Regional innovation systems in Hungary: The failing synergy at the national level

TL;DR

This study measures the synergy of knowledge functions in Hungary's regional innovation systems using entropy statistics, revealing distinct dynamics and a lack of national-level contribution to overall innovation synergy.

Contribution

It applies entropy-based configurational information to analyze regional innovation systems, highlighting the failure of national-level integration in Hungary.

Findings

Budapest's region is a knowledge-based innovation system.

Foreign-owned firms influence regional knowledge organization.

Eastern and southern regions respond to government expenditure.

Abstract

We use entropy statistics in this paper to measure the synergies of knowledge exploration, knowledge exploitation, and organizational control in the Hungarian innovation system. Our data consists of high- and medium-tech firms and knowledge-intensive services categorized by sub-regions (proxy for geography), industrial sectors (proxy for technology) and firm size (proxy for organization). Configurational information along these three dimensions is used as an indicator of reduction of uncertainty or, in other words, the synergy across the knowledge functions. Our results indicate that three regimes have been created during the Hungarian transition with very different dynamics: (1) Budapest and its agglomeration emerge as a knowledge-based innovation system on every indicator; (2) the north-western part of the country, where foreign-owned companies have induced a shift in knowledge-organization; while (3) the system in the eastern and southern part of the country seems to be organized as a response to government expenditure. The national level no longer adds to the synergy across these regional innovation systems.