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Tracing structure, tie Strength, and cognitive networks in LMX theory and research

Tracing structure, tie Strength, and cognitive networks in LMX theory and research

Sparrowe, Raymond T. and Emery, Cécile (2015) Tracing structure, tie Strength, and cognitive networks in LMX theory and research. In: Bauer, Talya and Erdogan, Berrin, (eds.) The Oxford Handbook of Leader-Member Exchange. OLOP . Oxford University Press (USA), pp. 293-310. ISBN 9780199326174

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Abstract

This chapter reflects on the growing relationship between Leader–Member Exchange (LMX) theory and research and social network analysis. We first discuss the themes of structure and tie strength in relation to several of the theoretical formulations of LMX theory that have served as the foundation for subsequent research. This section proceeds chronologically, beginning with the earliest work on the Vertical Dyad Linkage (as the LMX perspective was initially known) and concluding with recent empirical research integrating LMX and social networks. Our goal is to provide a narrative review of the development of the themes of structure and tie strength within the LMX literature. We then turn to recent developments in the field in which LMX differentiation figures prominently both theoretically and empirically, and engage in a close critical reading of this work from the perspective of cognitive social networks. We conclude by summarizing the opportunities for future research that emerge from our narrative and conceptual analysis.

Item Type: Book Section
Uncontrolled Keywords: Leader–member exchange; Vertical dyad linkage; Social networks; Cognitive networks
Subjects: H Social Sciences > HM Sociology
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Department of Human Resources & Organisational Behaviour
Faculty of Business > Centre for Work and Employment Research (CREW) > Leadership & Organisational Behaviour Research Group (LOB)
Related URLs:
Last Modified: 10 Jun 2019 13:31
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: GREAT 1
URI: http://gala.gre.ac.uk/id/eprint/13978

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