Performance indicators of management buyouts using the analytic hierarchy process methodPetra Grah
, Vesna Čančer
, Borut Bratina
, 2018, original scientific article
Abstract: Background and Purpose: In Slovenia, few management buyout (MBO) studies have been carried out. The focus was mostly on the motives for acquisition of companies and the success rate of the acquisitions. This paper aims to analyse the indicators which suggest an impending bankruptcy or financial restructuring of companies and explore how these indicators are different for successful and unsuccessful MBOs.
Methodology: In the survey, we included 23 selected MBOs in Slovenia between 2005 and 2008, using the following financial and non-financial indicators: profitability, performance, solvency and liquidity, using the analytic hierarchy process method. The key aim of the survey was to use financial and non-financial indicators to study if target companies where bankruptcy or financial restructuring has not yet been initiated prevalently have higher aggregate values compared to those in which bankruptcy or financial restructuring procedures have already begun. Thus, we used the selected indicators to demonstrate one of the possible methods to predict the success of a particular MBO.
Results: We found that in most examples of unsuccessful MBOs, target companies have poorer results in terms of performance, solvency and liquidity, when compared to successful MBOs. Based on the selected areas, we divided the results into four quarters. We found that most target companies where MBOs had been unsuccessful are ranked in a lower quarter than most of the target companies where the MBOs had been successful.
Conclusion: The papers main contribution is the finding that the selected financial and non-financial indicators differ in cases of successful and unsuccessful MBOs. This knowledge helps us to find ways of avoiding these situations in the future.
Keywords: management buy-outs, management, bankruptcy models, financial and non-financial indicators, the analytic hierarchy process
Published: 10.10.2018; Views: 286; Downloads: 144
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