Mergers and Acquisitions (M&A) are corporate actions pursued with the intention of achieving significant synergistic gains. They are also often considered a successful component of an expansionary business strategy. However, M&A have higher failure rates and can lead to significant diminution of shareholder wealth. Given the high risk and high reward of M&A, the factors responsible for their high failure rates are worthy of study. In this dissertation, I have identified some of the factors responsible for M&A failures in the global agribusiness industry. These include longer time-to-completion (TTC), possible asymmetric information (AI) in M&A deals, and high competition amongst acquirers. Therefore, in this dissertation, components studies include 1) the determinants of TTC, 2) the value added by financial and/or legal advisory firms to participating companies in an environment of AI, and 3) the profile and characteristics of successful acquirers.The first area, TTC, is highly and directly correlated with the probability of deal failure. However, the literature has not sufficiently addressed the factors that accelerate or delay the deal process. The second area, the role of legal and financial advisory firms, has been effectively analysed in the literature against the backdrop of the risk of adverse selection due to the presence of AI. The literature has also not sufficiently addressed the contribution of advisory services companies in an opaque business environment. Finally, the third area, the profile and characteristics of successful acquirers, has also not been effectively dealt in the literature.However, it is of immense importance from the point of view of potential targets. This dissertation addresses all these three issues with the intent of better understanding the global food and agri-business industry.M&A are a complex business strategy that involves several stakeholders, including acquirers, targets, investment banks, regulators, investors and advisory service firms. The objective function of each stakeholder is different and the strategic action of one stakeholder may impact upon other stakeholders. AI results in longer TTC which results in reduced deal profitability. It should be noted that 90% of the M&As turns our financially nonviable. Therefore, in the current complex economic situation, it is very challenging for the stakeholders to navigate through the M&A process and make it economically profitable for themselves if AI and TTC challenges are nor well understood.This dissertation should make significant contributions to the literature on M&A economics and the stakeholders in the M&A process. For example, the three component essays should be helpful to academic and other stakeholders in identifying the factors that lead to greater likelihood of the success of M&A deals through reduced TTC and mitigated risks of adverse selection and should help to improve understanding on the part of acquirers of the nature and potential for contemporaneous bidders. Practitioners in M&A process will find these results useful due to their practical applicability. For example, the analysis on TTC from the first essay of this dissertation suggests that a target should expect a non-cash deal involving an efficient acquirer to take a longer amount of time. Targets can also use the data to identify potential acquirers. Acquirers might also find the findings of this dissertation helpful in implementing their M&A strategies, navigating environments of AI, and anticipating the TTC of an M&A deal. M&A practitioners, especially financial advisory firms, may find this study helpful.
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