Date of Conferral
1-1-2011
Degree
Doctor of Business Administration (D.B.A.)
School
Management
Advisor
Roger Mayer
Abstract
Mergers and acquisitions have historically experienced failure rates from 50% to more than 80%. Successful integration of information technology (IT) systems can be the difference between postmerger success or failure. The purpose of this phenomenological study was to explore the entropy phenomenon during postmerger IT integration. To that end, a purposive sample of 14 midlevel and first-line managers in a manufacturing environment was interviewed to understand how the negative effects of entropy affect the ultimate success of the IT integration process. Using the theoretical framework of the process school of thought, interview data were iteratively examined by using keywords, phrases, and concepts; coded into groups and themes; and analyzed to yield results. The data indicated that negative entropy factors were associated with the postmerger integration process. Participants' perception of loss emerged as a central theme for employees from both sides of the merger. A majority of the participants perceived entropy in terms of loss similar to the loss of a family member. The findings may contribute to social change by providing a framework for merger integration managers to mitigate the negative effects of entropy and facilitate a successful IT integration outcome. Successful mergers increase shareholder value and customer satisfaction, which strengthen the company's financial condition. A financially stable company will be in a better position to provide a positive contribution to the surrounding community, offer stable employment opportunities, and sponsor corporate social responsibility programs.
Recommended Citation
Williams, Gloria S., "Entropy in Postmerger and Acquisition Integration from an Information Technology Perspective" (2011). Walden Dissertations and Doctoral Studies. 1038.
https://scholarworks.waldenu.edu/dissertations/1038
Included in
Business Administration, Management, and Operations Commons, Databases and Information Systems Commons, Management Sciences and Quantitative Methods Commons