The impact of local characteristics on innovation and business productivity has been studied extensively, including the impacts of labor force access, agglomeration benefits or access to financing. It remains largely unknown, however, to which degree multiplier effects generated by regional characteristics, network effects or accessibilities affect innovation and productivity.
Large-scale company surveys provide detailed information on business investments and innovation performance in Germany. A country-wide transport model will be implemented to calculate travel times and accessibilities. These indicators will augment the survey-level data allowing to study their impact on innovation and business performance. First, a nation-wide synthetic population of persons and jobs is generated. Next, the agent-based person travel demand model MITO will be implemented and complemented by simulations of long-distance person flows, freight, and non-freight commercial vehicles. The model will be used to calculate a large number of accessibilities, including cumulative accessibilities, potential accessibilities and logsum accessibilities. Using machine learning algorithms, accessibility calculations will be used to explain the impact of accessibilities on innovation, business productivity and the effectiveness of policy programs. After the impact of accessibility on economic performance has been established, employment forecasts can be provided that will be used in the agent-based transport model.