Can intellectual capital affect a company's performance?

Bachelor Thesis, 2017

96 Pages, Grade: 1,0


I . A B S T R A C T
This thesis investigates the relationship between corporate intellectual ability
and performance. The link between intellectual capital and corporate
performance has been advocated for decades, however, empirical studies
failed to fully acknowledge this relationship. For the conduct of this thesis,
data has been collected for 1780 business years from companies of all
industries from 5 developed countries. The contribution of this thesis has
been the analysis of data from not only one country or certain industries, but
the analysis of an extensive dataset, without making separations of
industries, in order to obtain general results. By using data from developed
countries, the comparison of the results with former studies, which
predominantly used data from developing countries, was possible. For
measuring the intellectual ability, this thesis used the value added
intellectual coefficient (VAIC
) and its subdomains human capital
efficiency, structural capital efficiency and capital employed efficiency as
independent variables. Performance for this study, has been defined as
productivity (measured by ATO), profitability (measured by ROA) and market
valuation (measured by market to book value ratio MB) which constituted
the dependent variables. For conducting the analysis, the Person's moment
correlation and the Spearman's rho have been used. Furthermore, various
simple and multiple regression models have been conducted. In total, 3
simple regression models and 3 multiple regression models have been
investigated. As former studies were, the findings of this thesis are mixed.
As the results of the simple linear regression models show, VAIC
is a bad
predictor for profitability, productivity, and the market value of a company.
The results of the multiple regression models show, that human capital
efficiency is predominantly negative related to the dependent variables.

Throughout all models, structural capital efficiency and capital employed
efficiency have been the best predictors for the dependent variables. The
explanation power of the multiple regression models varies between 9.9%
and 25%.
Intellectual Capital

I. Abstract ... 2
II.Table of Contents ... 4
III. Abbreviations List ... 6
IV. List of Tables ... 6
V. List of Figures ... 8
Chapter 1: Introduction ... 11
Chapter 2: Literature Review ... 13
Introduction ... 13
The Knowledge Economy ... 13
Market Value vs. Book Value: ... 14
Definition of Intellectual Capital ... 16
Importance of IC Measurement ... 21
IC measurement Models ... 22
Value Added Intellectual Coefficient - VAIC
... 24
Review of Empirical Studies ... 30
Hypotheses Development ... 33
Chapter Summary ... 36
Chapter 3: Methodology and Methods... 37
Introduction ... 37
Research Philosophy ... 37
The Research Approach... 37
The Research Method ... 38
Design of the Study ... 38
Measurement of Variables ... 39
Regression Models ... 40

Sampling Process ... 41
Method of Data Collection ... 42
Data Analysis ... 42
Credibility and Limitations of the Applied Methods ... 43
Ethical Considerations ... 44
Chapter Summary ... 44
Chapter 4: Data Analysis and Discussion of Findings ... 45
Descriptive Statistics ... 45
Correlation Analysis ... 47
Regression Analysis ... 50
Regression Analysis ­ Model 1, Model 3 & Model 5 ... 51
Regression Analysis ­ Model 2, Model 4 & Model 6 ... 54
Chapter 5: Summary and Conclusions ... 60
VII. Appendices ... 62
Appendix A - Reflective Statement ... 62
Appendix B ­ Testing Assumptions Model 1 ... 62
Appendix C ­ Testing Assumptions Model 2 ... 64
Appendix D ­ Testing Assumptions Model 3 ... 66
Appendix E ­ Testing Assumptions Model 4 ... 68
Appendix F ­ Testing Assumptions Model 5 ... 70
Appendix G ­ Testing Assumptions Model 6 ... 72
Appendix H ­ Figures of Interest ... 74
Appendix I - Full Pearson Moment Correlation... 77
Appendix J - Full Spearman's Correlation ... 78
Appendix K ­ Table of Used Bloomberg Fields... 79
VII. Acknowledgements ... 80
VIII. References ... 81

IX. Bibliography ... 88
Intellectual capital
Human capital
Structural capital
Capital employed
Value added
Human capital efficiency
Structural capital efficiency
Capital employed efficiency
Value Added Intellectual Coefficient
Market to book value ratio
Return on assets
Asset turnover
Table 1. IC Measurement Models...23 - 24
Table 2. Dependent Variables...40

Table 3. Independent Variables...41
Table 4. Descriptive Statistics...47
Table 5. Pearson's Moment Correlations...48
Table 6. Test of Normality...49
Table 7. Spearman's Correlation Test...50
Table 8. Overview of Assumption Tests...52
Table 9. Results of Model 1, Model 3 and Model 5...53
Table 10. Results of Model 2, Model 4 and Model 6...55
Table 11. Summary of Hypotheses...56
Table B1. Auto-Correlation Test Model 1 ... ...............................................................64
Table B2. Breusch-Pagan Test of Heteroscedasticity...65
Table B3. White's Test of Heteroscedasticity...65
Table C1. Auto-Correlation Test Model 2...66.
Table C2. Breusch-Pagan Test of Heteroscedasticity Model 2...66
Table C3. White's Test of Heteroscedasticity Model 2...66
Table C4. Test of Multicollinearity...67
Table D1. Auto-Correlation Test Model 3...68
Table D2. Breusch-Pagan Test of Heteroscedasticity Model 3...69
Table D3. White's Test of Heteroscedasticity Model 3...69

Table E1. Auto-Correlation Test Model 4...70
Table E2. Breusch-Pagan Test of Heteroscedasticity Model 4...70
Table E3. White's Test of Heteroscedasticity Model 4...70
Table E4. Test of Multicollinearity...71
Table F1. Auto-Correlation Test Model 5...72
Table F2. Breusch-Pagan Test of Heteroscedasticity Model 5...72
Table F3. White's Test of Heteroscedasticity Model 5...72
Table G1. Auto-Correlation Test Model 6...74
Table G2. Breusch-Pagan Test of Heteroscedasticity Model 6...74
Table G3. White's Test of Heteroscedasticity Model 6... ...74
Table G4. Test of Multicollinearity...75
Table I1. Full Pearson Moment Correlation...78
Table J1. Full Spearman's Correlation...80
Table K1. Used Bloomberg Fields...81
Figure 1. The IC Balance Sheet...16
Figure 2. Human Capital...18

Figure 3. Structural Capital...19
Figure 4. Relational Capital... ................................................................................20
Figure 5. Conceptualization of Intellectual Capital... ...22
Figure 6. Intangible Assets Measuring Models...25
Figure 7. Conceptualization of VAIC
Figure 8. RBV and IC Perspective...35
Figure 9. The Research Scheme...35
Figure 10. Scatter Plot Model 1 VAIC
and MB...54
Figure 11. Scatter Plot Model 3 VAIC
and ROA...54
Figure 12. Scatter Plot Model 5 VAIC
and ATO...54
Figure 13. Scatter Plot Model 2...58
Figure 14. Scatter Plot Model 4...59
Figure 15. Scatter Plot Model 6...59
Figure B1. Test of Normality MB and Histogram...64
Figure D1. Test of Normality ROA and Histogram...68
Figure E1. Test of Normality ATO and Histogram...72
Figure H1. Scatter Plot Human Capital and MB...76
Figure H2. Scatter Plot Human Capital and ROA...76

Figure H3. Scatter Plot Human Capital and ATO...76
Figure H4. Scatter Plot Human Capital and Value Added...76
Figure H5. Scatter Plot Structural Capital and MB...77
Figure H6. Scatter Plot Structural Capital and ROA...77
Figure H7. Scatter Plot Structural Capital and ATO...77
Figure H8. Scatter Plot Structural Capital and Value Added...77
Figuer H9. Scatter Plot Capital Employed and MB...78
Figure H10. Scatter Plot Capital Employed and ROA...78
Figure H11. Scatter Plot Capital Employed and ATO...78
Figure H12. Scatter Plot Capital Employed and Value Added...79

1. Chapter 1: Introduction
During the last decades, our economy was undergoing a crucial change.
This change affects the production of goods and services as well as the
value of the goods and services (Pulic, 2008). It is the change of the balance
between the resources which are exploited by companies. It is the shift from
material resources to knowledge, the shift from quantity to quality - the shift
which manifests itself in the change of the way value is being created
(Edvinsson and Malone, 1997; Stewart, 2000; Pulic, 1998).
Caused by this environmental changes, research activities in the field of
intellectual capital (IC) emerged. It was advocated, that the new environment
now requires proper IC management in order to succeed in the market
(Edvinsson and Malone, 1997; Pulic, 1998). Since the end of the 90's, the
strategic importance and management of IC are well advocated. Several
authors associated corporate performance with an efficient management of
IC (Bontis, 1998; Edvinsson and Malone, 1997; Sveiby, 1997; Stewart,
2000). In fact, although the theory links intellectual capital and performance
very reasonable, empirical research has not been able yet to approve this
relationship doubtlessly (Chen et al, 2005; Gan and Saleh, 2008; Firer and
Williams, 2003). In particular, the effort to prove this relationship with
quantitative research has been observed around and after the 2
millennium. The aim of this dissertation is, therefore, to approve or reject
such a relationship between the efficient exploitation of IC (= the intellectual
ability of a company) and corporate performance by using quantitative
research methods. For conducting the quantitative methods, financial data
has been collected from public listed companies from 5 different countries of
all industries. Following Firer and Williams' (2003) appeal, it was tried to
collect an extensive dataset to obtain more reliable results. Therefore, data
was also collected from companies for the years 2014 and 2015.
The contribution of this dissertation is, that it is the first one to analyse data
from more than one country. All former studies, collected data from only one

country, and from selected industries. However, for the conduct of this
research, data from 5 countries was collected, in order to obtain general
results, not only for specific industries. Furthermore, the collected data
stems from developed economies, whilst former research was focused on
developing countries (Firer and Williams, 2003; Chen et al., 2005; Alipour,
2012; Mehrelian et al., 2012; Gan and Saleh, 2008; Shiu, 2006). Thus, a
comparison of the results from former studies and this dissertation will
provide further insight into the importance of IC in developed countries.
In order to reach the research aim, the dissertation is structured in additional
4 chapters. Chapter 2 will show the change in the economic environment. It
will show, how these changes manifest themselves. Furthermore, chapter 2
will outline the key concepts of IC. Firstly, intellectual capital and its
subdomains will be defined. Afterwards, it will be outlined how IC is
supposed to contribute to a company's success, and how IC can be
measured and improved. This chapter will also include the explanation, the
construction, and the critics of the independent variable VAIC
. Crucial
empirical studies will be reviewed, which finally lead to the development of
the hypotheses. Following this, chapter 3 will explain the methods, which
were applied in order to reject or support the hypotheses. It will provide
information about the sample, the used variables, and the statistical
methods. Chapter 4 is the main chapter of this dissertation, it will comprise
the empirical study which will reveal the truth about the relationship between
IC and corporate performance. For the analysis in chapter 4, various
regression analysis models and correlation models will be applied and the
discussion of the findings will be held. Finally, chapter 5 will summarise the
insights of this dissertation.

2. Chapter 2: Literature Review
To provide a better understanding of intellectual capital (IC), this chapter will
present the current state of theory and research regarding the concept of
intellectual capital. The literature review will outline the key concepts and
identify the key issues regarding IC. It involves the review of academic
contributions of the major researchers. Consequently, this literature review
aims to provide a firm theoretical foundation to grasp the concept of IC.
Furthermore, it will involve the development of the hypotheses and
simultaneously prepare the reader for the empirical study of this dissertation.
In the industrial age, mass production and physical creation defined the
value added. Increasing wealth could be achieved in 2 different ways. Either
one multiplied the amount of output quantity by increasing the material
resource input and by increasing the customers' demands or one tried to
increase the material productivity and save material costs. This, however, is
not possible anymore. Value creation is now based on knowledge, not on
quantity (Pulic, 1998; Pulic, 2004, Stewart, 2000). It can be said that whilst
a company in the past focused on cost aspects for the customers, the
common business approach now is to create value for which the customers
are willing to pay for (Pulic, 1998).
This change can be observed by investigating the consumer behaviour of
the 21st century. The value of goods is not anymore decreasing due to their
physical state but due to the old knowledge which is built into the goods.
Consumers tend to replace goods not because the old ones do not serve
their function anymore, but new products have more knowledge built in
(Pulic, 2008; Stewart, 2000). It is believed that the industrial age of economy
is now replaced by the knowledge-based economy (Pulic, 1998; Burton-
Jones, 1999; Stewart, 2000; Edvinsson and Malone, 1997).

Consequently, companies are forced to efficiently exploit their knowledge
base, to enlarge their knowledge base and to create knowledge which can
be transformed into value (goods and services) for the customers and thus,
leads to added value for the company. This is a necessity in order to ensure
sustainable competitive advantage and to justify the existence of the
company in the market (Stewart, 2000; Sveiby, 1997).
Considering this change of the market environment one major question
arises: what exactly is it, which enables certain companies to operate better
in the knowledge-based economy than others and how does it manifest
itself? Before answering this questions its origin needs to be found.
Several observations have revealed the increasing market-to-book value
(MBV) ratios. Whilst the average MBV ratio for the S&P 500 index
companies has been between 2.0 and 3.5 in the period of 1990 and 1995,
the average ratio increased to 3.5 to 7.5 during the period 1996-2000 (Lev,
2001). Indeed, this gap between the book values and the market values
would have a reason. Around the second millennium, several authors
(Stewart, 2000; Sveiby, 1997; Edvinsson and Malone, 1997) defined this gap
as the intellectual capital of a company which is perceived and valued by the
market. This diverging development has finally led to sharp criticism against
the accounting methods which were extant (Marzo, 2013). It was claimed
that the accounting methods which have "beautifully described the
operations of companies for a half millennium, [...] [are] now failing to keep
up with the revolution taking place in business" (Edvinsson and Malone,
1997 p. 1).
Arguably, these criticisms might be justified. Respective accounting
standards determine which assets or which resources can be balanced and
which not. However, in many cases, intellectual resources can be balanced
solely to a certain extent (Starovic et al., 2003). This leads to an official

balance sheet which can only partially reflect a company's operations as
shown in figure 1:
Debt / Equity
"Intellectual Capital"
Figure 1. The IC Balance Sheet. Adapted from Edvinsson and Malone (1997) p. 43.
Among the intellectual capital researchers, it is believed the above-illustrated
balance sheet leads to several problems (Sveiby, 1997; Edvinsson and
Malone, 1997). As Lev and Zarowin (1999) mention, a balance sheet which
does not contain a major part of the company's resources/capital, could not
be a useful tool in efficient financial decision making. Thus, the assertion is
that this so called "accounting fallacy" (Marzo, 2013) leads to inefficiency on
the capital markets causing wrong financial decisions (Pulic, 1998).
However, it shall be mentioned that the demand for new accounting
standards, which could close the gap, is also questioned (Marzo, 2013).
Marzo (2013) criticises that the intellectual capital researchers have missed
to take one assess one consideration. If the assumption is adopted that the
market value of a company is the true value of a firm, accounting standards
would be already good enough or completely irrelevant (Marzo, 2013). He
makes clear that if investors make their decisions and expectations solely
Exploited to
Exploited to

on traditional accounting figures, and if the market prices already represent
the true value of a firm, then current accounting methods fulfil their function
and must not be changed. He elaborates, that the other case, where the
assumption is that investors make their decisions and expectations based
on completely different information sources, and if the market prices still
represent the true value of a firm, then the revolution of the extant accounting
methods would be useless and a waste of energy, as they were not
considered anyway in decision making (Marzo, 2013).
To summarise, it can be said that intellectual capital has been perceived as
the residual between the market value and the book value of a company
(Edvinsson and Malone, 1997). However, this definition is not very detailed
and cannot explain intellectual capital completely as it raises some
questions. What happens if one company has a negative book value? Does
it have no intellectual capital at all, or how can one identify such a company's
intellectual capital? These questions are not properly addressed.
Additionally, it was outlined which problems accounting is said to face (Pulic,
1998; Edvinsson and Malone, 1997). However, from the financial
perspective, it is arguable if these problems are as crucial as they are being
advocated by Pulic (1998) and Edvinsson and Malone (1997) as Marzo
(2013) has doubted these requests from a very clear point of view.
After IC has been perceived as the residual between the market-value and
the book value of a firm (Edvinsson and Malone, 1997; Stewart, 2000), the
term intellectual capital needs to be defined more exactly. Marr and Schiuma
(2001) (as cited in Starovic et al., 2003) define IC as the "group of knowledge
assets that are attributed to an organisation and most significantly contribute
to an improved competitive position [...]". Among IC researchers, IC has
been split into 2 or 3 subdomains. Whilst some researchers (Bontis, 2000;
Stewart, 2000) have adopted a 3-subdomain approach (human capital,
structural capital, and relational capital), some others like Pulic (1998) and
Edvinsson and Malone (1997) have divided IC only in the human capital and

structural capital. In fact, those who have adopted the 2 subdomain
approach do not reject or even deny the 3rd subdomain and its strategic
importance, they merely advocate the view that relational capital is a part of
the structural capital. Although the definitions of human capital, structural
capital and relational capital may vary among researchers, following
definitions have been adopted for this dissertation.
2.4.1 Human Capital
Human capital (HC) can be defined as the knowledge, the experience, and
the skills which are possessed by the employees of a respective company.
These skills are leaving the organisation with the employees if they leave
(Starovic et al., 2003). The tacit knowledge which employees have can be
transformed into explicit knowledge which can then, where appropriate, be
used by the organisation (Bontis, 2002). Examples are the innovation
capacity, the previous work experience of employees, their teamwork
capability, the employee flexibility etcetera which can be summarised as can
be seen in figure 2.
Among others researched by
Kaplan and Norton (1996)
Figure 2. Human Capital. Own creation with adaptations from Moon and Kym (2006).
2.4.2 Structural Capital
In contrast to HC where knowledge leaves the company when employees
leave, knowledge which belongs to the organisation itself and stays there is
defined as structural capital (SC) (Bontis, 2002). The SC comprises, for
example, cultures and databases, systems, processes and procedures, the
Human Capital

organisational learning capability and organisational flexibility (Starovic et
al., 2003) as shown in figure 3. Some of this knowledge can be protected
legally as patents, copyrights, and trademarks etcetera but the majority
cannot (Starovic et al., 2003).
Among others researched by
Saint-Onge (1996)
Stewart (1994, 1997)
Figure 3. Structural Capital. Own creation with adaptations from Moon and Kym (2006).
Relational Capital
Relational capital (RC) comprises the relationship of a company with its
external environment (Bontis, 2000). This environment includes not only
customers but also supplier relationships and relationships to the
government or other associations which impact the company on a macro-
level. RC regards the perception of the company which external
stakeholders have. It is about the customer loyalty, the customer
satisfaction, and the negotiation of power in the competition (see figure 4).

Among others researched by
Knight (1999)
Figure 4. Relational Capital. Own creation with adaptations from Moon and Kym (2006).
Development of Human-, Structural-, and Relational Capital
According to Bontis (2002), it is more difficult to develop structural capital
than to develop human capital. Furthermore, it is more difficult to develop
relational capital than structural capital. He justifies this assertion and
elaborates that the more the capital is away from an organisations core, the
harder it will be to influence (improve) it. Consequently, he puts HC in the
core of a company, SC however, is more distant to the company's core. As
relationships depend on a 2
(or more) party, RC is hardly influenceable.
The conceptualization of intellectual capital includes also supporting drivers
for the development of the subdomains human-, structural-, and relational
capital. These are trust and culture (Bontis, 2002). For building inter- and
intra-organizational cooperation, trust between the parties is indispensable
for the success (Barney and Hansen, 1994). However, trust, mutual respect,
and compatible modes of behaviour cannot be decreed. Therefore, many
companies initiate a relationship by cooperating in less strategically central
areas in order to build these trusty relationships (Gulati, 1995). A belief that
is related to the likely outcomes of partnerships is defined as trust (Lazaric
and Lorenz, 1995). Barney (1986) recommends that companies with an
encouraging and supporting culture for cooperative innovations should try to
with external

understand what exactly their culture is about and how it leads to a
competitive advantage. Hall (1995) believes that that values which build the
core of cultures (Hofstede, 1991), are the key to any successful
organisational transformation. Consequently, building trust in relationships,
being a trusty company towards the stakeholders and having a culture which
encourages innovation cooperation helps to develop the subdomains and
ultimately a company's intellectual capital
2.4.5 Summary
As can be seen in figure 5, IC consists of its three subdomains human
capital, structural capital and relational capital. However, although
intellectual capital can be defined as the sum of its three subdomains, it is
crucial to appreciate all three individually, as well as together as the entire
intellectual capital basis (Bontis, 2002). Whilst the essence of human capital
is the individual intellect which employees have, the knowledge (as routines,
processes etcetera) which belongs to the organisation is structural capital.
The relational capital comprises the relationships which a company has with
its external stakeholders (Bontis, 2002). The development of these
subdomains is driven by the company's strategic management and
supported by trust and organisational culture (Bontis, 2002; Hall, 1995;
Barney, 1986).
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Can intellectual capital affect a company's performance?
Northumbria University
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Intellectual Capital, IC, Performance, HRM, Value driver, Value, Market Value, VAIC, VAICTM, Pulic, Capital, Resources, Resource, Human Resource, Resource Based View
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Ender Gülcan (Author), 2017, Can intellectual capital affect a company's performance?, Munich, GRIN Verlag,


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