@article{MAKHILLIBM20159525958,
    title = {Expert System for Risk Assessment of M&A-Projects},
    journal = {International Business Management},
    volume = {9},
    number = {5},
    pages = {762-770},
    year = {2015},
    issn = {1993-5250},
    doi = {ibm.2015.762.770},
    url = {https://makhillpublications.co/view-article.php?issn=1993-5250&doi=ibm.2015.762.770},
    author = {Mariia,Violetta and},
    keywords = {Russia,metallurgy,Fuzzy logic,fuzzy set,membership functions,rule matrix,linguistic variables,risk,M&A},
    abstract = {The study researches the application of several fuzzy logic concepts to evaluating risk rating of M&A projects undertaken by a large Russian Metallurgic Holding: maxmin compression, fuzzy relationship of preferences, additive compression, linguistic vector estimates. The way of expert answer treatment is presented for the possibility of further fuzzy logic methods application. The 20 M&A projects are used as the empirical basis for the research. The methods applied show consistency in final estimates proving the ability of their use in MA deals’ risk outcomes evaluation. The findings suggest fuzzy logic is a useful tool to evaluating gross risk of M&A projects. The gross risk estimate obtained enables to forecast the outcome of M&A deal, adjust the key financials and make the decision on whether to proceed with the deal or not during the first stage of M&A process. The proposed algorithm of M&A deals gross risk evaluation at OJSC Magnitogorsk Metallurgy Plant has proven its applicability and might be advised for further implementation at industrial enterprises.}
    }