ABSTRACT. I develop a conceptual framework based on a systematic and comprehensive literature review on algorithmic decision-making in organizations. Building my argument by drawing on data collected from Bright & Company, Corporate Research Forum, Deloitte, Management Events, McKinsey, and Top Employers Institute, I performed analyses and made estimates regarding employees who understand data concepts very well or completely (% of respondents) and challenges to success with data and analytics (asked of those who reported being ineffective at meeting objectives, %). The data for this research were gathered via an online survey questionnaire and were analyzed through structural equation modeling on a sample of 4,600 respondents.
JEL codes: E24; J21; J54; J64

Keywords: algorithmic decision-making; work performance; managerial control

How to cite: Harrower, Kathryn (2019). “Algorithmic Decision-Making in Organizations: Network Data Mining, Measuring and Monitoring Work Performance, and Managerial Control,” Psychosociological Issues in Human Resource Management 7(2): 7–12. doi:10.22381/PIHRM7220191

Received 17 July 2019 • Received in revised form 12 September 2019
Accepted 14 September 2019 • Available online 11 October 2019

Kathryn Harrower
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The Institute of Smart Big Data Analytics,
New York City, NY, USA

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