Technical feasibility

SECTION I: Testing

 

1

Has the R & D result been tested?

YES

 

 

1a

In what mode has the result been tested?

                Prototype

                Pilot Application

                Alpha/BETA testing

 

The systemic analysis of innovation systems conceives complex analytical frameworks, with intense socio-technological aspects of knowledge generation and encompasses a detailed analysis of system failures. These frameworks are not suitable for benchmarking a wide range of regions, due to low availability of such elaborate data sources. On the other hand, metric regional innovation micro data offer the opportunity for large-scale cross-regional benchmarking exercise illustrating mainly the market failures of the innovation systems although this type of analysis does not provide any detailed systemic envisioning. Is the combination of these two analytical approaches possible? This study presents the integrated innovation interactions (3I) analytical framework, which is aligned with the demand of policy makers for periodical benchmarking of regional innovation systems combined with a systemic endoscopy in the innovation processes. This analytical framework is used to present an example of the proposed analysis, by comparing the innovation agglomeration capacity among the North-Western European and the Mediterranean regions in the periphery of Europe. For testing the micro data of the EIS 2006, 2005 and 2004 for 253 European regions has been used.

b.

Please describe and discuss the testing results

The systemic innovation analysis often reaches a high level of complexity, based on empirical data of a limited number of regional cases. Policy makers are presented with complicated systemic models that could not be utilised as a policy evaluation or benchmarking tool. On the other hand, the metric analysis provides a wide range of composite indicators that do not reveal any information about the systemic performance of a region.

 

SECTION 2: Current Stage of Development

 

2a

To what extent does the development team have technical resources for supporting the production of a new product? (Researchers, human resources, hardware, etc. )

URENIO is a university laboratory for the promotion of research and supply of scientific and technological services. URENIO is part of the Department of Urban and Regional Planning in the Faculty of Engineering, Aristotle University of Thessaloniki.

URENIO’s current research emphasis is on intelligent cities and regions. In particular:

   Innovation clusters development and planning: Development, assessment and planning of innovative clusters, technology districts, technopoles, science and technology parks, innovation centres and incubators.

   Regional innovation systems and strategies. Knowledge-based urban and regional development. Management of regional systems of innovation. Regional innovation strategies. RIS and RITTS projects. Measuring and benchmarking of innovation performance.

Intelligent cities: Intelligent-global clusters and technology parks. Virtual innovation environments. Digital city platforms and innovation e-communities. Strategic intelligence, foresight and benchmarking. Global technology transfer networks. Collaborative new product development. Global product promotion.

 

 

2b

What are the technical issues that need to be tackled for full deployment, if needed?

A geospatial database with LOT2 and LOT3 typologies claiming all-important demographics using open and linked data, so the database receives constant updates.

A visualization tool for presented benchmarks and visual representation of the 3I regional model in a single region or in a comparative mode.

A benchmarking application that will provide comparative regional innovation analysis among regions.

A data validation module for assigning Eurostat values and presented in a normalized form.

 

2c

What additional technical resources are needed for the production of this new product?

A data base administrator

A geospatial database license

A java programmer

A statistics expert

A data validation expert

 

 

 

2d

Overall assessment of the current stage of technical development.

The  methodology has been tested using existing statistical data examining the innovation systems of 253 European regional systems. Such a wide testing exercise gave the necessary feedback to fine tune deficiencies before transforming the methodology to tool. Thus, the case of 3I tool is advancing to technical terms transforming the requirements into a web based measurement platform.

 

SECTION 3: Deployment

3a

Define the demands for large scale production in terms of

·       Materials

There are no plans for mass production since the access to 3I is online via web.

·       technologies, tools, machineries

 

·       Staff effort

 

 

SECTION 4: Overall Assessment

1

What is you overall assessment of the technical feasibility of the research result?

 

The technical feasibility is based on benchmarking ICT skills. Generally, statistics soon become outdated and indicator measurements must be available quickly. To improve the speed and quality of the process, an interoperable technological platform for efficient, quick and web-based benchmarking is proposed. The technologies used to implement the platform are mainly Internet based. The tool for data collection is the on-line questionnaire. The on-line questionnaire is in fact the benchmarking model, the main themes and indicators, translated into a web-based format:

An expert supports the process by providing the3I .

The input of data is connected with a relational database, which holds 
all the data inserted by the person completing the benchmarking form.

Each authenticated user may create, view, edit or save an innovation report .

 The relational database of 3I  is connected with the user 
database. A person has the ability to log on to the system and view his 
completed questionnaires at any time.

Data are analyzed with customizable analysis tools that support the automatic 
generation of benchmarking reports and statistical results.

The graphs, statistical pies and reports are generated dynamically during the 
completion of the model . This reduces significantly the time for data 
analysis and report generation.


KEYWORDS QUANTITATIVE ASSESSMENT (0-5).

 

Please put X as appropriate.

1

2

3

4

5

Adequacy of testing activity undertaken so far

 

 

 

 

x

Adequacy and availability of technical resources of the development team

 

 

 

 

x

Current development stage

 

 

 

 

x

Overall technical feasibility

 

 

 

 

x

 

 


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