Formation Of Innovation Networks Research Articles

Patterns of innovation networks formation in a closed-cycle economy

The relevance of the study is due to the poor knowledge of the problems of the formation of innovation networks in a closed-cycle economy. Against this background, the purpose of the study is determined – to develop provisions that develop the methodology of managing innovation networks in the context of a closed-loop economy and allow identifying patterns of formation of innovation networks. In this regard, attempts have been made to assess the patterns of development of network interactions within the framework of innovation activities of territories. Using the example of European countries, the interrelation of indicators of cooperation in the field of innovation and indicators of a cyclical economy is evaluated, as a result of which countries of advanced, transitional and catching-up types of development are identified. Based on the proposed author’s methodology, a matrix of positioning territories according to the degree of interconnection of innovation networks and closed-cycle economic indicators is constructed, 4 development trajectories are identified. The methodology for assessing the aggregate index differs by taking into account the reference proportions of cooperation, allows for a differentiated approach to the support of territories, is universal and can be applied by public authorities in the development and refinement of spatial development strategies.

Industrial efficiency analysis based on the spatial panel model

High-tech industrial agglomeration is conducive to boosting technological progress, promoting industrial structure upgrading and realizing economic transformation, and certainly affects the overall industrial environmental efficiency. However, few recent studies have focused on its impact on industrial environmental efficiency from a green perspective. In the context of promoting the development of green economy, it is of great significance to clarify the links between high-tech industrial agglomeration and industrial environmental efficiency. In this research, we first analyzed the theoretical mechanism of the impact of high-tech industrial agglomeration and its spatial spillover effects on industrial environmental efficiency and then made an empirical analysis based on the panel data of 29 provinces and cities in China from 2003 to 2016. During the research, Super-DEA method, ESDA method and spatial Dubin model are used. The result shows that: (1) There is a significant spatial positive correlation between China's industrial environmental efficiency and high-tech industrial agglomeration; (2) high-tech industrial agglomeration has improved the local industrial productivity and industrial technology level through scale effects and technical effects, which has accordingly significantly enhanced the corresponding environmental efficiency; (3) through the association of regional industries, the cross-regional cooperation of enterprises and the formation of innovation networks, high-tech industrial agglomeration promotes the spillover of knowledge and technology among regions, improves the level of industrial technology in neighboring regions, and enhances the industrial environmental efficiency in neighboring regions. All these three is helpful to re-evaluate the development mode of high-tech industry agglomeration and to formulate relevant government policies.

ОСОБЛИВОСТІ МЕРЕЖЕВОЇ ОРГАНІЗАЦІЇ ІННОВАЦІЙНОЇ ДІЯЛЬНОСТІ

The article examines the features of a network organization of innovative activity. A definite trend of development of a knowledge economy is the shift towards partnerships in the innovation sphere. In the work it is determined that many problems associated with creating an enabling environment for activating innovative processes on the basis of network interaction are still poorly studied. It makes appropriate to carry out further research in this sphere. The network form of interaction bases on the principles of equal partnership, agreed in time and space of behavior of participants. It brings together the whole process of developing, producing and disseminating innovations. A typical network structure is an open system that consists of a set of interconnected elements (participants). They interact and exchange information to create and enhance competitive advantage, have roughly equal access to core resources, and have equal direct relations with other participants. They all get benefit from network interaction, regardless of their size and type of activity. The formation of innovation networks is a complex process that involves the selection and voluntary integration of stakeholders into a single network. Modern innovation networks are based on the concept of open innovation, which involves the use of external ideas and technologies while allowing other stakeholders to use their own ideas. The process of formation of innovation networks involves the emergence of the initiator bringing together a number of enterprises in the efficient production of innovation. The network structure is a modern model for the redistribution of tangible and intangible assets, allowing its participants to reduce time and material costs to adapt to market conditions. The presence of horizontal links and the sharing of available resources significantly accelerates the process of transforming scientific knowledge into innovation and its commercialization. Increasing the interaction between participants leads to the accumulation of innovation potential and the activation of innovative processes.

Reference model for building innovation networks in information technology

Abstract: The change in organizational processes by means of associating the new resources made available by IT (Information Technology) with the intrinsic characteristics of business-related areas embodies one of the innovation concepts. This work proposes a reference model for the formation of innovation networks focused on implementing systems that represent innovations by associating IT with the business area. The research methodology is based on an exploratory case study, composed of several analysis units, and on the organizational modeling methodology EKD (Enterprise Knowledge Development) to formulate the reference model. This research proposition contributes to systematize the formation process of collaborative alliances among the innovation agents in order to implement Information Technology-based systems.

The structure and proximity mechanism of formal innovation networks: Evidence from Shanghai high‐tech ITISAs

AbstractThe discussion on innovation networks of patents or papers has attracted many economic geographers; however, the Industrial Technology Innovation Strategy Alliance (ITISA) has been ignored, although it is also an important innovation form of firms, and the formation mechanism of alliance innovation networks is unclear. This study is based on the data of Shanghai high‐tech ITISAs between 2010 and 2015, and employs the methods of social networks and negative binomial regression to analyse the actor structure, spatial structure, and proximity mechanism of innovation networks of Shanghai high‐tech ITISAs. Results highlight the following: (a) Firms comprise the largest number of actors in alliance innovation networks, and universities, research institutions, and industry associations also play some roles. (b) The local and rooted characteristics of the innovation networks of ITISAs are obvious. The spatial distribution of innovation partners is mainly in Shanghai, and a few innovation actors are located in neighbouring cities, such as Suzhou, Hangzhou, and Ningbo in the Yangtze River Delta Urban Agglomeration. (c) Proximity significantly promotes the formation of innovation networks in an ITISA and contributes to the improvement of innovation ability, and organizational proximity plays a greater role than geographical proximity or cognitive proximity.

Interorganisational networks and proximity: an analysis of R&D networks for cultural goods

Purpose of the paper : The aim of this study is to measure the impact of various dimensions of proximity to form innovation networks. Methodology : We use a novel statistical methodology for modelling networks based on a well-studied class of models called exponential-family random graph models. Findings : Results underline the importance of various forms of proximity in the formation of innovation networks and the potential of the novel methodology to study large and complex networks in innovation studies and R&D management. Research limits : The research is mainly quantitative and contributes to the debate measuring the role and importance of various forms of proximity in innovation networks. Further analysis of how firms choose their partners is needed. Moreover, the analysis should be expanded to other contexts and industries in order to be able to generalise results. Practical implications : The work points out managerial implications in innovation studies and R&D management in order to guide firms when choosing their partners and forming a network. Originality of the paper : The study contributes to the debate on innovation network literature and tests a novel methodology to analyse large and complex inter-organisational networks.

How proximity matters in innovation networks dynamics along the cluster evolution. A study of the high technology applied to cultural goods

The role of proximity in innovation and inter-organisational networks has recently received increasing attention in management, organisational, economic geography and regional studies. Despite the rich literature devoted to these themes, most contributions on networks are mainly static, as they focus more on the network's structure than its dynamics. Our aim is to investigate the role of various forms of proximity in innovation network dynamics along the cluster evolution. The article focuses on two specific research questions: (i) How do the different forms of proximity influence the formation of innovation networks? and (ii) Does the impact of different forms of proximity change during the cluster's evolution?The analysis investigates the cluster of High Technology applied to Cultural Goods in Tuscany and adopts an advanced econometric method such as the Stochastic Actor-Oriented Models to investigate the evolution of the networks over a time period of more than ten years.

Análises das redes de inovação resultantes dos financiamentos dos fundos setoriais de biotecnologia e energia

Objective – This paper assessed the formation of innovation networks by firms and institutions of science and technology (IST) so that they can receive financial resources from science and technology sector funds (SFs). SFs are the cornerstones of the Brazilian national system of innovation (NSI). As the funds were created slightly over a decade ago, it is high time they underwent revision. Design/methodology/approach – The research used data from projects offered by FINEP, RAIS and Economatica. Beyond the pursuit of basic patents Derwent Knowledge of Reuters. Descriptive analyzes were performed, network analysis through Gephi software and applied a multiple regression to the available indicators on the impacts generated by FS. The indicators used originate from different areas of knowledge and are analyzed in light of the theory of open innovation. Findings – In the preliminary stage of the program, funds were largely allocated to the science and technology sector, but firms had a low level of participation in the projects. In addition, patent applications are below expectations at that stage, given that one of the aims of SF is the incentive for technological development. Practical implications – Despite the improved transparency in the Brazilian economy, restrictions on information do not permit the application of statistical tests to measure the impacts of investments in innovation Originality/value – The innovation networks were assessed by social network analysis, which indicated that most nodes (actors) are occupied by more active ISTs, lowering any expectations for a higher level of participation by firms. Some suggestions are made for improving incentive programs for innovation and their management.

On the role of Business relations Culture in FormingInnovative Networks (The Case of Stanford University)

It is commonly assumed that a dominant role in the formation of Silicon Valley was played by such factors as the availability of highly skilled workforce, policy in the sphere of public procurement of high-tech products, participation of large companies and financial institutions. The article reveals the content of programs at Stanford University to establish links between the university staff and companies, shows their influence on the formation of innovation networks in Silicon Valley.

Interaction with external agents, innovation networks, and innovation capability: the case of Uruguayan software firms

Purpose–The aim of this paper is to disentangle the interplay between nurturing interaction with external agents, innovation networks, and innovation capability. In particular, the paper argues that nurturing interaction with external agents (by means of participation in different events that allow face-to-face interaction, or via collaborative technology) positively affects the innovation capability of firms by allowing the development of innovation networks and making them run smoothly.Design/methodology/approach–For this to be tested, an analysis has been carried out in Uruguayan software firms. A questionnaire was designed and addressed to the managers of the firms making up the target population. Structural equation modeling (SEM) based on partial least squares (PLS) was then applied to test the hypotheses put forward by the research.Findings–The results obtained show that nurturing interaction with external agents has a positive and significant influence both on the formation of innovation networks and on their operational performance. This influence is much stronger when it comes to ensuring the smooth operation of the network than when it comes to facilitating its formation. Moreover, innovation networks and their functioning clearly mediate the relationship between interaction with external agents and innovation capability.Research limitations/implications–Traditional limitations of cross-sectional studies apply.Originality/value–Although previous literature highlights the relevance of social interaction for the creation of new knowledge and subsequent innovation, the role of mediating variables has been hardly considered. This research helps to shed some light on this issue in the case of social interaction with external agents. In particular, the mediating role of innovation networks has been analyzed.

Management Insights

Management Insights

The Knowledge-Base of the Firm in Biotechnology Based Sectors: Properties and Performance

A questão do conhecimento está se tornando cada vez mais um importante determinante do desempenho das firmas. Este fato é especialmente importante no caso dos setores baseados em biotecnologia. Apesar da crescente importância do conhecimento, sabemos muito pouco sobre a natureza e as propriedades do conhecimento dentro das firmas. Neste artigo discute-se, em primeiro lugar, questões associadas à dinâmica da criação e utilização do conhecimento e, em seguida — usando-se algumas técnicas que serão apresentadas no decorrer no artigo — como se pode medir e mapear este conhecimento. A base tecnológica das firmas pode ser definida como o conhecimento que as firmas usam para atingir seus propósitos produtivos. Seu caráter agregado deriva do fato de que a base tecnológica resulta do conhecimento dos membros individuais de uma firma, bem como de suas interações, como determinado pela estrutura organizacional da firma. Desta forma, a base tecnológica da firma inclui todos os tipos de conhecimento que são requeridos para se obter os produtos finais. O método baseia-se no uso de patentes registradas pelas firmas. No entanto, este é um método apenas aproximativo no sentido que representa os componentes científicos e tecnológicos da sua base tecnológica. Esta parece ser uma boa aproximação para o caso de segmentos altamente dependentes em tecnologia, como é o caso dos setores baseados em biotecnologia. O método repousa essencialmente em dois grupos principais: o de que é importante obter uma representação gráfica do conhecimento de uma firma por meio de uma análise lexicográfica e o de que certas propriedades da base tecnológica podem ser definidas e mensuradas através de patentes. Por exemplo, pode-se medir o grau de especialização, o escopo da coerência da base tecnológica e estudar as influências destas propriedades na performance da firma. Os dois conjuntos de metodologias e alguns dos resultados obtidos serão descritos neste artigo. As técnicas descritas conduzem-nos a análise do impacto da base tecnológica sobre o número de aspectos do desempenho da firma. Por exemplo, espera-se que a base tecnológica tenha que mudar de forma a permitir que a firma mude a estratégia. Desta forma, outros aspectos do desempenho da firma tal como fusões e aquisições, e de formação de redes de inovação poderão ser afetadas pela base tecnológica das firmas participantes.

Role of Knowledge Management in Entrepreneurial Innovations: A Comparative Study of Formal and Informal Sectors

The paper focuses on three issues- a) innovations are knowledge based resulting from the synthesis and application of the tacit and the coded knowledge; b) the role of entrepreneur (as knowledge manager) is important for exploiting the tacit knowledge and making use of the coded knowledge; and c) for the diffusion of innovations, variety of actors (as individuals or institutions) participate which leads to the formation of innovation networks. An attempt has been made to elaborate upon the above issues through two case studies from diverse sectors - formal and informal. One case study is related to the diffusion of new technology (plant biotechnology) at the field level. The process from technological innovation to diffusion level involved interaction amongst public and private institutions. The change was mainly based on the coded knowledge ( the adoption of new technology ) and in the process of change, the tacit knowledge played substantial role (in how to make use of the new technology) in accomplishing the technical change. In the second case of informal sector (the adoption of floriculture by traditional crop growing farmers), entrepreneurs' tacit knowledge initiated the change process. Tacit knowledge was used to fulfill customers needs and thus was used to capture the market. The new knowledge was created by combining the tacit one with the explicit and then applied meaningfully by the entrepreneurs so as to reap the economic benefits. The participation of different institutions in the later case was not so much differentiated and direct as it was in the first case. The role of the government, influenced by the circumstances, for the sustenance of the technical change was apparent.

Innovation Networks Taxonomy and Effciency - Toward Innovation Engineering

Innovation is considered instrumental in creating value and growth in the modern society and as such has been extensively studied in the past decade. In this context innovation networks are considered central for driving innovation in general and technological innovation specifically. Federal and local governments, as well as regional organizations, spend significant amounts of money in order to stimulate and support the formation of innovation networks that take on variety of forms and structures. Most of the research on innovation networks has focused on descriptive analysis. Using metrics borrowed from graph theory, as well as a newly defined metric, I set up the taxonomy and provide a systematic, quantitative, analysis of innovation networks in their broadest sense, topology-wise, as well as their efficiency from information flow perspective. I argue that public policy makers should apply a portfolio, holistic, approach to innovation networks and decide upon a balanced mix of different types of networks in order to maximize the innovation efficiency/intensity versus costs, a process that I refer to as innovation engineering.

Bilateral Collaboration and the Emergence of Innovation Networks

In this paper, we model the formation of innovation networks as they emerge from bilateral decisions. In contrast to much of the literature, here firms only consider knowledge production, and not network issues, when deciding on partners. Thus, we focus attention on the effects of the knowledge and information regime on network formation. The effectiveness of a bilateral collaboration is determined by cognitive, relational, and structural embeddedness. Innovation results from the recombination of knowledge held by the partners to the collaboration, and its success is determined in part by the extent to which firms’ knowledge complement each other. Previous collaborations (relational embeddedness) increase the probability of a successful collaboration, as does information gained from common third parties (structural embeddedness). Repeated alliance formation creates a network. Two features are central to the innovation process: how firms pool their knowledge resources, and how firms derive information about potential partners. When innovation is decomposable into separate subtasks, networks tend to be dense; when structural embeddedness is important, networks become cliquish. For some regions in this parameter space, small worlds emerge.

Bilateral Collaboration and Emergent Networks

In this paper we model the formation of innovation networks as they emerge from bilateral decisions. In contrast to much of the literature, here firms only consider knowledge production, and not network issues when deciding on partners. Thus we focus attention on the effects of the knowledge and information regime on network formation. The effectiveness of a bilateral collaboration is determined by cognitive, relational and structural embeddedness. Innovation results from the recombination of knowledge held by the partners to the collaboration, and its success is determined in part by the extent to which firms' knowledge complement each other. Previous collaborations (relational embeddedness) increase the probability of a successful collaboration; as does information gained from common third parties (structural embeddedness). Repeated alliance formation creates a network. Two features are central to the innovation process: how firms pool their knowledge resources; and how firms derive information about potential partners. When innovation is decomposable into separate sub-tasks, networks tend to be dense; when structural embeddedness is important, networks become cliquish. For some regions in this parameter space, small worlds emerge.

Bases conceituais para uma estratégia de gestão: o caso da Rede Nacional de Bancos de Leite Humano

The Brazilian National Network of Human Milk Banks (REDEBLH), with its headquarters in the Oswaldo Cruz Foundation in Rio de Janeiro, is experiencing rapid growth. The Network's activity has been acknowledged by the World Health Organization and received the Sasakawa Health Award in 2001 for best public health project. One of the main challenges is to ensure continuing development of competencies to respond to the needs arising from such growth. A new strategy is being pursued to deal with the Network's management issues. This article aims to develop a conceptual framework to contribute to the elaboration of a theoretical framework for new management strategies in the REDEBLH. Using such concepts, the aim is to draw on the typology of networks described in the specialized literature to identify the institutional profile of the REDEBLH. Based on the understanding that it is necessary to identify and understand the processes occurring within networks, and after which to consider management-related issues, the study used a proposal developed for the formation of innovation networks as its analytical tool.