A Multisensor Person-Centered Approach to Understand the Role of Daily Activities in Job Performance with Organizational Personas

Author:

Das Swain Vedant1,Saha Koustuv1,Rajvanshy Hemang1,Sirigiri Anusha2,Gregg Julie M.3,Lin Suwen4,Martinez Gonzalo J.4,Mattingly Stephen M.4,Mirjafari Shayan2,Mulukutla Raghu5,Nepal Subigya2,Nies Kari6,Reddy Manikanta D.1,Robles-Granda Pablo4,Campbell Andrew T.2,Chawla Nitesh V.4,D'Mello Sidney3,Dey Anind K.7,Jiang Kaifeng8,Liu Qiang9,Mark Gloria6,Moskal Edward4,Striegel Aaron4,Tay Louis10,Abowd Gregory D.1,De Choudhury Munmun1

Affiliation:

1. Georgia Institute of Technology, USA

2. Dartmouth College, USA

3. University of Colorado Boulder, USA

4. University of Notre Dame, USA

5. Carnegie Mellon University, USA

6. University of California, Irvine, USA

7. University of Washington, USA

8. Ohio State University, USA

9. University of Texas at Austin, USA

10. Purdue University, USA

Abstract

Several psychologists posit that performance is not only a function of personality but also of situational contexts, such as day-level activities. Yet in practice, since only personality assessments are used to infer job performance, they provide a limited perspective by ignoring activity. However, multi-modal sensing has the potential to characterize these daily activities. This paper illustrates how empirically measured activity data complements traditional effects of personality to explain a worker's performance. We leverage sensors in commodity devices to quantify the activity context of 603 information workers. By applying classical clustering methods on this multisensor data, we take a person-centered approach to describe workers in terms of both personality and activity. We encapsulate both these facets into an analytical framework that we call organizational personas. On interpreting these organizational personas we find empirical evidence to support that, independent of a worker's personality, their activity is associated with job performance. While the effects of personality are consistent with the literature, we find that the activity is equally effective in explaining organizational citizenship behavior and is less but significantly effective for task proficiency and deviant behaviors. Specifically, personas that exhibit a daily-activity pattern with fewer location visits, batched phone-use, shorter desk-sessions and longer sleep duration, tend to perform better on all three performance metrics. Organizational personas are a descriptive framework to identify the testable hypotheses that can disentangle the role of malleable aspects like activity in determining the performance of a worker population.

Funder

ODNI, IARPA

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction

Reference110 articles.

1. Activity Recognition API. 2018. https://developers.google.com/location-context/activity-recognition/. (2018). Accessed: 2018-11-01. Activity Recognition API. 2018. https://developers.google.com/location-context/activity-recognition/. (2018). Accessed: 2018-11-01.

2. Manager REST API. 2018. https://docs.gimbal.com/rest.html. (2018). Accessed: 2018-11-01. Manager REST API. 2018. https://docs.gimbal.com/rest.html. (2018). Accessed: 2018-11-01.

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