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

By Sinan Aral, Erik Brynjolfsson, Lynn Wu. Management Sciences, 2012

304 citations recorded by the source corpus.

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.

Subfields: Organizational Behavior and Human Resource Management, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/6aac8a44850e80855e3c77d3cde3eb3d39a313dc

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Citations in the corpus

An evidence-based review of HR Analytics (2017, methodology): “Providing triangulated evidence for a relationship between business impact and use of HR Analytics established empirically by Aral et al. (2012), 6 non-empirical articles provide illustrative case studies which the authors argue document a positive relationship.”
The Employment Consequences of Robots: Firm-Level Evidence (2020, unknown): “For example, technology can be used to organize and report the output of simple routine tasks and even make predictions about work outcomes (Aral et al. 2012), especially for standardized work where inputs and outputs can be specified and clearly measured (Brynjolfsson and Mitchell 2017).”
Information technology for competitive advantage within logistics and supply chains: A review (2017, background): “have looked into the business value of using IT for supply chain adaptation and co-creation of value (Jing and Zhao, 2014) and related benefits (Aral et al., 2012).”
Advanced Technologies Adoption and Use by U.S. Firms: Evidence from the Annual Business Survey (2020, unknown): “Aral et al. (2012) use survey data collected from customers of a major enterprise resource planning system to look at complementarities between IT, HR analytics and performance pay.”
AI Adoption and System-Wide Change (2021, background): “3 Each decision results in the choice of an action, a k ∈ A k , 1 One interpretation of investment in communication within an organisation is that this is a co-invention that enables AI; see Bresnahan and Greenstein (1996); Bresnahan et al. (2002); Aral et al. (2012); and Dranove et al. (2014).”