期刊名称:International Journal of Economics and Financial Issues
电子版ISSN:2146-4138
出版年度:2017
卷号:7
期号:3
页码:62-68
语种:English
出版社:EconJournals
摘要:The company will not easily eliminated if they did right strategy, such as decided to do a corporate action instance expansion. The decision of the company doing the merger increased every year in the period 2010-2013 compared to other mutual policies, such as the rights issue and stock split. The purpose of this research was to analyze the influence of liquidity, leverage and profitability to the possibility of merging the companies listed on the Stock Exchange on the period. This research uses a quantitative approach with secondary data. Using 54 samples, consist of 27 companies that merged and do not merger which categorized using dummy variables. The results of hypothesis testing using a binary logistic regression analysis proves only that profitability that proxy by ROE and leverage that proxy by DER affect the possibility of merger of the company. Keywords: Merger, Profitability, Variable Dummy, Binary Logistic Regression. JEL Classification s : G01,G11,G14,G32,G34
其他摘要:The company will not easily eliminated if they did right strategy, such as decided to do a corporate action instance expansion. The decision of the company doing the merger increased every year in the period 2010-2013 compared to other mutual policies, such as the rights issue and stock split. The purpose of this research was to analyze the influence of liquidity, leverage and profitability to the possibility of merging the companies listed on the Stock Exchange on the period. This research uses a quantitative approach with secondary data. Using 54 samples, consist of 27 companies that merged and do not merger which categorized using dummy variables. The results of hypothesis testing using a binary logistic regression analysis proves only that profitability that proxy by ROE and leverage that proxy by DER affect the possibility of merger of the company. Keywords: Merger, Profitability, Variable Dummy, Binary Logistic Regression. JEL Classification s : G01,G11,G14,G32,G34