Cited by 365AI and HR TechnologiesEmployer Branding and e-HRMHuman Resource and Talent Management

Three-Way Complementarities: Performance Pay, Human Resource Analytics, and Information Technology

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Aral, Sinan, Brynjolfsson, Erik, Wu, Lynn·2012·Management Science

Abstract

We test for three-way complementarities among information technology (IT), performance pay, and human resource (HR) analytics practices. We develop a principal–agent model examining how these practices work together as an incentive system that produces a larger productivity premium when the practices are implemented in concert rather than separately. We assess our model by combining fine-grained data on human capital management (HCM) software adoption over 11 years with detailed survey data on incentive systems and HR analytics practices for 189 firms. We find that the adoption of HCM software is greatest in firms that have also adopted performance pay and HR analytics practices. Furthermore, HCM adoption is associated with a large productivity premium when it is implemented as a system of organizational incentives, but has less benefit when adopted in isolation. The system of three-way complements produces disproportionately greater benefits than pairwise interactions, highlighting the importance of including all three complements. Productivity increases significantly when the HCM systems “go live” but not when they are purchased, which can be years earlier. This helps rule out reverse causality as an explanation for our findings. This paper was accepted by Sandra Slaughter, information systems.

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Crossref · 10.1287/mnsc.1110.1460

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  • HR technology facilitates the process of transforming workforce data into information, where executives, HR professionals and line managers can make strategic workforce decisions through its ability to conduct statistical and predictive analysis.

    “Second, HR technology facilitates the process of transforming workforce data into information, where executives, HR professionals and line managers can make strategic workforce decisions through its ability to conduct statistical and predictive analysis (Aral et al., 2012;Fernandez and Gallardo-Gallardo, 2020).”

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Authors
Aral, S., Brynjolfsson, E., & Wu, L.
Affiliations
  • New York University (US)
  • Massachusetts Institute of Technology (US)
Venue
Management Science
Published
2012-05
Volume
58
Issue
5
Pages
913-931
ISSN
  • 0025-1909 (ISSN-L)
  • 1526-5501
OpenAlex
W2132062278
Cited by
365
References
1
Citations by year
2026: 28 · 2025: 39 · 2024: 38 · 2023: 39 · 2022: 35 · 2021: 32 · 2020: 20 · 2019: 23 · 2018: 20 · 2017: 20 · 2016: 23 · 2015: 15 · 2014: 12 · 2013: 14 · 2012: 5
FWCI
29.91
Type
journal article
Language
en
Open access
Licence
cc-by-nc-sa
Locations
  • Management Science (publishedVersion)
  • ScholarlyCommons (University of Pennsylvania) (submittedVersion)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
  • SSRN Electronic Journal
Topics
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Employer Branding and e-HRM
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Human Resource and Talent Management
Keywords
performance-based pay, HR analytics, information technology adoption, principal-agent model, organizational incentives, productivity premium, incentive mechanisms, human resource management

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