Simulation and Relationship Strength: Characteristics of Knowledge Flows Among Subjects in a Regional Innovation System

2021 ◽  
pp. 097172182110204
Author(s):  
Yi Su ◽  
Xuesong Jiang ◽  
Zhouzhou Lin
Keyword(s):  
Innovation System ◽  
Small World ◽  
Coupled System ◽  
Mean Value ◽  
Knowledge Flows ◽  
Knowledge Flow ◽  
Regional Innovation System ◽  
Regional Innovation ◽  
Relationship Strength ◽  
Loosely Coupled

A small-world simulation model of a regional innovation system combining the strength of the intersubject relationship of the regional innovation system with the loosely coupled system is constructed. We use a simulation to observe knowledge flow within the regional innovation system under relationships of varying strength. The results show that when the relationship between the subjects of the regional innovation system reaches a certain strength, the system will exhibit high module independence and high network integrity, forming a loosely coupled system. The knowledge flow in the system exhibits the emergence of a fast flow rate, a high mean value and little variance. When relationship strength is at other levels, the emergence of knowledge cannot be identified.

Comparing knowledge bases: on the geography and organization of knowledge sourcing in the regional innovation system of Scania, Sweden

2011 ◽  
Vol 20 (2) ◽  
pp. 170-187 ◽  
Author(s):  
Roman Martin ◽  
Jerker Moodysson
Keyword(s):  
Knowledge Base ◽  
Spatial Organization ◽  
Knowledge Exchange ◽  
Innovation System ◽  
Knowledge Bases ◽  
Knowledge Flows ◽  
Regional Innovation System ◽  
Regional Innovation ◽  
Knowledge Sourcing ◽  
Different Types

This paper deals with knowledge flows and collaboration between firms in the regional innovation system of southern Sweden. The aim is to analyse how the functional and spatial organization of knowledge interdependencies among firms and other actors varies between different types of industries that draw on different types of knowledge bases. We use data from three case studies of firm clusters in the region: (1) the life science cluster represents an analytical (science-based) industry, (2) the food cluster includes mainly synthetic (engineering-based) industries, and (3) the moving media cluster is considered to be symbolic (artistic based). Knowledge sourcing and knowledge exchange in each of the cases are explored and compared using social network analysis in association with data gathered through interviews with firm representatives. Our findings reveal that knowledge exchange in geographical proximity is especially important for industries that rely on a symbolic or synthetic knowledge base, because the interpretation of the knowledge they deal with tends to differ between places. This is less the case for industries drawing on an analytical knowledge base, which rely more on scientific knowledge that is codified, abstract and universal and are therefore less sensitive to geographical distance. Thus, geographical clustering of firms in analytical industries builds on rationales other than the need for proximity for knowledge sourcing.

Coopetition strategies of start-ups: evidence from a Spanish regional innovation system

2021 ◽  
Vol 16 (4) ◽  
pp. 694
Author(s):  
Jasmina Berbegal Mirabent ◽  
Dolors Gil Doménech ◽  
Carolina Senent Bailach
Keyword(s):  
Innovation System ◽  
Regional Innovation System ◽  
Regional Innovation ◽  
Start Ups

scholarly journals Measuring university–industry collaboration in a regional innovation system

2009 ◽  
Vol 84 (3) ◽  
pp. 649-667 ◽  
Author(s):  
Irene Ramos-Vielba ◽  
Manuel Fernández-Esquinas ◽  
Elena Espinosa-de-los-Monteros
Keyword(s):  
Innovation System ◽  
Regional Innovation System ◽  
Regional Innovation ◽  
Industry Collaboration ◽  
University Industry

scholarly journals Modern trends in innovative development ofoil and gas producing region

2015 ◽  
Vol 13 (4) ◽  
pp. 57-62
Author(s):  
Tatyana N Bessonova
Keyword(s):  
Oil And Gas ◽  
Innovation System ◽  
Scientific Research ◽  
Innovation Process ◽  
Organizational Form ◽  
Regional Innovation System ◽  
Innovative Development ◽  
Regional Innovation ◽  
Industrial Sectors ◽  
Modern Development

Abstract: When forming the regional innovation system, everyone should take into account specific conditions and the possibility to develop regional economic complexes. Modern development of oil and gas producing region implies an increase in cooperation between all participants of the innovation process. The most promising organizational form of such an association in Khanty-Mansiysk Autonomous Okrug - Yugra is Yugra Technopolis. It aims to strengthen the interaction of research and industrial sectors, to improve the commercialization of scientific research results

scholarly journals Propuesta de un Método para la Aplicación de un Modelo de Simulación Basada en Agentes del Sistema Regional de Innovación

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
E Embuz ◽  
J D Fernández-Ledesma
Keyword(s):  
Simulation Model ◽  
Innovation System ◽  
Innovation Systems ◽  
Regional Innovation System ◽  
Regional Innovation Systems ◽  
Research Groups ◽  
Regional Innovation ◽  
Regional Systems ◽  
Project Analysis ◽  
Los Grupos

Este artículo propone un método que permite aplicar de forma práctica, precisa y efectiva un Modelo de Simulación Basado en Agentes del Sistema Regional de Innovación (SRI), el cual ha sido desarrollado dentro del Proyecto “Análisis de la Estructura, relaciones y dinámicas de agentes de los Sistemas Regionales de Innovación” liderado por los Grupos de Investigación GISAI y GTI pertenecientes a la Universidad Pontificia Bolivariana sede Medellín. Esta propuesta de método está centrada en una revisión de las necesidades más relevantes de los Sistemas Regionales de Innovación y cómo éstas deben ser suplidas paso a paso a través de la estructura del Modelo de Simulación en su aplicación. AbstractThis paper describes a method of applying a simulation model based on Agents of Regional Innovation System (SRI), which has beendeveloped within the project "Analysis of the structure, relationships and dynamics of agents of the Regional Systems described innovation"led by GISAI Research Groups and belonging to the Universidad Pontificia Bolivariana in Medellín GTI. This proposed method is focusedon a review of the most important needs of the Regional Innovation Systems and how they should be met step by step through the structure of the simulation model in its application.  

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