of great power relations.
  The lecture was successfully concluded.