Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/13007
Título: Indicadores econômico-financeiros determinantes de fusões e aquisições: um estudo em empresas de capital aberto do setor de tecnologia no Brasil
Título(s) alternativo(s): Economic and financial determinants in mergers and acquisitions: a study of public firms in the technology sector in Brazil
Autores: Carvalho, Francisval de Melo
Benedicto, Gideon Carvalho de
Campos, Renato Silvério
Martins, Caroline Miriã Fontes
Palavras-chave: Empresas - Fusões e aquisições
Indústria de tecnologia
Regressão logística
Firms - Mergers and acquisitions
Technology industry
Logistic regression
Data do documento: 18-Mai-2017
Editor: Universidade Federal de Lavras
Citação: VIGLIONI, M. T. D. Indicadores econômico-financeiros determinantes de fusões e aquisições: um estudo em empresas de capital aberto do setor de tecnologia no Brasil. 2017. 121 p. Dissertação (Mestrado em Administração)-Universidade Federal de Lavras, Lavras, 2017.
Resumo: The main purpose of this study was to analyze the main economic and financial determinants in mergers and acquisitions in the technology sector in Brazil from the perspective of the acquiring firms. This research is a descriptive exploratory and quantitative analysis using secondary data. To construct the quantitative model, economic and financial indexes were applied representing the independent variables and as dependent variables, the mergers, acquisitions or incorporations accomplished by the technology firms listed in the BM&FBovespa. The data set that composes the economic and financial index was collected from the balance sheet and income statement data base of the Economatica and the BM&FBovespa webpage. The time horizon of the sample is in a series of quarterly data from 2009 to 2015. The data was separated in panel by firms that conducted any process of M&A and by firms that did not perform any mergers and acquisitions. The quantitative model used was logistic regression – logit – which works with binary nomenclature. Firms with any merger, acquisition or incorporation process received the code (1), while those not utilizing any of these strategies received the code (0). The results of the descriptive statistics identified that there was a significant growth of the Brazilian technology sector in recent years. In this context, the most involved sectors in M&A’s were the chemical, software and telecommunications industry. The results of the logistic regression allow the inference that merger and acquisition determinants were found from the perspective of the acquiring firm, the third party equity (CT) and the firm size (TA), each with relevant and positive statistics. Contradictory results, statistically relevant despite negative, were identified The Return on Equity (ROE), the General Liquidity (LG) and the Economic Value Added (EVA). It is observed that the third party equity is an important factor for the firm to finance its activities, while the firm size represents the increase in total firm assets, which may entail benefits such as economies of scale and scope. The increased size of the firm may also represent the acquisition of research and development (R&D) in progress, patents, among other resources. With regard to the negative (ROE), it appears that this may be compensating for the increase in the size of the firm, and for the higher volume of private resources and the third party equity to pay for the M&A. In General Liquidity, the negative sign allows one to infer that firms in the technology sector may be demanding high investments in their activities. Regarding the EVA, the results revealed that there has been a loss of value to shareholders after the M&A. One of the reasons may be related to the period analyzed being insufficient for firms in the technology sector to obtain short-term returns, since intangible assets such as R&D and patents that demand longer terms to generate return and value to the firm.
URI: http://repositorio.ufla.br/jspui/handle/1/13007
Aparece nas coleções:Administração - Mestrado (Dissertação)



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