Knowledge network centrality, formal rank and research performance: evidence for curvilinear and interaction effects

Abstract

This study explores the curvilinear (inverted U-shaped) association of three classical dimension of co-authorship network centrality, degree, closeness and betweenness and the research performance in terms of g-index, of authors embedded in a coauthorship network, considering formal rank of the authors as a moderator between network centrality and research performance. We use publication data from ISI Web of Science (from years 2002-2009), citation data using Publish or Perish software for years 2010-2013 and CV's of faculty members. Using social network analysis techniques and Poisson regression, we explore our research questions in a domestic co-authorship network of 203 faculty members publishing in Chemistry and it's sub-fields within a developing country, Pakistan. Our results reveal the curvilinear (inverted U-shaped) association of direct and distant co-authorship ties (degree centrality) with research performance with formal rank having a positive moderating role for lower ranked faculty.

Understanding Complexity: the Curvilinear Relationship Between Environmental Performance and Firm Performance

“…All these examples support the possibility of curvilinear relationship between EP and FP. The existence of curvilinear impacts has been tested in the literature beyond EP and FP, for example, in the case of knowledge creation (Badar et al 2015) and in fairness perceptions in job satisfaction (Janssen 2001).Thus, we argue that existing levels of EP positively moderate the link between EP and FP, which implies a curvilinear (quadratic) relationship. This notion is somewhat supported by a recent study on the link between social performance and financial performance (Barnett and Salomon 2006) that found evidence for a curvilinear relationship in the context of mutual fund investments.…”

Exploring the Relationship of Network Centrality and Academic Performance of Female Students

“…It is argued that too high or too little network centrality may be restraining. There should be an intermediary degree of network centrality which wins the maximum incentives and/or rewards (Rotolo & Petruzzelli, 2013;Mcfayden & Cannella, 2004;Badar et al, 2015).In case of current research closeness centrality is high (all advisers are from the same class) due to which students can get access to large but conflicting viewpoints (Podolny & Baron, 1997). Which may be the cause of negative relationship between closeness centrality and female student"s academic performance.…”

“…For example, organizational integration (Sparrowe & Liden, 1997), advancement, progress, development or promotion (Burt, 1992), authority, power, control (Brass, 1984), creativity (Ibarra, 1993), learning aftermaths (Baldwin, Bedell, & Johnson, 1997), and job successes (Sparrowe, et al, 2001) all depends on actors position in social network. In addition, individuals embedded in advice networks can benefit from the ties by gaining structurally beneficial positions in the advice network to derive positive outcomes for example enhanced research performance (Badar, Hite, & Ashraf, 2015).…”

Enhancing Internal Learning in Teams: The Role of Network Centrality and Psychological Capital of Undergraduate Students

“…This current research used the measure of in-degree centrality to analyze the centrality in advice networks. In-degree centrality is the measure most commonly used to show the position of the actor in a network, which is based on the number of direct links that an actor has with other actors (Badar et al, 2015). Additionally, in-degree centrality is considered as the relative extent to which an individual can be connected to all other individuals in the network, thus allowing to quantify the relative number of relationships of an individual in a given context (Vardaman et al, 2012).…”