Improved Gravity Models of Commuting Conditions: A Czech Case Study

Abstract

The aim of this paper is to present the development of improved gravity models of commuting conditions based on alternatively-assessed “mass” of origins and destinations, as well as on improved distance evaluation. For the case study the Ostrava region (CZ) was selected and delimited as a catchment with significant everyday commuting flows to Ostrava, observed in the 2011 census.. The distribution of employers was constructed using the Albertina - Company Monitor. The number of employees in all companies within each municipality and each economical sector represents the attractiveness of municipalities as destinations in the gravity model. The origins in the gravity model are represented by municipalities. Their power to generate commuting flows is directed by the population of employed inhabitants. The distances between municipalities were enumerated using road network analysis and substituted by railway distances if they were shorter. For selected economic sectors (i.e. processing industries, internal trade) the specific gravity models of regional daily commuting flows were calibrated. The calibration was based on observed commuting flows between municipalities for each economic sector adjusted for missing census’ answers. Differences among sector gravity models are discussed. Their Root Mean Square Errors and Mean Errors show the overall fitness of models. The variability of models’ parameters generally corresponds to expected differences among economic sectors. Finally, extreme differences of observed and expected flows for each gravity model were analysed. The results prove the usefulness of applied improved gravity models to understand commuting conditions, discover drawbacks of existing public transport services and challenges to improve the current conditions towards better efficiency of transport organisation. The parameters of gravity models can be utilised in stochastic simulations of random commuting flows in the region.

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