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THE ANALYSIS OF COMPANIES’ FINANCIAL
PERFORMANCE BEFORE AND AFTER THE
MERGER AND ACQUISITIONS
(A Case Study of Two Companies: Vingroup and FPT)
By
Nguyen Thuy Linh
ID no. 014201100231
A Skripsi presented to the
Faculty of Business President University
in partial fulfillment of the requirements for
Bachelor Degree in Economics Major in Management
February 2015
i
PANEL OF EXAMINERS
APPROVAL SHEET This Panel of Examiners declare that the Skripsi entitled “Analysis of
Companies’ Financial Performance Before and After Merger and
Acquisitions – A Case Study of Two Companies: Vingroup and
FPT” that was submitted by Nguyen Thuy Linh majoring in
Management from the Faculty of Business was assessed and approved
to have passed the Oral Examinations on February 6, 2015.
Liswandi, S. Pd., MM
Chair – Panel of Examiners
Ir. Yunita Ismail Masjud, M. Si.
Examiner I
Vinsensius Jajat Kristanto, SE., MM., MBA.
Examiner II
ii
SKRIPSI ADVISER
RECOMMENDATION LETTER This Skripsi entitled “Analysis of Companies’ Financial
Performance Before and After Merger and Acquisitions – A Case
Study of Two Companies: Vingroup and FPT” prepared and
submitted by Nguyen Thuy Linh in partial fulfillment of the
requirements for the degree of Bachelor of Science in the Faculty of
Business has been reviewed and found to have satisfied the
requirements for a Skripsi fit to be examined. I therefore recommend
this Skripsi for Oral Defense.
Cikarang, Indonesia, January 26, 2015
Acknowledged by, Recommended by,
Vinsensius Jajat Kristanto, SE., MM., MBA. Vinsensius Jajat Kristanto, SE., MM., MBA.
Head, Management Study Program Advisor
iii
DECLARATION OF ORIGINALITY
I declare that this Skripsi, entitled “Analysis of Companies’
Financial Performance Before and After Merger and Acquisitions
– A Case Study of Two Companies: Vingroup and FPT” is, to the
best of my knowledge and belief, an original piece of work that has
not been submitted, either in whole or in part, to another university to
obtain a degree.
Cikarang, Indonesia, January 26, 2015
Nguyen Thuy Linh
iv
ABSTRACT
In this study, the researcher would like to find out how the effect of M&A toward
the company’s performance. As we know merger and acquisition are a
phenomenon and develop not only in Vietnam but also around the world in line
with the development of business world. To find out the answer, the researcher
took two companies that are Vingroup JSC and FPT Corporation in Vietnam from
the year of 2009 until 2013. This study did not include the non-economic factors.
The financial performance of the companies was measured by using the Financial
Ratios but the most focusing ratio is Profitability Ratio. The methodology used in
this study is quantitative research method using secondary data. The analysis of
this research used using Paired Sample T-Test with significance level of 0.05.
The result of Paired Sample T-Test showed that for Vingroup Company there has
no significant different of the financial performance of the company before and
after M&S. For FPT Corporation, there are a significant different of the
company’s financial performance before and after M&A. However, it cannot be
concluded that the reason of the changing is from M&A only. Because M&A is
not the only factors that can affect the financial performances of the companies.
Keywords: Financial Performance, Financial Ratios, Merger and Acquisitions.
v
ACKNOWLEDGEMENT
Certainly, I would have never finishing my skipsi without the help and support of
people around me. These months have been a challenging time for me, with both
happiness and sadness. Luckily, I was not alone on that path, but embraced by
love and help of an extended team of experts that always beside me to push me up
when I thought I could not stand longer. For this, I would like to kindly thank
them.
My most important person throughout all these months was Mr. Vinsensius Jajat
Kristanto SE., MM., MBA.. He is my advisor; he was always ready to find time
for me disregarding his busy schedule. Thank you so much for always being there
for me.
Thanks to Ms. Marien Ann C. Jimenesa and Mr. Orlando R. Santos for helping,
supporting, and advising me in doing this research. Without their help, I could not
finish my thesis as I expected.
Also I would like to say thanks and love to my beloved family for supporting and
taking care of me. Undoubtedly, they deserve a special word of appreciation for
their moral support, patience and love.
I would send special thanks with love to Henry Kadang who always gives me
motivation, help and support me to do things better and better.
The other thanks go to all other friends and people who help me in my process of
conducting this research and beside me during my university’s life.
Today I finished my thesis but it is not the end of the story, it just started a new
adventure of another pages of my life.
Nguyen Thuy Linh
vi
TABLE OF CONTENT
PANEL OF EXAMINERS APPROVAL SHEET ................................................... i
SKRIPSI ADVISER RECOMMENDATION LETTER ........................................ ii
DECLARATION OF ORIGINALITY ................................................................... iii
ABSTRACT ........................................................................................................... iv
ACKNOWLEDGEMENT ...................................................................................... v
TABLE OF CONTENT ......................................................................................... vi
LIST OF TABLES ................................................................................................. ix
LIST OF FIGURES ............................................................................................... xi
LIST OF TERMINOLOGIES ............................................................................... xii
CHAPTER I - INTRODUCTION .......................................................................... 1
1.1. Background of the Study .......................................................................... 1
1.2. Problem Identification .............................................................................. 4
1.3. Statement of the Problem ......................................................................... 4
1.4. Research Objectives ................................................................................. 5
1.5. Definition of Terms .................................................................................. 6
1.6. Scope and Limitations .............................................................................. 8
1.6.1. Scope of the study ............................................................................. 8
1.6.2. Limitation of the study ...................................................................... 9
1.7. Research Benefits ..................................................................................... 9
1.7.1. For Academic Community ................................................................ 9
1.7.2. For companies ................................................................................... 9
1.7.3. For researcher .................................................................................... 9
CHAPTER II - REVIEW OF LITERATURE ...................................................... 10
2.1. Theoretical Review................................................................................. 10
2.1.1. Definition of Merger and Acquisition ............................................. 10
2.1.2. Types of M&A ................................................................................ 12
2.1.3. Motives of Doing M&A .................................................................. 13
2.1.4. Successful and Fail M&A ............................................................... 17
vii
2.2. Previous Research .................................................................................. 22
2.3. Theoretical Framework .......................................................................... 25
2.4. Operational Definition ............................................................................ 26
2.4.1. Current Ratio: .................................................................................. 26
2.4.2. Total Asset Turnover Ratio: ............................................................ 26
2.4.3. Debt Ratio: ...................................................................................... 26
2.4.4. Debt to Equity Ratio: ...................................................................... 26
2.4.5. Net Profit Margin: ........................................................................... 26
2.4.6. Return on Asset: .............................................................................. 26
2.4.7. Return on Equity: ............................................................................ 26
2.4.8. Earnings per Share: ......................................................................... 26
2.5. Hypothesis .............................................................................................. 27
CHAPTER III - RESEARCH METHODOLOGY ............................................... 28
3.1. Research Design ..................................................................................... 28
3.2. Sampling Design .................................................................................... 29
3.3. Research Instrument ............................................................................... 30
3.4. Data Collection Procedure...................................................................... 33
3.5. Hypothesis Testing ................................................................................. 33
3.5.1. Paired Sample T – Test ................................................................... 34
3.5.2. Condition Required for Paired Sample T-Test: .............................. 34
3.5.3. Paired Sample Test Statistic. ........................................................... 35
CHAPTER IV - ANALYSIS AND INTERPRETATION ................................... 36
4.1. Company profile ..................................................................................... 36
4.1.1. Vingroup Joint Stock Company (Vingroup JSC) ........................... 36
4.1.2. FPT Corporation ............................................................................. 37
4.2. Data Analysis ......................................................................................... 38
4.2.1. Overview of the Research Object ................................................... 38
4.2.2. Classical Assumptions: ................................................................... 39
4.3. Result of the paired sample test statistics: .............................................. 57
4.4. Interpretation Analysis: .......................................................................... 66
CHAPTER V - CONCLUSION AND RECOMMENDATION .......................... 68
viii
5.1. Conclusion .............................................................................................. 68
5.2. Recommendation .................................................................................... 71
REFERENCES ..................................................................................................... 73
APPENDICES ...................................................................................................... 76
ix
LIST OF TABLES
Table 4. 1 Normality test for difference of CR - Vingroup .................................. 48
Table 4. 2 Normality test for difference of TATO - Vingroup ............................. 48
Table 4. 3 Normality test for difference of DR - Vingroup .................................. 49
Table 4. 4 Normality test for difference of DER - Vingroup ................................ 49
Table 4. 5 Normality test for difference of NPM - Vingroup ............................... 50
Table 4. 6 Normality test for difference of ROA - Vingroup ............................... 51
Table 4. 7 Normality test for difference of ROE - Vingroup ................................ 51
Table 4. 8 Normality test for difference of EPS - Vingroup ................................. 52
Table 4. 9 Normality test for difference of CR - FPT ........................................... 52
Table 4. 10 Normality test for difference of TATO - FPT ................................... 53
Table 4. 11 Normality test for difference of DR - FPT ........................................ 54
Table 4. 12 Normality test for difference of DER - FPT ...................................... 54
Table 4. 13 Normality test for difference of NPM - FPT ..................................... 55
Table 4. 14 Normality test for difference of ROA - FPT ...................................... 55
Table 4. 15 Normality test for difference of ROE - FPT ...................................... 56
Table 4. 16 Normality test for difference of EPS - FPT ....................................... 57
Table 4. 17 Paired Samples Test for CR of Vingroup .......................................... 58
Table 4. 18 Paired Samples Test for TATO of Vingroup ..................................... 58
Table 4. 19 Paired Samples Test for DR of Vingroup .......................................... 59
Table 4. 20 Paired Samples Test for DER of Vingroup........................................ 59
Table 4. 21 Paired Samples Test for NPM of Vingroup ....................................... 60
Table 4. 22 Paired Samples Test for ROA of Vingroup ....................................... 60
Table 4. 23 Paired Samples Test for ROE of Vingroup........................................ 61
Table 4. 24 Paired Samples Test for EPS of Vingroup ......................................... 61
Table 4. 25 Paired Samples Test for CR of FPT ................................................... 62
Table 4. 26 Paired Samples Test for TATO of FPT ............................................. 62
Table 4. 27 Paired Samples Test for DR of FPT .................................................. 63
Table 4. 28 Paired Samples Test for DER of FPT ................................................ 63
x
Table 4. 29 Paired Samples Test for NPM of FPT ............................................... 64
Table 4. 30 Paired Samples Test for ROA of FPT................................................ 65
Table 4. 31 Paired Samples Test for ROE of FPT ............................................... 65
Table 4. 32 Paired Samples Test for EPS of FPT ................................................ 66
xi
LIST OF FIGURES
Figure 2. 1 Theoretical Framework....................................................................... 25
Figure 3. 1 Research Framework .......................................................................... 33
Figure 4. 1 Box Plot for Difference of CR for Vingroup ...................................... 39
Figure 4. 2 Box Plot for Difference of TATO for Vingroup ................................ 40
Figure 4. 3 Box Plot for Difference of DR for Vingroup ..................................... 40
Figure 4. 4 Box Plot for Difference of DER for Vingroup ................................... 41
Figure 4. 5 Box Plot for Difference of NPM for Vingroup ................................. 41
Figure 4. 6 Box Plot for Difference of ROA for Vingroup................................... 42
Figure 4. 7 Box Plot for Difference of ROE for Vingroup ................................... 42
Figure 4. 8 Box Plot for Difference of EPS for Vingroup .................................... 43
Figure 4. 9 Box Plot for Difference of CR for FPT .............................................. 43
Figure 4. 10 Box Plot for Difference of TATO for FPT ....................................... 44
Figure 4. 11 Box Plot for Difference of DR for FPT ............................................ 44
Figure 4. 12 Box Plot for Difference of DER for FPT ......................................... 45
Figure 4. 13 Box Plot for Difference of NPM for FPT ......................................... 45
Figure 4. 14 Box Plot for Difference of ROA for FPT ......................................... 46
Figure 4. 15 Box Plot for Difference of ROE for FPT ......................................... 46
Figure 4. 16 Box Plot for Difference of EPS for FPT.......................................... 47
xii
LIST OF TERMINOLOGIES
WTO : World Trade Organization
GDP : Gross Domestic Products
FDI : Foreign Direct Investment
M&A : Merger and Acquisitions
CR : Current Ratio
TATO : Total Asset Turnover
DR : Debt Ratio
DER : Debt/Equity Ratio
NPM : Net Profit Margin
ROA : Return on Asset
ROE : Return on Equity
EPS : Earnings per Share
1
CHAPTER I
INTRODUCTION
1.1. Background of the Study
In 2007s, Vietnamese entered a turning point of the country’s Economy when
becoming a member of WTO, this step was to avoid being solitary in the business
world. It is in conformity with the current trend of international trade. Since
Vietnam became a member of WTO, it brought a lot of advantage to the economy
that is Vietnam could have access to latest technological advances for national
modernization and industrialization and the market also became attractive to a lot
of Foreign Companies to enter and invest in Vietnamese market.
After 5 years of joining WTO, Vietnam's Gross Domestic Products (GDP)
increased nearly 2.3 times, and GDP per capita up with over two times. The 5-
year average economic growth rate reached nearly 7 percent; the export turnover
rose by over three times; and Foreign Direct Investment (FDI) had increased. The
number of FDI projects increased 1.5 times registered FDI capital with 5.1 times,
and FDI implemented capital with 3.3 percent over the 2002-2006 period.
(English News: Vietnam's 5-years WTO entry brings opportunities and
challenges, 2012)
Those indexes have proved the advantages of becoming a member of WTO. But
besides the advantage, it also brought a lot of challenges to the domestic
companies in Vietnam. These challenges required the companies in Vietnam to
improve the technology and increase the quality of products and services to be
able to compete with the Foreign Companies and it also requires the companies to
extend the market in order to protect and enhance the position in the market. To
deal with those requirements, the domestic companies tend to merge the smaller
domestic companies that could not survive when they faced the challenges and
that have created trend of merger and acquisitions in Vietnam.
2
In Vietnam, M&A just formed newly and become popular from the year of 2000,
but it just becomes a trend for few years ago. The amount of M&A businesses is
becoming a lot and bigger but in this study, but because of the lacking of the data
and the information, the researcher is going to analyze two M&A business were
implemented from the year of 2000s until 2014 that are valued as the most
remarkable M&A in the period 2011 that has enough data and information that is
needed. Those are the M&A between Vincom Joint Stock Company and Vinpearl
Joint Stock Company become Vingroup Corporation; the second one is the M&A
business of FPT Corporation with three companies are FPT Information System
Joint Stock Company, FPT Trading Joint Stock Company, and FPT Software
Joint Stock Company.
On April 15th
2011, the Board of Directors of FPT Joint Stock Company had
announced the merger of 3 companies: FPT IS, FPT Trading, and FPT Software
into FPT Joint Stock Company.
On October 4th
2011, the Board of Directors of Vincom and Vinpearl Company
had resolutions approved the merger of Vinpearl Company into Vincom
Company. After merger, the shares of Vinpearl Company would be converted
into shares of Vincom. At the same time, Vincom Company would be renamed
into Vietnam Investment Group Joint Stock Company known as Vingroup Joint
Stock Company (Vingroup JSC).
Mergers and Acquisitions are a general term used to refer to the consolidation of
the companies. A merger is a combination of two companies to form a new
company, while an acquisition is the purchase of one company by another in
which no new company is formed. (Investopedia: Merger and Acquisition, 2014)
The reason that companies prefer doing merger and acquisitions as their strategy
is because merger and acquisitions are the fast way to develop their market share
and they can reduce the competitors. Other motivations are related to bargains,
economic scale, economic scope, utilization of unused tax shields, economies of
3
vertical integration, elimination of inefficient, utilization of surplus funds, and
combination of complementary resources.
But besides the benefits of M&A, there are also a lot of challenges that the
companies have to face after M&A that are: HRM issues after integration,
company culture conflict, risks from the acquisition of companies with high
prices, and the burden of bad giant debts.
Whenever the companies decide to choose M&A, they get not only a lot of
benefits but also facing a lot of challenges and when a lot of M&As have been
happening and becoming a trend strategy for companies, a question are proposed
that M&A does effect to the companies’ performance after M&A are
implemented, it is a positive effectiveness or negative effectiveness to the
companies’ performance.
Almost every day, there is a lot of information about M&A that are public on
media. All mention about the companies completed M&A or the forthcoming, the
M&As have fallen through, or the ones that appear to be successful or
unsuccessful and so on. The public and the politicians praise or criticize. The
Anti-Trust-Commission or the Competition Commission makes further additions
to the M&A anxieties. The employees become uneasy and skeptical about their
future. The management of the merging companies defends their M&A decisions.
The stock exchanges react positively or negatively. The fact remains M&A are
always risky endeavors of the management (Ray, 2010). Further they have
become central focus of public and corporate policy issues.
Therefore an analysis has to be made to find out how M&A influence to the
companies’ performance by comparing the financial performance of companies
before and after M&A. To analysis the financial performance, we need to look at
the Financial Ratios which are calculated from Financial Statement of the
companies before and after they did M&A.
By considering the issue of M&A and the curiosity of the civilization about the
successfulness of the M&A, the researchers is interested in conducting research
4
about the effect of M&A to the companies’ performance before and after doing
merger to find out that M&A does affect to the companies’ performance.
In this study, the researcher focused on the Profitability Ratio of the companies.
The reason is because when a company implements M&A, they will look for the
profit of company after M&A. So that is the reason why the researcher chose four
ratios that are NPM, ROA, ROE, and EPS to compare the financial performance
of the company before and after M&A.
1.2. Problem Identification
As mention before, when companies decide to implement M&A, they will get a
lot of benefits that will help the companies develop the market share and they can
reduce the competitor and consolidate their position in the market. But beside the
benefits, they have to face the challenges of M&A, these challenges can hold their
back, push them in troubles and make the M&A fail.
Therefore, the researcher would like to analyze whether there is a significant
different of financial performance caused by the M&As in Vietnam specifically
conducted by two companies that are Vingroup JSC and FPT company by
comparing their financial performance two years before and two years after
merger and acquisitions through the financial ratios of the companies which
includes eight financial ratios: Current Ratio, Total Asset Turnover, Debt Ratio,
Debt/Equity Ratio, Net Profit Margin, Return on Asset, Return on Equity, and
Earning per Share.
1.3. Statement of the Problem
This research is about analyzing the effect of M&A towards companies’
performance before and after M&A. The research decided to study this topic
because the researcher wants to find out whether the M&A effect to the
5
companies’ performance or not and hopefully can recommend practicable
solutions to minimize challenging of M&A. The researcher will evaluate the
financial ratios in order to analyze the company performance and at the end will
answer the following questions:
1. Is there any significant difference in the company performance before and
after M&A on CR?
2. Is there any significant difference in the company performance before and
after M&A on TATO?
3. Is there any significant difference in the company performance before and
after M&A on DR?
4. Is there any significant difference in the company performance before and
after M&A on DER?
5. Is there any significant difference in the company performance before and
after M&A on NPM?
6. Is there any significant difference in the company performance before and
after M&A on ROA?
7. Is there any significant difference in the company performance before and
after M&A on ROE?
8. Is there any significant difference in the company performance before and
after M&A on EPS?
1.4. Research Objectives
This studying is going to find out the effect of M&A to the companies’ financial
performance by analyzing the companies’ financial statement of two years before
M&A comparing with two years after the M&A. To compare the financial
performance, researcher used eight indexes of financial ratios that are CR, TATO,
6
DR, DER, NPM, ROA, ROE, and EPS, those eight indexes fully represent the
four financial ratios that are Liquidity, Activity, Debt Management and
Profitability Ratios so this study can give more insights about M&A to the
company and investors.
1.5. Definition of Terms
Merger: The combining of two or more companies, generally by offering the
stockholders of one company securities in the acquiring company in exchange for
the surrender of their stock.
Acquisition: A corporate action in which a company buys most, if not all, of the
target company's ownership stakes in order to assume control of the target firm.
Acquisitions are often made as part of a company's growth strategy whereby it is
more beneficial to take over an existing firm's operations and niche compared to
expanding on its own. Acquisitions are often paid in cash, the acquiring
company's stock or a combination of both.
Financial Performance: A subjective measure of how well a firm can use assets
from its primary mode of business and generate revenues. This term is also used
as a general measure of a firm's overall financial health over a given period of
time, and can be used to compare similar firms across the same industry or to
compare industries or sectors in aggregation.
Financial Ratios: A financial analysis comparison in which certain financial
statement items are divided by one another to reveal their logical
interrelationships.
Liquidity Ratios: Providing information about a firm's ability to meet its short-
term financial obligations. They are of particular interest to those extending short-
term credit to the firm. Two frequently-used liquidity ratios are the current ratio
(or working capital ratio) and the quick ratio.
7
Current Ratio: The ratio is mainly used to give an idea of the company's ability to
pay back its short-term liabilities (debt and payables) with its short-term assets
(cash, inventory, receivables). The higher the current ratio, the more capable the
company is of paying its obligations.
Activity or Efficiency or Turnover Ratio: Asset turnover ratios indicate of how
efficiently the firm utilizes its assets. They sometimes are referred to as efficiency
ratios, asset utilization ratios, or asset management ratios. Two commonly used
asset turnover ratios are receivables turnover and inventory turnover.
Total Asset Turnover: is a financial ratio that indicates the effectiveness with
which a firm's management uses its assets to generate sales. A relatively high
ratio tends to reflect intensive use of assets. Total asset turnover is calculated by
dividing the firm's annual sales by its total assets. Sales are listed on the firm's
income statement and assets are listed on its balance sheet.
Debt Management or Leverage and Profitability Ratios: providing an indication
of the long-term solvency of the firm. Unlike liquidity ratios that are concerned
with short-term assets and liabilities, financial leverage ratios measure the extent
to which the firm is using long term debt.
Debt Ratio: A financial ratio that measures the extent of a company’s or
consumer’s leverage. The debt ratio is defined as the ratio of total debt to total
assets, expressed in percentage, and can be interpreted as the proportion of a
company’s assets that are financed by debt. The higher this ratio, the more
leveraged the company and the greater its financial risk.
Debt/ Equity Ratio: a measure of a company's financial leverage calculated by
dividing its total liabilities by stockholders' equity. It indicates what proportion of
equity and debt the company is using to finance its assets. A high debt/equity
ratio generally means that a company has been aggressive in financing its growth
with debt. This can result in volatile earnings as a result of the additional interest
expense.
8
Profitability Ratios: A class of financial metrics that are used to assess a
business's ability to generate earnings as compared to its expenses and other
relevant costs incurred during a specific period of time. For most of these ratios,
having a higher value relative to a competitor's ratio or the same ratio from a
previous period is indicative that the company is doing well.
Net Profit Margin: A ratio of profitability calculated as net income divided by
revenues, or net profits divided by sales. It measures how much out of every
dollar of sales a company actually keeps in earnings.
Return on Asset: An indicator of how profitable a company is relative to its total
assets. ROA gives an idea as to how efficient management is at using its assets to
generate earnings. Calculated by dividing a company's annual earnings by its total
assets, ROA is displayed as a percentage. Sometimes this is referred to as "return
on investment".
Return on Equity: The amount of net income returned as a percentage of
shareholders equity. Return on equity measures a corporation's profitability by
revealing how much profit a company generates with the money shareholders
have invested.
Earnings per Share: The portion of a company's profit allocated to each
outstanding share of common stock. Earnings per share serve as an indicator of a
company's profitability.
1.6. Scope and Limitations
1.6.1. Scope of the study
The scope of the study was about the effect of the companies’ performance of two
years before and after M&A through each financial ratio which are CR. TATO,
Debt Ratio, DER, NPM, ROA, ROE and EPS. The Analysis of the effectiveness
is based on the differences between before and after M&A.
9
The researcher chose these ratios because these ratios represent the performance
of the companies and appropriate for analyzing the financial performance. The
research includes the companies which did M&A in period 2011 in Vietnam that
are Vingroup JSC and FPT Company.
1.6.2. Limitation of the study
This study limit only to analyze the performance of the companies that were
Vingroup JSC and FPT Corporation in Vietnam by using the financial ratios
which only included in the economic aspect, meanwhile there were many non-
economic aspects that were not included in this study. Some of the non-economic
aspects are technology, human resources, management culture and many more.
Therefore, this study could not represent the whole aspects of the companies’
financial performance.
1.7. Research Benefits
1.7.1. For Academic Community
Increase and comprehend the study of Investment Analysis and Corporate
Finance especially in corporate action.
1.7.2. For companies
Help the organization to get better understanding of the M&A and its affect to the
companies’ performance so that the next merger will become successful.
1.7.3. For researcher
Improve the knowledge and insights regarding the correlation and relationship
between M&A and companies’ performance.
10
CHAPTER II
REVIEW OF LITERATURE
2.1. Theoretical Review
2.1.1. Definition of Merger and Acquisition
According to Ben McClure, M&A is “One plus one makes three: this equation is
the special alchemy of a merger or an acquisition. The key principle behind
buying a company is to create shareholder value over and above that of the sum
of the two companies. Two companies together are more valuable than two
separate companies - at least, that's the reasoning behind M&A.” (McClure, 2012)
Although they are often uttered in the same breath and used as though they were
synonymous, the terms merger and acquisition mean slightly different things.
When one company takes over another and clearly established itself as the new
owner, the purchase is called an acquisition. From a legal point of view, the target
company ceases to exist, the buyer “swallows” the business and the buyer’s stock
continues to be traded. In the pure sense of the term, a merger happens when two
firms, often of about the same size, agree to go forward as a single new company
rather than remain separately owned and operated. (Dash A. P., 2010, p. 11)
Gaughan defines mergers as “a combination of two corporations in which only
the one corporation survives and the merged corporation goes out of existence”
(Gaughan, 2011, p. 12). Meaning that in a merger, the acquiring company will
become the new owner of the assets and take the liabilities of the merger
company.
Sherman stated that a merger as “a combination of two or more companies in
which the assets and liabilities of the selling firm(s) are absorbed by the buying
firm. Although the buying firm may be a different organization after the merger,
it retains its original identity”. (Sherman, 2010, p. 3)
11
Peng defined a merger as “the combination of assets, operations, and management
of two firms to establish a new legal entity” (Peng, 2009, p. 377)
For acquisition, an acquisition is “to take over ownership of another organization,
firm, company etc.” (Gerry Johnson, Kevan Scholes, and Richard Whittington,
2006, p. 349)
According to Sherman, he defined an acquisition is “the purchase of an asset such
as a plant, a division, or even an entire company” (Sherman, 2010, p. 3) and for
Peng, he defined an acquisition is “the transfer of control of assets, operations,
and management from one firm (target) to another (acquirer)” (Peng, 2009, p.
377)
In generally, the distinctions maybe not that matter, since the result often is
similar; two (or more) companies that in the beginning had separate ownership
are now operating together to achieve some strategic or financial objectives.
However, the strategic, financial, tax, and cultural impact of the deals may be
very different in both.
As important as distinguishing between a merger and an acquisition is, it is also
important to distinguish between a merger and a consolidation which is a business
combination whereby two or more companies join to form an entirely new
company. All of the combining companies are dissolved and only the new entity
continues to operate. In the consolidation, the original companies cease to exist
and their stockholders become stockholders in the new company. Despite the
differences between them, the terms merger and consolidation, as is true of many
of the terms in the mergers and acquisitions field, are sometimes used inter-
changeably. In general, when the combining firms are approximately the same
size, the term of consolidation is applies; when the combining firms have the
different size, merger is the more appropriate term, In practice, however, this
distinction is often blurred, with the term being broadly used for the combinations
that the firms have both different and similar size.
12
Another term used widely in the field of M&A transactions is a takeover. This
term however is vague; sometimes it refers only to hostile transactions, and other
times it could refer to both friendly and unfriendly mergers (Gaughan, 2011). In
mergers of equals, two companies combine in a friendly deal that is a result of
extensive negotiations between the management teams or the owners of both
companies, and particularly between the CEOs of both companies. A merger of
equals is often defined as “the combination of two firms of about the same size to
form a new company” (Colman, Helene Loe, Stensaker, Inger og Tharaldsen,
Jorunn Elise , 2011, p. 19)
2.1.2. Types of M&A
Mergers can be categorized into three different types: the vertical integration
mergers; the horizontal mergers; and the diversification/conglomerate. (Gaughan,
2011, p. 13)
1. Vertical Integration Merger
Vertical Integration Mergers are combinations of companies that have a buyer-
seller relationship or are symbiotically related. (Gaughan, 2011, p. 13) These
mergers happen when organizations that are engaged in related functions but at
different stages in the production process merge with one another.
2. Horizontal Merger
A horizontal merger occurs when two competitors combine. (Gaughan, 2011, p.
13) Or can understand that horizontal mergers occur when organizations
performing similar functions merge to increase the scale of their operations.
Pfeffer (Pfeffer, 1972) argues that horizontal mergers are more likely to occur
among firms located in industries exhibiting intermediate levels of concentration,
meaning situations of maximum intra-industry competition. If a horizontal merger
causes the merged companies to experience an increase in market power that will
have anticompetitive effects, the merger may be opposed on antitrust grounds
(Gaughan, 2011)
13
3. Diversification/conglomerate Merger
Diversification/conglomerate Merger occurs when the companies are not
competitors and do not have a buyer–seller relationship. (Gaughan, 2011, p. 13)
Diversification/conglomerate Merger happens when two firms producing
independent products for different markets. In the other words,
diversification/conglomerate mergers create larger diversified firms, although
these do not generate concerns about market dominance, there are concerns about
their ability to compete unfairly against undiversified competitors because of their
ability to cross-subsidize.
2.1.3. Motives of Doing M&A
The reasons for motivating for M&A are affluent. From achieving economies of
scale, reduce the risks, to satisfy the management and shareholders’ expectation
for growth of company, to get in a new market or segmentation and so on. In this
section, the researcher would like to provide an introduction for different
motivation for mergers.
First of all, the most popular reason for M&A is the expansion and growth.
External expansion is by acquiring a company in the segmentation or
geographical area where the company wants to expand to, this way will be faster
than internal expansion. An expansion might bring some certain synergy benefits,
such as when two lines of business complement one another. Synergy occurs
when the parts is more productive and valuable than the individual components.
Financial factors are also vital when understanding motives for merging. The
value of the acquiring company may be significantly increased in market value
when merged with the targeted company. (Sherman, 2010) (Gaughan, 2011)
14
1. Growth - internal or external
Companies seeking to expand are faced with a choice between internal growth,
organic growth or growth through M&A. Growth through M&A may be much
more rapid than internal growth, since companies may grow within their own
industries or expand outside their business category. Mergers can be an effective
and efficient way to enter a new market, add a new production line, or increase
distribution for a company. If a company seeks to expand within its own industry
it may conclude that internal growth is not an acceptable means of expansion. As
a company grows slowly through internal expansion, competitors may respond
quickly, use a limited window of opportunity, and take market share. Advantages
of a company may disappear over time because of actions of others, and one
solution here may be to acquire another company. In many cases, as shown in the
research presented on merger waves, M&A are driven by a key trend within a
given industry. These key trends affect the question of internal or external
growth. Key trends within an industry can be rapidly changing technology, fierce
competition, changing consumer preferences, pressure on costs control, and a
reduction in demand (Sherman, 2010; Gaughan, 2011).
2. Growth - geographical expansion and internationalization
Another example of using M&A to facilitate growth is when a company wants to
expand to another geographical region. A company could already be a national
company seeking to gain market share in other countries, or seeking market share
in other regions within the same country. Globalization has forced many
companies to explore M&A as a means of developing an international presence
and expanding their market share (Sherman, 2010).
This market penetration strategy is often more cost-effective than e.g. trying to
build an overseas operation from scratch. Therefore, in many instances, it may be
quicker and less risky to expand geographically through M&A than through
internal development. Many deals are therefore driven by the premise that it is
less expensive to buy brand loyalty and customer relationships than it is to build
15
them. This may be particularly true of international growth, where many
characteristics are needed to be successful in a new geographic area. The
company needs to know all of the nuances in the new market, recruit new
personnel, and deal with other hurdles such as language and law barriers. M&A
may therefore be the fastest and lowest risk alternatives. Companies that have
successful products in one national market may see cross border M&A as a way
of achieving greater revenues and profits. And a cross-border deal may enable an
acquirer to utilize the country specific know-how of the target, including its
indigenous staff and distribution network (Sherman, 2010; Gaughan, 2011).
3. Management
Corporate managers are often under constant pressure to demonstrate successful
growth, especially when the company has achieved growth in the past. When the
demand for a company’s products or services slows down, it becomes more
difficult to continue to grow. When this happens, managers often look to M&A as
a way to jump-start growth (Gaughan, 2011). However, managers need to make
sure that the growth will generate returns for both shareholders and the board.
According to Gaughan (2011) there are instances where management may be able
to continue to generate acceptable returns by keeping a company at a given size,
but instead choose to pursue aggressive growth through M&A. Some M&A are
motivated by the need to transform a company’s corporate identity, where the
targeted company may lead the acquiring company in a new direction or add
significantly new capabilities (Sherman, 2010).
Other M&A may be motivated more by a survival strategy from its managers than
by growth. Sometimes companies needs to merge or be acquired in order to
survive and cut costs efficiently (Sherman, 2010). Another management approach
on merger motives is the hubris hypothesis, or the pride of the managers. The
hypotheses implies that manager seek to acquire companies for their own
personal motives, and that economic gains are not the sole motivation or the
primary motivation in the deal (Gaughan, 2011). Improved management could
16
also be a motive in M&A deals. Deals can be motivated by a belief that an
acquiring company’s management can better manage the target’s resources. The
acquirer may believe that its management skills are such that the value of the
acquiring target would rise under its control. Gaughan argues that this improved
management argument may have particular validity in merger cases with large
companies making offers for smaller, entrepreneur led, and growing companies.
The lack of managerial expertise may be a block in a growing company, limiting
its ability to compete in a broader marketplace. Managerial resources are
therefore an asset larger firms can offer the targeted firm. (Gaughan, 2011)
4. Synergies
The key premise of a synergy is that the whole will be greater than the sum of its
parts (Sherman, 2010). The term synergy refers to “the reactions that occur when
two substances or factors combine to produce a greater effect than that which the
sum of the two operating independently could account for” ( (Gaughan, 2011, p.
132). Simply stated, synergy refers to the phenomenon of 2 + 2 = 5. In mergers
this translates into the ability for a corporate combination to be more profitable
than the individual parts of the combined companies. There are two main types of
synergy, operating synergy and financial synergy. The latter refers to the
possibility that combining one or more companies may lower the cost of capital.
Operating synergy comes in two forms; revenue enhancements and cost
reductions. In operating synergy, revenue-enhancing synergies may be more
difficult to achieve than cost reduction synergies (Gaughan, 2011). There are
many potential sources of revenue enhancements, and they may vary from deal to
deal. They may derive from a sharing of market opportunities by cross marketing
each merger partner’s products, they may derive from a company with a major
brand name lending its reputation and status to an upcoming product line of a
merger partner, and they may derive from a company with a strong distribution
network merging with a company that has products with potentials but low ability
to get them to the market before rivals can react. Although the sources for
17
revenue enhancement synergies are great, it is often difficult to achieve.
Enhancements are difficult to quantify and build into valuation models in merger
planning. This is why cost-related synergies are often highlighted in merger
planning, and potential revenue enhancements discussed but not clearly defined.
As merger planners tend to look for cost-reducing synergies, these synergies are
often the main source of operational synergies These cost reductions may be a
result of economies of scale, the decreasing in per unit cost caused by an increase
in the size or scale of a company’s operations, or by the need to spread the risk
and cost of developing new technologies, conduct research, or gaining access to
new sources of energy (Gaughan, 2011) (Sherman, 2010).
2.1.4. Successful and Fail M&A
Based on Hung Wu Chu’s book entitled “the strategic Determinants in The
Success or Failure of Merger and Acquisitions”, the author stated that there are
two techniques to measure: first one is by the perception of the top executive’s
team and second is by comparing financial ratio. Since this studying using the
quantitative method, the researcher will use the financial ratio comparison. There
are four financial ratios that the researcher has mentioned before: Liquidity,
Activity, Leverage, and Profitability Ratios.
2.1.4.1. Liquidity Ratios
Liquidity of a firm is measured by its ability to satisfy its short-term obligation as
they come due. Liquidity refers to the solvency of the firm’s overall financial
position – the ease with which it can pay its bills. Because a common precursor to
financial distress and bankruptcy is low or declining liquidity, these ratios can
provide early signs of cash flow problems and impending business failure.
(Gitman, 2009, p. 58)
18
2.1.4.2. Activity or Efficiency or Turnover Ratios
Activity Ratios measures the speed with which various accounts are converted
into sales or cash- inflow or outflows. With regard to current accounts, measures
of liquidity are generally inadequate because differences in the composition of a
firm’s current assets and current liabilities can significantly affect its “true”
liquidity. IT is therefore important to look beyond measures of overall liquidity
and to assets the activity (liquidity) of specific current accounts. (Gitman, 2009,
p. 59)
2.1.4.3. Debt Management or Leverage Ratios
The debt position of a firm indicates the amount of the other people’s money
being used to generate profits. In general, the financial analyst is most concerned
with long-term debts, because these commit the firm to a stream of contractual
payment over the long run. The more debt a firm has, the greater its risk of being
unable to meet its contractual debt payments. (Gitman, 2009, p. 62)
2.1.4.4. Profitability Ratios
This measure enables analysts to evaluate the firm’s profits with respect to given
level of sales, a certain level of assets, or the owners’ investment. Without profits,
a firm could not attract outside capital. Owners, creditors, and management pay
close attention to boosting profits because of the great importance the market
places on earning. (Gitman, 2009, p. 65)
In this study, the researcher focused on the Profitability Ratios because every firm
is most concerned with its profitability. (Gitman, 2009)
2.1.4.5. Current Ratio
Current Ratio represents the Liquidity Ratios. One of the most commonly cited
financial ratios, measures the firm’s ability to meet its short-term obligations. It is
19
defined as current assets divided by current liabilities and thus represents in ratio
form what net working capital measures by subtracting current liabilities from
current assets. Current assets include cash, current investments, debtors,
inventories (stocks), loan and advance and pre-paid expenses. Current liabilities
represent liabilities that are expected to mature in the next twelve months. These
comprise (i) loans, secured or unsecured, that are due in the next twelve months
and (ii) current liabilities and provisions. Normally, a high current ratio is
considered to be a sign of financial strength. ( John Graham,Scott Smart,William
Megginson, 2008)
2.1.4.6. Total Assets Turnover Ratio (TATO)
Total Asset Turnover Ratio represents the Activity or Efficiency or Turnover
Ratio. Asset Turnover Ratio measures a firm’s efficiency at using its assets in
generating sales or revenue – the higher the number the better. It also indicates
pricing strategy: companies with low profit margins tend to have high assets
turnover, while those with high profit margins have low assets turnover. In the
other words, total asset turnover ratio is the amount of sales generated for every
dollar’s worth of assets. It calculated by dividing sales in dollars by assets in
dollars. (John M. Griffin, Jin Xu, 2009)
2.1.4.7. Debt Ratio
Debt Ratio represents the debt management or leverage ratios. It measures the
proportion of a firm’s total assets that is financed with creditor’s funds. As used
here, the term debt encompassed all short-term liabilities and long-term
borrowing. Bondholders and the other long-term creditors are among those likely
to be interested in a firm’s debt ratio. They tend to prefer a low ratio because it
provides more protection in the event of liquidation or some the other major
financial problem. As the debt ratio increases, so the firm’s fixed – interest
charges. If the debt ratio becomes too high, the cash flow of a firm generates
20
during economic recessions may not be sufficient to meet interest payments.
Thus, a firm’s ability to market new debt obligation when it needs to raise new
funds is crucially affected by the size of the debt ratio and by investors’
perception about the risk implied by the level of ratio. (Moyer, 2008)
2.1.4.8. Debt / Equity Ratio (DER)
Debt/ Equity Ratio represent the Debt Management or Leverage Ratios; it is also
known as DER. Debt to equity capital ratio is computed by dividing total
liabilities by equity capital. Both DER and Debt Ratio are mirror images of the
same capital structure.
Some financial analysts prefer to measure the DER dividing only Long-term
Liabilities by equity capital because current liabilities include accounts payable
and accrued expense that do not strictly represent debt capital as compared to
equity capital. Either definition of DER is acceptable in measuring the overall
degree of dependence on equity capital versus debt capital by a company to fund
its total assets. (Esteban C. Buljevich,Yoon S. Park, 1999)
2.1.4.9. Net Profit Margin (NPM)
Net profit margin represents the profitability ratios. The net profit margin, which
is also called the profit margin on sales, is calculated by dividing net income by
sales. It gives the profit per dollar of sales. Profit margin vary by industry, but all
else being equal, the higher a company’s profit margin compared to its
competitor, the better.
This number is an indication of how effective a company is at cost control. The
higher the net profit margins, the more effective the company is at converting
revenue into actual profit. The net profit margin is a good way of comparing
companies in the same industry, since such companies are generally subject to
similar business conditions. However, the net profit margins are also a good way
to compare companies in the different industries in order to gauge which
21
industries are relatively more profitable, it is also called net margin.
(InvestorWords.com, 2015)
2.1.4.10. Return on Asset (ROA)
ROA tells you what earnings were generated from invested capital (assets). ROA
for public companies can vary substantially and will be highly dependent on the
industry. This is why when using ROA as a comparative measure, it is best to
compare it against a company's previous ROA numbers or the ROA of a similar
company.
The assets of the company are comprised of both debt and equity. Both of these
types of financing are used to fund the operations of the company. The ROA
figure gives investors an idea of how effectively the company is converting the
money it has to invest into net income. The higher the ROA number, the better,
because the company is earning more money on less investment. When you really
think about it, management's most important job is to make wise choices in
allocating its resources. Anybody can make a profit by throwing a ton of money
at a problem, but very few managers excel at making large profits with little
investment. (Investopedia: Return on Asset, 2015)
2.1.4.11. Return on Equity (ROE)
The ROE is useful for comparing the profitability of a company to that of other
firms in the same industry.
There are several variations on the formula that investors may use:
1. Investors wishing to see the return on common equity may modify the
formula above by subtracting preferred dividends from net income and
subtracting preferred equity from shareholders' equity, giving the
following: return on common equity (ROCE) = net income - preferred
dividends / common equity.
22
2. Return on equity may also be calculated by dividing net income by
average shareholders' equity. Average shareholders' equity is calculated by
adding the shareholders' equity at the beginning of a period to the
shareholders' equity at period's end and dividing the result by two.
3. Investors may also calculate the change in ROE for a period by first using
the shareholders' equity figure from the beginning of a period as a
denominator to determine the beginning ROE. Then, the end-of-period
shareholders' equity can be used as the denominator to determine the
ending ROE. Calculating both beginning and ending ROEs allows an
investor to determine the change in profitability over the period.
(Investopedia: Return on Equity, 2015)
2.1.4.12. Earnings per Share (EPS)
Basic Earnings per Share are reported on a corporation's income statement
directly below net income. Preferred dividends are removed from this calculation
because basic earnings per share consist of only the earnings available to common
stockholders. The preferred dividends are dividends on noncumulative preferred
stock that have been declared and the current dividends on cumulative preferred
stock whether or not they have been declared. (Loren Nikolai, John Bazley,
Jefferson Jones, 2010)
2.2. Previous Research
The research was conducted by Tajalli Fatima1 and Amir Shehzad in the Journal
of Poverty, Investment and Development Vol.5 2014 entitled “An Analysis of
Impact of Merger and Acquisition of Financial Performance of Companies:
A case of Pakistan”. This study aimed to analyze the impact of M&A of
Companies and provide insights about their role after M&A on Companies’
profitability. This research studied the impact of merger and acquisition of
23
Companies and provides insights about their role after merger on Companies
profitability. In this paper, six financial ratios were used for analysis these ratios
are profit after tax, return on asset, return on equity, debt to equity ratio, deposit
to equity ratio and EPS. Ten Companies were selected as sample for analysis
which got into merger from 2007-10. 3 year pre-merger and 3 year post-merger
data points were taken for all the 10 cases and their averages were compared.
SPSS is used for statistical analysis. The data is collected from the KSE listed
companies which are merger from 2007 to 2010. Through internet they got the
audited annual reports of the companies. The total mergers from 2007 to onwards
were 15 but they selected 10 cases due to the limitation of data availability
applied on this sampling. From the result of the analysis, only ROE was affected
by the M&A and other ratios have no impact from this strategy.
Another research was also conducted by Sarah Indriyani Sijabat together with
Azhar Maksum in Journal Accountancy 16 entitled “Analysis of Finance
Performance before and after merger and acquisitions on the companies
listed in Indonesia Stock Exchange”. The research aimed to give an empirical
evidences about the difference of company’s performance, bidding firms and
target firms, before and after the event of merger and acquisitions which showed
by financial ratios. The population in this study were all the go public companies
except kind of banking and other financing doing M&A of 2001 – 205. Using the
technique of purposive sampling, finally, it was gained 30 companies as the
sample of the study which consisted of 16 as bidding firms and 14 as target firms.
In the study, test of data using statistical analyze consist of analyze of
Kolmogorov-Sminorov, Wilcoxon Signed Ranks Test and Paired Sample T-Test.
The result of the analysis showed that there were no significant differences in
financial ratios in target firms like CR, QR and TATO indicate that there were
different significant but temporary and not consistent. From the result of the
analysis, it could be concluded that the M&A has no effect to the performance for
bidding firms and target firms. Concluded that economy aims of merger and
acquisition could not be achieved.
24
The other research is Timo Rene Göhlich also conducted a thesis regarding this
issue in 2007 with the title “The Performance Effects of Mergers within the
German Cooperative Banking Sector”, in this study, the objective is to find out
the performance effects of merger within the German cooperative banking sector
on the basis of agency, synergy and market power related changes by comparing
the company’s performance before and after Merger and Acquisitions. In this
study, the researcher used the data of the cooperative banking sector in Germany
within the year 2007 and 2008. The methods are used in this study are: the first
test, a sign-test for matched pairs, is used to test the impact of the bank merger on
the various ratios, or in other words, to test whether the median of the differences
of pre- and post-merger values is zero. Non-parametric analyses are not affected
by outliers and do not rely on the nearly normal condition. Afterwards, a paired t-
test (two-tailed) is conducted to test for differences between pre- and post-merger
means. the answer to the main research questions is that there is no significant
change in performance following a merger in the cooperative banking sector,
although it is possible to reduce interest expenditures (IE/IBL, IE/TA) facilitated
by scale synergies (H2) or an increase in market power (H3). The expected
performance change is hampered by a decrease in personnel efficiency (H2).
Further, it is possible to benefit from an increase in market power in the area of
other operating income (H3). This thesis contributes to the current M&A research
in three ways: First, it focuses on the cooperative banking sector that is far less
well investigated than the commercial banking due to missing public data. The
change has not only been analyzed in broad overall terms, but also in terms of
more detailed accounting ratios. Secondly, the validity of the synergy theory and
the market power theory is supported in a cooperative market context and
problems with synergy gains in the area of personnel costs are discovered.
Thirdly, it has been described that strategic similarities and size differences do not
influence performance changes. Instead differences in the area of other operating
revenues are found to be performance enhancing.
Along with the previous study, the researcher would like to analysis the financial
performance of the company with a differentiation by computing the financial
25
ratios based on the quarter financial report of the companies six quarters before
merger and acquisitions and six quarters after merger and acquisitions of the
manufacturing and services companies only from the HOSE (Ho Chi Minh Stock
Exchange), while the statistic use in this research using the paired Sample T-Test
with95% confidence of interval.
2.3. Theoretical Framework
The successfulness of a company in doing M&A can be seen from its
performance, especially the financial performance, which is reflected in the
financial ratio that can be gotten by some calculation from the financial statement.
The financial ratios used in this study were the most suitable ratios regarding
measuring financial performance.
In this study, the research compares the financial ratios two year before M&A and
two years after M&A of two companies that are Vingroup JSC and FPT
Corporation. Below is the theoretical framework of this study:
Figure 2. 1 Theoretical Framework
26
2.4. Operational Definition
2.4.1. Current Ratio:
An indication of a company's ability to meet short-term debt obligations; the
higher the ratio, the more liquid the company is.
2.4.2. Total Asset Turnover Ratio:
This ratio shows how efficiently a company can use its assets to generate sales.
2.4.3. Debt Ratio:
The debt ratio shows a company's ability to pay off its liabilities with its assets. In
other words, this shows how many assets the company must sell in order to pay
off all of its liabilities.
2.4.4. Debt to Equity Ratio:
The debt to equity ratio shows the percentage of company financing that comes
from creditors and investors.
2.4.5. Net Profit Margin:
It shows how good a company is at converting revenue into profits available for
shareholders.
2.4.6. Return on Asset:
It measures how efficiently a company can manage its assets to produce profits
during a period.
2.4.7. Return on Equity:
It shows how much profit each dollar of common stockholders' equity generates.
2.4.8. Earnings per Share:
This is the amount of money each share of stock would receive if all of the profits
were distributed to the outstanding shares at the end of the year.
27
2.5. Hypothesis
Based on the problem statement, there are 8 variables will be tested:
H01: (There is no significant difference between CR before and CR
after M&A)
H02: (There is no significant difference between TATO before and
TATO after M&A)
H03: (There is no significant difference between DR before and DR
after M&A)
H04: (There is no significant difference between DER before and DER
after M&A)
H05: (There is no significant difference NPM before and NPM after
M&A)
H06: (There is no significant difference ROA before and ROA after
M&A)
H07: (There is no significant difference ROE before and ROE after
M&A)
H08: (There is no significant difference EPS before and EPS after
M&A)
28
CHAPTER III
RESEARCH METHODOLOGY
This chapter present the research methods and procedures that are conducted by
the researcher in the process of investigating, sampling design and selection of
respondents, also the procedures in gathering the data and how it is been treated
by statistical application.
3.1. Research Design
There are two methods in doing scientific research those are qualitative and
quantitative research. The differences between qualitative and quantitative
research are the type of data, research process, instrument in collecting data and
the purpose of research.
Qualitative research is type of formative research that includes specialized
techniques for obtaining in-depth responses about what people think and how
they feel. It is seen as the research that seeks answer to the questions in the real
world. Qualitative researchers gather what they see, hear, read from people and
places, from events and activities, with the purpose to learn about the community
and to generate new understanding that can be used by the social world.
Qualitative research has often been conducted to answer the question “why”
rather than “what”. A purpose of qualitative research is the construction of new
understanding. (Amol R Dongre, Pradeep R Deshmukh, Ganapathy Kalaiselvan,
and Sanjeev Upadhyaya., 2009)
Quantitative research is typically considered to be the more “scientific” approach
to doing social science. The focus is on using specific definitions and carefully
operationalizing what particular concepts and variables mean. Qualitative
research methods provide more emphasis on interpretation and providing
29
consumers with complete views, looking at contexts, environmental immersions
and a depth of understanding of concepts. (Tewksbury, 2009)
Quantitative research, on the other hand, is focused on testing the strength and
persistence of relationships between distinct measures. Specifying exactly how
two (or more) very narrow, limited concepts/variables is of value, but often of
value only for very exact measurements of narrowly defined issues, concepts and
variables. As such, quantitative research relies on the ways that researchers
choose to have variables defined, and what they elect to include within the scope
of the definition of variables.
In this research uses quantitative research methodology that has the major
objective to know the company’s financial performance after doing M&A. For
this particular research, quantitative research method is preferred by the
researcher due to its main purpose for measurement.
Researcher chooses quantitative research because quantitative research can
provide specific facts that decision makers can use to (1) make accurate
prediction about the relationship between market factors and behaviors, (2) gain
meaningful insights into those relationships, (3) validate the existing relationship,
and (4) test various types of hypotheses (Joseph F. Hair, Robert P. Bush, and
David J. Ortinau, 2006). In addition, quantitative research uses data that are
structured in the form of numbers or that can be immediately transported into
numbers. It is a very controlled, exact approach to research.
3.2. Sampling Design
The researcher uses the purposive sampling with the criteria: population of
manufacturing and services companies which did M&A in the period 2012 listed
in the HOSE and have the quarters’ financial reports. Sample is the whole
population which includes two companies: Vingroup Joint Stock Company
(Vingroup JSC) and FPT Corporation.
30
1. Vingroup Joint Stock Company (Vingroup JSC), formerly known as
Technocom, was founded in Ukraine in 1993 by an ambitious group of
Vietnamese youths. Technocom began with food production and quickly
found great success with the Mivina brand. During the early years of the
21st century, Technocom was ranked among Ukraine’s Top 100 largest
and most influential companies. In 2000, Technocom - Vingroup returned
to Vietnam with ambition to contribute the country’s development.
Emphasizing sustainable long-term development, Vingroup initially
focused investments on real estate and hospitality through two key brands,
Vincom and Vinpearl.
2. FPT Corporation was founded on September 13rd
, 1988. For almost 26
years of development, FPT has always been the leading ICT Company in
Vietnam with the revenue of more than VND 28,647 billion, equivalent to
nearly USD 1.36 billion, creating more than 17,000 jobs for the society.
The company’s market capitalization (as of Feb 28 2014) reached VND
17,608 billion, being one of the largest private enterprises in Vietnam
(ranked by Vietnam Report 500). FPT conducts the core businesses in the
fields of information technology and telecommunications.
3.3. Research Instrument
In this research, researcher use secondary data as source of data. According to
Guffey and Loewy (2009P), secondary data come from reading what others have
experienced and observed. Secondary data are easier and cheaper to develop than
a primary data, which might involve interviewing large group or sending out
questionnaires. The resources of secondary data are within the firms, business
database services, government agencies, industry associations, special-interest
organizations and internet. The secondary data in this study is collected from the
financial statements which include income statement and balance sheet published
by the companies listed by the companies listed in Vietnamese Stock Exchange
31
and the financial ratio of companies that were provided on VietStock website
official. The researcher also uses some books and journals while completing this
study in order to support the theory, data or information.
The formulas of Financial Ratios are used in this study are explained below:
1. CR: represents the Liquidity Ratios. CR is one of the most common cited
financial ratios, measure the firm’s ability to meet its short-term
obligations.
2. TATO: represents the Activity Ratios. TATO measures a firm’s efficiency
at using its assets in generating sales or revenue – the higher number the
better
3. DR: represents the debt management or leverage ratios. Debt Ratio
measures the proportion of a firm’s total assets that is financed with
creditor’s funds.
4. DER: represent the Debt Management or Leverage Ratios. DER is
computed by dividing total liabilities by equity capital.
32
5. NPM: represents the profitability ratios. NPM is also called Profit Margin
in sales; it is calculated by diving net income by sales. It gives the profit
per dollar of sales.
6. ROA: represents the Profitability Ratios. ROA is an indicator of how
profitable a company is relative to its total assets.
7. ROE: represents profitability Ratios. ROE indicates the accounting rate of
return on the stockholders’ investment, as measured by net income
relative to common equity.
( )
8. EPS: is generally of interest to present or prospective stockholders and
management. EPS represents the number of dollars earned during the
period on behalf of each outstanding share of common stock.
33
3.4. Data Collection Procedure
The data used in this research are financial statement of the Companies to
calculate the Financial Ratio. To be clearer, the data that are used in this research
are stated as follow:
1. Financial Report Quarterly of from 2009 until 2013 for Vingroup JSC.
2. Financial Report Quarterly of from 2009 until 2013 for FPT Corporation.
In conducting this research, the researcher followed this below procedure to
collect the data for the research.
The financial reports of companies are taken from the official website of
Vietstock (http://finance.vietstock.vn/)
3.5. Hypothesis Testing
This part the researcher presents the statistical techniques were used to prove the
hypothesis that was mentioned in Chapter 2. The research will use the T-test and
SPSS 22.0 software for windows.
Figure 3. 1 Research Framework
34
3.5.1. Paired Sample T – Test
A paired sample t-test is used to determine whether there is a significant
difference between the average values of the same measurement made under two
different conditions. Both measurements are made on each unit in a sample, and
the test is based on the paired differences between these two values. The usual
null hypothesis is that the difference in the mean values is zero. (The Statistic
Glossary: Paired Sapmle t-test, 2015)
A pair sample T-test will be undertaken to prove whether there are any
significance differences or not between before and after M&A by comparing the
financial ratios which are Current Ratio, Total Asset Turnover, Debt Ratio, Debt
to Equity Ratio, Net Profit Margin, Return on Asset, Return on Equity , Earning
per Share.
3.5.2. Condition Required for Paired Sample T-Test:
Assumptions:
Assumption 1: Dependent variable should be measured on a continuous scale.
Assumption 2: Independent variable should consist of two categorical, "related
groups" or "matched pairs".
Assumption 3: There should be no significant outliers in the differences between
the two related groups.
Assumption 4: The distribution of the differences in the dependent variable
between the two related groups should be approximately normally distributed.
(statistic laerd: Paired t-test using Minitab, 2015)
35
3.5.3. Paired Sample Test Statistic.
1. Paired Sample Test Statistic
Test Statistic:
√
Sample Mean Sample Standard Deviation
∑
√
∑ ( )
2. Hypotheses
: (there is no significant difference before and after merger)
: (there is significant difference before and after merger)
3. Level of significance:
( )
4. and
= 2.365 (from the T- table)
= ∑
Sources: (Douglas C. Montgomery and George C.Runger, 2003)
5. Decision and Conclusion
Reject means there is significant difference before and after merger.
Do not reject means there is no significant difference before and after
merger.
36
CHAPTER IV
ANALYSIS AND INTERPRETATION
4.1. Company profile
4.1.1. Vingroup Joint Stock Company (Vingroup JSC)
Vingroup Joint Stock Company (Vingroup JSC), formerly known as Technocom,
was founded in Ukraine in 1993 by an ambitious group of Vietnamese youths.
Technocom began with food production and quickly found great success with the
Mivina brand. During the early years of the 21st century, Technocom was ranked
among Ukraine’s Top 100 largest and most influential companies. In 2000,
Technocom - Vingroup returned to Vietnam with ambition to contribute the
country’s development.
Emphasizing sustainable long-term development, Vingroup initially focused
investments on real estate and hospitality through two key brands, Vincom and
Vinpearl. Ten years of hard work and dedication turned Vincom into one of
Vietnam’s premier real estate brands with a number of mixed-used developments
in major cities, combining modern shopping malls, offices and luxury apartments
in a single complex, leading the trend towards smart, eco-luxury urban projects in
Vietnam. Alongside Vincom and Vinpearl has also become the leader in
Vietnam’s tourism industry, featuring international 5-star and above hotels,
resorts, beach villas, amusement parks and golf courses.
In January 2012, Vinpearl JSC merged into Vincom JSC to form Vingroup JSC.
The new structure ensures sustained development and allows Vingroup to focus
on developing its strategic brands:
1. Vinhomes (Luxury serviced apartments and villas)
2. Vincom (Premium shopping malls)
37
3. Vinpearl (Hotels & Resorts)
4. Vinpearl Land (Entertainment)
5. Vinmec (Healthcare services)
6. Vinschool (Education)
7. VinEcom (E-commerce)
8. Vincom Office (Offices for lease)
9. Vinmart (Supermarket)
10. Vinfashion (Fashion)
11. Vincharm (Fitness and beauty care)
12. Almaz (The International Cuisine & Convention Center)
Vingroup continues to pioneer and lead consumer trends in each of its businesses
introducing Vietnamese consumers to a brand new, modern life-style with
international-standard products and services. Vingroup has created a respected,
well-recognized Vietnamese brand and is proud to be one of the nation’s leading
private enterprises.
With these achievements, Vingroup is recognized as one of the most dynamic,
successful, well-capitalized companies in Vietnam, well-positioned for
international integration and comparable to the best regional and global peers.
4.1.2. FPT Corporation
FPT Corporation was founded on September 13rd
, 1988. For almost 26 years of
development, FPT has always been the leading ICT Company in Vietnam with
the revenue of more than VND 28,647 billion, equivalent to nearly USD 1.36
billion, creating more than 17,000 jobs for the society. The company’s market
38
capitalization (as of Feb 28 2014) reached VND 17,608 billion, being one of the
largest private enterprises in Vietnam (ranked by Vietnam Report 500).
FPT conducts the core businesses in the fields of information technology and
telecommunications, FPT has been providing services to fifty seven out of sixty
three cities and provinces of Vietnam and continued expanding its business to the
global market. FPT has had clients or opened representative offices and
companies in 17 countries including Vietnam, Laos, Cambodia, America, Japan,
Singapore, Germany, Myanmar, France, Malaysia, Australia, Thailand, United
Kingdom, Philippines, Kuwait, Bangladesh and Indonesia.
FPT has intensive experience of establishing and implementing large scale
business models. After nearly twenty six years, FPT is now the No. 1 company in
Vietnam specializing in Software Development, System Integration, IT Services,
Distribution and Manufacturing of IT products, and Retails. In
telecommunications area, FPT is one of three biggest Internet services providers
in Vietnam. In regard to content development, FPT is now the No. 1 online
advertising company in Vietnam, owning an e-newspaper with more than 42
million page views per day, which is equal to the number of Internet users in
Vietnam.
4.2. Data Analysis
4.2.1. Overview of the Research Object
Research object used in this research is two companies have implemented in the
period 2011 and are listed on the HOSE (Ho Chi Minh Stock Exchange). From
the criteria given, there are two companies are being researched that are Vingroup
JSC and FPT Corporation.
The financial statements per quarter are used in this research are obtained from
companies’ quarter report, and some ratios were taken from VietStock official
39
website. The other financial ratios are calculated by the researcher based on the
Financial Ratios’ Formula form Principle of Manager Finance Book.
4.2.2. Classical Assumptions:
4.2.2.1. Result of Outliners:
An outlier is an observation that lies an abnormal distance from other values in a
random sample from a population. In a sense, this definition leaves it up to the
analyst (or a consensus process) to decide what will be considered abnormal.
Before abnormal observations can be singled out, it is necessary to characterize
normal observations. (Engineering Statistics Handbook: What are outliners in the
data?, 2015)
The Box plot displays the three quartiles, the minimum, and the maximum of the
data on a rectangular box, aligned either horizontally or vertically. The box
encloses the interquartile range with the left of lower edge at the first quartile and
the right (or lower) edge at the third quartile. A line is drawn through the box at
the second quartile. A line, or whisker, extends from each end of the box. A point
beyond a whisker, but less than 3 interquartile ranges from the box edge, is called
an outliner. (Douglas C. Montgomery and George C.Runger, 2003)
Vingroup JSC:
The difference between before and after merger of CR:
Figure 4. 1 Box Plot for Difference of CR for Vingroup
(Sources: SPSS Data result by SPSS v.22.0)
40
Figure 4. 3 Box Plot for Difference of DR for Vingroup
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are CR before and after M&A.
The difference between before and after merger of TATO:
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are TATO before and after
M&A.
The difference between before and after merger of DR:
Figure 4. 2 Box Plot for Difference of TATO for Vingroup
41
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are DR before and after M&A.
The difference between before and after merger of DER:
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are DER before and after M&A.
The difference between before and after merger of NPM:
Figure 4. 4 Box Plot for Difference of DER for Vingroup
Figure 4. 5 Box Plot for Difference of NPM for Vingroup
42
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are NPM before and after M&A.
The difference between before and after merger of ROA:
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are ROA before and after M&A.
The difference between before and after merger of ROE:
Figure 4. 6 Box Plot for Difference of ROA for Vingroup
Figure 4. 7 Box Plot for Difference of ROE for Vingroup
43
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are ROE before and after M&A.
The difference between before and after merger of EPS:
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are EPS before and after M&A.
FPT Corporation:
The difference between before and after merger of CR:
Figure 4. 8 Box Plot for Difference of EPS for Vingroup
Figure 4. 9 Box Plot for Difference of CR for FPT
44
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are CR before and after M&A.
The difference between before and after merger of TATO:
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are TATO before and after
M&A.
The difference between before and after merger of DR:
Figure 4. 10 Box Plot for Difference of TATO for FPT
Figure 4. 11 Box Plot for Difference of DR for FPT
45
Figure 4. 13 Box Plot for Difference of NPM for FPT
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are DR before and after M&A.
The difference between before and after merger of DER:
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are DER before and after M&A.
The difference between before and after merger of NPM:
Figure 4. 12 Box Plot for Difference of DER for FPT
46
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are NPM before and after M&A.
The difference between before and after merger of ROA:
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are ROA before and after M&A.
The difference between before and after merger of ROE:
Figure 4. 14 Box Plot for Difference of ROA for FPT
Figure 4. 15 Box Plot for Difference of ROE for FPT
47
(Sources: SPSS Data result by SPSS v.22.0)
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are ROE before and after M&A.
The difference between before and after merger of EPS:
The figures above show that do not have any point beyond a whisker but less than
3 interquartile ranges from the box edge. It means there is no significant outliner
in the differences between two related group that are CR before and after M&A.
4.2.2.2. Result of the normal distribution test:
The two main tests to test the normal distribution are: Kolmogorov-Smirnoff (K-
S) and Shapiro-Wilks (S-W).
These tests compare the set of scores in a sample to a normally distributed set of
scores with the same mean and standard deviation. If the test is non-significant (ie
p>0.05) then this shows that the data set is not significantly different from a
normal distribution ie the data is normally distributed. If however the test statistic
is significant (ie p <0.05) then the data is not normally distributed. Like all
statistical tests the power of these tests depends on the sample size, and in the test
carried out below SPSS automatically quotes the S-W statistic when the sample
size is less than 100. (Storey, 2014)
Figure 4. 16 Box Plot for Difference of EPS for FPT
48
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
Vingroup JSC:
The difference between before and after merger of CR:
Table 4. 1 Normality test for difference of CR - Vingroup
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
DIFF_CR .194 8 .200* .935 8 .565
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
the Shapiro-Wilk Test (appropriate for samples up to 100 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
As the p – value of the difference between in the dependent variable between two
related group that are CR before and after M&A is 0.565 > 0.05 ( ) so the data of
the difference between in the dependent variable between two related group that
are CR before and after M&A is a normal distributed.
The difference between before and after merger of TATO:
Table 4. 2 Normality test for difference of TATO - Vingroup
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
DIFF_TATO .224 8 .200* .939 8 .597
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
49
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
the Shapiro-Wilk Test (appropriate for samples up to 2,000 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
As the p – value of the difference between in the dependent variable between two
related group that are TATO before and after M&A is 0.597 > 0.05 ( ) so the
data of the difference between in the dependent variable between two related
group that are TATO before and after M&A is a normal distributed.
The difference between before and after merger of DR:
Table 4. 3 Normality test for difference of DR - Vingroup
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
DIFF_DR .250 8 .149 .933 8 .547
a. Lilliefors Significance Correction
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
the Shapiro-Wilk Test (appropriate for samples up to 2,000 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
As the p – value of the difference between in the dependent variable between two
related group that are DR before and after M&A is 0.547 > 0.05 ( ) so the data of
the difference between in the dependent variable between two related group that
are DR before and after M&A is a normal distributed.
The difference between before and after merger of DER:
Table 4. 4 Normality test for difference of DER - Vingroup
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
DIFF_DER .254 8 .139 .862 8 .127
a. Lilliefors Significance Correction
50
(Sources: SPSS Data result by SPSS v.22.0)
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
the Shapiro-Wilk Test (appropriate for samples up to 2,000 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
As the p – value of the difference between in the dependent variable between two
related group that are DER before and after M&A is 0.127 > 0.05 ( ) so the data
of the difference between in the dependent variable between two related group
that are DER before and after M&A is a normal distributed.
The difference between before and after merger of NPM:
Table 4. 5 Normality test for difference of NPM - Vingroup
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
DIFF_NPM .178 8 .200* .967 8 .877
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
the Shapiro-Wilk Test (appropriate for samples up to 2,000 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
As the p – value of the difference between in the dependent variable between two
related group that are NPM before and after M&A is 0.877 > 0.05 ( ) so the data
of the difference between in the dependent variable between two related group
that are NPM before and after M&A is a normal distributed.
51
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
The difference between before and after merger of ROA:
Table 4. 6 Normality test for difference of ROA - Vingroup
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
DIFF_ROA .167 8 .200* .975 8 .932
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
the Shapiro-Wilk Test (appropriate for samples up to 2,000 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
As the p – value of the difference between in the dependent variable between two
related group that are ROA before and after M&A is 0.932 > 0.05 ( ) so the data
of the difference between in the dependent variable between two related group
that are ROA before and after M&A is a normal distributed.
The difference between before and after merger of ROE:
Table 4. 7 Normality test for difference of ROE - Vingroup
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
DIFF_ROE .218 8 .200* .906 8 .328
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
the Shapiro-Wilk Test (appropriate for samples up to 2,000 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
52
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
As the p – value of the difference between in the dependent variable between two
related group that are ROE before and after M&A is 0.328 > 0.05 ( ) so the data
of the difference between in the dependent variable between two related group
that are ROE before and after M&A is a normal distributed.
The difference between before and after merger of EPS:
Table 4. 8 Normality test for difference of EPS - Vingroup
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
DIFF_EPS .214 8 .200* .952 8 .733
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
the Shapiro-Wilk Test (appropriate for samples up to 2,000 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
As the p – value of the difference between in the dependent variable between two
related group that are EPS before and after M&A is 0.733 > 0.05 ( ) so the data
of the difference between in the dependent variable between two related group
that are EPS before and after M&A is a normal distributed.
FPT Corporation:
The difference between before and after merger of CR:
Table 4. 9 Normality test for difference of CR - FPT
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
Diff_CR .243 8 .180 .906 8 .329
a. Lilliefors Significance Correction
53
(Sources: SPSS Data result by SPSS v.22.0)
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
the Shapiro-Wilk Test (appropriate for samples up to 2,000 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
As the p – value of the difference between in the dependent variable between two
related group that are CR before and after M&A is 0.329 > 0.05 ( ) so the data of
the difference between in the dependent variable between two related group that
are CR before and after M&A is a normal distributed.
The difference between before and after merger of TATO:
Table 4. 10 Normality test for difference of TATO - FPT
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
Diff_TATO .179 8 .200* .887 8 .222
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
the Shapiro-Wilk Test (appropriate for samples up to 2,000 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
As the p – value of the difference between in the dependent variable between two
related group that are TATO before and after M&A is 0.222> 0.05 ( ) so the data
of the difference between in the dependent variable between two related group
that are TATO before and after M&A is a normal distributed.
54
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
The difference between before and after merger of DR:
Table 4. 11 Normality test for difference of DR - FPT
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
Diff_DR .189 8 .200* .900 8 .288
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
the Shapiro-Wilk Test (appropriate for samples up to 2,000 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
As the p – value of the difference between in the dependent variable between two
related group that are DR before and after M&A is 0.288> 0.05 ( ) so the data of
the difference between in the dependent variable between two related group that
are DR before and after M&A is a normal distributed.
The difference between before and after merger of DER:
Table 4. 12 Normality test for difference of DER - FPT
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
Diff_DER .205 8 .200* .912 8 .368
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
the Shapiro-Wilk Test (appropriate for samples up to 2,000 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
55
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
As the p – value of the difference between in the dependent variable between two
related group that are DER before and after M&A is 0.368 > 0.05 ( ) so the data
of the difference between in the dependent variable between two related group
that are DER before and after M&A is a normal distributed.
The difference between before and after merger of NPM:
Table 4. 13 Normality test for difference of NPM - FPT
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
Diff_NPM .164 8 .200* .975 8 .934
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
the Shapiro-Wilk Test (appropriate for samples up to 2,000 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
As the p – value of the difference between in the dependent variable between two
related group that are NPM before and after M&A is 0.934 > 0.05 ( ) so the data
of the difference between in the dependent variable between two related group
that are NPM before and after M&A is a normal distributed.
The difference between before and after merger of ROA:
Table 4. 14 Normality test for difference of ROA - FPT
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
Diff_ROA .147 8 .200* .949 8 .703
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
56
(Sources: SPSS Data result by SPSS v.22.0)
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
the Shapiro-Wilk Test (appropriate for samples up to 2,000 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
As the p – value of the difference between in the dependent variable between two
related group that are ROA before and after M&A is 0.703 > 0.05 ( ) so the data
of the difference between in the dependent variable between two related group
that are ROA before and after M&A is a normal distributed.
The difference between before and after merger of ROE:
Table 4. 15 Normality test for difference of ROE - FPT
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
Diff_ROE .198 8 .200* .970 8 .902
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
the Shapiro-Wilk Test (appropriate for samples up to 2,000 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
As the p – value of the difference between in the dependent variable between two
related group that are ROE before and after M&A is 0.902 > 0.05 ( ) so the data
of the difference between in the dependent variable between two related group
that are ROE before and after M&A is a normal distributed.
57
(Sources: SPSS Data result by SPSS v.22.0)
The difference between before and after merger of EPS:
Table 4. 16 Normality test for difference of EPS - FPT
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
Diff_EPS .194 8 .200* .963 8 .838
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
The Tests of Normality table gives us results from two well-known tests of
normality – the Kolmogorov-Smirnov Test (appropriate for “large” samples) and
the Shapiro-Wilk Test (appropriate for samples up to 2,000 cases). As sample size
of the study is 8, so the researcher decided to use the Shapiro-Wilk test.
As the p – value of the difference between in the dependent variable between two
related group that are EPS before and after M&A is 0.838 > 0.05 ( ) so the data
of the difference between in the dependent variable between two related group
that are EPS before and after M&A is a normal distributed.
4.3. Result of the paired sample test statistics:
The outcome of any hypothesis test you do is the P-value. SPSS isn’t always
consistent in what it calls the P-value, but Sig is always included somewhere. The
P-value measures the strength of evidence against the null hypothesis, H0. The
smaller the P-value, the stronger the evidence against H0.
A test result is significant when the P-value is “small enough”; usually we opt for
any P-values less than 0.05 (5%). (Marion Blumenstein and Leila Boyle, 2014)
Vingroup JSC:
CR variables:
58
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
Table 4. 17 Paired Samples Test for CR of Vingroup
Paired Samples Test
Paired Differences
t
d
f
Sig.
(2-
tailed
) Mean
Std.
Deviation
Std.
Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pai
r 1
CRBEFOR
E -
CRAFTER
2.987437
5
1.415641
2
.500504
7
1.803931
8
4.170943
2
5.96
9 7 .001
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is significant difference of CR, whereby the T-value and the
significant were not in the accepted range of H01 with Sig. (two-tailed) 0.01 <
0.05, which means H01 is rejected and Ha 1 is accepted.
TATO variables:
Table 4. 18 Paired Samples Test for TATO of Vingroup
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
TATOBEFORE
– TATOAFTER
-
.0166750 .0559524 .0197822
-
.0634524 .0301024
-
.843 7 .427
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is no significant difference of TATO, whereby the T-value
and the significant were in the accepted range of H02 with Sig. (two-tailed) 0.427
> 0.05, which means do not reject H02 .
59
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
DR variable:
Table 4. 19 Paired Samples Test for DR of Vingroup
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
DRBEFORE
- DRAFTER
-
.0734375 .0369967 .0130803 -.1043675 -.0425075
-
5.614 7 .001
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is significant difference of DR, whereby the T-value and the
significant were not in the accepted range of H03 with Sig. (two-tailed) 0.01 <
0.05, which means H03 is rejected and Ha3 is accepted.
DER variables:
Table 4. 20 Paired Samples Test for DER of Vingroup
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std.
Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
DERBEFORE
– DERAFTER
-
.1721000 1.0396903 .3675860
-
1.0413028 .6971028
-
.468 7 .654
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is no significant difference of DER, whereby the T-value and
the significant were in the accepted range of H04 with Sig. (two-tailed) 0.654 >
0.05, which means do not reject H04 .
60
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
NPM variables:
Table 4. 21 Paired Samples Test for NPM of Vingroup
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
NPMBEFORE
- NPMAFTER .1611375 .7186397 .2540775
-
.4396603 .7619353 .634 7 .546
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is no significant difference of NPM, whereby the T-value
and the significant were in the accepted range of H05 with Sig. (two-tailed) 0.546>
0.05, which means do not reject H05 .
ROA variables:
Table 4. 22 Paired Samples Test for ROA of Vingroup
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
ROABEFORE
- ROAAFTER .0015000 .0393768 .0139218
-
.0314198 .0344198 .108 7 .917
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is no significant difference of ROA, whereby the T-value
and the significant were in the accepted range of H06 with Sig. (two-tailed) 0.917
> 0.05, which means do not reject H06 .
61
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
ROE variables:
Table 4. 23 Paired Samples Test for ROE of Vingroup
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
ROEBEFORE
- ROEAFTER .0166375 .1727950 .0610923
-
.1278227 .1610977 .272 7 .793
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is no significant difference of ROE, whereby the T-value and
the significant were in the accepted range of H07 with Sig. (two-tailed) 0.793 >
0.05, which means do not reject H07 .
EPS variables:
Table 4. 24 Paired Samples Test for EPS of Vingroup
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
EPSBEFORE
- EPSAFTER 158.625 2969.473 1049.867 -2323.917 2641.167 .151 7 .884
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is no significant difference of EPS, whereby the T-value and
the significant were in the accepted range of H08 with Sig. (two-tailed) 0.884 >
0.05, which means do not reject H08 .
62
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
FPT Corporation:
CR variables:
Table 4. 25 Paired Samples Test for CR of FPT
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
CRBEFORE
- CRAFTER .1478000 .0693558 .0245210 .0898171 .2057829 6.027 7 .001
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is significant difference of CR, whereby the T-value and the
significant were not in the accepted range of H03 with Sig. (two-tailed) 0.01 <
0.05, which means H01 is rejected and Ha1 is accepted.
TATO variables:
Table 4. 26 Paired Samples Test for TATO of FPT
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std.
Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
TATOBEFORE
- TATOAFTER .4257750 .2278342 .0805516 .2353008 .6162492 5.286 7 .001
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is significant difference of TATO, whereby the T-value and
63
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
the significant were not in the accepted range of H03 with Sig. (two-tailed) 0.01 <
0.05, which means H02 is rejected and Ha 2 is accepted.
DR variable:
Table 4. 27 Paired Samples Test for DR of FPT
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
DRBEFORE
- DRAFTER .0532125 .0817450 .0289012 -.0151280 .1215530 1.841 7 .108
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is no significant difference of DR, whereby the T-value and
the significant were in the accepted range of H03 with Sig. (two-tailed) 0.108 >
0.05, which means do not reject H03 .
DER variables:
Table 4. 28 Paired Samples Test for DER of FPT
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
DERBEFORE
- DERAFTER .4796375 .5099340 .1802889 .0533220 .9059530 2.660 7 .032
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is significant difference of DER, whereby the T-value and
64
(Sources: SPSS Data result by SPSS v.22.0)
the significant were not in the accepted range of H04 with Sig. (two-tailed) 0.032 <
0.05, which means H04 is rejected and Ha 4 is accepted.
NPM variables:
Table 4. 29 Paired Samples Test for NPM of FPT
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
NPMBEFORE
- NPMAFTER
-
.0100750 .0087739 .0031021
-
.0174102
-
.0027398
-
3.248 7 .014
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is significant difference of NPM, whereby the T-value and
the significant were not in the accepted range of H05 with Sig. (two-tailed) 0.014 <
0.05, which means H05 is rejected and Ha 5 is accepted.
65
(Sources: SPSS Data result by SPSS v.22.0)
(Sources: SPSS Data result by SPSS v.22.0)
ROA variables:
Table 4. 30 Paired Samples Test for ROA of FPT
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
ROABEFORE
- ROAAFTER .0053750 .0081250 .0028726
-
.0014177 .0121677 1.871 7 .104
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is no significant difference of ROA, whereby the T-value
and the significant were in the accepted range of H06 with Sig. (two-tailed) 0.104
> 0.05, which means do not reject H06 .
ROE variables:
Table 4. 31 Paired Samples Test for ROE of FPT
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
ROEBEFORE
- ROEAFTER .0289750 .0129039 .0045622 .0181871 .0397629 6.351 7 .000
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is significant difference of ROE, whereby the T-value and
the significant were not in the accepted range of H07 with Sig. (two-tailed) 0.000 <
0.05, which means H07 is rejected and Ha 7 is accepted.
66
(Sources: SPSS Data result by SPSS v.22.0)
EPS variables:
Table 4. 32 Paired Samples Test for EPS of FPT
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std.
Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
EPSBEFORE -
EPSAFTER 379.500 376.687 133.179 64.581 694.419 2.850 7 .025
From the table above and according to the statistic calculation for the 95%
confidence interval and two-tailed test, which has a T-table is 2.365, could be
concluded that there is significant difference of EPS, whereby the T-value and the
significant were not in the accepted range of H05 with Sig. (two-tailed) 0.025 <
0.05, which means H08 is rejected and Ha8 is accepted.
4.4. Interpretation Analysis:
4.4.1.1. The financial performance of Vingroup Company before and
after M&A:
The result of this thesis showed that the financial performance of the company did
not have a lot differences before and after M&A as proved by the Paired Sample
T-Test with six ratios out of eight ratios that the researcher has chosen have no
significance difference before and after M&A. Those ratios are TATO, DER,
NPM, ROA, ROE, and EPS. But the M&A still has effect to the company’s
financial performance that is showed through two ratios that have significance
difference before and after M&A that are CR and DR.
67
So, in Vingroup Company after the M&A, the M&A did not have a lot of
influences to the company performance in Profitability and Activities but it
influences to the Leverage and Liquidity Ratios of the Company.
4.4.1.2. The financial performance of FPT Corporation before and after
M&A:
The result of this thesis showed that the financial performance of the company did
have a lot differences before and after M&A as proved by the Paired Sample T-
Test with only two ratios out of eight ratios that the researcher has chosen have no
significance difference before and after M&A. Those ratios are DR and ROA.
The rest of the ratios those are six ratios that have significance difference before
and after M&A that are CR, TATO, DER, NPM, ROE, and EPS.
68
CHAPTER V
CONCLUSION AND RECOMMENDATION
5.1. Conclusion
The purpose of this research is to analyze the companies’ performance before and
after M&A to find out the effect of M&A to the companies’ performance.
According to the analysis and the elaboration of the impact of merger on
performance of two companies that are: Vingroup JSC and FPT Corporation in
Chapter IV, hence it can be summarized as follow:
For Vingroup JSC:
There has no significant difference before and after M&A on TATO. So it means
that the M&A did not influence to the TATO of the company or can say that the
M&A did not affect the firm's management uses its assets to generate sales.
There has no significant difference before and after M&A on DER. So it means
that the M&A did not influence to the DER of the company or can say that the
M&A did not affect the percentage of the company financing that comes from
creditors and investors.
There has no significant difference before and after M&A on NPM. So it means
that the M&A did not influence to the NPM of the company or can say that the
M&A did not affect how the company converts revenue into profits available for
shareholders.
There has no significant difference before and after M&A on ROA. So it means
that the M&A did not influence to the ROA of the company or can say that the
M&A did not affect how efficiently the company manages its assets to produce
profits.
69
There has no significant difference before and after M&A on ROE. So it means
that the M&A did not influence to the ROE of the company or can say that the
M&A did not affect how much profit each dollar of the common stockholders’
equity generates.
There has no significant difference before and after M&A on EPS. So it means
that the M&A did not influence to the EPS of the company, or can say that the
M&A did not affect the amount of money each share of stock would receive.
There has significant difference before and after M&A on CR. So it means that
the M&A did not influence to the CR of the company or can say that the M&A
did affect the ability of the company to full fill the short term obligation.
There has significant difference before and after M&A on DR. So it means that
the M&A did not influence to the DR of the company or can say that the M&A
did affect the leverage of the company.
For Vingroup JSC, there are six financial ratios which are TATO, DER, NPM,
ROA, ROE, and EPS has no significant difference before and after M&A and
have two ratios that are CR and DR has a significant difference before and after
M&A. So it can be concluded that the financial performance of Vingroup JSC
have changed after M&A but it is not significant difference, it means that there is
no significant different of the financial performance of the company before and
after M&A.
FPT Corporation
There has significant difference before and after M&A on CR. So it means that
the M&A did not influence to the CR of the company or can say that the M&A
did affect the ability of the company to full fill the short term obligation.
There has significant difference before and after M&A on TATO. So it means
that the M&A did not influence to the TATO of the company or can say that the
M&A did affect the firm's management uses its assets to generate sales.
70
There has significant difference before and after M&A on DER. So it means that
the M&A did not influence to the DER of the company or can say that the M&A
did affect the percentage of the company financing that comes from creditors and
investors.
There has significant difference before and after M&A on NPM. So it means that
the M&A did not influence to the NPM of the company or can say that the M&A
did affect how the company converts revenue into profits available for
shareholders.
There has significant difference before and after M&A on ROE. So it means that
the M&A did not influence to the ROE of the company or can say that the M&A
did affect how much profit each dollar of the common stockholders’ equity
generates.
There has significant difference before and after M&A on EPS. So it means that
the M&A did not influence to the EPS of the company or can say that the M&A
did affect the amount of money each share of stock would receive.
There has no significant difference before and after M&A on DR. So it means
that the M&A did not influence to the DR of the company or can say that the
M&A did not affect the leverage of the company.
There has no significant difference before and after M&A on ROA. So it means
that the M&A did not influence to the ROA of the company or can say that the
M&A did not affect how efficiently the company manages its assets to produce
profits.
For the FPT Corporation, there are six ratios which are CR, TATO, DER, NPM,
ROE and EPS that showed a significant difference, but the other two ratios have
no significant differences after M&A that are DR and ROA. So it could be
concluded that the financial performance of the FPT Corporation before and after
M&A has changed or can say that the M&A had effect to the company’s
performance. However, it could not be concluded completely that the reasons of
71
those changes are from M&A. Because besides M&A is the factor can affect to
the company’s financial performance there are still having a lot of the Economy’s
factors that influence the company’s financial performance mostly.
The result is some companies can be influenced by M&A and some company
does not be influenced by M&A. For the companies were influenced by M&A, it
could not be concluded that M&A is only reason of those changes of the
companies’ performance.
The result of this research might have not indicated any significance impacts of
M&A cases of two represented companies. However, it does not mean that this is
the final outcome. It is expected that the M&A will bring a good impact and
challenges to the companies in an appropriate time period and the companies can
avoid the failure of M&A and exploit the benefit of M&A. It was presumed that
to reach the synergy of the M&A is needed more than two years analyzing for
companies were not affected by M&A.
Even though, two years before and two years after is not enough, it is expected
that the time period needed to reach the synergy will not be too long. Since, the
main objective of M&A is to create the synergy between them, hopefully it will
be reached in tan appropriate of time period and hence it can minimize the
operating costs and provide the better services and products to the customer in
order to enhance the position in the market.
5.2. Recommendation
After this study, the researcher would like to give some recommendations
regarding to this research:
1. For companies:
For the companies that have plan to M&A or implement M&A, there are some
recommendations from the researcher:
72
Consider the Debt that the companies might take after the M&A. Because it will
increases the Leverage Business and Finance for the companies in the future. This
will make the companies have heavier burdens that need to solve.
And the companies should pay the attention to the intangible assets of the target
company that are the brand, the patent, the copyright and goodwill, because in the
future the value of them will increase. Besides those aspects, the companies
should consider about the economy and policy that will make a lot of effect to the
financial performance of companies.
2. For the investor:
The investor should be aware of the challenges of M&A. So investor can prepare
the solution to face the problems.
3. For the future researcher:
For who would like to choose M&A as the topic of the research:
1. It will be better if the research include the other factors from the
economy rather than comparing only the Financial Ratios.
2. The time length of the analyzing should be longer so it can show the clear
effect of M&A toward the companies’ performance. Because, M&A has
a long term effect.
73
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76
APPENDICES
Appendix A - FPT Corporation’s Financial Quarter Report and Ratios for year
2009
Appendix B - FPT Corporation’s Financial Quarter Report and Ratios for year
2010
77
Appendix C - FPT Corporation’s Financial Quarter Report and Ratios for year
2012
Appendix D - FPT Corporation’s Financial Quarter Report and Ratios for year
2013
78
Appendix E – SPSS Result of VinGroup
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 CRBEFORE 4.129100 8 1.2628873 .4464981
CRAFTER 1.141663 8 .2665696 .0942466
Paired Samples Correlations
N Correlation Sig.
Pair 1 CRBEFORE & CRAFTER 8 -.502 .205
Paired Samples Test
Paired Differences
t
d
f
Sig.
(2-
tailed
) Mean
Std.
Deviation
Std.
Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pai
r 1
CRBEFOR
E -
CRAFTER
2.987437
5
1.415641
2
.500504
7
1.803931
8
4.170943
2
5.96
9 7 .001
79
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 TATOBEFORE .038588 8 .0523895 .0185225
TATOAFTER .055263 8 .0398015 .0140719
Paired Samples Correlations
N Correlation Sig.
Pair 1 TATOBEFORE &
TATOAFTER 8 .287 .490
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
TATOBEFORE
- TATOAFTER
-
.0166750 .0559524 .0197822
-
.0634524 .0301024
-
.843 7 .427
80
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 TATOBEFORE .038588 8 .0523895 .0185225
TATOAFTER .055263 8 .0398015 .0140719
Paired Samples Correlations
N Correlation Sig.
Pair 1 TATOBEFORE &
TATOAFTER 8 .287 .490
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
TATOBEFORE
- TATOAFTER
-
.0166750 .0559524 .0197822
-
.0634524 .0301024
-
.843 7 .427
81
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 DERBEFORE 3.508588 8 1.0658524 .3768357
DERAFTER 3.680688 8 .6364151 .2250067
Paired Samples Correlations
N Correlation Sig.
Pair 1 DERBEFORE & DERAFTER 8 .339 .411
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std.
Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
DERBEFORE
- DERAFTER
-
.1721000 1.0396903 .3675860
-
1.0413028 .6971028
-
.468 7 .654
82
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 NPMBEFORE .562025 8 .4080316 .1442610
NPMAFTER .400888 8 .5587339 .1975423
Paired Samples Correlations
N Correlation Sig.
Pair 1 NPMBEFORE & NPMAFTER 8 -.083 .845
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
NPMBEFORE
- NPMAFTER .1611375 .7186397 .2540775
-
.4396603 .7619353 .634 7 .546
83
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 ROABEFORE .019600 8 .0281614 .0099566
ROAAFTER .018100 8 .0207882 .0073497
Paired Samples Correlations
N Correlation Sig.
Pair 1 ROABEFORE & ROAAFTER 8 -.278 .505
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
ROABEFORE
- ROAAFTER .0015000 .0393768 .0139218
-
.0314198 .0344198 .108 7 .917
84
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 ROEBEFORE .093100 8 .1287092 .0455056
ROEAFTER .076462 8 .0807770 .0285590
Paired Samples Correlations
N Correlation Sig.
Pair 1 ROEBEFORE & ROEAFTER 8 -.325 .432
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
ROEBEFORE
- ROEAFTER .0166375 .1727950 .0610923
-
.1278227 .1610977 .272 7 .793
85
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 EPSBEFORE 1468.38 8 2272.036 803.286
EPSAFTER 1309.75 8 1388.468 490.898
Paired Samples Correlations
N Correlation Sig.
Pair 1 EPSBEFORE & EPSAFTER 8 -.274 .512
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
EPSBEFORE
- EPSAFTER 158.625 2969.473 1049.867 -2323.917 2641.167 .151 7 .884
86
Appendix E – SPSS Result of FPT
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 CRBEFORE 1.662525 8 .0698373 .0246912
CRAFTER 1.514725 8 .0506724 .0179154
Paired Samples Correlations
N Correlation Sig.
Pair 1 CRBEFORE & CRAFTER 8 .372 .364
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
CRBEFORE
- CRAFTER .1478000 .0693558 .0245210 .0898171 .2057829 6.027 7 .001
87
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 TATOBEFORE 1.086988 8 .2429099 .0858816
TATOAFTER .661213 8 .0534896 .0189114
Paired Samples Correlations
N Correlation Sig.
Pair 1 TATOBEFORE & TATOAFTER 8 .383 .349
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std.
Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
TATOBEFORE
- TATOAFTER .4257750 .2278342 .0805516 .2353008 .6162492 5.286 7 .001
88
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 DRBEFORE .554938 8 .0692463 .0244823
DRAFTER .501725 8 .0234140 .0082781
Paired Samples Correlations
N Correlation Sig.
Pair 1 DRBEFORE & DRAFTER 8 -.413 .309
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
DRBEFORE
- DRAFTER .0532125 .0817450 .0289012 -.0151280 .1215530 1.841 7 .108
89
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 DERBEFORE 1.647713 8 .4527335 .1600655
DERAFTER 1.168075 8 .1052880 .0372249
Paired Samples Correlations
N Correlation Sig.
Pair 1 DERBEFORE & DERAFTER 8 -.461 .250
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
DERBEFORE
- DERAFTER .4796375 .5099340 .1802889 .0533220 .9059530 2.660 7 .032
90
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 NPMBEFORE .029750 8 .0069543 .0024587
NPMAFTER .039825 8 .0064004 .0022629
Paired Samples Correlations
N Correlation Sig.
Pair 1 NPMBEFORE & NPMAFTER 8 .139 .743
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
NPMBEFORE
- NPMAFTER
-
.0100750 .0087739 .0031021
-
.0174102
-
.0027398
-
3.248 7 .014
91
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 ROABEFORE .031513 8 .0070833 .0025043
ROAAFTER .026138 8 .0034562 .0012220
Paired Samples Correlations
N Correlation Sig.
Pair 1 ROABEFORE & ROAAFTER 8 -.080 .851
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
ROABEFORE
- ROAAFTER .0053750 .0081250 .0028726
-
.0014177 .0121677 1.871 7 .104
92
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 ROEBEFORE .089662 8 .0121089 .0042811
ROEAFTER .060687 8 .0081130 .0028684
Paired Samples Correlations
N Correlation Sig.
Pair 1 ROEBEFORE & ROEAFTER 8 .234 .577
Paired Samples Test
Paired Differences
t df
Sig.
(2-
tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
ROEBEFORE
- ROEAFTER .0289750 .0129039 .0045622 .0181871 .0397629 6.351 7 .000