Modeling interregional research collaborations in German biotechnology using industry directory data

Area of Science:

• Biotechnology
• Regional Science
• Innovation Studies
• Social Network Analysis

Background:

• Mapping research collaborations is crucial for understanding knowledge flows.
• Existing data may not capture the nuances of interregional R&D partnerships.
• German biotechnology sector presents a dynamic landscape for collaboration studies.

Purpose of the Study:

• To introduce a comprehensive dataset on German biotechnology research collaborations.
• To facilitate empirical analysis of determinants influencing interregional R&D networks.
• To provide a resource for social network and regression analyses in innovation research.

Main Methods:

• Data extracted from the BIOCOM Year and Address book (2005, 2009).
• Micro-data on firms and institutions aggregated to NUTS3 regions.
• Linked to regional covariates: research capacities, policy support, innovation system strength.

Main Results:

• The dataset provides a detailed map of research collaborations in German biotech.
• It allows for the identification of factors influencing interregional collaboration patterns.
• Preliminary findings highlight capacity, proximity, and policy as key determinants.

Conclusions:

• The presented dataset is a valuable resource for researchers studying innovation networks.
• It supports empirical investigations into knowledge flows and collaboration drivers.
• Future research can leverage this data for advanced network and spatial analyses.