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Geographical mobility is often considered fundamental to a well-functioning labour market, and thus to the economy as a whole. Typically, geographical mobility can be achieved either through commuting or through migration. Commuting can be considered important for households to have access to job market opportunities and for business to access labour, skills and competencies. Previous research has found commuting patterns to differ between men and women, for example, in the sense that women travel shorter distances and rely more on public transport. However, we also know that factors such as higher education can influence an individual’s decision to commute, possibly because of specialization and a higher salary. As women’s education level approaches, or surpasses, that of men’s, one would expect to see more similarities between the travel behaviour of the two genders. In this study, we analyse gender patterns of commuting in Norway, Serbia and Sweden. We specifically address the issue of gender gap in commuting. Findings show that though there are signs of convergence, there are large regional variations. The gender gap is decreasing primarily in the more urban regions, while it is decreasing less, and even increasing, given the various levels of aggregation, in the more rural areas.

Large regional disparities lead, among other things, to significant internal migration flows. Internal migrations, on the other hand, reinforce existing regional disparities by causing a lack of human capital in underdeveloped regions. In this chapter, we apply the Multiple Criteria Decision Aiding (MCDA) sorting method, ELECTRE Tri-C, to determine the current internal migration potential for districts in Serbia. The method will provide four classes of migration potential, ranging from strong emigration to strong immigration potential, based on the main drivers of internal migration. The main determinants of internal migration flows fall into three groups: (1) economic and labour market indicators, (2) demographic indicators and (3) housing market and amenities indicators.