IPSE Sub-Project 2:
This SP investigates the empirical dynamics of innovation networks. It chooses a heterogeneous sample of geography-related (regional, national, all-Ireland, international) and sector-specific (healthcare) case studies providing empirical input for SP1.
In this package, we will provide information on geographical aspects of innovation in Ireland:
(a) with a particular emphasis on the Dublin regional network investigating the mechanisms and optimising strategies to improve it, and;
(b) with a comparison of Irish and Northern-Irish local high-tech clusters.
The research will contribute to the academic understanding of how local and regional innovation systems nurture and promote high-tech businesses.
The sector-specific aspects of innovation will be tackled in a sub-study of the healthcare sector. This sectoral study relates to the geographical dimension, as outlined above, offering various synergy opportunities.
(c) Selecting a representative sample of Primary Care Teams (PCTs), across two or more HSE regions, the Geary team will collect a baseline of retrospective decision data, which includes qualitative and quantitative decision model oriented data. The same sample of PCTs is used to collect subsequent longitudinal network and decision data at two further time points during our study, facilitating prospective and comparative decision model and longitudinal dynamic network analysis. We conduct case studies of two representative PCTs and use action research techniques to compile data on the establishment and management decision issues of these PCTs as they emerge in real time. The substantive focus is on the re-configuration of Irish hospital services such as the establishment and on-going management of the Primary Care Teams for which successful implementation requires building consensus across a multi-disciplinary team of health professionals and administrators. We will use our empirical decision data and longitudinal network data, to provide realistic insights on how to manage the dynamics of group processes in the decision-making networks for PCTs in Ireland.
This task will be concerned with analysing the knowledge/competence profile, network structure, and performance of the Dublin regional innovation network. We will use a variety of knowledge mapping techniques (Innovation Score Board data, other OECD, CIS, and EUROSTAT data, WIPO and other patent statistics, Irish Government agency data, RTA indicator analysis, own databases etc.). The team from IRU and WIT/TSSG will reconstruct the knowledge portfolio of the Dublin regional innovation network with a focus on investigating potential differences in the concepts of innovation and knowledge creation between ICT/Telecoms and the biotechnology-based pharmaceutical industry to offer a conceptual point of contact to the sector-specific case studies. WIT/TSSG will provide insights from the South-West on how to connect under-privileged organisations to regional networks.
In this task, we will (i) provide a literature review on technology clusters and refinement of conceptual framework of analysis, (ii) refine the identification of clusters for analysis, (iii) develop survey-based tools for data capture, (iv) conduct an empirical survey of cluster organisations at QUB and NovaUCD , (v) focus on some case studies of selected cluster organisations, and (vi) analyse and write-up the survey results for inputting our data into SP1. With our survey data, we will make a significant contribution to the project in providing relevant and context-specific input for modelling. Among others, we will use the Irish Innovation Panel (IIP), a database providing information on the innovation, technology adoption, networking and performance of manufacturing and tradable services plants in Ireland and Northern Ireland over the period 1991-2008. Through analysis of this unique dataset, networking activity throughout Ireland can be examined and the innovation system profiled. Specific data will also be derived from the database on academic-industry partnerships and how this has contributed to innovation at a micro-level. Drawing on the IIP to inform cluster research, we will further qualitatively examine the clusters under investigation. In particular, analysis will explore the inherent tensions that exist in building a locally-embedded innovation network and at the same time internationalising the cluster. Mapping of the social networks in the clusters will be complemented by semi-structured interviews.
Dynamic network modelling techniques (e.g. SIENA modelling) are used to study the interaction over time between changing network structure and network actors' behaviour/attitudes in PCTs. Formal longitudinal network analysis (across a sample of PCTs) allows rigorous comparison and assessment, of alternative network processes for enhancing the coherence and innovation of the PCTs (Geary/TCD). Analysing decision-making in innovation networks: Here, we are concerned to identify the conditions under which the PCT model, as a health policy innovation, can build interdisciplinary collaboration across the health professionals and others involved. Group decision modelling and simulation techniques are used to identify the actor strategies and network structures, which can facilitate cohesive collective decision outcomes in PCTs.