ALES BELOHRADSKY

THE VARIEGATED ROLE OF PROXIMITIES IN ACQUISITIONS BY DOMESTIC AND INTERNATIONAL COMPANIES IN DIFFERENT PHASES OF ECONOMIC CYCLES

V Kveton, A Belohradsky, J Blazek (2020)
Papers in Regional Science

This paper aims at an understanding of acquisition processes in a strongly industrialized and export‐oriented economy in Central Europe. Drawing on a proximity framework and behaviour theory, the paper investigates that the geographical proximity dimension is more influential than the cognitive proximity dimension. At the same time, cognitive proximity matters more for foreign firms investing into the economy than for domestic acquisitions. While the role of cognitive proximity diminished during the economic crisis, geographical proximity keeps its importance throughout the economic cycle. Moreover, cognitive proximity has become more important for acquisitions of large companies and less for SMEs.

REGIONAL HEALTH INEQUALITIES EXPLAINED: EMPIRICAL EVIDENCE FROM CZECHIA

A Belohradsky, D Glocker (2018)
GEOGRAFIE 124 (4), 365-383

Health outcomes in Central and Eastern Europe have been generally improving over the last two decades. However, in Czechia, similar to other countries, the outcomes vary significantly across the regional dimension. In 2016, life expectancy at birth ranged from between 75.5 to 80 years – across 77 districts. ;is article empirically analyses the determinants of these differences using a wide range of explanatory variables that are available on a district level. Applying factor analysis, our findings indicate that the socio-economic situation within a district is the main driver – explaining a difference of up to four years in life expectancy at birth. Further, controlling for gender specific variables, the results suggest that for men alcohol consumption significantly reduces life expectancy. Both factors capturing the socio-economic situation and alcohol consumption exceed the impact of health care accessibility or environmental causes on life expectancy. ;e results remain robust when using more disaggregated information on 206 administrative districts – per geographic scale.

 

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