Network studies of science offer researchers a great insight into the dynamics of knowledge creat... more Network studies of science offer researchers a great insight into the dynamics of knowledge creation and the social structure of scientific society. The flow of ideas and overall cognitive structure of the scientific community is observed through citations between scientific contributions, usually manifested as patents or papers published in scientific journals. The social structure of this society consists of relationships among scientists. De Haan suggests six operationalized indicators of collaborative relations between scientists: coauthorship; shared editorship of publications; shared supervision of PhD projects; writing a research proposal together; participation in formal research programs; and shared organization of scientific conferences. Due to accessibility and the ease of acquiring data through bibliographic databases, most scientific collaboration analyses are performed on co-authorship data, which play a particularly important role in research into the collaborative social structure of science. Coauthorship networks are personal networks in which the vertices represent authors, and two authors are connected by a tie if they co-authored one or more publications. These ties are necessarily symmetric. The study of community structures through scientific co-authorship is especially important because scientific (sub)disciplines can often display local properties that differ greatly from the properties of the scientific network as a whole. Co-authorship
Network studies of science offer researchers a great insight into the dynamics of knowledge creat... more Network studies of science offer researchers a great insight into the dynamics of knowledge creation and the social structure of scientific society. The flow of ideas and overall cognitive structure of the scientific community is observed through citations between scientific contributions, usually manifested as patents or papers published in scientific journals. The social structure of this society consists of relationships among scientists. De Haan suggests six operationalized indicators of collaborative relations between scientists: coauthorship; shared editorship of publications; shared supervision of PhD projects; writing a research proposal together; participation in formal research programs; and shared organization of scientific conferences. Due to accessibility and the ease of acquiring data through bibliographic databases, most scientific collaboration analyses are performed on co-authorship data, which play a particularly important role in research into the collaborative social structure of science. Coauthorship networks are personal networks in which the vertices represent authors, and two authors are connected by a tie if they co-authored one or more publications. These ties are necessarily symmetric. The study of community structures through scientific co-authorship is especially important because scientific (sub)disciplines can often display local properties that differ greatly from the properties of the scientific network as a whole. Co-authorship
Over the past few decades, scientific collaboration has been widely considered an important drive... more Over the past few decades, scientific collaboration has been widely considered an important driver of research innovation. By collaborating together, scientists can benefit from both methodological and technological complementarities and synergy, improving the quality and quantity of their research outputs. As evidence of this, collaboration among scientists is increasing in all disciplines and government policies in international exchange programs are aimed at promoting collaboration among researchers. Collaboration among scientists can be represented as a network, usually adopting co-authorship as linkages. In this view, Social Network Analysis provides a useful theoretical and methodological approach because collaboration features can be related to the topological characteristics of the network. Recently, several empirical studies have found positive associations between researchers' position in the co-authorship network and their productivity, although the results can be different depending on the discipline, scientific performance measure, and data source retrieved to construct the co-authorship networks. In this contribution, we propose the use of SNA tools for scientific evaluation purposes. Network indices at the individual and subgroup levels will be introduced
Depoliticization of Governance in Large Municipalities in Europe
Urban Affairs Review
The premise of our research paper is that large (by the size of the population) municipalities ar... more The premise of our research paper is that large (by the size of the population) municipalities are more complex to govern and manage, and this, in turn, calls for a more professional and apolitical local government. Using data from the largest European survey of mayors, we analyzed the influence of mayors and chief administrative officers in Europe and checked for correlations with the size of the local government. We present empirical evidence to support that the perceived influence of mayors varies with the size of the municipality regardless of the institutional configuration of power relationships. We found that very large municipalities (80,000 or more inhabitants) had weaker mayors. The presumption that a larger, more complex local (urban) environment calls for more professional leadership has been addressed in numerous publications; however, the answer was usually beyond the reach of the empirical tests.
ki znotraj discipline ne sodelujejo. Nadgradnja metode posplošenega blocnega modeliranja, ki omog... more ki znotraj discipline ne sodelujejo. Nadgradnja metode posplošenega blocnega modeliranja, ki omogoča sledenje spremembam v strukturi znotraj disciplin, pokaže, da imajo laboratorijske discipline, kjer je delitev dela, virov in vlog natančneje določena, stabilnejšo strukturo od pisarniških disciplin, v katerih raziskovalci niso tako strogo povezani z raziskovalnim okoljem. V vseh disciplinah lahko na podlagi uporabe večih metod potrdimo močno prisotnost strukture malih svetov, hkrati pa je v laboratorijskih disciplinah struktura, ki je posledica preferenčne izbire, manj izrazita kot v pisarniških disciplinah.
Responding to the call for cooperation between the policy network and governance literature, we a... more Responding to the call for cooperation between the policy network and governance literature, we apply social network analysis (SNA) to a study of European multi-level policymaking using empirical data gathered as part of the INTEREURO project. We focus on the studied network’s characteristics and, building on hypotheses developed in the policy network and governance literature, judge the potential capacity to coordinate EU networks. Based on our analysis, we redefine the decisional centre of EU networks and argue that coordination capacity varies among different policy fields.
Povzetek. Z metodami za analizo socialnih omrežij preučujemo strukturo slovenske politične razpra... more Povzetek. Z metodami za analizo socialnih omrežij preučujemo strukturo slovenske politične razprave na spletnem družbenem omrežju Twitter pred volitvami v Evropski parlament 2019. Opisujemo omrežje 2867 uporabnikov in 40670 objav (tvitov), središčne uporabnike, pretok informacij prek posredovanih objav (retvitov) in skupnosti uporabnikov. Med najaktivnejšimi uporabniki prevladujejo širši javnosti manj znani posamezniki, med najvplivnejšimi pa politične stranke, politiki in znane osebnosti. V omrežju pretoka informacij se pojavljajo politično/mnenjsko homogene skupnosti uporabnikov, kar nakazuje na fragmentacijo mrežne javne sfere in polarizacijo slovenske spletne politične razprave. Rezultati ponujajo enega izmed prvih vpogledov v pretok informacij med slovenskimi uporabniki Twitterja skozi prizmo fragmentacije družbenih omrežij.
This study reviews the presence of articles related to Central and Eastern Europe (CEE) in Web of... more This study reviews the presence of articles related to Central and Eastern Europe (CEE) in Web of Science (WOS). Bibliometric analysis first reveals the trends of CEE-related articles in the areas of international business (IB), management and economics up to 2016. The results show steady growth in absolute and relative numbers after 1990, intensifying since 2010. Second, we conduct topic research using network analysis with blockmodeling. We identify a network of topics and their interrelations over time and used them to periodise the CEE-related research in IB. The most-cited CEE-related IB articles and the main citation path are also presented. The analysis adds to the discussion of how the CEE region is explored in IB research, its contributions, impacts and the challenges facing regional research in the future. In this study, a methodology and framework for performing a comprehensive bibliometric analysis on regional IB research is applied.
Environmental consciousness of European consumers: A segmentation-based study
Journal of Cleaner Production, 2019
Abstract Sustainable consumption is not a one-dimensional phenomenon; it entails various attitudi... more Abstract Sustainable consumption is not a one-dimensional phenomenon; it entails various attitudinal and behavioural dimensions. To promote sustainability, decision-makers are encouraged to recognise the heterogeneity of sustainable consumers. The aim of this study was to examine a model of environmental consciousness and use its variables to segment European Union (EU) consumers. The study used a structural equation modelling approach to verify the environmental consciousness model and hierarchical agglomeration method for segmentation. It was based on secondary data on environmental issues gathered in 28 EU member states. Personal attitudinal dimensions in the model explained a relatively high proportion of the variance in sustainable behaviour. The segmentation analysis yielded three distinct segments that differ in their environmental consciousness and are affiliated with different EU country clusters. The use of secondary data to a certain extent limited the analysis. However, its strengths are its scope, the potential generalisability of the results and comparability based on EU data.
This study addressed an important question about the meaning of corporate social responsibility (... more This study addressed an important question about the meaning of corporate social responsibility (CSR), and how it is measured. Based on a comparison of the meaning networks of CSR in two countries with fundamentally different cultural and socioeconomic backgrounds, we argue that there is a need for an institutional perspective when studying CSR associations and expectations in a particular society. Thus empirical study involved the use of three methods the word-association technique, social network analysis, and blockmodeling using Pajek software; to provide deep insight into the structure of CSR associations. The findings suggest that the two societies have diverse collective cognitive structures regarding CSR. In Turkey, the philanthropic understanding of CSR is highly dominant, while the Slovenian social meaning of CSR is multidimensional. The findings point to the social construction of the concept of CSR with implications both for academic research and practice.
The paper introduces the use of blockmodeling in the micro-level exploration of the internal stru... more The paper introduces the use of blockmodeling in the micro-level exploration of the internal structure of coauthorship networks over time. Variations in scientific productivity and researcher or research group visibility were determined by observing authors' role in the core-periphery structure and crossing this information with bibliometric data. Three techniques were applied to represent the structure of collaborative science: (1) blockmodeling; (2) the Kamada-Kawai algorithm based on the similarities in co-authorships present in the documents analysed; (3) bibliometrics to determine output volume, impact and degree of collaboration from the bibliographic data drawn from publications. The results were examined to determine the extent to which the use of these two complementary approaches, in conjunction with bibliometric data, provides greater insight into the structure and characteristics of a given field of scientific endeavour. The paper describes certain features of Pajek software and how the application might be used to study research group composition, structure and dynamics. The approach involves combining bibliometric and social network analysis to explore scientific collaboration networks and monitor individual and group careers from new perspectives. The contributionof the paper is more on methodology than the conclusions drawn from the data. Its description of a small-scale case study is intended as an example for application and can be used in other disciplines. It may be very useful for the appraisal of scientific developments.
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