the impact of diversification on the financial …
TRANSCRIPT
MBA 2005/2006
THE IMPACT OF DIVERSIFICATION ON THE FINANCIAL PERFORMANCE
OF ORGANISATIONS LISTED ON THE INDUSTRIAL SECTOR OF THE JSE.
LOUIS THOMAS RUSHIN
A research project submitted to the Gordon Institute of Business Science,
University of Pretoria in partial fulfillment of the requirement for the degree of
Masters of Business Administration
November 2006
©© UUnniivveerrssiittyy ooff PPrreettoorriiaa
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ABSTRACT
Corporate diversification is one of the fundamental strategic alternatives
available to organisations to sustain growth and search for greater profits.
International research has been conducted since the 1950’s to establish if
diversification creates value and if it resulted in greater financial performance.
The findings are inconsistent and there remains a lack of consensus regarding
the diversification-performance relationship, although there has been a trend
since the 1990’s of organisations focusing more on their core competencies.
A quantitative research methodology was followed whereby organisations listed
on the industrial sector of the Johannesburg Securities Exchange (JSE) were
categorised as either diversified or focused organisations. Each category
consisted of 15 organisations, against which four financial measures were
compared from the period 2001 to 2005 in the form of hypotheses, to determine
which category of organisations performed better than the other.
Three of the four performance measures are not statistically significant to prove
that either the diversified group or the focused group of organisations
outperformed the other. One of the financial measures is statistically significant
and it was found that the Average Market Return (AMKTRET) of focused
organisations outperform the AMKTRET of diversified organisations.
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DECLARATION
I declare that this research project is my own work. It is submitted in partial
fulfilment of the requirements for the degree of Master of Business
Administration at the Gordon Institute of Business Science, University of
Pretoria. It has not been submitted before for any degree or examination in any
other University.
………………………………………………. Date: 2 November 2006
Louis Thomas Rushin
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ACKNOWLEDGEMENTS I would like to make the following acknowledgements of individuals who
assisted me, without whom the MBA and research project would not have been
possible.
From a personal perspective I would first like to take this opportunity to thank
my wife Nicola Rushin, for being supportive, loving, caring and patient during
the difficult times. Without your assistance I would never have been able to see
the MBA through. Secondly I would also like to thank my parents, John and
Marieta Rushin who have given me the foundation and support to be able to do
an MBA.
From an academic perspective I would like to thank the following individuals:
• Dr. Raj Raina, my supervisor, for being supportive, accessible and providing
me with direction and insights.
• Tudor Maxwell for assisting me with the statistical methods of the research.
• Beulah Muller from the GIBS Information Centre for assisting me in
obtaining the financial information for the research.
• Judy Crossman for proof reading the research.
• My fellow students who assisted me throughout the MBA programme, with a
special thanks to Nicholas Towle.
• The management and staff of the Gordon Institute of Business Science who
has made my experience of higher education a life changing journey.
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TABLE OF CONTENTS
ABSTRACT II
DECLARATION III
ACKNOWLEDGEMENTS IV
GLOSSARY OF TABLES X
1. INTRODUCTION TO RESEARCH PROBLEM 1
1.1 BACKGROUND 1
1.2 THE RESEARCH PROBLEM 3
1.3 OBJECTIVE OF THIS RESEARCH 4
1.4 SCOPE AND LIMITATIONS OF THIS RESEARCH 5
1.4.1 SCOPE 5
1.4.2 POTENTIAL LIMITATIONS 6
2. LITERATURE REVIEW 8
2.1 CORPORATE STRATEGY 8
2.1.1 DEFINITION OF CORPORATE STRATEGY 8
2.1.2 GENERIC STRATEGIC ALTERNATIVES AVAILABLE TO ORGANISATIONS 9
2.2 DIVERSIFICATION AS A STRATEGIC ALTERNATIVE 11
2.2.1 DEFINITION OF DIVERSIFICATION 11
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2.2.2 REASONS FOR DIVERSIFICATION 12
2.2.3 DIVERSIFICATION REASONS IN SOUTH AFRICA 15
2.3 DIVERSIFICATION TRENDS 16
2.3.1 DIVERSIFICATION TRENDS IN SOUTH AFRICA 20
2.4 ENTRY STRATEGIES FOR DIVERSIFICATION 21
2.5 DIVERSIFICATIONS IMPACT ON AN ORGANISATION’S FINANCIAL
PERFORMANCE 22
2.5.1 BACKGROUND 22
2.5.2 DETERMINING THE LEVEL OF AN ORGANISATION’S DIVERSIFICATION 23
2.5.2.1 Rumelt’s categorisation model 24
2.5.2.2 Product Count Measures (Standard Industrial Classification) 29
2.5.2.3 Combination of both approaches 32
2.5.3 THE PERFORMANCE MEASURES USED IN RESEARCH 33
2.5.4 RESULTS OF FINANCIAL PERFORMANCE OF DIVERSIFIED COMPANIES 37
2.5.4.1 Diversification has a positive relationship with an organisation’s financial
performance 37
2.5.4.2 Diversification has a negative relationship with an organisation’s
financial performance 39
2.5.4.3 Diversification has a curvilinear relationship with an organisation’s
financial performance 41
2.5.4.4 Other research studies relating to diversification 42
2.5.4.4.1 Ansoff 42
2.5.4.4.2 Rumelt’s study 43
2.5.4.4.3 Porter’s study 44
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2.5.4.4.4 Hamel and Prahalad 46
2.6 SOUTH AFRICAN STUDIES 46
3. RESEARCH HYPOTHESES 48
4. RESEARCH METHODOLOGY 50
4.1 RESEARCH DESIGN 50
4.2 UNIT OF ANALYSIS 51
4.3 POPULATION OF RELEVANCE 51
4.4 SAMPLE SIZE AND SAMPLING METHOD 53
4.5 DETAILS OF DATA COLLECTION 55
4.5.1 DATA TO DETERMINE THE LEVEL OF DIVERSIFICATION 55
4.5.2 PERFORMANCE DATA 57
4.5.2.1 Return on Equity 57
4.5.2.2 Return on Assets 57
4.5.2.3 Market Return 58
4.5.2.4 Earnings per share 59
4.6 PROCESS OF DATA ANALYSIS 60
4.6.1 DESCRIPTIVE STATISTICS 60
4.6.2 INFERENTIAL STATISTICS 61
4.6.2.1 Hypothesis Testing 61
4.7 LIMITATIONS OF THE RESEARCH 65
5. RESULTS 67
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5.1 SIC CODE CLASSIFICATION 67
5.1.1 FOCUSED ORGANISATIONS 67
5.1.2 DIVERSIFIED ORGANISATIONS 70
5.2 PERFORMANCE MEASURE RESULTS 73
5.2.1 PERFORMANCE DATA 74
5.2.1.1 Return on Equity 74
5.2.1.2 Return on Assets 75
5.2.1.3 Market Return 75
5.2.1.4 Earnings per share 76
5.2.2 DESCRIPTIVE STATISTICS OF THE PERFORMANCE MEASURES 77
5.2.3 HYPOTHESIS TEST RESULTS 78
5.2.3.1 Hypothesis 1: AROE 79
5.2.3.2 Hypothesis 2: AROA 81
5.2.3.3 Hypothesis 3: AMKTRET 82
5.2.3.4 Hypothesis 4: AEPSGR 84
6. DISCUSSION OF RESULTS 87
6.1 CLASSIFICATION OF DIVERSIFICATION 87
6.2 PERFORMANCE MEASURES 88
6.2.1 HYPOTHESIS 1: AROE 89
6.2.2 HYPOTHESIS 2: AROA 92
6.2.3 HYPOTHESIS 3: AMKTRET 94
6.2.4 HYPOTHESIS 4: AEPSGR 96
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7. CONCLUSION 99
7.1 BACKGROUND 99
7.2 FINDINGS 100
7.3 IN SUMMARY 102
7.4 RECOMMENDATIONS 103
REFERENCES 105
APPENDIX 1: SIC CODE DESCRIPTIONS 112
APPENDIX 2: FOCUSED ORGANISATIONS SPECIALISATION RATIOS 124
APPENDIX 3: DIVERSIFIED ORGANISATIONS SPECIALISATION RATIOS
130
APPENDIX 4: PRICE / EARNINGS RATIOS 138
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GLOSSARY OF TABLES Table 1: Ansoff's business growth alternatives 9
Table 2: Alternative strategies available to organisations 10
Table 3: Internal and external incentives for diversification 14
Table 4: Entry Strategies for organisations 21
Table 5: Rumelt's major categories of diversification 25
Table 6: Rumelt’s subcategories of diversification 25
Table 7: Panday and Rao's SR classification 27
Table 8: SIC Code Levels 30
Table 9: Example of SIC code description 31
Table 10: Summary of performance measures used in research 35
Table 11: Organisations listed in the industrial sector of the JSE 52
Table 12: Specialisation Ratios used in this research 54
Table 13: Descriptive statistical elements 60
Table 14: Focused Organisations 68
Table 15: Diversified Organisations 70
Table 16: ROE % of the focused and diversified organisations 74
Table 17: ROA % of the focused and diversified organisations 75
Table 18: Market Return % of the focused and diversified organisations 76
Table 19: EPS growth rate of the focused and diversified organisations 77
Table 20: Descriptive statistics of performance measures 78
Table 21: AROE Tests 80
Table 22: AROA Tests 82
Table 23: AMKTRET Tests 83
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Table 24: AEPSGR Tests 85
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1. INTRODUCTION TO RESEARCH PROBLEM
1.1 BACKGROUND
Corporate diversification has long been regarded as a strategic tool for
organisations to sustain growth and profitability. Rumelt’s pioneering research in
the 1970’s on United States of America (USA) organisations suggested that
focused organisations performed well, and the success of the book “In search of
Excellence” written by Peters and Waterman in the 1980’s further reinforced the
view that staying focused results in superior performance. However, there is
some evidence that a few organisations that operate a diversified set of
businesses do exceeding well such as Berkshire Hathaway (Bruner, 2003) and
General Electric in the USA.
Internationally, research conducted by Palich, Cardinal and Miller (2000),
concluded that although substantial research has been conducted in the
diversification field in the USA and Western Europe, findings were inconsistent
and that there remains a lack of consensus regarding the diversification-
performance relationship.
In South Africa, there has been no systematic study of the diversification-
performance relationship. The apartheid policies of the past drove South Africa
into economic isolation, forcing many organisations to diversify during the
period from the 1960’s to the early 1990’s. With the integration of South Africa
into the world economy, many organisations divested their non-core assets, and
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there is ample evidence that organisations which divested their non-core
businesses and focused on core industries have also done well (Bhana, 2004).
A few diversified organisations however retained their diverse portfolio of
businesses. Notable examples are Bidvest Limited, Barloworld Limited and
Imperial Holdings Limited to mention a few, which seem to have had a
successful track record.
A study of this kind would be of significant benefit to Chief Executive Officers
(CEO’s) and managers in designing their growth strategies.
Diversification is a key strategic decision used as part of an organisation’s
corporate strategy to pursue different markets in anticipation of creating
enhanced returns and ultimately greater profits. This study is an attempt to
answer the key question: Does a high degree of diversification result in greater
financial performance vis-à-vis a focused (low degree) strategy? Within the
resource based view of the picture, Collis and Montgomery (2005) suggest that
an effective diversification strategy can only be conducted if there is a fit
between the resources and the businesses so that the resources contribute in
an important way to competitive advantage.
Gourlay and Seaton (2004) in their research in the UK, argue that firms diversify
for two main reasons. The first reason is in line with the resource based view
that organisations utilize their excess capacity of propriety assets in the
presence of transactional costs. The Organisational specific assets such as
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managerial skills, research and development (R&D) and brand reputation
increases the bias towards the diversification decision. The second reason for
diversification relates to governance factors such as the agency problem that
exists between shareholders and management. Gourlay and Seaton (2004)
mentioned that managers have an incentive to diversify as it entrenches the
managers’ positions within the organisation by increasing the demand for their
skills, which is not necessarily to the benefit of the shareholders.
The core focus of this research report relates to the question of whether
diversified organisations deliver superior financial performance than
organisations that choose to operate as a focused organisation. The research
conducted in determining the diversification and performance relationship has
been inconclusive and has been debated since the 1950’s. Piscitello (2004)
noted that the diversification-performance literature has failed to reach
consensus and that there is still considerable disagreement about how and
when diversification can be used to build long term competitive advantage.
1.2 THE RESEARCH PROBLEM
To diversify or not to diversify is one of the key strategic decisions taken by the
CEO, the Board or the Executive team of an organisation. The effectiveness of
diversification as a strategic tool has been mixed and questioned by many
practitioners, as well as by academics. It is unclear if diversification adds value
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to an organisation and if it leads to superior financial performance than
organisations that follow a more focused strategy.
Several international studies have been conducted to determine if diversification
leads to superior financial and economic performance, or if it leads to value
destruction. The evidence in different markets, countries and functions are
contradictory. Panday and Rao (1998) suggests that there is a difference in
opinion between functional disciplines within organisations, with Management
and Marketing favouring related diversification on the one hand, while Finance
makes a strong case against corporate diversification. Ushijima and Fukui
(2004) attempted to measure economic performance of diversified companies in
Japan as they wanted to understand why firms refocused in the 1990’s and to
establish what went wrong for Japanese companies. Ramanujam and
Varadarajan (1989) in their attempt to conduct a synthesis concluded that the
literature on diversification covers a great degree of breadth and scope, but that
no comprehensive review of the literature exists.
The research study will attempt to measure the financial performance of a group
of diversified and focused organisations of a sample of companies listed on the
industrial sector of the JSE.
1.3 OBJECTIVE OF THIS RESEARCH
The objective of the research is to provide empirical evidence on the impact of
the level of diversification on the financial performance of organisations that are
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listed in the industrial sector of the JSE. The diversified organisations will be
compared against the focused organisations on the industrial sector of the JSE
to ensure that the comparisons are within the same sector. The aim is to
measure and determine if there is a difference in financial performance between
the two categories of organisations from the period 2001 to 2005. The
categorisation would have to be determined over the five year period to ensure
that the organisations remain diversified or focused to be able to measure the
financial performance in a consistent manner.
1.4 SCOPE AND LIMITATIONS OF THIS RESEARCH
1.4.1 Scope
The scope of this research is limited to study two extreme categories of
organisations: Diversified versus Focused organisations.
The research was concerned with the classification of organisations as
diversified versus focused using a categorisation method developed by Rumelt
(1982), as well classifying the organisations’ activities according to their
reported Standard Industrial Classification (SIC) code. The organisations that
were analysed as part of the population had to meet the following criteria:
• The organisations in the sample had to be listed organisations on the JSE
over the five year period from 2001 to 2005.
• The organisations’ annual reports had to be reviewed and SIC codes
assigned to their segmented revenue reporting.
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• The identified organisations within the sample had to remain diversified or
focused throughout the five year time period.
• The comparison of the organisations had to be in the industrial sector of
companies trading on the JSE.
• The same financial ratios and adjusted financial data had to be used
throughout the calculation process.
The four financial measurements that were used in the research to calculate the
financial performance of the two groups of diversified versus focused
organisations were measurements previously used in research conducted by
Rumelt (1982) and Panday and Rao (1998).
1.4.2 Potential limitations
The potential limitations of the research report can be summarised as follows:
• Using only two extreme categories of diversified versus focused
organisations. Rumelt (1982) study made use of nine categories.
• Research was limited to the industrial sector due to availability of data and
the manual nature of determining the level of diversification.
• Obtaining accurate information per organisation to calculate the
Specialization Ratio (SR). The SR is a methodology to determine the level of
an organisation’s diversification.
• The annual reports do not clearly classify the segmented revenue reporting
necessary to assign a relevant SIC code to the reported revenue.
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• Classification of the companies SIC codes as per the segmentation reporting
could be subjective if the information is not clear enough.
• Analysis of the organisations SIC code is done at the three-digit level which
is at a high level. A more in depth analysis would require the SIC code
analysis to be done at the four-digit SIC code level.
• Only four hypotheses and average measures are used to calculate the
financial performance of the diversified versus the focused organisations.
• The sample size of 15 organisations per category of diversified and focused
organisations is relatively small.
• The lack of South African research material relating to the financial
performance measurement of diversification.
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2. LITERATURE REVIEW
2.1 CORPORATE STRATEGY
2.1.1 Definition of corporate strategy
Since the 1950’s, corporate strategy has evolved as a discipline with greater
focus and organisations are constantly investigating ways to create more value.
In formulating a definition of strategy, Porter (1987) divided strategy into two
distinct levels. The first level of strategy is business unit strategy, which is
concerned with strategic decisions within each separate business unit as they
operate and compete as independent units. The second level of strategy is the
company wide or corporate strategy. The corporate strategy is the overarching
strategy that makes the corporate whole add up to more than the sum of the
individual business unit parts.
Collis and Montgomery (2005) define corporate strategy as the way a company
creates value through the configuration and coordination of its multimarket
activities. This research report relates to the topic of diversification which is a
strategic tool within corporate strategy which managers can follow in the quest
to create greater value.
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2.1.2 Generic strategic alternatives available to organisations
Managers have various generic strategic tools and alternatives available to
pursue the organisation’s desired strategy, depending on their objectives.
Ansoff (1958) developed a conceptual matrix whereby an organisation could
pursue growth alternatives as different product-market strategies. The four
business growth alternatives that were available to managers are described in
Table 1 below.
Table 1: Ansoff's business growth alternatives Business Growth Alternative Description
Market Penetration Increase sales without departing from an original product-
market strategy. The business can grow sales by
increasing volume to present customers or finding new
customers.
Market Development Business strategy to adapt the current product line to new
markets.
Product Development Business strategy to retain the present market and
develop the product characteristics which will increase the
performance of the product to the current market.
Diversification Business strategy to simultaneously depart from the
current product line and the present market structure. Source: Ansoff, I. (1958)
Ansoff (1958) argued that a simultaneous pursuit of market penetration, market
development and product development was a sign of a healthy progressive
organisation, but that diversification was different from the other strategies in
that it required new skills, techniques and facilities and would lead to
organisational changes in its structure and functioning.
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David (1997) summarized various strategies that organisations can follow into
thirteen actions as described in Table 2.
Table 2: Alternative strategies available to organisations
Strategy Definition
Forward Integration Gaining ownership or increased control over
distributors or retailers
Backward Integration Seeking ownership or increased control of a
company’s suppliers
Horizontal Integration Seeking ownership or increased control over
competitors
Market Penetration Seeking increased market share for present
products or services in present markets
through greater marketing efforts
Market Development Introducing present products or services into
new geographical areas
Product Development Seeking increased sales by improving present
products or services or developing new
products or services
Concentric Diversification
(Related Diversification)
Adding new, but related products or services
Conglomerate Diversification
(Unrelated Diversification)
Adding new, but unrelated products or services
Horizontal Diversification Adding new, but unrelated products or services
for present customers
Joint Venture Two or more sponsoring companies forming a
separate company for cooperative purposes
Retrenchment Regrouping through costs and asset reduction
to reverse declining sales and profits
Divesture Selling a division or part of a company
Liquidation Selling all of a company’s assets, in parts, for
their tangible worth Source: David, F. (1997)
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From a corporate strategy point of view, De Wit and Meyer (2004) argue that
corporate strategy is about selecting an optimal set of businesses and
determining how they should be integrated as a whole. The process of deciding
the best array of businesses and relating them to one another is referred to as
corporate configuration. In determining the configuration of the organisation two
questions can be asked:
1. What business areas should the organisation operate in?
2. How should the group of businesses be managed?
The first question relates to the direction and level of diversification and the
second question relates to management of such an organisation.
This research report will focus on diversification as one of the corporate strategy
alternatives available to organisations.
2.2 DIVERSIFICATION AS A STRATEGIC ALTERNATIVE
2.2.1 Definition of diversification
In researching diversification, it is important to define diversification as a
concept and offer various definitions of diversification. Diversification as a
corporate strategy choice has been suggested as an alternative to foster
continuous growth and change. One of the pioneers of diversification, Ansoff
(1957) defined diversification in terms of a particular kind of change in the
product-market makeup of an organisation. Extending Ansoff’s definition, Aaker
(2001) defined diversification as the strategy of entering product markets
different from those in which a firm is currently engaged. Ansoff (1957)
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suggested that diversification is more difficult than other strategies such as
market development and product development, as diversification requires new
skills, new techniques and organisational changes in the structure of the firm.
Diversification is usually driven by the desire (or financial ability) to expand
beyond the apparent limits of existing markets, and / or by the desire to reduce
business risk by developing new “legs” (Koch, 1995).
Ramanujam and Varadarajan (1989) defined diversification as the entry of a
firm or business unit into new lines of activity, either by processes of internal
business development or acquisition, which entail changes in its administrative
structure, systems and other management processes.
2.2.2 Reasons for diversification
Hill and Jones (1998) suggest that companies consider diversification when
they generate financial resources in excess of the funding required to maintain
a competitive advantage in their core business. They argue that a diversified
company can create value in three ways:
• Acquiring and restructuring: The focus of the acquisition is to
purchase a company that is poorly managed and increase efficiencies
through the management expertise of the acquirer. The approach is
considered a form of diversification as the acquirer does not have to be
in the same industry as the acquired company.
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• Transferring Competencies: This approach is achieved by the
company transferring key competencies in one of their value creation
functions such as manufacturing, marketing or R&D to a new business to
improve the competitive advantage of the new business.
• Realising economies of scope: This approach applies when two or
more business units share resources such as Research and
Development and advertising. Each business unit that shares resources
has to invest less in the shared function.
Haberberg and Rieple (2001) identified six reasons as to why organisations
might want to diversify:
• Seek growth and capture value added opportunities: Organisations
might perceive opportunities for growth that are not available in their core
businesses and by diversifying into other businesses, they could capture
value and profits for the organisation.
• Spread risk: Organisations might want to spread their risk and diversify
into different businesses as a hedge.
• Prevent competitors from gaining ground: From a defensive point of
view, organisations might want to diversify into other businesses to
prevent their competitors from gaining a foothold in a specific market.
• Achieve synergy: In achieving synergy, the organisation would want to
coordinate some functions by sharing the value chain. Activities such as
purchasing and production across business units could lead to
economies of scale and scope.
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• Control the supply and distribution channel: Organisations might
want to diversify to gain control either by backward or forward integration
therefore influencing prices and the supply of raw materials to the entire
organisation.
• The fulfillment of personal ambition by senior management:
Managers might be rewarded for the size of the organisation rather than
the financial performance, thus leading to behaviour of management
seeking diversification as the ultimate strategy.
Incentives also exist externally and internally for a company to follow a
diversification strategy. Hitt, Ireland and Hoskisson (1999) suggest that there
are several reasons for companies to diversify that are value neutral and that
there are several incentives for managers to do so. Table 3 below summarizes
the internal and external incentives of diversification.
Table 3: Internal and external incentives for diversification
Internal Incentives External Incentives
Low Performance: Companies that have had poor
performance over a prolonged period of
time might be willing to take greater risks in
an attempt to improve performance,
thereby diversifying into new businesses.
Antitrust Regulation: Regulation either promoting or inhibiting
diversification plays a role. The regulation
could encourage either diversification in
unrelated businesses due to the strict
regulation to encourage competition and thus
avoid monopolisation, or the regulation might
be more conducive to take-overs and mergers
within the same industries.
Uncertain future cash flows: Companies operating in mature industries
might find it necessary to diversify as a
Tax Laws: Tax laws could encourage companies to rather
reinvest funds as opposed to distribute the
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defensive strategy to survive over the long
term.
funds to shareholders. Higher personal taxes
encourage shareholders to want the
companies to retain the dividends and use the
cash to acquire new businesses as opposed to
distribution to shareholders.
Risk Reduction: Companies that have synergy between
business units face greater risk as the
interdependencies between the business
units increase the risk of corporate failure.
Diversification could reduce the
interdependency and hence reduce the
risk.
Source: Hitt, M. ,Irelan, R and Hoskisson, R. (1999)
2.2.3 Diversification reasons in South Africa
From a South African perspective, diversification has had a different element
due to the political anomaly that occurred during apartheid. Whereas the
traditional reasons for diversification would have applied to South African
organisations, the political isolation led to an inward focused economy.
According to Rossouw (1997) the South African economy was dominated by six
large conglomerates which accounted for 80% of the JSE market capitalization
in the 1970’s and 1980’s. The reasons for the high degree of capitalization by
the six conglomerates was the fact that the South African government
prohibited South African companies from foreign investment, and strict
exchange controls prohibited the organisations from investing offshore. The
regulation and the sanctions that were placed on South African organisations
16
compelled South African organisations to invest and diversify by acquiring local
companies which led to the formation of large diversified conglomerates.
2.3 DIVERSIFICATION TRENDS
As the economic outcome of diversification has been mixed since the early
1900’s, various phases and trends have occurred. In a study conducted by
Chandler (1969), the changing industrial structure of the USA economy was
researched where the concentration of organisations was measured per decade
from 1909 to 1963. In Chandler’s study a concentrated industry was defined
where six or fewer organisations contributed to fifty percent, or twelve or fewer
organisations contributed to 75%of the total product value.
Chandler’s (1969) research had the following findings:
• Concentration tended to increase through World War II and declined slightly
thereafter.
• The depression of the 1920’s forced organisations into diversification,
especially chemical companies and electrical manufacturers such as
General Electric and Westinghouse.
• World War II encouraged organisations to adopt diversification by opening
new opportunities for the production of new products such as radar
equipment and other war products.
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• The post World War II boom was characterized by constrained demand and
the rapid expansion of government spending on R&D which gave
momentum to diversification in the 1940’s and 1950’s.
• Diversification was primarily in those industries which made use of
sophisticated scientific techniques in modern chemistry and physics.
• In 1947 the largest 200 organisations accounted for 30% of the value added
by manufacturing, and by 1963 the figure rose to 41%.
• By the 1960’s organisations developed the decentralized organisational
structure which was fashioned by the DuPont Corporation. The
decentralized structure was developed as an effective administrative
process to be able to lever the autonomous operating divisions of an
organisation and as a result institutionalized the strategy of diversification.
Chandler’s (1969) research thus indicated a steady increase in organisations
diversifying from the early 1900’s to the 1960’s due to the various reasons listed
above.
During the 1970’s the concept of portfolio planning was developed in response
to the problem and prospects of managing sustainable growth. This became the
primary tool for resource allocation in organisations and represented an
analytical breakthrough in corporate strategy and diversification (Collis and
Montgomery, 2005). In research conducted by Haspeslagh (1982), portfolio
planning philosophy would have taken place in three steps within an
organisation:
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• Redefine the business as Strategic Business Units (SBU’s) which may or
may not differ from operating units.
• Classification of SBU’s on a portfolio grid according to the competitive
position and attractiveness of the particular product market.
• Allocate resources to the SBU’s in terms of the growth and financial
objectives.
According to Haspeslagh (1982) the above portfolio planning process was a
mechanism for managers to determine each SBU’s position within an industry
and allocate resources to those SBU’s for differentiating strategic influences
and to best manage diversification. Haspeslagh (1982) further concluded that
by 1979, 45% of the Fortune 500 industrial companies had introduced the
portfolio planning process to some extent and that it had been increasingly
introduced.
According to Collis and Montgomery (2005) the portfolio planning process was
not sustainable as it assumed that organisations needed to be internally self-
financed, while in practice there was no rationale for such a policy when the
capital markets were efficient. The 1980’s saw the failure of diversification
strategies in the USA, and a new drive for organisations to focus on their core
competence.
Berger and Ofek (1995) mentioned that during the 1950’s and 1960’s massive
diversification programs were undertaken with the climax being reached in the
19
USA in the late 1960’s. The last 25 years have seen a reversal of the
diversification strategy whereby many firms in the USA were refocusing on their
core business. A similar study was conducted by Ushijima and Fukui (2004)
which showed that many Japanese organisations reversed the diversification
strategy to focus on their core business. Koch (1995) phrases this term as
“sticking to the knitting.”
Turner (2005) summarized the history of diversification into three phases:
• 1960’s and 1970’s: The period was well known as an era when
diversification was fashionable as a remedy to companies that were
faced with maturity in their core businesses.
• 1980’s: Companies were urged to sell non-core businesses and to focus
on much smaller, more manageable portfolio businesses and to occupy
dominant market positions.
• 1990’s onwards: Companies were refocusing and were not diversifying
to the extent as in the 1960’s and 1970’s. The trend, however, was to
pursue international diversification (compared to product diversification)
which has been increasing in importance and has led to greater financial
performance relative to product diversification.
Although the phases of diversification studies were mainly conducted in the
USA, Hitt et al. (1999) remarks that although the trends are more significant in
the USA, Europe, Asia and other industrialized countries have followed similar
trends.
20
2.3.1 Diversification trends in South Africa
Due to the economic sanctions and regulation placed on South African
organisations, many South African organisations were obliged to invest within
South Africa which led to the formation of large diversified conglomerates in the
1970’s and 1980’s (Rossouw, 1997), resulting in a trend of increased
diversification.
Since the early 1990’s, according to research conducted by Bhana (2004) there
had been a decline in the amount of mergers, acquisitions and other forms of
expansions, and many conglomerates downsized and focused their businesses
on their core competencies. Bhana (2004, p. 5) researched the performance of
corporate restructuring through spin-offs on the JSE, and defined a spin-off as
“When an organisation distributes shares of a subsidiary to its shareholders.
The primary effect is that the subsidiary becomes a separate decision-making
organisation with separation of control from the parent organisations
management”.
Bhana’s (2004) study identified a total of 47 voluntary spin-offs that were
initiated by 19 parent organisations during the period 1988 to 1999, which was
an indication that South African organisations were following the same trend as
other countries by focusing on their core competencies.
21
2.4 ENTRY STRATEGIES FOR DIVERSIFICATION
Various diversification entry strategies exist for organisations to pursue. Aaker
(2001) suggested that diversification strategies could be accomplished through
various entry strategies such as internal development, acquisitions, joint
ventures, licensing agreements and alliances. The various entry strategies have
certain advantages and disadvantages which organisations have to consider.
Some of the entry strategies available to organisations are summarized in
Table 4 below.
Table 4: Entry Strategies for organisations
Entry Strategy Advantages Disadvantages
Internal Development • Uses existing resources
• No acquisition costs
• Time lag
• Uncertain prospects
Internal Venture • Uses existing resources
• May keep talented
entrepreneurs
• Mixed success record
• Can create internal stress
Acquisition • Saves calendar time
• Overcomes entry barriers
• Could be costly
• Difficulty in integrating two
companies
Joint Venture or
Alliance • Technological/Marketing
unions can exploit
small/large synergies
• Distributes risks
• Potential for conflict in
operations between
companies
• Value of one company may
be reduced over time
Licensing from others • Rapid access to technology
• Reduced financial risk
• Lack of propriety technology
and technological skills
• Dependent on licensor
Educational Acquisition • Provides window and initial
staff
• Risk of departure of
entrepreneurs
Licensing to others • Rapid access to a market
• Low cost/risk
• Will lack knowledge/control of
market
• Dependent on license Source: Aaker, D. (2001)
22
Although an organisation has a wide variety of entry strategies available, Collis
and Montgomery (2005) suggests that choosing among the various models
involves unavoidable trade-offs that need to be carefully analysed.
2.5 DIVERSIFICATIONS IMPACT ON AN ORGANISATION’S
FINANCIAL PERFORMANCE
2.5.1 Background
The core focus of this research report relates to the question of whether
diversified organisations achieve superior financial results than organisations
that choose to operate as a focused organisation. The research conducted in
determining the diversification and performance relationship has been
inconclusive and has been debated since the 1950’s. Piscitello (2004) noted
that the diversification-performance literature has failed to reach consensus and
that there is still considerable disagreement about how and when diversification
can be used to build long-term competitive advantage.
In conducting research in the diversification versus performance debate, there
are three aspects that are commonly found in the literature that will be focused
on and will be expanded on in the sections below:
• The two primary approaches in determining the level of an organisation’s
diversification are examined. The two primary approaches are the
categorisation approach, and the product count measure approach.
23
• The performance measures used to determine the organisation’s
performance are examined. The two primary measures are accounting and
market based approaches.
• The findings of some of the research as either being supportive of the
statement that diversified organisations have a positive relationship or
negative relationship to their economic performance are examined.
The three aspects are important, as they form the core of the research
conducted in the literature and are interrelated. The research would be
conducted by first grouping the organisations as diversified versus focused,
determining the performance measurements to be used in the hypotheses,
resulting in the overall findings of the research.
Other research findings are also presented that are either conceptual or
empirical that do not follow the same methodology as presented above.
2.5.2 Determining the level of an organisation’s diversification
The first aspect in the literature relating to the diversification versus
performance debate relates to the approaches used to establish the level of an
organisation’s diversification. In the literature there are two primary approaches
used to determine the level of an organisation’s diversification.
The first approach was pioneered by researchers such as Rumelt (1982) who
developed a categorisation approach whereby organisations were categorised
24
into various categories based on measurements obtained from financial data,
financial data base information and Standard Industrial Classification (SIC) code
descriptions. The second approach is referred to as the product count measure,
whereby an organisation’s SIC code is used to determine the organisation’s
primary activity, and therefore the business segments the organisation operates
in. The two approaches will be discussed in more detail below, and in her
research to compare the use of the two approaches, Montgomery (1982) found
that neither approach is superior to the other.
2.5.2.1 Rumelt’s categorisation model
The first approach developed by Rumelt (1982) contains various categories of
diversification which were classified utilising ratios of revenues earned as a
fraction of the total revenues earned within the total revenue of an organisation.
Table 5 summarizes the major categories Rumelt developed to study the
financial performance of organisations and the degree of diversification. In
Rumelt’s scheme, the least diversified (Single Business) is on the one side of
the scale and the most diversified (Unrelated Business) is on the other side of
the diversification scale. The various ratios of importance that Rumelt used to
measure the revenues earned as a fraction of total revenues earned were:
• Specialization Ratio (SR): This ratio measures the proportion of an
organisation’s revenues derived from its largest single business.
• Related Ratio (RR): This ratio measures the proportion of an organisation‘s
revenues derived from its largest single group of related businesses.
25
Table 5: Rumelt's major categories of diversification
Category Definition Ratio
Single Business Company committed to a single business SR ≥ 0.95
Dominant Business Companies that have diversified to some
extent but still obtain the predominance of
their revenues from a single business
0.7 ≤ SR < 0.95
(SR between 0.7 and 0.95)
Related Business Nonvertical dominant companies that
have diversified by building on some
particular strength with the original
dominant activity
SR < 0.7
Unrelated Business Nonvertical companies that have chiefly
diversified without regard to relationships
between new businesses and current
activities
RR < 0.7
Source: Rumelt, R. (1982)
Rumelt (1986) calculated the SR in first identifying the businesses the
organisation operated in. The activity breakdown information was obtained via
the four-digit SIC code classification over the period of study. Secondarily to the
segment breakdown via the four-digit SIC code, financial data per segment was
obtained per organisation via databases and the organisation’s prospectuses in
order to calculate the SR and RR.
Rumelt (1986) developed a further categorization of the diversification
strategies into subcategories. Table 6 below indicates the further breakdown
and definition of the subcategories Rumelt used in his research.
Table 6: Rumelt’s subcategories of diversification Category Definition
1-Single Business Organisation committed to a single business
2-Dominant Vertical Vertically integrated organisations that produce and
sell a variety of end products, no one of which
26
contributes more tan 95% of total revenues.
3-Dominant Constrained Nonvertical dominant organisations that have
diversified by building on some particular strength
with the original dominant activity.
4-Dominant Linked Nonvertical dominant organisations that has
diversified by building on new strengths, skills, or
resources as they are acquired.
5-Dominant Unrelated Nonvertical dominant organisations in which the
prevalence of the diversified activities are unrelated
to the dominant business.
6-Related Constrained Related organisations that has diversified by
relating new businesses to a specific central skill or
resource and in which each business activity is
related to almost all of the other business activities.
7-Related Linked Related organisations that have diversified by
relating new businesses to some strength or skill
already possessed, but not always the same
strength or skill. These organisations diversify in
several directions and become active in a widely
disparate business.
8-Unrelated Passive Unrelated organisations that do not qualify as
acquisitive conglomerates.
9-Acquisitive
Conglomerates
Nonvertical organisations that have aggressive
programs for the acquisition of new unrelated
businesses. Source: Rumelt, R. (1986)
The term diversification has various meanings to various individuals or
organisations, and from Rumelt’s (1982) classification and other literature, the
two primary diversification types that are most referred to are related
diversification and unrelated diversification. Related diversification is defined by
Hill (1994) as realising economies of scope in the sharing of resources and / or
the transfer of skills between two or more otherwise distinct businesses within
an organisation. Unrelated diversification is defined by Rumelt (1986) as firms
27
that diversify into areas not related to the original skills and strengths, other than
financial resources.
Rumelt’s (1982) classification has been used and modified by numerous other
researchers such as Panday and Rao (1998), Markides (1995) and Harper and
Viguerie (2002). Research conducted by Panday and Rao (1998) in the USA
used Rumelt’s classification schemes, but adjusted the SR values for their
purposes to focus on three of the categories. Panday and Rao (1998) utilized a
Compustat database to calculate the various organisations SR, whereby the
organisations were classified into their modified scheme which is summarized in
Table 7 below.
Table 7: Panday and Rao's SR classification Category Rumelt’s SR values Panday and Rao’s SR values
Single Business SR ≥ 0.95 SR ≥ 0.95
Dominant Business
(Moderately diversified
organisation)
0.7 < SR < 0.95
(SR between 0.7 and 0.95)
0.5 < SR < 0.95
(SR between 0.5 and 0.95)
Related Business
(Highly diversified
organisation)
SR < 0.7 SR < 0.5
Source: Pandaya, A. and Rao, N. (1998)
Panday and Rao (1998) argued that the adjustment of the SR from 0.7 to 0.5
was to address the contradictory arguments advanced by researchers in
finance and management disciplines.
28
Similar to Panday and Rao (1998), Harper and Viguerie (2002) modified the
categories in their Mckinsey Quarterly research whereby they classified 412 of
the Standard & Poors 500 (S&P 500) companies from the period 1990 to 2000.
Harper and Viguerie’s (2002) classification can be summarized as follows:
• Focused Organisations: Deriving at least 67% of revenues from one
business segment.
• Moderate Diversification: Deriving at least 67% of revenues from two
business segments.
• Diversified Organisations: Deriving less than 67% of revenues from two
business segments.
Harper and Viguerie (2002) argued that the cutoff point of 67% was not chosen
empirically, but that they were confident that the results would be the same
even if the cutoff varied within 10 percentage points in either direction.
Research conducted by Markides (1995) to establish refocusing efforts in the
1980’s, used Rumelt’s (1982) original categorisation classification as one of the
approaches to measure the refocusing efforts of firms during the time period of
1981 to 1987.
In research conducted by Sambharya (2000) to compare the approaches
available to researchers in the measurement of corporate diversity, he noted
various strengths and weaknesses of using Rumelt’s classification as an
approach to measure the level of diversity of an organisation.
29
Sambhaya (2000) noted the following advantages:
• Conceptual rigour. The researcher would rely on the insight in the
organisations history and behaviour to determine its utilisation of strength,
core skills and its diversification objectives.
Sambhaya (2000) noted the following disadvantages:
• The classification is subjective, and the reliability is questionable.
• The classification process is time consuming and requires extensive
information on the organisations from various sources.
The research report will focus on categorizing companies as either diversified or
focused using Rumelt’s (1982) Specialization Ratio (SR) in conjunction with the
product count measure.
2.5.2.2 Product Count Measures (Standard Industrial Classification)
The second approach used by researchers is the product count measure which
was built on the Standard Industrial Classification (SIC) system developed in
the USA. Montgomery (1982) defines the SIC classification as a numerical
system developed by the USA Federal Government for classifying all types of
economic activity within the USA economy. Each firm’s activity is classified
according to its primary activity. As Harper and Viguerie (2002) remarked that
publicly USA listed organisations have to report segmented revenues by a
Financial Accounting Standards Board (FASB) segmentation scheme.
30
Although the SIC classification was developed in the USA, the SIC system has
been adopted throughout the world and has become an internationally accepted
classification mechanism of all economic activities. According to the South
African Companies and the Intellectual Property Registration Office (CIPRO)
(2006), the SIC was developed for the classification of the kind of economic
activity and provides a standardised framework for the collection and analysis of
statistical data. See Appendix 1 for an extract of some of the SIC codes
obtained from CIPRO.
The SIC classification consists of a five digit number that has the following
meaning and filters down to more deeper levels of economic activity as
indicated in Table 8 below:
Table 8: SIC Code Levels SIC Digit Level of economic activity
First Digit Major Division
Second Digit Division
Third Digit Major Group
Fourth Digit Group
Fifth Digit Sub-Group Source: South African Companies and Intellectual Property Registration Office (CIPRO)
http://www.cipro.co.za/info_library/sic_codes.asp
If for example the SIC code was 35592, the following meaning can be derived
from the SIC code in Table 9 below:
31
Table 9: Example of SIC code description SIC Digit SIC
Code Level of economic activity
Description of the activity relative to the corresponding SIC Code
First Digit 3 Major Division Manufacturing
Second Digit 5 Division Manufacture of basic metals, fabricated metal
products, machinery and equipment and of
office, accounting and computing machinery.
Third Digit 5 Major Group Manufacture of other fabricated metal products;
metalwork service activities
Fourth Digit 9 Group Manufacture of other fabricated metal products
Fifth Digit 2 Sub-Group Manufacture of cables and wire products Source: South African Companies and Intellectual Property Registration Office (CIPRO)
http://www.cipro.co.za/info_library/sic_codes.asp
Researchers such as Rumelt (1986), Berger and Ofek (1995), Delios and
Beamish (1999) and Ushijima and Fukui (2004) used the SIC code approach to
measure the level of diversification in their studies.
Berger and Ofek (1995) researched diversification’s effect on firms’ value, and
utilised the SIC code approach to classify the diversification levels of the
organisations in their samples from 1986 to 1991. In the USA, organisations are
required to report segmented information where sales or profits exceed 10% of
the consolidated totals. From the segmented reporting, the SIC code
information was obtained.
In Delios and Beamish (1999) research, the diversification levels of 399
Japanese manufacturing organisations were tested. The source of information
32
in their study was the Japanese Company Handbook to determine the
industries in which the organisations operated. Delios and Beamish (1999) used
the three-digit SIC level to classify the diversification levels, but would have
preferred to use the four-digit SIC code classification level. Due to limitations on
industry details and source information, the three-digit SIC code level was
utilised. In a similar study Ushijima and Fukui (2004) studied 118 Japanese
manufacturing organisations from 1973 to 1998. During their study the
organisations’ sales were segmented by product into SIC codes, whereby
analysis was done at the four-digit SIC code level.
In research conducted by Sambharya (2000) to compare the approaches
available to researchers in the measurement of corporate diversity, he noted
various strengths and weaknesses of using the product-count approach (SIC) to
measure the level of diversity of an organisation.
Sambhaya (2000) noted the following advantages:
• Simplicity and ease of measurement and computation.
Sambhaya (2000) noted the following disadvantage:
• Validity and reliability is questioned.
2.5.2.3 Combination of both approaches
Research conducted by Montgomery (1982) in the use of both the
categorisation and the product count approach (SIC code), concluded that there
are strengths and weaknesses in both approaches. In her findings she found
33
that the SIC code approach was more acceptable than previous criticism would
indicate, and that at the two-digit, three-digit and four-digit SIC code level
analysis was favourable. In her findings she also concluded that neither
approach is superior to the other.
Research conducted by Rumelt (1986), Markides (1995) and Harper and
Viguerie (2002) used both approaches to measure the level of diversification of
the organisations in their studies. Markides (1995) used Rumelt’s classification
in his sample of 200 organisations from 1981 to 1987 as well as the SIC code
approach. Markides (1995) made use of a USA database called Trinet and
measured the level of diversification up to the two-digit SIC code level.
Harper and Viguerie (2002) used their modified categorisation as indicated
above, as well as the SIC code analysis. In their research they found that the
organisations that formed part of their classification system were similar to the
organisations that were identified using the SIC code approach.
2.5.3 The performance measures used in research
The second aspect that relates to the diversification-performance literature is
the use of performance measures. In the literature, various researchers made
use of different performance measures, although the most common
performance measures used were Return on Equity (ROE) and Return on
Assets (ROA).
34
Varadarajan and Ramanujam (1987) researched diversification and
performance and used four performance measures in their study. They
mentioned that the four measures they used were consistent with previous
studies and that their work would be comparable to previous studies conducted.
The four performance measures used and calculated using a five year average
by Varadarajan and Ramanujam (1987) were:
• Profitability Measures
o Return on Equity (ROE)
o Return on Capital (ROC)
• Growth Measures
o Sales Growth Rate (SRG)
o Earnings per share Growth Rate (EPSGR)
Research conducted by Panday and Rao (1998) focused on accounting
variables and a market variable during their study of 2 637 US firms during the
period 1984 to 1990. The performance measures used by Panday and Rao
(1998) were as follows:
• Accounting Variables
o Return on Equity (ROE)
o Return on Assets (ROA)
• Market Variable
o Market Return (MKTRET)
The three performance measures were averaged over the period of study per
diversification category to calculate an Average Return on Equity (AROE), an
35
Average Return on Assets (AROA) and an Average Market Return (AMKTRET)
per category, to be able to identify if the one category of organisations
performed better than the other.
According to Hall and Lee (1999), past empirical studies on diversification made
use of accounting-based performance such as Return on Assets (ROA) and
Return on Equity (ROE), but more focus is being given to market-based
performance measures such as Market Value of Equity (MVE) and Market
Value of Assets (MVA).
Table 10 below is a summary of some of the performance measures that were
used by a variety of researchers in their studies to determine the diversification-
performance relationship:
Table 10: Summary of performance measures used in research Performance Measure Description of the measure Researcher
• Annual Rate of growth in
sales (GSALES)
• Annual Rate of growth in
earnings after tax
GERN)
• Annual Rate of growth in
earnings per share
(GEPS)
• Price – Earnings Ratio
(P/E Ratio)
• Return on Equity (ROE)
• Return on Capital (ROC)
• Internal Financing Ratio
(IFR)
Rumelt’s (1986) study was conducted
on a sample of 246 organisations in
the USA. The population was the 500
largest industrial corporations.
Rumelt (1986) measured the
performance of the 246 organisations
over the period from 1951 to 1970.
The strategic categorisation was
conducted at three points in time:
1949, 1959 and 1969 and the annual
financial measures were averaged
per decade, and then further
averaged over the entire period from
1951 to 1970.
Rumelt (1986)
36
• Return on Assets (ROA)
The average ROA per firm was
calculated then divided by its
standard deviation to allow for
comparison across firms.
Dubofsky and
Vardarajan (1987)
• Return on Equity (ROE)
• Return on Capital (ROC)
• Sales Growth Rate
(SRG)
• Earnings per Share
Growth Rate (EPSGR)
The research focused on four
measures as SGR and EPSGR
measures the firm’s rate of growth,
while ROE and ROC reflect the
productivity of capital employed by
the firm.
Varadarajan and
Ramanujam (1987)
• Return on Capital (ROC)
• Sales Growth
ROC and sales growth were
employed over a three year period
from 1978 to 1980.
Capon, Hulbert, Farley
and Martin (1988)
• Operating Margin
(EBIT/Sales)
• Return on Assets (ROA)
Calculated the Operating Margin and
ROA per category.
Berger and Ofek
(1995)
• Return on Equity (ROE)
• Return on Assets (ROA)
• Market Return
(MKTRET)
Used accounting and performance
measures to measure the average
calculation of each category of either
diversified or focused group.
Panday and Rao
(1998)
• Return on Equity (ROE)
• Return on Assets (ROA)
• Return on Sales (ROS)
During the research the accounting
based measures were computed as a
5 year average from 1991-1995.
Delios and Beamish
(1999)
• Return on Equity (ROE)
• Return on Assets (ROA)
• Market Value of Equity
(MVE)
• Market Value of Assets
(MVA)
The research conducted utilised
accounting based measures in ROE
and ROA as well as market based
measures in MVE and MVA.
Hall and Lee (1999)
• Return on Equity (ROE)
• Return on Assets (ROA)
The research was conducted using
ROE and ROA to determine the firms
operating profit.
Singh et al. (2001)
• Return on Assets (ROA)
In the analysis of profitability the
average ROA was calculated per
industry classification.
Ushijima and Fukui
(2004)
37
The performance measures used in previous research as indicated above were
used in this research report to ensure consistency in performance
measurements.
2.5.4 Results of financial performance of diversified companies
The third aspect relating to research conducted in the diversification-
performance debate was the outcome of the results. Many studies have been
conducted internationally to establish if diversification has led to an increase in
a firm’s economic performance. The various studies have resulted in different
outcomes. Palich et al. (2000) noted that there has been inconsistency in the
findings of the diversification-performance research for more than 30 years and
that there is a lack of consensus. Some of the empirical findings were either a
positive relationship to economic performance (e.g., Panday and Rao, 1998:
Singh, Mathur, Gleason and Etebari 2001; and Piscetello, 2004), a negative
relationship with economic performance (e.g., Markides, 1995; Lins and
Servaes, 2002 and Gary, 2005), a curvature relationship depending on the level
of diversification (e.g., Varadarajan and Ramanujam, 1987; Hitt et al.,1999 and
Palich et al. 2000) or a result that depends on the various levels and types of
diversification (Rumelt, 1986).
2.5.4.1 Diversification has a positive relationship with an organisation’s
financial performance
Researchers such as Panday and Rao (1998), Singh et al. (2001) and
Piscetello (2004) and others have found that the relationship between the level
38
of diversification and the financial performance of an organisation is positively
related.
Panday and Rao’s (1998) study concluded that, on average, diversified firms
showed superior performance compared to focused firms on both risk and
return dimensions. Their study made use of accounting and market return ratios
to measure the performance. In a study conducted by Singh et al. (2001)
utilising a sample of 1 528 firms from 1990 to 1996, they found that diversified
firms performed better than focused firms. The reasons for their results were
that diversified firms improved their leverage, and had a nominal decline in
operating performance, whereas focused firms reduced their leverage and had
a superior operating performance.
In a study conducted by Piscetello (2004) to measure corporate diversification,
coherence and economic performance over the period 1987 to 1993, it was
found that there was a positive relationship between corporate diversification,
coherence and financial performance. The study was conducted using a sample
of 248 industrial organisations of which 109 were USA organisations, 86
European organisations and 53 were Japanese organisations.
39
2.5.4.2 Diversification has a negative relationship with an organisation’s
financial performance
Researchers such as Markides (1995), Lins and Servaes (2002) and Gary
(2005) and other researchers have found a negative relationship between the
level of diversification and the economic performance of an organisation.
Studies conducted by Markides (1995) suggested a negative relationship
between diversification and the organisation’s average profitability, but did not
necessarily imply that diversified organisations were not maximizing profits, only
that their marginal returns decreased as they diversify further. The
measurements were applied utilising profitability ratios, debt ratios and capital
expenditure ratios.
Delios and Beamish’s (1999) research tested the performance of 399 Japanese
manufacturing firms. The nature of the study focused on accounting ratios to
measure performance, and applied the SIC code approach to determine the
diversification categories. They found that performance was not related to the
extent of product diversification, although investments levels in rent-generating,
propriety assets were related to the extent of product diversification.
In a study conducted by Gary (2005) to determine strategy and performance
outcomes in related diversification, found that a higher degree of relatedness
could intensify resource overstretching in an organisation, which caused lower
profitability compared to an organisation which was less related. He argued that
40
the potential costs of increased relatedness could outweigh the benefits
created. The measurements were applied in developing and modeling cost
structures of organisations that included the fixed costs, costs of shared
resources and variable costs of servicing new business customers.
Berger and Ofek (1995) calculated that on average, diversified organisations
had a value loss of between 13% and 15% of the 3 659 organisations that were
studied in the USA during 1986 and 1991. They measured the excess value of
the diversified organisations as the natural logarithm of the ratio of an
organisation’s actual value to its imputed value. An organisation’s imputed value
was defined as the sum total of imputed segment’s, with each segment’s
imputed value equal to the segments’ assets, sales or earnings before interest
and tax (EBIT), multiplied by its industry median ratio of capital to that
accounting item.
Similar findings were reported by Lins and Servaes (2002), who measured
corporate diversification in emerging markets from a sample of over 1 000 firms
in 1995, and found that diversified firms traded at a discount of approximately
7% compared to focused firms, and that diversified firms were less profitable
than focused firms. The method to determine the results were a valuation
approach whereby the median market-to-sales ratios were used to compare
with the individual organisation segmented level of sales.
41
2.5.4.3 Diversification has a curvilinear relationship with an organisation’s
financial performance
Research conducted by Palich et al. (2000) noted that the curvilinear
relationship between corporate diversification and financial performance
(measured as accounting data) suggested that benefits accrue to diversification,
but at some point the efforts of diversification are associated with major costs.
The research was supported by Varadarajan and Ramanujam (1987), using
accounting ratios, which found that related diversified organisations
outperformed unrelated diversified organisations, and that the performance
between extremely low levels and extremely high levels of diversity was
generally insignificant.
Hitt et al. (1999) illustrates that a curvilinear relationship exists between
diversification and performance. An increased level of diversification at a point
where a company diversifies at a related constrained level, leads to an
increased level of performance. Levels of performance reduce, however, when
companies diversify at high levels in unrelated businesses. Figure 1 below
illustrates the curvilinear relationship between diversification and performance.
42
Figure 1: Curvilinear relationship between diversification and performance
Source: Hitt, M. ,Irelan, R. and Hoskisson, R. (1999)
2.5.4.4 Other research studies relating to diversification
Other research findings are also presented that are either conceptual or
empirical that do not necessarily follow the same methodology as presented
above.
2.5.4.4.1 Ansoff Ansoff (1958) in his conceptual planning framework for diversification suggested
that there could be a multiple variety of tests that could be used to measure the
value of the proposed diversification on the organisation. He concluded that the
most common single test was in the form of Return on Investment, and his
model was one of successive elimination of alternatives involving the
Level of Diversification
Perf
orm
ance
Dominant Business
Related Constrained
Unrelated Business
43
application of qualitative criteria, followed by a mathematical comparison of
potential profit earned before and after a diversification scenario has been
developed for an organisation. Ansoff (1958) argued that in order to asses the
full effect of diversification, an organisation would have to calculate an average
return over a period which included the transition to diversify the operations.
Only if the potential profit is greater than the cost should a diversified strategy
be considered.
2.5.4.4.2 Rumelt’s study
Rumelt’s studies are regarded as one of the most influential and widely
investigated typologies in the strategy literature (Hall and St. John, 1994). The
findings of Rumelt’s (1986) empirical study conducted on a sample of 246
organisations over a period of two decades from 1949 to 1969 are summarized
below:
• Performance differences existed between the major categories of
diversification strategy (Single, dominant, related and unrelated businesses).
The differences were however highlighted in more detail once the categories
were broken down into subcategories.
• The Dominant Vertical organisations were low performing while the
Dominant Constrained organisations were among the highest performing.
• The Related Constrained subgroup was high performing while the Related
Linked subgroup was slightly below average.
44
• The Dominant Constrained and the Related Constrained subgroups were
the best overall performers and both strategies were not totally dependent
upon a single business or a true multi-industry organisation.
2.5.4.4.3 Porter’s study Porter (1987) studied the diversification record of 33 large US companies over a
period from 1950 to 1986. Unlike other researchers using financial data and
shareholder value, Porter (1987) conducted an empirical study in which he used
the number of units retained by the company over the period of 26 years as an
indication of the success of the organisations in terms of their diversification.
Porter’s (1987) study is summarized below:
• Each organisation entered on average 80 new industries and 27 new fields.
• Just over 70% of the new entries were acquisitions of which 22% were start-
ups and 8% were joint ventures.
• On average the organisations divested more than half their acquisitions and
more than 60% of their acquisitions in entirely new fields.
• Fourteen organisations divested more than 70% of all the acquisitions they
made in the new fields.
In Porter’s view, only the investment bankers, lawyers and the original sellers of
the businesses prospered in most of the acquisitions. Porter further concluded
that diversification did not add value due to the following reasons:
45
• Competition occurs at the business unit level and not as a diversified
organisation.
• Diversification adds costs and constraints to business units, such as
corporate overheads and bureaucracy.
Porter (1987) argued that certain conditions need to be met in order for
diversification to create shareholder value and are called the essential test. The
three questions that need to be answered are:
• How attractive is the industry? Diversification cannot create shareholder
value unless new industries have favourable structures that support returns
in excess of the cost of capital, and an industry needs to be attractive before
diversification commences. After the diversification has taken place, only
then can the industry’s structure be transformed.
• What is the cost of entry? Organisations strive to enter the market through
acquisition or start-up, and organisations could end up paying more than
market value for an acquisition. Organisations should do proper costing and
not forget to apply the cost-of-entry tests.
• Will the business be better off? Organisations should consider
diversification when new businesses present benefits in excess of a once off
yield, and organisations should employ a diversification of risk strategy only
as a by-product of corporate strategy and not as the primary motivator.
46
2.5.4.4.4 Hamel and Prahalad
Hamel and Prahald (1996) wrote in their book “Competing for the future” that
organisations destroyed shareholder value in the 1970’s and early 1980’s, and
that diversification into areas where organisations lack knowledge and
capabilities was a disaster.
Hamel and Prahald (1996) argued that organisations tended to get involved in
areas they had no experience in and that growth and diversification around
organisations’ core competencies should be pursued. Hamel and Prahald
(1996, p. 322) define core competence as “the connective tissue that holds
together a portfolio of seemingly diverse businesses”. They argue that core
competence-based diversification reduces risk and investment and increases
the opportunity for transferring skills and best practice across business units
2.6 SOUTH AFRICAN STUDIES
From a South African perspective, there has been no systematic study of the
diversification-performance relationship. The apartheid policies of the past
drove South Africa into economic isolation, forcing many organisations to
diversify from the 1960’s to the early 1990’s.
From a corporate restructuring point of view an empirical study was conducted
by Bhana (2004), which measured the performance of corporate restructuring
through spin-offs of organisations that were listed on the JSE. In his study,
47
which was conducted from 1988 to 1999, he found that the divesture by the
parent organisations via a spin-off had a positive outcome for both the parent
organisation as well as the spun-off organisation. Bhana (2004) found in his
sample of 47 voluntary spin-offs that were initiated by 19 parent organisations
that positive abnormal returns were achieved for up to three years beyond the
spin-off announcement date, thus suggesting that the South African
organisations that became more focused did benefit in terms of financial
performance.
This research report intends to conduct a study to compare the financial
performance of the industrial sector of JSE listed companies divided into
diversified organisations and focused organisations and to establish if the one
group’s financial performance is superior to the other group’s financial
performance.
48
3. RESEARCH HYPOTHESES Various international studies focus on different measures to establish if
diversification results in greater economic performance. Palich et al. (2000)
found in their study that the two main measures that were used were accounting
and market based performance measures. In their study they found that
diversification was related to accounting and market performance outcomes.
The specific research hypotheses that will be used are a combination of the
accounting and market based performance measures:
Hypothesis 1: The Average Return on Equity (AROE) of the diversified
organisations is higher than the AROE of the focused organisations.
Hypothesis 2: The Average Return on Assets (AROA) of the diversified
organisations is higher than the AROA of the focused organisations.
Hypothesis 3: The Average Market Return (AMKTRET) of the diversified
organisations is higher than the AMKTRET of the focused organisations.
Hypothesis 4: The Average Earnings per share growth rate (AEPSGR) of the
diversified organisations is higher than the AEPSGR of the focused
organisations.
Hypotheses 1, 2 and 3 were used in the research conducted by Panday and
Rao (1998) in their study of 637 USA firms during the period 1984 to 1990.
Hypotheses 1 and 2 relate to accounting measures, while hypothesis 3 relates
to market based measures. The three performance measures were averaged
over the period of study per diversification category to calculate an Average
49
Return on Equity (AROE), an Average Return on Assets (AROA) and an
Average Market Return (AMKTRET) per category, to be able to identify if the
one category of organisations performed better than the other.
Hypothesis 4 was used in the research conducted by Rumelt (1986) where the
Earnings per share growth rate were measured over the period from 1951 to
1970. The strategic categorisation of the organisations was conducted at three
points in time: 1949, 1959 and 1969 and the Earnings per share growth rates
were averaged per decade, and then further averaged over the entire period
from 1951 to 1970, resulting in an Average Earnings per share growth rate
(AEPSGR) per category.
50
4. RESEARCH METHODOLOGY
4.1 RESEARCH DESIGN
The research design used for the study was quasi-experimental research as
described by Welman and Kruger (2005). To define quasi-experimental
research it is important to define experimental research first to be able to
recognize the difference between the two.
Welman and Kruger (2005) define experimental research as research where the
units of analysis are exposed to something to which they otherwise would not
have been subjected. True experimental research is conducted where the
researcher has optimal control over the research situation and where the
researcher can assign the unit of analysis randomly to groups of design.
Quasi-experimental research described by Welman and Kruger (2005) differs
from true experimental research in that the researcher cannot randomly assign
a unit of analysis to the different groups of study.
The goal of this study was to categorise organisations listed in the industrial
sector of the JSE into two groups of 15 organisations as being diversified or
focused, based on the calculation of the SR of each organisation. It was for this
reason that the quasi-experimental research design was chosen as the
organisations had to be categorised into the two groups utilising the SIC code
measure as indicated in Appendix 1. The SR was calculated for the year 2001
51
and 2005 to ensure that the organisations remained diversified or focused at the
start of the period, and at the end of the period.
4.2 UNIT OF ANALYSIS
Welman and Kruger (2005) define units of analysis as the members or elements
of a population. In the research conducted, the unit of analysis was the
organisations listed in the industrial sector of the JSE. The list of organisations
listed in the industrial sector was obtained from the daily financial press as listed
by The Business Day’s Market Wrap (2006).
For the purposes of the research, the organisations listed in the industrial sector
were grouped as either diversified or focused using Rumelt’s (1982)
Specialization Ratio (SR).
4.3 POPULATION OF RELEVANCE
Welman and Kruger (2005) define a population as an entire collection of cases
or units about which one wishes to make conclusions. The population of
relevance that applied to the research was the organisations that were listed in
the industrial sector of the JSE. In Table 11 below are the 58 listed
organisations that were listed in the industrial sector of the JSE which
represents the complete population of relevance of the research.
52
Table 11: Organisations listed in the industrial sector of the JSE
Source: Market Wrap (2006) Business Day.
Com pany Nam e JSE SharecodeAdcorp Holdings Lim ited ADRAG Industries Lim ited AG IAllied Electronics Corporation Lim ited ATNAm algam ated Electronic Corporation Lim ited AERArgent Industrial Lim ited ARTAstrapak Lim ited APKAveng Lim ited AEGBarloworld Lim ited BAWBasil Read Holdings Lim ited BSRBell Equipm ent Lim ited BELBicc Cafca Lim ited BICBidvest Group Lim ited BVTBowler Metcalf Lim ited BCFBuildm ax Lim ited BDMCargo Carriers Lim ited CRGCeram ic Industries Lim ited CRMCom m and Holdings Lim ited CMAConcor Lim ited CNCConsol Lim ited CSLControl Instrum ents Group Lim ited CNLDelta Electrical Industries Lim ited DELDigicor Holdings Lim ited DGCDistribution and W arehousing Network Lim ited DAWDorbyl Lim ited DLVELB Group Lim ited ELREnviroServ Holdings Lim ited ENVExcellerate Holdings Lim ited EXLG rindrod Lim ited GNDG roup Five Lim ited GRFHowden Africa Holdings Lim ited HW NHudaco Industries Lim ited HDCIliad Africa Lim ited ILAIm perial Holdings Lim ited IPLInvicta Holdings Lim ited IVTJasco Electronic Holdings Lim ited JSCKairos Industrial Holdings Lim ited KIRKAP International Holdings Lim ited KAPMasonite Africa Lim ited MASMetrofile Holdings Lim ited MFLMobile Industries Lim ited MOBMonteagle Holdings Societe Anonym e MTEMurray & Roberts Holdings Lim ited MURMvelaphanda G roup Lim ited MVGNam pak Lim ited NPKPasdec Resources SA Lim ited PSCPretoria Portland Cem ent PPCPrim eserv Group Lim ited PMVQ uyn Holdings Lim ited QUYReunert Lim ited RLOSekunjalo Investm ents Lim ited SKJSet Point Technology Holdings Lim ited STOSuper G roup Lim ited SPGTranspaco Lim ited TPCTrencor Lim ited TREValue Group Lim ited VLEVenter Leisure and Com m ercial T railers Lim ited VTLW ilson Baily Holm es-O vcon Lim ited W BOW inhold Lim ited W NH
53
4.4 SAMPLE SIZE AND SAMPLING METHOD
The sampling method that was employed in the research was by way of a non-
probability convenient sample. According to Welman and Kruger (2005) non-
probability sampling is the probability that any unit of analysis will be included in
a non-probability sample and cannot be specified, and in some instances
certain members may have no chance at all of being included in such sample.
Albright, Winston and Zappe (2003) refer to non-probability sampling as a
judgement sample where no formal random mechanism is used and that the
sampling units are chosen according to the sampler’s judgement.
The organisations were analysed according to the three-digit SIC code analysis
in 2001 and 2005. The SIC code analysis was important to confirm if an
organisation was diversified or focused based on the information obtained in the
organisation’s published annual reports. The SIC code analysis was applied to
organisations that reported segmented revenues in the annual reports in 2001
as well as 2005 to ensure that an organisation was diversified or focused at the
beginning of the period, as well as the end of the period. The SIC code analysis
was conducted at the three-digit SIC code level whereby the various
classifications were assigned to the revenue streams of the organisations.
Once the SIC code analysis was completed, the organisation’s SR was
calculated utilising Rumelt’s (1982) classification. Rumelt (1982) developed
nine categories of diversification, while this research only focused on two levels
of diversification. Similar to the research conducted by Panday and Rao (1998),
54
adjustments were made to the SR threshold in their research. The SR for the
focused organisations has been adjusted from 0.95 to 0.90, as it was found that
very few organisations SR was greater than 0.95 as indicated in Table 12
below.
Table 12: Specialisation Ratios used in this research Category Rumelt’s SR values This research report SR
values
Single Business
(Focused Organisation)
SR ≥ 0.95 SR ≥ 0.90
Related Business
(Diversified
Organisation)
SR < 0.7 SR < 0.7
Source: Rumelt, R. (1982)
Organisations were classified into two groups based on their SR. Organisations
SR that was greater than 0.90 in 2001 and 2005 were grouped as focused, and
organisations where their SR was less than 0.70 in 2001 and 2005 were
grouped as diversified organisations.
The following organisations were excluded from the samples:
• Organisations that were not listed on the JSE during the period of study.
• Organisations’ SR that did not remain constant in the diversified or focused
categories in 2001 and 2005.
• Organisations that have their primary listing in another country other than
South Africa.
• Organisations that had a separate listing for preference shares or options
listed as separate instruments to the ordinary shares.
55
• Organisations that did not report separate revenue streams or where no
conclusion of separate revenue per business unit could be made
Each category of diversified or focused group had a sample of 15 organisations
so as to ensure similar sample sizes. The categorisation process was important
as the organisations’ financial performance was compared to identify which
group outperformed the other.
4.5 DETAILS OF DATA COLLECTION
The details of the data collection can be divided into two categories. The first
category related to the collection of data to determine the level of diversification
of the various organisations, and the second category related to the collection of
the performance data of the organisations once the categorisation of the
diversified versus focused was completed.
4.5.1 Data to determine the level of diversification
The data that was required to establish if an organisation was diversified or
focused was primary data. Welman and Kruger (2005) define primary data as
original data that has been collected by a researcher for the purposes of his or
her own study at hand. The organisations’ published annual reports were
required for the year 2001 as well as 2005 to be able to establish the revenue
earned per reported segment. The majority of the 2005 annual reports were
56
available on the organisations’ websites, whereas the majority of the 2001
annual reports had to be requested from the organisations.
The reported revenues per segment and operational review description were
used to correlate to the three-digit SIC code to establish the revenue earned per
economic activity as described by the three-digit SIC code definitions. (An
extract from the CIPRO website is contained in Appendix 1).
The above process in establishing the three-digit SIC code per segment and
operational review was manual in nature as there is no public database
available in South Africa that has all the SIC code information available per
organisation. This was unlike the research that was conducted by Berger and
Ofek (1995), Delios and Beamish (1999) and Ushijima and Fukui (2004) where
databases with the relevant SIC code information was available. In the case of
the research that was conducted by Berger and Ofek (1995) in the USA, the
Compustat Industry Segment (CIS) database was used to extract the
segmented information.
Where additional information was required to clarify the operations of an
organisation the following additional sources were used:
• The internet websites of the particular organisation was consulted to gain a
further understanding
• Profiles bi-annually published “Stock Exchange Handbook”
• McGregor’s annually published “Who owns whom” handbook
57
4.5.2 Performance data
Once the categorisation of the diversified versus the focused organisations was
completed, the performance data per organisation per year was required. The
performance data that was used was secondary data. Welman and Kruger
(2005) define secondary data as information obtained by individuals, agencies
and institutions other than the researcher himself. The performance data was
obtained from McGregor’s Bureau of Financial Analysis (BFANet) database,
which is a vendor that supplies financial data relating to listed companies to
subscribers.
The various performance data definitions and timeframes are listed below.
4.5.2.1 Return on Equity
The Return on Equity %( ROE %) data was obtained from the McGregor’s
BFANet database. The return data obtained was data per organisation per year
from 2001 to 2005. The definition of ROE % used by McGregor was:
ROE %= Profit attributable to ordinary shareholders
(Ordinary shareholders interest + Directors loans + Shareholders loans) X 100
4.5.2.2 Return on Assets
The Return on Assets %( ROA %) data was obtained from the McGregor’s
BFANet database. The return data obtained was data per organisation per year
from 2001 to 2005. The definition of ROA % used by McGregor was:
58
ROA % = Investment Income + Operating Profit + Interest Received + Associated Income
Total Assets X 100
4.5.2.3 Market Return
The Market Return per organisation had to be calculated using the year end
share price and the dividends paid for the year. The year end share price and
dividend data was obtained from the McGregor’s BFANet database. The data
obtained was data per organisation per year from 2001 to 2005. The calculation
of the Market Return as used by Panday and Rao (1998) was calculated as
follows:
Market Return = Difference between the current year’s ending share price and
the previous year’s share price + Dividends paid for the year, divided by the
previous year’s share price.
In order to have calculated the Market Return, which was not available, two
data sets were obtained from the McGregor’s BFANet database to calculate the
Market Return:
• The Year end share price. The definition of year end share price used by
McGregor was:
Year end share price = Dividing the total monetary value of shares sold during
the last month of the financial year, by the number of shares sold during that
month.
• The ordinary dividends paid for the year. The definition of the ordinary
dividends used by McGregor was:
59
Ordinary dividends = Ordinary dividends declared or provided in favour of the
various classes of ordinary shareholders in respect of the current financial
period.
4.5.2.4 Earnings per share
The Earnings per share (EPS) data was obtained from the McGregor’s BFANet
database. The EPS data obtained was data per organisation per year from
2001 to 2005. The definition of EPS used by McGregor was the Headline
Earning per share per year per organisation. Once the EPS was obtained, the
annual growth rate of the EPS had to be calculated.
Once all the performance data was received, the validity of the data had to be
verified. In some cases the data was incorrect and a full reconciliation and data
scrub was performed to ensure that the data was corrected for any errors. The
performance data from the McGregor’ BFANet database was compared to other
sources of financial information. The sources that were used to reconcile and
correct the performance data were:
• Profiles bi-annually published “Stock Exchange Handbook”
• McGregor’s annually published “Who owns whom” handbook
• Moneyweb website
• Sharenet website
60
4.6 PROCESS OF DATA ANALYSIS
Welman and Kruger (2005) mentioned that statistical techniques could be
divided into two categories. The first category was referred to as descriptive
statistics, and the second category was inferential statistics. The data analysis
below was divided into descriptive and inferential statistics.
4.6.1 Descriptive statistics
According to Welman and Kruger (2005) descriptive statistics refer to the
description and general characteristics of the data that was obtained for a group
of individual units of analysis. Descriptive statistics per performance
measurement were presented in a tabular format which consisted of the
following elements: mean, median, range, minimum, maximum and standard
deviation. Black (2004) defined the various descriptive statistical elements as
detailed in Table 13 below.
Table 13: Descriptive statistical elements Statistical Element Definition
n The amount of occurrences within the sample
Mean The long-run average of occurrences
Median The middle value in an ordered array of numbers
Range The difference between the largest and smallest values in a
set of numbers
Minimum The smallest value in a set of numbers
Maximum The largest value in a set of numbers
Skewness The lack of symmetry of a distribution of values
Kurtosis The amount of peakedness of a distribution
Standard deviation The square root of the variance that provides and indication of
the spread of the data Source: Black, K. (2004)
61
4.6.2 Inferential statistics
Welman and Kruger (2005) defined inferential statistics as inferences a person
can make about a population index on the basis of a corresponding index
obtained from samples of populations. The use of parametric and
nonparametric statistics was used to make such inferences about a population
in hypothesis testing. Black (2004) referred to parametric statistics as statistical
techniques that were based on assumptions about a population from which the
sample data was selected. One of the assumptions of parametric statistics was
that the population was normally distributed.
The other statistical technique, nonparametric statistics, was defined by Black
(2004) as statistics that have fewer assumptions about the population, one of
which was the assumption that the population was not normally distributed.
4.6.2.1 Hypothesis Testing
In order to prove or disprove the hypothesis in the research it was necessary to
compare the means of the two independent categories of organisations. The
means of the focused organisations had to be compared to the means of the
diversified organisations of which parametric and nonparametric tests were
conducted.
The parametric test used in this research study was the one-tailed t-test where
the ρ-value approach was used. Albright et al. (2003) defines a one-tailed t-test
as one that is supported only by evidence in a single direction. The use of one
direction (one-tailed test) was used as the hypotheses tested the means of the
62
performance data as greater for the one category than the other. Albright et al.
(2003) further noted that the use of the ρ-value approach of one-tailed t-tests
had become more popular, and defined the ρ-value approach as the probability
of seeing a sample with at least as much evidence in favour of the alternative
hypothesis as the sample actually observed. The smaller the ρ-value, the more
evidence existed in favour of the alternative hypothesis.
Rumelt (1986) and Varadarajan and Ramanujam (1987) studies made use of
Analysis of Variance (ANOVA) statistical techniques to prove or disprove their
hypotheses. The ANOVA test analysed data from a randomized sample and
measured whether there are differences in the means of two or more
independent groups. As Rumelt’s study and Varadarajan and Ramanujam’s
study analysed more than two groups, ANOVA was used to measure
differences between the means of the various independent groups. This
research study only focuses on two independent groups (focused and
diversified organisations), thus the one-tailed t-test was applied.
Similar to this research study, Panday and Rao’s (1998) study tested the null
hypothesis of equality of the means of each independent group, two groups at a
time, instead of an ANOVA test across all three of the groups. The null
hypothesis was rejected where the observed t-value was greater than the t-
critical level (significant level), which is similar to the one-tailed t-test where the
ρ-value approach was used in this study.
63
The one-tailed t-test with the ρ-value approach was used and performed
according to the steps that were outlined by Berenson and Levine (1996). The
steps that were performed were as follows:
• The null hypothesis (H0) was stated.
• The alternative hypothesis (H1) was stated.
• The significant level alpha (α) was chosen.
• The sample size (n) was determined from the performance data.
• The ρ-value was calculated from the statistical software used. The statistical
software used in the research was the Number Cruncher Statistical System
(NCSS).
• The ρ-value was compared with the significant alpha (α) level.
• The outcome of the test determined if the null hypothesis (H0) was going to
be rejected or not. The following rules were applied to the observed ρ-
values:
o If ρ≥ α, the null hypothesis (H0) was not rejected
o If ρ< α, the null hypothesis (H0) was rejected
The one-tailed t-test with the ρ-value approach used above assumed the
sample distribution to be normally distributed. Berenson and Levine (1996)
remarked that for most population distributions, the sampling distribution of the
mean will approximately be normally distributed if samples of at least 30
observations were selected. Although each independent category of focused
organisations and diversified organisation had 15 organisations in each
category, five years data was used in the test. Each hypothesis test tested the
independent categories with a sample of 75 data observations (15 organisations
64
multiplied by five years of data each), which was in excess of the 30 sample
observations mentioned by Berenson and Levine (1996).
Although the one-tailed t-test with the ρ-value approach assumed a normal
distribution, NCSS automatically performed additional nonparametric tests in
conjunction with the t-test that enabled the research to be tested with additional
tests. The additional nonparametric tests performed were:
• Aspin-Welch unequal-variance test. The test was performed where
unequal variances occur and gave another level of comfort when the tests
were performed.
• Mann-Whitney U test. Black (2004) mentioned that the Mann-Whitney U
test tested and compared the means of two independent samples. It was to
be used when there was doubt of the distribution being normally distributed.
Although the sample size of the two independent categories was greater than
30 observations and therefore could assume normality, the additional tests were
performed to confirm the results.
The tests were conducted per hypothesis whereby all the observations were
included in the sample. As there were large outliers present in the observations,
a second test per hypothesis was performed whereby the large outliers were
removed from the sample to evaluate the impact the outliers had on the results.
One additional test per hypothesis was conducted to evaluate the impact the
65
removal of the outliers had on the results. Black (2004) defined an outlier as a
data point that lay apart from the rest of the observations.
4.7 LIMITATIONS OF THE RESEARCH
The limitations of the research that was conducted can be summarised as
follows:
• The population of the Industrial sector on the JSE limited the number of
organisations to 58. It would have been ideal to expand the research to all
the organisations listed on the JSE.
• The manual nature of calculating and interpreting the segmented and
operational overview revenue of each organisation to correspond to the
appropriate SIC code was judgemental at times. Where the SIC code
description did not match the description in the annual reports, a judgement
call had to be made to correspond the SIC code to the revenue segment as
closely as possible.
• The performance data had to be reconciled and data scrubbed to ensure the
data was accurate as errors were found.
• The sample size of 15 organisations per category was limited in size,
although there were 75 observations within the samples.
• Large outliers existed in the samples which skewed some of the test results.
The research methodology used in the research was a two step approach. The
first step was to calculate and determine the level of diversification per
66
organisation and to categorise the organisations as being either focused or
diversified. The second step was to apply hypotheses using financial
performance data to prove if one category of organisations outperformed the
other.
67
5. RESULTS
The results of the research are divided into two sections, the first section reflect
the results of the classification of the organisations into either focused or
diversified organisations, and the second section shows the results of the
performance data obtained from the McGregor’s BFANet database as well as
the results of the hypothesis testing.
5.1 SIC Code classification
The summary of the results of the SIC Code classification per organisation into
the two categories as either focused or diversified is reflected below. The
detailed analysis of each organisation’s classification and three-digit SIC Code
breakdown and revenue per segment can be viewed in Appendix 2 (Focused
Organisations) and Appendix 3 (Diversified Organisations).
5.1.1 Focused Organisations
The classification of the focused organisations is listed in Table 14 below. The
15 focused organisations are listed in alphabetical order against which the
three-digit SIC code for the largest contributing segment to the revenue of the
organisation is listed. The three-digit SIC Code for the year 2005 with the
corresponding SR is listed as well as the three-digit SIC code and
corresponding SR for the year 2001, to ensure that the organisation remained
68
focused at the beginning of the period and the end of the period of study. The
largest contributing segment for the purpose of classifying the organisation into
SIC Codes was obtained from the CIPRO website.
Table 14: Focused Organisations Organisation Name 3 Digit SIC for 2005 SR for
2005 3 Digit SIC for 2001 SR for
2001
Adcorp Holdings Limited 889 - Business
Activities
0.96 889 - Business
Activities
0.94
Asrtapak Limited 338 - Manufacture
of plastic products
1.00 338 - Manufacture
of plastic products
1.00
Bell Equipment Limited 387 - Manufacture
of transport
equipment
1.00 387 - Manufacture
of transport
equipment
1.00
Bowler Metcalf Limited 338 - Manufacture
of plastic products
0.98 338 - Manufacture
of plastic products
1.00
Cargo Carriers Limited 741 - Supporting
and auxiliary
transport activities
0.91 741 - Supporting
and auxiliary
transport activities
0.98
Ceramic Industries
Limited
342 - Manufacture
of non-metallic
mineral products
0.92 342 - Manufacture
of non-metallic
mineral products
1.00
Control Instruments
Group Limited
383 - Manufacture
of parts and
accessories for
motor vehicles and
their engines
1.00 383 - Manufacture
of parts and
accessories for
motor vehicles and
their engines
1.00
Digicore Holdings Limited 633 - Sale of motor
vehicle parts and
0.95 633 - Sale of motor
vehicle parts and
0.99
69
accessories accessories
Distribution and
Warehousing Network
Limited
614 - Wholesale
trade in non-
agricultural
intermediate
products, waste and
scrap
0.90 614 - Wholesale
trade in non-
agricultural
intermediate
products, waste and
scrap
0.95
EnviroServ Holdings
Limited
395 - Recycling 0.93 395 - Recycling 0.97
Iliad Africa Limited 614 - Wholesale
trade in non-
agricultural
intermediate
products, waste and
scrap
1.00 614 - Wholesale
trade in non-
agricultural
intermediate
products, waste and
scrap
1.00
Pretoria Portland Cement
Company Limited
342 - Manufacture
of non-metallic
mineral products
0.94 342 - Manufacture
of non-metallic
mineral products
0.92
Primeserv Group Limited 889 - Business
Activities
0.94 889 - Business
Activities
0.91
Value Group Limited 741 - Supporting
and auxiliary
transport activities
1.00 741 - Supporting
and auxiliary
transport activities
1.00
Venter Leisure and
Commercial Trailers
Limited
382 - Manufacture
of bodies
(Coachwork) for
motor vehicles;
Manufacture of
trailers and semi-
trailers
1.00 382 - Manufacture
of bodies
(Coachwork) for
motor vehicles;
Manufacture of
trailers and semi-
trailers
1.00
70
5.1.2 Diversified Organisations
The classification of the diversified organisations is listed in Table 15 below.
The 15 diversified organisations are listed in alphabetical order against which
the three-digit SIC code for the largest contributing segment to the revenue of
the organisation is listed. The three-digit SIC Code for the year 2005 with the
corresponding SR is listed as well as the three-digit SIC code and
corresponding SR for the year 2001, to ensure that the organisation remained
diversified at the beginning of the period and the end of the period of study.
Table 15: Diversified Organisations Organisation Name 3 Digit SIC for 2005 SR for
2005 3 Digit SIC for 2001 SR for
2001
AG Industries Limited 341 - Manufacture
of glass and glass
products
0.50 341 - Manufacture
of glass and glass
products
0.62
Allied Electronics
Corporation Limited
752 -
Telecommunications
0.38 372 - Manufacture
of television and
radio transmitters
and apparatus for
line telephony and
telegraphy
0.44
Aveng Limited 502 - Building of
complete
constructions or
parts thereof; Civil
Engineering
0.63 502 - Building of
complete
constructions or
parts thereof; Civil
Engineering
0.70
Barloworld Limited 615 - Wholesale
trade in machinery,
equipment and
0.41 615 - Wholesale
trade in machinery,
equipment and
0.48
71
supplies supplies
Bidvest Group Limited 612 - Wholesale
trade in agricultural
raw materials,
livestock, food,
beverages and
tobacco
0.35 612 - Wholesale
trade in agricultural
raw materials,
livestock, food,
beverages and
tobacco
0.41
Delta Electrical Industries
Limited
632 - Maintenance
and repair of motor
vehicles
0.48 632 - Maintenance
and repair of motor
vehicles
0.46
Howden Africa Holdings
Limited
357 - Manufacture
of special purpose
machinery
0.62 357 - Manufacture
of special purpose
machinery
0.70
Hudaco Industries Limited 614 - Wholesale
trade in non-
agricultural
intermediate
products, waste and
scrap
0.59 614 - Wholesale
trade in non-
agricultural
intermediate
products, waste and
scrap
0.54
Imperial Holdings Limited 741 - Supporting
and auxiliary
transport activities
0.28 741 - Supporting
and auxiliary
transport activities
0.35
Jasco Electronics
Holdings Limited
752 -
Telecommunications
0.55 862 - Software
consultancy and
supply
0.64
Murray & Roberts
Holdings Limited
502 - Building of
complete
constructions or
parts thereof; Civil
Engineering
0.40 502 - Building of
complete
constructions or
parts thereof; Civil
Engineering
0.35
Nampak Limited 323 - Manufacture
of paper and paper
0.47 338 - Manufacture
of plastic products
0.39
72
products
Reunert Limited 613 - Wholesale
trade in household
goods
0.41 613 - Wholesale
trade in household
goods
0.44
Super Group Limited 631 - Sale of motor
vehicles
0.41 631 - Sale of motor
vehicles
0.57
Transpaco Limited 338 - Manufacture
of plastic products
0.55 338 - Manufacture
of plastic products
0.66
Out of the total of 58 listed organisations in the industrial sector of the JSE, 15
organisations were categorised as focused and15 organisations as diversified.
The remainder of the organisations were rejected from the samples due to the
following reasons:
• The organisations that did not remain constant as focused or diversified at
the start of the study period compared to the end of the period were not
included in the samples. An example of an organisation is:
o Kairos Industrial Holdings Limited whose SR was 0.51 in 2005 and
0.83 in 2001.
• Organisations whose SR were between 0.9 and 0.7 have not been used in
the data. Examples of the organisations are:
o Argent Industrial Limited whose SR was 0.89 in 2005 and 0.78 in
2001.
o Concor Limited whose SR was 0.81 in 2005 and 0.80 in 2001.
• Organisations which obtained their JSE listings after 2001 were not included
in the samples. The organisations listed after 2001 were:
73
o Amalgamated Electronic Corporation Limited which listed in 2005.
o Consol Limited which listed in 2005.
• Organisations that did not have their primary listing in South Africa were not
included in the samples. The non-primary South African listed organisations
are:
o Bicc Cafca Limited as the primary listing is in Zimbabwe.
o Monteagle Holdings Societe Anonyme as the primary listing is in
Luxembourg.
• Organisations that did not report their segmented revenues sufficiently to be
used in the samples. Examples are Wilson Baily Holmes-Ovcon Limited and
KAP International Holdings Limited who did not clearly report or document
operational reviews to be able to link the revenues with a particular three-
digit SIC code.
5.2 Performance measure results
The results section of the performance data is divided into three sections. The
first section presents the results of the data that was obtained from the
McGregor’s BFANet database, the second section presents the descriptive
statistics of the performance measures and the third section presents the
results of the hypothesis testing.
74
5.2.1 Performance data
The performance data obtained from McGregor’s BFANet database are
presented below per performance measurement from 2001 to 2005.
5.2.1.1 Return on Equity
The ROE % for each category of focused and diversified organisation per year
from 2001 to 2005 can be viewed in Table 16 below.
Table 16: ROE % of the focused and diversified organisations Industrial Sector Companies
Focused OrganisationsJSE Sharecode 2001 2002 2003 2004 2005
Adcorp Holdings Limited ADR 18.51 -16.6 -4.53 25.02 26.1Astrapak Limited APK 32.43 31.44 30.02 32.10 25.06Bell Equipment Limited BEL 14.89 17.50 5.15 -1.63 -1.17Bowler Metcalf Limited BCF 27.67 28.10 29.63 36.87 25.89Cargo Carriers Limited CRG -2.46 7.16 3.91 12.10 11.72Ceramic Industries Limited CRM 28.20 26.74 24.69 21.63 22.41Control Instruments Group Limited CNL -13.06 10.07 22.22 21.75 13.53Digicor Holdings Limited DGC 24.96 12.60 14.03 20.02 26.87Distribution and Warehousing Network Limited DAW 18.69 15.88 32.71 36.56 43.55EnviroServ Holdings Limited ENV 2.90 24.24 23.48 21.63 19.34Iliad Africa Limited ILA 26.60 32.62 17.23 27.29 27.23Pretoria Portland Cement PPC 21.31 25.98 29.34 33.60 47.04Primeserv Group Limited PMV 5.35 7.21 -50.72 -23.32 7.83Value Group Limited VLE 16.59 7.59 19.3 19.75 19.43Venter Leisure and Commercial Trailers Limited VTL -306.44 -227.35 14.19 7.96 15.91
Diversified OrganisationsJSE Sharecode 2001 2002 2003 2004 2005
AG Industries Limited AGI 20.64 18.47 6.97 11.08 4.38Allied Electronics Corporation Limited ATN 20.22 15.84 20.93 13.82 13.28Aveng Limited AEG 14.55 14.19 20.80 7.67 14.10Barloworld Limited BAW 5.40 13.42 11.92 13.60 15.41Bidvest Group Limited BVT 25.87 22.03 24.81 25.44 28.09Delta Electrical Industries Limited DEL 31.47 27.99 19.60 11.67 64.15Howden Africa Holdings Limited HWN -7.75 5.48 16.94 21.83 15.61Hudaco Industries Limited HDC 18.28 16.53 17.81 17.36 20.85Imperial Holdings Limited IPL 17.23 16.34 18.01 18.77 26.03Jasco Electronic Holdings Limited JSC -561.22 37.76 52.21 1.47 7.03Murray & Roberts Holdings Limited MUR 12.73 19.08 22.06 18.57 15.10Nampak Limited NPK 14.74 13.71 20.09 17.91 14.92Reunert Limited RLO 44.05 34.62 25.56 51.29 48.82Super Group Limited SPG 41.99 16.49 24.95 28.29 21.26Transpaco Limited TPC -1.07 15.37 19.22 20.67 17.59
ROE %
ROE %
Source: McGregor BFANet
75
5.2.1.2 Return on Assets
The ROA % for each category of focused and diversified organisation per year
from 2001 to 2005 can be viewed in Table 17 below.
Table 17: ROA % of the focused and diversified organisations Industrial Sector Companies
Focused OrganisationsJSE Sharecode 2001 2002 2003 2004 2005
Adcorp Holdings Limited ADR 33.92 1.33 13.24 24.97 24.94Astrapak Limited APK 16.78 18.35 17.52 20.54 19.17Bell Equipment Limited BEL 17.88 25.15 25.97 9.51 9.69Bowler Metcalf Limited BCF 29.41 33.18 30.94 35.85 26.43Cargo Carriers Limited CRG 4.18 10.04 6.63 11.71 11.43Ceramic Industries Limited CRM 25.47 24.74 22.93 22.90 24.39Control Instruments Group Limited CNL 0.57 10.40 13.15 19.59 13.25Digicor Holdings Limited DGC 38.58 20.79 23.33 25.74 33.78Distribution and Warehousing Network Limited DAW 13.14 11.79 18.08 21.29 23.28EnviroServ Holdings Limited ENV 8.48 12.44 13.79 13.34 12.05Iliad Africa Limited ILA 17.11 21.52 15.44 22.89 24.06Pretoria Portland Cement PPC 20.44 27.27 29.02 36.13 49.16Primeserv Group Limited PMV 10.42 8.98 12.01 -9.34 6.57Value Group Limited VLE 11.19 8.3 18.06 16.87 14.67Venter Leisure and Commercial Trailers Limited VTL -42.07 -6.84 8.60 3.93 6.27
Diversified OrganisationsJSE Sharecode 2001 2002 2003 2004 2005
AG Industries Limited AGI 26.68 22.82 16.66 18.75 18.47Allied Electronics Corporation Limited ATN 13.20 11.92 22.79 16.20 20.25Aveng Limited AEG 11.87 11.10 14.51 7.35 8.57Barloworld Limited BAW 7.32 11.25 11.68 13.04 14.29Bidvest Group Limited BVT 17.09 14.82 17.05 16.54 17.71Delta Electrical Industries Limited DEL 28.76 29.88 20.08 11.79 64.97Howden Africa Holdings Limited HWN 12.30 21.02 32.66 23.26 18.01Hudaco Industries Limited HDC 15.77 20.72 22.75 18.92 21.45Imperial Holdings Limited IPL 14.89 13.00 14.06 13.46 15.00Jasco Electronic Holdings Limited JSC -46.19 18.74 29.27 13.23 23.15Murray & Roberts Holdings Limited MUR 6.63 10.21 11.96 9.51 9.62Nampak Limited NPK 10.24 10.80 18.67 17.87 15.83Reunert Limited RLO 21.04 21.86 20.01 32.65 28.43Super Group Limited SPG 25.11 13.17 15.92 18.35 15.54Transpaco Limited TPC 3.58 15.01 19.44 17.59 12.07
ROA %
ROA %
Source: McGregor BFANet
5.2.1.3 Market Return
The calculated Market Return % for each category of focused and diversified
organisation per year from 2001 to 2005 can be viewed in Table 18 below.
76
Table 18: Market Return % of the focused and diversified organisations Industrial Sector Companies
Focused OrganisationsJSE Sharecode 2001 2002 2003 2004 2005
Adcorp Holdings Limited ADR -27.86 -30.80 94.75 54.79 40.08Astrapak Limited APK -12.31 37.67 72.80 84.99 48.91Bell Equipment Limited BEL 33.24 8.48 -24.87 -18.64 64.44Bowler Metcalf Limited BCF 75.90 30.20 23.19 44.24 42.82Cargo Carriers Limited CRG -28.63 30.46 148.56 33.79 46.15Ceramic Industries Limited CRM 48.84 40.78 -10.32 7.85 61.33Control Instruments Group Limited CNL -26.60 44.93 53.57 94.93 84.15Digicor Holdings Limited DGC 63.64 -22.22 0.00 184.62 125.76Distribution and Warehousing Network Limited DAW 0.00 -24.00 134.21 146.07 167.58EnviroServ Holdings Limited ENV 108.06 12.40 80.16 47.44 22.37Iliad Africa Limited ILA 100.00 142.02 94.57 95.95 14.63Pretoria Portland Cement PPC 45.09 37.30 70.49 69.72 66.35Primeserv Group Limited PMV 18.18 30.77 -45.59 38.89 -16.00Value Group Limited VLE -53.66 -44.74 114.29 206.67 58.21Venter Leisure and Commercial Trailers Limited VTL -61.54 280.00 -36.84 350.00 -55.56
Diversified OrganisationsJSE Sharecode 2001 2002 2003 2004 2005
AG Industries Limited AGI 32.97 5.13 -30.81 1.45 59.27Allied Electronics Corporation Limited ATN 9.30 3.33 13.65 40.91 55.23Aveng Limited AEG 29.93 12.70 11.89 -12.34 62.11Barloworld Limited BAW 20.19 20.77 4.72 37.50 49.84Bidvest Group Limited BVT 7.75 8.15 -10.18 30.97 42.18Delta Electrical Industries Limited DEL 39.36 6.26 -25.50 -8.35 17.61Howden Africa Holdings Limited HWN -11.39 17.14 75.61 87.23 135.58Hudaco Industries Limited HDC 59.68 57.36 38.40 53.68 29.72Imperial Holdings Limited IPL 21.03 -13.30 3.48 33.95 52.90Jasco Electronic Holdings Limited JSC -81.28 85.71 152.31 -45.10 167.86Murray & Roberts Holdings Limited MUR 87.93 56.51 31.31 20.02 8.32Nampak Limited NPK -13.02 30.14 -2.53 18.69 17.69Reunert Limited RLO 46.66 24.03 -3.90 69.99 61.28Super Group Limited SPG -4.80 -21.84 4.45 95.89 4.89Transpaco Limited TPC -19.51 -28.28 246.48 69.26 54.96
Market Return %
Market Return %
Source: McGregor BFANet
5.2.1.4 Earnings per share
The calculated EPS growth rate for each category of focused and diversified
organisation per year from 2001 to 2005 can be viewed in Table 19 below. As
mentioned in section 4.5.2.4 the McGregor’s BFANet database uses Headline
Earnings per share in their database.
77
Table 19: EPS growth rate of the focused and diversified organisations Industrial Sector Companies
Focused OrganisationsJSE Sharecode 2000 2001 2002 2003 2004 2005 2001 2002 2003 2004 2005
Adcorp Holdings Limited ADR 192 156 110 96.4 164.5 195.1 -18.75 -29.49 -12.36 70.64 18.60Astrapak Limited APK 44.8 47.1 59 73.8 93 119.3 5.13 25.27 25.08 26.02 28.28Bell Equipment Limited BEL 87 105 133 39 -13 -11 20.69 26.67 -70.68 -133.33 -15.38Bowler Metcalf Limited BCF 18.3 25.6 33 35.5 59.2 50.6 39.89 28.91 7.58 66.76 -14.53Cargo Carriers Limited CRG 18.3 9.7 40.6 14.7 41.4 64.2 -46.99 318.56 -63.79 181.63 55.07Ceramic Industries Limited CRM 329.8 479 621.9 706.5 754 964.5 45.24 29.83 13.60 6.72 27.92Control Instruments Group Limited CNL 6.8 -6.7 13.6 28.6 29.1 28.3 -198.53 302.99 110.29 1.75 -2.75Digicor Holdings Limited DGC 0.5 10.8 7.2 7.5 12.2 21.1 2060.00 -33.33 4.17 62.67 72.95Distribution and Warehousing Network Limited DAW 14.7 11.8 6.8 17.1 30.5 52.1 -19.73 -42.37 151.47 78.36 70.82EnviroServ Holdings Limited ENV 22.1 26.2 30.6 35.7 40.7 51.1 18.55 16.79 16.67 14.01 25.55Iliad Africa Limited ILA 29.9 32.3 62 76.4 97.4 110.6 8.03 91.95 23.23 27.49 13.55Pretoria Portland Cement PPC 500.2 709.7 829.5 1154 1463.2 1729.5 41.88 16.88 39.12 26.79 18.20Primeserv Group Limited PMV 23.9 8.8 16.7 3 -7.3 0.3 -63.18 89.77 -82.04 -343.33 104.11Value Group Limited VLE 12.6 10.7 3.9 14.2 19.2 23.3 -15.08 -63.55 264.10 35.21 21.35Venter Leisure and Commercial Trailers Limited VTL 0.3 -22.2 -3.3 0.5 1.2 2.5 -7500.00 -85.14 -115.15 140.00 108.33
Diversified OrganisationsJSE Sharecode 2000 2001 2002 2003 2004 2005 2001 2002 2003 2004 2005
AG Industries Limited AGI 22.2 29.2 33.3 15.5 22.5 19 31.53 14.04 -53.45 45.16 -15.56Allied Electronics Corporation Limited ATN 85.6 101.5 129.5 149.4 139 161.2 18.57 27.59 15.37 -6.96 15.97Aveng Limited AEG 79.3 99.4 111.2 118.6 56.5 93.5 25.35 11.87 6.65 -52.36 65.49Barloworld Limited BAW 380.4 499 621.7 592.8 857.2 893.6 31.18 24.59 -4.65 44.60 4.25Bidvest Group Limited BVT 310 365.4 436.2 479 546.7 686.6 17.87 19.38 9.81 14.13 25.59Delta Electrical Industries Limited DEL 326.2 448 487.5 369.5 220.8 199.4 37.34 8.82 -24.21 -40.24 -9.69Howden Africa Holdings Limited HWN 7.6 -2.1 7.9 29.5 38.3 40.5 -127.63 476.19 273.42 29.83 5.74Hudaco Industries Limited HDC 171.1 224.1 315.7 365 370.6 415 30.98 40.87 15.62 1.53 11.98Imperial Holdings Limited IPL 444 535 608.8 700.2 840.5 1045.8 20.50 13.79 15.01 20.04 24.43Jasco Electronic Holdings Limited JSC 21 -43.2 27.6 58 33.6 16.3 -305.71 163.89 110.14 -42.07 -51.49Murray & Roberts Holdings Limited MUR 36 76 154 175 152 142 111.11 102.63 13.64 -13.14 -6.58Nampak Limited NPK 123.1 88.1 138.6 145.4 146.1 119.2 -28.43 57.32 4.91 0.48 -18.41Reunert Limited RLO 140.7 176 229.5 183.5 277.5 406 25.09 30.40 -20.04 51.23 46.31Super Group Limited SPG 85 94 68.6 101.6 123.8 129.5 10.59 -27.02 48.10 21.85 4.60Transpaco Limited TPC 50 -2.4 37.5 60.5 71.8 80.2 -104.80 1662.50 61.33 18.68 11.70
Earnings per share in cents Earnings per share growth rate %
Earnings per share in cents Earnings per share growth rate %
Source: McGregor BFANet
The above data were used to test each of the four hypotheses which will be
discussed in the section below.
5.2.2 Descriptive statistics of the performance measures
The descriptive statistics relating to the performance measures are summarised
in Table 20 below. Two sets of tests are presented. The first set, (Hypothesis
Test 1) includes the tests whereby all the observations per category of focused
or diversified organisations were tested, and the second set of results
(Hypothesis Test 2) excludes the large outliers.
78
The existence of large outliers in the 75 observations per category resulted in
the need to perform an additional test per hypothesis. The aim of the research
is to present and test all the observations in the samples (75 observations) as
the observations were actual financial data that was recorded by the
organisations. The additional test without the large outliers is done to examine
the impact on the results if they are removed.
Table 20: Descriptive statistics of performance measures Hypothesis Test 1Statistical Element Focused Diversified Focused Diversified Focused Diversified Focused DiversifiedSample Size (n) 75 75 75 75 75 75 75 75Mean 10.0272 12.1652 17.0228 16.7198 51.16133 30.81573 -50.99147 41.32187Median 19.75 17.91 17.5 16.2 44.24 20.77 20.69 15.37Range 353.48 625.37 91.23 111.16 411.54 327.76 9560 1968.21Minimum -306.44 -561.22 -42.07 -46.19 -61.54 -81.28 -7500 -305.71Maximum 47.04 64.15 49.16 64.97 350 246.48 2060 1662.5Skewness -8.666 -10.2218 -3.9492 -3.9965 4.204 4.5786 -9.8803 9.4935Kurtosis 6.4757 7.3684 4.2474 5.8015 3.3376 3.9081 7.2745 7.0761Standard deviation 48.99234 68.14739 12.38106 11.03575 73.29012 48.7843 907.6891 207.1199
Hypothesis Test 2Statistical Element Focused Diversified Focused Diversified Focused Diversified Focused DiversifiedSample Size (n) 72 72 73 73 71 71 72 71Mean 18.56319 18.85069 17.39206 16.92068 39.65929 22.66127 27.20792 19.63085Median 20.66 17.86 17.5 16.2 40.78 20.02 21.02 15.37Range 70.36 59.04 47.92 29.08 229.12 177.17 517.09 378.22Minimum -23.32 -7.75 -9.34 3.58 -61.54 -81.28 -198.53 -104.8Maximum 47.04 51.29 38.58 32.66 167.58 95.89 318.56 273.42Skewness -2.7331 2.7073 -0.5334 1.9632 0.6604 -0.4409 3.3325 5.3325Kurtosis 1.7737 2.6148 0.446 0.5933 -0.7784 0.7048 3.3096 4.8372Standard deviation 13.09912 10.18581 9.724535 16.92068 54.65929 33.88287 83.8177 49.96984
AROE AROA AMKTRET AEPSGR
AROE AROA AMKTRET AEPSGR
5.2.3 Hypothesis test results
The results of the four hypothesis tests are presented below in tabular form.
The results include the one-tailed t-test with the ρ-value approach as well as
non-parametric tests that include the following:
• Aspin-Welch unequal-variance test
• Mann-Whitney U test for difference in medians
79
The first section of the results in the tables indicates the results of the test
conducted on all the observations (75 observations), and the second section of
the results are the results where the large outliers have been removed to
examine what the impact of the results would be if the outliers were removed.
5.2.3.1 Hypothesis 1: AROE
The alternative hypothesis (H1):
The AROE of diversified organisations is greater than the AROE of the focused
organisations.
The null hypothesis (H0):
The AROE of diversified organisations is less or equal to the AROE of the
focused organisations.
H0: µAROEDiv≤ µAROEFocus
H1: µAROEDiv> µAROEFocus
Where µx = mean
As indicated in Table 21 below, the probability level (ρ) = 0.412851 ≥ 0.05
therefore it fails to reject the H0. It is important to note that this does not imply
the acceptance of the null hypothesis, rather that the alternative hypothesis is
not significant at the 5% alpha level and that the difference in the AROE
between the diversified organisations and the focused organisations is due to
sampling error.
80
The second test conducted without the large outliers (72 observations) indicates
a probability level (ρ) = 0.441663 which also results in a failure to reject the H0.
The result of the hypothesis thus concludes that although the AROE of the
diversified organisations (12.1652%) is greater than the AROE of the focused
organisations (10.0272%), the difference is not statistically significant.
Table 21: AROE Tests One-tailed test with ρ-valueVariable n Mean (µ) Std. Deviation Std. Error Prob. Level (ρ) Alpha (α) ResultFocused Organisation 75 10.0272 48.99234 5.657148 0.412851 0.05 Accept H 0Diversified Organisation 75 12.1652 68.14739 7.868983Aspin-Welch unequal-variance testVariable n Mean (µ) Prob. Level (ρ) Alpha (α) ResultFocused Organisation 75 10.0272 0.412867 0.05 Accept H 0Diversified Organisation 75 12.1652Mann-Whitney U test for difference in mediansVariable n Median Prob. Level (ρ) Alpha (α) ResultFocused Organisation 75 19.75 0.338946 0.05 Accept H 0Diversified Organisation 75 17.91
One-tailed test with ρ-valueVariable n Mean (µ) Std. Deviation Std. Error Prob. Level (ρ) Alpha (α) ResultFocused Organisation 72 18.56319 13.09912 1.543746 0.441663 0.05 Accept H 0Diversified Organisation 72 18.85069 10.18581 1.200409Aspin-Welch unequal-variance testVariable n Mean (µ) Prob. Level (ρ) Alpha (α) ResultFocused Organisation 72 18.56319 0.441669 0.05 Accept H 0Diversified Organisation 72 18.85069Mann-Whitney U test for difference in mediansVariable n Median Prob. Level (ρ) Alpha (α) ResultFocused Organisation 72 20.66 0.153187 0.05 Accept H 0Diversified Organisation 72 17.86
81
5.2.3.2 Hypothesis 2: AROA
The alternative hypothesis (H1):
The AROA of diversified organisations is greater than the AROA of the focused
organisations.
The null hypothesis (H0):
The AROA of diversified organisations is less or equal to the AROA of the
focused organisations.
H0: µAROADiv≤ µAROAFocus
H1: µAROADiv> µAROAFocus
Where µx = mean
As indicated in Table 22 below, the probability level (ρ) = 0.437266 ≥ 0.05
therefore it fails to reject the H0. It is important to note that this does not imply
the acceptance of the null hypothesis, rather that the alternative hypothesis is
not significant at the 5% alpha level and that the difference in the AROA
between the diversified organisations and the focused organisations is due to
sampling error.
The second test conducted without the large outliers (73 observations) indicates
a probability level (ρ) = 0.363419 which also results in a failure to reject the H0.
The result of the hypothesis thus concludes that the AROA of the diversified
organisations (16.7198%) is less than the AROA of the focused organisations
(17.0228%), and the difference is not statistically significant.
82
Table 22: AROA Tests One-tailed test with ρ-valueVariable n Mean (µ) Std. Deviation Std. Error Prob. Level (ρ) Alpha (α) ResultFocused Organisation 75 17.0228 12.38106 1.429641 0.437266 0.05 Accept H 0Diversified Organisation 75 16.7198 11.03575 1.274299Aspin-Welch unequal-variance testVariable n Mean (µ) Prob. Level (ρ) Alpha (α) ResultFocused Organisation 75 17.0228 0.437267 0.05 Accept H 0Diversified Organisation 75 16.7198Mann-Whitney U test for difference in mediansVariable n Median Prob. Level (ρ) Alpha (α) ResultFocused Organisation 75 17.5 0.336199 0.05 Accept H 0Diversified Organisation 75 16.2
One-tailed test with ρ-valueVariable n Mean (µ) Std. Deviation Std. Error Prob. Level (ρ) Alpha (α) ResultFocused Organisation 73 17.39206 9.724535 1.138171 0.363419 0.05 Accept H 0Diversified Organisation 73 16.92068 6.150461 0.719857Aspin-Welch unequal-variance testVariable n Mean (µ) Prob. Level (ρ) Alpha (α) ResultFocused Organisation 73 17.39206 0.363466 0.05 Accept H 0Diversified Organisation 73 16.92068Mann-Whitney U test for difference in mediansVariable n Median Prob. Level (ρ) Alpha (α) ResultFocused Organisation 73 17.5 0.329855 0.05 Accept H 0Diversified Organisation 73 16.2
5.2.3.3 Hypothesis 3: AMKTRET
The alternative hypothesis (H1):
The AMKTRET of diversified organisations is greater than the AMKTRET of the
focused organisations.
The null hypothesis (H0):
The AMKTRET of diversified organisations is less or equal to the AMKTRET of
the focused organisations.
H0: µAMKTRETDiv≤ µAMKTRETFocus
H1: µAMKTRETDiv> µAMKTRETFocus
Where µx = mean
83
Table 23: AMKTRET Tests One-tailed test with ρ-valueVariable n Mean (µ) Std. Deviation Std. Error Prob. Level (ρ) Alpha (α) ResultFocused Organisation 75 51.16133 73.2901 8.462815 0.023594 0.05 Reject H 0Diversified Organisation 75 30.81573 48.7843 5.633126Aspin-Welch unequal-variance testVariable n Mean (µ) Prob. Level (ρ) Alpha (α) ResultFocused Organisation 75 51.16133 0.023731 0.05 Reject H 0Diversified Organisation 75 30.81573Mann-Whitney U test for difference in mediansVariable n Median Prob. Level (ρ) Alpha (α) ResultFocused Organisation 75 44.24 0.026797 0.05 Reject H 0Diversified Organisation 75 20.77
One-tailed test with ρ-valueVariable n Mean (µ) Std. Deviation Std. Error Prob. Level (ρ) Alpha (α) ResultFocused Organisation 71 39.65929 54.0407 6.413452 0.013151 0.05 Reject H 0Diversified Organisation 71 22.66127 33.8829 4.021156Aspin-Welch unequal-variance testVariable n Mean (µ) Prob. Level (ρ) Alpha (α) ResultFocused Organisation 71 39.65929 0.013302 0.05 Reject H 0Diversified Organisation 71 22.66127Mann-Whitney U test for difference in mediansVariable n Median Prob. Level (ρ) Alpha (α) ResultFocused Organisation 71 40.78 0.020171 0.05 Reject H 0Diversified Organisation 71 20.02
As indicated in Table 23 above, the probability level (ρ) = 0.023594 ≥ 0.05
therefore it fails to reject the H0, as the AMKTRET of the focused organisations
is greater than the diversified organisations. As the alternative hypothesis (H1)
stated that the AMKTRET of diversified organisations is greater than the
AMKTRET of the focused organisations, the AMKTRET of diversified
organisations is in fact less than the AMKTRET of the focused organisations.
The second test conducted without the large outliers (71 observations) indicates
a probability level (ρ) = 0.013151 which also results in a failure to reject the H0.
The result of the hypothesis thus concludes that the AMKTRET of the focused
organisations (51.16133%) is greater than the AMKTRET of the diversified
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organisations (30.81573%), the difference being statistically significant, and the
opposite outcome of what was expected.
5.2.3.4 Hypothesis 4: AEPSGR
The alternative hypothesis (H1):
The AEPSGR of diversified organisations is greater than the AEPSGR of the
focused organisations.
The null hypothesis (H0):
The AEPSGR of diversified organisations is less or equal to the AEPSGR of the
focused organisations.
H0: µAEPSGRDiv≤ µAEPSGRFocus
H1: µAEPSGRDiv> µAEPSGRFocus
Where µx = mean
As indicated in Table 24 below, the probability level (ρ) = 0.19595 ≥ 0.05
therefore it fails to reject the H0. It is important to note that this does not imply
the acceptance of the null hypothesis, rather that the alternative hypothesis is
not significant at the 5% alpha level and that the difference in the AEPSGR
between the diversified organisations and the focused organisations is due to
sampling error.
The second test conducted without the large outliers (72 observations in the
focused category and 71 observations in the diversified category) indicates a
probability level (ρ) = 0.256623 which also results in a failure to reject the H0.
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The result of the hypothesis thus concludes that the AEPSGR of the diversified
organisations (41.3218%) is greater than the AEPSGR of the focused
organisations (-50.9915%), and the difference is not statistically significant.
Table 24: AEPSGR Tests One-tailed test with ρ-valueVariable n Mean (µ) Std. Deviation Std. Error Prob. Level (ρ) Alpha (α) ResultFocused Organisation 75 -50.99147 907.6891 104.8109 0.19595 0.05 Accept H 0Diversified Organisation 75 41.3218 207.1199 23.91614Aspin-Welch unequal-variance testVariable n Mean (µ) Prob. Level (ρ) Alpha (α) ResultFocused Organisation 75 -50.99147 0.196512 0.05 Accept H 0Diversified Organisation 75 41.3218Mann-Whitney U test for difference in mediansVariable n Median Prob. Level (ρ) Alpha (α) ResultFocused Organisation 75 20.69 0.281347 0.05 Accept H 0Diversified Organisation 75 15.37
One-tailed test with ρ-valueVariable n Mean (µ) Std. Deviation Std. Error Prob. Level (ρ) Alpha (α) ResultFocused Organisation 72 27.20792 83.8177 9.878012 0.256623 0.05 Accept H 0Diversified Organisation 71 19.63085 49.96984 5.930329Aspin-Welch unequal-variance testVariable n Mean (µ) Prob. Level (ρ) Alpha (α) ResultFocused Organisation 72 27.20792 0.256033 0.05 Accept H 0Diversified Organisation 71 19.63085Mann-Whitney U test for difference in mediansVariable n Median Prob. Level (ρ) Alpha (α) ResultFocused Organisation 72 21.02 0.217325 0.05 Accept H 0Diversified Organisation 71 15.37
The results of the performance measures indicate that large outliers exist in the
test of the hypotheses. The hypotheses are tested inclusive of all the
observations and a second test without the large outliers. Although the tests
without the outliers indicate differences in the descriptive statistics, the overall
results remain the same. The aim of the research is to test the hypotheses
inclusive of all observations as the data are real financial data that are
observed.
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The overall results thus indicate that three of the hypotheses are not statistically
significant and that the differences in the average (mean) performance
measures of AROE, AROA and AEPSGR are due to sampling error. The
hypothesis of AMKTRET indicates however that the difference in the average
(mean) performance is statistically significant and that the AMKTRET of the
focused organisations is greater than the performance of the diversified
organisations and is the opposite of what the hypothesis intended to prove.
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6. DISCUSSION OF RESULTS
The discussion of results chapter is divided into two sections. The first section
presents the manual SIC code and SR classification of organisations as either
focused or diversified, and the second section discusses the performance data
per hypothesis.
6.1 Classification of diversification
The SIC code classification and SR categorisation per organisation for the year
2001 and 2005 are presented in Table 14 for the focused organisations and
Table 15 for the diversified organisations. Table 14 and 15 present the high
level breakdown of the organisations per category, the three-digit SIC code as
well as the SR for the particular largest SIC code contributor. Appendix 2 and 3
detail the complete analysis of each of the organisations that are part of the
focused or diversified categories.
The research regarding the classification of the organisations represents the
two possible approaches used to ensure a thorough classification. The SIC
code and SR approach are found to be the best, as Montgomery (1982)
concludes that both approaches have strengths and weaknesses and that both
approaches, although manual in nature in this research, were also conducted
by Rumelt (1986), Markides (1995) and Harper and Viguerie (2002).
88
It is evident from the Tables 14 and 15 that the resultant three-digit SIC code is
a categorisation at a high level, although Montgomery (1982) states that the
three-digit level of activity for the SIC code analysis is acceptable.
6.2 Performance measures
The key question in the research is to determine if diversified organisations
have superior financial performance over organisations that follow a focused
strategy. As South African organisations are integrated in the world economy
and divest more of their non-core businesses (Bhana, 2004) to focus on core
industries, it is necessary to determine if organisations that choose to diversify
or not outperform the other. It is also interesting to determine if the
organisations have a special capability due to regulation and the sanctions that
were placed on South African organisations, which compelled South African
organisations to invest and diversify by acquiring local companies, leading to
the formation of large diversified conglomerates (Rossouw, 1997).
This research report does not find that there are significant differences in
performance between the two groups in three out of the four hypotheses. The
one statistically significant result shows that the AMKTRET of focused
organisations is superior to the AMKTRET of diversified organisations.
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6.2.1 Hypothesis 1: AROE
The annual ROE% results of each organisation per category as being either
focused or diversified from the period 2001 to 2005 is presented in Table 16.
The results of the hypothesis test are presented in Table 21.
The null hypothesis fails to reject in both instances where the full sample of 75
organisations are tested, as well as where the outliers are removed from the
test. Although the AROE of the diversified organisations (12.1652%) is greater
than the AROE of the focused organisations (10.0272%) it is not statistically
significant and it cannot be proved statistically that diversified organisations
have a superior AROE than focused organisations. The test without the outliers
yields the same overall result, although the AROE of each category is narrower
and the standard deviation is also less for the second test.
The outliers excluded during the second test for the focused category are:
• -306.44% for Venter Leisure and Commercial Trailers Limited during 2001
and -227.35% during 2002
• -50.72% for Primeserv Group Limited during 2003
The outliers excluded during the second test for the diversified category are:
• 64.15% for Delta Electrical Industries Limited during 2005
• 52.21% for Jasco Electronics Holdings Limited during 2003 and -561.22%
during 2001
The results show that the focused organisations category has larger variance as
shown in the larger standard deviation. This could be an indication that the
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focused organisations are more volatile in terms of the return to shareholders as
focused organisations will tend to be more prone to economic cycles and more
sensitive to the parts of the economy that affect the focused organisations core
businesses.
The larger variance and standard deviation is also an indication of the portfolio
theory of finance whereby diversification leads to a smaller beta coefficient than
investments that are not diversified. The more diverse a portfolio of investments
are, the more likely the return of the investment will be to the return of the
overall market.
Rumelt’s (1986) study shows that the AROE amongst two of the four major
categories are statistically significant at the 5% alpha level during his research
of organisations from 1951 to 1970. The AROE of the four major categories are
indicated below:
• Single Business AROE: 13.20%
• Dominant Business AROE: 11.64%
• Related Business AROE: 13.55%
• Unrelated Business AROE: 11.92%
The dominant business category (AROE 11.64%) is statistically significant lower
than the mean, and the related business category (AROE 13.55%) is
statistically greater than the mean at the 5% alpha level. If the AROE of the
single business (AROE: 13.20%) and the related business (AROE: 13.55%) is
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compared, the differences are low, which in effect is the same measure and
result as this study, whereby the diversified AROE (12.1652%) is greater than
the focused AROE (10.0272%).
In comparing this study with the Panday and Rao (1998) study in the USA of the
organisations between 1984 and 1990, the AROE of the diversified
organisations (14.6%) was greater than the focused organisations (-1.6%),
which is the same finding as this study. However, the Panday and Rao (1998)
findings were proven as statistically significant at the 1% alpha level and that
the AROE of diversified organisations is superior to the AROE of the focused
organisations.
Another comparison of this study is the study of Hall and Lee (1999). The
difference in ROE is measured between USA and Korean organisations using
multiple regression techniques. The ROE of the USA diversified organisations
performed weaker than the ROE of the focused organisations, and is found to
be statistically significant at the 1% alpha level. Whereas the Korean
organisations show the same result as this study, that the ROE of diversified
organisations perform better than focused organisations, although it is not found
to be statistically significant. Similarly, Singh et al. (2001) study in the USA
reveals on an annual basis in 1994, 1995 and 1996 that the ROE of diversified
organisations is greater than the focused organisations. In two of the years,
1995 and 1996 the difference in ROE is statistically significant at the 5% alpha
level, whereas for 1994 it is not.
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6.2.2 Hypothesis 2: AROA
The annual ROA% results of each organisation per category as being either
focused or diversified from the period 2001 to 2005 is presented in Table 17.
The results of the hypothesis test are presented in Table 22.
The null hypothesis fails to reject in both instances where the full sample of 75
organisations are tested as well as the test where the outliers are removed from
the test. Although the AROA of the focused organisations (17.7198%) is greater
than the AROA of the diversified organisations (16.7198%) it is not statistically
significant and it cannot be proved statistically that focused organisations have
a superior AROA than diversified organisations. The results show that the
focused organisations AROA is marginally greater than the diversified
organisations, which is surprising, as it is expected for the AROA to yield similar
results to the test in Hypothesis 1. The test without the outliers yields the same
overall result, although the standard deviation is less for the second test.
The outliers excluded during the second test for the focused category are:
• -42.07% for Venter Leisure and Commercial Trailers Limited during 2001
• 49.16% for Pretoria Portland Cement Company Limited during 2005
The outliers excluded during the second test for the diversified category are:
• 64.97% for Delta Electrical Industries Limited during 2005
• -46.19% for Jasco Electronics Holdings Limited during 2001
The results show that the focused organisations category variance as shown in
the standard deviation is similar. This could be an indication that both
93
categories of organisations’ total asset base are similar, and further
investigation can be done to determine the compilation of the asset base in
terms of net assets and intangible assets to gain a better understanding.
In comparing this study with the Panday and Rao (1998) study in the USA of the
organisations between 1984 and 1990, the AROA of the diversified
organisations (5.8%) was greater than the focused organisations (-1.9%), which
is the inverse finding of this study, however Panday and Rao (1998) findings
were proven as statistically significant at the 5% alpha level and that the AROA
of diversified organisations was superior to the AROA of the focused
organisations.
The study of Hall and Lee (1999) shows the difference in ROA as measured
between USA and Korean organisations. Similar to this study, the ROA of the
USA diversified organisations performed weaker than the ROA of the focused
organisations, and is found to be statistically significant, whereas the Korean
organisations show that ROA for diversified organisations perform better than
focused organisations, and is found to be statistically significant. Similar to this
research, the Singh et al. (2001) study reveals on an annual basis in 1994,
1995 and 1996 that the ROA of diversified organisations perform weaker than
the focused organisations. In two of the years, 1995 and 1996 the difference in
ROA is found not to be statistically significant, whereas for 1994 it is.
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6.2.3 Hypothesis 3: AMKTRET
The AMKTRET% results of each organisation per category as being either
focused or diversified from the period 2001 to 2005 is presented in Table 18.
The results of the hypothesis test are presented in Table 23.
The null hypothesis fails to reject in both instances where the full sample of 75
organisations are tested as well as the test where the outliers are removed from
the test. The AMKTRET of the focused organisations (51.16133%) is greater
than the AMKTRET of the diversified organisations (30.81573%), it is
statistically significant at the 5% alpha level and it can be proved statistically
that focused organisations have a superior AMKTRET than diversified
organisations. The results show the opposite of what is expected. The
hypothesis assumes that the diversified organisations will have superior
performance, but in fact the focused organisations outperformed the diversified
organisations by a large margin. The test without the outliers yields the same
overall result, although the standard deviation is less for the second test.
The outliers excluded during the second test for the focused category are:
• 280% for Venter Leisure and Commercial Trailers Limited during 2002 and
350% during 2003
• 184.62% for Digicor Holdings Limited during 2004
• 206.67% for Value Group Limited during 2004
The outliers excluded during the second test for the diversified category are:
• 246.48% for Transpaco Limited during 2003
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• 152.31% for Jasco Electronics Holdings Limited during 2003 and 167.86%
during 2005
• 135.58% for Howden Africa Holdings Limited during 2005
The results show that the focused organisations category has a larger variance
as shown in the larger standard deviation. This could be an indication that the
focused organisations are more volatile in terms of share price and dividends
paid during the year. The higher market returns could also be an indication of
the higher returns that are demanded from shareholders as the risk of focused
strategies might be higher. The volatile share price of the focused organisations
would be more prone to the liquidity and tradability of the securities, the
economic cycles and more sensitive to the parts of the economy that affect the
focused organisations core businesses.
In comparing this study with the Panday and Rao (1998) study in the USA of the
organisations between 1984 and 1990, the AMKTRET of the diversified
organisations (16.3%) is greater than the focused organisations (8.2%), which is
the inverse finding of this study, and similarly the Panday and Rao (1998) study
is proven as statistically significant and that the AROA of diversified
organisations is superior to the AROA of the focused organisations.
The study of Hall and Lee (1999) measures the difference in market-based
measures MVE between USA and Korean organisations. Although different to
AMKTRET which is also a market-based measure, the study found that the
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MVE of the USA diversified organisations performed weaker than the MVE of
the focused organisations, and is found to be statistically significant, whereas
for the Korean organisations it shows that the MVE for diversified organisations
performed better than focused organisations, and is found to be statistically
significant. It is interesting that Hall and Lee’s study of the USA organisations
yielded a similar result to this study, that focused organisations outperform
diversified organisations in terms of market return.
6.2.4 Hypothesis 4: AEPSGR
The AEPSGR % results of each organisation per category as being either
focused or diversified from the period 2001 to 2005 is presented in Table 19.
The results of the hypothesis test are presented in Table 24.
The null hypothesis fails to reject in both instances where the full sample of 75
organisations are tested as well as the test where the outliers are removed from
the test. The AEPSGR of the diversified organisations (41.3218%) is greater
than the AEPSGR of the focused organisations (-50.99147%) it is not
statistically significant and it proves not to be statistically true that diversified
organisations have a superior AEPSGR than focused organisations. The results
show a large difference in AEPSGR between the two categories due to the
outliers. The test without the outliers yields the same overall result in terms of
failing to reject the null hypothesis, although the second test AEPSGR are much
less dispersed. The second test result shows the opposite and that the
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AEPSGR of the focused organisations (27.20792%) is greater than the
AEPSGR of the diversified organisations (19.63085%), although the standard
deviation is less for the second test.
The outliers excluded during the second test for the focused category are:
• -7,500% for Venter Leisure and Commercial Trailers Limited during 2001
• 2,060% for Digicor Holdings Limited during 2004
• -343.33% for Primeserv Group Limited during 2004
The outliers excluded during the second test for the diversified category are:
• 1,662.50% for Transpaco Limited during 2002
• -305.71% for Jasco Electronics Holdings Limited during 2001
• -127.63% for Howden Africa Holdings Limited during 2001 and 476.19%
during 2002
The results show that the focused organisations category has a larger variance
as shown in the larger standard deviation. This could be an indication that the
focused organisations are more volatile in terms of the economic cycles and are
more sensitive to the parts of the economy that affect the focused organisations
core businesses.
Rumelt’s (1986) study shows that the AEPSGR is the measure that yields the
least amount of variation of all the other performance measures used in his
research of organisations from 1951 to 1970. This is evident in the relevant low
differences in the AEPSGR of the four major categories as indicated below:
• Single Business AEPSGR: 3.92%
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• Dominant Business AEPSGR: 5.99%
• Related Business AEPSGR: 7.64%
• Unrelated Business AEPSGR: 7.92%
The only category result that is statistically significant at the 5% alpha level is
the single business category measure of AEPSGR 3.92%, which is less than
the other categories. Similar to this study, the AEPSGR of most of the
categories in Rumelt’s study is not statistically significant.
The objective of the study is to determine if there is a difference in the financial
performance of organisations that follow a focused or diversified strategy. The
results prove that three of the four hypotheses (financial measures) cannot be
proven to be statistically significant, whereas one of the financial measures
indicates that the AMKTRET of focused organisations is superior to the
AMKTRET of diversified organisations. The result is the opposite of what was
expected, and there seem to be some synergies between the results of this
study and findings of other international studies.
99
7. CONCLUSION
7.1 Background
Corporate diversification is one of the fundamental strategic choices available to
CEO’s and managers of organisations to foster growth and profitability. The
question of whether diversification leads to superior performance has been
discussed, debated and researched since the early 1950’s. From an
international perspective, ample research has been conducted. The findings,
however, are inconsistent and there remains a lack of consensus regarding the
diversification-performance relationship.
In South Africa, there has been no systematic study of the diversification-
performance relationship. South Africa has unique circumstances due to its past
economic isolation, forcing many organisations to diversify from the 1960’s to
the early 1990’s. With the integration of South Africa into the world economy,
many organisations divested their non-core assets, and there is ample evidence
that organisations which divested their non-core businesses and focused on
core industries have also done well. However, there is also evidence that
diversified organisations are performing well and have had a successful track
record.
This research study was conducted to determine if a high degree of corporate
diversification results in superior financial performance versus a focused
strategy.
100
7.2 Findings
The research was conducted on organisations that are listed on the industrial
sector of the JSE from the period 2001 to 2005. The research followed a two
step approach, first the organisations had to be categorised as either being
diversified or focused, and second once the categorisation was completed, the
financial performance of the two categories were statistically measured to
determine if diversified organisations outperform focused organisations.
The classification of the organisations as being diversified or focused was a
systematic approach adopted from international studies whereby a standard
industrial classification (SIC) code was assigned to the various revenue streams
of the organisations. As the information was not available on a public database,
a manual process had to be developed to measure the diversification level of
the organisations. The organisations that qualified and met all the criteria had to
remain as diversified or focused throughout the five year study period, which
resulted in two categories of organisations consisting of 15 organisations each.
The second step of the research entailed the comparison of financial data
between the two categories of organisations to determine if diversified
organisations outperformed focused organisations. Four hypotheses were
developed, whereby the Average Return on Equity (AROE), Average Return on
Assets (AROA), Average Market Return (AMKTRET) and the Average Earnings
per share growth rate (AEPSGR) of the diversified and focused organisations
were compared to each other over the period 2001 to 2005. The alternative
101
hypothesis assumed that diversified organisations would outperform the
focused organisations, and the hypotheses were tested using the parametric
one-tailed t-test where the ρ-value approach was used as well as nonparametric
tests as confirmation of the findings.
The findings reveal that three of the four hypotheses (AROE, AROA and
AEPSGR) cannot be proven and are statistically insignificant. The AMKTRET is
the only hypothesis that could be proven and focused organisations are found
to be superior to the AMKTRET of diversified organisations, which is the
opposite of what was expected. In the case of the AROE, diversified
organisations outperform focused organisations, but the result is not statistically
significant. The AROA of the focused organisations marginally outperform the
diversified organisations, however is found to be statistically insignificant, and
the AEPSGR of diversified organisations is also superior to the focused
organisations, but is also found not to be statistically significant.
Although three of the four measures could not be proven, two additional
propositions could be investigated to add to this research study. The first
proposition is that diversified organisations have developed unique
competencies to operate effectively in their environments. The research needs
to be done to understand these competencies and how they impact the
organisations and their business units.
102
The second proposition relates to the market analysis and expectations of
returns by the market. As the AMKTRET of the focused organisations were
greater than the AMKTRET of the diversified organisations, the globally
accepted belief of a market premium on the focused organisations can be
investigated. As per Appendix 3, the average Price / Earnings (P/E) ratio of the
focused organisations are compared to the P/E ratios of the diversified
organisations. The P/E ratios are similar, except for 2005 whereby the average
P/E ratio for the focused organisations are far greater than the average P/E
ratio of the diversified organisations. Further detailed studies could confirm the
belief that focused organisations P/E ratios would be greater than diversified
organisations.
7.3 In Summary
It is therefore found in this research study that three of the hypotheses
(performance measures) cannot be statistically proven between the diversified
organisations and focused organisations. One of the performance measures,
the AMKTRET of focused organisations outperform the AMKTRET of diversified
organisations and is proven to be statistically significant.
103
7.4 Recommendations
The research was an attempt to use international research methodologies in the
South African context. Various recommendations are made to gain a better
understanding of diversification’s impact within the South African environment.
The first recommendation is to expand the study to other sectors on the JSE,
thus gaining a better understanding of all the organisations listed, and not just
on the industrial sector. A second recommendation is to extend the study period
over a period of between 10 and 20 years. The extended time period will
capture the changes South African organisations underwent when economic
sanctions were lifted, as well as the trend of organisations becoming more
focused since the 1990’s. A third recommendation is to increase the number of
categories used in research. As this research only focused on two extreme
categories of diversified or focused organisations, other categories such as
those in the model developed by Rumelt (1986) can be used.
From an international diversification perspective, it is recommended that
research be conducted whereby the level and performance be measured of
South African organisations that diversify their businesses and operations
internationally, thus measuring performance across geographical borders as a
diversification strategy.
The final recommendation is to establish a South African database where all
organisational information can be stored. A South African equivalent of the USA
104
Compustat database can be developed where all the SIC code information,
annual reports, financial information, segmental information and organisational
activities can be stored in a central facility.
105
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APPENDIX 1: SIC CODE DESCRIPTIONS THE DETAILED CLASSIFICATION The italic headings indicate a logical grouping normally on a level between that of the Division and the Major group and which does not have a code but corresponds to “Division” in the ISIC. In cases where these groupings correspond with major groups, the major group heading is also in italics. MAJOR DIVISION 1: AGRICULTURE, HUNTING FORESTRY AND FISHING MAJOR DIVISION 2: MINING AND QUARRYING
Division Major Group
Group Sub Group
Title of Category
29 290 2900 29000 SERVICE ACTIVITIES INCIDENTAL TO MINING OF MINERALS
MAJOR DIVISION 3: MANUFACTURING
Division Major Group
Group Sub Group
Title of Category
30 MANUFACTURE OF FOOD PRODUCTS, BEVERAGES AND TOBACCO PRODUCTS
304 MANUFACTURE OF OTHER FOOD PRODUCTS
3041 30410 Manufacture of bakery products
3042 30420 Manufacture of sugar, including golden syrup and castor sugar
3043 30430 Manufacture of cocoa, chocolate and sugar confectionery
3044 30440 Manufacture of macaroni, noodles, couscous and similar farinaceous products
3049 Manufacture of other food products n.e.c.
30491 Manufacture of coffee, coffee substitutes and tea
30492 Manufacture of nut foods
30499 Manufacture of spices, condiments, vinegar, yeast, egg products, soups and other food products n.e.c.
30523 Manufacture of malt
32 MANUFACTURE OF WOOD AND OF PRODUCTS OF WOOD AND CORK, EXCEPT FURNITURE; MANUFACTURE OF ARTICLES OF STRAW AND PLAITING MATERIALS; MANUFACTURE OF PAPER AND PAPER PRODUCTS; PUBLISHING, PRINTING AND REPRODUCTION OF RECORDED MEDIA
MANUFACTURE OF WOOD AND PRODUCTS OF WOOD, EXCEPT FURNITURE; MANUFAC-TURE OF PAPER AND PAPER PRODUCTS; MANUFACTURE OF ARTICLES OF STRAW AND PLAITING MATERIALS (321 AND 322)
323 MANUFACTURE OF PAPER AND PAPER PRODUCTS
3231 32310 Manufacture of pulp, paper and paperboard
113
Division Major Group
Group Sub Group
Title of Category
32321 Manufacture of corrugated paper and paperboard
32322 Manufacture of containers of paper and paperboard 3239 Manufacture of other articles of paper and paperboard
32391 Stationery
32399 Other paper products
PUBLISHING, PRINTING AND REPRODUCTION OF
RECORDED MEDIA (324, 325 AND 326)
33 MANUFACTURE OF COKE, REFINED PETROLEUM PRODUCTS AND NUCLEAR FUEL; MANUFACTURE OF CHEMICALS AND CHEMICAL PRODUCTS; MANUFACTURE OF RUBBER AND PLASTIC PRODUCTS
MANUFACTURE OF COKE, REFINED PETROLEUM PRODUCTS AND NUCLEAR FUEL (331, 332 AND 333)
MANUFACTURE OF CHEMICALS AND CHEMICAL PRODUCTS (334, 335 AND 336)
334 MANUFACTURE OF BASIC CHEMICALS
3341 33410 Manufacture of basic chemicals, except fertilizers and nitrogen compounds
3342 33420 Manufacture of fertilizers and nitrogen compounds
3343 33430 Manufacture of plastics in primary form and of synthetic rubber
335 MANUFACTURE OF OTHER CHEMICAL PRODUCTS
3351 33510 Manufacture of pesticides and toher agro-chemical products
3352 33520 Manufacture of paints, varnishes and similar coatings, printing ink and mastics
3353 33530 Manufacture of pharmaceuticals, medicinal chemicals and botanical products
3354 Manufacture of soap and detergents, cleaning and polishing preparations, perfumes and toilet preparations
33541 Manufacture of soap and other cleaning compounds
33542 Manufacture of perfumes, cosmetics and other toilet preparations
33549 Manufacture of other preparations such as polishes, waxes and dressings
3359 Manufacture of other products n.e.c. 33591 Manufacture of edible salt
33592 Manufacture of explosives and pyrotechnic products
33593 Manufacture of adhesives, glues, sizes and cements
33599 Manufacture of other chemical products n.e.c.
338 3380 33800 MANUFACTURE OF PLASTIC PRODUCTS
114
Division Major Group
Group Sub Group
Title of Category
34 MANUFACTURE OF OTHER NON-METALLIC MINERAL PRODUCTS
341 3411 MANUFACTURE OF GLASS AND GLASS PRODUCTS 34111 Manufacture or sheet and plate glass, glass blocks, tubes
and rods; glass fibres and glass wool
34112 Manufacture of glass containers; glass kitchenware and tableware; scientific and laboratory glassware, clock and watch glasses and other glass products n.e.c.
342 MANUFACTURE OF NON-METALLIC MINERAL PRODUCTS N.E.C.
3421 34210 Manufacture of non-structural non-refractory ceramicware
3422 34220 Manufacture of refractory ceramic products
3423 34230 Manufacture of structural non-refractory clay and ceramic products
3424 34240 Manufacture of cement, lime and plaster
3425 34250 Manufacture of articles of concrete, cement and plaster
3426 34260 Cutting, shaping and finishing of stone
3429 Manufacture of other non-metallic mineral products n.e.c.
34291 Abrasives
34299 Other non-metallic mineral products n.e.c. 35 MANUFACTURE OF BASIC METALS, FABRICATED
METAL PRODUCTS, MACHINERY AND EQUIPMENT AND OF OFFICE, ACCOUNTING AND COMPUTING MACHINERY
MANUFACTURE OF BASIC METALS (351, 352 AND 353)
351 3510 MANUFACTURE OF BASIC IRON AND STEEL
35101 Basic iron and steel industries, except steel pipe and tube mills
35102 Steel pipe and tube mills
MANUFACTURE OF FABRICATED METAL PRODUCTS (354 AND 355)
354 MANUFACTURE OF STRUCTURAL METAL PRODUCTS, TANKS, RESERVOIRS AND STEAM GENERATORS
3541 Manufacture of structural metal products
35411 Manufacture of metal structures or parts thereof
35419 Other structural metal products, e.g. metal doors, windows and gates
3542 35420 Manufacture of tanks, reservoirs and similar containers of metal
3543 35430 Manufacture of steam generators, except central heating hot water boilers
355 MANUFACTURE OF OTHER FABRICATED METAL PRODUCTS; METALWORK SERVICE ACTIVITIES
115
Division Major Group
Group Sub Group
Title of Category
3551 35510 Forging, pressing, stamping and roll-forming of metal; powder metallurgy
3552 Treatment and coating of metals; general mechanical engineering on a fee or contract basis
35521 Treating and coating of metals
35522 General mechanical engineering on a fee or contract basis
3553 35530 Manufacture of cutlery, hand tools and general hardware
3559 Manufacture of other fabricated metal products n.e.c.
35591 Manufacture of metal containers, e.g. cans and tins 35592 Manufacture of cables and wire products
33593 Manufacture of springs (all types)
35594 Manufacture of metal fasteners
35599 Manufacture of other metal products n.e.c.
MANUFACTURE OF MACHINERY AND EQUIPMENT
N.E.C. (356, 357 AND 358)
357 MANUFACTURE OF SPECIAL PURPOSE MACHINERY
3571 35710 Manufacture of agricultural and forestry machinery
3572 35720 Manufacture of machine tools
3573 35730 Manufacture of machinery for metallurgy
3574 35740 Manufacture of machinery for mining, quarrying and construction
3575 35750 Manufacture of machinery for food, beverage and tobacco processing
3576 35760 Manufacture of machinery for textile, apparel and leather production
3577 35770 Manufacture of weapons and ammunition
3579 35790 Manufacture of other special purpose machinery
358 3580 35800 MANUFACTURE OF HOUSEHOLD APPLIANCES N.E.C.
359 3590 35900 MANUFACTURE OF OFFICE, ACCOUNTING AND COMPUTING MACHINERY
36 MANUFACTURE OF ELECTRICAL MACHINERY AND APPARATUS N.E.C.
MANUFACTURE OF ELECTRICAL MACHINERY AND APPARATUS N. E.C. (361, 362, 363, 364 AND 365)
361 3610 36100 MANUFACTURE OF ELECTRIC MOTORS, GENERATORS AND TRANSFORMERS
362 3620 36200 MANUFACTURE OF ELECTRICITY DISTRIBU-TION AND CONTROL APPARATUS
363 3630 36300 MANUFACTURE OF INSULATED WIRE AND CABLE
364 3640 36400 MANUFACTURE OF ACCUMULATORS, PRIMARY CELLS AND PRIMARY BATTERIES
116
Division Major Group
Group Sub Group
Title of Category
365 3650 MANUFACTURE OF ELECTRIC LAMPS AND LIGHTING
EQUIPMENT
36501 Manufacture of electric bulbs and fluorescent tubes
36502 Manufacture of illuminated signs and advertising displays
36503 Manufacture of lamps and lampshades
366 3660 36600 MANUFACTURE OF OTHER ELECTRICAL EQUIPMENT N.E.C
37 MANUFACTURE OF RADIO, TELEVISION AND COMMUNICATION EQUIPMENT AND APPARATUS AND OF MEDICAL, PRECISION AND OPTICAL INSTRUMENTS, WATCHES AND CLOCKS
MANUFACTURE OF RADIO, TELEVISION AND COMMUNICATION EQUIPMENT AND APPARATUS (371, 372 AND 373)
371 3710 37100 MANUFACTURE OF ELECTRONIC VALVES AND TUBES AND OTHER ELECTRONIC COMPONENTS
372 3720 37200 MANUFACTURE OF TELEVISION AND RADIO TRANSMITTERS AND APPARATUS FOR LINE TELEPHONY AND LINE TELEGRAPHY
373 3730 37300 MANUFACTURE OF TELEVISION AND RADIO RECEIVERS, SOUND OR VIDEO RECORDING OR REPRODUCING APPARATUS AND ASSOCIATED GOODS
MANUFACTURE OF MEDICAL, PRECISION AND OPTICAL INSTRUMENTS, WATCHES AND CLOCKS (374, 375 AND 376)
38 MANUFACTURE OF TRANSPORT EQUIPMENT
MANUFACTURE OF MOTOR VEHICLES, TRAILERS AND SEMI-TRAILERS (381, 382 AND 383)
381 3810 38100 MANUFACTURE OF MOTOR VEHICLES
382 3820 38200 MANUFACTURE OF BODIES (COACHWORK) FOR MOTOR VEHICLES; MANUFACTURE OF TRAILERS AND SEMI-TRAILERS
383 3830 MANUFACTURE OF PARTS AND ACCESSORIES FOR MOTOR VEHICLES AND THEIR ENGINES
38301 Manufacture of radiators
38302 Activities of specialised automotive engineering workshops working primarily for the motor trade
38309 Manufacture of other motor vehicle parts and accessories
MANUFACTURE OF OTHER TRANSPORT EQUIPMENT (384, 385, AND 386)
387 MANUFACTURE OF TRANSPORT EQUIPMENT N.E.C.
3871 38710 Manufacture of motor cycles 3872 38720 Manufacture of bicycle and invalid carriages
3879 38790 Manufacture of other transport equipment n.e.c.
117
Division Major Group
Group Sub Group
Title of Category
39 MANUFACTURE OF FURNITURE; MANUFACTURING N.E.C.; RECYCLING
MANUFACTURE OF FURNITURE; MANUFACTURING N.E.C. (391 AND 392)
391 3910 MANUFACTURE OF FURNITURE
39101 Manufacture of furniture made predominantly of metal
39102 Manufacture of furniture made predominantly of plastic materials
39103 Manufacture of furniture made predominantly of materials other than metal, plastic or concrete
395 RECYCLING N.E.C.
3951 39510 Recycling of metal waste and scrap n.e.c.
3952 39520 Recycling of non-metal waste and scrap n.e.c.
MAJOR DIVISION 4: ELECTRICITY, GAS AND WATER SUPPLY MAJOR DIVISION 5: CONSTRUCTION
Division Major Group
Group Sub Group
Title of Category
50 CONSTRUCTION
CONSTRUCTION (501, 502, 503, 504 AND 505)
501 5010 50100 SITE PREPARATION
502 BUILDING OF COMPLETE CONSTRUCTIONS OR PARTS THEREOF; CIVIL ENGINEERING
5021 Construction of buildings
50211 Construction of homes
50219 Construction of other buildings 5022 50220 Construction of civil engineering structures
5023 50230 Construction of other structures
5024 50240 Construction by specialist trade contractors
503 BUILDING INSTALLATION
5031 50310 Plumbing
5032 50320 Electrical contracting
5033 50330 Shopfitting
5039 50390 Other building installation n.e.c.
504 BUILDING COMPLETION
5041 50410 Painting and decorating
5049 50490 Other building completion n.e.c.
505 5050 50500 RENTING OF CONSTRUCTION OR DEMOLITION
EQUIPMENT WITH OPERATORS
118
MAJOR DIVISION 6: WHOLESALE AND RETAIL TRADE; REPAIR OF MOTOR VEHICLES, MOTOR CYCLES AND PERSONAL AND HOUSEHOLD GOODS; HOTELS AND RESTAURANTS Division Major Group Group Sub
Group Title of Category
61 WHOLESALE AND COMMISSION TRADE, EXCEPT OF MOTOR VEHICLES AND MOTOR CYCLES
WHOLESALE AND COMMISSION TRADE EXCEPT OF MOTOR VEHICLES AND MOTOR CYCLES (611, 612, 613, 614, 615 AND 616)
612 WHOLESALE TRADE IN AGRICULTURAL RAW MATERIALS, LIVESTOCK, FOOD, BEVERAGES AND TOBACCO
6121 61210 Wholesale trade in agricultural raw materials and livestock
6122 Wholesale trade in food, beverages and tobacco
61221 Wholesale trade in foodstuffs
61222 Wholesale trade in beverages
61223 Wholesale trade in tobacco products
613 WHOLESALE TRADE IN HOUSEHOLD GOODS
6131 61310 Wholesale trade in textiles, clothing and footwear
6139 Wholesale trade in other household goods
61391 Wholesale trade in household furniture, requisites and appliances
61392 Wholesale trade in books and stationery
61393 Wholesale trade in precious tones, jewellery and silverware
61394 Wholesale trade in pharmaceuticals and toiletries
61399 Wholesale trade in other household goods n.e.c.
614 WHOLESALE TRADE IN NON-AGRICULTU-RAL INTERMEDIATE PRODUCTS, WASTE AND SCRAP
6141 61410 Wholesale trade in solid, liquid and gaseous fuels and related products
6142 61420 Wholesale trade in metals and metal ores 6143 61430 Wholesale trade in construction materials, hardware,
plumbing and heating equipment and supplies
6149 61490 Wholesale trade in other intermediate products, waste and scrap
615 6150 WHOLESALE TRADE IN MACHINERY, EQUIPMENT AND SUPPLIES
61501 Office machinery and equipment including computers
61509 Other machinery
63 SALE MAINTENANCE AND REPAIR OF MOTOR VEHICLES AND MOTOR R CYCLES; RETAIL TRADE IN AUTOMOTIVE FUEL
SALE, MAINTENANCE AND REPAIR OF MTOOR VEHICLES AND MOTOR CYCLES; RETAIL TRADE IN
119
Division Major Group Group Sub Group
Title of Category
AUTOMOTIVE FUEL (631, 632, 633, 634 AND 635)
631 SALE OF MOTOR VEHICLES
6311 63110 Wholesale sale of motor vehicles
6312 Retail sale of motor vehicles
63121 Retail sale of new motor vehicles
63122 Retail sale of used motor vehicles
632 6320 MAINTENANCE AND REPAIR OF MOTOR VEHICLES
63201 General repairs
63202 Electrical repairs
63203
Radiator repairs
63204 Body repairs
63209 Other maintenance and repairs n.e.c.
633 SALE OF MOTOR VEHICLE PARTS AND ACCESSORIES
6331 Sale of new parts and accessories
63311 Sale of tyres
63319 Sale of other new parts and accessories
6332 63320 Sale of used parts and accessories
634 6340 63400 SALE, MAINTENANCE AND REPAIR OF MOTOR CYCLES AND RELATED PARTS AND ACCESSORIES
635 6350 63500 RETAIL SALE OF AUTOMOTIVE FUEL MAJOR DIVISION 7: TRANSPORT, STORAGE AND COMMUNICATION Division Major
Group Group Sub
Group Title of Category
71 LAND TRANSPORT; TRANSPORT VIA PIPELINES
LAND TRANSPORT; TRANSPORT VIA PIPELINES (711, 712 AND 713)
711 7111 RAILWAY TRANSPORT
71111 Inter-urban railway transport
71112 Railway commuter services
712 OTHER LAND TRANSPORT
7121 Other scheduled passenger land transport
71211 Urban, suburban and inter-urban bus and coach passenger lines
71212 School buses
7122 Other non-scheduled passenger land transport
120
Division Major Group
Group Sub Group
Title of Category
71221 Taxis
71222 Safaris and sightseeing bus tours
71229 Other passenger transport, including the renting of motor cars with drivers
7123 Freight transport by road
71231 Transport of furniture
71239 Other freight transport by road
713
7130 71300 TRANSPORT VIA PIPELINES
73 AIR TRANSPORT
730 7300 73000 AIR TRANSPORT 74 741 SUPPORTING AND AUXILIARY TRANSPORT
ACTIVITIES; ACTIVITIES OF TRAVEL AGENCIES
7411 74110 Cargo handling
7412 74120 Storage and warehousing
7413 Other supporting transport activities
74131 Parking garages and parking lots
74132 Salvaging of distressed vessels and cargoes
74133 Maintenance and operation of harbour works, lighthouses, etc., pilotage
74134 Operation of airports, flying fields and air navigation facilities
74135 Operation of roads and toll roads
74139 Other supporting transport activities n.e.c.
7414 74140 Travel agency and related activities
7419 74190 Activities of other transport agencies
75 POST AND TELECOMMUNICATION
POST AND TELECOMMUNICATION (751 AND 752)
751 POSTAL AND RELATED COURIER ACTIVITIES
7511 75110 National postal activities
7512 75120 Courier activities other than national postal activities
752 7520 75200 TELECOMMUNICATION MAJOR DIVISION 8: FINANCIAL INTERMEDIATION INSURANCE, REAL ESTATE AND BUSINESS SERVICES Division Major Group Group Sub
Group Title of Category
81 FINANCIAL INTERMEDIATION, EXCEPT INSURANCE AND PENSION FUNDING
FINANCIAL INTERMEDIATION, EXCEPT INSURANCE AND PENSION FUNDING (811 AND 819)
121
Division Major Group Group Sub Group
Title of Category
811 8111 MONETARY INTERMEDIATION
81110 Central banking
8112 Other monetary intermediation
81121 Discount houses and commercial and other banking
81122 Building society activities
819 OTHER FINANCIAL INTERMEDIATION N.E.C.
8191 81910 Lease financing
8192 81920 Other credit granting
8199 81990
Other financial intermediation n.e.c.
82 INSURANCE AND PENSION FUNDING, EXCEPT COMPULSORY SOCIAL SECURITY
821 INSURANCE AND PENSION FUNDING, EXCEPT COMPULSORY SOCIAL SECURITY
8211 82110 Life insurance
8212 82120 Pension funding
8213 82130 Medical aid funding
8219 82190 Other insurance n.e.c. 85 RENTING OF MACHINERY AND EQUIPMENT, WITHOUT
OPERATOR AND OF PERSONAL AND HOUSEHOLD GOODS
RENTING OF MACHINERY AND EQUIPMENT, WITHOUT OPERATOR AND OF PERSONAL AND HOUSEHOLD GOODS (851, 852 AND 853)
851 RENTING OF TRANSPORT EQUIPMENT
8511 85110 Renting of land transport equipment
8512 85120 Renting of water transport equipment
8513 85130 Renting of air transport equipment
852 RENTING OF OTHER MACHINERY AND EQUIPMENT
8521 85210 Renting of agricultural machinery and equipment
8522 85220 Renting of construction and civil engineering machinery and equipment
8523 85230 Renting of office machinery and equipment (including computers)
8529 85290 Renting of other machinery and equipment n.e.c.
853 RENTING OF PERSONAL AND HOUSEHOLD GOODS N.E.C.
8530 85300 Renting of personal and household goods n.e.c. 86 COMPUTER AND RELATED ACTIVITIES
COMPUTER AND RELATED ACTIVITIES (861, 862, 863,
864, 865 AND 866)
122
Division Major Group Group Sub Group
Title of Category
861 8610 86100 HARDWARE CONSULTANCY
862 8620 86200 SOFTWARE CONSULTANCY AND SUPPLY 863 8630 86300 DATA PROCESSING 864 8640 86400 DATA BASE PROCESSING
865 8650 86500 MAINTENANCE AND REPAIR OF OFFICE, ACCOUNTING
AND COMPUTING MACHINERY
869 8690 86900 OTHER COMPUTER RELATED ACTIVITIES 88 OTHER BUSINESS ACTIVITIES
OTHER BUSINESS ACTIVITIES (881, 882, 883 AND 884)
881 LEGAL, ACCOUNTING, BOOKKEEPING AND AUDITING
ACTIVITIES; TAX CONSULTANCY; MARKET RESEARCH AND PUBLIC OPINION RESEARCH; BUSINESS AND MANAGEMENT CONSULTANCY
8811 Legal activities
88111 Activities of attorneys, notaries and conveyancers
88112 Activities of advocates
8812 Accounting, bookkeeping and auditing activities; tax consultancy
88121 Activities of accountants and auditors registered in terms of the Public Accountants and Auditors Act
88122 Activities of cost and management accountants
88123 Bookkeeping activities, including relevant data processing and tabulating activities
8813 88130 Marketing research and public opinion polling
8814 88140 Business and management consultancy activities
882 ARCHITECTURAL, ENGINEERING AND OTHER TECHNICAL ACTIVITIES
8821 Architectural and engineering activities and related technical consultancy
88211 Consulting engineering activities
88212 Architectural activities
88213 Activities of quantity surveyors
88214 Activities of land surveyors 88215 Geological and prospecting activities on a fee or contract
basis
88216 Activities of non-registered architects, eg. Tracers and draughtsmen of plans for dwellings
8822 Technical testing and analysis
88220 Other activities - engineering and other commercial research, developing and testing - eg SABS
889 BUSINESS ACTIVITIES N.E.C.
8891 Labour recruitment and provision of staff
123
Division Major Group Group Sub Group
Title of Category
88911 Activities of employment agencies and recruiting organisations
88912 Hiring out of workers (labour broking activities)
8892 88920 Investigation and security activities
8893 88930 Building and industrial plant cleaning activities
8894 88940 Photographic activities
8895 88950 Packaging activities
8899 Other business activities n.e.c.
88991 Credit rating agency activities
88992 Debt collecting agency activities
88993 Stenographic, duplicating, addressing, mailing list and similar activities
88999 Other business activities n.e.c. MAJOR DIVISION 9: COMMUNITY, SOCIAL AND PERSONAL SERVICES Division Major Group Group Sub
Group Title of Category
92 EDUCATION
920 9200 EDUCATIONAL SERVICES
92001 Pre-primary education and activities of after-school centres
92002 Primary and secondary education
92003 Special education and training of mentally retarded children
92004 Education by technical colleges and technical institutions
92005 Education by technikons
92006 Education by teachers’ training colleges and colleges of education for further training
92007 Education by universities
82008 Education by correspondence and private vocational colleges
92009 Other educational services - own account teachers, motor vehicle driving schools/tutors and music, dancing and other art schools, etc.
MAJOR DIVISION 0: PRIVATE HOUSEHOLDS, EXTERRITORIAL ORGANISATIONS, REPRESENTATIVES OF FOREIGN GOVERNMENTS AND OTHER ACTIVITIES NOT ADEQUATELY DEFINED Source: South African Companies and Intellectual Property Registration Office (CIPRO)
http://www.cipro.co.za/info_library/sic_codes.asp
124
APPENDIX 2: FOCUSED ORGANISATIONS SPECIALISATION RATIOS
Company Name Sharecode Adcorp Holdings Limited ADR 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Permanent Recruitment 889 - Business Activities R 328
Flexible staffing solutions - Outsourcing of tempory staff 889 - Business Activities R 1,848 Corporate Communications 889 - Business Activities R 81
Marketing Research
881 - Legal, Accounting, Bookkeeping and auditing services; Tax Consultancy; Market Research R 101
Total Revenue R 2,358 SR 0.96 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Permanent Recruitment 889 - Business Activities R 178
Flexible staffing solutions - Outsourcing of tempory staff 889 - Business Activities R 718 Corporate Communications 889 - Business Activities R 144
Marketing Research
881 - Legal, Accounting, Bookkeeping and auditing services; Tax Consultancy; Market Research R 66
Total Revenue R 1,106 SR 0.94
Company Name Sharecode Astrapak Limited APK 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Rigid plastic products 338 - Manufacture of plastic products R 648 Film plastics - Polyethylene Films 338 - Manufacture of plastic products R 735 Flexible plastic products 338 - Manufacture of plastic products R 267 Total Revenue R 1,650 SR 1.00 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Rigid plastic products 338 - Manufacture of plastic products R 107 Film plastics - Polyethylene Films 338 - Manufacture of plastic products R 432 Flexible plastic products 338 - Manufacture of plastic products R 158 Total Revenue R 697 SR 1.00
125
Company Name Sharecode Bell Equipment Limited BEL 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of heavy duty vehicles and earthmoving equipment 387 - Manufacture of transport equipment R 3,209 Total Revenue R 3,209 SR 1.00 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of heavy duty vehicles and earthmoving equipment 387 - Manufacture of transport equipment R 1,658 Total Revenue R 1,658 SR 1.00
Company Name Sharecode Bowler Metcalf Limited BCF 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of plastics and plastic mouldings 338 - Manufacture of plastic products R 338 Other R 7 Total Revenue R 345 SR 0.98 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of plastics and plastic mouldings 338 - Manufacture of plastic products R 114 Total Revenue R 114 SR 1.00
Company Name Sharecode Cargo Carriers Limited CRG 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Transport Services - Land transport and warehousing
741 - Supporting and auxiliary transport activities R 338
Information Technology 862 - Software Consultancy and supply R 33 Total Revenue R 371 SR 0.91 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Transport Services - Land transport and warehousing
741 - Supporting and auxiliary transport activities R 319
Information Technology 862 - Software Consultancy and supply R 0 Other R 8 Total Revenue R 327 SR 0.98
126
Company Name Sharecode Ceramic Industries Limited CRM 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of wall & floor tiles 342 - Manufacture of non-metallic mineral products R 731
Manufacture of sanitaryware 342 - Manufacture of non-metallic mineral products R 151
Other R 72 Total Revenue R 954 SR 0.92 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of wall & floor tiles 342 - Manufacture of non-metallic mineral products R 375
Manufacture of sanitaryware 342 - Manufacture of non-metallic mineral products R 42
Other R 0 Total Revenue R 417 SR 1.00
Company Name Sharecode Control Instruments Group Limited CNL 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of instruments and parts for the automotive industry
383 - Manufacture of parts and accessories for motor vehicles and their engines R 395
Total Revenue R 395 SR 1.00 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of instruments and parts for the automotive industry
383 - Manufacture of parts and accessories for motor vehicles and their engines R 260
Total Revenue R 260 SR 1.00
Company Name Sharecode Digicor Holdings Limited DGC 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of instruments and tracking devices and parts for the automotive industry
383 - Manufacture of parts and accessories for motor vehicles and their engines R 12
Distribution and installation of automotive parts and tracking devices
633 - Sale of motor vehicle parts and accessories R 240
Total Revenue R 252 SR 0.95 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
127
Manufacture of instruments and tracking devices and parts for the automotive industry
383 - Manufacture of parts and accessories for motor vehicles and their engines R 2
Distribution and installation of automotive parts and tracking devices
633 - Sale of motor vehicle parts and accessories R 191
Total Revenue R 193 SR 0.99
Company Name Sharecode Distribution and Warehousing Network Ltd DAW 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of sanitaryware 342 - Manufacture of non-metallic mineral products R 258
Distribution in brassware, sanitaryware and plumbing
614 - Wholesale trade in non-agricultural intermediate products, waste and scrap R 1,225
Total Revenue R 1,357 SR 0.90 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of sanitaryware 342 - Manufacture of non-metallic mineral products R 37
Distribution in brassware, sanitaryware and plumbing
614 - Wholesale trade in non-agricultural intermediate products, waste and scrap R 655
Total Revenue R 692 SR 0.95
Company Name Sharecode EnviroServ Holdings Limited ENV 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Waste Services 395 - Recycling R 538
Container Management 354 - Manufacture of structural metal products, tanks, reservoirs and steam generators R 0
Plant Hire 852 - Renting of other machinery and equipment R 41
Total Revenue R 579 SR 0.93 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Waste Services 395 - Recycling R 369
Container Management 354 - Manufacture of structural metal products, tanks, reservoirs and steam generators R 11
Plant Hire 852 - Renting of other machinery and equipment R 0
Total Revenue R 380 SR 0.97
128
Company Name Sharecode Iliad Africa Limited ILA 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Distribution in building materials and hardware products
614 - Wholesale trade in non-agricultural intermediate products, waste and scrap R 2,683
Total Revenue R 2,683 SR 1.00 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Distribution in building materials and hardware products
614 - Wholesale trade in non-agricultural intermediate products, waste and scrap R 752
Total Revenue R 752 SR 1.00
Company Name Sharecode Pretoria Portland Cement PPC 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of cement, lime and limestone
342 - Manufacture of non-metallic mineral products R 3,827
Manufacture of paper sacks and containers 323 - Manufacture of paper and paper products R 255 Total Revenue R 4,082 SR 0.94 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of cement, lime and limestone
342 - Manufacture of non-metallic mineral products R 1,961
Manufacture of paper sacks and containers 323 - Manufacture of paper and paper products R 161 Total Revenue R 2,122 SR 0.92
Company Name Sharecode Primeserv Group Limited PMV 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Flexible staffing solutions - Outsourcing of tempory staff 889 - Business Activities R 334 Computer Training 920 - Educational Services R 21 Human Resource Solutions 889 - Business Activities R 19 Total Revenue R 374 SR 0.94 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Flexible staffing solutions - Outsourcing of tempory staff 889 - Business Activities R 713 Training Services 920 - Educational Services R 67 Total Revenue R 780
129
SR 0.91
Company Name Sharecode Value Group Limited VLE 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Freight services, warehousing, cargo and terminal management
741 - Supporting and auxiliary transport activities. R 718
Total Revenue R 718 SR 1.00 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Freight services, warehousing, cargo and terminal management
741 - Supporting and auxiliary transport activities. R 326
Total Revenue R 326 SR 1.00
Company Name Sharecode Venter Leisure and Commercial Trailers VTL 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of luggage and commercial trailers and trailer accessories
382 - Manufacture of bodies (Coachwork) for motor vehicles; Manufacture of trailers and semi-trailers R 53
Total Revenue R 53 SR 1.00 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of luggage and commercial trailers and trailer accessories
382 - Manufacture of bodies (Coachwork) for motor vehicles; Manufacture of trailers and semi-trailers R 44
Total Revenue R 44 SR 1.00
130
APPENDIX 3: DIVERSIFIED ORGANISATIONS SPECIALISATION RATIOS
Company Name Sharecode AG Industries Limited AGI 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of glass sheets and tempered glass 341 - Manufacture of glass and glass products R 631
Manufacture of aluminium frames and patio doors
354 - manufacture of structural metal products, tanks, reservoirs and steam generators R 622
Total Revenue R 1,253 SR 0.50 2001
Manufacture of glass sheets and tempered glass 341 - Manufacture of glass and glass products R 427
Manufacture of aluminium frames and patio doors
354 - manufacture of structural metal products, tanks, reservoirs and steam generators R 265
Total Revenue R 692 SR 0.62
Company Name Sharecode Allied Electronics Corporation Limited ATN 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Telecommunication 752 - Telecommunications R 4,713
Multi-media and electronics
372 - Manufacture of television and radio transmitters and apparatus for line telephony and telegraphy R 3,724
Information Technology 862 - Software and consultancy supply R 3,835 Total Revenue R 12,272 SR 0.38 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Telecommunication 752 - Telecommunications R 3,190
Multi-media and electronics
372 - Manufacture of television and radio transmitters and apparatus for line telephony and telegraphy R 3,997
Information Technology 862 - Software and consultancy supply R 1,940 Total Revenue R 9,127 SR 0.44
131
Company Name Sharecode Aveng Limited AEG 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Construction 502 - Building of complete constructions or parts thereof; Civil Engineering R 8,561
Steel 351 - Manufacture of basic iron and steel R 4,974 Total Revenue R 13,535 SR 0.63 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Construction 502 - Building of complete constructions or parts thereof; Civil Engineering R 7,270
Steel 351 - Manufacture of basic iron and steel R 3,047 Total Revenue R 10,317 SR 0.70
Company Name Sharecode Barloworld Limited BAW 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Distribution of earthmoving equipment 615 - Wholesale trade in machinery, equipment and supplies R 10,422
Industrial distribution of forklifts 615 - Wholesale trade in machinery, equipment and supplies R 5,905
Distribution of motor vehicles 631 - Sale of motor vehicles R 10,421
Cement 342 - Manufacture of non-metallic mineral products R 3,974
Coatings 335 - Manufacture of other chemical products R 2,622 Other R 6,057 Total Revenue R 39,401 SR 0.41 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Distribution of earthmoving equipment 615 - Wholesale trade in machinery, equipment and supplies R 8,362
Industrial distribution of forklifts 615 - Wholesale trade in machinery, equipment and supplies R 5,143
Distribution of motor vehicles 631 - Sale of motor vehicles R 6,608
Cement 342 - Manufacture of non-metallic mineral products R 1,971
Coatings 335 - Manufacture of other chemical products R 2,249 Other R 3,612 Total Revenue R 27,945 SR 0.48
Company Name Sharecode Bidvest Group Limited BVT 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Freight services, warehousing, cargo and terminal management
741 - Supporting and auxiliary transport activities. R 14,583
132
Outsourcing of business services 889 - Business activities R 2,890
Financial services, travel services and foreign exchange 819 - Other financial intermediation R 693
Food distribution
612 - Wholesale trade in agricultural raw materials, livestock, food, beverages and tobacco R 22,716
Baking products 304 - Manufacture of other food products R 1,066
Office supplies 615 - Wholesale trade in machinery, equipment and supplies R 8,282
Distribution of motor vehicles - New and used vehicles 631 - Sale of motor vehicles R 13,628 Corporate Services 881 - Other business activities R 331 Other R 3 Total Revenue R 64,192 SR 0.35 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Freight services, warehousing, cargo and terminal management
741 - Supporting and auxiliary transport activities. R 12,131
Outsourcing of business services 889 - Business activities R 1,163
Financial services, travel services and foreign exchange 819 - Other financial intermediation R 465
Food distribution
612 - Wholesale trade in agricultural raw materials, livestock, food, beverages and tobacco R 12,574
Baking products 304 - Manufacture of other food products R 652
Office supplies 615 - Wholesale trade in machinery, equipment and supplies R 3,372
Total Revenue R 30,357 SR 0.41
Company Name Sharecode Delta Electrical Industries Limited DEL 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of chemicals in the manufacturing of batteries 335 - Manufacture of other chemical products R 524
Repair and service of rotating machinery and transformers 632 - Maintenance and repair of motor vehicles R 629
Supplier of replacement parts to earthmoving equipment
614 - Wholesale trade in non-agricultural intermediate products, waste and scrap R 151
Total Revenue R 1,304 SR 0.48 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of chemicals in the manufacturing of batteries 335 - Manufacture of other chemical products R 508
Repair and service of rotating machinery and transformers 632 - Maintenance and repair of motor vehicles R 548
Supplier of replacement parts to earthmoving equipment
614 - Wholesale trade in non-agricultural intermediate products, waste and scrap R 125
Total Revenue R 1,181 SR 0.46
133
Company Name Sharecode Howden Africa Holdings Limited HWN 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of fans and heat exchangers 357 - Manufacture of special purpose machinery R 310
Environmental Control - Waste water treatment 395 - Recycling R 187 Total Revenue R 497 SR 0.62 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Manufacture of fans and heat exchangers 357 - Manufacture of special purpose machinery R 273
Environmental Control - Waste water treatment 395 - Recycling R 104 Total Revenue R 377 SR 0.70
Company Name Sharecode Hudaco Industries Limited HDC 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Distribution of bearings & transmission products
614 - Wholesale trade in non-agricultural intermediate products, waste and scrap R 911
Distribution in powered products - Diesel engines & power tools
615 - Wholesale trade in machinery, equipment and supplies R 376
Distribution of security equipment - CCTV's & access control
615 - Wholesale trade in machinery, equipment and supplies R 263
Total Revenue R 1,550 SR 0.59 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Distribution of bearings & transmission products
614 - Wholesale trade in non-agricultural intermediate products, waste and scrap R 576
Distribution in powered products - Diesel engines & power tools
615 - Wholesale trade in machinery, equipment and supplies R 233
Distribution of security equipment - CCTV's & access control
615 - Wholesale trade in machinery, equipment and supplies R 126
Manufacture of automotive parts 383 - Manufacture of parts and accessories for motor vehicles and their engines R 135
Total Revenue R 1,070 SR 0.54
Company Name Sharecode Imperial Holdings Limited IPL 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Logistics - Road transport and warehousing
741 - Supporting and auxiliary transport activities R 12,721
Leasing & Fleet management of forklifts and machinery
852 - Renting of other machinery and equipment R 2,569
134
Aviation - Leasing solutions 851 - Renting of transport equipment R 2,699 Car rental 851 - Renting of transport equipment R 3,069
Motor vehicle parts distribution 633 - Sale of motor vehicle parts and accessories R 9,655
Motor vehicle dealerships 631 - Sale of motor vehicles R 12,073
Insurance 821 - Insurance and pension funding, except compulsory social security R 2,027
Total Revenue R 44,813 SR 0.28 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Logistics - Road transport and warehousing
741 - Supporting and auxiliary transport activities R 8,745
Leasing & Fleet management of forklifts and machinery
852 - Renting of other machinery and equipment R 1,289
Aviation - Leasing solutions 851 - Renting of transport equipment R 1,460 Car rental 851 - Renting of transport equipment R 1,294
Motor vehicle parts distribution 633 - Sale of motor vehicle parts and accessories R 3,064
Motor vehicle dealerships 631 - Sale of motor vehicles R 7,956
Insurance 821 - Insurance and pension funding, except compulsory social security R 862
Total Revenue R 24,670 SR 0.35
Company Name Sharecode Jasco Electronic Holdings Limited JSC 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Telecommunication 752 - Telecommunications R 140
Manufacturing of domestic appliances and leisure products 391 - Manufacture of furniture R 72
Security, CCTV's and solutions
372 - Manufacture of television and radio transmitters and apparatus for line telephony and telegraphy R 36
Other R 8 Total Revenue R 256 SR 0.55 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Telecommunication 752 - Telecommunications R 91
Manufacturing of domestic appliances and leisure products 391 - Manufacture of furniture R 35
Security, CCTV's and solutions
372 - Manufacture of television and radio transmitters and apparatus for line telephony and telegraphy R 13
Data - Software 862 - Software consultancy and supply R 267 Other R 12 Total Revenue R 418 SR 0.64
135
Company Name Sharecode Murray & Roberts Holdings Limited MUR 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Construction 502 - Building of complete constructions or parts thereof; Civil Engineering R 3,128
Mining 290 - Service activities incidental to mining of minerals R 2,506
Engineering 882 - Architectural, Engineering and other technical activities R 603
Construction Materials & Services 502 - Building of complete constructions or parts thereof; Civil Engineering R 1,164
Steel 351 - Manufacture of basic iron and steel R 2,268
Infrastructure Materials & Services, Fabrication & Services
355 - Manufacture of other fabricated metal products; Metalwork service activities R 1,024
Total Revenue R 10,693 SR 0.40 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Construction 502 - Building of complete constructions or parts thereof; Civil Engineering R 2,077
Mining 290 - Service activities incidental to mining of minerals R 1,328
Engineering 882 - Architectural, Engineering and other technical activities R 1,628
Construction Materials & Services 502 - Building of complete constructions or parts thereof; Civil Engineering R 917
Steel 351 - Manufacture of basic iron and steel R 1,628
Infrastructure Materials & Services, Fabrication & Services
355 - Manufacture of other fabricated metal products; Metalwork service activities R 1,024
Total Revenue R 8,602 SR 0.35
Company Name Sharecode Nampak Limited NPK 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Glass Packaging 341 - Manufacture of glass and glass products R 4,521
Paper 323 - Manufacture of paper and paper products R 7,329 Plastics 338 - Manufacture of plastic products R 3,758 Total Revenue R 15,608 SR 0.47 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Glass Packaging 341 - Manufacture of glass and glass products R 2,762
Paper 323 - Manufacture of paper and paper products R 3,348 Plastics 338 - Manufacture of plastic products R 3,880 Total Revenue R 9,990 SR 0.39
136
Company Name Sharecode Reunert Limited RLO 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Electrical Engineering - Manufacturing of cables and circuit breakers 363 - Manufacture of insulated wire and cable R 1,986
Electronics - Office automation 615 - Wholesale trade in machinery, equipment and supplies R 981
Electronic consumer products 613 - Wholesale trade in household goods R 3,770 Telecommunications 752 - Telecommunications R 993
Reutech - Defence products 366 - Manufacture of other electrical equipment R 298 Total Revenue R 8,028 SR 0.41 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Electrical Engineering - Manufacturing of cables and circuit breakers 363 - Manufacture of insulated wire and cable R 1,007
Electronics - Office automation 615 - Wholesale trade in machinery, equipment and supplies R 694
Electronic consumer products 613 - Wholesale trade in household goods R 2,335 Telecommunications 752 - Telecommunications R 922
Reutech - Defence products 366 - Manufacture of other electrical equipment R 400 Total Revenue R 5,358 SR 0.44
Company Name Sharecode Super Group Limited SPG 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Supply chain management & warehousing 741 - Supporting and auxiliary transport activities R 1,755
Long distance transport 712 - Other land transport R 421 Fleet solutions 851 - Renting of transport equipment R 748 Motor vehicle dealerships 631 - Sale of motor vehicles R 3,439
Services - Treasury and Insurance 832 - Activities auxiliary to insurance and pension funding R 146
Motor vehicle parts distribution 633 - Sale of motor vehicle parts and accessories R 1,876
Total Revenue R 8,385 SR 0.41 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Supply chain management & warehousing 741 - Supporting and auxiliary transport activities R 1,712
Motor vehicle dealerships 631 - Sale of motor vehicles R 2,581
Services - Treasury and Insurance 832 - Activities auxiliary to insurance and pension funding R 212
Total Revenue R 4,505 SR 0.57
137
Company Name Sharecode Transpaco Limited TPC 2005
Main Business Segments 3 Digit SIC Code Revenue in R million
Rigid plastic products 338 - Manufacture of plastic products R 72 Recycling 395 - Recycling R 62 Flexible plastic products 338 - Manufacture of plastic products R 112
Packaging - Paper 323 - Manufacture of paper and paper products R 86 Total Revenue R 332 SR 0.55 2001
Main Business Segments 3 Digit SIC Code Revenue in R million
Rigid plastic products 338 - Manufacture of plastic products R 67 Recycling 395 - Recycling R 42 Flexible plastic products 338 - Manufacture of plastic products R 84
Packaging - Paper 323 - Manufacture of paper and paper products R 57 Total Revenue R 250 SR 0.60
138
APPENDIX 4: PRICE / EARNINGS RATIOS Industrial Sector Companies
Focused OrganisationsJSE Sharecode 2001 2002 2003 2004 2005
Adcorp Holdings Limited ADR 7.20 13.90 6.80 5.80 13.90Astrapak Limited APK 5.00 7.90 6.30 5.00 11.00Bell Equipment Limited BEL 9.70 14.10 3.80 7.20 217.50Bowler Metcalf Limited BCF 7.50 9.10 9.10 8.00 8.50Cargo Carriers Limited CRG 7.70 3.30 20.40 3.90 7.60Ceramic Industries Limited CRM 13.60 9.40 8.90 13.50 13.20Control Instruments Group Limited CNL 4.40 6.60 4.40 -11.80 14.90Digicor Holdings Limited DGC 7.20 8.90 3.80 2.60 11.90Distribution and Warehousing Network Limited DAW 2.80 13.50 6.70 6.00 18.10EnviroServ Holdings Limited ENV 5.20 9.00 6.90 4.70 9.60Iliad Africa Limited ILA 2.80 8.50 5.10 3.60 11.10Pretoria Portland Cement PPC 11.00 12.80 10.60 10.20 16.80Primeserv Group Limited PMV 11.40 7.00 4.60 8.00 -1.90Value Group Limited VLE 3.30 7.40 5.30 7.70 9.70Venter Leisure and Commercial Trailers Limited VTL -0.20 38.50 -3.60 -1.70 39.10
6.57 11.33 6.61 4.85 26.73
Diversified OrganisationsJSE Sharecode 2001 2002 2003 2004 2005
AG Industries Limited AGI 12.80 13.90 6.70 8.80 13.50Allied Electronics Corporation Limited ATN 10.40 10.20 7.30 8.60 13.10Aveng Limited AEG 10.20 8.30 8.30 9.00 18.80Barloworld Limited BAW 13.80 9.30 10.50 10.60 11.80Bidvest Group Limited BVT 14.50 11.30 10.10 10.30 13.60Delta Electrical Industries Limited DEL 13.00 8.50 8.80 10.50 20.00Howden Africa Holdings Limited HWN 10.50 4.40 11.10 -28.20 12.50Hudaco Industries Limited HDC 5.90 6.70 5.50 5.60 10.20Imperial Holdings Limited IPL 13.80 9.40 8.80 8.10 12.10Jasco Electronic Holdings Limited JSC -0.70 3.20 1.70 2.90 14.30Murray & Roberts Holdings Limited MUR 11.90 7.20 8.80 7.20 9.80Nampak Limited NPK 12.00 9.10 8.20 12.30 11.70Reunert Limited RLO 10.60 12.00 7.10 9.00 13.40Super Group Limited SPG 9.50 8.30 7.70 10.90 9.30Transpaco Limited TPC 1.80 6.40 4.40 -14.60 7.90
10.00 8.55 7.67 4.73 12.80
P/E Ratio
P/E RatioAverage P/E Ratio
Average P/E Ratio
P / E Ratios
0.00
5.00
10.00
15.00
20.00
25.00
30.00
2001 2002 2003 2004 2005
Year
P/E
Rat
io
Focused Organisations Diversified Organisations
Source: Financial Mail (2001-2005)