Summary of the PhD thesis: The impact of diversification on performance and risk of firms

MINISTRY OF EDUCATION AND TRAINING
HO CHI MINH CITY OPEN UNIVERSITY

VU HUU THANH

THE IMPACT OF DIVERSIFICATION ON
PERFORMANCE AND RISK OF FIRMS

Major

: Business Administration

Major Code

: 62 34 01 02

SUMMARY OF THE PHD THESIS

HCMC, 2018


The thesis is completed at the:

HO CHI MINH CITY OPEN UNIVERSITY
Reviewer:
1:………………………………………………………………………
Reviewer:
2:………………………………………………………………………

The thesis will be defended in front of the Thesis Committee at Academy level,
at the Open University of Ho Chi Minh city

At…… date …… month …… year 2018


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CHAPTER 1. INTRODUCTION
1.1. Research problem
Diversification is considered as one of the strategic activities of a firm (Ramanujam
and Varadarajan, 1989) and it has a profound effect on many aspects of firms; notably, its impact
on performance and risk. Following the structure-conduct-performance paradigm (S – C – P
paradigm) in theory of industrial organization (IO theory), the output of a firm is linearly related
to the market structure (Weiss, 1979). The S – C – P paradigm describes the structure of the
market determines the behaviour of the firms, and then the behaviour of the firms determines
their output (McWilliams and Smart, 1993). The S – C – P framework is integrated into the
theory of strategic management (Jemison, 1981) to describe the impact of a variety of strategic
activities, including diversification, on business performance (McWilliams and Smart, 1993).
Thus, derived from industrial organization theory, diversification is regarded as a component of
strategic management and this component has significant implications for firms’ output.
Besides performance, risk also receives particular attention in strategic management.
The link between diversification and risk was soon considered by Bettis and Hall (1982) and
has since formed a direction to this day. The impact of diversification on risk is quite
complicated. This complexity is due to the diversity of the type of firm diversification, each of
which diversifies into lower-level diversification based on different classification. Different
types of diversification at the lower level tended to have different impacts on risk, and each type
of diversification itself may have certain relationships. For example, business diversification in
a firm is divided into two broad categories which are related and unrelated diversification.
Diversification of related business can increase performance (Palich et al., 2000) but also
increase specific risk (Bettis and Hall, 1982). Meanwhile, unrelated diversification has the
opposite effect.
Based on the theoretical and empirical studies on the effects of diversification on the
performance and risk, the thesis found some following issues:

Firstly, the study of the impact of business diversification (BDIV) is prevalent in the
world. However, the dissertation has not found any similar study up to 2015. By 2016, the
research by Santarelli and Tran (2016) on the effect of diversification on the performance of
Vietnamese enterprises appears. The study used GSO data to measure overall BDIV and to
estimate the impact of this variable on business performance. The study has not conducted an
estimation of the impact of various types of diversification on performance; in particular, the
effect of related and unrelated business on performance. According to Palich et al. (2000) and
Benito-Osorio et al. (2012), the related and unrelated BDIV tended to have different effects on
the performance due to the distinctive characteristics of the two types of diversification. Thus,
by combining these two types of diversification into overall business diversification, it is
difficult for firms to choose which type of diversification is appropriate for their business. In
practice, firms need to decide what type of diversification to pursue (diversification of the
related business, diversification of the unrelated business, geographic diversification,
international diversification, ...) rather than pursue diversification in general.


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Secondly, the impact of BDIV on risks, especially bankruptcy risk, which has rarely
been studied in the empirical literature, has been reported in about 17 studies up to 2016.
Bankruptcy risk variables are primarily measured by the Atman Z - Score, a measure that is only
suitable for the US market that may not be suitable for an emerging market like Vietnam.
Thirdly, the study of the effects of BDIV on the performance and bankruptcy risk is
often conducted separately in individual research models without being simultaneously
performed in an empirical model.
In addressing the three issues mentioned above, the thesis deals with the first topic
titled "The impact of business diversification on performance and risk." This topic will explore
the impact of related and unrelated business diversification on performance, and this research
employs the Linear Structural Model (SEM) to estimate these relationships. Also, firm
performance variables will be viewed from a shareholder's perspective and measured by ROE
(return on equity), the bankruptcy risk variable is measured MKV model (probability of default).

Using SEM model and MKV bankruptcy risk measurement can be considered as the new point
of the research.
Fourth, diversification can be seen in various angles when placed in relation to the
performance and risk of a firm. Diversification can be seen in terms of business diversification
(Asoft, 1957), product diversification (Rumelt, 1974), geographic diversification (Stopford and
Wells, 1972; Daniels and Bracker, 1989; and Sullivan, 1994), merger diversification (Morck et
al., 1990), and customer diversification (Hsu and Liu, 2008). These types of diversification are
commonly referred to as business diversification because they are all oriented towards the
business of firms. However, there are other forms of diversification taking place in the internal
environment of a firm such as capital diversification or asset investment diversification have
been not be explored. The three types of diversification are capital diversification (CDIV), asset
investment diversification (ADIV), and BDIV that may have a specific relationship with each
other in the context of corporate financial decision-making. In particular, CDIV may impact on
ADIV and then ADIV may impact on BDIV. In addition, ADIV and CDIV may also affect
performance and risk if based on such theories as Rumelt's "escape hypothesis" (Rumelt, 1974),
theory of resource-based view” (Wernerfeld, 1984 and Barney,1991), the capital structure
theory (Modilligani and Miler, 1958 and Myers, 1977), and theory of free cash flow of Jensen
(1986). Given the above, two questions are posed: first, is there a practical effect of ADIV on
performance and the risk of bankruptcy through the mediating effect of BDIV? Moreover,
secondly, is there a practical effect of the CDIV on performance and risk through mediating
effect of ADIV?
In response to these two questions, the thesis continues to carry out two further
research topics. The second research topic titled "The impact of asset investment diversification
on business diversification, performance and risk," and the third research topic titled "The
impact of capital diversification on asset investment diversification, performance and risk. "
On the second research topic, the dissertation will classify the ADIV into two
components, namely, related assets and unrelated assets to the core business of a firm. Then the
dissertation builds the theoretical relationship among ADIV, BIDV, performance, and risk.
Then, the thesis builds the SEM model to estimate these relationships empirically. Building the

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links among ADIV, BDIV, performance, and risk and employing SEM model to estimate these
links can be considered as a new point in the thesis.
Similarly, in the third research topic, the thesis will classify CDIV into equity
diversification and debt diversification. The thesis then builds the theoretical relationship among
CDIV, ADIV, performance and risk. Next, the thesis employs the SEM model for empirical
estimation. Establishing the links among CDIV, ADIV, performance, and risk, as well as
estimating with the SEM model, may be considered as a new point in the thesis.
1.2. Research questions
The thesis should answer three research questions as follows:
Question 1: How does the BDIV affect performance and risk?
Question 2: How does ADIV affect performance and risk through the mediating effect
of BDIV?
Question 3: How does the CDIV affect performance and risk through the mediating
effect of ADIV?
1.3. Research objectives
The dissertation should address three research objectives as follows:
Objective 1: Evaluate the impact of BDIV on the performance and risk of firms.
Objective 2: Assess the impact of ADIV on the performance and risk of firms through
the mediating effect of BDIV.
Objective 3: Evaluate the impact of the CDIV on the performance and risk of firms
through the mediating effect of ADIV.
1.4. Object and scope of the study
The object of the study is the impact of the diversification on the performance and
risk of a firm. More specifically, the impact of BDIV on the performance and risk of firms; the
impact of ADIV on the performance and risk of firms through mediating effect of BDIV; and
impact of the CDIV on the performance and risk of firms through the mediating effect of ADIV.
The research scope is non-financial businesses listed on the Ho Chi Minh City Stock
Exchange and the Hanoi Stock Exchange between 2008 and 2015.

1.5. Research contents
Based on research, the research questions and objectives, the dissertation has four
main research contents as follows:


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Firstly, a theoretical study on the linkages between the three types of diversification,
including the BDIV, ADIV, and CDIV.
Second, a theoretical study on the linkage among the three types of diversification,
performance, and risk.
Third, develop a research method to empirically estimate relationships mentioned
above, including (i) BDIV, performance, and risk; (ii) ADIV, BDIV, performance, and risk; (iii)
CDIV, ADIV, performance, and risk.
Fourth, empirically estimate these relationships and discuss results.
1.6. New research contributions
The thesis has three research topics to address three research objectives and has new
contributions described as followings:
Topic one: The impact of business diversification on performance and risk. This topic
is performed in chapter two. The research in topic one is still a repetitive study of the impact of
BDIV on performance and risk. However, by measuring the risk of bankruptcy using the
Merton-KMV model (probability of default model), and estimated these relationships using the
SEM model, the research in the topic has contributed in terms of: (i) measuring the risk of
bankruptcy by Merton-KMV model and (ii) employing SEM model to estimate empirically..
Topic two: The impact of ADIV on BDIV, performance and risk. The research is
addressed in chapter three. The second topic considered ADIV as related and unrelated assets
diversification and built the relationship between these two variables with BDIV, performance,
and risk. Thus, the second research topic has contributed regarding: (i) create new concepts
(related and unrelated asset investment diversification) and (ii) build new link among concepts
(ADIV, BDIV, performance, and risk).
Topic three: The impact of CDIV on ADIV, performance, and risk. The topic is

organized in chapter four. The research on the topic focused on understanding the CDIV. The
study analyzes CDIV as two components: equity diversification and debt diversification. Then
the thesis establishes the linkage of these two variables to the ADIV, performance, and risk.
Thus, similar to topic two, topic three has contributed to the following new points: (i) build new
concepts (equity diversification and debt diversification) and (ii) establish new relationships
among concepts (CDIV, ADIV, performance, and risk).
1.7. Thesis structure
The thesis is organized into five chapters with the following title:
Chapter 1. Introduction
Chapter 2. Impact of business diversification on performance and risk.
Chapter 3. Impact of Asset investment diversification on business diversification,
performance, and risk.


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Chapter 4. The Impact of capital diversification on asset investment diversification,
performance, and risk.
CHAPTER 2. THE IMPACT OF BUSINESS DIVERSIFICATION ON
PERFORMANCE AND RISK
2.1. Literature review
2.1.1. ĐDH
This section explores four issues: (i) concept of diversification, (ii) classification of
diversification, (iii) identification of diversification content used in the thesis, and (iv) measure
diversification.
2.1.1.1. Khái niệm ĐDH
Based on previous studies, the thesis presents the concept of two types of business
diversification as follows:
Related business diversification (RBDIV) occurs when a firm adds a new line of
products related to existing core product.
Unrelated business diversification occurs when a firm expands a new line of products

unrelated to existing core product.
2.1.1.2. Diversification measurement
The favourite way to measure diversification in studies is to combine the classification
of Rumelt (1974) and the entropy method. The first author proposed using entropy to calculate
the degree of diversification was Jacquemin and Berry (1979). Then Palepu (1985) based on
Rumelt's classification and associated with the theory of entropy calculated a firm
diversification, including total diversification, related diversification, and unrelated
diversification. Whereby:
Total diversification:
𝑡

1
𝐷𝑇 = 1 − ∑ 𝑝𝑡 log 2 ( )
𝑝𝑡
𝑡=1

Of which: “t” is the tth segment, “pt” is the sales of the tth segment to total sales.
Related diversification:
𝑟

1
𝐷𝑅 = ∑ 𝑝𝑟 log 2 ( )
𝑝𝑟
𝑟=1

Of which: r is the rth segment related to the primary business, “pr” is the sales of the
rth segment to total sales.


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Unrelated diversification:
𝑢

1
𝐷𝑈 = ∑ 𝑝𝑢 log 2 ( )
𝑝𝑢
𝑢=1

Of which: “u” is is the uth segment unrelated to the primary business, “pu” is the sales
of the rth segment to total sales.
2.1.2. Performance of Firms
2.1.2.1. Definition
This study approaches the concept of "business performance " from a shareholder's
point of view, so corresponding to this angle is the profit aspect of firms. Profit is considered
the common factor used in most studies on the effects of diversification on performance.
2.1.2.2. Performance measurement
This research measures performance in a shareholder's perspective because
shareholders will be interested in the company's strategic activities, including diversification.
Also, this is also a measure of the accounting performance of firms and is widely used by many
studies (Lee and Li, 2012). The variable employed to measure performance under shareholder’s
perspective is "return on equity" (ROE).
2.1.3. Bankruptcy risk
2.1.3.1. Definition
Bankruptcy risk is considered as "the probability of occurrence of an event where a
firm is unable to pay its debts when it is due".
2.1.3.2. Measurement
This research approaches the risk from the perspective of the probability of
bankruptcy of Merton (1974), Kealhofer and Bohn (1998), McQuown (1997) and Vasicek
(1984), which is named Merton-MKV model. We employ this model to estimate the probability
of bankruptcy of a firm.

2.1.4. The relationship between BDIV and performance
2.1.4.1. Theories on the effect of BDIV on performance
Theory of firm growth
According to Penrose (1959), the goal of business owners is to increase long-term
profitability and to achieve this goal the firm must achieve growth through expansion including
diversification. This theory indirectly explains the relationship between BDIV and performance
firm growth.
Economies of scope


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The theory of economies of scope was developed by Panzar and Willig (1977). This
theory states that the average cost of production falls when firms expand on the type of goods
and services it produces. Firms get a cost advantage when they produce complementary products
while they still concentrate on their core competencies. As firms diversify their products,
especially the diversification of related products, they will have the opportunity to convert
resources and share resources, such as skills and technology… (Rumelt, 1982; Teece, 1982;
Markides and Williamson, 1994; and Barney, 1997). If two or more businesses of firms share
some common resources with each other, the total cost of production will decrease; hence, the
efficiency will increase. This theory is used to explain the positive relationship between RBID
and performance.
Theory of resource-based view – RBV
Wernerfelt (1984) and Barney (1991) then developed Penrose's perspective on RBV
theory. According to Barney (1991), firms’ resources including all kinds of assets, capabilities,
processes, knowledge, ... are controlled by firms and can help firms perform effective strategies.
Resources will provide a sustainable competitive advantage if they have characteristics that are:
valuable, rare, imperfectly imitable, strategically nonsubstitutable. This theory is used to explain
the negative impact of UBIDV on performance.
2.1.4.2. Empirical evidence on the impact of BDIV on performance
The thesis explored 71 articles and 51 articles on the impact of the RDIV and UDIV

on performance alternately. The study found that for the RDIV variable, the positive impact
dimension was dominant (45.6%); In contrast, negative influences account for a majority
(39.2%) in the studies the effect of UDIV on performance.
Based on the theory, empirical studies and meta-analyses, the thesis hypothesizes the
relationship between BDIV and performance as follows:
Hypothesis H1.1: RBDIV tends to have a positive impact on the performance of a
firm.
Hypothesis H1.2: UBDIV tends to affect the performance of a firm negatively.
2.1.5. BDIV and risk
2.1.5.1. Theories on the effect of BDIV on performance
Lubatkin và Chatterjee (1994a)
Lubatkin and Chatterjee (1994) research the impact of business diversification on the
specific and systematic risk of a firm. They argue that portfolio theory may not be applied to all
cases of the impact of business diversification on risk; notably, the impact of business
diversification on the specific risk (unsystematic risk). They conclude that related diversification
reduces unsystematic risk; conversely, unrelated diversification has a positive effect on this risk.
Their conclusion is contrary to the theory of portfolio. They explain that firms diversifying into
related industries own some synergistic interrelationship (tangible and intangible
interrelationship), so that specific risk is reduced. On the contrary, when firms expand their


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business into unrelated industries, they will lack internal relationships, and it will lead to the
increase in unsystematic risk.
Bettis và Hall (1982)
Bettis and Hall (1982) study on the relationship between business diversification and
accounting risk. They state that related diversification has a lower effect on accounting risk than
unrelated diversification. They explain as follows:
Assuming that a firm operates only in one industry and it gains profit R1. Based on
the theory of tradeoffs between profit and risk, the variation of R1 (Var (R1)) is the accounting

risk of the firm. The meaning of the Var (R1) is that if the profit of firm increases or decreases
considerably in successive periods of time, the risk rises rapidly.
Next, the firm expands from the existing industry to other. R1 and R2 alternatively
represent the profit of the first and the second industry, the combined risk of both industries gets
measured by the sum of the variances of both R1 and R2:
Var(R1 + R2) = Var(R1) + 2Cov(R1,R2) + Var(R2)
If Cov(R1, R2) is positive or the correlation between returns is positive, the combined
risk is higher. Conversely, if the correlation is negative, the firm gets the smaller sum of risk.
Bettis and Hall (1982) suggest that when a firm operates in two related industry, Cov(R1, R2)
is positive. On the contrary, if a firm operates in two unrelated industry, Cov(R1, R2) is
negative. These imply that the firm copes with the problem of the business cycle when they
enter more than an industry. Unrelated diversification can eliminate the cycle and lower the risk
while related diversification can exacerbate firm business cycle downturn and raise the
combined risk.
From here, the thesis presents the relationship between business and bankruptcy risk
as follows:
Hypothesis H1.3: The risk of bankruptcy of a firm can increase when the firm
conducts RBDIV.
Hypothesis H1.4: The risk of bankruptcy of a firm can be reduced if the firm conducts
UBDIV.
2.1.5.2. Empirical evidence on the impact of BDIV on risk
The following table summarizes the impact of BDIV on specific risks.
Table 2.12. Summarize the impact of business diversification to specific risks
Direction
Possitive effect
Negative effect
No effect
Tổng

RBDIV

Frequency
5
9
3
17

UBDIV
Percent
29.4%
52.9%
17.7%
100%

Frequency
10
5
2
17

Percent
58.8%
29.4%
11.8%
100%


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2.2. Methods
2.2.1. Empirical model
The thesis proposes an empirical SEM model, consisting of a two-equation system for

research topic one as follows:
P = f(RB_DIV, UB_DIV, Control variables) (1.1)
{
R = f(RB_DIV, UB_DIV, Control variables) (1.2)
In which: P is the performance, R is the risk, RB_DIV represents the related business
diversification, UB_DIV represents the unrelated business diversification.
2.2.2. Variable measurement
2.2.2.1. Dependent variable
(i) Performance variable
𝑅𝑂𝐸 =

𝐸𝐴𝑇
𝐸𝑞𝑢𝑖𝑡𝑦

(ii) Risk variable
In Chapter 2, the study specified Merton-KMV model to estimate bankruptcy
probability. Based on the study by Kealhofer and Bohn (1998), McQuown (1997) and Vasicek
(1984), the thesis will calculate the bankruptcy probability of the firm over a nine year period
(Measurement of risk variables is described in detail in Appendix 2)
2.2.2.2. BDIV measurement
The BDIV consists of two variables: RB_DIV and UB_DIV. This study will
incorporate Rumelt's (1974) calculation and entropy density. Details of the measurement of
business metrics are described in Appendix 1:
n

1
RB_DIV = ∑ pr log 2 ( )
pr
r=1
n

1
UB_DIV = ∑ pu log 2 ( )
pu
u=1

2.2.2.3. Control variable
Control variables affect performance: Firm size, the ratio of operating costs to
revenue, sales growth, firm age, current payment ratio, cash conversion cycle, assets structure,
and assets turnover.
Control variables affect risk: Firm size, the ratio of operating costs to revenue, current
payment ratio, cash conversion cycle, assets turnover, price to book ratio, operating cash flow
ratio, and Interest Coverage Ratio.


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2.2.3. Estimation
The study will use the method of "maximum likelihood estimation" to estimate the
SEM model and perform necessary model tests such as (i) Good-of- Fitness test), (ii)
homoscedasticity test, and (iii) normal distribution of residuals. If the model encounters
heteroscedasticity or residuals have not a normal distribution, the GSEM (Generalized structural
equation model) can be employed to replace SEM.2.2.4. Dữ liệu nghiên cứu
2.2.4. Data
This study is conducted within the scope of non-financial firms listed on Vietnam's
stock market from 2008 to 2015. 470 firms are selected (over about 700 listed firms), with a
total of 3760 observations (= 470 x 8).
2.3. Analysis and result discussion
2.3.1. Data description
2.3.1.1. Number of firms divided in each stock exchange
Table 2.16. Number of firms divided in each stock exchange

Number of
observation
2064

Number of
firms
258

HOSE

1696

212

45.1

Tổng

3760

470

100

Stock exchange
HASTC

Percent
54.9

2.3.1.2. Statistics of the number of firms classified by sector, industry group, industry, and
sub-industry
In this section, the thesis presents the statistics of the number of firms classified by
sector, industry group, industry, and sub-industry.
2.3.2. Descriptive statistics
(i). Dependent variable
Table 2.22. Dependent variable
Min

Max

Mean

Std

ROE

0.0016

20.18

0.147

0.34

Risk

0.002

0.72

0.186

0.26

(ii). Business diversification
Table 2.23. Business diversification
Uit

Min

Max

Mean

Std


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RB_DIV

Bit

0.00

1.15

0.79

0.42

UB_DIV

Bit

0.00

1.01

0.45

0.33

2.3.3. Correlation matrix analysis
2.3.4. Regression results
2.3.4.1. Regression results and SEM model tests
It can be concluded that the model is overall consistent with market data. Also, the
study conducts a homoscedasticity test and a normal distribution test to analyze the consistency
of the model. The test results (item vi and vii) give the P-value of the two tests less than 0.05,
so these imply that the structural model encounters both problems: heteroscedasticity and nonnormal distributions of residuals.
2.3.4.2. GSEM estimation results
As mentioned above, SEM model regression has encountered two problems; then the
regression results are not biased but inconsistent. We propose GSEM model combined with
robust estimation techniques to replace the original model. The regression coefficients of the
GSEM model are not different from the ones of SEM model but more robust than SEM model.
The results of GSEM model described below:
Figure 2.28. Summary of GSEM estimation
Expectation Coef.

Robust
P>z
Std.Err.

+

-0.00088

0.0009

0.33

+

0.00013

0.0004

0.76

0.00007

0.0019

0.97

-0.03295(***)

0.0120

0.01

0.00468(***)

0.0007

0.00

CCC

The ratio of operating costs to
revenue
Natural log of total assets
+
Cash conversion cycle
-

0.00000

0.0000

0.58

AS

Assets structure

-

-0.16050(***)

0.0260

0.00

AT

Assets turnover

+

0.04156(***)

0.0076

0.00

RB_DIV

Related business

+

0.09568(***)

0.0027

0.00

UB_DIV

Unrelated business

-

-0.12297(***)

0.0012

0.00

0.07000(**)

0.0313

0.03

Notation

Name of variables

Affecting ROE
Firm age
AGE
SG

Sales growth

CR

Current payment ratio

SGA_S
LNA

_cons
Affecting RISK


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CR

Current payment ratio

-

-0.00100

0.0013

0.45

0.02755(***)

0.0084

0.00

0.00000(**)

0.0000

0.23

0.01049(**)

0.0051

0.04

P_B

The ratio of operating costs to
+
revenue
Interest Coverage Ratio
Price to book ratio
-

LNA

Natural log of total assets

-

0.00014

0.0005

0.78

CCC

Cash conversion cycle

+

0.00000

0.0000

0.72

OCF_S

Operating cash flow ratio

-

-0.00976(**)

0.0049

0.04

AT

Assets turnover

-

-0.00395

0.0053

0.45

RB_DIV

Related business

+

0.00678(***)

0.0019

0.00

UB_DIV

Unrelated business

-

-0.00376(***)

0.0009

0.00

0.54440(***)

0.0169

0.00

SGA_S
EBIT_I

_cons
2.3.4.3. Discussion

Based on the results of the regression, the thesis discusses the effect of RB_DIV and
UB_DIV on performance and risk as follows:
Firstly, the impact of RB_DIV, UB_DIV on ROE and RISK is opposite (RB_DIV
affects ROE positively whereas UB_DIV is the opposite, RB_DIV has a positive effect on RISK
while UB_DIV is the opposite). This demonstrates that RB_DIV and UB_DIV will result in
various outcomes for the firm's operations.
Secondly, the impact of RB_DIV and UB_DIV on ROE and RISK is a trade-off.
However, the trade-offs may not be commensurate.
Thirdly, regarding the impact on ROE, the marginal impact of UB_DIV is higher than
that of RB_DIV and vice versa. This is also consistent with about 78.5% of the previous
research.
Finally, regarding factors affecting RISK, the marginal impact level of RB_DIV is
higher than that of UB_DIV and vice versa.
2.4. Conclusion and recommendation
2.4.1. Conclusion
Firstly, the SEM estimation model in the thesis satisfies most of the required tests
except for two tests that are heteroskedasticity and normal distribution of residuals. From here,

the study recommends employing GSEM model for estimation.
Secondly, from the GSEM model, RB_DIV has a positive impact on ROE and RISK.
Conversely, UB_DIV has a negative impact on both ROE and RISK.
Thirdly, RB_DIV affects ROE positively.


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Finally, considering the impact of the variable UB_DIV on ROE, the regression
coefficient of the variable UB_DIV is negative.
2.4.2. Recommendation
Based on the results of the analysis, the thesis gives some recommendations related
to the business activities of firms as follows:
Firstly, if firms expand their business to related business, the ROE will be improved
but RISK will increase. Conversely, expanding the business to unrelated busines will reduce
RISK but also reduce ROE. If the core business of the business is high risk, the business can
consider the business diversification in the unrelated sectors to minimize RISK and accept the
return as ROE will reduce. If the business sector tends to go down or have a low level of risk,
then the business should expand the business to related industries.
Secondly, on the whole, the impact of the two types of diversification to ROE and
RISK is significant, but the tradeoff is not symmetrical. Thus, firms in the normal business
condition should be expanded to related business.
2.4.3. Limitations and further research


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CHAPTER 3. THE IMPACT OF ASSET INVESTMENT DIVERSIFICATION ON
PERFORMANCE AND RISK
3.1. Literature review
3.1.1. Asset investment diversification definition and measurement
3.1.1.1. Asset investment diversification definition

(i) Related asset investment diversification (RADIV): Investments in assets that
generate revenue classified as the same 2-digit SIC level but not classified as the same 3-digit
SIC level with the primary business.
(ii) Unrelated asset investment diversification (UADIV): Investments in assets that
generate revenue not classified as the same 2-digit SIC level as the primary business.
3.1.1.2. Asset investment diversification measurement
(i). Related assets:
𝑛

1
𝑅𝐴_𝐷𝐼𝑉 = ∑ 𝑝𝑟 log 2 ( )
𝑝𝑟
𝑟=1

Of which: r is the rth business industry is invested and this is related to the main
business, “pr” is the ratio of a related asset to total assets.
(i). Unrelated assets:
𝑛

1
𝑈𝐴_𝐷𝐼𝑉 = ∑ 𝑝𝑢 log 2 ( )
𝑝𝑢
𝑢=1

Of which: u is is the uth business industry is invested, and this is unrelated to the
primary business, “pu” is the ratio of an unrelated asset to total assets.
3.1.2. The link between ADIV and BDIV
In the area of financial management, there are four main types of decisions: (i)
financing decision, (ii) asset investment decision, (iii) asset management decision, and (iv) profit
distribution decision. Financing decisions relate to how to find the source of funds, the amount

of capital, the cost of capital, the maturity of the capital, and the structure of the capital used to
invest in assets. Decisions on asset investment involve using of financial capital to invest in
assets that generate revenue. Asset management decisions concern about how to use asset
structure effectively, which related to short-term assets and long-term assets management. The
decision to divide the profit is whether the business decides to distribute the profit such as cash
dividend for shareholders or retained earnings for future investment. Firm diversification does
not fall outside this decision flow. On the financing side, a firm can make decisions regarding


15
the diversification of capital supply. In terms of asset investment, a firm can diversify different
types of assets to generate revenue. Alternatively, in the business aspect, business diversification
involves expanding business activities.
It is possible to model this relationship as follows:
Figure 3.1. The relationship between management decisions and diversifications

The three aspects of diversification place a firm in different decision-making choices
and these decisions can have a specific impact on the performance and risk of the firm.
From here, two hypotheses are proposed as follows:
Hypothesis H2.1: Diversification of related assets will increase the diversification of
related business.
Hypothesis H2.2: Diversification of unrelated assets impacts positively to the
diversification of the unrelated business, but this effect is weaker than the effect of related asset
diversification on related business diversification.
3.1.3. The relationship among ADIV, performance and risk
3.1.3.1. ADIV and performance
(i). Theories on the effect of ADIV on performance
Based on the theory of investment behaviour of firm, Rumelt (1974) build the "escape
hypothesis" to explain the phenomenon of firm diversification and the relationship of
diversification to performance. Accordingly, when the current business industry is not attractive

enough or the competition is fierce, firms will find ways to "escape" from the current industry
by investing in other types of assets to have the opportunity to receive higher profit. Some recent
studies, such as Hutzschenreuter and Gröne (2009), also agree with Rumelt (1974), they
demonstrate that firms tend to invest assets abroad when domestic competition becomes fiercer.
Also, following theory of resource-based view (Wernerfelt's, 1984 and Barney, 1991),
we realize that if a firm converts available resources into assets related to the existing business,
the conversion will become easier. It is due to certain similarities in the characteristics of new


16
(related) assets to existing assets (invested in core business). Easy conversions help firms save
transition costs and time so that firms can make better performance. Conversely, when firms
invest in assets unrelated to the primary industry, it will take more time and costs to convert. It
is because firms do not have much experience and knowledge to manage and operate new
unrelated assets. Spending too much time and money can cause firms to miss opportunities or
to delay new entrances and to reduce performance.
From the above contents, this study proposes research two hypotheses about the
impact of asset diversification on business performance as follows:
Hypothesis H2.3: Related assets diversification tend to improve business
performance.
Hypothesis H2.4: Unrelated assets diversification can reduce business performance.
(ii). Empirical evidence on the impact of BDIV on performance
In limited understanding, the thesis found no empirical research that refers to the
impact of ADIV on performance and this can be considered as a new point of the thesis.
3.1.3.2. ADIV and Risk
(i). Theories on the effect of ADIV on risk
Bettis and Hall (1982) study on the relationship between business diversification and
accounting risk. They state that related diversification has a lower effect on accounting risk than
unrelated diversification. Lubatkin and Chatterjee (1994) research the impact of business
diversification on the specific and systematic risk of a firm. They argue that portfolio theory

may not be applied to all cases of the impact of business diversification on risk; notably, the
impact of business diversification on the specific risk (unsystematic risk). They conclude that
related diversification reduces unsystematic risk; conversely, unrelated diversification has a
positive effect on this risk. Their conclusion is contrary to the theory of portfolio. They explain
that firms diversifying into related industries own some synergistic interrelationship (tangible
and intangible interrelationship), so that specific risk is reduced. On the contrary, when firms
expand their business into unrelated industries, they will lack internal relationships, and it will
lead to the increase in unsystematic risk.
From this point of view, the study suggests the relationship between business
diversification and bankruptcy risk as follows:
Hypothesis H2.5: The risk of bankruptcy of the firm is likely to increase as the firm
broaden its business to related diversification.
Hypothesis H2.6: The bankruptcy risk of a firm might decrease if the firm diversifies
into unrelated business.
(ii). Empirical evidence on the impact of BDIV on performance


17
In limited understanding, the thesis found no empirical research that refers to the
impact of ADIV on risk and this can be considered as a new point of the thesis.
3.1.4. The links among ADIV, BDIV, performance and risk
Figure 3.4. The links among ADIV, BDIV, performance and risk

In these relations, ADIV affects performance and risk via the mediating effect of
BDIV.
3.2. Methods
3.2.1. Empirical model
Figure 3.5. Research model 2

3.2.2. Variable measurement

3.2.2.1. Dependent variable
Variables are measured as described in topic one.


18
3.2.2.2. BDIV and ADIV measurement
Measurement of BDIV was described in topic one. ADIV is measured as follows:
(i). Related assets:
𝑛

1
𝑅𝐴_𝐷𝐼𝑉 = ∑ 𝑝𝑟 log 2 ( )
𝑝𝑟
𝑟=1

(i). Unrelated assets:
𝑛

1
𝑈𝐴_𝐷𝐼𝑉 = ∑ 𝑝𝑢 log 2 ( )
𝑝𝑢
𝑢=1

3.2.2.3. Control variable
Control variables affecting the two output variables (performance and risk) were
identified in topic one.
2.3.2.3. Estimation
With the proposed theoretical and empirical model of research, the study used
RB_DIV and UB_DIV as two mediators. So this model is also known as the mediation model
or path model which is a kind of SEM (Stata, 2015).

3.2.4. Data
Described in Chapter 2.
3.3. Analysis and result discussion
This analysis will begin with statistical analysis describing variables as well as
regression. The study will then conduct a discussion based on the regression results.
3.3.1. Descriptive statistics
3.3.2. Regression results
3.3.2.1. Regression results and SEM model tests
This study implements SEM regression analysis; then we perform the necessary tests
such as (i) good-of-fitness test, (ii) homoscedasticity test, and (iii) normal distribution of the
residual test. The thesis finds that SEM fails to satisfy homoscedasticity test and normal
distribution of the residual test. Hence, this research will employ GSEM to replace SEM.
3.3.2.2. GSEM estimation results
As mentioned above, SEM model regression has encountered two problems; then the
regression results are not biased but inconsistent. We propose GSEM model combined with


19
robust estimation techniques to replace the original model. The regression coefficients of the
GSEM model are not different from the ones of SEM model but more robust than SEM model.
The results of GSEM model described below:
Figure 3.6. Summary of GSEM estimation
Notation

Name of variables

Affecting ROE
RB_DIV Related business

Expectation Coef.

Robust
Std. Err.

P>z

+

0.095471

0.0028

0.000

UB_DIV

Unrelated business

-

-0.122959

0.0012

0.000

RA_DIV

Related assets

+

0.025516

0.0079

0.001

UA_DIV

Unrelated assets

-

0.016931

0.0130

0.193

AGE

Firm age

+

-0.000849

0.0009

0.351

SG

Sales growth

+

0.000162

0.0004

0.700

CR

Current payment ratio

0.000197

0.0019

0.918

-0.033490

0.0120

0.005

0.004662

0.0007

0.000

CCC

The ratio of operating costs to
revenue
Natural log of total assets
+
Cash conversion cycle
-

-0.000001

0.0000

0.596

AS

Assets structure

-

-0.160113

0.0259

0.000

AT

Assets turnover

+

0.040105

0.0076

0.000

SGA_S
LNA

Affecting RISK
RB_DIV

Related business
Unrelated business

+

0.006920

0.0019

0.000

UB_DIV

-

-0.003736

0.0009

0.000

RA_DIV

Related assets

+

0.010889

0.0055

0.050

UA_DIV

Unrelated assets

+

0.061860

0.0091

0.000

CR

Current payment ratio

-0.000997

0.0013

0.453

0.026354

0.0083

0.002

0.000000

0.0000

0.259

P_B

The ratio of operating costs to
+
revenue
Interest Coverage Ratio
Price to book ratio
-

0.010485

0.0051

0.038

LNA

Natural log of total assets

-

0.000112

0.0005

0.825

CCC

Cash conversion cycle

+

0.000000

0.0000

0.730

OCF_S

Operating cash flow ratio
Assets turnover

-

-0.010195

0.0049

0.038

-

-0.005265

0.0052

0.314

+

-0.036146

0.1720

0.834

SGA_S
EBIT_I

AT

Affecting UB_DIV
UA_DIV Unrelated assets
Tác động tới RB_DIV


20
RA_DIV

Related assets

+

0.091767

0.0470

0.051

3.3.2.3. Discussion

Based on the results of the regression, the thesis discusses the effect of ADIV on BDIV
UB_DIV, ROE, and RISK as follows:
First, regarding structural impact, the RA_DIV variable has a direct and indirect effect
on ROE and RISK. In this case, the RB_DIV has become the mediating variable that transmits
the impact of RA_DIV on ROE and RISK. In contrast, UA_DIV does not show the structural
impact to both ROE and RISK because UB_DIV does not become the mediator transmitting
UA_DIV's impact on the ROE and RISK.
Second, the effect of RA_DIV on ROE and RISK is a trade-off. RA_DIV has a
positive impact on ROE, but in return is RISK. However, this tradeoff is not significant when
the coefficient of RA_DIV on RISK is quite low (1.063%). In contrast, the impact of UA_DIV
on ROE and RISK shows no a trade-off. UA_DIV has a positive effect on RISK, but this does
not show any statistically significant effects on ROE.
Third, regarding the overall impact on ROE. The magnitude impact of RA_DIV is
greater than that of UA_DIV (3.37% vs. 0.00%).
Fourth, in terms of total marginal impact on RISK. The magnitude of the impact of
RA_DIV is higher than that of UA_DIV (1.063% vs. 0.62%).
Final, related to marginal impact level, RA_DIV has a positive effect on RB_DIV
whereas UA_DIV does not show any effect on UB_DIV.
3.4. Conclusion and recommendation
3.4.1. Conclusion
Firstly, the SEM estimation model in the thesis satisfies most of the required tests
except for two tests that are heteroskedasticity test and normal distribution of residuals test.
From here, the study recommends employing GSEM model for estimation.
Secondly, regarding the structural impact of RA_DIV on ROE, the thesis explores the
direct impact of RA_DIV on ROE and the indirect impact of RA_DIV on ROE through
RB_DIV. RA_DIV has a statistically significant direct impact on ROE with a marginal impact
of 0.025.
Thirdly, the thesis also evaluates the structural effect of UA_DIV on ROE. Regarding
direct impact, the coefficient of UA_DIV is not statistically significant, which means that there
is no direct impact on the model. From the angle of indirect impact, the effect of UA_DIV on

UB_DIV is also not statistically significant. Thus, the total impact of UA_DIV on ROE is zero.
The thesis also investigates the structural effect of UA_DIV on RISK, in which the direct effect
is positive and statistically significant (equal to 0.062), but the indirect effect level is zero. As a
result, the total impact of UA_DIV on RISK is equal to the level of direct impact.


21
Finally, the impact of RA_DIV on ROE and RISK is on a trade-off. ROE has a
positive impact on ROE, but RISK may be increased.
3.4.2. Recommendation
Based on the results of the analysis, the thesis gives some recommendations related
to the business activities of firms as follows:
First, to obtain better returns in the short term and at the same risk of bankruptcy,
firms should focus on RADIV. Increasing RA_DIV also increases RB_DIV then increase ROE.
Reducing UADIV does not reduce the ROE in the short run but reduces RISK.
Second, in the long run, the impact of the investment may change the structural impact
to ROE and RISK, especially the impact of UA_DIV. Delay effect may occur in the model.
Therefore, firms need to monitor the historical data of investment to decide whether to expand
or narrow each type of investment.
3.4.3. Limitations and further research


22
CHAPTER4. THE IMPACT OF CAPITAL DIVERSIFICATION ON ASSET
INVESTMENT DIVERSIFICATION, PERFORMANCE AND RISK
4.1. Literature review
4.1.1. Capital diversification definition and measurement
4.1.1.1. Capital diversification definition
Owner diversification (ODIV): a firm uses its equity capital with different
characteristics to form the equity.

Debt diversification (DDIV): a firm use different types of debt financing to form the
total debt.
4.1.1.2. Capital diversification measurement
Owner diversification
𝑛

1
𝑂. 𝐷𝑖𝑣 = ∑ 𝑝𝑜 ln( )
𝑝𝑜
𝑜=1

Debt diversification:
𝑛

1
𝐷_𝐷𝐼𝑉 = ∑ 𝑝𝑙 ln( )
𝑝𝑙
𝑙=1

4.1.2. The link between CDIV and ADIV
As mentioned, the thesis divides the capital diversification into two main components:
owner and debt diversification. It is difficult to determine which source of capital will finance
what kind of assets. However, based on research by Montgomery and Singh (1984),
Rajagopalan and Harrigan (1986), Lubatkin and O'Neill (1987), and Barton (1988), unrelated
business activities are risky therefore they are financed by equity. On the other hand, related
business activities are less risky, so they are likely to be financed by debt. Also, according to
Rauh and Sufi (2010), in all sources of capital, equity is the most sensitive information. Because,
based on the theory of agency, the agents easy to use equity to perform overinvestment for the
sake of themselves, or address risky investment. Meanwhile, the use of debt financing for risky
projects is difficult because creditors tightly control it.

From here, the thesis gives two research hypotheses:
Hypothesis H3.1: Debt diversification may increase RADIV.
Hypothesis H3.2: Owner diversification will have a positive effect on UADIV.
However, the level of its impacts will be lower than the impact of debt diversification.
4.1.3. The links among CDIV, performance and risk
4.1.3.1. ODIV, performance and risk


23
Agency theory
According to Jensen and Meckling (1976), the agent tends to allocate the resources of
a firm to serve their interests. Diversification is also a means of allocating resources of
representatives. Through this activity, the agent wants to consolidate the position or satisfy the
personal interest.
To address the "Agency problem I," Amihud and Lev (1981) suggest that the firm
needs to be financed by a large shareholder. The owner has more power to reject additional
proposals through diversification. Through empirical research (Amihud and Lev, 1981), it is
found that a firm with concentrated ownership generally decrease diversification. There are
some issues to consider as follows:
Firstly, the more dispersed shareholders, the more seriously "Agency problem I" will
appear;
Secondly, to solve the "Agency problem I," the firm needs to have a concentrated
ownership structure. However, the concentrated ownership has a twofold effect. There are
different types of shareholders; each has a different motivation. Therefore when the company
focuses on each type of shareholder, it will benefit from the characteristics of the shareholder
but will also receive disadvantage of this type.
Finally, in the context of diversification, firms have different sources of equity, it
means that firms disperse the right to make decisions. It will be difficult for owners to prevent
representatives’ decisions on diversification. This lead to the performance may decline, but the
risk of bankruptcy will be reduced since firms own various financing source.

Research hypothesis about the impact of CDIV on performance and risk:
Hypothesis H3.3: ODIV reduces the performance of the firm.
Hypothesis H3.4: The bankruptcy risk of the business will decrease as the firm
expands its equity financing.
4.1.3.2. The links among DDIV, performance, and risk
(i). Free cash flow theory and capital structure theory
Free cash flow theory
Conflicts of interest between shareholders and representatives increase as firms have
free cash flow (Jensen, 1986). When free cash flow occurs, the agency costs of free cash flows
also appear. It means that managers prefer using free cash flow to invest in projects for personal
interest although these projects are less effective for firms. The problem is how to prevent
managers from using this cash flow to invest in inefficient projects while still ensuring firm
growth. This is a problematic contradiction because using the entire free cash flow to pay
dividends leads to the firm having less money to invest and losing growth momentum in the
future, resulting in reducing dividends in the future and the stock price will fall. Meanwhile,