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CHAPTER 2

THEORETICAL FRAMEWORK

2.1 Definition Intellectual Capital

2.1.1 Intangible Assets

“An intangible asset is an identifiable non-monetary asset without

physical substance.” (IAS, 2009). Intangible assets are contrast with tangible

assets. Intangible asset has no physical substance, similar as the IAS

definition, while in contrast, tangible asset has physical shape.

Intangible assets essentially have two core characteristics, which they

are lacking in physical existence and they are not considered as a financial

instruments (Kieso, Weygandt, and Warfield, 2008). Some other

characteristics that makes intangible assets different are intangibles may be

used simultaneously for multiple uses by multiple people, market for

intangibles are either thin or do not exist, and the value of intangibles is very

dependent on specific use and context (Chatzkel, 2003).

2.1.2 Intellectual Capital

There are lots of definitions in defining intellectual capital. Each

expert has their own way in defining it. In general, intellectual capital is

considered intangible. In Goh (2005) literature, it is written that Itami (1987)

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as the pioneer of intellectual capital defined intellectual capital as intangible

assets that are very worthwhile to a firm’s competitive power which includes

certain technology, customer information, brand name, reputation, and

corporate culture. However, as the time goes by, there are many debates

among fellow researcher, discussing about intellectual capital and had come

up with different perspective in defining intellectual capital. The following

statements are few definitions of intellectual capital from several experts:

• “The intellectual material – knowledge, information, intellectual

property, experience – that can be put to use to create wealth.” (Stewart,

1997)

• “Intellectual capital is therefore the pursuit of effective use of knowledge

as opposed to information” (Bontis, 1998). Bontis defines the knowledge

as finished product and information as the raw material.

• “Intellectual capital encompasses intangibles such as patents, intellectual

property rights, copyrights, and franchises.” (Brennan, 2001)

• Based on El-Bannany (2008) intellectual capital “covers the knowledge

and experience which skilled staff can use to gain a competitive

advantage for the company through applying some creative strategies.”

• From El-Bannany (2008) literature, Edvinsson and Malone (1997) stated

intellectual capital definition as “Information, knowledge applied to work

to create value.”

• Harrison and Sullivan (2000) explain on their literature, in 1995, there

was ICM (Intellectual Capital Management) Gathering which results

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defining intellectual capital as “knowledge that can be converted into

profit.”

• “Intellectual Capital can be defined as something which already exists in

a firm but cannot be seen on its balance sheet exactly, a competitive

advantage over the firm’s competitors, future values and includes all its

intangibles assets, the value of knowledge, information, intellectual

property and experience, a key factor influencing the future value of the

firm” (Yalama and Coskun, 2007).

Hence, we can conclude intellectual capital is considered as a

valuable knowledge that are used to create value and gain performance of

the company. In addition, it also may affect the company’s competitive

advantage in market and increase value of the company.

2.2 Intellectual Capital Components

According to Mouritsen (2009), intellectual capital consists of three concepts,

which are human, structural, and relational or customer capital.

Figure 2.1 Components of Intellectual Capital

Source: Mouritsen, 2009

Intellectual Capital

Human Capital Structural Capital Customer Capital

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2.2.1 Human Capital

Hudson define human capital as an individual level that combined

from four factors which includes genetic inheritance, education, experience,

and attitudes about life and business (Bontis, 1998).

Employees or human capital are very essential in keeping the

sustainability of company. It is also important because human capital is

counted as one of the sources to help development of the company, through

brainstorming then it will result in new findings, new innovation creativity,

and new strategy. However, Bontis (1998) stated that human capital is

practically useless with no supportive structure of an organization or

structural capital that can utilize and maintain human skills. However,

human capital has its own benefits. In Donkin (2002), he explained

Theodore Schultz, an economist who was awarded the Nobel Prize in

economic scien ces in 1970s, stated human capital can be invested through

education, training, and improves benefits that will lead to an improvement

in the quality and levels of production.

2.2.2 Structural Capital

Riahi-Belkaoui (2003) defines structural capital as all knowledge

which include data, inventions, publication, technologies, strategy and

culture, structures, systems, organizational routine and procedure, which be

included to the organization. All knowledge occurs to support human capital

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or employees, in order to improve intellectual performance of the company

and its overall performance. Edvinsson stated (cited in García-Álvarez, Ma

Mariz-Pérez, and Álvarez, 2011) that necessary to separate two basic

components of structural capital into organizational capital and technological

capital, and analyze them separately. It is because to become a better

organizational management, it cannot be measured or identify by

homogenous blocks of knowledge, so it needs to be separate.

“Organization capital is thus an agglomeration of technologies—

business practices, processes and designs, including incentive and

compensation systems—that enable some firms to consistently extract out of

a given level of resources a higher level of product and at lower cost than

other firms.” (Lev and Radhakrishnan, 2003).

Generally, organizational capital is all aspects that related to

decision-making process and any organizational aspects of the firm.

Furthermore, technological capital is combination of those intangibles that

are associated to the development of activities and functions that related to

the technical systems. In this twentieth century, technological becomes

critical needs of all the people and companies. It is one of determinants in

determining developments of market.

2.2.3 Customer Capital

Customer capital is about knowledge of maintaining relationship of

customer. Customer capital is also core of customer relations and the idea

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that customer capital is separate from human and structural capital indicates

its central importance to an organization’s worth (Bhartesh and

Bandyopadhyay, 2005). Customer capital is the most difficult and crucial

type of intellectual capital because it involves not only external parties but

also relates to the sustainable competitive advantage of companies.

2.3 Intellectual Capital Measurement

Intellectual capital has many ways to measured it. However, until now, there

is no standardizing measurement for intellectual capital. The purpose of measuring

intellectual capital is not to make an accurate representation or result of it, but to

make it ready for any management interference either inside or outside the firm

(Mouritsen, 2009). Measurement of intellectual capital produced data that turn out to

be knowledge and help the development of company.

In de Pablos (2003) literature, he explain five of many measurements exist to

measure intellectual capital, which are the Skandia Navigator, the Intellectual Assets

Monitor, Balanced Scorecard, Technology Broker, and Competence Strategic

Management Model. In his research it stated, although there are another famous

measurement, like Economic Value Added (EVA™), Market Value Added (MVA),

and Tobin’s Q Ratio that are not discussed because do not directly measure

intellectual capital in a way they were early responses to the fact that book

valuations of firm as supplied by accounting were lacking in valuable information.

Nevertheless, even though there are many measures for intellectual capital, this

literature using VAIC™ as measurement.

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This thesis use VAICTM as measurement because of several reasons. First,

this method is designed to provide information about the value creation efficiency of

tangible and intangible assets within a company during operation (Tan, Plowman,

and Hanckok, 2007). Then, it is measure using financial data and it also simple and

easy to calculate. It also can be employed to any size of organization (Goh, 2005).

Furthermore, the result easily understand by those who have very fundamental

knowledge of accounting information, and the results from this method can be used

to compare different entities of different sizes and industries (Joshi, Cahill, and

Sidhu, 2010).

2.3.1 Skandia Navigator

Since 1994, Scandinavian insurance company has been reporting

their intellectual capital information as a supplement in their annual report

(Bhartesh and Bandyopadhyay, 2005). Scandinavian insurance company has

been a pioneer in calculation of intellectual capital which includes measuring

and reporting intellectual capital.

Skandia navigator was made and designed to provide a balanced

picture of the financial and intellectual capital (de Pablos, 2005). This model

visualizes value components that make up intellectual capital as well as the

method of how to manage and report it. It is assumed that intellectual capital

show the difference between book and market value of the company (Berg,

2005).

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2.3.2 Intellectual Assets Monitor

Intellectual assets monitor or Sveiby’s intangible asset monitor,

represents a theory of stocks and flows which aim is to guide managers in

the utilization of intangible assets, the recognition and renewal of these

flows and stocks and the avoiding of it loss (de Pablos, 2003). In Berg

(2005), Sveiby stated that intellectual asset monitor focused on three types of

intangible assets which are external structure, internal structure, and

employee competence assets. In Berg (2005), it explain the three kinds of

intangible asset are one variable in measuring total market value, which

another factor is visible equity or book value. Intellectual assets measures a

firm’s ability at growth or renewal, efficiency, and stability across the three

forms of external, internal, and competence, that author mentioned above.

Thus, from Berg (2005) explained there does not appear to be any evidence

that using the intellectual asset monitor leads to better financial-economic

performance.

2.3.3 Balanced Scorecard

Balanced Scorecard is management system and strategic planning

that is used in any business. It was created by Robert Norton and David

Kaplan, in purpose to provide managers with a translation of their

organization’s mission and strategy into a comprehensive set of performance

measures which provides the framework for a strategic measurement and

management system.

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De Pablos (2003) explain that Balance Scorecard complements the

information provided by traditional tools with three additional view, which

are clients, internal and business processes, and learning and growth.

Balance Scorecard, in tracking financial results, it simultaneously monitors

progress to build capabilities and acquiring of intellectual capital or

intangible assets for future growth (Kaplan and Norton, 1996).

2.3.4 Technology Broker

Brooking as the founder of theory technological broker, states that

the market value of a firm consists of two elements, which are tangible and

intangible assets. This model also state that intellectual capital is formed by

four asset categories which are market assets, human assets, intellectual

property skills, and infrastructure assets (de Pablos, 2003). De Pablos also

argues in his writing that there is no empirical evidence that using this model

will lead to better economic performance.

2.3.5 Competence Strategic Management Model

Bueno in de Pablos (2003) defines intellectual capital as set of basic

distinctive competences of intangible nature that create and sustain the

competitive advantage. He said that basic distinctive competence has three

elements, which are attitudes, knowledge, and capacities. He proposes that

intellectual capital can be translated to the following formula:

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IC = HC + OC + TC + RC

Where IC = intellectual capital, HC = human capital, OC = organizational

capital, TC = technological capital, and RC = relational capital.

2.3.6 Value Added Intellectual Coefficient (VAIC™)

Although there is no standard measurement to measure intellectual

capital, VAIC™ is one way to measure it. VAIC™ found by Prof. Dr. Ante

Pulic who found VAIC™ in 1997. VAIC™ measured by the difference

between output and input. Pulic (2004) stated that basic definition of value

added for the company consists of output as total sales and in as cost of

bought-in materials components and services.

1. VA = OUT – IN

Value added also can be calculated in another way:

VA = OP + EC + D + A

Where OP is operating, EC as employee costs, D as depreciation and A as

amortization. This measurement shows the ability of company to create

value. To measure VAIC™, it needs to sum up two components of

intellectual capital as mentioned also in Pulic (2004) which are human and

structural capital. VAIC™ is specifically sum up of intellectual capital

efficiency coefficient and capital employed efficiency coefficient. Thus,

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after measuring value added of company, then measured human capital

efficiency as follows:

2. HCE = VA/HC

Where HCE is human capital efficiency coefficient, VA is value added, and

HC is human capital which is total salaries and wages for the company. Then

calculate structural capital by:

3. SC = VA-HC

Next step is measuring structural capital efficiency, which followed

by measuring intellectual capital efficiency coefficient, capital employed

efficiency coefficient, and compute VAIC™ by totalize both coefficient.

4. SCE = SC/VA

5. ICE = HCE + SCE

6. CEE = VA/CE

7. VAIC™ = ICE + CEE

Where SCE = structural capital efficiency coefficient; SC = structural

capital; VA = value added; ICE = intellectual capital efficiency coefficient;

HCE = human capital efficiency coefficient; CEE = capital employed

efficiency coefficient; CE = book value of the net assets of company;

VAIC™ = value added intellectual coefficient

.

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2.4 Stock Return, Profitability, Leverage, and Size

2.4.1 Stock return

Total stock return = (P1 – P0)

P0

Where, P0 = Initial Stock Price; P1 = Ending Stock Price

The computation of total stock return is the appreciation in the price,

and then divided by the original price of the stock. Due to its irregularity of

stock price, it affects fluctuate the price of stock return.

2.4.2 Profitability

Profitability ratio is one of financial metrics that are used to assess firm’s

ability to generate earnings as compared to relevant costs during a specific period

of time. The higher the profitability ratio indicates better company performance.

The measurement from profitability ratio that this research uses is ROA or return

on assets. Equation of ROA:

ROA = Net Income Total Assets

Liu and Thomas (1998) shown and add the evidence of findings that a

large proportion of variation in stock returns can be explained by variation in

earnings, dividends, and other fundamentals. Their findings explain that

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profitability have correlation with stock return. They also explain there are

positive relationship between profitability and stock return.

Tsay and Goo (2006) in their literature about relationship of

profitability and growth with stock market returns, founds that there is

relationship between profitability and stock returns tested positive significant.

It proves by comparing three methods of calculations and tests twelve ratio of

profitability ratio or index. It shows that financial information about

profitability gives useful information about the earning power of firms.

2.4.3 Leverage

Leverage commonly defines as the amount of debt used to finance a

firm’s assets. Highly leveraged is when a firm with significantly more debt

than equity. In this research, author used Market to Debt ratio as the

measurement of leverage that act as control variable.

Market to Debt Ratio = Total Liabilities Total Liabilities – Equity

According to Adami et al. (2010) there are few studies have examined

the effect of capital structure on stock returns by Dimitrov and Jain (2007) and

George and Hwang (2009). Capital structure is about the way a firm finances

its operations and growth by using different sources of funds. Overall, it is

combination of debt and equity. Afterwards, it shows that there is relationship

between the combination of debt and equity and stock return.

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Relationship between leverage and stock return discussed by Penaman

et al. (2007) literature that observe leverage component is negatively

associated with stock returns. They argue about the negative relation between

leverage and stock returns show how leverage should be priced and also taken

into account while evaluating risk in the asset pricing model. This study

suggests that leverage is priced by the market, results from the negative

relation between stock returns and leverage.

Muradoglu and Sivaprasad (2008) stated from their findings, there are

evidence that are make clear implications that leverage has an important role

to play in explaining stock returns. However, they found positive relationship

between leverage and stock returns, which in contrast with another research

that already discussed. Unlike others, Kose (2011) find something

interestingly that the significant positive relation between stock returns and

short-term leverage appear among large firms, while significant negative

relation between stock returns and long-term debt issuance exist among small

and medium sized firms, but not among large firms.

Higher leverage is systematically associated with higher stock returns

in banking (Yang and Tsatsaroni, 2012). The statement proves by their results

of findings. Other research by Cooper, Jackson, and Patterson (2003) who

using different methodologies and a cross-section of banks, found that

information about earnings, leverage, and non-interest income can predict a

cross-section of future bank stock returns. In literature about the impact of

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derivatives on the financial performance of depository institution, which using

cross-section time-series estimation show positive relationship between

leverage and volatility of stock returns (Brewer, Jackson, and Moser, 1996).

Baele, Vennet, and Landschoot (2005) use European data and find evidence of

cyclical variation in bank stock returns and shows bank that are better

capitalized, which is higher equity to loan ratio, and more diversified have

higher returns than poorly capitalized less diversified banks.

2.4.4 Size

Company size can be determined by number of employees, or sales

revenue, market value of equity or valuation of company. This research will

use natural log of total asset as the measurement of company size. It simply

computes by ln total assets. The bigger the natural log of total asset means the

bigger the company.

In Davis (2001) research, Basu (1983) findings showed that company

size affect the stock returns. The result was showed small firms tend to have

higher return than big one. This statement is also supported by other

researchers, Cui and Wu (2007), which found that there is negative relation

between stock returns and firm size that measured by the size of tradable

shares. The obtainable results of Ahmadpour (2007) also show negative

relation between size and stock return.

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2.5 Intellectual Capital and Stock Return

Hurwitz, Lines, Montgomery, and Schmidt (2002) research about

relationship between intangibles asset and stock return, and demonstrate that human

and organizational capital are fundamental to stock returns. However, it is not only

human and organizational capital that fundamental to stock returns, but also

highlights management policies that promote the successful engagement of human

and organization capital in executing strategies across all organizations. They also

explain correlation between stock return and intangible performance (see Figure

2.2).

The graph show that intangibles performances has the same form with

earnings line which explained above, has positive relationship with stock returns.

Over a 15-year period, this relationship has shown. Furthermore, cash flow and

earnings has no strong correlation which makes intangibles performance provides

more relevant information to investors. However, it needs further deep research to

know how strong this relationship, and if it is information were valuable as it

appears, it would create some measure of intangibles to help predict future changes

in market valuation.

In Ghosh and Wu (2007) finding, it explains that Lev and Sougiannis found

there is significant association between R&D capital and stock returns. They explain

intellectual capital is knowledge that person or company have, and will grow, then

can affect stock return a company. It means when the knowledge grow and establish

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improvement to company and results in gain in profit, then it affect stock return

company to also increase.

Tan, Plowman and Hancock (2007) also support Ghosh and Wu finding by

their result of research. Their research is about intellectual capital and financial

returns of companies, which used stock returns as one of their financial returns

measurement. The result of research proves that there is correlation between

intellectual capital and stock returns and has positive relationship between those two.

They also use VAICtm model and stock returns as measurement which also use in

this research.

Figure 2.2 Correlations to Stock Return

Source : Hurwitz (2002) cite from Lev (2001)

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Research conduct in Pakistan by Bharathi (2010), the research results show

that human capital efficiency is in higher than other component efficiency. This

literature shown that the investment in human capital yields a relatively higher return

than investment in others capital. Higher return which means profitability has

positive correlation with stock returns. Thus, it concludes that human capital affects

stock return the most. Saengchan (2008) who research about the role intellectual

capital in creating value in the banking industry, he discovers that strong correlation

between bank financial performance and efficiency of intellectual capital. He

explains from his research, banks have relatively higher human capital efficiency

than others.

2.6 Banking Industry

In essence, bank is financial institution and financial intermediary that

serve deposit and lending, and stand between households and the corporate

sector. The largest depository institution in terms of size is banks. This financial

intermediary is special because it helps to control the market then avoid market

failure. It is also special because its cost advantage over direct lending or

borrowing. Without bank or financial intermediary, there will be excess savings

could only be held as cash or invested in corporate securities. On the other hand,

banks also important in country’s economic development. Bank has roles in

serving provider payment mechanisms and accept savings from customers, then

lends it to those who need the funds. If those roles running well and proper, a

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country’s economy will increase. Otherwise, it can make a country’s economy

performance decrease or even in crisis.

Amadeo (2008) in his article said bank provides liquidity needed for

individual, families, and business to invest for the future. There are many types

of bank. The most familiar for all of the people are retail banking because retail

banking is type of bank that individual people usually face. Besides retail

banking, there are various type of it, such as commercial bank, community bank,

online banks, savings and loan, credit unions, shariah banking, and many more.

There is a special type of bank which is central banks. It has primary tools like

reserve requirement, discount window, regulator, prime interest rate, and funds

rate. Central bank in Indonesia is Bank Indonesia. Bank Indonesia as central

bank, carries a three-fold responsibility as monetary authority, regulatory, and

supervisory authority for the banking system and payment system. Bank

Indonesia most important task is not only to safeguard monetary stability, but

also financial system stability.

According to Mavridis (2004), banking sector offers an ideal area for the

research of intellectual capital because there are reliable data available, such as

financial report. He also said because the nature of banking sector is

“intellectually” intensive. Next reason is because the whole staff is intellectually

more homogeneous than in other economy sectors (Kubo and Saka, 2002). In

other sectors such as agricultural and industrial, physical capital is more

important rather than intellectual capital, but in other sectors like banking which

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relies mainly on knowledge, intellectual capital is more important rather than

physical capital in the process of wealth creation.

Banking sector is one of the sectors that utilizing intellectual capital

intensively (Saengchan, 2008). Several past studies have been research about

intellectual capital in banking industry. In 2005, Goh research about intellectual

capital performance of commercial banks in Malaysia using VAICTM, which

basically rank intellectual capital performance of banks in Malaysia. He found as

a whole, banks have relatively higher human capital efficiency than others

component of intellectual capital. On the other hand, there is a study conduct by

El Bannany (2008) who research about determinants of intellectual capital

performance in UK banking sector. The result of his literature illustrates bank

that invest more in information technology tend to have lower human capital

performance, which means there is negative impact of investment in information

technology systems on the motivations of human capital to perform better. The

other test shows bank’s relative efficiency, bank profitability, and bank risk have

positive impact and determinants of intellectual capital.

Yalama and Coskun (2007) also research for banking industry in Istanbul.

Their research outcomes result in intellectual capital more important than

physical capital for banks. It is also supported by a study that shows firms’ with

higher intellectual capital and less in the usage of their physical capital have

better performing in Best Practice Index (BPI) as proves in Japanese banking

sector studies (Mavridis, 2004). However, even though intellectual capital proves

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more important than physical capital for banks, there is predictive analysis that

physical capital has positive relationship with value added, especially with

human or intellectual capital (Mavridis and Kyrmigzolou, 2005).

In Saengchan (2008) research about the role of intellectual capital in

creating value in the banking industry, he found that strong association between

the efficiency of intellectual capital and bank financial performance. Ting and

Lean (2009) conduct study to find the relationship between intellectual capital

and financial performance with Return on Assets (ROA) as dependent variable.

Their study reflects the relationship between intellectual capital and financial

performance is positive. All the component of VAICTM measurement; HCE and

CEE, shows positive relationship with that profitability ratio while SCE or

structural capital efficiency, show negative relationship. Najibullah (2005) as

cited by Ting and Lean (2009), has research about association between banks’

market value and intellectual capital in Bangladesh, and found positive

relationship correlation between those two variables.

Hence, all literature shows that intellectual capital plays important role,

and has a positive and strong relationship with the firm’s performance, especially

in banking sector. It proves that intellectual capital can be measured in banking

industry, as proved by previous literature and it seems to be a more important

factor than physical for banks and also has strong relationship with performance

of the bank (Mavridis and Kyrmizoglou, 2005; Yalama and Coskun, 2007;

Saengchan, 2008).