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Although simulation models of geographical systems in general and agent-based models in particular represent a fantastic opportunity to explore socio-spatial behaviours and to test a variety of scenarios for public policy, the validity of generative models is uncertain unless their results are proven robust and representative of 'real-world' conditions. Sensitivity analysis usually includes the analysis of the effect of stochasticity on the variability of results, as well as the effects of small parameter changes. However, initial spatial conditions are usually not modified systematically in geographical models, thus leaving unexplored the effect of initial spatial arrangements on the interactions of agents with one another as well as with their environment. In this paper, we present a method to assess the effect of some initial spatial conditions on simulation models, using a systematic spatial configuration generator in order to create density grids with which spatial simulation models are initialised. We show, with the example of two classical agent-based models (Schelling's models of segregation and Sugarscape's model of unequal societies) and a straightforward open-source work-flow using high performance computing, that the effect of initial spatial arrangements is significant on the two models. Furthermore, this effect is sometimes larger than the effect of parameters' value change.

This paper undertakes empirical analysis of the relationship between productivity and transportation-induced agglomeration effects in the megacity region of the Paris Basin. The authors believe this to be the first study in the French context to produce elasticities of urban agglomeration economies for different industry sectors. Furthermore, the measure of agglomeration used by the authors explicitly took account of accessibility to economic mass in terms of driving times. This study is the first attempt to investigate the presence of nonlinearities in the relationship between productivity and agglomeration with French data. The findings indicate that transportation-induced agglomeration effects differ across industry groups and are greater for business services; these findings agree with existing evidence for other countries. The results also suggest considerable nonlinearity in the relationship between productivity and transportation-induced agglomeration effects and imply that the conventional estimation of country-level aggregate elasticities is likely to misrepresent the actual magnitude of any productivity gains from agglomeration.

Urban planners have explored many solutions for reducing the energy and environmental costs of daily mobility in cities and one of them is to encourage households to embrace more efficient commuting patterns. As research on "excess commuting" has shown, the spatial distribution of housing and jobs in many cities would theoretically allow much shorter commuting distances than are actually observed. The question this paper tackles is how a more efficient commuting pattern would affect the transport modes workers use to travel to work. If workers and jobs were rematched in such a way as to minimise average commute distance, how would such a change impact the way people travel to work? While one might easily imagine an increase in the share of trips covered by soft modes of transport, there are reasons to believe that in some cases there might also be unexpected outcomes such an increase in car use. So how would people travel to work in a city where there is no "excess commuting"? We looked for an answer to this question through empirical simulations in the case of the Paris Metropolitan Area. Highlights  An original way to explore the issue of excess commuting  A simulation-based approach to estimating the share of car use in trips-towork under the hypothesis of commute minimisation  Pioneering research on excess commuting in the case of the Paris Metropolitan Area  In the Paris Metropolis, cutting average commuting distance could result in an increase in commuting by car  Minimising commute length converts many long-range trips by public transport into mid-range trips by car