Structure Of Knowledge Networks Research Articles

Potential index: Revealing the future impact of research topics based on current knowledge networks

• The relationship between the impact of a research topic and its knowledge structure is investigated. • Potential index, an immediate indicator based on the current knowledge network structure, is proposed to model the future impact of research topics. • Knowledge novelty and diversity, quantified by the betweenness centrality and network entropy, are considered two major driving fore of topic impact. • The proposed indicator is highly correlated with the topic impact and fits the developing trend well. It serves as a promising predictor for the scholarly impact of research topics. As the volume of scientific publications has been growing at an increasingly rapid speed, it is important to identify prominent research trends for scientists and institutions. While a considerable number of researchers have attempted to map the current state of scientific research, more efforts should be made to reveal potentially influential research topics. In this study, we investigate the relationship between the scientific impact of a research topic and the structure of its knowledge network. A novel indicator, potential index , is proposed to model topic impact based on the structural information. It is an immediate indicator with two components: knowledge novelty and diversity, which are operationalized using the concepts of betweenness centrality and network entropy. The empirical results show that potential index serves as a good predictor of future topic impact, with a high R 2 and positive correlation. Its superiority sustains when used as the input feature of regression models. Moreover, the proposed index achieves better results, and the differences between it and other features become more prominent as the model complexity increases. Quantitative and qualitative analysis on the topic evolution process is also conducted to explain the change in the proposed indicator. This study contributes to the research of scientific impact modeling by establishing an explicit relationship between the impact of topics and the knowledge structure, and is thus helpful in predicting the potential impact of research topics.

Knowledge integration between technical change and strategy making

This paper looks at the different strategies that two of the tire industry’s most prominent players, Pirelli and Michelin, deployed to exploit a radical process innovation: robotized, modular manufacturing. This paper argues that Pirelli, originally the technological follower, could develop a more nuanced, complex and ultimately successful strategy thanks to its superior knowledge integration capabilities. Empirically, we examine the structural characteristics and evolution of inventors’ networks in the two companies to reveal their knowledge integration capabilities. We apply the cohesive blocking method developed by White and Harary (Sociol Methodol 31(1):305–359, 2001) to argue that Pirelli, while relying on comparable skills in terms of technical fields, leveraged a more connected, cohesive and structured skills than Michelin. On this basis, it could develop and deploy a more complex strategy that better fit the characteristics of the new process technology. Pirelli’s knowledge network structure enhanced its knowledge integration capabilities and allowed for a more efficient fit between technology and strategy.

International Knowledge Sourcing by Foreign MNE Subunits: Competence Creating vs. Exploiting

This paper examines the patterns of international knowledge sourcing in competence- creating (CC) vs competence-exploiting (CE) types of innovative activity by foreign-located MNE subunits in the pharmaceutical industry. We use backward patent citations to establish the structure of the knowledge sources on which foreign- located subunits rely in developing new inventions. For the period 1976-2015 we examine the effects on international knowledge search for foreign subunits of their capacity to draw upon different types of organizational ties in a relational system, and show the relative significance of local, diverse knowledge sourcing of CC subunits vs the more international, application focus of CE subunits. To further understand the knowledge landscape, we provide a descriptive investigation of the changing structure of CC vs CE knowledge networks over time, and compare the change in composition of sources. We discuss the organizational affiliations and differentiated networks within which foreign subunits source knowledge to develop innovative activity. Our findings shed light on the conditions under which foreign-located subunits source knowledge internationally and the impact external knowledge sources have on this trend.

Structure and resilience of local knowledge networks: the case of the ICT network in Trentino

ABSTRACT Literature on regional innovation systems (RIS) points to the importance of the knowledge network inside the RIS. Empirics have shown the importance of certain pivotal actors for the RIS, however, their identification differs from case to case due to the different embeddedness of the actors to the knowledge network. This paper traces these influential actors for the Trentino information and communication technologies (ICT) innovation system, by analysing its knowledge network, for understanding their contribution to the resilience of the network. The local knowledge network is developed around a tightly knit core of key actors, whose malfunction would raise several issues for knowledge management and funding.

Impacts of malicious attacks on robustness of knowledge networks: a multi-agent-based simulation

Purpose Malicious attacks extremely traumatize knowledge networks due to increasing interdependence among knowledge elements. Therefore, exposing the damage of malicious attacks to knowledge networks has important theoretical and practical significance. Despite the insights being offered by the growing research stream, few studies discuss the diverse responses of knowledge networks’ robustness to different target-attacks, and the authors lack sufficient knowledge of which forms of malicious attacks constitute greater disaster when knowledge networks evolve to different stages. Given the irreversible consequences of malicious attacks on knowledge networks, this paper aims to examine the impacts of different malicious attacks on the robustness of knowledge networks. Design/methodology/approach On the basic of dividing malicious attacks into six forms, the authors incorporate two important aspects of robustness of knowledge networks – structure and function – in a research framework, and use maximal connected sub-graphs and network efficiency, respectively, to measure structural and functional robustness. Furthermore, the authors conceptualize knowledge as a multi-dimensional structure to reflect the heterogeneous nature of knowledge elements, and design the fundamental rules of simulation. NetLogo is used to simulate the features of knowledge networks and their changes of robustness as they face different malicious attacks. Findings First, knowledge networks gradually form more associative integrated structures with evolutionary progress. Second, various properties of knowledge elements play diverse roles in mitigating damage from malicious attacks. Recalculated-degree-based attacks cause greater damage than degree-based attacks, and structure of knowledge networks has higher resilience against ability than function. Third, structural robustness is mainly affected by the potential combinatorial value of high-degree knowledge elements, and the combinatorial potential of high-out-degree knowledge elements. Forth, the number of high in-degree knowledge elements with heterogeneous contents, and the inverted U-sharp effect contributed by high out-degree knowledge elements are the main influencers of functional robustness. Research limitations/implications The authors use the frontier method to expose the detriments of malicious attacks both to structural and functional robustness in each evolutionary stage, and the authors reveal the relationship and effects of knowledge-based connections and knowledge combinatorial opportunities that contribute to maintaining them. Furthermore, the authors identify latent critical factors that may improve the structural and functional robustness of knowledge networks. Originality/value First, from the dynamic evolutionary perspective, the authors systematically examine structural and functional robustness to reveal the roles of the properties of knowledge element, and knowledge associations to maintain the robustness of knowledge networks. Second, the authors compare the damage of six forms of malicious attacks to identify the reasons for increased robustness vulnerability. Third, the authors construct the stock, power, expertise knowledge structure to overcome the difficulty of knowledge conceptualization. The results respond to multiple calls from different studies and extend the literature in multiple research domains.

Pattern and trend of scientific knowledge production in North Korea by a semantic network analysis of papers in journal titled technological innovation

This study aims to examine current trends and patterns of North Korea’s knowledge production in science and technology (S&T) by employing scientometrics analysis. In order to capture the distinctive nature and characteristics of S&T activities in the Global South, this study analyzes co-occurring keywords of papers in the North Korean journal titled Technological Innovation to construct and visualize semantic and network structure of scientific knowledge. Although S&T has long been emphasized as an important means of rebuilding the economy and society in the country, research and development (R&D) activities have been veiled in the shadows, mainly due to difficulties in accessing adequate data and information. The results found that the terms “use” and “method” are predominately associated with a variety of keywords concerning urgent domestic issues regarding energy resources, agriculture, virus, and industrial automation. This pattern of knowledge production is manifested in the national S&T policy framework that has primarily focused on applied and problem-solving knowledge and techniques responding to social and economic needs. While North Korea has embraced S&T as a strategic means to cope with challenges encountered in its autarkic economy, a close and interactive relationship has established between science, technology and society.

The impact of dual network structure on firm performance: the moderating effect of innovation strategy

ABSTRACT Firm innovation is embedded in a collaboration network among researchers and a knowledge network composed of knowledge elements; the two networks are decoupled. Guided by social network theory, this study puts forward the definition and the classification of firm dual network structure, probes into the influence of dual network structure on firm performance, and explores the alignment between innovation strategy and firm dual network structure. We conduct an empirical study of 183 listed companies in China from 2004 to 2018. It is found that the four types of dual network structure all have positive impacts on firm performance, and the impact of a collaboration network is slightly higher than that of a knowledge network. Besides, innovation strategy plays a positive moderating role in the relationship between dual network structure and firm performance. Our findings provide new ideas for firms to identify and optimise knowledge and collaboration network structures and match them with innovation strategy to improve performance.

Research on Teachers’ Knowledge Sharing Features Based on Departmental WeChat Group

The article analyzes the knowledge sharing process and behavior of teachers in the network professional community through social network analysis and content analysis. A semester of interactive data is selected as a sample in the college WeChat group. It analyzes social network structure of network professional community knowledge sharing and the interactive relationship from the aspects of community map, density, centrality, cohesive subgroups, core-edge, etc. The article analyses that, teachers’ knowledge sharing in departmental WeChat group presented the characteristics about complexity of shared subjects, unity of shared knowledge, missing interactions and sharing potential.

Analysing the structure of bioplastic knowledge networks in the automotive industry

Analysing the structure of bioplastic knowledge networks in the automotive industry

Analysing the structure of bioplastic knowledge networks in the automotive industry

The purpose of this paper is to understand the structure and characteristics of bioplastic knowledge flows between organisations and the technology in the automobile field. However, the existing network analysis method has the limitation in that it can only analyse the structural characteristics and major actors of the knowledge network. In order to overcome these limitations, we apply the bow-tie model. In particular, we select patent citation information from the global automobile companies Hyundai and Toyota, which have set environmental sustainability as a corporate management priority. The results suggest that these automobile companies have a virtuous circle in bioplastic technology. They internalise outside knowledge through the strategic collaboration and then disseminate this knowledge. We also find that there are companies that play an important role in the flow of knowledge. The methodologies used in this paper can gainfully be applied to the analysis of knowledge flow in other fields.

Enterprise supply chain risk assessment based on improved neural network algorithm and machine learning

It is of practical significance to study the decision-making subject in the supply chain under the influence of risk aversion to make a decision and make the supply chain compete in an orderly market environment. In order to improve the effect of enterprise supply chain risk assessment, this paper improves the traditional neural network algorithm, combines machine learning methods and supply chain risk assessment time requirements to set system function modules, and builds the overall system structure. Considering the multiple relationship attributes of supply chain risk knowledge, this paper uses a multi-element semantic network to represent the network structure of supply chain risk knowledge, and proposes a multi-level inventory control modelThis is based on the inventory of the coordination center and other retailers’ procurement/relocation strategy models. After building the model, this paper designs a simulation test to verify and analyze the model performance. The research results show that the model proposed in this paper has a certain effect.

Differential Equations E-course in Nomotex DLS

The electronic course “Differential Equations” in the Digital Learning System (DLS) NOMOTEX is developed and used for the mathematical training of future engineers. The artcle presents the content and features of the development of the module, as well as the methodology for conducting classroom studies in a digital educational environment. In the Nomotex DLS, the e-course is presented as a neural network structure of knowledge a tree. The content of the e-course is divided into chapters and paragraphs. Within a paragraph, the content is presented in the form of units of knowledge called quanta. The structure of quanta is described in detail, examples are given. The peculiarity of the described methodology is the preservation of traditional forms of education lectures and seminars with the use of a digital educational environment together. At the same time, in the learning process using the NOMOTEX DLS, traditional classroom lessons change significantly. The features of conducting lectures and seminars, measures for monitoring students’ knowledge are described. The Digital Learning System NOMOTEX allows you to implement various courses, forming the content of lectures and seminars from the existing knowledge bank. E-course, usually a part of the course “Integrals and Differential Equations”, read to future engineers in the spring semester of the first year at the Bauman Moscow State Technical University.

Innovation and diversity: the role of knowledge networks in the inventive capacity of cities

The aim of this paper is twofold. First, it aims to investigate whether the structure of knowledge networks (within and across urban areas) is important for the inventive capacity of cities. Second, it analyses whether the diversity and variety of the industrial structures of cities influence local knowledge networks and, consequently, foster invention. The research analyses co-patenting activities at firm level in the Italian provinces during the period 2004–2016. Patents’ data have been retrieved from the European Patent Office PATSTAT database. Results show that agglomeration economies of inventors are the most important force in fostering local invention capacity. However, the structure of knowledge networks also impacts on invention productivity. Moreover, either the impact of agglomeration economies of inventors or the structure of knowledge networks on local invention capacity increases when there is greater variety in the local industrial structure.

Knowledge networks and industrial structure for regional innovation: An analysis of patents collaborations in Italy

AbstractThe aim of the research is to investigate whether the structure of knowledge networks and the variety of the local industrial structure are important for regional innovation and if the interplay between these two forces has an additional effect on local innovativeness.The research analyses co‐patenting collaborations at firm level in the Italian provinces in three five‐year intervals in the period 2001–2016. Results show that the structure of knowledge networks and agglomeration economies of inventors boost local inventive capacity. It also highlights how these forces have an increasing impact on innovation as the variety of the area increases.

Knowledge structure, network structure, exploitative and exploratory innovations

ABSTRACTTaking the data of 20,863 patents in the field of Artificial Intelligence between 2000 and 2018 as an example, this paper examined the relationships among organisations’ knowledge structure, network structure, exploratory innovation and exploitative innovation. The results show that organisations’ knowledge combinatorial potential and knowledge diversity have positive effects on both exploratory innovation and exploitative innovation. Organisations’ degree centrality and structural holes in the collaboration network can partly mediate the relationships between their knowledge structure and exploratory and exploitative innovations.

Can a golf course support biodiversity and ecosystem services? The landscape context matter

In the last 30 years, the number of golf courses has increased dramatically worldwide. Since no other sport occupies and manages such large areas of green space, landscape context is crucial for determining their impacts or benefits. (1) Examine how they affect the main landscape socio-environmental landscape components; (2) analyze the knowledge network structure characterizing the research focused on golf courses; (3) discuss the most common best management practices to mitigate their environmental impacts; and (4) suggest new research perspectives. This paper has reviewed 239 papers from academic library databases through a literature review and co-word network analysis. Golf courses have impacted negatively on water and soil components, while positively on biodiversity, ecosystem services, and tourism, mainly in urban contexts. The best management practices have focused on soil, biodiversity and ecosystem services, water quality and quantity, and have given specific indications for amphibians, birds, turtles, and bee species. Few articles have considered the landscape perspective, despite the potential impact on natural or semi-natural landscapes. New clusters of research and management issues, in order to link biodiversity conservation with landscape perspective, have emerged: the need to increase (1) studies focused on the effects of golf courses on the ecological processes behind the functioning of the landscape, taking into account its composition and spatial configuration; (2) the proportion of native vegetation in the landscape composition, and density and complexity of vegetation in the landscape configuration.

Methodological research on partial least squares structural equation modeling (PLS-SEM)

PurposeThe purpose of this paper is to explore the knowledge infrastructure of methodological research on partial least squares structural equation modeling (PLS-SEM) from a network point of view. The analysis involves the structures of authors, institutions, countries and co-citation networks, and discloses trending developments in the field.Design/methodology/approachBased on bibliometric data downloaded from the Web of Science, the authors apply various social network analysis (SNA) and visualization tools to examine the structure of knowledge networks of the PLS-SEM domain. Specifically, the authors investigate the PLS-SEM knowledge network by analyzing 84 methodological studies published in 39 journals by 145 authors from 106 institutions.FindingsThe analysis reveals that specific authors dominate the network, whereas most authors work in isolated groups, loosely connected to the network’s focal authors. Besides presenting the results of a country level analysis, the research also identifies journals that play a key role in disseminating knowledge in the network. Finally, a burst detection analysis indicates that method comparisons and extensions, for example, to estimate common factor model data or to leverage PLS-SEM’s predictive capabilities, feature prominently in recent research.Originality/valueAddressing the limitations of prior systematic literature reviews on the PLS-SEM method, this is the first study to apply SNA to reveal the interrelated structures and properties of PLS-SEM’s research domain.

Coevolutionary Characteristics of Knowledge Diffusion and Knowledge Network Structures: A GA-ABM Model

The co-evolutionary dynamics of knowledge diffusion and network structure in knowledge management is a recent research trend in the field of complex networks. The aim of this study is to improve the knowledge diffusion performance of knowledge networks including personnel, innovative organizations and companies. In order to study the co-evolutionary dynamics of knowledge diffusion and network structure, we developed a genetic algorithm-agent based model (GA-ABM) by combining a genetic algorithm (GA) and an agent-based model (ABM). Our simulations show that our GA-ABM improved the average knowledge stock and knowledge growth rate of the whole network, compared with several other models. In addition, it was shown that the topological structure of the optimal network obtained by GA-ABM has the property of a random network. Finally, we found that the clustering coefficients of agents are not significant to improve knowledge diffusion performance.

Research Trend Analysis on Practical Arts (Technology & Home Economics) Education Using Social Network Analysis

This study analyzed research trends in the field of Practical Arts (Technology & Home Economics) education. From 958 articles published between 2010 and 2018 in the Journal of Korean Practical Arts Education (JKPAE), Journal of Korean Home Economics Education Association (JHEEA), and Korean Journal of Technology Education Association (KJTEA), 958 keywords were extracted and analyzed using NetMiner 4. When the general network structure was analyzed, keywords such as practical arts education, curriculum, textbook, home economics education, and students were high in the degree centrality and closeness centrality, and textbook, practical arts education, curriculum, student, home economics education, and invention were high in the node betweenness centrality. The cluster analysis showed that a four-cluster solution was most appropriate: cluster 1, technology and experiential learning activities; cluster 2, curriculum studies and practical problem; cluster 3, relationships; and cluster 4, creativity and character education. The three journals showed differences in the knowledge network structure: The topics of JKPAE and JKHEEA focused on general content knowledge and curriculum, while the topics of KJTEA were spread across invention and creativity education, and curriculum studies.

Neural network model of mathematical knowledge and development of information and educational environment for mathematical training of engineers

The paper proposes a new model of mathematical knowledge representation based on the hierarchical neural network structure of the links between various elements of knowledge. The concept of the level of knowledge and the minimum element of knowledge-«the quantum of knowledge» are introduced. On the base of the developed model, the structuring of mathematical knowledge corresponding to the basic mathematical training of engineers was carried out. The information and educational environment Nomotex was developed for mathematical training of engineers based on the proposed model of knowledge representation and a unique collection of 3D animation of all basic mathematical knowledge, as well as examples of the use of knowledge in engineering. The information and educational environment allows implementing individual educational trajectories in which the educational process is automatically formed from the neural network structure of knowledge according to the specified output competences of the engineer. A specialized software for visualizing educational trajectories was developed. Informational and educational environment allows to realize the multilevel and continuity of mathematical preparation, taking into account the nature of the activity of engineers in their mathematical preparation, taking into account the specifics of engineering training in mathematical courses. The information and educational environment allows implementing distance education, creating online courses, video lectures and automated testing. The introduction of the information and educational environment provides an increase in the attractiveness of the learning process through the extensive use of 3D visualization and animation, as well as computer game elements in the process of mathematical learning. Information and educational environment NOMOTEX, provides the possibility of implementing a systematic approach in the study of mathematical knowledge. The results of the experimental implementation of the information and educational environment in the educational process of engineers at the Bauman MSTU are presented.