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MERGERS AND ACQUISITIONS: A QUANTITATIVE APPROACH TO HUMAN RESOURCE MODELING

thesis
posted on 2023-04-18, 20:21 authored by Nikhil ShahNikhil Shah

   

M&A activity is significant in today’s economy, as well as the need for M&A deals to be successful. Human resourcing is a necessary component in executing M&A deals and without it, anticipated growth through expected synergies cannot be achieved. What was particularly sparse in the extant literature of human resources support for M&A was the research into developing a function supporting M&A activities. The purpose of this research was to gather data of previously completed M&A deals at a business to examine if a correlation exists between the available M&A deal data and the number of human resources that were hired for integration. This study used existing data from previous M&A deals to develop a model for predicting the ideal number of human resources required to complete integration activities for future M&A deals. In a case wise diagnostic of the resulting model, 28 of the 31 previous M&A deals were correctly predicted by the model for the needed number of contractors. These findings answered the research question posed by this study, and these resulted in the creation of a multiple regression model with statistically significant coefficients for future M&A deals. A process model was developed and may be useful for businesses, by providing a methodology to leverage its own historical data to predict human resource needs during M&A integrations. This study provided businesses pursuing M&A a quantitative process for intentional planning to ensure that there are dedicated human resources to support the business strategy and outcomes. 

  

History

Degree Type

  • Doctor of Technology

Department

  • Technology Leadership and Innovation

Campus location

  • West Lafayette

Advisor/Supervisor/Committee Chair

Darlene Russ-Eft

Additional Committee Member 2

Linda Naimi

Additional Committee Member 3

Brandon Grant

Additional Committee Member 4

Daniel Boylan

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