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Three-Way Complementarities: Performance Pay, HR Analytics and Information TechnologySinan AralNew York University (NYU) - Leonard N. Stern School of Business; Massachusetts Institute of Technology (MIT) - Sloan School of Management; New York University (NYU) - Department of Information, Operations, and Management Sciences Erik BrynjolfssonMassachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER) Lynn WuUniversity of Pennsylvania - Operations & Information Management Department; Massachusetts Institute of Technology (MIT) August 25, 2010 Management Science, Forthcoming Abstract: We test for three-way complementarities among information technology (IT), performance pay, and 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.
Number of Pages in PDF File: 33 Keywords: Incentive Systems, Information Technology, Monitoring, Complementarity, Enterprise Systems, ERP, Productivity, Production Function, Principal-Agent Model Accepted Paper SeriesDate posted: August 26, 2010 ; Last revised: February 26, 2013Suggested CitationContact Information
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