scholarly journals Regionalne strategie innowacji jako czynnik aktywizacji polskiej przestrzeni przemysłowej

2006 ◽  
Vol 9 ◽  
pp. 20-27
Author(s):  
Andrzej Wieloński ◽  
Katarzyna Szmigiel
Keyword(s):  
Economic Policy ◽  
Innovation System ◽  
Regional Innovation System ◽  
Regional Innovation Systems ◽  
European Regions ◽  
Regional Innovation ◽  
The West ◽  
The Third ◽  
New Instrument ◽  
Innovation Strategies

The main goal of the article is to present the regional innovation strategies in the context of the industrial changes in Poland. The analysis has three parts. The first part introduces the general aims of RIS and their history in Europe, the second concerns the RIS in Poland and one of the Polish RIS in particular – RIS Silesia, and the third part describes the effects of Regional Innovations Strategies.RIS are the instruments of regional governments to build the regional innovation systems. A regional innovation system is the environment improving the entrepreneurship and innovation. RIS have been known in Europe since the 1980s but in Poland they are a new instrument implemented by the relatively new structures of regional government.The process of creation and implementation of these documents should be observed by the academics from the beginning, as it may turn out to be one of the most important instruments of the economic policy of the Polish regions. This is because of the financial capacity of the Polish regions and their willingness to follow the West European regions’ example.

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.  

scholarly journals Productive articulation model as a regional innovation system

2020 ◽  
Vol 20 (2) ◽  
pp. 87-99
Author(s):  
Denisse Ballardo-Cárdenas ◽  
Pedro L. López-de Alba ◽  
Ernesto León-Castro ◽  
Ramón Martínez-Huerta
Keyword(s):  
Triple Helix ◽  
Innovation System ◽  
Industrial Sector ◽  
Jel Classification ◽  
Regional Innovation System ◽  
Transfer Of Knowledge ◽  
Regional Innovation Systems ◽  
Regional Innovation ◽  
Success Story ◽  
Regional Problems

This paper presents a productive articulation model that serves as the basis for developing and enhancing regional innovation systems. The main objective is to generate a process of linkage between the industrial sector, academia, and government within which specific regional problems can be solved through the effective intervention of each of the actors. In addition to the process, a success story is presented from the State of Guanajuato, Mexico, which serves to visualize as a clear and defined process of articulation that allows a transfer of knowledge between the actors. Keywords: Productivity articulation model; regional Innovation system; triple helix. JEL Classification: L38, O18 Received: 30/06/2020. Accepted: 05/11/2020.  Published: 01/12/2020

R&D Centre Growth Based on Regional Innovation System

2011 ◽  
pp. 9-17
Author(s):  
Jingyuan Zhao
Keyword(s):  
Innovation System ◽  
Innovation Systems ◽  
Regional Innovation System ◽  
Regional Innovation Systems ◽  
Regional Innovation ◽  
Development Models ◽  
The World ◽  
Relationship Of ◽  
The Relationship

The chapter focuses on comparing and analyzing the development models of typical regional innovation systems in the world, discussing the relationship of regional innovation system and R&D centre growth, and points out that the emergence of R&D centre and growth are tight relative with the development of regional innovation system. Through researching on typical cases of India’s Banglore, Singapore and Taiwan’s Xinzhu, the paper summarizes the experience that establishing and perfecting regional innovation system will improve R&D centre growth. Using the experience for reference, some strategies to promote R&D centre are put forward as conclusions.

scholarly journals New Actor of the Local Economies, Regional Innovation Strategies: RIS Mersin Application

2013 ◽  
Author(s):  
Filiz Tutar ◽  
Emine Fırat ◽  
Çisil Erkan ◽  
Erdinç Tutar
Keyword(s):  
Innovation System ◽  
Innovation Strategy ◽  
Eastern Coast ◽  
Regional Innovation Systems ◽  
Port City ◽  
Regional Innovation ◽  
Local Economies ◽  
Innovation Potential ◽  
The World ◽  
Innovation Strategies

Innovation is in a key position of competition and development in our globalizing world.Regional innovation system can be defined to minimize interzonal imbalances,to take the skilled labor and policies and strategies implemented to enhance the competitiveness of firms.In this connection , regional innovation strategy plays an important role in terms of increasing the regions innovation. Mersin which is an important port city in the eastern coast of the Mediterranean, is not at the place it deserves in socio-ecenomic sense either in turkey or in the world. In general to promote regional innovation systems in order to increase of the region’s innovation potential and competitiveness and in particular put forth of Mersin’s regional innovation strategy’s strengths and weaknesses and opportunities and threats is form of the purpose of the study.

scholarly journals Institutional Management Elaboration through Cognitive Modeling of the Balanced Sustainable Development of Regional Innovation Systems

2020 ◽  
Vol 6 (2) ◽  
pp. 32
Author(s):  
Anna A. Firsova ◽  
Elena L. Makarova ◽  
Ryasimya R. Tugusheva
Keyword(s):  
Sustainable Development ◽  
Cognitive Modeling ◽  
Innovation System ◽  
Innovation Systems ◽  
Cognitive Map ◽  
Regional Innovation System ◽  
Regional Innovation Systems ◽  
Regional Innovation ◽  
Institutional Management ◽  
The Impact

The main aim of this research was to search for relevant indicators and effective instruments for modeling the impact and institutional management of the regional innovation system for its balanced development. The objective of the study was to justify approaches for institutional management elaboration for balanced sustainable development of regional innovation systems regarding related factors and the needs of the region. The methodology of cognitive modeling and scenario impulse modeling are used for the analysis of the interconnection between the regional innovation system and higher education institutions and developing an instrument to diagnose the problems of no-congruence and improving the institutional management elaboration in the regional innovation policy. The analysis of system indicators of the cognitive map allowed to define the basic patterns in the regional system, determine the most significant factors and relationships for the economic system of the region and visualize them in the form of a cognitive map, identify the influence of the innovation environment elements on the target indicators, quantify its positive and negative impact, forecast and determine the directions of its improvement and enhancing the interaction of regional actors. The results of the study have practical value for use in improving institutional management in planning reforms and transformations of regional innovation systems.

Evaluation of critical factors for the regional innovation system within the HsinChu science-based park

Kybernetes ◽  
2016 ◽  
Vol 45 (4) ◽  
pp. 699-716 ◽  
Author(s):  
Chung-Lin Tsai ◽  
Han-Chao Chang
Keyword(s):  
Innovation System ◽  
Innovation Systems ◽  
Regional Innovation System ◽  
Regional Innovation Systems ◽  
Regional Innovation ◽  
Industry Cluster ◽  
Operational Effectiveness ◽  
Content Type ◽  
Parent Firm ◽  
Knowledge Infrastructure

Purpose – The purpose of this paper is to collate relevant literature on the theoretical background of regional innovation systems and factors that impact the operational effectiveness of regional innovation systems. Design/methodology/approach – The collated information is then used to determine the opinions of experts from industries within science-based parks, and the scholars on the researches of regional innovation systems in Taiwan. The analytic hierarchy process (AHP) is used to evaluate the critical factors of regional innovation systems. Findings – This study finds that industry cluster effects constitute the most significant operating factor for regional innovation systems within the Taiwanese science-based parks. In addition, this study not only confirms that partners or parent firm location which were advocated by Tödtling et al. are also critical to Taiwanese regional innovation systems, but also verifies how well the relationships to partners or parent firm are equally important for expansion the regional innovation systems. Research limitations/implications – The concepts of regional innovation system have been established since 1990, and related articles have been published from European and Asian scholars, however, seldom does literature offer questionnaires or research items to measure the operational effectiveness of a regional innovation system. Therefore this study has developed a questionnaire, by reviewing literature and verifying it by the AHP method, with Taiwan’s HsinChu Science Park as the subject case. For the contribution on theories, this study inducted the construction of new innovation environments, new interactional behavior in regional organization innovation, and injection of new resources into regional innovation as the three main constructs to influence the operational effectiveness of regional innovation systems. In addition, this study has used experts’ questionnaire answers and the AHP method to clarify the priority of factors to operate the regional innovation system. Practical implications – Industry cluster effect, construction of knowledge infrastructure and how close partners or parent firm are (distance and relationship) are the top three factors in HsinChu Science Park. The duties of the government are not merely picking good firms for the regional innovation system, but also making policies and defining regimes, providing a good business environment for campus firms, universities, and research institutions, as well as offering plenty of R & D funding to encourage industry-academia cooperation. Governments must invest in infrastructures, such as: establishing databases, libraries, information networks, the national technical standards for certification, and other public services, to facilitate industry-academia cooperation. Social implications – These research results indicate the operating essentials of regional innovation systems are not limited to interactions among regional organizations. This study suggests that the success or failure of a new regional innovation system would instead, be dependent on the regional environment, as in software planning and support, as well as the relationship of innovation with policy implementation and administration. Originality/value – Results showed that the top-five factors influencing the operational effectiveness of regional innovation systems are the industry cluster effect, the construction of knowledge infrastructure, how close to partner’s or parent’s firm (distance and relationship), import of foreign capital and technology, and the implementation of regional innovation policy.

Regional Innovation Systems in Centralised States

2015 ◽  
pp. 71-90 ◽  
Author(s):  
Philip Cooke
Keyword(s):  
Innovation Policy ◽  
Policy Formation ◽  
Regional Innovation Systems ◽  
Regional Innovation ◽  
The Third ◽  
Regional Innovation Policy ◽  
The Face ◽  
Resource Transfers ◽  
Innovation Strategies ◽  
The Eu

The chapter explores the processes by which regional administrations displaying various statutory capabilities and weaknesses have demonstrated accomplishment, creativity, and innovativeness in the face of having to operate in centralised, relatively un-devolved, and non-federal national states. The focus is on a few exemplars of creative regional policy activity from contrasting regional settings in Sweden and Portugal in pursuit of improved innovation accomplishment drawn entirely from the apparently ever-centralising EU. A key reason for this is that in the EU all regions receiving regional assistance from Brussels were required in 2013 to draw up Regional Innovation Strategies if they were to qualify for regional resource transfers from Brussels. So these and other regions are behaving, in innovation terms, according to a logic of uniform rules from both Brussels and their own centralised states. They are thus doubly constrained in their quest for regional innovation policy assistance but their responses display enormous variety and creativity. The chapter proceeds by, first, outlining the rules of the RIS3 then, second, theorising ongoing processes. In the third and fourth sections, there is concentration on regional innovation policy formation in Sweden and Portugal, with preliminary drawing of contrasts and comparisons. Then, in the final section, a brief discussion and conclusions profile can be found.

Learning in the Regional Innovation Systems: An Agent Based Model

2017 ◽  
Vol 33 (57) ◽  
Author(s):  
Santiago Quintero Ramirez ◽  
Walter Lugo Ruiz Castañeda ◽  
Jorge Robledo Velásquez
Keyword(s):  
Innovation System ◽  
Innovation Systems ◽  
Regional Innovation System ◽  
Complex Phenomenon ◽  
Regional Innovation Systems ◽  
Agent Based Model ◽  
Regional Innovation ◽  
Agent Based ◽  
Market Opportunities ◽  
Simulation Exercises

Learning in regional innovation systems is a complex phenomenon. Therefore, its analysis is being increasingly approached through computer-simulated strategies. The agent-based model in particular has demonstrated to be a useful approximation to overcome the limitations of other methodological strategies since it allows a more trustworthy representation of the agent’s capabilities, their reasoning limitations, of the mechanisms used for decision making, their interaction, and their success formulas to take advantage of market opportunities. Nevertheless, the development of these models represents serious conceptual and methodological challenges. This article proposes a model that represents the agents of a regional innovation system as vectors of capabilities and the learning process as the accumulation of their innovation capabilities. The proximity among agents and the influence of public policies favors the result of the interaction induced by the market. Methodologically, the development of the model starts with a conceptual proposal validated through contrast against. specialized literature. After that, a model verified by computer was elaborated and its behavior was validated. Finally, a simulation of scenarios was performed to prove its potential application. The resulting model contributes to the understanding the learning dynamics and the emerging patterns of the agent’s specialization and their influence on the system’s performance. Finally, the simulation exercises demonstrate the model’s potential to guide policy decisions that seek to improve the performance regional innovation systems.

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