research-article

Birds of a Feather Clock Together: A Study of Person-Organization Fit Through Latent Activity Routines

Authors:

Vedant Das Swain,

Manikanta D. Reddy,

Kari Anne Nies,

Munmun De Choudhury,

Gregory D. AbowdAuthors Info & Claims

Proceedings of the ACM on Human-Computer Interaction, Volume 3, Issue CSCW

Article No.: 165, Pages 1 - 30

https://doi.org/10.1145/3359267

Published: 07 November 2019 Publication History

Abstract

Organizations often strive to recruit and retain individuals who would be a "good fit" with their core values, beliefs and practices. Person-Organization (P-O congruence is known to explain employee satisfaction, commitment and absenteeism. This paper proposes a new measure of P-O fit by empirically investigating the similarity of routine within an organization. This measure of routine fit is motivated by the theory of entrainment, which refers to the synchrony of individual and community behaviors. We use unobtrusive bluetooth sensing to examine how the concurrence of latent activity patterns is related to job performance and wellbeing. Routine fit echoes traditional constructs of congruence as it is significantly related to higher task performance and lower workplace deviance. Additionally however, it is also related to greater stress and higher arousal. Prior work in organizational psychology have used single-occasion survey instruments to infer uni-dimensional models of fit. These methods are limited by subjective perceptions of employees. In contrast, we demonstrate a data-driven and multidimensional approach to study normative routines in an organization as a measure of P-O fit. We discuss the potential of our approach in designing technologies that understand the congruence of employee routines and positively impact employee functioning at the workplace.

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Index Terms

Birds of a Feather Clock Together: A Study of Person-Organization Fit Through Latent Activity Routines
1. Applied computing
  1. Law, social and behavioral sciences
    1. Psychology
2. Human-centered computing
  1. Collaborative and social computing
    1. Empirical studies in collaborative and social computing
  2. Ubiquitous and mobile computing
    1. Empirical studies in ubiquitous and mobile computing

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Published In

cover image Proceedings of the ACM on Human-Computer Interaction

Proceedings of the ACM on Human-Computer Interaction Volume 3, Issue CSCW

November 2019

5026 pages

EISSN:2573-0142

DOI:10.1145/3371885

Editors:
Airi Lampinen
Stockholm University, Sweden
,
Darren Gergle
Northwestern University, USA
,
David A. Shamma
FXPAL, USA

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Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 November 2019

Published in PACMHCI Volume 3, Issue CSCW

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Das Swain VSaha K(2024)Teacher, Trainer, Counsel, Spy: How Generative AI can Bridge or Widen the Gaps in Worker-Centric Digital Phenotyping of WellbeingProceedings of the 3rd Annual Meeting of the Symposium on Human-Computer Interaction for Work10.1145/3663384.3663401(1-13)Online publication date: 25-Jun-2024
https://dl.acm.org/doi/10.1145/3663384.3663401
Nepal SHernandez JLewis RChaudhry AHouck BKnudsen ERojas RTankus BPrafullchandra HCzerwinski M(2024)Burnout in Cybersecurity Incident Responders: Exploring the Factors that Light the FireProceedings of the ACM on Human-Computer Interaction10.1145/36373048:CSCW1(1-35)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637304
Woo STay LOswald F(2024)Artificial intelligence, machine learning, and big data: Improvements to the science of people at work and applications to practicePersonnel Psychology10.1111/peps.1264377:4(1387-1402)Online publication date: 4-Mar-2024
https://doi.org/10.1111/peps.12643
Nepal SHernandez JAmores Fernandez JBin Morshed MLewis RPrafullchandra HCzerwinski M(2023)Workplace Rhythm Variability and Emotional Distress in Information WorkersExtended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544549.3585626(1-8)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544549.3585626
Das Swain VGao LWood WMatli SAbowd GDe Choudhury M(2023)Algorithmic Power or Punishment: Information Worker Perspectives on Passive Sensing Enabled AI Phenotyping of Performance and WellbeingProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581376(1-17)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581376
Das Swain VHernandez JHouck BSaha KSuh JChaudhry ACho TGuo WIqbal SCzerwinski M(2023)Focused Time Saves Nine: Evaluating Computer–Assisted Protected Time for Hybrid Information WorkProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581326(1-18)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581326
Das Swain VWilliams SFourney AIqbal S(2022)Two Birds with One Phone: The Role of Mobile Use in the Daily Practices of Remote Information WorkProceedings of the 1st Annual Meeting of the Symposium on Human-Computer Interaction for Work10.1145/3533406.3533416(1-8)Online publication date: 8-Jun-2022
https://dl.acm.org/doi/10.1145/3533406.3533416
Nepal SWang WVojdanovski VHuckins JdaSilva AMeyer MCampbell A(2022)COVID Student Study: A Year in the Life of College Students during the COVID-19 Pandemic Through the Lens of Mobile Phone SensingProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3502043(1-19)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3502043
Booth BHickman LSubburaj STay LWoo SD'Mello S(2021)Bias and Fairness in Multimodal Machine Learning: A Case Study of Automated Video InterviewsProceedings of the 2021 International Conference on Multimodal Interaction10.1145/3462244.3479897(268-277)Online publication date: 18-Oct-2021
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Das Swain VSaha KAbowd GDe Choudhury M(2020)Social Media and Ubiquitous Technologies for Remote Worker Wellbeing and Productivity in a Post-Pandemic World2020 IEEE Second International Conference on Cognitive Machine Intelligence (CogMI)10.1109/CogMI50398.2020.00025(121-130)Online publication date: Oct-2020
https://doi.org/10.1109/CogMI50398.2020.00025

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