Corporate Diversification

CORPORATE DIVERSIFICATION AND FINANCIAL
PERFORMANCE
The corporate diversification and financial performance has been subject of many studies in
finance in last few decades. There are many definitions of corporate diversification. However
diversification word comes from the diverse, which means distinct and different that shows
discrepancy in the firm activities. When a firm operates in more than one business or industries,
it is called the diversified firm. Furthermore, diversification means increased activity of their
business scopes except their currently business. Many scholars defined diversification as firm
enters new sector, or new industry, or new segment or a new line of business. Diversification
has been a central topic in strategic management studies since the work of Ansoff. The costs
and benefits derived from the various diversification strategies have been examined mainly for
their impact on a firm’s value. Studies on the interaction between diversification and capital
structure became of interest because of their associated strategic implications regarding
corporate governance. Indeed, starting with the study of financial choices have been evaluated
because of the close interaction between capital structure and management choices. In the
1980s, other researchers, motivated by the connection between investment and financial
choices, highlighted the link between capital structure and diversification.
Santalo and Becerra (2008) argue that the effects of diversification are heterogeneous across
industries. That is, diversified firms might be valued at a discount in some industries, but trade
at a premium in others. Several recent studies examine the value impact of diversification
across the business cycle and conclude that corporate diversification becomes more efficient
when external capital markets are relatively inefficient and when the various segments of a
diversified firm would be financially constrained as single-segment firms (e.g., Dimitrov and
Tice, 2006; Yan et al., 2010; Hovakimian, 2011). Under these circumstances, external capital
supply will be highly restricted, enabling diversified firms to benefit from their internal capital
markets, especially during recessions and exogenous (industry) shocks. During the financial
crisis of 2007 to 2009, Kuppuswamy and Villalonga (2010) find that the relative value of
diversified firms increased significantly. The findings indicate that financial constraints and the
state of the capital market apparently continue to play a key role in determining the value of
diversification, and that there should be a dynamic change in the diversification discount or
premium over time.

Moreover, according to Ansoff (mathematician, 1957), corporate diversification classified into
two groups, product diversification (related and unrelated) and international (geographic)
diversification. Product diversification means a firm produces more than one kind of product
and international diversification means a firm acts in abroad markets. Also, product
diversification can be divided into three dimensions, which are diversification degree,
diversification type and diversification mode.
Diversification degree
It introduced through three main methods of computing based on the business count
measurement which are: Standard Industrial Classification (SIC) codes, Herfindahl index and
Entropy index. In addition, there is no agreement of which measurement is the best one for
determining corporate diversification.
SIC codes are a system for identifying a business according to its activity, which is the easiest
way for counting diversification and Martin and Sayrak (2003) noted that there is a problem
for using the SIC codes. They expressed if a firm operates in many industries, SIC codes cannot
explain which industry is more important than others for the firm. For solving this problem, it
is suggested to use Herfindahl index, which was introduced for firm’s concentration counting
(Berry, 1971; McConnell, Brue, & Flynn, 2009; McVey, 1972).
Herfindahl Index: is defined as the total square of the sales share of each product of the firm
as noted in Equation
H= S; 0 H ≤1
Where, Si is the sales share of product i in the firm in terms of percentage and n is the number
of product units of the firm. When this index is near zero, it means that the firm is diversified.
The high Herfindahl index is, the more focus the firm is (Berry, 1971; McVey, 1972). This
index also is known as Herfindahl-Hirschmann index.
The last measurement is Entropy Index which was proposed primarily in physics; however, it
spread into other subjects. Jacquemin and Berry (1979) extended entropy index in
diversification researches. The index has three significant elements, which are different from

other indexes. The elements are the number of industry of firm’s activities, the amount of total
sales/assets divide across industry parts, and the third is that power of part of unrelated and
related diversification in a firm. Park and Jang (2011) said the index is objective, continues and
decomposable. In addition, Chatterjee and Blocher (1992) reported the entropy index for
diversification is better than other diversification measurements. Therefore, these privileges
cause the wide range of using entropy index (C. J. Chen & Yu, 2011; Park & Jang, 2011). The
total entropy index is measures as:
Total Entropy Index:
E ∑ Pln (1/P)
Where, Pi is the share sale of segment i in total sales of the firm and n is the number of firm’s
segments. As it mentioned, the main privilege of entropy index is that it can determine the
score of related and unrelated diversification in the firm (refer to (Jacquemin & Berry, 1979)).
In addition, if total entropy is near zero, it means that firm is focus and becomes greater with
increasing levels of diversification, and the maximum and minimum of Entropy is 0 E ln n.
Diversification type
Wringley (1970) defined diversification type based on relatedness within the firm’s portfolio
in four majors which are single, dominant, related and unrelated diversification. Rumelt (1974)
extended these four parts into seven parts, which are single dominant, dominant vertical,
dominant constrained, dominant linked-unrelated, related constrained, related linked and
unrelated business. However, he said sometimes it is difficult to count these ratios because of
the firm’s incomplete reports. In addition, he stated that related diversification could transfer
core skill to new businesses; however, unrelated diversification could not. Additionally, some
scholars used another classification with mix Wringley and Rumelt‘s ideas together which are
single, moderately diversified and highly diversified (Li, 2004; Pandya & Rao, 1998).
Diversification mode
Scholars define mode of diversification as internal development and merger and acquisition
(NA Berg, 1973; Lamont & Anderson, 1985; R. Pitts, 1976; R. A. Pitts, 1977; Yip, 1982).
Internal development takes advantage of interior resources and core competency for
establishing a new business (Datta, et al., 1991). In contrast, if a firm likes to diversify via
merger and acquisition, it must pay attention to the weaknesses and strengths of a target firm
(N. Berg & Pitts, 1979).

International diversification
International diversification means a firm acts in the market which is not in its country. This
strategy is a growth strategy that has a major effect on firm performance. This effect is stated
by Ansoff (1965) as growth strategy.
As a matter of fact, international diversification offers several advantages to firms. Buhner
(1987) argued that international diversification offers prospective market opportunities, which
gives firms the opportunity for greater growth. The most accepted argument for international
diversification has been developed on the theoretical assumption that firms exploit the benefits
of internalization in international markets (Caves, 2007; Hymer, 1976). Internalization of
markets has advantages such as economies of scale, scope, and learning (Ghoshal, 1987; W.
Kim, Hwang, & Burgers, 1989; W. C. Kim, Hwang, & Burgers, 1993; Kogut, 1993), and
sharing core competencies among different business segments and geographic markets (Hamel,
1991).
Firms with strong competencies that are developed at home can utilize these in international
markets (Bartlett & Ghoshal, 1999). Thus it is argued that the higher the involvement of a firm
in international markets is, the higher will be the exploitation of tangible and intangible
resources, which is expected to lead to higher performance (Hymer, 1976).
In addition, multinational firms have the opportunity to integrate their activities across borders
by standardizing products, rationalizing production, and/or allocating their resources more
efficiently and effectively (Kobrin, 1991). Furthermore, multinational firms can gain additional
competitive advantages by exploiting market imperfections (such as a less competitive
environment) and cross-border transactions (such as transfer pricing), and can also achieve a
greater bargaining power with increased size (Sundaram & Black, 1992). All of these
arguments support the view that a positive, linear relationship exists between international
diversity and performance. Although some studies have demonstrated a positive relationship
(Daniels & Bracker, 1989; Gomes & Ramaswamy, 1999; Grant, 1987; Haar, 1989), other
studies have shown either a negative relationship or no relationship at all (Siddharthan & Lall,
1982). Most of these studies have assumed that the relationship between international
diversification and performance is linear (Gomes & Ramaswamy, 1999).

However, some of research has examined a nonlinear relationship between multinationality
and performance, and has argued for a theoretical rationale to justify their position (Gomes &
Ramaswamy, 1999; M. A. Hitt, Hoskisson, & Kim, 1997; Kotabe, Srinivasan, & Aulakh, 2002;
Tallman & Li, 1996). These studies have found an inverse U-shaped relationship between
multinationality and firm performance, where performance increases up to a certain point, and
then levels off.
The Theory of Why Firm Diversify
The main theories about why firm diversify, are as agency theory, free cash flow theory,
efficiency theory, resource based theory and market power theory.
Agency Theory: Jensen and Meckling (1976) define that the conflict between owner
(principal) and manager (agent) of the firm. In addition, the theory states that diversification is
driven by managers' interests such as employment risk-reduction, power, prestige and high
compensation (Ahmad, Ishak, & Manaf, 2003). Whilst, shareholders can diversify their
portfolios at low cost to balance their investment risk and therefore they might not favor
corporate diversification strategies. Due to the nature of corporate structure, shareholders might
be forced to accept the firms’ diversification strategy although it might not suit their risk and
return profiles. Hence, agency theory would predict a negative relationship between
diversification and firm value.
Free Cash Flow Theory: the theory is explained by Jensen (1986) that anticipate which type
of diversification create or destroy value. Managers can spend free cash flow (FCF) in
profitable investment opportunities or paying out to shareholders. So, the theory states
managers with unused borrowing power and large FCF are more probable to undertake low-
benefit or even value-destroying mergers.
Efficiency Theory: The efficiency theory suggests that diversification occurs once managers
are expected to make some synergies (Mat nor, 2003). These synergies are such as financial
synergy (unrelated diversification) and operational synergy (related diversification).
Resource based Theory: Penrose (1959) developed resource based theory which states every
firm has remarkable resources that are known as its competitive advantages and firm can use
some unused capacities by applying diversification strategy. This view implies that a firm can
be more profitable where applying the unused resources (C. Montgomery, 1994) where these
resources of firm has differences in specificity (C. A. Montgomery & Werner felt, 1988).
Market Power Theory: this theory stemmed from a fear of market being monopolized (C.
Montgomery, 1994). Because, diversified firms act in many geographic market and produce
many products so its market power increases (Edwards, 1955). Furthermore, when a firm

diversifies related diversification, it increases the market power. By having market power, it
can stabilize the position and use predatory pricing to improve its profitability. Researchers
hypothesized that diversification increases market power; then, more profit can gain for the
diversified firm (Caves, 1981; R. A. Miller, 1973)
Studies on developed countries
Bobillo et al. (2010) - examined the association between international diversification and firm
performance. Based on a sample of manufacturing firms in five countries as Germany, France,
the United Kingdom, Spain, and Denmark, the results showed that the mix of internal and
external competitive advantages affected the relation between international diversification and
firm performance.
Some scholars did a research in 308 restaurant firms from USA (Park & Jang, 2011). They
utilized Entropy index as corporate diversification and ROA, ROS and risk of profitability as
financial performance indicators. They discovered that at a certain level, related diversification
declines profitability. On the other hand, at a certain level, unrelated diversification increases
profitability. They concluded on the volatility of accounting profitability that at a certain level,
related diversification increases volatility and unrelated diversification decreases it. In addition,
they found these firms did not profit from a low level of related diversification.
Studies on developing country
Lins and Servaes (2002) done their studies in one thousand firms from some emerging markets
such as Hong Kong, India, Indonesia, Malaysia, Singapore, South Korea, and Thailand in 1995.
They found diversified firms less profitable than focus firms. In addition, they concluded there
is a discount for industrial group firms and for diversified firms which has a ten to thirty percent
management ownership concentration. Finally, the results did not support internal capital
market efficiency in economies with severe capital market imperfections.
Chakrabarti et al. (2007) examined the effect of corporate diversification on performance for
some firms acting in stable period and economy shock. They did their research in six Asian
countries between 1988 and 2003. They concluded that diversification has a negative effect on
performance in more developed institutional environments; although, in least developed
environments there is an improving performance. Even though in least developed institutional
environments, diversification proposes limited advantages once an economy-wide shock
strikes. As a result, they found out that the consequent of diversification is influenced with
institutional environments, economic stability and affiliation in business groups.
Chen and Yu (2011) developed several hypotheses based on the agency theory and tests the
relationships among managerial ownership, corporate diversification, and firm performance

using a sample of 98 firms listed on the Taiwan Stock Exchange. The results show a U-shaped
relationship between managerial ownership and corporate diversification. Moreover, corporate
diversification is positively associated with short-term firm performance and bears no
relationship with mid-term firm performance, while firms engaged in unrelated diversification
outperform those engaged in related diversification.
Other researchers examined diversification and performance of 70 Malaysian firms from years
2001 to 2005 (Daud, Salamudin, & Ahmad, 2009). Their independent variable was number of
segments, the dependent variables were ROA and market measure and the control variables
were risk, size, inflation and leverage. They showed firms with focused strategy can achieve
high performance and financial ratio is affected by risk and size of firms. In addition, firms at
low risk usually get high returns.

ADITYA BIRLA NUVO
Aditya Birla Nuvo, an AV Birla Group company traces its origin to a modest beginning with
the acquisition of Indian Rayon Corporation Limited, a viscose filament yarn manufacturing
unit, in 1963. Aditya Birla Nuvo is now a diversified conglomerate and the platform that has
launched many new businesses for India. Aditya Birla Nuvo has a balanced portfolio of
traditional and new age businesses under its fold, ranging from textiles to life insurance.
The Aditya Birla Group is in the league of Fortune 500. It is anchored by an extraordinary force
of 130,000 employees, belonging to 25 different nationalities. In India, the Group has been
adjudged 'The Best Employer in India and among the top 20 in Asia' by the Hewitt–Economic
Times and Wall Street Journal Study 2007.
Over 50 per cent of the Group's revenues flow from its overseas operations. The Group operates
in 25 countries: India, UK, Germany, Hungary, Brazil, Italy, France, Luxembourg,
Switzerland, Australia, USA, Canada, Egypt, China, Thailand, Laos, Indonesia, Philippines,
Dubai, Singapore, Myanmar, Bangladesh, Vietnam, Malaysia and Korea.
The razor sharp focus on each business has made it a leading player in most segments, including
viscose filament yarn, carbon black, branded garments, agri business, textiles and insulators.
Over the past few years, Aditya Birla Nuvo, through its subsidiaries and joint ventures, has
made successful forays into life insurance, telecom, business process outsourcing (BPO), IT
services, asset management and financial services.
Powered by an intellectual capital of over 37,000 employees and an optimum mix of revenue
and profit streams, the company is in a strong position to invest in high growth businesses to
maximise long–term shareholder gains.

Business area of the company includes:
Viscose Filament Yarn – Indian Rayon – Indian Rayon, a major player in the Indian viscose
filament yarn business, is the second largest producer of viscose filament yarn (VFY) in India
with a 30 per cent domestic market share.
Garments – Madura Garments – Indian Rayon, a major player in the Indian viscose filament
yarn business, is the second largest producer of viscose filament yarn (VFY) in India with a 30
per cent domestic market share.
Carbon Black – Hi–Tech Carbon – –Tech Carbon, the carbon black business of Aditya Birla
Nuvo, is the second largest producer of Carbon Black in India, covering 33 per cent of the
domestic market share.
Agri solutions – Indo Gulf Fertilisers - It is the first company to introduce the principles of
Six Sigma in the agricultural fields, Indo Gulf aims at providing complete agri solutions to
farmers with unique value–added products and services.
Textiles – Jaya Shree Textiles – A leading player in the domestic linen and worsted yarn
segment, Jaya Shree Textiles has revolutionised the Indian textile market by popularising linen
across a wide customer base with the brand Linen Club.
Insulators – Aditya Birla Insulators– Aditya Birla Insulators, India's largest manufacturer of
high–performance insulators, has leveraged the power of reliability, to provide world–class
insulating solutions to the power industry.

Joint ventures and subsidiaries:
Idea Cellular Limited, the fifth largest mobile telephony service provider in India
Birla Sun Life Insurance, one of the leading life insurance companies in India
Birla Sun Life Asset Management, one of the leading asset management companies in India
Aditya Birla Minacs Worldwide Limited, among the top five BPO players in the country by
revenue size.
Achievements/ recognition:
Aditya Birla Nuvo won the most admired company of the year at Clothing Manufacturers
Association of India (CMAI) Awards 2008 under domestic category.
In the carbon black segment it was awarded TPM Excellence award (II Category) from JIPM,
Japan.
Aditya Birla Insulators won the Golden Peacock National Quality Award in the manufacturing
category.
In the textiles segment it received the first prize by the Government of India for best energy
conservation measures.
In the BPO segment it was awarded Innovation Award by CIO magazine 2007.

CHAPTER 2
REVIEW OF LITERATURE

Meysam Doaei (2012) said that the impact of corporate diversification on financial
performance has been subject of some studies from the past. In addition scholar found positive
or negative relationships between the two variables. However there are some theories and
motivations which explain the part of the relationships that state in this paper. In this paper we
try to show measurement of diversification and summary of related studies.
Maurizio La Roca (2009) said that previously, empirical financial studies paid little attention
to the role of diversification strategy on financial choices. The aim of the present study is to
analyse the financing strategies of multi business firms, suggesting the relevance of sorting the
diversification phenomena into its related and unrelated components. The implications of our
findings are very relevant in that they explain earlier contradictory results on capital structure
determinants. The degree of product specialization/diversification and the direction of
diversification (related or unrelated) translate into different corporate financial behaviours. In
particular, the two types of diversification- related or unrelated, had opposite effects on debt.
Specifically, a related diversification strategy, which is associated with lower debt ratios, has
a negative influence on leverage. By contrast, unrelated diversity, which is associated with
higher debt usage, has a positive effect on debt. According to the coinsurance effect and the
transaction-cost hypothesis, unrelated-diversified firms have a higher debt capacity and can
assume more debt as a source of finance. Moreover, the capital-structure decisions of unrelated-
diversified firms seem to be strictly aimed at reaching their target optimal debt level—a
behaviour that is consistent with the trade-off hypothesis. On the other hand, related-diversified
firms adjust more slowly towards their target capital structure.
Rebecca N. Hann, Maria Ogneva and Oguzhan Ozbas (2012) said by researching that we
examine whether organizational form matters for a firm’s cost of capital. Contrary to
conventional view, we argue that coinsurance among a firm’s business units can reduce
systematic risk through the avoidance of countercyclical deadweight costs. We find that
diversified firms have on average a lower cost of capital than comparable portfolios of
standalone firms. In addition, diversified firms with less correlated segment cash flows have a
lower cost of capital, consistent with a coinsurance effect. Holding cash flows constant, our
estimates imply an average value gain of approximately 5-6% when moving from the highest
to the lowest cash flow correlation quintile.

Andre P. Liebenberg discussed that they investigate the effects of corporate diversification
using a sample of property-liability (P/L) insurers over the period 1995 to 2002. The richness
and consistency of our data set enables us to carefully test two alternative hypotheses regarding
diversification’s effect on firm performance. The strategic focus hypothesis predicts a negative
relation between diversification and performance while the conglomeration hypothesis predicts
a positive relation. They develop and test a model that explains performance as a function of
line-of-business diversification and other correlates. We consistently find that undiversified
insurers outperform diversified insurers. Our results indicate that diversification is associated
with a penalty of at least 1% of ROA or 2% of ROE. The diversification penalty is robust to
corrections for potential endogeneity bias, alternative risk measures, and an alternative
estimation technique. Our findings provide strong support for the strategic focus hypothesis.
With respect to our control variables we find that insurance groups underperform unaffiliated
insurers and that stock insurers outperform mutual.
Stefan Erdorf (2012) stated, we survey the recent literature on corporate diversification. How
does corporate diversification influence firm value? Does it create or destroy value? While,
until the beginning of this century, the predominant thinking among researchers and
practitioners was that corporate diversification leads to an average discount on firm value,
several studies cast doubt on the diversification discount. In the last decade, there has been no
clear consensus of whether there is a discount or even a premium on firm value. However, the
recent literature concludes that the effect on value differs from firm to firm, and that corporate
diversification alone does not drive the discount or premium. Rather, the effect is
heterogeneous across certain industry settings, economic conditions, and governance
structures.
Andreea Apostu (2010): the role of diversification strategies in financial choices has received
little attention in previous empirical financial studies. The aim of this paper is to study the
effect of corporate diversification strategies on firm capital structure using a panel data analysis
for a sample of 232 European firms during the period 2004-2007. Theoretical and empirical
studies suggest that corporate leverage is positively related to diversification across product
lines but negatively related to geographic diversification. Some studies show that these
diversification strategies are complementary in generating debt usage. In the univariate
analysis, we find product diversified firms to be significantly more leveraged, larger, less risky,

less profitable and more diversified geographically. Multinational firms appear to be
significantly larger, riskier and more diversified across product lines. After controlling for firm
size, profitability, growth, assets tangibility and operating risk, we find that product and
geographical diversification do not have a significant influence on leverage.
Gordon M. Bodnar (1999) This paper examines the effect of geographic and industrial
diversification on firm value for a sample of over 31,000 firm-year observations of U.S.
corporations from 1984 1997. Consistent with the predictions of most theories, we find the
value of a firm with international operations is 2.7% higher than a comparable single-activity
domestic firm, while the value of a multiactivity firm is 6.0% lower than a comparable portfolio
of single-activity domestic firms. In addition, we demonstrate the existence of an omitted
variable bias in estimating the value effect of industrial diversification when failing to account
for geographic diversification when estimating. Sources of the value effects of both
dimensions of diversification are also investigated.
John D. Martin (2001) discussed that they survey the recent developments in the literature on
corporate diversification. This literature is voluminous, diverse, and quite old. To make the
task more manageable, we focus our attention on recent contributions to that subset of the
diversification literature that is in our judgment most influential in setting the agenda for
financial research. The study of diversification at the corporate level can be grouped into one
of two bodies of literature: cross-sectional studies of the link between corporate diversification
and firm value (i.e., the diversification discount) and longitudinal studies of patterns in
corporate diversification through time. The prevailing wisdom among financial economists
throughout much of the last decade has been that diversified firms sell at a discount and that
the level of corporate diversification has been trending downward. However, recent research
questions both these tenets and a number of studies now suggest that the diversification
discount is either not due to diversification at all, or may be a result of improper measurement
techniques. Furthermore, some researchers are now beginning to argue that previous attempts
to assess changes in the levels of corporate diversification through time is also flawed as a
result of biases built into the COMPUSTAT database in combination with the use of noisy
proxies for corporate diversification. D 2002 Elsevier Science B.V. All rights reserved.

Ugwuanyi Georgina this paper examines the relationship between excess value and excess
profitability using deposit money banks in Nigeria as focal points of the study. The study relied
on historic accounting data generated from financial (annual) reports and accounts of sampled
banks between the ten-year periods covered by the study. Borrowing from previous studies,
appropriate regression and correlation equations were formulated to measure the relationship
between excess value and excess profitability of Nigerian banks. The regression and correlation
analyses revealed that the correlation is positive and significantly different from zero. This
implies that there is significant relationship between excess value and excess profitability of
deposit money banks in Nigeria. Thus the study provides evidence that there is a significant
relationship between excess value and excess profitability of both diversified and standalone
banks
Ivan Pavić,(2010) described that although a number of authors have tried to investigate
different aspects of insurance industry, there is still little research done and evidence on the
performance effect of diversification in either life or non-life insurance industry. This is
especially true for the Croatian insurance industry. Therefore, the authors of this article find it
valuable to investigate the relationship between product diversification and performance. In
testing this relationship we employ different methods of financial performance and
diversification assessment.
Rebecca N. Hann Robert (2009) stated in this paper examines whether coinsurance arising
from corporate diversification affects a firm’s cost of capital. We develop a model in which
diversification reduces systematic risk and leads to a lower cost of capital. This coinsurance
benefit of diversification is decreasing in the cross segment correlation of cash flows. Using
measures of implied cost of capital constructed from analyst forecasts, we test and find support
for the model’s empirical predictions. We find that on average diversified firms have lower
implied cost of capital compared to portfolios of standalone firms. This difference decreases as
cross-segment cash flow and investment correlations increase. Overall, our results are
consistent with the coinsurance effect of diversification lowering the cost of capital.

Rebecca N. Hann (2012) explained, we examine whether organizational form matters for a
firm's cost of capital. Contrary to conventional view, we argue that coinsurance among a firm's
business units can reduce systematic risk through the avoidance of countercyclical deadweight
costs. We find that diversified firms have on average a lower cost of capital than comparable
portfolios of standalone firms. In addition, diversified firms with less correlated segment cash
flows have a lower cost of capital, consistent with a coinsurance effect. Holding cash flows
constant, our estimates imply an average value gain of approximately 5% when moving from
the highest to the lowest cash flow correlation quintile.
Singh Manohar (2003) research shows that corporate leverage is positively related to
diversification across product lines but negatively related to geographic diversification. Why
this difference occurs is an important empirical question since diversification appears to be
value destroying. After controlling for geographic diversification, asset turnover, and firm size
as well as other variables, we find that diversification across product lines is at best unrelated
to debt usage; it may be negatively related to debt usage in some instances.
Imed Eddine Chkir (2001) expressed that this study examines the relationship between the
capital structure of multinational corporations (MNCs) and their diversification strategy. Both
the international market (multi-country operations) and the product (multi-industry operations)
dimension of diversification are integrated into the analysis and a switching of regression
regimes methodology is employed that accounts for the bi-dimensional nature of the
diversification strategy pursued by MNCs. The model identifies four types of diversification
regimes. The results suggest that leverage increases with both international and product
diversification. It is also found that the combination of both types of diversification leads to
lower levels of bankruptcy risk. Although the role of the determinants of MNC capital structure
varies with the diversification strategy, there seem to be common determinants. In particular,
profitability and bankruptcy risks are negatively related to the debt ratio of MNCs.
Sheng-syan chen (2000): We provide international evidence on the level and value of
corporate diversification using a sample of 145 Singapore firms. We find that the level of
diversification is positively related to firm size and negatively related to the equity ownership
of outside block holders. However, we find no evidence that insider ownership has a significant
impact on the level of diversification. We find significant value loss from diversification only

for those firms with low managerial ownership, suggesting that value-reducing diversification
stems from agency problems. Outside block ownership does not have a significant impact on
the value of diversification. Thus, while outside block holders may act as a deterrent on the
level of diversification, there is no evidence that they can effectively reduce the agency
problems for those firms with low managerial ownership.

CHAPTER 3
RESEARCH METHEDOLOGY

A. OBJECTIVE OF THE STUDY
The general objective of this study is to evaluate the relationship that exists between corporate
diversification and firm performance in selected companies. While the specific objectives of
the study are to: 1) Examine the intents and/or objectives necessitating corporate diversification
by Indians companies; 2) Investigate the diversification Strategies of these companies; 3)
Appraise empirically the relationship between corporate diversification and financial
performance of the companies under study; and 4) To formulate recommendation regarding
corporate diversification and firm performance.
B. RESEARCH HYPOTHESIS
We have done hypothesis testing for both primary and secondary data
For the testing purpose, we need to take two hypothesis, namely, null hypothesis (Ho) and
alternative hypothesis (H1).
1. Using the primary data, we have tested the hypothesis on the awareness of jayasree textiles
based on gender.
Null Hypothesis (H0) = Gender and awareness of jayasree textile are independent.
Alternative Hypothesis (H1) = Gender and awareness of jayasree textile are not independent.
As the two variables taken are category variables, we have used chai square distribution.
2. Using the secondary data, we have tested the Hypothesis on the relationship of Sales
Turnover and Reported Net Profit.
Null Hypothesis (H0) = Sales Turnover and Reported Net Profit are independent.
Alternate Hypothesis (H1) = Sales Turnover and Reported Net Profit are not independent.
As the two variable taken are continuous data, we have used correlation analysis.

C. SAMPLE AND SAMPLING TECHNIQUES
A set of primary and secondary data were used for the analysis
The primary data was collected to understand the awareness among public regarding Aditya
Birla Nuvo and their Brand Jayasree Textiles.
For the purpose of the survey, 100 samples were collected. As the sample size is more than 30,
it can be called a large sample. While collecting the samples, simple random sample was used.
The secondary data were extracted from the balance sheet of Aditya Birla Nuvo
D. METHOD OF DATA COLLECTION
The primary data were collected by interviewing 100 customers of Aditya Birla Group. The
respondents were also ask to fill a questionnaire. The questionnaire contained questions about
the awareness regarding Aditya Birla Nuvo’s Brand and Jayasree Textile.
To understand the effect of the corporate diversification on the profitability of Aditya Birla
Group, Sales Turnover and Reported Net Profit of last 10 years (2005-2014), are used.
E. DATA ANALYSIS TOOL
Various tools are used to analyse both the primary and secondary data.
SPSS and MS-Excel are used for the univariate and bivariate analysis.
The univariate data and bivariate data are described in pic-charts and bar diagrams respectively.
For bivariate analysis, cross tabulation and rank correlation are used. In hypothesis testing, chi-
square distribution and correlation analysis are used.
F. LIMITATION OF THE STUDY
Time constraints were one of the limitations encountered in the case of the study.
Secondly, finance was yet another problem that put a check on the extent of investigation.
Finally there was the problem of inadequate information and unavailable material or
information for the study.

4.1. UNIVARIATE ANALYSIS
Gender
Table 4.1.a: Analysis of Gender
Figure 4.1.a: Pie-chart of Gender
Interpretation: The above table shows the numbers of total male and female respondents. It
is been observed from the survey that 53% of respondents are male and remaining 47% are
female. Majority of the respondents are male.
Male
53%
Female
47%
GENDER
Male Female
Options Frequency Percent
Male 53 53.0
Female 47 47.0
Total 100 100.0

Age
Table 4.1.b: Analysis of age.
Figure 4.1.b: Pie-chart of Age
Interpretation: The above table shows percentage of ages of respondents. We can say from
the above table and pie-chart that 30% of people are in the age group of 18-24, 44% of people
in the age group of 25-30, 22% of people in the age group of 30-45 and 4% of people in the
age group of 46-60.
18-24
30%
25-30
44%
30-45
22%
46-60
4%
AGE
18-24 25-30 30-45 46-60
18-24 30 30.0
25-30 44 44.0
30-45 22 22.0
46-60 4 4.0
Total 100 100.0

OCCUPATION
Table 4.1.c: Analysis of Occupation
student 26 26.0
self-employed 11 11.0
Businessman 28 28.0
Professionals 29 29.0
other 6 6.0
Total 100 100.0
Figure 4.1.c: Pie-chart of Occupation
Interpretation: The above table shows the percentage of Occupation of total respondents. It
is found from the survey that 26% of the total respondent are students, 11% of the total
respondent are self-employed, 28% of the total respondent are Businessman, 29% of the total
respondent are Professionals, and 6% of the total respondent are others.
student
26%
self-employed
11%
Businessman
28%
Professionals
29%
other
6%
Occupation
student self-employed Businessman Professionals other

Annual Income
Table 4.1.d: Analysis of Annual Income
<1 lacs 26 26.0
1-3 lacs 28 28.0
3-5 lacs 32 32.0
5-8 lacs 10 10.0
10 lacs> 4 4.0
Total 100 100.0
Figure 4.1.d: Pie-chart of Annual Income
Interpretation: The above table indicates the percentage of Annual Income of Total
respondents. From the survey it is found that the out of total respondent 26% of people’s
income are in below 1 lacs, 28% of people’s income are between in 1-3 lacs, 32% of people’s
income are in between 3-5 lacs, 10% of people’s income are in between 5-8 lacs and 10% of
people’s income are in above 10 lacs.
<1 lacs
26%
1-3 lacs
28%
3-5 lacs
32%
5-8 lacs
10%
10 lacs>
4%
ANNUAL INCOME
<1 lacs 1-3 lacs 3-5 lacs 5-8 lacs 10 lacs>

Have you ever heard about Jayasree Textile?
Table 4.1.e: Analysis of awareness of jayasree Textile
Figure 4.1.e: Pie-chart of jayasree Textile
Interpretation: The above table shows the awareness of jayasree textile .We get to know from
the survey that 47% of the respondent are aware about jayasree Textile and 53% of the
respondent are not aware about Jayasree Textile. It indicates that majority of respondent are
not aware of jayasree textile.
yes
47%no
53%
JAYASREE TEXTILE
yes no
yes 47 47.0
no 53 53.0
Total 100 100.0

Which product comes first in your mind by listening Aditya Birla
Nuvo?
Table 4.1.f: Analysis of First product comes in mind
Figure 4.1.f: Pie-chart of product comes first in mind
Interpretation: The above table shows the percentage of products that comes first in the mind.
It is been observed from the survey that 33% of the people prefer Idea as their first choice,
10% of people prefer Rayone, 26% of people prefer Birla Sun Life Insurance, and 31% of
people prefer pantaloons as their first choice.
Idea
33%
Rayone
10%
Birla sun life
insurance
26%
Pantaloons
31%
WHICH PRODUCT COMES FIRST IN YOUR MIND
Idea Rayone Birla sun life insurance Pantaloons
Idea 33 33.0
Rayone 10 10.0
Birla sun life insurance 26 26.0
Pantaloons 31 31.0
Total 100 100.0

What is your feedback on Aditya Birla Nuvo's product?
Table 4.1.g: Analysis of Feedback
Table 4.1.g: Pie-chart of Feedback
Interpretation: We get to know from the above table and pie-chart that 11% of the total
respondents are extremely satisfied by using Aditya Birla Nuvo’s product,60% of the total
respondents are very satisfied, 27% of the total respondents are somewhat satisfied and 2% of
the total respondents are not satisfied by using Aditya Birla group Nuvo’s product.
Extremly Satisfactory
11%
Very Satisfactory
60%
Somewhat
Satisfactory
27%
Not Satisfactory
2%
FEEDBACK
Extremly Satisfactory Very Satisfactory Somewhat Satisfactory Not Satisfactory
Extremely Satisfactory 11 11.0
Very Satisfactory 60 60.0
Somewhat Satisfactory 27 27.0
Not Satisfactory 2 2.0
Total 100 100.0

Rank the factors that influence your buying behaviour of Aditya
Birla Nuvo's product _Affordability.
Table 4.1.h: Rank of Affordability
Figure 4.1.h: pie-chart of rank of Affordability
Interpretation: The above table along with graphs reflects the rank of the Affordability.58%
of the total respondent ranked 1st the affordability as an influencing buying behaviour of Aditya
Birla Nuvo’s product. 33% of the total respondent ranked 2nd and 9% of the total respondent
ranked 3rd the affordability as an influencing buying behaviour of Aditya Birla Nuvo’s Product.
1
58%
2
33%
3
9%
AFFFORDABILITY
1 2 3
Rank Frequency Percent
1 58 58.0
2 33 33.0
3 9 9.0
Total 100 100.0

Birla Nuvo's product _Brand Image
Table 4.1.i: Rank of Brand Image
Figure 4.1.i: Pie-chart of Rank of Brand Image
Interpretation: The above table along with graphs reflects the rank of the rand image.63% of
the total respondent ranked 1st the Brand Image as an influencing buying behaviour of Aditya
Birla Nuvo’s product. 25% of the total respondent ranked 2nd, 10% of the total respondent
ranked 3rd, 1% of the total respondent ranked 4th and 1% of the total respondent ranked 5 the
Brand Image as an influencing buying behaviour of Aditya Birla Nuvo’s Product.
1
63%
2
25%
3
10%
4
1%
5
1%
BRAND IMAGE
1 2 3 4 5
1 63 63.0
2 25 25.0
3 10 10.0
4 1 1.0
5 1 1.0
Total 100 100.0

Birla Nuvo's product _Quality
Table 4.1.j: Rank of Quality
Figure 4.1.j: Pie-chart of Rank of Quality
Interpretation: The above table along with graphs reflects the rank of the Quality.67% of the
total respondent ranked 1st the Quality as an influencing buying behaviour of Aditya Birla
Nuvo’s product. 18% of the total respondent ranked 2nd, 11% of the total respondent ranked 3rd
and 4% of the total respondent ranked 4th the Quality as an influencing buying behaviour of
Aditya Birla Nuvo’s Product.
1
67%
2
18%
3
11%
4
4%
QUALITY
1 2 3 4
1 67 67.0
2 18 18.0
3 11 11.0
4 4 4.0
Total 100 100.0

Birla Nuvo's product _Discounts and Availability
Table 4.1.k: Rank of Discounts and Availability
1 20 20.0
2 13 13.0
3 44 44.0
4 18 18.0
5 5 5.0
Total 100 100.0
Figure 4.1.k: Pie-chart of Rank of Discounts and Availability
Interpretation: The above table along with graphs reflects the rank of the Discounts and
Availability.20% of the total respondent ranked 1st the Discounts and Availability as an
influencing buying behaviour of Aditya Birla Nuvo’s product. 13% of the total respondent
ranked 2nd and 44% of the total respondent ranked 3rd ,18% of the total respondent ranked 4th
and 5% of the total respondent ranked 5th the Discounts and Availability as a influencing
buying behaviour of Aditya Birla Nuvo’s Product.
1
20%
2
13%
3
44%
4
18%
5
5%
DISCOUNTS AND AVAILIBILITY
1 2 3 4 5

Rank the company’s performance as per your view Aditya Birla
Nuvo.
Table 4.1.l: Rank of Aditya Birla Nuvo
1 28 28.0
2 57 57.0
3 14 14.0
4 1 1.0
Total 100 100.0
Figure 4.1.l: Pie-chart of Rank of Aditya Birla Nuvo
Interpretation: The above chart indicates the rank of Aditya Birla Nuvo.28% of the
respondents ranked 1st the Aditya Birla Nuvo as per their own view, 57% of the respondents
ranked 2nd, 14% of the respondents ranked 3rd and 1% of the total respondents ranked 4th as per
their own views.
1
28%
2
57%
3
14%
4
1%
RANK ADITYA BIRLA NUVO
1 2 3 4

Rank the company’s performance as per your view_TATA
Table 4.1.m: Rank of TATA
1 76 76.0
2 21 21.0
3 2 2.0
4 1 1.0
Total 100 100.0
Figure 4.1.m: Pie-chart of Rank of TATA
Interpretation: The above chart indicates the rank of TATA.76% of the respondents ranked
1st the TATA as per their own view, 21% of the respondents ranked 2nd, 2% of the respondents
ranked 3rd and 1% of the total respondents ranked 4th as per their own views.
1
76%
2
21%
3
2%
4
1%
RANK TATA
1 2 3 4

Rank the company’s performance as per your view_Goenka
Table 4.1.n: Rank of Goenka
1 2 2.0
2 27 27.0
3 37 37.0
4 30 30.0
5 4 4.0
Total 100 100.0
Figure 4.1.n: Pie-chart of Rank of Goenka
Interpretation: The above chart indicates the rank of Goenka.2% of the respondents ranked
1st the Goenka group as per their own view, 27% of the respondents ranked 2nd, 37% of the
respondents ranked 3rd, 4% of the respondents ranked 4th and 1% of the total respondents
ranked 5th as per their own views.
1
2%
2
27%
3
37%
4
30%
5
4%
RANK GOENKA
1 2 3 4 5

Rank the company’s performance as per your view Reliance
Table 4.1.o: Rank of Reliance
1 45 45.0
2 40 40.0
3 12 12.0
4 3 3.0
Total 100 100.0
Figure 4.1.o: Pie-chart of Rank of Reliance
Interpretation: The above chart indicates the rank of Reliance.45% of the respondents ranked
1st the Reliance as per their own view, 40% of the respondents ranked 2nd, 12% of the
respondents ranked 3rd and 3% of the total respondents ranked 4th as per their own views.
1
45%
2
40%
3
12%
4
3%
RANK RELIANCE
1 2 3 4

2. Bivariate Analysis
Respondent's gender * which product comes first in your mind by
listening Aditya Birla Nuvo? Cross tabulation
Table 4.2.a: Analysis of most popular product based on gender basis
Which productcomes firstin your mind by listening Aditya Birla
Nuvo?
Total
Idea Rayone Birla sun
life
insurance
Pantaloons
Respondent's
gender
Male 20 7 16 10 53
37.7% 13.2% 30.2% 18.9% 100.0%
Female 13 3 10 21 47
27.7% 6.4% 21.3% 44.7% 100.0%
Total 33 10 26 31 100
33.0% 10.0% 26.0% 31.0% 100.0%
Figure 4.2.a: Analysis of most popular product based on gender basis
Interpretation: The above table shows the analysis of most popular product based on gender
basis. It is seen from the table that 37.7% of male respondent voted for Idea, 13.2% of male
respondent voted for Rayone, 30.2% of male respondent asked for Birla Sun Life Insurance
and 18.9% of male respondent went for Pantaloons. On the other hand 27.7% of female
respondent voted for Idea, 6.4% of female respondent voted for Rayone, 21.3% of female
respondent voted for Birla Sun Life Insurance and 44.7% of female respondent went for
Pantaloons.
0
5
10
15
20
25
Chart Title
Male Female

Which product comes first in your mind by listening Aditya Birla
Nuvo? * What is your feedback on Aditya Birla Nuvo's product?
Cross tabulation
Table 4.2.b: Analysis of feedback on the most popular product of Aditya Birla Nuvo
What is your feedback on Aditya Birla Nuvo's
product?
Total
Extremly
Satisfactor
y
Very
Satisfactor
y
Somewhat
Satisfactor
y
Not
Satisfactor
y
Which
product
comes
first in
your
mind
by
listenin
g
Aditya
Birla
Nuvo?
Idea Coun
t
5 22 6 0 33
% of
count
15.2% 66.7% 18.2% 0.0% 100.0
%
Rayone Coun
t
2 3 4 1 10
% of
count
20.0% 30.0% 40.0% 10.0% 100.0
%
Birla sun
life
insurance
Coun
t
3 12 10 1 26
% of
count
11.5% 46.2% 38.5% 3.8% 100.0
%
Pantaloon
s
Coun
t
1 23 7 0 31
% of
count
3.2% 74.2% 22.6% 0.0% 100.0
%
Total Coun
t
11 60 27 2 100
% of
count
11.0% 60.0% 27.0% 2.0% 100.0
%

Figure 4.2.b: Analysis of feedback on the most popular product of Aditya Birla Nuvo
Interpretation: It is clear from the table that Idea users 15.2% extremely satisfied, 66.7% very
satisfied, and 18.2% somewhat satisfied. And Rayone users 20% extremely satisfied, 30% very
satisfied, 40% somewhat satisfied and 10% not satisfied. And Birla Sun Life Insurance users
11.5% extremely satisfied, 46.2% very satisfied, 38.5% somewhat satisfied and 3.8% not very
satisfied. And Pantaloons users 3.2% extremely satisfied, 74.2% very satisfied, and 22.6%
somewhat satisfied.
0
5
10
15
20
25
Extremly Satisfactory Very Satisfactory Somewhat Satisfactory Not Satisfactory
Chart Title

Rank correlation between Brand image And Discounts and
availability.
Table 4.2.c: Analysis of the correlation between rank of Brand Image and Discounts
and availability as the important factor for buying decision
Rank the factors
that influence
your buying
behaviour of
Aditya Birla
Nuvo's product
_Brand Image
Rank the factors
that influence
your buying
behaviour of
Aditya Birla
Nuvo's product
_Discounts and
Availability
Spearman's rho Rank the factors
that influence
your buying
behaviour of
Aditya Birla
Nuvo's product
_Brand Image
Correlation
Coefficient
1.000 -0.404
Sig. (2-
tailed)
. 0.016
N 35 35
Rank the factors
that influence
your buying
behaviour of
Aditya Birla
Nuvo's product
_Discounts and
Availability
Correlation
Coefficient
-0.404 1.000
Sig. (2-
tailed)
0.016 .
N 35 35
Interpretation: Spearman’s correlation coefficient is a statistical measure of the strength of a
monotonic relationship between paired data. In a sample it is denoted by rs and is buy design
constraint as follows:
-1 ≤ rs ≤ 1
The strength of the correlation can be described as
.00-.19 Very weak
.20-.39 Weak
.40-.59 Moderate
.60-.79 Strong
.80-1.0 Very strong
From the table, we can see rs of the two variables, Viz, Brand image and Discounts and
Availability as the driving factor for buying Aditya Birla group’s product is -0.404. So we can
conclude that there is moderately negative correlation between the two variables. This implies
that some of the respondents who gave higher rank to Brand image are likely to give lower
rank to Discounts and Availability.

Relation between sales turnover and reported net profit of Aditya
Birla Nuvo. Cross Tabulation
Table 4.2.d: Analysis of relationship between sales turnover and reported net profit
Year Mar
'05
Mar'
06
Mar'
07
Mar'
08
Mar'
09
Mar'
10
Mar'
11
Mar'
12
Mar'
13
Mar'
14
Sales
Turno
ver
1987.
82
2786.
39
3577.
89
4145.
75
4997.
21
4981.
85
6693.
03
8855.
67
9754.
5
8020.
35
Report
ed Net
Profit
113.7
2
186.9
3
224.9
7
243.0
7
137.4
3
283.4 379.6
9
345.3
9
423.0
5
673.9
5
Figure 4.2.c: Analysis of relationship between Sales Turnover and Reported Net Profit
Interpretation: It can be said from the above table and chart that due to corporate
diversification sales of the company increased in every year (excluding 2013-2014). And
simultaneously profit has increased slightly in last few years.
0
2000
4000
6000
8000
10000
12000
Sales Turnover Reported Net Profit
Turnover Vs. Net Profit
Mar '05 Mar'06 Mar'07 Mar'08 Mar'09 Mar'10 Mar'11 Mar'12 Mar'13 Mar'14

Relation between net worth and reported net profit of Aditya
Birla Nuvo.
Table 4.2.e: Analysis of relationship between Net Worth and Reported Net Profit
Year Mar
'05
Mar'
06
Mar'
07
Mar'
08
Mar'
09
Mar'
10
Mar'
11
Mar'
12
Mar'
13
Mar'1
4
Net
worth
114.6
4
2098.
5
3493.
51
4032.
87
5894.
42
5474.
78
6678.
35
7517.
09
9387.
29
11189.
23
Repor
ted
Net
Profit
113.7
2
186.9
3
224.9
7
243.0
7
137.4
3
283.4 379.6
9
345.3
9
423.0
5
673.95
Figure 4.2.d: Analysis of relationship between Net Worth and Reported Net Profit
Interpretation: It can be said from the data that the net worth has increased in every year and
besides that net profits also increased year by year. Increasing trend of net worth indicates that
corporate diversification is in a right way.
0
2000
4000
6000
8000
10000
12000
Net worth Vs. Net profit
Networth Reported Net Profit

3. Hypothesis testing
Null hypothesis (H0) = Gender and Awareness of Jayasree
Textiles are independent.
Alternative Hypothesis (H1) = Gender and Awareness of Textile
are not independent.
Table 4.3.a: Hypothesis testing on awareness of Jayasree textile based on gender
Respondent's gender * Have you ever heard about Jayasree Textile? Crosstabulation
Have you ever heard about
Jayasree Textile?
Total
yes no
Respondent's gender Male 20 33 53
37.7% 62.3% 100.0%
Female 27 20 47
57.4% 42.6% 100.0%
Total 47 53 100
47.0% 53.0% 100.0%
Figure 4.3.a: Analysis of awareness regarding jayasree textile based on gender.
Interpretation: The above diagram and table shows the relation between the genders and the
awareness of jayasree textile. By analysing that we can see that 20% of male and 27% of female
are aware of jayasree textile. But on the other hand 33% of male and 20% of female are not
aware of Jayasree Textile.
20
33
27
20
yes no
Gender Vs. Awareness Of JayasreeTextile
Male Female

Chi-Square Tests
Table 4.3.b: Chi-square table
Value df Asymp. Sig. (2-
sided)
Pearson Chi-Square 3.885 1 0.049
Continuity Correction(a) 3.134 1 0.077
Likelihood Ratio 3.908 1 0.048
Fisher's Exact Test
Linear-by-Linear Association 3.846 1 0.050
N of Valid Cases 100
Interpretation: As 0.049 is smaller than 0.05, (H0) is not accepted so the two variables namely
gender and awareness of textile are not independent.
As (H0) is rejected, (h1) is accepted which indicates two variables namely gender and awareness
of textile are dependent.

Null Hypothesis (H0) = Sales turnover and Reported net profit are
independent.
Alternative Hypothesis (H1) = Sales turnover and Reported net
profit are not independent.
Table 4.3.c: Hypothesis on the relationship of Sales Turnover and Reported Net Profit
Correlation between Sales turnover and Reported net profit
Table 4.3.d: Correlation Table
Sales Turnover Reported Net Profit
Sales Turnover 1
Reported Net Profit 0.75869 1
Interpretation: The correlation coefficient is 0.75869 which is greater than 0.5, so it can be
concluded that there is a highly positive correlation (positive relationship) between two
variables.
Year Mar
'05
Mar'
06
Mar'
07
Mar'
08
Mar'
09
Mar'
10
Mar'
11
Mar'
12
Mar'
13
Mar'
14
Sales
Turno
ver
1987.
82
2786.
39
3577.
89
4145.
75
4997.
21
4981.
85
6693.
03
8855.
67
9754.
5
8020.
35
Report
ed Net
Profit
113.7
2
186.9
3
224.9
7
243.0
7
137.4
3
283.4 379.6
9
345.3
9
423.0
5
673.9
5

Regression Table
Table 4.3.e: RegressionAnalysis
Regression Statistics
Multiple R 0.76
R Square 0.58
Adjusted R Square 0.52
Standard Error 114.34
Observations 10.00
ANOVA
df SS MS F Significance F
Regression 1 141851.82 141851.82 10.85 0.01
Residual 8 104585.54 13073.19
Total 9 246437.35
Coeffici
ents
Standard
Error
t
Sta
t
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept 36.00 88.24 0.4
1
0.69 -167.49 239.49 -167.49 239.49
X
Variable
1
0.05 0.01 3.2
9
0.01 0.01 0.08 0.01 0.08
Interpretation: We have taken two variables namely Sales Turnover and Reputed Net Profit,
to predict the value of a dependent variable using the value of an independent variable and to
form the linear regression equation.
Here the independent variable is Sales Turnover(X) and the dependent variable is Reputed Net
Profit.
The Regression Equation can be expressed as:
Y=36+0.05X, where intercept (a) = 36 and slope (b) = 0.05
As the value of R2 is 0.58, we can see that 58% of the variance in the value of Reputed Net
Profit can be explained by the variance in the value of Sales Turnover

Therefore we can formulate regression equations.
Figure 4.3.b: RegressionEquation
Interpretation: From the above line charts we get two regression equation
Sales Turnover Y=830.82x+1010.5
(Where Y = sales turnover and X= no. of years)
Reported Net Profit Y=47.593x+39.399
(Where Y = Reported Net Profit and X=no. of years)
y = 47.593x + 39.399
y = 830.82x + 1010.5
0
2000
4000
6000
8000
10000
12000
0
100
200
300
400
500
600
700
800
Reported Net ProfitVs. Sales TurnOver
Reported Net Profit Sales Turnover
Linear (Reported Net Profit) Linear (Sales Turnover)

Chapter 5
FINDING AND SUGGESTIONS

FINDINGS
This study had attempted investigate the effect of corporate diversification on the profitability
of Aditya Birla Group. From the primary Data Analysis the following findings are observed
 Majority of the respondents are male
 Most of the respondents are in the age group of 25-30 years
 Mostly the respondents are professionals
 Majority of the respondents are 3-5 lacs annually
 Most of the respondents are not aware off jayasree textile
 When the respondents were asked that which product comes first in their mind by
listening Aditya Birla Nuvo, they responded it to be ‘Idea’
 Majority of the respondents are very satisfied with the product
 Most of the respondent said affordability, brand image and quality are the prime
influencing factors for buying the product than discount and availability
 Majority of the respondents gave higher ranks to TATA and Reliance group rather than
Goenka and Aditya Birla Group.
 Female respondents are more aware of jayasree textiles
 Respondents are very satisfied with ‘idea’ ‘pantaloons’ and Birla Sun life Insurance
 Respondents who gave higher rank to brand image are likely to give lower rank to
discounts and availability
 It is been observed from the analysis that Reported Net Profit is slightly dependent on
Sales Turn Over.
 I found a little bit increasing trend from the analysis that Net worth and Net profit both
are increased due to the diversification of the company.
 As we can see that there is positive growth in sales as well as in profits, so it can be
concluded that here corporate diversification happened in a positive manner.
SUGGESTIONS
In the light of this study, the following recommendations of the researcher were given to
effectively maximize the dividends of corporate diversification on firm performance. First, the
companies should engage in more feasibilities studies and improve the management of both
the human and material resources. Second, the organization should understand that
diversification and performance are linearly and positively related. Third, these companies
should also embark on geographic diversification in addition to other diversification strategies
they are used to. This means that they need to extend their businesses to other countries as well
as other continents of the world. Finally, prudent management of diversification strategies is
very important in any business as it is said that diversification enhances the well-being of the
business and it effective and efficient management will contribute to sound performance and
profitability of the business. Various reasons, models and explanations have been given in this
research to enlighten people about the positive impact of diversification on the organization’s
performance and the reason why managers should welcome diversification in their business
and avail themselves of the prevailing benefits of adopting diversification

REFERENCES
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literature.
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