The aim of the thesis is to investigate the impact of mergers and acquisitions on the performance of acquirers in the luxury industry by developing an EVA valuation system and to identify factors that influence post-merger performance. The golden era of the merger wave in the luxury industry began around the 1980s, when conglomerates gradually emerged to replace family operations.
Literature Review
- The concept of mergers and acquisitions
- Six M&A waves
- Classification of M&A
- Luxury goods and luxury industry
- Research on M&A motives, measurement and performance
- Theories of M&A Motives
- Research on M&A Performance Measurement Methods
- Research on the influencing factors
This was also closely related to the technology of the textile industry in the United States at this stage. In addition, the tax incentives that M&A can bring are also one of the motivations of M&A.
Empirical Analysis of M&A Performance Based on EVA
Hypotheses Statement
H.2.2: The higher the acquirer's book-to-market ratio in the year before the merger, the better the company's results after the merger. H.2.3: The higher the acquirer's D/E ratio in the year before the merger, the worse the results after the merger. Searching the literature on firm characteristics, the authors found previous analyzes in the literature on the impact of target firm age.
Previous researchers have argued that the age of the target firm has a negative impact on the post-merger. H.2.4: The age of the target company has a negative impact on the acquiring company's post-merger results. The transaction method is also one of the factors that receives attention in connection with M&A performance.
Principle of M&A performance evaluation using EVA
Stock deals represent the M&A firm's perception that its stock is overvalued and cash deals represent the M&A firm's perception that its stock is undervalued. If the acquirer's EVA increases significantly after the M&A, it represents that the shareholders' investment has achieved a higher return as a result of this transaction, the return on capital is higher and the M&A performance is excellent. If there is no change or a negligible increase in the acquirer's EVA after the M&A, this represents that the shareholders' investment paid for the transaction costs and the M&A did not generate abnormal returns, but the overall M&A performance is positive .
If the acquirer's EVA falls after the M&A, it represents a low return on invested capital and destroys shareholder wealth growth, so the M&A result is negative. In EVA, the above expenses are recognized as investments in the company and must be amortized and regulated. After the above accounting adjustments, the formula for calculating NOPAT and invested capital in EVA is changed as follows.
Data and sample
To cope with the possible loss of assets and changes in the business in the future, part of the funds is reserved for possible future situations, resulting in an impairment loss of assets in the current period, which reduces the company's net worth to generate income is underestimated. profits in the current period and cause a reduction in total capital. At the same time, after the economic crisis in the luxury industry, a change from crisis to recovery to a new normal has formed, which can be a reference for the recovery of the luxury industry after COVID-19, so the chosen full time in this dissertation starts on January 1, 2008. Since the luxury industry is a relative concept, the choice of the more detailed classification of the industrial code is beneficial for the author to avoid the problem of overlooking deals as much as possible.
In addition, when the author conducted literature research and industry survey, he noticed the special situation of this industry giant Kering, which had used the name Pinault-Printemps-Redoute (PPR) before 2013 to acquire famous luxury brands Gucci and YSL from the start. as around 1990, but its industry classification was always Retail, so the author added the Retail classification (4522 - Super Stores) for the special case of Kering in the industry review. From the 83 results provided by Zephyr, the author has made further checks, mainly to exclude duplicate transaction data, non-luxury companies, etc. The author classifies these transactions as the same transaction and eliminates 5 transactions based on this criterion, and there are currently 63 transactions that qualify.
Adjusted EVA calculation
- Accounting adjustment for NOPAT and capital employed
- Capital employed calculation
- WACC calculation
- Adjusted EVA calculation result
- Performance change trend analysis
Compared to the year before the M&A, the operating result for the completed year increased significantly. compared to the year before the merger, the operating result in the completed year increased significantly. In the first year after M&A, the number of companies with EVA greater than zero decreased slightly compared to the year of M&A implementation, and the maximum and average values of EVA increased compared to the year of M&A implementation. In the third year after the merger, the number of companies with EVA greater than zero decreased compared to the previous year, and the maximum and minimum values of EVA began to decrease.
Z-value of -2.261 and P-value of 0.024 in the first year after M&A compared to the year before M&A, indicating good operating performance since the first year. In the second year after the merger, the Z-value was -3.168 compared to the year before the merger, and the EVA value tended to increase significantly with a p-value less than 0.05, reaching statistical significance. The operating performance in the third year after the M&A is also higher than that in the year before the M&A and tends to be stable.
Empirical analysis
- Research methodology
- Variable Definitions
- Variable correlation test
- Regression model results
The age (target) The time of establishment of the target company from the year in which the acquisition was completed. R Square represents the degree of explanation of the dependent variable by the independent variables in the regression model. Adjusted R Square eliminates the effect of the number of independent variables and has better accuracy.
Based on the results of the attribution analysis, the authors explain in more detail the influence of each independent variable on EVA. The author argues that this is due to the special nature of the luxury industry, where greater goodwill represents higher social status and social recognition, which will bring luxury companies better post-merger performance. The p-value of TAGE in the year before the merger is greater than 0.10, but it is negligible because the EVA of the acquirer before the merger is not affected by the target company.
Sub-sample analysis
This demonstrates that deals made using cash transactions do not end up with positive post-merger performance. In previous studies, the use of cash payments has often been attributed to the acquirer's belief that its stock is undervalued, but the author argues that the acquirer's manager may be. According to the table above, it is observed that all the models are still statistically significant and according to the Durbin-Watson test, there is no autocorrelation of the independent variables in the models from the pre-merger year to the second post-merger year. .
Based on the increase in R-squared and adjusted R-squared, the five independent variables have stronger explanatory power for the subsample than the full sample. Based on the coefficients of the influencing factors, it can be seen that the relationship between goodwill and assets has a much greater positive impact on the post-merger for giant companies (conglomerates) than for the entire sample. At the same time, the more leveraged the firm is before the merger, the worse the post-merger performance, and the negative correlation is more significant for the sub-sample than for the entire sample.
Main findings and discussion
Managerial implications
In the previous sections of this chapter, an attribution analysis of post-merger performance in the luxury industry was conducted and hypotheses were tested. For investors, the higher the ratio of goodwill to total assets for a luxury company in the year in which the M&A is carried out, the more likely it is to generate positive operating results in later years, making it more investment-worthy, especially for . On the other hand, the higher the debt-to-equity ratio of luxury companies before the implementation of M&A, the greater the possibility of poor performance after M&A, which is not worth investing in.
For luxury acquirers, M&A does generate positive post-merger performance, but the following issues should be noted. Additionally, high pre-M&A leverage may result in negative post-M&A performance. Finally, try to use non-cash payment methods such as shares and earnings or other combinations at the time of transaction.
Limitations and Recommendations
Of course, five years is only a relatively long-term concept, so perhaps in the future, other researchers can expand on the basis of this thesis and extend the research interval to a relatively longer period to explore the effect of M&A on the luxury industry. Examining the impact of M&A on the performance of acquiring firms in the luxury industry is the main question that this thesis attempts to answer. Based on the literature review, the authors propose the main hypotheses of this study and validate the impact of M&A events on the performance of acquiring firms in the luxury industry and the factors affecting the post-merger firms' performance, respectively.
In the attribute analysis, considering the specificity of the luxury industry, the author mainly selects influencing factors through goodwill, market reaction and riskiness. In the empirical results, goodwill to total assets ratio and acquirer age are positively related to post-merger performance, while book-to-market ratio, D/E ratio and cash payout are negatively related to post-merger performance. In conclusion, the findings of this thesis conclusively demonstrate positive post-merger changes in the overall performance of the luxury industry and the main factors influencing M&A in this industry.
Zephyr filter criteria
Adjusted NOPAT calculation result for example
Adjusted NOPAT calculation result
WACC result for all samples