Network centrality and delegated investment performance

Rossi, Alberto G.; Blake, David; Timmermann, Allan; Tonks, Ian; Wermers, Russ

doi:10.1016/j.jfineco.2018.02.003

Cited by 117 publications

(44 citation statements)

References 52 publications

(63 reference statements)

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“…Therefore, SNA is an increasingly interdisciplinary field that focuses on a set of actors and the relationships that link them (Borgatti et al, 2009). The theory of social networks aims to explain the structure of relationships between social entities and how social structure influences other social phenomena, such as psychological well-being, reciprocal support and social capital, knowledge management, and financial risk-adjusted performance (Bae et al, 2018;Rossi et al, 2018).…”

Section: Network Centralitymentioning

confidence: 99%

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

2020

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This study aims to analyze the mediating role of psychological capital (PsyCap) in the relationship between network centrality and internal learning in teams. A questionnaire was administered to 480 undergraduate students to test this relationship. The results confirmed the positive relationship between network centrality and internal learning in teams, and a mediating role of PsyCap in the relationship between student network centrality and internal learning in teams. This study suggests that it is important to promote centrality in advice networks among undergraduate students. In addition, this study might raise awareness among students, teachers, and public policymakers about the need to promote a socially responsible environment in higher education institutions.

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Section: Network Centralitymentioning

confidence: 99%

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

2020

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“…Previous studies on ranking influential actors within networks have predominantly focused on individual centrality measures such as Degree centrality, Closeness Centrality, Information Centrality, Betweeness Centrality and Eigenvector Centrality [41], which overlook a unifying ground for the different purpose driven centrality measures. In the view of Rossi, Blake [38] decision making with single attributes turns to side-line of the importance of other equally significant measures in determining worker relevance. The emergence of different measures of influence in social network analysis is the conviction of the unreliableness of the individual measures of centrality in reaching universal reliability as suggested by Deng, Yeh [25] [42].…”

Section: Discussionmentioning

confidence: 99%

An Application of TOPSIS Approach in Determination of Spread Influencers in a Competitive Industrial Space: Evidence from the Banking Network of Ghana

Kong¹,

Dankyi²,

Ankomah-Asare³

et al. 2019

JHRSS

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In this paper, we investigated into aggregated social influence. We adopted and modified the weighted TOPSIS approach to ascertain the overall social influences of management members in the banking network of Ghana. The weighted TOPSIS method employs a composite approach of classical centrality influence that uses the position of the actor in the network hierarchy, the intensity of his interaction, extent of his connectivity and flow of information within the network. The approach offers an extensive advantage in ensuring holistic decision making by implementing an algorithm that employs a multi-criteria approach. The study revealed that although most single attributes were significant in measuring the niched aspect of social influence, the closeness to ideal that was attained through a weighted TOPSIS algorithm showed stronger ties and was conclusive enough to judge the social influence of actors to warrant its sole application in the determination of spreaders or influential nodes in a network. To enhance efficiency in decision making in relation to employment and layoffs, it is recommended that a social network analysis which adapts a multi-attribute decision-making approach that reflects both individual strength and weaknesses in totality for all aspect of social influences should be employed. We recommend further studies into Actor Ranking and its impact on recruitment practices for organizational innovation.

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“…Whereas previous studies have focused on CEOs' high network centrality or partially interlocking boards (Cai & Sevilir, 2012;Helmers et al, 2017;Rossi et al, 2018;Skousen et al, 2018), we provide the first fully integrated evidence of the impact of TMT network centrality on corporate bond yield spreads using unique Chinese listed firms across the sample period of 2007 to 2016. We find that the TMT network centrality significantly impacts bond spreads.…”

Section: Discussionmentioning

confidence: 99%

“…This paper makes contributions to the development of social networks from several aspects. First, there is a lot of literature examining the value of CEO or board interlocking network centrality partially (Cai & Sevilir, 2012;Chuluun et al, 2014;Cohen, Frazzini, & Malloy, 2008;El-Khatib et al, 2015;Helmers et al, 2017;Larcker et al, 2013;Rossi et al, 2018;Skousen et al, 2018). In this paper, however, we take all TMT members into account rather than only a few members.…”

mentioning

confidence: 99%

Do social ties matter for corporate bond yield spreads? Evidence from China

Qiu

Xiao

2019

Corporate Governance

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Research Question/Issue: This paper studies the effect of top management team (TMT) network centrality on corporate bond yield spreads. In additional analyses, we examine the hierarchical structures of TMT and study which parts contribute to the decrease in bond yield spreads. We also examine the mediating roles (including informed trading probability, media coverage, political ties, financial ties, and bond ratings) and the moderating roles (including marketization and analysts following) in the correlation between TMT network centrality and corporate bond yield spreads.Research Findings/Insights: This paper finds that firms with high TMT network centrality are significantly negatively correlated with lower bond yield spreads. The findings are robust after controlling for a series of sensitivity checks and endogenous concerns. The results of the hierarchical structures show that the decrease of bond spreads is accounted for CFOs' networks and board members' networks, whereas the role of CEOs' networks is not apparent. More importantly, after controlling CEOs'

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Network centrality and delegated investment performance

Cited by 117 publications

References 52 publications

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

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

An Application of TOPSIS Approach in Determination of Spread Influencers in a Competitive Industrial Space: Evidence from the Banking Network of Ghana

Do social ties matter for corporate bond yield spreads? Evidence from China

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