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Title: An integrated model to predict M&A decisions
Author: Chui, Bing Sun
ISNI:       0000 0004 6495 9018
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 2017
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Mergers and acquisitions (M&A) are internationally adopted expansion strategies which are imperative to business growth. However, not all M&A are successfully executed nor all post-M&A business expansion have achieved the intended results. Some M&A might have taken place for the wrong reasons. Studies on M&A typically focus on the M&A wave or post-M&A integration. By contrast, this research concentrates on the pre-M&A analysis and planning. Incorporating fuzzy set theory and Monte Carlo simulation, an M&A evaluation and prioritisation model (MAEPM) was established in this study to assist decision makers to implement and execute M&A deals more objectively and effectively, with the aim of maximising the success rate. Risk analysis, fuzzy critical path analysis, cost-benefit evaluation, as well as decision rule and prioritisation were integrated to support the MAEPM development. The success of M&A is highly uncertain and for that reason four risk factors (i.e., schedule, estimation, process, and external risks) were identified and mapped in every task in the M&A process for assessment and management. Time is one of the critical success factors in M&A. To enhance the accuracy of the MAEPM and to ensure effective M&A project delivery, fuzzy critical path analysis was employed to deal with subjective and vague human judgment in M&A project scheduling. The risk-bearing budget percentage and adjusted rate of return were calculated based on the cost-benefit evaluation of the model, particularly including the cost of manpower, which is regarded as the essential and second largest cost in M&A. All of these which form the MAEPM can provide insight into M&A evaluation and serve as indicators. In order to further facilitate firms to screen and select potential M&A projects in an effective manner, decision rule and prioritisation were created in this study as two decision gates to support M&A decision-making. Eleven case studies were conducted to verify the MAEPM. The results from the MAEPM were compared with the actual results of M&A deals made by the case company that confirmed the MAEPM is promising and reliable. By applying the MAEPM, firms can gain insight into the optimistic, normal, and pessimistic scenarios of different M&A deals for better strategic planning, resource allocation, and risk management. This enables firms to select the most ideal M&A deal(s) according to the availability of resources and capital, thus enhancing the success rate of M&A. The subject company, Sage International Group Limited (SAGE), used this tool to reevaluate some of its past M&A cases to better understand their post-M&A issues, and also to objectively and effectively evaluate all its possible future M&A. By using the MAEPM, SAGE not only reduced the turnaround time for each M&A deal screening by one third to more effectively compete for favourable M&A deals, which were less uncertain and had higher value in return, but also substantially reduced pre- and post-M&A costs by around HK$5-10 million annually. Another profound impact on the case company should be the improved chances of success of M&A deals because of the expected values generated. The novel MAEPM is confirmed to be reliable and is an important contribution to the field of M&A. The extension of its applicability is warranted to enable a better understanding of this holistic method of analysis and its impact on M&A deals in other sectors.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: HG Finance