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

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

The offline landscape of an online social network: distance and size shaping community spread and activity

This initial paper of our interest on geography of online social network is based on a literature in which geographers reformulated major concepts and hypotheses in the ‘90ies due to revolutionary development of internet (Cairncross, 1997). Cyberspace quickly became central issue in understanding human behaviour in the virtual world and cyber world has been always claimed to strongly twitted with physical world (Hayes, 1997). Parallel shift in economic geography research moved the focus of interest from distance to proximity, which is essential in our understanding for new knowledge creation and innovation in cities while the importance of distance is decreasing (Boschma, 2005). Economic geographers also claim that innovation and knowledge creation remained local in the era of internet because the need of face-to-face interactions (Feldman, 2002); internet-based communication seems to stimulate local offline communication (Storper and Venables, 2004). Social network sites are major fields of online communication and "enable users to articulate and make visible their social networks" (boyd and Ellison, 2007). Online social network (OSN) are large-scale networks and claimed to be supplemental forms of communication between people who have known each other primarily in real life (Ellison et al, 2006, 2007). We believe that studying these networks will give new insights to local learning and social capital issues by providing excellent data on online local learning and also proxies of offline local learning. According to recent findings on large scale OSNs (Facebook and Twitter), geographical location of users and their friends turns to be a determining factor for the structure of the network (Backstrom et al, 2011, Takhteyev et al, 2012, Ugander et al, 2011). However, more traditional geographical aspects are also needed to analyse spatial distribution of OSN activity. Our research questions address both the effects of distance and settlement size on population shares involved in online communities such as online social networks. Preliminary findings on iWiW, a leading online social network in Hungary with more than 4 million users, suggest that share of users is higher in bigger settlements and positively associated with geographical proximity of Budapest. On the other hand, the average number of friendship ties is independent from settlement size and is higher in peripheral regions of the country. In sum, settlement size and distance may play decisive role in shaping geographies of OSN

Atypical combinations of technologies in regional co-inventor networks

Novel combinations of technologies are usually the result of collaborative work that builds on existing knowledge. Albeit inventors and their respective communities tend to be specialized, inventor collaborations across differently specialized peers have the potential to generate co-inventor networks that provide access to a diverse set of knowledge and facilitate the production of radical novelty. Previous research has demonstrated that short access in large co-inventor networks enables innovative outcomes in regional economies. However, how connections in the network across different technological knowledge domains matter and what impact they might generate is still unknown. The present investigation focuses on ‘atypical’ combinations of technologies as indicated in patent documents. In particular, the role of technological specializations linked in co-inventor networks that result in radical innovation in European regions is analyzed. Our results confirm that the share of atypical patents is growing in regions where bridging ties establish short access to and across cohesive co-inventor sub-networks. Furthermore, the evidence suggests that the strong specialization of co-inventor communities in regions fosters atypical combinations because these communities manage to increase the scale and scope of novel combinations. Thus, bridges between communities that are specialized in different technologies favor atypical innovation outcomes. The work shows that not diversity per se, but links across variously specialized inventor communities can foster radical innovation

Data from: Social capital predicts corruption risk in towns

Corruption is a social plague: gains accrue to small groups, while its costs are borne by everyone. Significant variation in its level between and within countries suggests a relationship between social structure and the prevalence of corruption, yet, large-scale empirical studies thereof have been missing due to lack of data. In this paper, we relate the structural characteristics of social capital of settlements with corruption in their local governments. Using datasets from Hungary, we quantify corruption risk by suppressed competition and lack of transparency in the settlement’s awarded public contracts. We characterize social capital using social network data from a popular online platform. Controlling for social, economic and political factors, we find that settlements with fragmented social networks, indicating an excess of bonding social capital has higher corruption risk, and settlements with more diverse external connectivity, suggesting a surplus of bridging social capital is less exposed to corruption. We interpret fragmentation as fostering in-group favouritism and conformity, which increase corruption, while diversity facilitates impartiality in public life and stifles corruption

Data from: Social capital predicts corruption risk in towns

Corruption is a social plague: gains accrue to small groups, while its costs are borne by everyone. Significant variation in its level between and within countries suggests a relationship between social structure and the prevalence of corruption, yet, large-scale empirical studies thereof have been missing due to lack of data. In this paper, we relate the structural characteristics of social capital of settlements with corruption in their local governments. Using datasets from Hungary, we quantify corruption risk by suppressed competition and lack of transparency in the settlement’s awarded public contracts. We characterize social capital using social network data from a popular online platform. Controlling for social, economic and political factors, we find that settlements with fragmented social networks, indicating an excess of bonding social capital has higher corruption risk, and settlements with more diverse external connectivity, suggesting a surplus of bridging social capital is less exposed to corruption. We interpret fragmentation as fostering in-group favouritism and conformity, which increase corruption, while diversity facilitates impartiality in public life and stifles corruption

Productivity spillovers through labor flows: productivity gap, multinational experience and industry relatedness

Labor flows are important channels for knowledge spillovers between firms; yet competing arguments provide different explanations for this mechanism. Firstly, productivity differences between the source and recipient firms have been found to drive these spillovers; secondly, previous evidence suggests that labor flows from multinational enterprises provide productivity gains for firms; and thirdly, industry relatedness across firms have been found important, because industry-specific skills have an impact on organizational learning and production. In this paper, we aim to disentangle the effects of productivity gap, multinational experience and industry relatedness in a common framework. Hungarian employee–employer linked panel data from 2003–2011 imply that the incoming labor from more productive firms is associated with increasing future productivity. The impact of multinational spillovers cannot be confirmed, once productivity differences between the firms are taken into account. Furthermore, we find that flows from related industries outperform the effect of flows from same and unrelated industries even if we control for the effects of productivity gap and multinational spillovers

Understanding European integration with bipartite networks of comparative advantage

Core objectives of European common market integration are convergence and economic growth, but these are hampered by redundancy, and value chain asymmetries. The challenge is how to harmonize labor division to reach global competitiveness, meanwhile bridging productivity differences across the EU. We develop a bipartite network approach to trace pairwise co-specialization by applying the revealed comparative advantage method within and between the EU15 and Central and Eastern European (CEE). This approach assesses redundancies and the division of labor in the EU at the level of industries and countries. We find significant co-specialization among CEE countries but a diverging specialization between EU15 and CEE. Productivity increases in those CEE industries that have co-specialized with other CEE countries after EU accession, while co-specialization across CEE and EU15 countries is less related to productivity growth. These results show that a division of sectoral specialization can lead to productivity convergence between EU15 and CEE countries

A novel approach for determining instantaneous centers of rotation of the mandible with an intraoral scanner: A preliminary study.

ObjectivesRecording and reproducing mandibular movements have been of key importance in the practice of dentistry for over a century. Recently, it has become possible to use digital technologies for these tasks. This study presents a preliminary method to try to identify the mandibular instantaneous centres of rotation based solely on intraoral scanners.MethodsThe dentitions of four participants were scanned, multiple inter-occlusal registrations and buccal scans were performed in closed and opened positions. Blender software was used to align the meshes during the post-scan digital workflow. Bite alignment accuracy was assessed and then improved with a strict exclusion protocol. An automated algorithm was used to find rotations between closed stage and open stage meshes.ResultsOur exclusion protocol reduced the bite alignment error significantly (p = 0.001) and the root-mean-square error value of the meshes decreased from 0.09 mm (SD = 0.15) to 0.03 mm (SD = 0.017). However, the remaining translational error caused an unexpectedly large shift in the axis of rotation (mean = 1.35 mm, SD = 0.77) with a 41.83: 1 ratio. As found in other studies, our results showed even a small amount of error during registration can shift the axis of rotation a large amount. This phenomenon will compromise the results of common pantographic methods which assume a rotation axis of the condyle. It also adds valuable information to the concept of instantaneous centers of rotation by revealing their true characteristics