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An Empirical Study On M & A Performance Of Chinese Listed Pharmaceutical Manufacturing Enterprises

Posted on:2019-05-12Degree:MasterType:Thesis
Country:ChinaCandidate:X MaoFull Text:PDF
GTID:2359330566459687Subject:Finance
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In the context of the consumption escalation and the two-child policy,residents' demand for pharmaceuticals continues to increase.these promote the development of pharmaceutical manufacturing.At the same time,it is affected by the reform of the supply side and the reform of the health care system.The development of small and medium-sized pharmaceutical manufacturing companies in China is becoming more and more difficult,For the purpose of seeking development for survival,China's pharmaceutical manufacturing companies have embarked on the road to M&A development.M&A is an important means to optimize resource allocation,achieve economies of scale,and increase economic efficiency in the context of market economy,especially in the context of economic financialization.However,due to the special nature of medical reform involving medical reform and the government's strict control policy,Whether mergers and acquisitions of listed companies in the pharmaceutical manufacturing industry can and can improve industry performance in which areas there is no consensus conclusion.Through a large amount of literature reading,sorting out the latest developments in domestic M & A theory and performance research,The related theories of M & A performance are introduced,the status quo of the development of pharmaceutical manufacturing enterprises in China,the status of listing and M & A,and the types of M & A.Based on the theoretical analysis,the effect of mergers and acquisitions of listed pharmaceutical manufacturing companies that took over in China from 2010 to 2015 was studied.Select the evaluation index from the three aspects of financial status,human resources and innovation ability,set up the performance evaluation index system of listed pharmaceutical manufacturing enterprises.Using factor analysis to reduce the dimension of evaluation index,The clustering method is used to classify the sample data into two types: relatively good and relatively poor M&A performance.Then use the support vector machine model to detect the accuracy of the classification.Analyze the influencing factors of M&A performance,and give suggestions for M&A of pharmaceutical manufacturing companies.The results of empirical research show that,of the 231 listed pharmaceutical manufacturers studied,22 were relatively well-performing in the one-year period after the merger and acquisition,and 209 were relatively poor,with overall performance bias.The results of the study found that the status of human resources,the amount of R&D investment,and whether the M&A parties are related to each other have a significant effect on M&A performance.There are four main reasons leading to the deviation in M&A performance of listed pharmaceutical manufacturing companies in China.First,the huge amount of money spent on mergers and acquisitions has made the company's financial situation tense.Second,M&A companies have insufficient investment in R&D and insufficient innovation.Third,there is no choice of suitable target company that matches its own business,lack of strategic planning before acquisition.Fourth,the integration of resources after mergers and acquisitions is not in place,especially in terms of human resources.Based on the research results,four suggestions for improving the performance of mergers and acquisitions of listed pharmaceutical manufacturing enterprises in China:Expand financing channels for mergers and acquisitions in the pharmaceutical manufacturing industry;Increase the investment in research and development of mergers and acquisitions in pharmaceutical manufacturing companies;Make reasonable M&A decisions to achieve long-term development;Strengthen the effective integration of resources after mergers and acquisitions.
Keywords/Search Tags:Pharmaceutical manufacturing listed company, M&A performance, Factor analysis, Cluster analysis, Support Vector Machines
PDF Full Text Request
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