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New network models for the analysis of social contagion in organizations: an introduction to autologistic actor attribute models

New network models for the analysis of social contagion in organizations: an introduction to autologistic actor attribute models

Parker, Andrew, Pallotti, Francesca and Lomi, Alessandro (2021) New network models for the analysis of social contagion in organizations: an introduction to autologistic actor attribute models. Organizational Research Methods, 25 (3). pp. 513-540. ISSN 1094-4281 (Print), 1552-7425 (Online) (doi:https://doi.org/10.1177/10944281211005167)

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Abstract

Autologistic Actor Attribute Models (ALAAMs) provide new analytical opportunities to advance research on how individual attitudes, cognitions, behaviors, and outcomes diffuse through networks of social relations in which individuals in organizations are embedded. ALAAMs add to available statistical models of social contagion the possibility of formulating and testing competing hypotheses about the specific mechanisms that shape
patterns of adoption/diffusion. The main objective of this paper is to provide an introduction and a guide to the specification, estimation, interpretation and evaluation of ALAAMs. Using original data, we demonstrate the value of ALAAMs in an analysis of academic performance and social networks in a class of graduate management students. We find evidence that both high and low performance are contagious, i.e., diffuse through
social contact. However, the contagion mechanisms that contribute to the diffusion of high performance and low performance differ subtly and systematically. Our results help us
identify new questions that ALAAMs allow us to ask, new answers they may be able to provide, and the constraints that need to be relaxed to facilitate their more general adoption
in organizational research.

Item Type: Article
Uncontrolled Keywords: autologistic actor attribute model (ALAAM), individual performance, diffusion, exponential-family random graph models (ERGMs), social contagion, social influence, social networks, statistical models
Subjects: H Social Sciences > H Social Sciences (General)
Faculty / School / Research Centre / Research Group: Faculty of Business
Faculty of Business > Department of International Business & Economics
Faculty of Business > Networks and Urban Systems Centre (NUSC)
Faculty of Business > Networks and Urban Systems Centre (NUSC) > Supply Chain Management Research Group
Last Modified: 15 Jun 2022 11:30
URI: http://gala.gre.ac.uk/id/eprint/31330

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