Return to search

MERGERS AND ACQUISITIONS: A QUANTITATIVE APPROACH TO HUMAN RESOURCE MODELING

<p>   </p>
<p>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. </p>
<p>  </p>

  1. 10.25394/pgs.22654165.v1
Identiferoai:union.ndltd.org:purdue.edu/oai:figshare.com:article/22654165
Date18 April 2023
CreatorsNikhil Shah (15315766)
Source SetsPurdue University
Detected LanguageEnglish
TypeText, Thesis
RightsCC BY 4.0
Relationhttps://figshare.com/articles/thesis/MERGERS_AND_ACQUISITIONS_A_QUANTITATIVE_APPROACH_TO_HUMAN_RESOURCE_MODELING/22654165

Page generated in 0.011 seconds