Mapping collaboration networks in talent management research

Abstract

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.

Exploring the conceptual structure of the auditing discipline through co‐word analysis: An international perspective

“…The apparently low-density value was not particularly surprising and it was attributable to the large size of the network in our case(Gallardo-Gallardo et al, 2017). The density values across the years (i.e., 0.006 in 2000-2005, 0.006 in 2006-2010, and 0.004 in 2011-2016) indicated a decreasing trend in the final period, and it was 0.003 for allperiods, implying that 0.3% of all possible links between keywords actually existed.…”

“…In other words, the degree of a network indicates the number of lines emanating from a particular node (i.e., keyword) (Andrikopoulos & Kostaris, 2017); hence, the higher the degree, the greater the number of lines connecting a particular keyword to other keywords, implying the tightness of the network (Wang & Chen, 2003). The increasing value of the average degree across the periods indicated the propensity for higher connectedness of the keywords in the auditing discipline (i.e., 7.17 in 2000-2005, 7.26 in 2006-2010, and 8.19 in 2011-2016 (Gallardo-Gallardo et al, 2017). Third, across the periods, the consistent increase in connectedness and decrease in fragmentation in the network showed that the co-word network became increasingly tight and cohesive (Kılıç et al, 2019;Varga, 2011), because the connectedness index measures the extent to which individual actors are connected in the network, whereas the fragmentation index indicates how the network fragments into clusters (Shimada & Sueur, 2014).…”

Co‐authorship Network Analysis in the Accounting Discipline

“…Indeed, it is not surprising to have low density and it does not mean decreasing research collaboration, particularly in a large network size (i.e., in our case) as density is inversely related to network size (Gallardo‐Gallardo et al. ). The co‐authorship network of authors in the scientometrics field is composed of one large component (known as the main, giant or core component) which fills a large portion of the graph, and many small components that fill the rest (Newman ; Abbasi et al.…”

“…Hence, any two authors have a high probability of co-authorship if they have collaborated with a third author. Network density ranging from zero to one at maximum is the proportion of actual links in a network to maximum possible links (Racherla and Hu 2010;Gallardo-Gallardo et al 2017), which means the probability of a tie formation (Andrikopoulos and Kostaris 2017). The low and steady density rate (0.001) of the co-authorship network in all sub-periods indicates that only 0.1% of all possible links are present in all periods.…”

Gender disparities and positioning in collaborative hospitality and tourism research

“…They found that papers with female first authors have a lower citation rate than those with male first authors. A study by Gallardo-Gallardo et al, (2017) (Zupic and Čater, 2015, p. 439). The present study relies on a commonly used technique for the analysis of co-authorships -social network analysis (Munoz et al, 2016).…”