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Spread of Employee Engagement in a Large Organizational Network: A Longitudinal Analysis

Authors:

Tanushree Mitra,

Michael Muller,

N. Sadat Shami,

Abbas Golestani,

Mikhil MasliAuthors Info & Claims

Proceedings of the ACM on Human-Computer Interaction, Volume 1, Issue CSCW

Article No.: 81, Pages 1 - 20

https://doi.org/10.1145/3134716

Published: 06 December 2017 Publication History

Abstract

Behavioral statescan be transferred to others, leading people to behave in ways similar to those around them. Can this phenomenon of behavioral contagion be seen in the workplace? Using employees' organizational social media data and their workplace hierarchical network structure, we studied contagion across a large multinational corporation, focusing on an important workplace behavior - employee engagement. We measured employees' engagement based on their word choice in organizational social media, and we applied a longitudinal statistical technique which controls for homophily, employees' traits and prior expressions of engagement. We found that engagement and disengagement spread from one employee to another with direct peers exerting the strongest influence. While engagement-spread was more powerful laterally among people at the same organizational level, disengagement-spread followed the vertical managerial chain. Further, we found that disengaged co-workers exerted a stronger influence on employee's future engagement compared to the engaged co-workers. Our results suggest the need for organizations to sense and address workplace disengagement promptly. Moreover, our findings offer opportunities for using workplace interventions to promote engagement and mitigate disengagement.

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Cited By

Kawakami AChowdhary SIqbal SLiao QOlteanu ASuh JSaha K(2023)Sensing Wellbeing in the Workplace, Why and For Whom? Envisioning Impacts with Organizational StakeholdersProceedings of the ACM on Human-Computer Interaction10.1145/36102077:CSCW2(1-33)Online publication date: 4-Oct-2023
https://dl.acm.org/doi/10.1145/3610207
Chowdhary SKawakami AGray MSuh JOlteanu ASaha K(2023)Can Workers Meaningfully Consent to Workplace Wellbeing Technologies?Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency10.1145/3593013.3594023(569-582)Online publication date: 12-Jun-2023
https://dl.acm.org/doi/10.1145/3593013.3594023
Corvite SRoemmich KRosenberg TAndalibi N(2023)Data Subjects' Perspectives on Emotion Artificial Intelligence Use in the Workplace: A Relational Ethics LensProceedings of the ACM on Human-Computer Interaction10.1145/35796007:CSCW1(1-38)Online publication date: 16-Apr-2023
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Index Terms

Spread of Employee Engagement in a Large Organizational Network: A Longitudinal Analysis
1. Human-centered computing
  1. Collaborative and social computing
    1. Empirical studies in collaborative and social computing

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cover image Proceedings of the ACM on Human-Computer Interaction

Proceedings of the ACM on Human-Computer Interaction Volume 1, Issue CSCW

November 2017

2095 pages

EISSN:2573-0142

DOI:10.1145/3171581

Editors:
Clifford Lampe
University of Michigan
,
Jeff Nichols
Google
,
Karrie Karahalios
University of Illinois Urbana-Champaign
,
Geraldine Fitzpatrick
Vienna University of Technology
,
Uichin Lee
KAIST
,
Andres Monroy-Hernandez
Snap Inc.
,
Wolfgang Stuerzlinger
Simon Fraser University

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Published: 06 December 2017

Published in PACMHCI Volume 1, Issue CSCW

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Kawakami AChowdhary SIqbal SLiao QOlteanu ASuh JSaha K(2023)Sensing Wellbeing in the Workplace, Why and For Whom? Envisioning Impacts with Organizational StakeholdersProceedings of the ACM on Human-Computer Interaction10.1145/36102077:CSCW2(1-33)Online publication date: 4-Oct-2023
https://dl.acm.org/doi/10.1145/3610207
Chowdhary SKawakami AGray MSuh JOlteanu ASaha K(2023)Can Workers Meaningfully Consent to Workplace Wellbeing Technologies?Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency10.1145/3593013.3594023(569-582)Online publication date: 12-Jun-2023
https://dl.acm.org/doi/10.1145/3593013.3594023
Corvite SRoemmich KRosenberg TAndalibi N(2023)Data Subjects' Perspectives on Emotion Artificial Intelligence Use in the Workplace: A Relational Ethics LensProceedings of the ACM on Human-Computer Interaction10.1145/35796007:CSCW1(1-38)Online publication date: 16-Apr-2023
https://dl.acm.org/doi/10.1145/3579600
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