Interactive knowledge exchanges under complex social relations: A simulation model of a developing country cluster

This is a model of knowledge exchange by informal interaction among agents in a low technology cluster. The paper studies these knowledge exchanges in an environment of complex social relations. This study tests whether the small-world network structure is the most favorable for knowledge exchanges in these environments, and explores the influence of social relations and network distance on magnitude and equity of knowledge diffused. The results show that, when knowledge exchanges are undertaken in environments of complex social relations, a small-world network structure may still be the best network structure facilitating the highest performance, but it is not the best in terms of the most equitable knowledge distribution. The results also confirms that the highest and most equitable knowledge distribution is achieved when there is perfect affinity among the agents. These results contribute to the existing series of studies on efficient network structures for knowledge diffusion, and on the broader literature on the social forces shaping learning and knowledge diffusion.     

基于外部知识网络利用的团队创新机制研究

本研究旨在考查基于团队外部知识网络利用的团队创新机制。通过对114个团队样本的研究,探讨了外部知识网络利用,知识整合,团队创新,以及团队内部社会资本的三个子维度——结构紧密度、关系亲密度、认知一致性的关系。结果表明外部知识网络利用能够促进团队创新,知识整合在其中承担了中介作用,认知一致性对于外部知识网络利用对知识整合的影响起到调节作用。     

Identification of technological knowledge intermediaries

Intermediaries in a technological knowledge network have recently been highlighted as crucial innovation drivers that accelerate technological knowledge flows. Although the patent network analysis has been frequently used to monitor technological knowledge structures, it has examined only sources or recipients of the technological knowledge by mainly estimating technological knowledge inflows or outflows of a network node. This study, therefore, aims to identify technological knowledge intermediaries when a technology-level knowledge network is composed of several industries. First, types of technological knowledge flows are deductively classified into four types by highlighting industry affiliations of source technologies and recipient technologies. Second, a directed technological knowledge network is generated at the technology class level, using patent co-classification analysis. Third, for each class, mediating scores are measured according to the four types. The empirical analysis illustrates the Korea’s technological knowledge network between 2000 and 2008. As a result, the four types of mediating scores are compared between industries, and industry-wise technological knowledge intermediaries are identified. The proposed approach is practical to explore converging processes in technology development where technology classes act as technological knowledge intermediaries among diverse industries.     

A knowledge accumulation approach based on bilayer social wiki network for computer-aided process innovation

Under the fierce competition, manufacturing companies pay more attention to innovation and the knowledge that enables innovation. Manufacturing process innovation is a knowledge-intensive activity, and efficient knowledge accumulation is the prerequisite and basis for computer-aided process innovation (CAPI). Hence, this research aims to build an open knowledge accumulation approach to obtain organised and refined process innovation knowledge (PIK). By considering the similarity of PIK network with biological neural network and combining the technical characteristics of social network with wiki, a novel PIK accumulation schema based on bilayer social wiki network is proposed. In social wiki network environment, PIK is accumulated in public knowledge space through participants’ social interactions and knowledge activities. The process of knowledge fusion is investigated to form the preliminary knowledge containing collective intelligence, and the mechanisms of collaborative editing and collaborative evolution are studied to refine the knowledge. The outcomes of this study lay the foundation for knowledge application of CAPI. Finally, a case study is presented to demonstrate the applicability of the proposed approach.     

Research and innovation in South African universities: from the triple helix’s perspective

Different from most prior research studying the influence of networks on scientific knowledge creation by taking on a single social-based perspective, this study offers an integrated frame based upon both social-based and knowledge-based views. This study incorporates quantitative bibliometric methods of analysis and network analysis. Based on 51,972 alternative energy patents in 1998–2012, we build knowledge networks composed of technological classifications and social networks capturing collaborations. Based on patent citation networks, we use citations in every period to calculate researcher’s knowledge creation performance. We hypothesize that centrality of researchers in the knowledge network and their knowledge creation display an inverted-U relationship. What’s more, we propose that this curvilinear relation is moderated by their structural holes and centrality in the collaboration network. Based on the negative binomial model with fixed effects and robust tests, results indicate that (1) locations of the researchers in knowledge network contribute more to knowledge creation when their centrality is moderate, rather than high or low; (2) at a moderate level of knowledge network centrality, the researchers, who occupy more central positions or span more structural holes in collaboration network, will benefit more than the ones who do not. The findings of this research, besides having implications for research on knowledge networks, have implications on scientometric indicators, multiple networks study, and knowledge creation process.     

Shaping the interdisciplinary knowledge network of China: a network analysis based on citation data from 1981 to 2010

This study builds the interdisciplinary knowledge network of China, which is used to catch the knowledge exchange structure of disciplines, and investigates the evolution process from 1981 to 2010. A network analysis was performed to examine the special structure and we compare state of the networks in different periods to determine how the network has got such properties. The dataset are get from the reference relationship in literature on important Chinese academic journals from 1980 to 2010. The analytical results reveal the hidden network structure of interdisciplinary knowledge flows in China and demonstrate that the network is highly connected and has a homogeneous link structure and heterogeneous weight distribution. Through comparing of the network in three periods, that is 1981–1990, 1991–2000 and 2001–2010, we find that the special evolution process, which is limited by the number of nodes, play an important influence on interdisciplinary knowledge flows.     

Knowledge convergence and organization innovation: the moderating role of relational embeddedness

Knowledge convergence is an important means of innovation. The study aims to explore how knowledge convergence influences innovation performance at an organizational level. Furthermore, we address the moderating role of network relational embeddedness on the innovation deriving from knowledge convergence. Our empirical analyses adopting negative binomial regression models employ patent counts and patent citations from the nanotechnology field. The findings reveal that the scientific intensity in the convergence between scientific knowledge and technological knowledge has an inverted U-shaped influence on innovation performance and that this association is flattened in organizations with high network relational diversity. Also, we find that the technological scope in convergence of technological knowledge self has an inverted U-shaped influence on innovation performance and that this association is steepened in organizations with high network relational strength. Our findings add understandings of knowledge convergence on organization innovation and also have important practical and political implications.

     

Bayesian Diagnostic Network： A Powerful Model for Representation and Reasoning of Engineering Diagnostic Knowledge

Engineering diagnosis is essential to the operation of industrial equipment. The key to successful diagnosis is correct knowledge representation and reasoning. The Bayesian network is a powerful tool for it. This paper utilizes the Bayesian network to represent and reason diagnostic knowledge, named Bayesian diagnostic network. It provides a three-layer topologic structure based on operating conditions, possible faults and corresponding symptoms. The paper also discusses an approximate stochastic sampling algorithm. Then a practical Bayesian network for gas turbine diagnosis is constructed on a platform developed under a Visual C environment. It shows that theBayesian net work is a powerful model for representation and reasoning of diagnostic knowledge. The three-layer structure and the approximate algorithm are effective also.     

包装机械故障诊断的新方法——神经网络专家系统(PMNS)

提出了一种基于知识与模糊神经网络专家系统故障诊断方法,设计了包装机械故障诊断的神经网络专家系统的知识获得、知识库、推理机制等主要功能模块,并实现了基于改进型神经网络的包装机械诊断专家系统。     

Absorptive and desorptive capacity configurations in supply chains: An inverted U-shaped relationship

The extant literature has highlighted the importance of knowledge transfer between a buyer and its supply network for strengthening supply chain competence. This is a bi-directional exchange where the buyer and supply network each act as the sender and receiver of knowledge. Prior research has however largely focused on the knowledge recipient only. We consider both sender and recipient using two key dynamic capabilities related to knowledge transfer: (i) desorptive capacity, which enables the safe transfer of knowledge from the sender; and, (ii) absorptive capacity, which enables the acquisition and assimilation of external knowledge by the recipient. Using the concept of ‘fit’, we investigate whether organisations strengthen supply chain competence when their desorptive capacity exceeds that of their supply network's (positive misfit) and consider the moderating role of the organisation’s and supply network’s absorptive capacity. Multiple regression analysis of survey data from 250 firms identifies an inverted U-shaped relationship between positive desorptive capacity misfit and supply chain competence. Further, this relationship is shown to be moderated by the supply network’s absorptive capacity level. The paper furthers our understanding of supply chain knowledge management enabling buyers and their supply networks to achieve more successful knowledge transfer outcomes.     

On the benchmarking method of patent-based knowledge flow structure: Comparison of Korea and Taiwan with USA

Summary This paper suggests an international benchmarking method of disembodied knowledge flow structure. Using patent citation as a proxy measure of disembodied knowledge flow, national knowledge network is developed. Structural equivalence measure is applied to comparing the knowledge network of Korea and Taiwan with that of USA. Static and dynamic comparison make it possible to benchmark disembodied knowledge flow structure efficiently and identify convergent and divergent industries between developing countries and USA. It is also a meso-study that could be conducive to building a comprehensive analytical framework of national innovation system.     

基于EBP模型的服务化制造业集群知识共享风险评价

通过与传统制造业集群的对比,分析了服务化制造产业集群的知识共享过程,识别了服务化制造业集群知识共享过程中关系、利益与知识共享能力三方面的知识流并生风险,构建了基于EBP（熵值法和BP神经网络法）的服务化制造业集群知识共享风险组合评价模型。通过实证分析验证了模型的有效性与合理性,并通过与BP神经网络模型的误差对比分析,证实了该模型在知识共享风险识别方面的准确度更高。所提供的模型方法可为服务化制造业集群企业知识共享风险管理提供决策支持。     

Knowledge Networks and Innovative Performance in an Industrial District: The Case of a Footwear District in the South of Italy

The traditional district literature tends to assume that: (1) the competitiveness of firms depends on external sources of knowledge; (2) all firms in a district benefit from knowledge externalities; (3) relying on external knowledge relationships necessarily means these are confined to the district area. Our case study of the Barletta footwear district in the South of Italy suggests otherwise. Based on social network analysis, we demonstrate that the local knowledge network is quite weak and unevenly distributed among the local firms. A strong local network position of a firm tended to increase their innovative performance, and so did their connectivity to extra-local firms. So, it mattered being connected either locally or non-locally: being co-located was surely not enough. Having a high absorptive capacity seemed to raise only indirectly, through non-local relationships, the innovative performance of firms.     

Multi-network embeddedness and innovation performance of R&D employees

Taking the perspective of multi-network embeddedness, this paper constructs the collaboration network of R&D organizations, the collaboration network and knowledge network of R&D employees based on the patent data of 879 R&D employees from 224 R&D organizations, and analyses factors that have significant impacts on R&D employees’ innovation performance. The results show that R&D employees’ knowledge combinatorial potential and knowledge diversity have significant positive impacts on their innovation performance. R&D employees’ degree centralities in the collaboration network mediate the impacts of their knowledge combinatorial potential and knowledge diversity on innovation performance. The degree centralities of R&D organizations moderate the impacts of R&D employees’ degree centralities on innovation performance.

     

Makers’ relationship network,knowledge acquisition and innovation performance: An empirical analysis from China

In makerspaces, the embeddedness in open communities helps makers to build relationship networks and gives them access to ample knowledge, which will be finally transformed into the source of innovation. Based on strong-weak ties theory and the knowledge-based view, this study divides the ties in the makers' relationship network into strong and weak ties according to the intensity and explores their effects on makers' knowledge acquisition and innovation performance, respectively. An empirical analysis of the data collected from 232 makers in China indicates that the makers' relationship network has an indirect positive effect on their innovation performance while knowledge acquisition plays a partial intermediary role between the makers’ relationship network and their innovation performance. The results can help makers focus more on building and maintaining a relationship network through open community embedding and give insights into how a makerspace helps makers build a relationship network to improve their knowledge integration and utilization efficiency.     

The Role of Large Multinationals in the Dutch Technology Infrastructure. A Patent Citation Analysis

This paper investigates the impact of large multinational firms on the Dutch technology infrastructure. More specifically, it asks how the structure of the knowledge flows network matters for diffusion of technological knowledge in the Dutch economy. Patent citation analysis based on European Patent applications is used to quantify this network. The paper finds that there are large differences between firms in terms of the density of their 'ego-network', and the amount of knowledge spillovers to the Dutch economy that they generate.     

Knowledge transfer in time of crisis: evidence from the Trentino region

The last decade has shown a shift of focus of the literature on networks to a more dynamic perspective, and towards the study of mechanisms that drive network evolution inside regions. The strategic behaviour of network agents and the evolution of networks may be affected by the occurrence of macroeconomic events external to the region. This paper assesses the impact of different factors on the trust created between agents through repetition of previous collaborations before and after the global economic recession of 2008. Main findings show that actors in periods of crisis prefer collaboration with trustful actors with whom they cooperated in the past, than to actors with whom they share common characteristics (proximities). In high-risk periods, the knowledge network is more inert, while in low risk periods, actors prefer to expand the knowledge network of the region, investing in global pipelines and importing knowledge from distant regions.     

The impact of small world on patent productivity in China

Based on the patent co-authorship data from State Intellectual Property Office of China, this paper examines the evolution of small world network and its impact on patent productivity in China. Compared with the western countries, the small-world phenomenon of the innovation network in China is becoming more obvious. Empirical result shows that the small world network may only have significant impact on patent productivity in those patent productive provinces, e.g., Beijing and Guangdong that filed larger number of patents. Although the collaborations in the network are more endurable in China than ones in western countries, it may be less efficient in transmitting knowledge because of large ratio of administration oriented state owned enterprises (SOEs). With larger ratio of SOEs, the small world network has longer path length and knowledge thus flows less efficiently in Beijing than in Guangdong. The policy implication of the findings lies in that the Chinese government should let the market rather than the administration determine the collaboration of technological innovation, in order to encourage innovation and establish an effective small world network for speeding up flow of knowledge among different type of firms during the innovative process.     

The knowledge network dynamics in a mobile ecosystem: a patent citation analysis

The paradigm of the mobile ecosystem is rapidly changing, especially since the uction of smart devices. New important players are emerging, and the scope of the mobile ecosystem is expanding and encroaching on the technological boundaries of other IT ecosystems. However, our understanding of the mobile ecosystem has been limited given the few existing studies. Therefore, in this paper, we empirically examine the network structure of a mobile ecosystem by measuring the technology knowledge flows between firms based on a patent citation analysis of the mobile industry. We found that platform providers are emerging as the center of the knowledge flow activity in the ecosystem. By introducing a new network index, the Network Concentration Index, which measures a firm’s knowledge concentration ratio toward subsectors, we also found that each platform provider shows distinctive changing patterns in their technology knowledge network and that each is forming its own sub-network with increased influence on affiliated firms.     

A dynamic curation method for manufacturing-related knowledge

A method for the dynamic curation of manufacturing-related knowledge is proposed, based on the impact of successive paradigm introduction on the network structure within manufacturing companies. This draws together manufacturing system structure in terms of interacting component network types, the nature and consequences of knowledge silos and the underpinning dichotomous influence of language. The need and opportunities for an objective- rather than subjective paradigm-based view of manufacturing are identified, leading to a curation process in which paradigms and other knowledge specialisms are different viewpoints based on particular models of manufacturing processes and resources. The consequences of this are explored in terms of knowledge silo reduction, improved communication within component social- and information networks, increased operational resilience and better informed decision-making for future business.