Merger and acquisitions in South African banking: A network DEA model |
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| Affiliation: | 1. COPPEAD Graduate Business School, Federal University of Rio de Janeiro, Rua Paschoal Lemme, 355, 21949-900 Rio de Janeiro, Brazil;2. School of Economics and Decision Science, North West University, Private Bag X2046, Mmabatho 2735, South Africa;3. Department of Economics, University of Pretoria, Pretoria 0002, South Africa;1. Department of Finance, Faculty of Business and Law, Deakin University, 221 Burwood Highway, Burwood, Vic − 3168, Australia;2. School of Business Administration, American University of Sharjah, P.O. Box 26666, Sharjah, United Arab Emirates;3. Blix, 283 Normanby Road, Port Melbourne, Vic − 3207, Australia;1. Department of Banking and Financial Management, University of Piraeus, Greece;2. Department of Economics, University of Pretoria, South Africa;1. Department of Management and Marketing, School of Business, Manhattan College, Riverdale, NY 10471, United States;2. Pamplin School of Business Administration, University of Portland, Portland, OR 97203, United States;3. Department of Operations and Information Management, Isenberg School of Management, University of Massachusetts, Amherst, MA 01003, United States;1. College of Business Administration, Gulf University for Science and Technology, Kuwait;2. Royal Military College of Canada, Canada;3. Mount Royal University, Canada |
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| Abstract: | Banking in South Africa is known for its small number of companies that operate as an oligopoly. This paper presents a strategic fit assessment of mergers and acquisitions (M&A) in South African banks. A network DEA (Data Envelopment Analysis) approach is adopted to compute the impact of contextual variables on several types of efficiency scores of the resulting virtual merged banks: global (merger), technical (learning), harmony (scope), and scale (size) efficiencies. The impact of contextual variables related to the origin of the bank and its type is tested by means of a set of several robust regressions to handle dependent variables bounded in 0 and 1: Tobit, Simplex, and Beta. The results reveal that bank type and origin impact virtual efficiency levels. However, the findings also show that harmony and scale effects are negligible due to the oligopolistic structure of banking in South Africa. |
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| Keywords: | Banks South Africa Merger and acquisitions Network DEA Robust regression analysis |
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