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The Intellectual Scorecard in the Egyptian Travel & Leisure
Companies
Mohamed Samy El Deeb, PhD, Modern Sciences and Arts University, Egypt
moh.eldeeb2@hotmail.com, msamy@msa.eun.eg
Abstract:
Due to the expansion of the knowledge and information technology economy, a new thought had
been raised which is the strategic management accounting techniques for dealing with the
intellectual capital. Intellectual capital is one of the most shadowy issues to be raised in relation to
accounting for intangible assets. It is an innovative insight, among accountants and consultants
where there is no settlement with respect to the exact way of measuring or managing intellectual
capital in a firm. The balance scorecard is also, one of the most influential strategic management
accounting techniques used for performance measurement of a business. The research propose the
combination of both intellectual capital concept (IC) and the balanced scorecard technique (BSC)
to deal with measuring, reporting and strategically managing the intellectual capital in the Travel
& Leisure businesses listed in the Egyptian stock exchange market.
The empirical study of the research based on exploratory study by analyzing secondary data for 13
Travel & Leisure firms annual reports listed in EGX 30 in the Egyptian exchange market. This is
to proof the relation between existing of the intellectual capital (measured through difference
between the market value and the book value of the company), IC disclosure in annual reports and
the performance of the companies (measured through ROA and ROE). Furthermore, a
questionnaire distributed to test the usefulness of ISC (Intellectual Scorecard) proposed model on
enhancing performance the Travel & Leisure businesses listed in EGX30. The findings shed light
on rationality of the intellectual scorecard model constructs in the Egyptian travel and leisure
companies.
Purpose:
Egypt, as a country emerged in the knowledge economy, has a large number of companies that are
knowledge-based enterprises, hence, the value creation of the firms stem from this resource.
However, more research and evidence is needed concerning exactly what and how IC is measured
and managed in Egyptian setting. To improve the recognition, measurement, reporting and
managing of the intellectual capital in the Travel & Leisure businesses working in Egypt, this
research evaluate the use of intellectual scorecard proposed model within best practice Travel &
Leisure businesses listed in the EGX30 index in the Egyptian stock exchange market. The main
aim of the research is to fill the gap in the literature regarding the treatment of intellectual capital
in the Egyptian travel and leisure companies and how it can be strategically managed to enhance
the financial performance of this sector.
Research limitations:
The results of the research based on analyzing secondary data (annual reports of selected
companies) and on a limited survey that were disseminated on the same firms to validate the
proposed model. The research is limited to 13 Travel & Leisure firms managers listed in EGX30
and it is accepted that additional investigation is necessary to create the precise nature of the causal
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connections among intellectual scorecard model measures and intellectual capital constructs and
also, to increase understandings into practice elsewhere.
Key Words:
Intellectual capital • Balanced Scorecard • Intellectual scorecard • Travel and leisure companies •
Performance Measurement
Research Problem:
Strategic management accounting is one of the most crucial and up to date topic in the accounting
research areas nowadays. The integration of the financial and non-financial measures started to be
with urgency since the emergence of the BSC and the additional strategic management accounting
approaches. Moreover, financial measures alone are insufficient for strategically managing the
intellectual capital in the Travel & Leisure sector. This sector that focuses on intangible products
to deliver reliable product (Service). Due to lack of empirical research that examines IC measuring,
managing and reporting within Egyptian firms, with special emphasis on travel and leisure firms,
this study will try to close this gap. Therefore, the integration between the intellectual capital and
the balance scorecard has been suggested as the most suitable technique to deal with this
problematic situation.
Research Objectives:
To improve the performance of the company through the application of the intellectual
scorecard measures (Financial perspective/ shareholder capital value).
To improve the performance of the company through the application of intellectual
scorecard measures (Internal business process perspective/ Structural Capital value)
To improve the performance of the company through the application of intellectual
scorecard measures (Learning and growth perspective/ Human capital value)
To improve the performance of the company through the application of intellectual
scorecard measures (Customer perspective/ Customer Capital value)
To enhance the performance of the Travel & Leisure companies in Egypt through applying
the intellectual scorecard model.
Hypotheses:
H1: There is a positive relation between intellectual scorecard measures (Financial perspective/
shareholder capital value) and the performance of the company (ROA and ROE).
H2: There is a positive relation between intellectual scorecard measures (Internal business process
perspective/ Structural Capital) and the performance of the company (ROA and ROE).
H3: There is a positive relation between intellectual scorecard measures (Learning and growth
perspective/ Human capital) and the performance of the company (ROA and ROE).
H4: There is a positive relation between intellectual scorecard measures (Customer perspective/
Customer Capital) and the performance of the company (ROA and ROE).
H5: The proposed model is valid for application in the Egyptian Travel & Leisure companies.
Introduction:
In the current economy, which known as the knowledge-based economy due to the critical role
played by this knowledge factors like external factors (related to the competition’s modalities) and
internal factors (related to the resources’ composition) has caused a modification in value creation
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models. The main source is no longer based on the production of material goods, but on the creation,
acquisition and managing of intangibles. Since intangibles have become the main value drivers for
the 21st century firms, the problem measuring intellectual capital (IC) performance became an
essential issue in measuring firm’s performance (Eustace, 2003).
In numerous businesses, intellectual capital has been considered as the greatest valued asset. Such
expansion of intangible issues in the business led to an increasing number of researchers to do
additional dynamic search for more and more efficient approaches for measurement, recognition
and keeping record of this types of assets within the traditional system of accounting. It is vital, to
find out an appropriate model that will contribute in raising the efficiency of the company by taking
into consideration the attributes of the intangible assets. In real business, it is hard to plan, apply
and control these procedures, the main goal is to increase the efficiency of a resource, and the value
of which is problematic to be measured, or to be exactly considered within the normal assets of the
business (Marr, B., et al., 2003).
Several models were been adopted to measure intellectual capital. The mainstream of models
created so far have not recognized the relation between intellectual components and organizational
intellectual capital performance. Limited models have been established that connection to enable
management to screen this relation, or have recognized directories other than the traditional
accounting system measures. The Intellectual Scorecard is one of those models that succeeded in
this trend. It tried to remedy these issues by measuring and reporting the intangibles through using
the traditional accounting reporting system and non- traditional accounting measures. Some point
of views was to classify each intellectual capital item as an intellectual revenue and intellectual
expenses that having an impact on the income of the business, or as an intellectual assets and
intellectual liabilities having an influence on the balance sheet (Arthur Andersen., 1998). Some
other models used ratios to screen operational and strategic performance of the intellectual capital
then these ratios to be tailored within the perspectives of the balance scorecard. The intellectual
scorecard model anticipates making the intellectual capital characteristics measureable in a
quantitative form that can be understandable within the accounting context (Bontis et al., 1999).
The main aim of this study is to scrutinize the role of dual new strategic accounting instruments,
the Intellectual Capital (IC) and the Balanced Scorecard (BSC) to measure, manage and report the
intellectual capital in the annual reports of the travel and leisure companies in Egypt. In consistently
with Bukh et al., (2005), the researcher began from the idea that BSC and IC are not substitute, but
harmonizing (complementary) tools in measuring, managing intangibles, addressing the desires of
companies to measure, manage and report intangibles. The researcher selected the companies under
the sector of travel and leisure companies to test the research hypotheses, since it makes sense of
using this model in the travel and leisure sector due to its special nature. The influence of the study
to the IC literature is to spread the results of the Bukh et al., (2003) study, in the Egyptian market
through verifying the hypotheses of the research.( Bukh et al., 2003)
Through the transformation of the global economy, established management and reporting systems
increasingly lose their relevance because they are unable to provide executives with information
essential for managing knowledge-based processes and intangible resources. This is the case in the
financial accounting system, which has always focused on physical and financial assets (the balance
sheet) as well as transactions (the income statement) and has not been able, so far to systematically
trace the transactions of intangibles within the company. Furthermore, the financial accounting
system hardly delivers information for future-oriented strategic management decisions on
knowledge-based resources and intangible investments. (Leitner, and Karl-Heinz, 2002)
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These characteristics of knowledge and intangibles keep causing severe difficulties for developing
and running a management and accounting model. The greatest challenge facing the accounting
profession today is to understand the huge gap between companies’ book value represented in
balance sheets and market value, which is one of the methods used in evaluating intellectual capital.
This gap represents the impeded value of the company and constitute its intellectual capital
represented by many factors like patents, competitive advantage, trade marks, , customer
relationships, Research & Development, human capital, etc. (Tariq H. Ismail, 2008)
According to the accompanied previous studies for measuring and managing intellectual capital, it
appears that values of intangible properties is essential in a business's strategy application.
However, it should be pointed out that in spite of undertaken efforts, still there is no a definite
pointer which would fully reflect the value of the most valuable resource in today’s business, which
is intellectual capital. (Bontis, N. , 2001)
Suggestions of the study are for business’s manager, to have the right tools at their disposal to
manage intangibles. The study emphasizes the subject of intellectual capital due to the fact that this
is a comparatively original concept, between accountants, economists and consultants of
management. There is no uniformity with respect to the spirit and the role of this investment in a
business. It consequently contributes to the creation of differences in insight and measurement of
its efficiency of the travel and leisure firms. The research offers the well-known models and
approaches for evaluating the intellectual capital. The consideration was concentrated on synthetic
and analytical approaches, which are most often functional when calculating effectiveness of
company's intellectual capital. Intellectual capital, includes human capital, intellectual property,
intellectual assets, or knowledge resources, in the age of knowledge-based economy it shows a vital
part virtually in each business. Such a components leads to a credible reflection on the firms value
and on enhancing the competency of a business. Obviously, it is tough to measure, manage and
control intangibles, which has not been completely reflected in the construction of properties of a
business.
Balanced Scorecard
The Balanced Scorecard (BSC) is a strategic management notion shaped by Robert Kaplan and
David Norton, and it customs performance measures to path strategy application on short and long
period. It was exposed to be effective in commercial businesses. Furthermore, since financial
indicators only cannot always arrest the significant info, it is significant to practice the Balanced
Scorecard particularly in operations where profit is the crucial goal. The BSC take into
consideration other features of performance evaluation, as it will be offered underneath. (Kaplan
and Norton,1992)
Balanced Scorecards, once established as strategic planning and management systems, was
intended to help line up an organization behind a joint image of achievement, and develop persons
occupied on the right things and concentrating on outcomes. A scorecard is more than a way of
possession score. It is a structure, containing of people, strategy, processes, and technology; it offers
a foundation for well aligning strategic objectives with properties. (Kaplan and Norton, 1996,
2001)
Intellectual Capital
Intellectual capital is original concept, consequently in the previous studies there is no uniformity
in the explanation of this item. The concept is sometimes recognized with human capital, human
resources, intellectual property, intellectual assets or knowledge resources. (Mikuła, et al 2002)
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The creation of the expression itself is not explicit. According to S. Kasiewicz, Rogowski &
Kicińska, (2006) basics of the intellectual capital concept can be found in J. Rea's publication from
1834 entitled "The Sociological Theory of Capital". In addition, other reseachers inspected the
impact of variety of properties possessed by a business on rivalry and earnings, referred to the idea
of intellectual capital. (Zambon, 2003)
The definition and classification of intangibles (IC) is still an open enquiry (Zambon, 2003). The
definition accepted in this paper considers IC as a dynamic system of intangible resources and
activities, at the basis of the organization’s sustainable competitive advantage. All of the major
players in the IC field share the idea that intellectual capital, from a qualitative point of view, can
be separated into three categories: structural (organizational) capital, human capital and relational
capital; even if the labels utilized are different, the content of categories is more or less quite similar.
Briefly, Organizational capital is constituted by structured knowledge possessed by firm and
shareable (database, procedures etc.). Human capital consists in knowledge, capabilities,
competencies and skills possessed by firm workers. Relational capital is constituted by the whole
of relations between firms and its main stakeholders (Bontis et al., 1999).
When examining many meanings of intellectual capital, dual elementary guidelines of its
clarification may be distinguished. It was expected that intellectual capital is recognized not only
with the human factor, but actually, it is stretched with systems, procedures and structures which
support looking for optimal intellectual efficiency and relationships of the co-workers system.
(Bontis, N. 2002)
According to many authors, intellectual capital to be defines as the totality of "islands of
knowledge" remaining in a business, and it is the duty of managers to proficiently organize
knowledge of employees for the persistence of application of the strategy conducted by the
business. (Mikuła, et al 2002).
Intellectual capital to be described in somewhat wider way as "intellectual material" containing of
knowledge and experience, which may be used for generating prosperity, but also draws courtesy
to intellectual property (Jarugowa & Fijałkowska, 2002). It is value pointing out that intellectual
property is officially distinct as the possessions of patents, trademarks and exclusive rights. Other
researchers stress that intellectual capital is not only the stimulus of the human attention, but also
a brand, trademarks and assets reserved in ancient values, which in the course of time have
transformed into something of extensive value (Edvinsson & Malone, 2001).
The mainstream of experts contribute to even a broader definition of intellectual capital. An
example may be J. Fitz-enz, (2001) who entitlements that intellectual capital is:
"Intellectual property of the company and a complicated strand of processes and culture,
connected with a network of various kinds of relations and human capital. On the other
hand, he calls firm's ability to obtain values from the owned intellectual capital the
intellectual potential".
This clarification, apart from aptitude of personnel and intellectual property, also reflects
relationships among the employed, their situation and structure in which they function.
Edvinsson and Malone, (2001) understand intellectual capital in the subsequent way:
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"it is studying the roots of company's value, measurement of hidden factors that are the
grounds for a visible company, buildings and products".
These features contain human capital and structural capital. Rendering to it, intellectual capital may
contain four constituents: market assets, assets associated with the human factor, assets concerning
infrastructure, and intellectual value. K. E. Sveiby has an exciting method to categorize intellectual
capital with intangible resources based on a model known as the Intangible Assets Monitor created
by himself. (Sveiby,1997) He distinguishes three concepts of intellectual capital: individual
competencies as well as internal and external structure of an organization (Jarugowa &
Fijałkowska, 2002).
It may be determined that regardless of numerous clarifications and arrangements of intellectual
capital, their mutual denominator are aspects grounded on broadly understood knowledge. This
knowledge is often notable at different levels, which are interrelated and jointly affect creation of
values of intangible resources of an organization (Bukowicz & Williams, 2000).
Human capital:
It is the resource of an organization considered by its staff number however it is connected to
education, knowledge, training, experience of employees, and behavior towards life and business,
skills, qualities and values. Human capital is a multi-aspect concept including tangible and
intangible perspectives which considered a one component of the productive process, human
capital refer to the explicit knowledge which individuals have, and, in addition, their ability to
obtain it, which is beneficial for the organization mission and incorporates values and attitude,
aptitudes and skill. Human capital is vital for any firm, as a source of innovativeness, development
innovation, and strategic renewal. (Bontis et al., 1999).
Employees’ innovation empowers them to utilize their insight and abilities flexibly and to be
creative constantly. Similarly, elaborated intellectual alertness, which allow employees to alter
practices and consider creative solution to problems. (Chen, Jet al. 2004)
Relational capital:
Relational capital is illustrated as connections presented between either staff and external economic
parties, or connections presented among staff and other departments within the organization. Come
up with the term customer capital as a part of relational capital. In addition, concept of market
assets combines several factors included in the perspective of relational capital most related to the
travel and leisure industry. A substantial part of the travel and leisure’s value is intangible and
depend on the goodwill and the brand name. (Brooking, A. 1996)
Structural capital:
Structural capital includes all the non-human aspects of learning in firms, such as process manuals
, databases, strategies, routines, organizational charts ,legal parameters, research and development
and anything whose value to the company is greater than its tangible value . (Bontis et al., 1999).
The structural capital is in charge of the organization's value making and replenishment techniques.
The linkage between human capital, innovation and knowledge management is essential.
Knowledge management is significant for travel and leisure firms to cope with expanding market
changes . (Cooper, C. 2006)
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IC reporting:
Intellectual capital reporting becomes a necessity for knowledge-based firms because of the criteria
of intangible assets, which are knowledge-based and fundamentally different from tangible assets.
Firms includes financial and non-financial information in the annual reports, although the latter is
currently dominating. The integration of new approaches to the established accounting,
management, and reporting systems leads to more enhancement disclosure in the annual reports.(
M. Paloma and E Susana., 2000)
Intellectual capital disclosure (Reporting) is a needed instrument in the knowledge based firms,
which serves as a management and communication instrument to deliver information for investors
to aid them in taking the useful decisions and to enable the managers of the firms to wisely use the
increasingly important intangible resources, such as human capital, R&D, software, and customer
relations. (Bukh, Per Nikolaj et al, 2005).
Many criticisms are to be directed to the current accounting and financial reporting practices that
they fail to measure, manage and disclose the most significant building blocks of business; like the
intellectual capital. As a result, unreliable and un-useful decisions probably to be taken as the
financial statements fail to communicate such information to the management and investors
(AICPA, 1994; Starovic and Marr, 2003).
Intellectual capital reporting and disclosure represents an approach that can be used to measure
intangible assets and describe the results of a company's knowledge-based activities. Intellectual
capital reporting emerged in the nineties, primarily in the Scandinavian countries, when companies
started to implement and publish intellectual capital Reports, often as a supplement to the annual
report. (Sirinuch Nimtrakoon , 2015)
There is increasing confirmations that the value creation drivers of a firm in modern competitive
markets is in a firm’s intangibles rather than in its physical and financial capital. Many studies of
listed firms showed a significant difference between the book value of the firm and its market value.
Ballow et al. 2004 indicated that, for knowledge based firms, physical and financial assets and
resources typically represent between fifteen and twenty-five percent of company value in the last
five years. The same study showed that, across the majority of the United States listed firms,
expectations of future growth value compared to current earnings represent at least sixty percent of
current firm value. This can lead as to state that disclosing and reporting intangible assets and
especially intellectual capital is a way for firms to identify, measure, and manage intangible sources
of value creation and communicate them both internally and externally. (Xuelian Liu , et al , 2014)
Measuring and reporting Intellectual Capital within the Accounting Context
Intellectual capital assessment and management is not probable without measuring its value. This
measurement is a problematic mission because Intellectual capital of a business is severely
connected to the form of action, occupational situation, history and culture of a given business.
(April, K, et al. 2003)
One very important question is how to measure the unmeasurable Intellectual capital taking into
consideration its constructing blocks, fundamentals, variables and indicators. Researches first tried
to agree on an agreement around the constructing blocks of intellectual capital. There appears to be
some settlement that human capital, relational capital and structural capital are the corner stones of
the intellectual capital components. However, talking about relational capital and ideas appear to
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become a slight more confused: customer capital is surely one of the features here while in some
periodicals this arrangement encompasses alliance and partner capital. In trying to arrest the entire
image, social capital and even cultural capital may be added to the list. However, once the main
blocks are distinct, experts slope one pace further into the depths of intellectual capital secrets
looking to sum up all the fundamentals that are portion of the inventory of each main scope.
(Horsten M., et al. 2008)
Some managers who are provoked with the (sales) mention it from intellectual capital accounting
promoters are lured into starting an application, which is often called: the placing together of an
Intellectual Capital Balance Sheet. All of these schemes started to list the elements of the
intellectual capital indicators In numerous cases, these Intellectual Capital Balance Sheets are then
used for internal and/or external communications, i.e. to show the innovative spirit of management.
This approach had faced some problems, first the common denominator for the values of the
intellectual balance sheet indicators, second the understandability of the numbers included in the
reports of performance using these indicators. (Liebowitz, J.,& Suen, Ch. 2000)
Preparing a balance sheet report in a meaningful format is very easy but a great debates about
including the intellectual capital resources, which needs ordering these properties in a comparable
manner to the financial assets, on a conservative balance sheet. Financial assets are financed with
equity (shareholders' capital) and external funds (banks, financial institutions, suppliers, creditors,
etc.). The 'financing' of intellectual capital properties may be approached in precisely the same way.
These assets either are possessed by the business (explicit) or are 'borrowed' by the business (tacit).
Understanding this clues to the structure of the liabilities side of the Intellectual Capital Balance
Sheet (April, K, et al. 2003).
In order to assess the existence of intellectual capital, researchers have used three broad indicators
at organizational level. These indicators are derived from the audited financial statements of a firm
and are independent of the definition of intellectual capital of a firm. There are three major
indicators to measure net intangible assets at a firm level and they are market to net book value,
Tobin’s q, calculated intangible value (CIV). (Stewart, 1997).
Sveiby (1997) discussed the construction of Intangible Assets Monitor TM in the mid 80s. The
Intangible Assets Monitor TM designates the change in intellectual assets through constructing
ratios in relation to the fair value or calculating the change in the fair value of the firm. This is
because fair value characterizes the intellectual capital of the firm, and change in fair value
represents the change of intellectual capital for the period. The individual ratios therefore indicate
their positive or negative influence towards intellectual capital of the firm. It is crucial to decide
the level of increased focus the firm has on given intellectual capital category or categories. For
example, a trading firm will have more focus on external capital and a R&D firm is likely to have
more focus on human capital. This is why Firms must classify the strategic and operational goals
of the firm and its key performance indicators in order to construct ratios to support its strategic
and operational goals so that they can be combined into key performance indicators.
To sum up, methods for measuring IC can be categorized in methods focused on the financial side
of measurement and the monetary value of intangible assets and “scorecard” methods that look for
indicators able to measure intangible resources and activities (Sveiby, 2004). To the category of
scorecard methods belong methods measuring multiple aspects of firm’s performance, including
intangibles, such as the Balanced Scorecard (BSC) and methods develop ad hoc to measure
intangibles through a system of IC indicators revealed in an IC report (Chiucchi, 2004).
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Intellectual capital measures, in this paper, depend on publicly disclosed information, where,
comparisons of book values to market values of the sample of firms collected. Data collection for
this study is mainly depending on manual and electronic survey of the public information disclosed
by the CASE 30 companies. Book values were undertaken from annual report of each listed
company as of December 31, 2014. Market values in some cases were not available as the company
is recently listed; hence, market values at the nearest available date were used.
IC and firms Performance
Seleim et al. (2007) tested empirically a variety of hypotheses related to human capital and
organizational performance within software companies in Egypt. The results provided evidence
that certain types of human capital indicators show a positive statistically significant relationship
with company performance.
Odette (2007) used a case study examined the nature of human capital in the gaming industry in
Egypt and replicates the work of Bontis (2002) to measure the effectiveness of human capital
management on the firms performance. The results of study revealed the importance of intellectual
capital and knowledge management in enhancing the performance of the firms. However,
management does play a role in structural capital and value alignment, and this affects knowledge
management activities such as knowledge sharing and education insignificantly affects the value
of human capital; and did not significantly correlate with relational capital. In addition, the results
reveal that the gaming industry's ROI was the highest compared to benchmark industries (Odette,
2007).
While many studies are able to comment on the lack of cohesive IC, they provide only limited
explanation for their observations. One main explanation involves the degree to which users of
annual reports need IC information for their decision-making purposes, which affect the firms
performance. Indeed, very few studies have been conducted to examine the need of decision makers
for IC information. Among these studies: Lev (2001), Johanson (2003), Cuganesan et al. (2005)
and Petty et al. (2008).
According to Cuganesan et al. (2005); a survey is conducted on a sample of 238 financial analysts
of professional financial bodies in Hong Kong to offer an empirical evidence of how a group of
financial professionals uses IC information and the value that this group imputes to IC disclosure.
The results concluded that there is considerable support for the mandated disclosure of IC with
87% of respondents agreeing that the accounting profession or the regulatory authorities may make
listed firms provide more information on their intellectual capital. In addition, a majority of
respondents (68%) claimed to be in a good or very good position to obtain information on
intellectual capital of listed firms through private information contracts.
Intellectual capital and innovation in this setting let firms managers present new services
that enhance quality, accordingly both meeting the altering requirements of potential
clients and increasing their market share, sales and profits. This is especially critical for the
travel and leisure firms in order sustain their competitive edge by stressing on
differentiation strategies presenting innovative services, and offering quality standards that
meet the expectations of their customers (Tseng, C., et al. 2008).
A powerful intellectual capital management model embodies organizational procedures
and processes that request a synergistic connection of data and information-processing
capacity of information technologies, and the creative and innovative capacity of people.
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A tremendous variety of intellectual capital models are present, elaborating on the tangible
and intangible aspects of intellectual capital management (Malhotra, Y., 2003).
The areas of knowledge management (KM) and intellectual capital (IC) are focused around
implicit assumption that superior business performance is the reason of management of the
knowledge in staff heads. What has been carried out typically is associated to specific
pieces of IC (e.g. human capital) and whether they influences performance (Prahalad, C.
K. and Gary Hamel, 1990).
Managers try to find a consistent approach to help travel and leisure firms’ utilization of
intellectual capital and, significantly, this approach is intended to empower firms managers
to be aware and responsible for the whole process. This approach will be concerned on
meeting organizations different needs, developing an enterprise's strategy, as well as
executing that strategy, as an ongoing process of building collaborative decisions and to
support the intellectual capital approach of reinforcing the firms performance (Malhotra,
Y., 2003).
IC Scorecard Measurement Systems
The Balanced Scorecard (BSC) belong to the multidimensional firm’s performance models
(Bititci et al., 1997), developed to overwhelmed the limits of the traditional, mono-
dimensional performance measurement models, concentrated only on the
accounting/financial side of firm’s performance. Briefly, in the BSC four perspectives are
considered: financial, customer, processes and learning and growth perspective. The
financial perspective identifies long-term financial results. The customer perspective
allows managers to ask themselves on what factors client consider important and which
actions the firm have to implement to reach customer satisfaction. The processes
perspective is an internal one, which allows managers to evaluate which factors have a
deep impact on client’s valuation, such as production and delivery times, productivity,
flexibility, etc. The learning and growth perspective concurs to the distinctive
competencies that maintain and increase the firm’s competitiveness. BSC tool had great
evolution with time, from a performance measurement system (Kaplan and Norton, 1992),
to a strategic performance management system (Kaplan and Norton, 1996, 2001), to a
system focused on transformation on intangible assets intangible results (Kaplan and
Norton, 2004).
The research focuses on BSC in relation with the measurement of intangibles and on its
role in measuring them. Until 2004, in fact, researchers had never explicated their concept
of IC, so the IC scholars made a linking between the three non-financial areas, especially
the one of learning and growth, and the IC. In 2004 Kaplan and Norton “making official”
the shift of the BSC from strategic management tool to an intangibles management tool by
providing their own version of IC, identifiable within the learning and growth perspective.
According Kaplan and Norton (2004), IC can be separated into human (employees’ skills,
talent and knowledge), information (databases, information systems, networks and
technology infrastructure) and organizational capital (culture, leadership, employee
alignment, team work and knowledge management). Such separation confused some IC
scholars, since it does not consider the traditional IC division: human, structural and
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relational capital on which, in latest times, there is an almost general conjunction (Marr
and Adams, 2004). For this reason, BSC is a model included, by some IC scholars, in the
measurement of intangibles models (Sveiby, 2004; Zambon, 2003).
There are different point of views regarding the effectiveness of BSC in measuring
intangibles. Some researchers Bontis et al., (1999); Petty and Guthrie, (2000) consider BSC
a fundamental tool to measure intangibles. Some others question the use of the BSC model
to value intangibles since it is not a model created basically to measure IC, and intangibles
because their own peculiarities that had to be measured by special measurement systems
(Mouritsen et al., 2005; Lev, 2001).
The IC scorecard measurement models had a development transient from the first,
pioneering studies to the advanced ones (Chiucchi, 2004; Veltri 2007). To the pioneering
models, belong, among others, the Intangible Asset Monitor – IAM (Sveiby, 1997) and the
Skandia Navigator (Edvinsson and Malone, 1997); to advanced models belong, among
others, the IC report models developed under the Meritum (Meritum 2002) and the Danish
project (DMSTI, 2003).
To cut it short it can be said, that focus is in this research is on the content of the intellectual
capital subcategories within an accounting vision. This vision is a typical accounting
vision, according to which intellectual capital is an collective of intangible resources. The
main pillars of these models is the intellectual capital value measurement and their main
goal is to clarify cause and effect of the differential between accounting and market value,
mainly attributed to intellectual capital. The advanced models adopt the evolved notion of
intellectual capital as an active system on intangibles resources and activities based on
knowledge. (Chiucchi, 2004)
The consideration is focused on the interactions between the intellectual capital categories,
at the basis of the firm’s value creation, and on intangible activities essential to provide,
maintain and develop intangible resources. The main aim of the advanced models is to
recognize the paths of the firm’s value creation based on knowledge. (Veltri 2007)
Intellectual capital measuring, managing and reporting is just like environmental reporting
there is no unified acceptable model to deal with it. (Kirkman & Hope, 1992). However,
several models suggested at least point to the right direction (Guthrie & Petty, 2000).
The next section of the research will present the proposed model (intellectual scorecard
model) as a suggested tool to enhance the performance of the travel and leisure firms listed
in the EGX30 in the Egyptian exchange market.
The Model
The researcher present below the proposed intellectual scorecard model as a tool for enhancing the
measurement, management, and disclosure of the intellectual capital in the travel and leisure firms
listed in the Egyptian stock exchange market. The proposed model is a comprehensive model that
integrate two main concepts, which are the Intellectual capital and the most famous balanced
scorecard. The main challenge was to come up with a model which is transparent, auditable,
repeatable (objective), and simple to be used by the top management level of the firms to measure
12
and manage the intellectual capital. The model tries to translate and present intellectual capital into
a language and format that managers can understand, and apply.
The model is important as it classifies Intellectual Capital into what one might call sub domains of
intellectual capital. The model tries to help managers of the firms to include the intangibles mainly
the intellectual capital in their decisions considerations in addition to the other factors like the
tangible assets.
13
intellectual
Scorecarde
Shareholder
capital
Human
capital
Relational
Capital
Structural
Capital
Financial
Perspective
Internal
business
process
Learning and
growth
(Innovation
and learning)
Customer
Efficiency of operations:
- Time for providing the
service
- Expenses for R&D
- Number of new services
- No. of software licenses.
- No. of quality certificates
- Ratio of innovation cost to
total revenue
- Cost of IT infrastructure
Profitability and sustainability:
- Profit from new services
- Operating cash flow
- Asset turnover
- Intangible assets to total assets.
- Investing cash flow
- Shareholder equity/total assets
- Intangible assets to total assets.
- Investment in the development of new markets
- Market value of the firm
- Reporting of intellectual capital
-Benchmark cost versus competitor’s cost
Leadership skills and employees
satisfaction and:
-
Employee turnover.
-
Training expenses per
employee.
-
% of time spent on training
-
Average length of work
experience of professionals in
the firms
-
Percentage of team sharing in
strategic planning
-
Time of providing the service
-
Cost of absenteeism
-
Cost of work related accidents
Customer satisfaction and loyalty:
- No. of clients complains.
- Market share
- Ratio of services to total no. of clients.
-
Average repeated visits per client during
the period
- Brand awareness
- Suppliers turnover
- Quality control
- No. of new clients.
-
Average period of retaining the supplier
Figure (1): Proposed Intellectual scorecard model
14
The Statistical Analysis
The researcher conducted the statistical analysis through two parts:
Part one:
This part included the analysis of the secondary data to illustrate the reporting of intellectual capital
in the sample of annual reports selected (Travel and leisure companies listed in EGX30). The
researcher used the difference between the market value and the book value of the companies to
calculate the value of the intellectual capital in accordance to the information obtained from the
Egypt for information and Dissemination Company to prove the existence of the intellectual capital.
The researcher also, used the descriptive and path analysis to illustrate the relation between the
existence, disclosure of the intellectual capital in the financial statements of the sample and its
effect on the performance of the company measured by ROA and ROE ratios.
The sample included 13 travel and leisure firms listed within the EGX30 in the Egyptian
exchange market. The researcher chose those firms that are listed in the stock exchange
market due to the availability of data and the nature of the EGX 30 indicator itself in order
to assess better the strict environment of travel and leisure firms and to conform with the
requirements of the research. The names of the companies included in the sample are listed
as follows:
Name of the firms
Initials of registration
in EGX30
1.
Rowad Tourism
(ROTO)
2.
Orascom Hotels and Development)
(ORHD
3.
Trans oceans tours
(TOR)
4.
Orascom Development Holding AG
(ODHN)
5.
El Wadi for Touristic Investment
(ELWA)
6.
Sharm Dreams Company for Touristic Investment
(SDTI)
7.
Pyramisa Hotels and Resorts
(PHTV)
8.
Egyptian Resorts
(EGTS)
9.
Remco for Tourism Villages Construction
(RTVC)
10.
Marsa Marsa Alam for Tourism Development
(MMAT)
11.
Egyptian Company for International Tourism Projects
(EITP)
12.
El Shams Pyramids for Hotels and Touristic Projects
(SPHT)
13.
Golden Coast
(GOCO)
Descriptive statistics for Intellectual capital, ROA, and ROE in travel and leisure
companies in Egypt:
The researcher carried out descriptive statistics that includes means, standard deviation, standard
error, and the measures of distribution, as shown below in table (1 ):
15
Table (1 ): Descriptive statistics for Intellectual capital, ROA, and ROE in travel and leisure
companies in Egypt
No.
Performance of
the company
mean
Standard
deviation
Standard
error
skewness
Kolmogorov-Smirnov
statistic
Sig.
1
ROE
0.0267
0.074399
0.01121
0.287
0.073
0.20
2
ROA
0.0269
0.0470
0.0071
0.661
0.117
0.146
3
Log IC
16.775
1.31758
0.19863
-0.858
0.124
0.088
***Parameter is significant at the (.001) level.
According to Descriptive statistics in table (1), it can be concluded that:
The arithmetic mean of ROE is (0.0267), with skewness coefficient (0.287) tends to right,
which indicates normality distribution of ROE, since the significant of Kolmogorov-
Smirnov statistic higher than (0.05).
The arithmetic mean of ROA is (0.0269), with skewness coefficient (0.0.661) tends to
right, which indicates normality distribution of ROE, since the significant of Kolmogorov-
Smirnov statistic higher than (0.05).
The arithmetic mean of IC is (16.775), with skewness coefficient (-0.858) tends to right,
which indicates non-normality distribution of ROE, since the significant of Kolmogorov-
Smirnov statistic less than (0.05).
Disclosure of IC has a percentage of existence of capital 54.5% in the selected sample of
the annual reports.
Figure (2): Path analysis for the ROA, ROE, and IC in travel and leisure companies
The path analysis indicating the direction of impact among the research variables. It indicates that
Intellectual capital is influencing the ROA and that disclosure of the intellectual capital is
influencing the ROA and the ROE. This relation can be identified through the coefficients shown
in the path analysis figure.
Table (2): Regression weights according to Maximum Likelihood Estimates
path
Standardized estimate
Unstandardized estimate
S.E.
C.R.
P
ROA
<---
IC
.531
.497
.081
6.108
***
ROA
<---
DIS
.290
.287
.086
3.341
***
ROE
<---
DIS
.274
.282
.077
3.683
***
ROE
<---
ROA
.606
.632
.077
8.163
***
IC
<-->
DIS
.702
0.506
.084
5.998
***
*** Significant at level less than (0.001)
16
There are significant positive linear relationships between the Intellectual capital, disclosure in
annual reports and the return on assets at significant level less than (0.001) respectively. This
validates the research hypothesis, with regression model:
DISICROA 290.0531.0
There are significant positive linear relationships between the disclosure in annual reports, the
return on assets and return on equity at significant level less than (0.001) respectively. This
validates the research hypothesis, with regression model:
ROADISROE 606.0274.0
There are significant positive linear relationships between the Intellectual capital and disclosure in
annual at significant level less than (0.001) respectively. This validates the research hypothesis,
with regression model:
DISIC 702.0
Measuring the Goodness of Fit of the (SEM) model:
Table (3): The Goodness of Fit Indices in the SEM
Chi-Square
2.556
Degree of Freedom
1
Probability level
.110
Normed Chi-Square
2.556
Root Mean Square Residual (RMR)
.013
Goodness of Fit Index (GFI)
.989
Adjusted Goodness of Fit Index (AGFI)
.885
Normed Fit Index (NFI)
.991
Relative Fit Index (RFI)
.947
Incremental Fit Index (IFI)
.995
Tucker Lewis Index (TLI)
.967
Comparative Fit Index (CFI)
.995
Root Mean Square Residual Approximation (RMSEA)
.119
R2 : ROA=58.20 % , R2 : ROE=66.30%
From table (3), the researcher noticed the following:
All the goodness of fit measures of the model indicate that all indicators at acceptable limits or
greater than cut-off values, especially GFI, NFI, RFI, IFI.TLI, and CFI close to one. The fit
measures indicate the goodness of fit of the final structural model and its ability to measure the
effect of existence of Intellectual capital and the disclosure of intellectual capital in the annual
reports..
The exogenous variables were existence of Intellectual capital and the disclosure of intellectual
capital in the annual reports, in SEM explain (58.20% ) from total variation of dependent variable;
Return on Assets, the rest percent due to either the random error in the regression model or other
Independent Variables excluded from regression model.
The exogenous variables were entered, existence of Intellectual capital and the disclosure of
intellectual capital in the annual reports, in SEM explain (66.30% ) from total variation of
dependent variable; Return on equity, the rest percent due to either the random error in the
regression model or other Independent Variables excluded from regression model.
This part conducted to examine the relation between the Intellectual capital, disclosure of
intellectual capital in the annual reports and their effect on the ROA and ROE of travel and leisure
17
firms. The statistical results confirmed the positive reaction and showed a high R2 for both ROA
and ROE. These results derived the researcher to test the validity of the proposed Intellectual
scorecard model on travel and leisure firms listed in the stock exchange market to enhance their
performance.
Part two:
This part of the statistical analysis is to verify the hypothesis of the research and to validate the ICS
proposed model application in the travel and leisure companies listed in the EGX 30 in the Egyptian
stock exchange market.
The sample included 13 travel and leisure firms listed within the EGX30 in the Egyptian
exchange market. The questionnaire was sent to 130 financial managers and employees
within the 13 selected sample firms. The response were 108 positive response with 83%
response rate. The proposed model constructs was also, tested for approval from the respondents
as a valid measures for enhancing the performance of the companies.
Reliability and intrinsic validity for research variables:
Table (4): Reliability and intrinsic validity for research variables
No
Dimension
Reliability
coefficient
intrinsic
validity
1
Financial perspective/ shareholder capital value
0.920
0.959
2
Internal business process perspective/ Structural
Capital
0.864
0.929
3
Learning and growth perspective/ Human capital
0.922
0.960
4
Customer perspective/ Customer Capital
0.906
0.950
Total
0.964
0.949
According to Table (4), researcher finds out that reliability coefficient and intrinsic validity, for
research dimensions are (0.964), (0.949) respectively; highly internal consistency based on the
average inter-item correlation. The most four dimensions with highly Reliability coefficients are:
Financial perspective/ shareholder capital value, Internal business process perspective/ Structural
Capital, Learning and growth perspective/ Human capital, and Customer perspective/ Customer
Capital, with Reliability coefficient (0.920), (0.864), (0.922), (0.906) respectively.
The performance of the Egyptian travel and leisure companies:
Table (5): Descriptive statistics for performance of the firms
NO.
statements
MEAN
SD
CV
RANK
1
ROA
4.1759
0.70815
16.96
1
2
ROE
4.0463
0.67512
16.68
2
TOTAL
4.1111
0.64247
15.63
--
According to Descriptive statistics in table (5), it can be concluded that:
The two selected financial measures are homogeneous variables, which are return on asset
and return on equity, with coefficient of variation (16.96%), and (16.68 %%) respectively.
While the value of total weighted mean for performance of the company is (4.1111), with
coefficient of variation (15.63%), therefore there is a trend in answers toward approving
the two variables as mediators for measuring the performance of the companies.
18
1. Financial perspective/ shareholder capital value:
Table (6): Descriptive statistics for financial perspective/ shareholder capital value
NO.
statements
MEAN
SD
CV
RANK
1.
Profit from new services
3.9074
0.84872
21.72
3
2.
Operating cash flow
3.8704
0.88700
22.92
6
3.
Market value of the firm
3.8241
0.80685
21.10
1
4.
Intangible assets to total assets
3.8889
0.83536
21.48
2
5.
Investing cash flow
3.8148
0.86628
22.71
4
6.
Shareholder equity/total assets
3.8056
0.88030
23.13
7
7.
Intangible assets to total assets.
3.8426
0.87715
22.83
5
8.
Investment in the development of new markets
3.8704
0.93821
24.24
9
9.
Asset turnover
3.7222
0.86287
23.18
8
TOTAL
3.8463
0.65259
16.97
--
According to Descriptive statistics in table (6), it can be concluded that:
The most three homogeneous variables are: Market value of the firm, Intangible assets to total
assets, Profit from new services, with coefficient of variation (21.10%), (21.48%), (21.72%)
respectively.
On the other hand the most three heterogeneous variables are Shareholder equity/total assets,
Asset turnover, and Investment in the development of new markets, with coefficient of variation
(23.13%), (23.18%), (23.18%) respectively.
While the value of total weighted mean for financial perspective/ shareholder capital
value is (3.8463), with coefficient of variation (16.97%), therefore we have sometimes
direction to the financial perspective/ shareholder capital value dimension.
2. Internal business process perspective/ Structural Capital:
Table (7): Descriptive statistics for internal business process perspective/ Structural
Capital
NO.
statements
MEAN
SD
CV
RANK
1.
Leadership skills and employees satisfaction
3.8148
0.75068
19.68
3
2.
Employee turnover.
3.8241
0.82969
21.70
4
3.
Training expenses per employee.
4.1759
0.77132
18.47
2
4.
% of time spent on training
4.0093
0.71689
17.88
1
5.
Average length of work experience of
professionals in the firms
3.8611
0.90128
23.34
5
TOTAL
3.9290
0.61362
15.62
--
According to Descriptive statistics in table (7), it can be concluded that:
the most three homogeneous variables are: % of time spent on training, Training expenses
per employee, Leadership skills and employees satisfaction, with coefficient of variation
(17.88%), (18.47%), (19.68%) respectively.
On the other hand the most two heterogeneous variables are Employee turnover, and
Average length of work experience of professionals in the firms, with coefficient of
variation (21.70%), (23.34%) respectively.
19
While the value of total weighted mean for internal business process perspective/
Structural Capital is (3.9290), with coefficient of variation (15.62%), therefore we have
sometimes direction to the internal business process perspective/ Structural Capital
dimension.
3. Learning and growth perspective/ Human capital:
Table (8): Descriptive statistics for Learning and growth perspective/ Human capital
NO.
statements
MEAN
SD
CV
RANK
1.
No. of customers complains.
3.8148
0.92875
24.35
4
2.
Market share
3.8145
0.94867
24.87
7
3.
Ratio of sales to total customer
3.8055
0.85880
22.57
1
4.
Average repeat sales per customer during the
period
3.6944
0.88030
23.83
2
5.
Cost of absenteeism
3.8148
0.93876
24.61
5
6.
Cost of work related accidents
3.7315
0.89240
23.92
3
7.
No. of customers complains.
3.8055
0.94184
24.75
6
TOTAL
3.7778
0.72874
19.29
--
According to Descriptive statistics in table (8), it can be concluded that:
The most three homogeneous variables are Ratio of sales to total customer, Average repeat
sales per customer during the period, Cost of work related accidents, with coefficient of
variation (22.57%), (23.83%), (23.92%) respectively.
On the other hand the most three heterogeneous variables are Cost of absenteeism, No. of
customers complains, and Market share, with coefficient of variation (24.61%), (24.75%),
(24.87%) respectively.
While the value of total weighted mean for Learning and growth perspective/ Human
capital is (3.7778), with coefficient of variation (19.29%), therefore we have sometimes
direction to the Learning and growth perspective/ Human capital dimension.
4. Customer perspective/ Customer Capital:
Table (9): Descriptive statistics for Customer perspective/ Customer Capital
NO.
statements
MEAN
SD
CV
RANK
1.
Time for providing the service
3.8241
0.86282
22.56
2
2.
Expenses for R&D
3.8333
0.89129
23.25
3
3.
Number of new services
3.8889
0.94060
24.19
4
4.
No. of software licenses.
3.7593
0.92595
24.63
6
5.
No. of quality certificates
3.8241
0.81835
21.40
1
6.
Ratio of innovation cost to total
revenue
3.6852
0.89284
24.23
5
TOTAL
3.7989
0.70258
18.49
--
According to Descriptive statistics in table (9), it can be concluded that:
The most three homogeneous variables are No. of quality certificates, Time for providing
the service, and Expenses for R&D with coefficient of variation (21.40%), (22.56%),
(23.25%) respectively.
20
On the other hand the most three heterogeneous variables are: Number of new services,
Ratio of innovation cost to total revenue, and No. of software licenses, with coefficient of
variation (24.19%), (24.23%), (24.63%) respectively.
While the value of total weighted mean for Customer perspective/ Customer Capital is
(3.7989), with coefficient of variation (18.49%), therefore we have sometimes direction to
the Customer perspective/ Customer Capital dimension.
Confirmatory analysis:
Confirmatory factor analysis (CFA) was first conducted to test how well the measured variables
represent the constructs. The key advantage is that the researcher can analytically test a
conceptually grounded theory explaining how different measured items represent important
business measures. When CFA results are combined with construct validity tests, the researcher
can obtain a better understanding of the quality of their measures. The construct validity is the
extent to which a set of measured items actually measures the construct. The model fit is
assessed in terms of ten indices: Normed Chi-Square with cut-off values less than (5),
goodness-of-fit index (GFI), Adjusted Goodness of Fit Index (AGFI) ,Normed Fit Index (NFI),
Relative Fit Index (RFI), Incremental Fit Index (IFI), Tucker Lewis Index (TLI), Comparative
Fit Index (CFI), Root Mean Square Residual Approximation (RMSEA) , Root Mean Square
Residual (RMR) , and The average variance extracted with cut-off values greater than (0.5) .
A model is considered to be satisfactory if CFI > 0.90, GFI > 0.90 and RMSEA ˂ 0.10 (Hair
et al., 2010).
The researcher conducted both initial Confirmatory factor analysis and final Confirmatory
factor analysis with the fit measured variables represents the constructs, as the following
Figure (3): The initial Confirmatory factor analysis for a measurement model
21
Table (10): Confirmatory Factor Analysis by standardized and unstandardized regression
weights
Path
Standardized
estimate
Unstandardized
estimate
S.E.
t_test
Significant
level
Q1.1
<---
F1
.800
1.000a
Q1.2
<---
F1
.907
1.080
.120
9.033
0.001***
Q2.3
<---
F2
.761
1.278
.170
7.501
0.001***
Q2.2
<---
F2
.718
1.155
.163
7.094
0.001***
Q2.1
<---
F2
.704
1.000
Q2.4
<---
F2
.717
1.096
.155
7.080
0.001***
Q2.5
<---
F2
.740
1.171
.160
7.304
0.001***
Q2.6
<---
F2
.765
1.256
.166
7.542
0.001***
Q2.7
<---
F2
.735
1.225
.169
7.250
0.001***
Q2.8
<---
F2
.757
1.257
.169
7.461
0.001***
Q2.9
<---
F2
.747
1.328
.180
7.372
0.001***
Q2.10
<---
F2
.668
1.092
.165
6.609
0.001***
Q3.1
<---
F3
.785
1.000
Q3.2
<---
F3
.656
.795
.114
7.002
0.001***
Q3.4
<---
F3
.737
.917
.114
8.037
0.001***
Q3.6
<---
F3
.764
1.111
.132
8.394
0.001***
Q4.1
<---
F4
.754
1.000
Q4.2
<---
F4
.809
1.177
.134
8.785
0.001***
Q4.3
<---
F4
.792
1.177
.137
8.573
0.001***
Q4.4
<---
F4
.759
1.022
.125
8.166
0.001***
Q4.5
<---
F4
.752
1.036
.128
8.070
0.001***
Q4.6
<---
F4
.779
1.145
.136
8.406
0.001***
Q4.7
<---
F4
.799
1.117
.129
8.661
0.001***
Q4.8
<---
F4
.742
1.094
.138
7.949
0.001***
Q5.1
<---
F5
.847
1.000
Q5.2
<---
F5
.769
.964
.102
9.436
0.001***
Q5.3
<---
F5
.733
.949
.108
8.794
0.001***
Q5.4
<---
F5
.773
1.056
.111
9.500
0.001***
Q5.5
<---
F5
.778
1.047
.109
9.611
0.001***
Q5.6
<---
F5
.742
.882
.099
8.943
0.001***
Q5.7
<---
F5
.674
.875
.112
7.826
0.001***
According to Table (10), the researcher can conclude the following:
1. All standardized regression weights (factor loading) are greater than 0.50, which means
that all measured variables, are statistically significant, i.e., the measured variables
represent the constructs.
2. t- Test for all measured variables is significant at a level of significance less than (0.001),
which shows the importance of the observed variables in measuring the impact of
corporate social responsibility on the employees’ organizational affective commitment.
3. as a result of Squared Multiple Correlations ,i.e., average variance extracted, for the
variables of Q3.3(Employee turnover), ,and Q3.5(% of time spent on training), have less
than (0.50) ,then they have been excluded from the Learning and growth perspective/
Human capital construct.
22
Measuring the Goodness of Fit of the (CFA) model:
Table (11): The Goodness of Fit Indices in the Confirmatory Factor Analysis
Chi-Square
724.819
Degree of Freedom
424
Level of Significance
0.000
Normed Chi-Square
1.709
Root Mean Square Residual (RMR)
.046
Goodness of Fit Index (GFI)
.723
Adjusted Goodness of Fit Index (AGFI)
.675
Normed Fit Index (NFI)
.740
Relative Fit Index (RFI)
.715
Incremental Fit Index (IFI)
.873
Tucker Lewis Index (TLI)
.858
Comparative Fit Index (CFI)
.871
Root Mean Square Residual Approximation (RMSEA)
.081
The average variance extracted
0.564379
From table (11), the researcher revealed that:
All the goodness of fit tests of the model showed significant results or i.e., the majority of indicators
at acceptable limits or near to cut-off values, and then the possibility of matching the actual form
of the model estimated. The values of Root Mean Square Residual (RMR) and Root Mean Square
Residual Approximation (RMSEA) less than (0.10),which indicates a close fit of the model in
relation to the degrees of freedom . The mean variance extracted for all latent constructs is
0.564379, i.e., there is adequate convergent validity.
The average variance extracted for the constructs of Financial perspective/ shareholder capital
value, Internal business process perspective/ Structural Capital, Learning and growth perspective/
Human capital, and Customer perspective/ Customer Capital are: (0.5354), (0.543), (0.5985),
(0.579), respectively, i.e., there is a highly internal consistency based on the average inter-item
correlation. AVEs of all scales turned out to be more than the cut-off values.
The average variance extracted for the construct of Learning and growth perspective/ Human
capital is: (0.5985), i.e., AVEs of a specific scale turned out to be near the cut-off values. The
average variance extracted for the performance of the companies is: (0.731), i.e., AVEs of a specific
scale turned out to be more than the cut-off values.
Overall, the evidence of a good model fit, reliability, and convergent validity, indicates that the
measurement model should be improved for testing the regression model by excluding the variables
of Q3.3, ,and Q3.5 from the initial CFA.
The logistic regression model:
There are many important research topics for which the dependent variable is "limited." or
categorical response variable. Logistic regression is useful for situations in which you want to be
able to predict the presence or absence of a characteristic or outcome based on values of a set of
predictor variables. It is similar to a linear regression model but is suited to models where the
dependent variable is dichotomous. Logistic regression coefficients can be used to estimate odds
ratios for each of the independent variables in the model. Logistic regression is applicable to a
broader range of research situations than discriminant analysis.
23
Table (12): Stepwise logistic regression model for Financial perspective/ shareholder
capital value
Prob.
R2
Chi –square test
Wald test
Estimated
coefficient
Independent Variables
No
Sig.
value
Sig.
value
70%
35.5%
***0.001
19.283
*0.003
4.523
0.847
constant
1
97%
***0.001
10.434
3.497
Financial perspective/
shareholder capital value
2
* Parameter is significant at the 0.005 level
Table (13): Stepwise logistic regression model for Internal business process perspective/
Structural Capital
Prob.
R2
Chi –square test
Wald test
Estimated
coefficient
Independent Variables
No
Sig.
value
Sig.
value
58%
39.4%
***0.001
21.634
0.493
0.470
0.318
constant
1
79%
***0.001
16.404
3.454
Internal business process
perspective/ Structural
Capital
2
Table (14): Stepwise logistic regression model for Learning and growth perspective/ Human
capital
Prob.
R2
Chi –square test
Wald test
Estimated
coefficient
Independent Variables
No
Sig.
value
Sig.
value
72.41%
26.1%
***0.001
13.819
0.020
5.396
0.965
constant
1
93.60%
***0.001
10.520
2.686
Learning and growth
perspective/ Human
capital
2
Table (15): Stepwise logistic regression model for Customer perspective/ Customer Capital
Prob.
R2
Chi –square test
Wald test
Estimated
coefficient
Independent
Variables
No
Sig.
value
Sig.
value
78.12%
15%
**0.001
7.742
0.030
8.862
1.273
constant
1
87.20%
0.008
6.949
1.919
Customer perspective/
Customer Capital
2
Table (16): STEPWISE Logistic Regression
Prob.
R2
Chi –square test
Wald test
Estimated
coefficient
Independent Variables
No
Sig.
value
Sig.
value
46%
49.7%
**0.005
28.086
0755
0.098
-0.163
constant
1
92.58%
0.029
4.766
2.525
Financial perspective/
shareholder capital value
2
92.30%
0.007
7.278
2.484
Internal business process
perspective/ Structural
Capital
3
24
According to logistic regression models in table (16), the following can be concluded:
1- Chi –square test:
The chi-square statistic is the change in the -2 log-likelihood from the previous step, block, or
model. Use the “Model Chi-Square” statistic to determine if the overall model is statistically
significant, Like F test in linear regression model, since The value of "chi square test" is between
(7.742) and (21.634) with significant at the (0.001) level for the constructs of the model individually
and with value of (28.086) with significant at the (0.005) level, then the researcher concludes that
the overall independent variables statistically significant impact on the dependent variable or the
model is fitted to logistic regression.
2- The Classification table:
The classification table helps you to assess the performance of your model by cross tabulating the
observed response categories with the predicted response categories. For each case, the predicted
response is the category treated as 1, if that category's predicted probability is greater than the user-
specified cutoff. Cells on the diagonal are correct predictions, whereas Cells off the diagonal are
incorrect predictions. The overall Classification ratio between (90.7% and 92.6%)
3- Coefficient of determination:
The Independent Variables accepted in the model explain (49.7% ) from total variation of log odds
ratio or logit model ,i.e., dependent variable, ROE and ROE, the rest percent due to either the
random error in the regression model or other Independent Variables excluded from regression
model. Larger pseudo r-square statistics indicate that more of the variation is explained by the
model, to a maximum of 1.
4- Wald test:
It would be useful in determining the significant value of each of the individual independent
variables coefficient in the logistic regression model. The ratio of B to S.E., squared, equals the
Wald statistic. If the Wald statistic is significant (i.e., less than 0.05) then the parameter is useful
to the model. The significant independent variables are, Financial perspective/ shareholder capital
value and Internal business process perspective/ Structural Capital and Institutional ownership,
with significant at less than (0.001) level respectively.
5- Probability event:
The Probability event of each independent variable is the odds ratio divided by Odds ratio plus one,
then the important variables are Financial perspective/ shareholder capital value and Internal
business process perspective/ Structural Capital with probabilities (92.58%),(92.30%) respectively.
6- Logistic Regression model:
By substituting the values of independent variables, researcher can then predict the dependent
variable: performance of the company.
25
Financial perspective/ shareholder capital value, Internal business process perspective/ Structural
Capital, Learning and growth perspective/ Human capital, and Customer perspective/ Customer
Capital
The logistic regression models shows the verification of the hypothesis from 1 to 4 as it illustrate
the impact of each of the model constructs on the dependent variable (performance of the travel
and leisure companies).
The overall model below includes the two variables with the highest effect (impact) on the
dependent variable, which is the performance of the company as in the following logistic model.
The independent variables that had been selected by the statistical analysis are financial
perspective/ shareholder capital value and internal business process perspective/ Structural Capital.
HYPOTHESES VERIFICATION:
The hypotheses of the research had been tested and verified through the research
methodology, which included in the literature review and the empirical study.
The first part of the statistical analysis used Path analysis and the Structural equation
modeling (SEM) indicated the impact of the research variables. The results indicated that
Intellectual capital and its disclosure is influencing the ROA and the ROE. The R2 values
for ROA, ROE are 58.20 % and 66.30 % respectively showed the importance of the
intellectual capital and its disclosure on the performance of the company. So, the researcher
selected based on that results to use the ROA and ROE as a measures for the performance
of the firms as a result of that analysis.
The second part of the statistical analysis used the descriptive analysis, confirmatory
analysis, and logistic regression model to analyze the results of the questionnaire
distributed to the managers and employees of the travel and leisure firms listed in EGX30
in the Egyptian stock exchange market.
The descriptive analysis provided rank for the importance of the measures proposed by the
researcher for applying the proposed model for the four perspectives.
The confirmatory analysis excluded the least important measures from the model and
qualified the model to be tested by the regression analysis.
The logistic regression results showed the relationship between the four constructs
measures of intellectual scorecard proposed model via the output achieved by the
researcher through the most influential measures that are included in the proposed
model.
Hypothesis 1 (Financial perspective/ shareholder capital value)
Hypothesis 2 (Internal business process perspective/ Structural Capital)
Hypothesis 3 (Learning and growth perspective/ Human capital)
Hypothesis 4 (Customer perspective/ Customer Capital)
p
p
Ln 1
IPFP 484.2525.2163.0
26
The logistic regression shows degree of impact for each of the four constructs of
the proposed model on the performance of the Egyptian travel and leisure firms
within EGX30, then the whole model through the values of the R2 for each construct
and then with overall value for the model which is R2 equal 49.7%.
The first 4 hypotheses have been verified through the statistical analysis and the logistic
model, which support the positive effect of intellectual scorecard model on performance of
the travel and leisure firms listed in the stock exchange market. The fifth hypothesis have
been verified through the statistical analysis and the logistic model that showed the validity
of the model in enhancing the performance of travel and leisure in Egypt.
The analysis for the variables shows also the importance of the four perspectives of the
intellectual scorecard proposed model, which have been verified to be used for enhancing
performance of the travel and leisure firms.
The researcher reached the following results:
The proposed model is valid for application in the travel and leisure firms for
enhancing the performance of the travel and leisure firms.
The four dimensions of intellectual scorecard proposed model have been verified
through the statistical analysis and indicated the suitability of the proposed model
for improving the performance.
The analysis proved that the most influential perspectives of the model on the
performance of the firms are the financial perspective/ shareholder capital value,
internal business process perspective/ Structural Capital.
CONCLUSION
This study tried to contribute in covering the gab in the literature review regarding two
main points. The first issue is the measurement and disclosure of intangible assets with
special emphasis on the intellectual capital within an accounting context. The second issue
is recognition of the intellectual capital in the annual financial reports for listed companies
listed in the Egyptian exchange market. The researcher selected the travel and leisure firms
due to their special nature and the nature of operations. The researcher used two approaches
to verify the hypotheses of the research. The first approach was to determine the value of
the intellectual capital in the selected firms through calculating the difference between
market value and the book values of the firms then examining the disclosure of these values
in the annual reports. The researcher then tested the relation between the values of the
intellectual capital and the disclosure of IC in the annual reports on the performance of the
firms measured by ROA and ROE. The second approach was to examine the validity of
the proposed Intellectual scorecard on the performance of the travel and leisure firms listed
in the Egyptian stock exchange market.
The results of the empirical study verified the validity of the proposed intellectual scorecard
model and proved the relation between the application of the proposed model and the
performance of the travel and leisure firms listed in the Egyptian stock exchange market.
The results also, indicated that performance of the Egyptian travel and leisure firms are
27
affected with financial perspective/ shareholder capital value and internal business process
perspective/ Structural Capital and then come the other two perspectives of the proposed model.
The proposed Intellectual Scorecard acknowledges that the basic framework of financial
reporting, that is, income statement, the balance sheet and the statement of cash flows, are
going to stay, and it is necessary to integrate intellectual capital reporting into the
mainstream reporting of firms. Intellectual capital items are identified by their impact on
the statement of income and the balance sheet to construct ratios to integrate them into the
key performance indicators of the firm, having an operational impact, strategic impact and
a cash flow impact. The type and nature of ratios can vary depending on the type of firm,
and its strategic and operational focus.
In Egypt, as a developing country, reposting the intellectual capital is still in progress and disclosure
of intellectual capital is voluntary. Firms should consider intellectual capital statement as this would
represent an integral part of working with knowledge management within the company. The
intellectual capital can contribute to creating value for the company by improving the basis for
growth, flexibility and innovation.
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