Dynamics Of Knowledge Flows Research Articles

Desempenho de spin-offs e startups brasileiras: Um estudo sobre a evolução tecnológica a partir do empreendedorismo e das redes

Objective: to understand the relationships in advance of technological maturity and organizational performance in academic spin-offs and Brazilian startups. Method: quantitative research, with the application of 62 questionnaires, 17 of which were used as a pre-test. Originality/Relevance: this paper develops an approach oriented towards knowledge-intensive entrepreneurship in the context of a developing country, using data obtained from academic spin-offs and startups, based on an original model that relates the studied constructs. Results: empirical results made it possible to highlight the importance of Entrepreneurial Orientation as an antecedent of both Knowledge Conversion Capacity and Network Capacity. Theoretical/methodological contributions: aspects related to Entrepreneurial Orientation, Knowledge Conversion Capacity, Network Capacity and Technological Maturity were articulated in a conceptual model with a view to ultimately identifying the determinant mechanisms of Organizational Performance. Social/Management Contributions: the findings underscore the role of the ecosystem as a critical meta-structure for entrepreneurial development. This is because the components of the Entrepreneurial Orientation at the firm level are intrinsically connected with the diffusion of a culture of entrepreneurship in the agents. Additionally, both the Knowledge Conversion Capacity and the Network Capacity encompass the dynamics of interactions and knowledge flows between the firm and agents with complementary capacities. Thus, the results of this research underscore the need to develop a systemic orientation for understanding new knowledge-intensive enterprises.

Headquarter and Subsidiaries: Analyzing a Social Media Platform Within MNCs

Knowledge sharing and knowledge transfer within the corporation form an important source of knowledge capital within multinational corporations (MNCs). With the development of social media technologies, more and more MNCs are adopting knowledge sharing platform to facilitate the knowledge sharing and knowledge transfer in their global network, and break the knowledge silo across geographical boundaries. The adoption of this new technology is expected to improve MNCs’ competitive advantage by reducing manufacturing cost, improving employee performance, facilitating product development and localization, and advancing innovation. In this research, we employ a unique dataset from a social media knowledge sharing platform within a leading multinational manufacturing company headquartered in Europe. We estimate a Hidden Markov Model (HMM) that explicitly allows employee latent engagement to drive employee knowledge sharing decisions on this social media platform, and examine the dynamics of knowledge flow between corporate headquarter and subsidiaries). We illustrate that by contributing more answers and high quality answers on the platform, receiving unit members can improve peers’ engagement towards them, and obtain higher knowledge benefit in the long run. In addition, while social media platform is employed to break the knowledge silo, our results suggest that colocation has a positive impact on knowledge sharing, thus lead to formation of knowledge silo along the boundary between headquarter and subsidiary units. However, engagement and knowledge sharing towards receiving unit can moderate the colocation effect thus break the knowledge silos. Our results provide important managerial implications for implementation of future knowledge sharing platforms.

A novel machine-learning approach to measuring scientific knowledge flows using citation context analysis

We measure the knowledge flows between countries by analysing publication and citation data, arguing that not all citations are equally important. Therefore, in contrast to existing techniques that utilize absolute citation counts to quantify knowledge flows between different entities, our model employs a citation context analysis technique, using a machine-learning approach to distinguish between important and non-important citations. We use 14 novel features (including context-based, cue words-based and text-based) to train a Support Vector Machine (SVM) and Random Forest classifier on an annotated dataset of 20,527 publications downloaded from the Association for Computational Linguistics anthology ( http://allenai.org/data.html ). Our machine-learning models outperform existing state-of-the-art citation context approaches, with the SVM model reaching up to 61% and the Random Forest model up to a very encouraging 90% Precision–Recall Area Under the Curve, with 10-fold cross-validation. Finally, we present a case study to explain our deployed method for datasets of PLoS ONE full-text publications in the field of Computer and Information Sciences. Our results show that a significant volume of knowledge flows from the United States, based on important citations, are consumed by the international scientific community. Of the total knowledge flow from China, we find a relatively smaller proportion (only 4.11%) falling into the category of knowledge flow based on important citations, while The Netherlands and Germany show the highest proportions of knowledge flows based on important citations, at 9.06 and 7.35% respectively. Among the institutions, interestingly, the findings show that at the University of Malaya more than 10% of the knowledge produced falls into the category of important. We believe that such analyses are helpful to understand the dynamics of the relevant knowledge flows across nations and institutions.

Geographical dynamics of knowledge flows: descriptive statistics on inventor network distance and patent citation graphs in the pharmaceutical industry

In the knowledge-based geography of innovation literature, there are two opposing claims on the spatio-temporal pattern in knowledge flows over a technological trajectory. Firstly, after the breakthrough, externalities stimulate agglomeration of specialised firms and thus cause incremental inventions to take place progressively localised. Secondly, after the breakthrough, progressive codification and technological crystallisation facilitates collaboration over greater distances. In this study, forward citation graphs of breakthrough patents are constructed and enriched with locations of inventors. Using these citation graphs, we study claims on co-inventor distances and distances of groups of inventors across citations. We find support for existing claims and alternative spatio-temporal patterns. Notably that, early on in trajectories, inventors generally collaborate mostly locally, yet cite knowledge sources found more remotely. Later on, inventors collaborate over greater distances, yet cite more local sources. Conclusively, there is progressive globalisation of inventor networks, whereby inventors increasingly use local sources in follow-up inventions.

Local Buzz, Global Pipelines and Hallyu: The Case of the Film and TV Industry in South Korea

While the local buzz and global pipeline approach has provided a useful platform for understanding knowledge creation and diffusion in the creative industries, little attention has been paid to the complex dynamics of knowledge flows through time and space. This article examines how the dynamics of local buzz and global pipelines supported Hallyu (translated into English as the ‘Korean Wave’, which refers to the increased popularity of South Korean cultural goods outside of Korea) by analysing the Korean film and TV industry. It is argued that changes in extra-local knowledge linkages offer opportunities for the expansion of the industry, both in domestic and international markets. The main findings indicate that not only did the dynamics of local buzz and global pipelines reconfigure Hallyu but also public support policies, private sector’s exertion and increased demand in the global market promoted Hallyu.

Geographical dynamics of knowledge flows: descriptive statistics on inventor network distance and patent citation graphs in the pharmaceutical industry

In the knowledge-based geography of innovation literature, there are two opposing claims on the spatio-temporal pattern in knowledge flows over a technological trajectory. Firstly, after the breakthrough, externalities stimulate agglomeration of specialised firms and thus cause incremental inventions to take place progressively localised. Secondly, after the breakthrough, progressive codification and technological crystallisation facilitates collaboration over greater distances. In this study, forward citation graphs of breakthrough patents are constructed and enriched with locations of inventors. Using these citation graphs, we study claims on co-inventor distances and distances of groups of inventors across citations. We find support for existing claims and alternative spatio-temporal patterns. Notably that, early on in trajectories, inventors generally collaborate mostly locally, yet cite knowledge sources found more remotely. Later on, inventors collaborate over greater distances, yet cite more local sources. Conclusively, there is progressive globalisation of inventor networks, whereby inventors increasingly use local sources in follow-up inventions.

Civil society knowledge networks: how international development institutions reshape the geography of knowledge

What role have the processes and institutions of international development played in creating and propagating ideas around the world? This paper demonstrates that networks of development-focused civil society institutions can form global epistemic bridges even where communication technology, global markets, infrastructure, or state services do not reach. Given the penetration of these ‘civil society knowledge networks’ throughout the world, it is crucial to understand how these networks form, and how they create and spread ideas, mediating between global discourses and local needs. This paper builds on a multi-sited case study of one such civil society knowledge network, which includes an international foundation, its partner non-governmental organisations (NGOs) in Kenya, and one village where these NGOs run a forest conservation project. The case study provides a closely textured analysis of the mechanisms of knowledge production and consumption in the network, including personality politics, language, technology, political connections and the power dynamics of knowledge flows. It demonstrates the ways remoteness and disconnection are overcome through the epistemic reach of institutional networks involved in development interventions.

Is China transmuting to fast overtake the USA in innovation?

Purpose – This paper aims to argue for a China transmuting to fast overtake USA in innovation based on the extrapolation of past statistical trend. Case studies in self and co-innovation are provided so that the documentation of the dynamics of knowledge flows and a brain-linguistic explanation is given as to why, in the future, the Chinese are likely to lead in innovation. Design/methodology/approach – This paper illustrates a multi-method approach in research for Chinese Management Studies. First, the sociological background of China is highlighted (Mao Zedong’s aphorism). Second, insights from OECD patent database are utilized. Third, the use of comparative research and development case-studies: self-innovation (Chinese) and co-innovation (contrasting Japanese versus French cooperation with Chinese). Fourth, is the inter-disciplinarily approach wherein the assimilating of knowledge is related to recent advances in brain research. Fifth, emphasizing the different levels in organizing for innovation: national (China), organizational (SOE), group processes and person-to-person, synapses within individual brains. Findings – Statistical trend suggests that China is transforming and is on the path toward overtaking the USA in innovation. When will this happen? Using extrapolation as an indication, China may surpass the USA by the 50 per cent mark within the next decade. Insights into the processes of self-innovation and co-innovation are provided. Authors argue for a brain-linguistic explanation (Hebb, 1949) for further understanding why China will eventually lead ceteris paribus innovation, a function of the human brain. Originality/value – This paper highlights on the basis of statistical trends (using OECD database) a rising, innovative China that is poised to overtake the USA in the near future. A major contribution is in providing insights of interactional processes required to foster innovation: self and co-innovation (comparing Japanese and French). The critical brain-linguistic role as the rationale as to why the Chinese are given a greater, more developed brain power that will eventually surpass the West in innovation.

Analyzing knowledge flows of scientific literature through semantic links: a case study in the field of energy

In this paper we propose a new technique to semantically analyze knowledge flows across countries by using publication and citation data. We start with the identification of research topics produced by a given source country. Then, we collect papers, published by the authors outside the source country, citing the identified research topics. At last, we group each set of citing papers separately to determine the scholarly impact of the actual identified research topics in the cited topics. The research topics are identified using our proposed topic model with distance matrix, an extension of classic Latent Dirichlet Allocation model. We also present a case study to illustrate the use of our proposed techniques in the subject area Energy during 2004---2009 using the Scopus database. We compare the Japanese and Chinese papers that cite the scientific literature produced by the researchers from the United States in order to show the difference in the use of same knowledge. The results indicate that Japanese researchers focus in the research areas such as efficient use of Photovoltaic, Energy Conversion and Superconductors (to produce low-cost renewable energy). In contrast with the Japanese researchers, Chinese researchers focus in the areas of Power Systems, Power Grids and Solar Cells production. Such analyses are useful for understanding the dynamics of the relevant knowledge flows across the nations.

Student Mobility and Migrant Knowledge

For a better understanding of the impact of global student flows on industries and knowledge societies, we need to rethink the relationship between global student mobility and migrant knowledge. The authors elaborate on the view that current policy and practice relating to higher education mobility puts too much emphasis on mobilizing pools of knowledge, thereby ignoring the fact that knowledge flows tend to be concentrated among people who are actively participating in the knowledge flow. Adopting a shared social context perspective on the dynamics of knowledge flow embedded in mobile minds may enable a better assessment to be made of the impact of student mobility over time on industries and societies. Given such an assessment, policy and practice measures can be developed to encourage those involved in the knowledge flow to exploit student talent flow more effectively.

Wading and jumping into a new job-exploring dynamics of knowledge flow for systems engineers

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Uncovering the Knowledge Flows in Supply Chain Relationships

The acquisition process of knowledge by organizations is not easy and its spread among individuals, organizations and networks is even more complex. The understanding of the mechanisms involved in the knowledge flow between organizations can help to minimize the problems associated with processes in supply chains. In this paper, we present a systematic search of literature, which aimed to identify the relevance of this issue and how it has been studied on the academic literature. We performed an identification and mapping of knowledge flows between two types of organizations (inter-firm level) of Brazilian chain pig farming: industries and producers (farmers). Among the agricultural activities, this activity is one of the most aggressive to the environment. Some factors associated with environmental sustainability and current market barriers in this chain were identified, where it is necessary to consider the dynamics of knowledge flows. For knowledge flows and practices being effectively implemented across organizations, it was noted that issues such as the motivation of the members are key factors which in order to apply valuable knowledge. Considering this, it is necessary that the reasons and benefits for sharing being clearly established. This study contributes to the perception of the importance of identify and map knowledge flows. It also contributes to the realization of further empirical research in order to examine knowledge flows among organizations.

Platforms of innovation: dynamics of new industrial knowledge flows

Platforms of innovation: dynamics of new industrial knowledge flows

Networks and geography in the economics of knowledge flows

This paper reviews the literature dealing with the economic geography of knowledge flows by summarising the most relevant problems and open questions that, according to the authors’ view, have been dealt in the past and should be dealt in the future by network analysis in order to model, understand and measure the structure and dynamics of knowledge flows. The interaction between “networks” and “geography” elements within a theoretical, methodological and empirical perspective is discussed throughout the paper by making reference to previous works by the authors and to the established literature. Thus, these references, far from being complete and exhaustive, are instrumental to the achievement of the paper’s goal: to demonstrate that “networks” and “geography” are the necessary ingredients for every study of the innovative process at any level of analysis, from individual agent to institution/organization, from the regional to the national and international level.

The dynamics of knowledge stocks and knowledge flows: innovation consequences of recruitment and collaboration in biotech

To extend the knowledge-based view of the firm, we examine how managing the dynamic balance that a firm must undertake between applying knowledge stocks and accessing knowledge flows may determine innovativeness. We found that while the effect of scientist's recruitment and alliances as two sources of knowledge flow decay overtime, high degrees of human and social capital stock reduces the speed of new assets erosion. Failing to account for the interactions between knowledge stocks and flows, as well as the underlining causalities associated with each knowledge source, will result in an incomplete picture of the relationship between knowledge development efforts and innovative success. We test our assumptions on a longitudinal event history data set of the complete US biotech population of 857 firms founded during the period 1973--1999. Copyright 2011 The Author 2011. Published by Oxford University Press on behalf of Associazione ICC. All rights reserved., Oxford University Press.

Wading and Jumping into a New Job—Exploring Dynamics of Knowledge Flow for Systems Engineers

Engineering companies are growing increasingly concerned with identifying ways to effectively transfer knowledge, both to new employees and between employees who collaborate to develop new products. Effective knowledge capture is difficult in research and development contexts where design knowledge is rapidly changing and often poorly documented. This paper uses a case study at a small engineering company to suggest that effective knowledge transfer must be both relational (asking intelligent questions of mentors who are taxed for time) and procedural (using documentation to record how decisions are made). Cultural consensus analysis identifies two distinct cultural domains regarding effective socialization for new systems engineers. Waders advocate guided introduction, while Jumpers advocate immediate responsibility. These common themes for companies dealing with rapidly changing knowledge offer insights to scholars interested in studying the broader domain of anthropology of work.

Merging Frameworks for Interaction

A variety of logical frameworks have been developed to study rational agents interacting over time. This paper takes a closer look at one particular interface, between two systems that both address the dynamics of knowledge and information flow. The first is Epistemic Temporal Logic (ETL) which uses linear or branching time models with added epistemic structure induced by agents’ different capabilities for observing events. The second framework is Dynamic Epistemic Logic (DEL) that describes interactive processes in terms of epistemic event models which may occur inside modalities of the language. This paper systematically and rigorously relates the DEL framework with the ETL framework. The precise relationship between DEL and ETL is explored via a new representation theorem characterizing the largest class of ETL models corresponding to DEL protocols in terms of notions of Perfect Recall, No Miracles, and Bisimulation Invariance. We then focus on new issues of completeness. One contribution is an axiomatization for the dynamic logic of public announcements constrained by protocols, which has been an open problem for some years, as it does not fit the usual ‘reduction axiom’ format of DEL. Finally, we provide a number of examples that show how DEL suggests an interesting fine-structure inside ETL.

'Mode 3' and 'Quadruple Helix': toward a 21st century fractal innovation ecosystem

'Mode 3' allows and emphasises the co-existence and co-evolution of different knowledge and innovation paradigms: the competitiveness and superiority of a knowledge system is highly determined by its adaptive capacity to combine and integrate different knowledge and innovation modes via co-evolution, co-specialisation and co-opetition knowledge stock and flow dynamics. The 'Quadruple Helix' emphasises the importance of also integrating the perspective of the media-based and culture-based public. What results is an emerging fractal knowledge and innovation ecosystem, well-configured for the knowledge economy and society.

Evaluation in R&D management and knowledge use: a knowledge value mapping approach to currency accessible to the visually impaired

The dynamics of knowledge flow between R&D activities and a diverse set of actual or potential users is clearly critical to the realization of desired outcomes. However, current R&D evaluation frameworks focus almost exclusively on measurable discrete outputs and outcomes. We show that more general categories of the realization of values from the creation and utilization of knowledge are needed to make R&D evaluation more relevant to R&D program management. We propose a set of procedures that comprise a knowledge value mapping approach to R&D evaluation. This is achieved by considering the explicit and implicit normative dimension of the evaluation situation as an empirical domain that requires its own analytical elucidation to direct and give meaning to other technical aspects of the evaluation agenda. The benefits for research portfolio management are explored based on the experience of deployment of a specific technology in the context of rehabilitation research in the USA, namely, accessible currency.

Agent-based modeling of knowledge dynamics

Knowledge is distributed unevenly through most enterprises. Hence, flows of knowledge (e.g., across time, people, locations, organizations) are critical to organizational efficacy and performance under a knowledge-based view of the firm. However, supported principally by narrative textual theory in the emerging knowledge management (KM) field, the researcher has difficulty describing how different kinds of knowledge will flow through various parts of an organization. This causes difficulty also for predicting the effects of alternate approaches to dispersing knowledge that ‘clumps’ in various areas. This problem is also manifest for the KM professional, who lacks clear theory or tools to anticipate how any particular information technology or other managerial intervention may enhance or impede specific knowledge flows in the enterprise. In this expository article, we build upon a steady stream of research in computational organization theory to develop agent-based models of knowledge dynamics. This work draws from emerging theory for multidimensional representation of the knowledge-flow phenomenon, which enables the dynamics of enterprise knowledge flows to be formalized and emulated through computational models. This approach provides the means for knowledge-flow processes to be visualized and analyzed in new ways. Computational experimentation enables the performance of many alternate process designs and technological interventions to be compared through examination of dynamic models, before committing to a specific approach in practice. We illustrate this research method and modeling environment through semi-formal representation and agent-based emulation of several knowledge-flow processes from the domain of software development. We also outline key directions for the new kinds of KM research and practice elucidated by this work.