Development Of Knowledge Networks Research Articles

Creating innovation capabilities for improving global health: Inventing technology for neglected tropical diseases in Brazil

Previous research on innovation capabilities in emerging economies shows knowledge networks tied to Western multinationals and national governments focused on economic growth. Less understood is the innovation capability building of emerging economies to achieve ‘good health’, an important Sustainable Development Goal. Here, we present a longitudinal study of a public research organization in an emerging economy and examine how it builds innovation capabilities for creating vaccines, drugs, and diagnostics for diseases primarily affecting the poor. We study FIOCRUZ in Brazil using archival, patent, and interview data about invention of technologies for neglected tropical diseases. We contribute novel insights into the evolution of knowledge networks, as national policy integrates innovation and health goals. We found significant diversification of local and foreign knowledge sources, and substantial creation of networks with public, private, and non-governmental organizations enabling collective invention. These R&D networks attract many multinationals to collaborate on socially driven innovation projects previously non-existent in their portfolios. The public research organization leads collaborations with multinationals and diverse partners, harnessing distributed international knowledge. Our results indicate emerging economies’ capabilities depend on elevating policies to increase health access for the poor to drive innovation and promoting local R&D to generate solutions to improve health.

Infrastructure for rapid open knowledge network development

AbstractThe past decade has witnessed a growth in the use of knowledge graph technologies for advanced data search, data integration, and query‐answering applications. The leading example of a public, general‐purpose open knowledge network (aka knowledge graph) is Wikidata, which has demonstrated remarkable advances in quality and coverage over this time. Proprietary knowledge graphs drive some of the leading applications of the day including, for example, Google Search, Alexa, Siri, and Cortana. Open Knowledge Networks are exciting: they promise the power of structured database‐like queries with the potential for the wide coverage that is today only provided by the Web. With the current state of the art, building, using, and scaling large knowledge networks can still be frustratingly slow. This article describes a National Science Foundation Convergence Accelerator project to build a set of Knowledge Network Programming Infrastructure systems to address this issue.

Knowledge Network Evolution of Smokers, Adaptive Behaviors and Enhancement of Knowledge Capability

Objectives: With the evolution of knowledge networks of smokers, we analyzed how adaptive behaviors affect the enhancement of the knowledge capability of their organization. Methods: Through the empirical analysis of 228 questionnaire data from smoker-dense zone, this paper conducts a regression analysis between the implementation of different behaviors and the capability improvement, in the context of knowledge flow evolution. Results: Conclusions show that different behavioral decisions of knowledge subjects have different influences on their knowledge capability, and the routine behaviors have a significant negative impact on their knowledge capability, while the imitative behavior and innovative behavior have a significant positive impact on the improvement of knowledge capability. These effects are also affected by the regulatory effects of the three stages of knowledge flow. Conclusion: In different stages of the functional evolution of the knowledge network of smokers, different behavioral decisions of knowledge subjects will promote or restrict their own knowledge capabilities. Based on the knowledge growth expectation, knowledge subjects can adopt different behavior strategies to achieve dynamic environment adaptation and gain competitive advantage.

The multidimensional clustering of health and its ecological risk factors

A diverse set of research has examined the ways in which population-level health and its ecological risk factors are embedded within self-reinforcing structures. Syndemic theory, for example, focuses on the co-occurrence of multiple diseases, whereas the spatial diffusion literature highlights the concentration of poor health among communities sharing geographic boundaries. This study combines these related but disciplinarily-isolated perspectives to examine the clustering of population-level health and its determinants across four dimensions: co-occurrence, spatial, temporal, and social network. Using data on U.S. county-level health outcomes and health factors from the Robert Wood Johnson Foundation's County Health Rankings, this study estimates associations between health outcomes within communities and the co-occurrence of community-level factors theorized to influence ecological health. Not only do health outcomes and their ecological risk factors cluster within counties, but also between geographically adjacent counties and counties connected via migration network pathways. Moreover, the self-reinforcing structures uncovered across the co-occurrence, spatial and network dimensions persist over time, and this clustering has consequences on county health and well-being. Rather than adopting the perspective that either health and its community-level factors should be broadly targeted and detached from local context or communities are different, have unique needs and thus should be treated in isolation, the approach advanced in this study identifies shared vulnerabilities in a way that allows for the development of knowledge networks between communities dealing with similar issues.

Still in the shadow of the wall? The case of the Berlin biotechnology cluster:

The evolution of knowledge networks has recently received a lot of attention from researchers. Empirical studies have shown that different types of proximities and network structural properties pla...

Still in the shadow of the wall? The case of the Berlin biotechnology cluster

The evolution of knowledge networks has recently received a lot of attention from researchers. Empirical studies have shown that different types of proximities and network structural properties play a decisive role in tie formation. The present paper contributes to this literature by arguing that while these are crucial, they do not capture the full range of localities’ influence on the evolution of knowledge networks. We support our argument with an empirical study on the development of the biotechnology knowledge network of Berlin from the early 1990s till 2016. The network was created by combining data on co-patenting, co-authorship and joint R&D projects. Forces driving the evolution of the network were identified with separable temporal exponential random graph models (STERGM). In addition to the ‘usual suspects’ (main proximity dimensions and structural factors), we found that the network is still developing in the ‘shadow of the wall’. The different social contexts in the different parts of the city of Berlin still hamper the establishment of collaborative ties between the former East and the former West Germany even 30 years after reunification.

On the structural evolution of the knowledge network and behaviors of the knowledge subjects

The variation of the network topology directly indicates the knowledge network evolution, the principal composition of which is the structural evolution. Based on the principles of both the minimum coupling costs between knowledge subjects and the network average value threshold, this paper constructs the evolution model of a small-world knowledge network. Using MATLAB programming, this paper analyzes the characteristics of the evolution of knowledge network. It then examines the main parameter changes and the distribution of the network node degree as well as its probability distribution and then proceeds to investigate the variation of the subjects’ knowledge level as well as the variation speed. The simulation results show that with the structural evolution of the knowledge network, the connection between the network subjects has been improved after numerous rewiring. Compared with the initial state, the total knowledge stock of the knowledge network and the average knowledge stock of the subjects are significantly enhanced.

Knowledge diffusion simulation of knowledge networks: based on complex network evolutionary algorithms

Based on the evolutionary algorithms of the four complex networks, the evolution of knowledge network is regarded as that of complex networks. With the heterogeneity of knowledge level, knowledge absorptive and innovative capacity and agents’ knowledge types considered, theoretical models of knowledge network evolution are constructed. Through numerical simulation, different network structures are analyzed in terms of their effects on the diffusion efficiency of the overall knowledge as well as of various types of knowledge. The simulation results show that: with the diffusion of the overall knowledge considered, although the overall knowledge level in a small-world structure is lower than the random network in the early and middle stage, it is close to the highest one later on; moreover, its growth rate is relatively higher among all four networks and its knowledge levels are distributed most uniformly. With regard to the diffusion of different types of knowledge, the small-world network is proved to produce the most uniform gap between knowledge types and help those dominant industries in the early stage remain advanced during the evolutionary process.

Software teams and their knowledge networks in large-scale software development

ContextLarge software development projects involve multiple interconnected teams, often spread around the world, developing complex products for a growing number of customers and users. Succeeding with large-scale software development requires access to an enormous amount of knowledge and skills. Since neither individuals nor teams can possibly possess all the needed expertise, the resource availability in a team's knowledge network, also known as social capital, and effective knowledge coordination become paramount. ObjectiveIn this paper, we explore the role of social capital in terms of knowledge networks and networking behavior in large-scale software development projects. MethodWe conducted a multi-case study in two organizations, Ericsson and ABB, with software development teams as embedded units of analysis. We organized focus groups with ten software teams and surveyed 61 members from these teams to characterize and visualize the teams’ knowledge networks. To complement the team perspective, we conducted individual interviews with representatives of supporting and coordination roles. Based on survey data, data obtained from focus groups, and individual interviews, we compared the different network characteristics and mechanisms that support knowledge networks. We used social network analysis to construct the team networks, thematic coding to identify network characteristics and context factors, and tabular summaries to identify the trends. ResultsOur findings indicate that social capital and networking are essential for both novice and mature teams when solving complex, unfamiliar, or interdependent tasks. Network size and networking behavior depend on company experience, employee turnover, team culture, need for networking, and organizational support. A number of mechanisms can support the development of knowledge networks and social capital, for example, introduction of formal technical experts, facilitation of communities of practice and adequate communication infrastructure. ConclusionsOur study emphasizes the importance of social capital and knowledge networks. Therefore, we suggest that, along with investments into training programs, software companies should also cultivate a networking culture to strengthen their social capital, a known driver of better performance.

Small business activity and knowledge exchange in informal interfirm networks

This article explores knowledge search strategies of technology-based small firms (TBSFs) and the role that informal and proximate relationships play in the development of knowledge networks, through which knowledge exchange occurs. Drawing on interfirm relationship and social network theory, we contend that TBSFs participate in informal networks to exchange technology, market and managerial knowledge, to the extent that these knowledge configurations facilitate acquisition of external knowledge critical for their learning processes by TBSFs. Results indicate that a firm’s engagement in the exchange of various sources of knowledge is directly related to its economic activity and strategic knowledge priorities, which shape the structural dimensions of interfirm informal networks. While informal networks remain informal, certain TBSFs formalize their participation as they obtain and combine knowledge resources that are important for their activity. In examining how different interests and roles impact participation in informal interfirm networks, this study contributes to the literature on small firms and collaborative relationships.

Demonstration projects in transition processes to sustainable energy and transport

In this paper, an analysis was made of the role of public support schemes funding demonstration, test and trial activities for sustainable development in energy and road transport. This paper presents the analysis of the effects of demonstration projects in transition processes to sustainable energy and transport in the Scandinavian countries on the development of knowledge networks and on interaction with users. The main purpose of this paper is: (1) to analyse the role of publically funded demonstration projects concerning changes in knowledge networks of project participants over time; (2) analysing policy priorities in collaboration by the public funding programmes. The paper addresses following research questions: (1) How successful are Scandinavian demonstration projects in contributing to the development of knowledge networks for sustainable energy and transport transitions? (2) Do Scandinavian demonstration programmes prioritise learning in international knowledge networks and user involvement? (3) How have demonstration projects contributed to transition processes?

Structural holes, knowledge intermediaries and evolution of the triple helix system with reference to the hard disk drive industry in Thailand

Abstract This article explores the evolutionary process underlying the development of the triple helix innovation system and the role of knowledge intermediaries in the process. It draws on the experience of knowledge network development in an SME cluster in the Thai hard disk drive industry. Conceptually, the evolutionary process starts with inter-firm networks, which occur in the form of supply chain-based vertical links and trade association or cluster-based horizontal links. These evolve into triple helix networks and culminate into the triple helix innovation system through the agency of network dynamics. Intermediaries enhance network development as sponsors, providing funds; as brokers, closing and bridging structural holes that disconnect network players; and as boundary spanners, facilitating knowledge circulation. The case study suggests that knowledge network development in Thailand has a long way to go before morphing into the triple helix innovation system. Some evidence of network dynamics was nonetheless detected; but for lack of trust in the triple helix culture the fledgling network dynamics fizzled out when the government prop, which initiated the process, was withdrawn. The article concludes by highlighting the need for policy to promote the culture of trust among network players and for knowledge intermediaries to be robustly systemic in their organization and operation.

An attractive choice: Education researchers' use of participatory methodology

Participatory methodologies are often favoured in education research. This study aimed to determine collaborative partnership trends between education researchers and teachers in order to understand the use of participatory theory and practice in education studies. Seven symposium presentations by education scholars from various higher education institutions were analysed using trend analysis from a community of practice theoretical framework. It emerged that participatory methodology denotes various characteristics which indicate favourable use by education researchers. Partnerships between education researchers and teachers share common goals, are contextual in nature, have a process-oriented emphasis and foreground knowledge exchange and the development of knowledge networks. In addition, collaborative partnerships between education researchers and teachers appear to be directed by an overarching philosophy of ‘care’.

Tacit Knowledge Network Development: The Comparative Analysis of Knowledge Threads in Complex Systems

Knowledge-based groups or communities are complex systems that emerge, evolve and mature through stages that display specific features and capabilities of the community or group. Understanding these capabilities and features are fundamental to building sustainable economic, social and learning networks systems. Understanding emergent behaviour within and beyond organizational communities requires understanding the social or sociological aspects in relation to the explicit formal/physical structures in the organization. Looking deeper into the development of informal networks across boundaries highlights the geographic structures and scales of knowledge flows and their influence on urban communities. Purpose – The purpose of the paper is to examine the theory of knowledge networks through applied research Design/methodology/approach – This is a case study approach, incorporating action research through embedded practice, utilizing interdisciplinary (or rather non-disciplinary) techniques and is thus a novel approach and application. Originality/value –This methodology translation of knowledge networks from theory into practice to yield little known or understood technical issues when working in social complex adaptive systems. Practical implications – The outcomes of the application contributes to the understanding of how, what and why sustainable social networks develop, offering the possibility of application in the field.

Portugal at the crossroads of change, facing the shock of the new: People, knowledge and ideas fostering the social fabric to facilitate the concentration of knowledge integrated communities

Portugal has recently achieved the average OECD level in terms of the number of researchers per thousand workforce and the need to continue fostering the advanced training of human resources and the concentration of knowledge integrated communities as drivers of larger communities of users is discussed in the context of changing and evolving patterns in Portugal. This requires an ongoing public effort, but also a better understanding of the effectiveness of the mix of public support mechanisms and private incentives for the development of knowledge networks and flows of skilled people in times of increased uncertainty. Our hypothesis gains from the experience of a unique set of international collaborations with leading institutions worldwide that has been successfully developed over the last years based on thematic R&D networks, integrating advanced training initiatives and programs of industrial affiliation. It is in this context that we frame our hypothesis and argue for the need for Portugal to continue attracting and fostering open and dynamic “creative communities”. The main policy implication of our analysis is that Portugal needs to double the number of researchers per thousand workforce in the coming years. This requires a broad social basis for science policies across a wide range of public and private sectors, as well as that innovation is considered together with competence building and the need to foster individual skills through the complex interaction between formal and informal qualifications. Emerging user-centered innovation requires users able to access new knowledge. This implies a broad societal engagement in knowledge activities, including higher education enrolment, and we need to strengthen the top of the research system in order to create a locus of knowledge production at the highest level. But it also implies consideration of the social shaping of technology, because incentives and infrastructures do not operate in a vacuum, but shape and are shaped by the particular context in which they operate. Strengthening external societal links and “system linkages” is critical in making the institutional changes required to meet the needs of global competition and the knowledge economy.

Latecomer firms and the emergence and development of knowledge networks: The case of Petrobras in Brazil

This paper addresses the emergence and development of firm-centred knowledge networks within learning and innovation systems in late-industrialising countries. A key contribution of the paper is conceptual and methodological: the development of an original typology of knowledge network properties to trace out changes in the form of networks as they evolve over time. A second contribution consists in providing an example of the application of the typology by examining the emergence and development of a firm-centred knowledge network in the case of Petrobras, the Brazilian oil company over more than 30 years between the late 1960s and the early 2000s. This demonstrates that the properties of Petrobras’ knowledge networks continuously evolved through a succession of stages towards (i) increasing intentionality in the management decision-making underlying network development, (ii) growing complexity and diversity in selected cognitive characteristics, and (iii) greater complementarity in the division of innovative labour between Petrobras and its network partners. These original results from applying the typology, in conjunction with retrospective historical methods, illustrate only one aspect of its potential value in the analysis of knowledge networks in late-industrialising economies: tracking out organisational evolution over long periods of time. Others include the comparative examination of network differences across different circumstances and the analysis of relationships between changes/differences in network properties and other characteristics of learning/innovation systems and their contexts.

Business associations and their contribution to knowledge networks in Mexico

Mexican businesses are organized in a highly complex system, comprising an enormous variety of associations that group individual firms according to sectors and geographical lines of division. These associations may constitute an efficient means of support for the construction of knowledge networks benefiting their members. We analyze academicindustry relationship in which business associations (BAs) of different types participate in order to explore the connection between different institutional settings and knowledge network development. We argue that the structure of BAs is a key factor in their ability to sustain networking. It is, therefore, possible to speak of structural advantages or disadvantages as regards the building of triple helix relations.

Knowledge network development in water resources and irrigation management: the case of CKNet‐INA in Indonesia

AbstractThe national water reform in Indonesia requires capable individuals and institutions for water management at national, regional and local level, and an external environment that enables institutions and individuals to perform according to stakeholders' expectations. Universities, research and study centres, and other knowledge centres (capacity builders) can play a strategic role as national human resources development instruments in providing education, training, assistance and guidance to support the needed competences.In 2005, 10 universities in Indonesia from Java, Sulawesi and Sumatra founded CKNet‐INA, a knowledge network with the objective to collaborate as a sustainable academic and professional community in the area of infrastructure, water and environment. On the basis of a demand‐oriented approach, selected capacity is strengthened in the universities, and effective capacity‐building services are developed and delivered in support of decentralized water resources management.From the experiences and lessons learned it is argued that knowledge network development is a feasible approach to enhance sustainable capacity building if: water sector knowledge needs are explicitly addressed with the sector; a network development strategy includes the delivery of cost recovering services; the management and governance of the network concentrate on building up trust while maintaining quality criteria. Copyright © 2008 John Wiley & Sons, Ltd.

The persistence of ‘capabilities’ as a central issue in industrialization strategies: How they relate to MNC spillovers, industrial clusters and knowledge networks

Summary Until late 1960s there was little interest in understanding technological change in developing countries. Since then, enormous conceptual and empirical advancements have been achieved. Martin Bell is one of the pioneering scholars, who in the 1970s introduced a significant push in the understanding of innovation in developing countries. Ranging from his original studies on the importance of the accumulation of firm‐level capabilities to more recent work, the authors discuss how Martin influenced research in three new domains: (i) MNCs and technology learning in industrialising countries; (ii) knowledge networks and innovation in clusters and (iii) the development of knowledge networks and capabilities over time in industrialising countries.

Learning by developing knowledge networks

A central challenge for research on how we should prepare students to manage crossing boundaries between different knowledge settings in life long learning processes is to identify those forms of knowledge that are particularly relevant here. In this paper, we develop by philosophical means the concept of adialectical system as a general framework to describe the development of knowledge networks that mark the starting point for learning processes, and we use semiotics to discuss (a) the epistemological thesis that any cognitive access to our world of objects is mediated by signs and (b)diagrammatic reasoning andabduction as those forms of practical knowledge that are crucial for the development of knowledge networks. The richness of this theoretical approach becomes evident by applying it to an example of learning in a biological research context. At the same time, we take a new look at the role of mathematical knowledge in this process.