Co-authorship networks in electronic markets research

Fischbach, Kai; Putzke, Johannes; Schoder, Detlef

doi:10.1007/s12525-011-0051-5

Cited by 46 publications

(50 citation statements)

References 74 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Finally, the results of H4 show that centrality values clearly affect the number of citations. This is exactly in line with the results of studies by [74,98], which confirmed a positive correlation between centrality values and citation values.…”

Section: Discussionsupporting

confidence: 91%

Social Network Analysis of Scientific Articles Published by Food Policy

et al. 2018

View full text Add to dashboard Cite

Abstract:The article analyses co-authorship and co-citation networks in Food Policy, which is the most important agricultural policy journal in the field of agricultural economics. The paper highlights the principal researchers in this field together with their authorship and citation networks on the basis of 714 articles written between 2006 and 2015. Results suggest that the majority of the articles were written by a small number of researchers, indicating that groups and central authors play an important role in scientific advances. It also turns out that the number of articles and the central role played in the network are not related, contrary to expectations. Results also suggest that groups cite themselves more often than average, thereby boosting the scientific advancement of their own members.

show abstract

Section: Discussionsupporting

confidence: 91%

Social Network Analysis of Scientific Articles Published by Food Policy

et al. 2018

View full text Add to dashboard Cite

show abstract

“…At the micro level (node or actor level), the most widely statistic used to describe the co-authorship network is an author's degree centrality (Fischbach et al, 2011), which reflects the number of collaborators of researchers. In other words, degree centrality measures how many connections tie authors to their immediate neighbours in the network (i.e.…”

Section: --Insert Figure 3--mentioning

confidence: 99%

“…Indeed, co-citation analysis would allow for a better appraisal of knowledge flow among academic papers and specialties (i.e., the cross-pollination of ideas across knowledge domains) (Ciotti et al, 2016, Nerur et al, 2015. Further, this analysis would help in estimating the impact of how authors' embeddedness in research communities affects their research in terms of impact (see Collet et al, 2014, Fischbach et al, 2011 Another possible line of future research is to examine co-authorship networks by means of an improved mixed-method approach (i.e., combining qualitative and quantitative methods to enrich the explanation of underlying processes and their meaning to the actors involved). This would avoid an overemphasis on the structural dimension of social networks at the expense of the relational contents (see Kase et al, 2013), and assist in finding answers to questions regarding processes and factors that explain co-authorship (Velden and Lagoze, 2013;Velden et al 2010;Fry and Talja, 2007).…”

Section: Limitations and Suggestions For Future Researchmentioning

confidence: 99%

Mapping collaboration networks in talent management research

Gallardo-Gallardo¹,

Moliner²,

Gallo³

2017

JOEPP

View full text Add to dashboard Cite

Purpose (100 words): Despite the popularity of talent management (TM), very little has been published on the community of scholars that contribute to the knowledge base of the field. The aim of this paper is to disclose the dynamics in TM research through a detailed analysis of its evolving collaboration networks (i.e., research communities) in order to identify key authors and major topics covered.Design/Methodology/approach (100 words): A total of 225 co-authored articles published on TM from 2001 to May 2016 were retrieved from the Web of Science and Scopus and then analyzed and mapped using Social Network Analysis methods. Findings (100 words):We identified two major scientific communities (one of 63 authors and the other one of 24 authors). Both communities not only have different characteristics and structure, but also focus on different topics. We identified key players within each community and we offer a dynamic view on the main topics studied. Research implications:Our findings offer evidence on how collaborations among researchers shape the debates on the field. This can assist in drafting adequate strategies (at individual and discipline level) so as to help consolidate the field by encouraging new associations both in terms of actors involved and topics covered. Our study also offers a promising perspective for further using bibliometrics and social network analysis in TM research. Practical implications:This article may help practitioners and newcomers to the field to rapidly identify key players and main topics studied in TM field. It may assist academic institutions and journal editorial teams in better assessing and identifying key scholars in this field.Originality: This paper offers the first analysis of TM collaborative research networks.

show abstract

“…Quanto mais pontos estão ligados uns aos outros, mais denso será o gráfico. No contexto de uma rede de coautoria, a densidade reflete o percentual do total da rede com o qual um ator foi coautor de um artigo (FISCHBACH;PUTZKE;SCHODER, 2011).…”

Section: Análise De Redes Sociaisunclassified

Análise da colaboração científica departamental através de redes de coautoria

Bordin

Gonçalves

Todesco

2014

Perspect. ciênc. inf.

View full text Add to dashboard Cite

O entendimento da rede de colaboração de um departamento de Pós-graduação permite a identificação de uma série de itens relacionados ao processo de colaboração científica, tais como: nível de colaboração da comunidade envolvida, distância média entre os colaboradores, autores que mais colaboram, grupos que colaboram com mais intensidade, etc. Através da produção bibliográfica informada ao sistema Coleta de Dados da CAPES, referente ao período de 2005-2012, redes de coautoria foram criadas e analisadas através de métricas de análise de rede social. Foi encontrado um índice médio de colaboração de 3,4 autores por publicação, redes de coautoria com baixa densidade, um maior número de componentes nos primeiros anos do programa e autores com alta produtividade, porém, com baixa centralidade de grau. Acredita-se que a análise e discussão dos resultados apresentados nesse artigo alcançaram o objetivo macro de diagnosticar a produção bibliográfica do programa, em termos de colaboração científica, e espera-se que seja uma ferramenta útil para tomada de decisão em nível organizacional e individual.

show abstract

Co-authorship networks in electronic markets research

Cited by 46 publications

References 74 publications

Social Network Analysis of Scientific Articles Published by Food Policy

Social Network Analysis of Scientific Articles Published by Food Policy

Mapping collaboration networks in talent management research

Análise da colaboração científica departamental através de redes de coautoria

Contact Info

Product

Resources

About