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E-commerce usage and business
performance in the Malaysian
tourism sector: empirical analysis
Mohamed Intan Salwani
Faculty of Accountancy, Universiti Teknologi MARA Malaysia,
Shah Alam, Malaysia
Govindan Marthandan
Faculty of Management, Multimedia University, Cyberjaya, Malaysia
Mohd Daud Norzaidi
Faculty of Business Management, Universiti Teknologi MARA Malaysia,
Shah Alam, Malaysia, and
Siong Choy Chong
Principal and Chairman’s Office, Putra International College,
Ayer Keroh, Malaysia
Abstract
Purpose – Based upon the E-VALUE model developed, this paper aims to investigate the impact
of e-commerce usage on business performance in the tourism sector.
Design/methodology/approach – A cross-sectional survey is carried out on 165 Malaysian firms
involved in the tourism sector (hotels, resorts, and hospitals engaged in health tourism) through the
use of a structured questionnaire.
Findings – The structural equation modeling results indicate that technology competency, firm size,
firm scope, web-technology investment, pressure intensity, and back-end usage have significant
influence on e-commerce usage. Among these variables, back-end integration is found to function as a
mediator. E-commerce experience (in years) is found to moderate the relationship between e-commerce
usage and business performance.
Research limitations/implications – The paper focuses on the tourism sector in Malaysia and
concentrates only on the management perspective of e-commerce adoption.
Practical implications – The results provide insights to the Malaysian tourism sector and other
organizations of similar structures of how they could improve upon their e-commerce adoption and/or
usage for improved business performance.
Originality/value – This paper is perhapsone of the first to investigate e-commerceusage in the tourism
sector using a comprehensive set of variables through an interactive, comp rehensive and multi-dimensional
theoretical model (the E-VALUE model) in investigating their influences on business performance.
Keywords Electronic commerce, Business performance, Tourism, Malaysia
Paper type Research paper
Introduction
It is widely acknowledged that the emergence of information and communications
technology (ICT) have contributed to the rapid growth of electronic marketplace
(Norzaidi et al., 2007). With the strong waves of globalization and liberalization across
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/0968-5227.htm
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Received 24 November 2008
Revised 28 December 2008
Accepted 14 January 2009
Information Management &
Computer Security
Vol. 17 No. 2, 2009
pp. 166-185
qEmerald Group Publishing Limited
0968-5227
DOI 10.1108/09685220910964027
the world, ICT, particularly the internet, is believed to be the most cost-efficient tool to
help brick and mortar companies gain bigger markets and the ability to compete with
other rival organizations in attracting customers to their products, services and
information (Tan et al., 2009). The favourable characteristics inherent in the internet
such as speed, user-friendliness, low cost and wide accessibility have allowed
electronic commerce (e-commerce) to be increasingly diffused globally, bringing
countries together into a global networked economy (Gibbs and Kraemer, 2004). It is
for these reasons that e-commerce has been widely regarded as a new frontier for
business environment and that businesses all over the globe are attempting to shift to
e-commerce to achieve their business objectives (Chandran et al., 2001) in terms of
pursuing efficiency and quality (Mougayar, 1998).
There is, however, consensus that many organizations in general, irrespective of
size, have not been able to realize the full potential of the values brought about by
e-commerce. In a developing country such as Malaysia, for instance, enterprise attitude
has been identified as a major hindrance to e-commerce involvement. It has been found
that Malaysian companies tend to be followers rather than pioneers in e-commerce
investment because many of them fear failure to invest in such an unknown space
(Ng, 2000). Further, lack of success stories by click and mortar companies have been
identified as a reason why traditional businesses are reluctant to embark in
e-commerce investments. In a study on e-commerce stimuli and practices among the
small and medium enterprises (SMEs) in Malaysia, Ainin and Noor Ismawati (2003)
provide empirical support where 79 percent of the respondents cited “not many success
stories of e-commerce” as the main barrier to e-commerce adoption, followed by “not
having knowledge in e-commerce” (72.6 percent), “low internet access among buyers”
(72.2 percent), and “lack of knowledge on the potential of e-commerce” (69.6 percent).
This problem is also prevalent among larger organizations in different parts of the
world where most of them are still at the infancy stage of positioning themselves to
exploit business opportunities enabled by the internet (Zhu, 2004).
Notwithstanding, it is believed that e-commerce has the potential to create value for
different types of firms across different sectors, including the tourism industry. Being a
sector that is largely service-based, e-commerce can serve as a unique tool for the
tourism industry to enhance their services, which could well determine their value
creation and business performance. This in turn could ensure the success of
e-commerce implementation. However, the involvement of the firms in e-commerce in
Malaysia is still in its formative years. Chow (2000) found that only 20.5 percent of the
firms involved in hospitality services are involved in e-commerce due to the lack of
success stories and information on the potential impact of e-commerce implementation
on firms’ performance.
It is therefore imperative to further conduct research to understand the issues and
potential of e-commerce implementation on the performance of the firms in the tourism
industry. The literature indicates that relevant studies conducted on this industry are
scarce (Intan Salwani et al., 2008). Further, while many efforts have been devoted to
studying e-commerce at the pre-adoption stage (initiation) and its formal adoption
(Norhayati, 2000), very little attention has been paid to the post-adoption issues
(Zhu and Kraemer, 2005), especially in the developing countries. While similar reasons
have been advanced of why organizations in general still struggle with e-commerce
implementation, the theories developed particularly in the context of mature markets
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may not be suitable to the developing economies (Austin, 1990). As such, in order to
fully realize the value of e-commerce investment and usage in the tourism sector,
a full-scale deployment at the post-adoption stage and its impact on business
performance especially in a developing economy such as Malaysia stand out as an
important research topic. Specifically, this paper aims to fulfill the following objectives:
.to advance our understanding on the extent to which technological,
organizational and environmental factors influence the level of e-commerce
usage and business performance by considering the direct and indirect effects;
.to provide input on how e-commerce capabilities (front-end functionalities and
back-end integration), through usage, will influence business performance; and
.to provide information on the relationship between level of e-commerce usage
and business performance by considering the effects of moderating variables (i.e.
e-commerce experience).
To accomplish the above research objectives, this research uses an interactive,
comprehensive and multi-dimensional theoretical model (E-VALUE model) to fill the
gaps of knowledge in the literature. The findings of this paper serve to not only inform
decisions on the value of e-commerce but also to furnish useful guides to the organizations
in the tourism sector as well as firms of similar structure on how e-commerce can be best
deployed for improved business performance. The findings also provide useful information
to related bodies such as the regulatory bodies and industrial and/or business associations.
The rest of the paper is organized as follows. The next section reviews the
technological, organizational, and environmental (TOE) model and the resource-based
view (RBV) theory. The resulting model, i.e. the E-VALUE model, acts as the
theoretical foundations of this paper. The research framework and a series of testable
hypotheses are presented next before the methodology is provided. The data collected
were then analyzed and interpreted. The implications are discussed and
recommendations are provided before concluding the paper.
Literature review
E-commerce is an unfolding phenomenon in view of technological advancement. From
the research perspective, technological innovations have led to the development of
various theories related to the diffusion of information technology (IT) and information
systems (IS). A review of literature indicates that there is a rich stream of research
focusing on technology diffusion on individuals and organizations (Cooper and Zmud,
1990; Rogers, 1962; Tornatzky and Fleischer, 1990). Some of the popular areas studied
were on adoption and/or usage of different types of technologies such as electronic
fund transfer (EFT), electronic data interchange (EDI), enterprise resource planning,
adoption drivers, adoption barriers or hindrance, and many others. In the late 1990s,
however, the focus seems to shift to e-commerce adoption. In line with the objectives of
this research, the following sub-sections discuss one of the more popular models, i.e.
the TOE model and the corresponding RBV theory in brief.
Technological, organizational and environmental (TOE) model
Realizing the importance of technology adoption, Tornatzky and Fleischer (1990)
developed the TOE model to evaluate technology adoption. The TOE model is
consistent with the theory of innovation diffusion in organizations by Rogers (1983).
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The model identifies three aspects of firm’s characteristics that influence the process of
adopting, implementing and using technological innovations (DiPietro et al., 1990;
Robertson, 2005; Tornatzky and Fleischer, 1990) which is explained below:
(1) Technological context. Technological context describes both existing and new
technologies relevant to the firm such as prior technology usage, and number of
computers in the firm which determines the ability of the firm to move to
e-commerce and other technology initiatives.
(2) Organizational context. Organizational context refers to descriptive measures
related to organizations such as firm scope, firm size and managerial beliefs.
(3) Environmental context. Environmental context focuses on areas which the firm
conducts its business operations, with the priority given to external factors
influencing the industry that have significant impacts on the firm such as
government incentives and regulations.
According to DePietro et al. (1990), the three suggested elements interact with each
other in influencing technology adoption decisions.
One can safely conclude by drawing upon prior theoretical and empirical evidences
that the TOE model has been a popular foundational model used for studying the drivers
contributing to successful e-commerce initiatives from the interactions of the three
characteristics, particularly in examining issues such as adoption, implementation and
usage. Table I summarizes some of the more popular studies in chronological order.
Dedrick and West (2003),however, believe that the TOE framework is just a taxonomy
for categorizing variables and does not represent an integrated conceptual framework or a
well developed theory. However, they agree that the model is a useful analytical tool to
distinguish between inherent qualities of an innovation itself and the motivations,
capabilities, and broader environmental context of adopting organizations. As
e-commerce has been viewed as a global technological innovation (Kraemer et al., 2006),
more meaningful insights on the whole process of e-commerce diffusion can be generated
if the TOE model is used to study e-commerce adoption and value creation in conjunction
with other theories or model. To achieve this, Zhu and Kraemer (2005) combined the TOE
model with the RBV theory to study the post-adoption variations in usage and value of
e-business. As the drivers of e-commerce are categorized into three characteristics;
technology, organization, and environment, the value creation of e-commerce is analyzed
from a resource-based perspective that stems from the unique characteristics of the
internet, i.e. the front-end functionalities and back-end integration (Zhu, 2004). The next
sub-section discusses the RBV theory and relates it to the current research.
Resource-based view (RBV) theory
The RBV theory has been developed to facilitate the understanding of how
organizations achieve sustainable competitive advantages (Caldeira and Ward, 2003).
Rooted in the strategic management literature, the RBV theory focuses on the idea of
costly-to-copy attributes of the firm as sources of business returns and as a means to
achieve superior performance and competitive advantage (Conner, 1991). The theory
argues that sustained competitive advantage is generated by the unique bundle of
resources at the core of the firm (Conner and Prahalad, 1996) where business owners
build their businesses from the resources and capabilities that they currently possess
or acquired (Dollinger, 1999). In general, the RBV theory addresses the central issue of
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Theoretical framework
Study Constructs Technology Organization Environment
Zhu et al. (2006) Technological context: (technology readiness, technology integration) p
Innovation assimilation Organizational context: (size, global scope, managerial obstacles) p
Environmental context: (competition intensity, regulatory environment) p
Robertson (2005)
Critical drivers in B2B
Technological context: (discontinuity of services, compatibility integration,
benefits of new technology, EDI, asset specificity)
p
e-commerce Organizational context: (readiness, decision makers IT knowledge, managerial
structure)
p
Environmental context: (competitive environment, relationship with business
partners, industry dynamics, external resources, industry support, institutional
factors)
p
Zhu and Kraemer (2005) Technological context: (technology competence) p
Usage and value of Organizational context: (size, international scope, financial commitment) p
e-business Environmental context: (competitive pressure, regulatory support) p
Zhu et al. (2004) Technological context: (technology readiness) p
IT payoff in e-business Organizational context: (firm size, firm scope) p
environments Environmental context: (competition, government regulation) p
Kuan and Chau (2001) Technological context: (perceived direct benefits) p
EDI adoption Organizational context: (perceived financial cost, perceived technical competence) p
Environmental context: (perceived industry pressure, perceived government
pressure)
p
Thong (1999) CEO characteristics: (CEOs’ innovativeness and IS knowledge) p
IS adoption IS characteristics: (relative advantage/compatibility, complexity) p
Organizational characteristics: (business size, employees’ IS knowledge) p
Environmental characteristics p
Table I.
Summary of previous
studies that intersect with
TOE model
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how superior performance can be attained relative to other firms in the same market
and posits that superior performance results from acquiring and exploiting unique
resources of the firm (Saffu, 2004).
Prior IS literature indicates that the RBV theory has been used to analyze IT
capabilities (Mata et al., 1995) and to explain how the business value of IT resides more
in the organization’s skills to leverage on IT as compared to the technology itself (Soh
and Markus, 1995). It shows that the business value of IT depends on the extent to
which IT is used in the key activities in the firm’s value chain (Zhu and Kraemer, 2005).
In relation to e-commerce innovation, the RBV theory is used to demonstrate how firms
leverage their investments in e-commerce to create unique internet-enabled capabilities
that determines a firm’s overall e-commerce effectiveness (Zhu, 2004). Although some
people might argue that e-commerce technologies are already available in the software
and hardware market (e.g. EDI and EFT) for which the investment in e-commerce will
not create value, there is a counterargument that regardless of how commodity-like the
technology is, the architecture that removes the barriers of system incompatibility and
makes it possible to build a corporate platform for launching e-business applications is
never a commodity (Keen, 1991). The costly-to-copy attributes of e-commerce
capabilities are tightly connected to the resource base and embedded in the business
process of the firms but the degree varies as the firms themselves are unique with
respect to their resource endowments (Smith et al., 2001). As such, the value creation
through information sharing and the availability of online communities will lead to
performance advantages in e-commerce (Lederer et al., 2001).
Looking at the application of the RBV theory in discussing e-commerce usage and
value creation, Zhu and Kraemer (2005) attempt to integrate the TOE model and the RBV
theory as their conceptual model to assess the use and value of e-business in
organizations. By investigating the e-business functionalities that make use of the
unique characteristics of the internet, which consequently enable value creation, they
posit that e-business leverages the unique characteristics of the internet to improve
business performance. In this case, e-business capabilities are classified as front-end
functionalities and back-end integration. The front-end functionalities refer to the
medium in which customers interact with the marketspace. It refers to the seller’s portal,
electronic catalogs, a shopping cart, a search engine and a payment gateway. On the
other hand, activities related to order aggregation and fulfillment, inventory
management, purchases from supplier, payment processing, packaging, and delivery
are known as back-end integration of the business (Turban et al., 2006). By applying the
RBV theory in looking at the post-adoption variations in usage and value of e-business,
Zhu and Kraemer (2005) found that both front-end functionalities and back-end
integration contribute to value creation of e-business, but back-end integration has a
much stronger impact. The following sub-section discusses the E-VALUE model which
is a result of combination of the TOE model and the RBV theory.
E-VALUE model – the theoretical foundation of the study
As the e-commerce technology is increasingly attracting the attention of researchers
and managers, the literature on e-commerce remains fragmented and ambiguous
especially from organizational perspectives, particularly on e-commerce usage and
value creation (Govindarajulu et al., 2004). The absence of an integrated theoretical
framework has led to a fractured research stream with many simultaneous but
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non-overlapping conversations (Chan, 2000). There is thus a need to develop a
conceptual model that is not based only on theory, but rooted in one that is inherently
suitable for analyzing the complexity of IT and firm performance (Melville et al., 2004).
This issue is merely solved by Zhu and Kraemer (2005) who developed an integrated,
multi-dimensional model of e-business use and value which combined the TOE model
and RBV theory. Although the efforts by Zhu and Kraemer (2005) solved some missing
link in the literature, there are at least four improvements that can be made on the
integrated model as shown in Table II.
The combination of Zhu and Kraemer’s (2005) model with the improvements shown
in Table II lead to the development of an interactive, comprehensive, and
multi-dimensional theoretical model known as E-VALUE model (Figure 1) which is
used in this paper, to further examine the impact of e-commerce usage on business
performance.
In short, in proposing the specific constructs within the E-VALUE model, this paper
considers all significant factors found in prior studies such as the pre- and
post-adoption of e-commerce usage, direct and indirect effects, and effect of the
moderator variable. Besides, combining the TOE model with the RBV theory, this
paper also includes an e-business scorecard which contains elements from IT and
accounting perspectives in order to provide a comprehensive and multi-dimensional
research model. Based on Figure 1 and the research objectives above, the following
section presents the hypotheses constructed for this paper.
Gaps existed in Zhu and Kraemer’s (2005) model Suggested improvements to the proposed model
1. The absence of important variables such as
managerial beliefs and pressure intensity (as
suggested in the literature) that could have
significant influence on e-commerce usage
1. The inclusion of two new variables:
managerial beliefs and pressure intensity
2. In the RBV theory, front-end functionalities
and back-end integration were regressed
directly to e-business value. Both variables
should be regressed towards e-commerce
usage because front-end functionalities and
back-end integration are the predictors of
e-business usage
2. Front-end functionalities and back-end
integration were regressed towards business
performance
3. The absence of a moderator variable which
could have a strong contingent effect on the
relationship between e-commerce usage and
business performance
3. EC experience is included as a moderator
variable to test whether its inclusion could
modify the original relationship between the
independent and the dependent variables
4. The measurement of business performance is
not comprehensive enough from the
accounting point of view. The model only
focused on three factors; the impact of sales,
impact on internal operations, and impact on
procurement. Other important dimensions and
attributes were ignored
4. Business performance is measured based on
the four perspectives of balanced scorecard as
suggested by Kaplan and Norton (1992).
However, with some modifications in the
measurement attributes to suit the needs of
performance measurement from technological
and accounting points of view, this study
introduces “e-commerce scorecard” as a
comprehensive and multi-dimensional
performance measurement tool
Table II.
Proposed improvements
to Zhu and Kraemer’s
(2005) model
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Hypotheses development
Technological competence and e-commerce usage
Many researchers found technological resources an important factor for successful IS
adoption (Crook and Kumar, 1998; Kuan and Chau, 2001), specifically as an enabling
backbone of e-business service (Robertson, 2005). The resources consist of
infrastructure, human resources and knowledge (Bharadwaj, 2000; Mata et al., 1995)
which could well determine the technological competency of the firm. In this paper,
technological competency refers to the technological infrastructure and IT personnel
that enable the development and implementation of e-commerce. The infrastructure
establishes a platform on which e-business can be developed. With the availability of
infrastructure, the IT personnel function by using their knowledge and skills to
develop e-commerce applications (Zhu and Kraemer, 2005). Realizing the importance of
technology competence towards e-commerce usage, H1 is developed to test the
relationship of technology competence and e-commerce usage:
H1. Technology competence significantly explains the variance in e-commerce
usage.
Firm size and e-commerce usage
Firm size is one of the most commonly studied factors in the diffusion of innovation
literature (Damanpour, 1991; Zhu et al., 2004). While increasing the efficiency of business
processes such as reducing processing costs related to commercial transactions, it is also
a major objective that drives companies to implement e-commerce irregardless of the
size-bands (The European E-Business Report, 2004). Large companies are more likely to
benefit from the smaller ones in view of the higher fixed costs for technology
implementation and maintenance. This is not difficult to understand as firm size
represents several important aspects of the organization such as resource availability,
decision agility and prior technology experience (Zhu and Kraemer, 2005). It is therefore
Figure 1.
E-VALUE model
Technological context
Technology competence
Organizational context
Managerial beliefs
Firm size
Firm scope
Environmental context
Regulatory support
E-commerce
usage Business
performance
H1
H2
H3
H4
H5
H6
H7
Mediator
Front-end functionalities
Back-end integration
H11
H10
H9
H8
Pressure intensity
H12
Moderator
Web-technology investment
EC
experience
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posited in this paper that size (as proxied by the number of employees) has a significant
effect on firm’s e-commerce usage:
H2. Firm size significantly explains the variance in e-commerce usage.
Firm scope and e-commerce usage
Firm scope is another commonly studied factor in the diffusion of technology literature.
It refers to the geographical extent of the firm’s operation and its trading globalization.
Dewan and Kraemer (2000) and Hitt (1999) propose that greater scope leads to greater
demand of IT. This is because e-commerce eliminates the geographical boundaries of
doing businesses (Khan and Motiwalla, 2002). With e-commerce, firms are now
connected to the global market which provides opportunities to widen their market size
and reach. Based on these arguments, H3 is constructed to test the relationship
between firm scope and e-commerce usage:
H3. Firm scope significantly explains the variance in e-commerce usage.
Web technology investment cost and e-commerce usage
The findings on the extent to which web technology investment influences e-commerce
usage have been mixed and inconclusive. Caldeira and Ward (2003) argue that despite
high IT investments, not all firms are successful in innovating an effective IT
capability. Zhu and Kraemer (2005) however, believe that higher investment on
e-business development lead to greater extent of usage. The degree of investment
normally relates to what extent the top management believes that e-commerce leads to
firm’s value creation. It relates to the financial commitment of the firms in terms of
their willingness to invest in hardware, software, system integration, and employee
training. As such, H4 is proposed to identify the nature of relationship between costs of
web technology investment and e-commerce usage:
H4. Web technology investment costs significantly explain the variance in
e-commerce usage.
Managerial beliefs and e-commerce usage
Many studies have singled out top management support and leadership as the most
critical factor for successful implementation of technology innovation and e-commerce
usage (Gould, 2001; Igbaria et al., 1998; Quinn et al., 1997). In this paper, managerial
beliefs refer to how top management perceives and acts on e-commerce technology
innovation. This relates to their beliefs on the ease of use and usefulness of e-commerce
investment in creating values for the firms. To test whether managerial beliefs have
significant effect on e-commerce usage, H5 is developed:
H5. Managerial beliefs significantly explain the variance in e-commerce usage.
Regulatory support and e-commerce usage
The development of digital technology and the emergence of new products and
services require formulation of a new policy and regulatory framework. This is
because without parallel development of laws, policies and strategic directions by
government can result in abuses and discourages the adoption and use of e-commerce
(Dasgupta et al., 1999; Zhu and Kraemer, 2005). For e-commerce to flourish, the legal
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framework needs to facilitate the use and access to basic infrastructure and technology
(Country Progress Report, 2005). Besides, regulatory framework, government support
in terms of providing incentives would facilitate e-commerce usage. To test whether
regulatory support provided by the Malaysian government affects e-commerce usage,
H6 is proposed:
H6. Regulatory support significantly explains the variance in e-commerce usage.
Adoption intention and e-commerce usage
Sociological research on threshold models suggest that decisions to engage in a
particular behaviour depends on perceived number of similar others in an environment
that have already done likewise (Krassa, 1988). According to Windrum and Berranger
(2003), factors that influence firms’ decisions to invest in e-commerce can be classified
into two, internal drivers and external drivers. Improved knowledge-sharing, costs
reduction, and increased efficiency are some of the internal drivers to e-commerce
adoption intention (Daniel and Wilson, 2002; Martin, 2001) while customer pressures,
competitive pressures and key suppliers make up the external drivers (Martin, 2001;
Quayle, 2002). To identify whether adoption intention has significant effect on
e-commerce usage, H7 is formulated:
H7. Adoption intention significantly explains the variance in e-commerce usage.
E-commerce usage, front-end functionalities, and business performance
Customers interact in the digital market via a front-end, defined as the portion of an
e-seller’s business process through which customers interact (Turban and King, 2003).
In simple words, front-end refers to the seller’s web site, an interface that helps
business organizations to interact directly with customers and to outperform their
competitors. Front-end functionalities have been identified as a critical success factor
of e-commerce (Wen et al., 2003). Interactive technology such as live chat, interactive
catalogs and three dimensional modeling gives online buyers more control over their
shopping experience and draws them deeper into the buying process. Front-end
functionalities help firms to deliver real-time product information, offer customization
and facilitate customers via online account management which lead to improving
transactional efficiencies and expanding the existing channel (Zhu and Kraemer, 2002).
This would help firms to improve their business performance. To test whether
front-end functionalities create values in e-commerce, H8 is developed:
H8. Through e-commerce usage, front-end functionalities significantly explain the
variance in business performance.
E-commerce usage, back-end integration, and business performance
Turban and King (2003) define back-end as the activities that support online order
taking and fulfillment, inventory management, purchases from suppliers, payment
processing, packaging, and delivery. Zhu and Kraemer (2005) discover that the process
of back-end integration which is more difficult to imitate, have stronger impact on
e-business performance compared to front-end functionalities. Since not much focus
was given on how back-end integration affects business performance in prior
literature, H9 is constructed to test the relationship between back-end integration and
business performance:
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H9. Through e-commerce usage, back-end integration significantly explains the
variance in business performance.
As back-end integration helps to fit the transactions offered by front-end systems by
linking disparate systems and fragmented resources which help to facilitate order
fulfillment and logistics management with suppliers and distributors (Zhu, 2004), thus,
H10 is formulated to test the relationship between front-end functionalities and
backend integration:
H10. Front-end functionality has significant influence on the level of back-end
integration.
E-commerce usage and business performance
The ultimate goal of using e-commerce is to improve business performance (Zhu and
Kraemer, 2005). Clayton and Criscuolo (2002) demonstrate firms that use e-commerce
are more likely to assess their innovations as having high positive impacts on firm
performance than those without e-commerce. Similarly, Khan and Motiwalla (2002) in
their paper on the influence of e-commerce on corporate performance in the USA found
that from 44 companies under study, 64 percent of them found favourable e-commerce
impact on return on investments. There is so far no evidence on the extent of how
e-commerce usage influences business performance in the Malaysian tourism industry.
To answer this question, H11 is formulated:
H11. E-commerce usage significantly explains the variance in business
performance.
In this paper, a moderating variable is proposed. It is posited that experience of
implementing e-commerce will have a strong contingent effect on the relationship
between e-commerce usage and business performance. This makes up H12:
H12. The relationship between e-commerce usage and business performance is
significantly moderated by e-commerce experience (years).
The next section explains the methodology used in this paper.
Methodology
Sampling procedures
Firms involved in online tourism services such as hotels, resorts, and hospitals
engaging in health tourism constitute the population of interest. These firms were
chosen because of their high degree of usage of technological equipments such as
computers and more importantly, their involvement in e-commerce initiatives. As of
June 2006, there are about 456 members registered with the Malaysian Virtual Tourism
Portal, which largely consists of hotels and resorts. The Directory of the Association of
Private Hospitals of Malaysia reveals that there are 35 hospitals involved in health
tourism as of September 2006. The population is thus made up of 491 companies.
Based on the population of interest, a sample was selected using the stratified
random sampling method. Sekaran (2003) considers this the most efficient sampling
design when differentiated information is needed from the various strata within the
population, with the aim to avoid members of population being significantly under or
over represented (Hussey and Hussey, 1997). The optimum sample size was
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determined based on the sampling table provided by Sekaran (1992) where 217
samples are deemed adequate for a population of 491.
Data collection and analysis procedures
A set of structured questionnaires is used for primary data collection. Only one
questionnaire is distributed to each organization through the respective human
resource or public relations managers to be given to the appropriate higher-level
personnel who is identified to be involved in policy setting and is well aware of the
overall aspects and performance of his or her firm. It is observed that among the
positions of the respondents involved in this paper include the president, managing
director, chief executive officer, chief information officer, chief technology officer, chief
operating officer, chief financial officer, vice president of information systems,
information systems director/manager, business operations manager, administration
manager and/or finance manager. The constructs and number of questions (Table III)
are based upon the research objectives and the H12 formulated earlier in this paper in
which the sources are largely based on literature reviews, reports, and documents
gathered.
Based on the 217 questionnaires sent through mail to the companies, 165 responses
were received. According to Hussey and Hussey (1997), in order to avoid sample bias,
the response rate using the mail distribution method should be more than 10 percent. In
this research, the response rate of 33.6 percent (165 out of 491 companies) indicates that
sample bias was avoided and the responses received represent the population
adequately.
The data were coded and run using the Statistical Package for Social Sciences
version 12.0.1 and Analysis Moment of Structure Graphics version 5.0. The main data
analysis involved the use of the structural equation modeling (SEM) technique. SEM is
noted as a more powerful data analyzing technique that takes into account the
modeling of interactions, non-linearity, correlated independents, measurement errors,
correlated error terms, multiple latent independents each measured by multiple
indicators, and one or more latent dependents also each with multiple indicators
(Garson, 1999). The use of SEM is believed to be able to allow more meaningful and
accurate results to be generated.
Constructs No. of indicators Cronbach’s
a
Technology competence 3 0.704
a
Firm scope 2 0.761
Managerial beliefs 6 0.911
Web technology costs 2 0.780
Regulatory support 4 0.909
Pressure intensity 3 0.761
E-commerce usage 4 0.958
Front-end functionalities 5 0.973
Back-end integration 4 0.980
Business performance 19 0.987
Note:
a
Standardized item
a
(due to multiple-item scales to quantify the construct)
Table III.
Cronbach’s
a
for each
construct
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177
Construct reliability
In this paper, Cronbach’s
a
was performed on each construct to measure internal
consistency reliability for the individual scales and the overall measures. As shown in
Table III, all the constructs scored above 0.70 and therefore are considered reliable in
all aspects.
Evaluation of model fit
Table IV shows the results of evaluation of the model’s fitness. The
x
2
/DF value is
1.268 which is less than the desired cut-off value of 3.0 suggested by Segars and Grover
(1993). Moreover, the incremental fit index (IFI) (0.983), comparative fit index (CFI)
(0.983), and Tucker-Lewis index (TLI) (0.976) values are considered close to the
recommended values. Further, the root mean square error of approximation (RMSEA)
score of 0.045 shows that the model meets a reasonable error of approximation with a
cut-off of 0.08 (Browne and Cudek, 1993). It can therefore be concluded that the model
used in this paper is valid in all aspects. The results confirmed that the responses of
the managers generally support the theoretical and conceptual distinctions of all the
variables proposed in this paper. As such, the data can be applied for further analyses.
The next section presents the results of the H12 tested in this paper.
Results
Table V presents the results of the H12. Technology competence, firm scope, costs of
web technology investment, and adoption intention were found to have significant
Goodness-of-fit-measure Recommended value Approximate boundary as a good fit
Relative
x
2
,3.00 1.268
IFI Close to 1.0 is better 0.983
TLI Close to 1.0 is better 0.976
CFI Close to 1.0 is better 0.983
RMSEA ,0.08 0.045
Table IV.
Evaluation of model fit
Proposition Causal relationship
b
a
p
b
Result
H1 TC !ECU 0.146 0.003 Supported
H2 SZ !ECU 0.007 NS Not supported
H3 FS !ECU 0.164 *Supported
H4 WTI !ECU 0.240 0.046 Supported
H5 MB !ECU 0.043 NS Not supported
H6 RS !ECU 20.031 NS Not supported
H7 AI !ECU 0.415 *Supported
H8 FE !BP 0.192 NS Not supported
H9 BE !BP 0.279 0.004 Supported
H10 FE !BE 0.912 *Supported
H11 ECU !BP 0.438 *Supported
H12 EC experience on ECU !BP 0.749 *Supported
Notes:
a
Regression coefficient;
b
statistical significant of the test (
a
¼0.05, *,0.001)
Table V.
Summary of hypothesis
testing
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influence on the extent of e-commerce usage. As such, H1,H3,H4, and H7 are
supported. Back-end integration and e-commerce usage were found to significantly
explain the variance in business performance and therefore, H9 and H11 are
supported. H10 is also supported where front-end functionality has significant
influence on the level of back-end integration. Finally, the relationship between
e-commerce usage and business performance is significantly moderated by number of
years of experience in e-commerce and therefore, H12 is supported. No support was
found for H4, in that, firm size (H2), managerial beliefs (H5), regulatory support (H6)
do not significantly explain the variance in e-commerce usage, while front-end
functionalities do not significantly explain the variance in business performance (H8).
Discussion and implications
This research has fulfilled all the three objectives set forth in the paper. It offers
significant contributions to the tourism sector not only in terms of the potential of
e-commerce usage but also advances knowledge as far as the use of the E-VALUE model
is concerned. Grounded in the diffusion of innovation literature which covers the TOE
model and the RBV theory, this paper has empirically evaluated the proposed E-VALUE
model and proven its applicability in assessing the various issues related to e-commerce.
By examining firms with experience in e-commerce, it provides a holistic picture of the
post-adoption diffusion and the consequences of e-commerce adoption and usage.
The results suggest that usage appears to be determined by adoption intention (H7),
followed by costs of investment (H4), firm scope (H3), and technology competence (H1)of
the firm in chronological order. The findings are consistent with the resultsof prior studies
(Crook and Kumar, 1998; Dewan and Kraemer, 2000; Hitt, 1999; Khan and Motiwalla, 2002;
Kuan and Chau, 2001; Robertson, 2005; Windrum and Berranger, 2003;Zhu and Kraemer,
2005). This is not difficult to comprehend as many of the firms involved in tourism in
Malaysia have engaged in e-commerce due to their nature of businesses and stakeholders
which transcends theirgeographical boundary. Further,their key suppliers such as hotels,
airlines, and pharmaceutical companies have gone online and they require the firms to
synchronize their operations through the use of computerized and e-commerce systems.
These become the external drivers for the other firms which wish to have businesses with
the suppliers and distributors to follow (Martin, 2001; Quayle, 2002).
However, e-commerce implementation requires a certain amount of investment on web
technology in order to fulfill the needs of suppliers. For the firms, their ultimate aim is
profit through working with the key suppliers and distributors inoffering their services to
customers. Their investment is important in order to get business support from the
suppliers. The substantial investments made on e-commerce development for the sake of
suppliers and distributors explained the adoption intention and utilization by the firms
(Zhu and Kraemer, 2005). It is therefore not difficult to understand the relationship
between firm scope and e-commerce usage. The wider the scope of the tourism firms’
activities, the more likelyit is for the firms to use e-commerce (Dewan and Kraemer, 2000;
Hitt, 1999). These, however, depend very much on the technological competency of the
firms as the availability of necessary technological infrastructure and knowledgeable IT
personnel can determine the success of the firms’ e-commerce initiatives and usage (Crook
and Kumar, 1998; Kuan and Chau, 2001; Zhu and Kraemer, 2005). The findings suggest
that the tourism firms must consistently create value through their willingness to invest in
hardware, software, system integration, and employee training.
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179
On the other hand, firm size (H2), managerial beliefs (H5), and regulatory support
(H6 ) do not determine e-commerce usage. This is in contrast with prior studies
(Dasgupta et al., 1999; Gould, 2001; Igbaria et al., 1998; Quinn et al., 1997; Zhu and
Kraemer, 2005). The finding on firm size reaffirms the earlier argument on the priority
given to the key suppliers across geographical boundaries. The firms are required to
have e-commerce presence in order to meet the requirements of their suppliers, be they
small or large in size. This also explains why managerial beliefs are not a significant
criterion for e-commerce usage. It seems to indicate that e-commerce use is not a
priority to key managers of the firms, but rather meeting the needs and requirements of
key suppliers that dictate their e-commerce initiatives. The significance of back-end
integration to e-commerce usage and business performance (H9) substantiates this
claim. This may also be the reason why the firms perceive regulatory support provided
by the Malaysian government does not induce e-commerce usage due to the many such
laws enacted for the benefits of protecting customers.
The non-significance between front-end functionalities and business performance (H8)
imply that the firms perceive usage of e-commerce as an important means of meeting the
requirements of their key suppliers rather than their customers. This is in contrast with
prior studies which insist that front-end functionalities are critical success factors that
create values for firms (Wen et al., 2003; Zhu and Kraemer, 2005). The results of which
front-end functionalities significantly influence back-end integration suggest that Zhu’s
(2004) argument is supported where integration isneeded to facilitate the activities of key
suppliers and distributors rather than towards meeting the requirements and needs of
customers. It appears clearly that although front-end functionalities are not seen as
important as back-end integration, an integration of both is necessary to facilitate
e-commerce usage.
Consistent with prior studies, the findings also demonstrate that e-commerce
experience significantly moderates the relationship between e-commerce usage and
business performance (H11 (Clayton and Criscuolo, 2002; Khan and Motiwalla, 2002;
Zhu and Kraemer, 2005)). This is proven by the increase of 6.9 percent in the R
2
value.
This implies that experience in e-commerce is an important factor which determines
usage and business performance (H12). Firms with e-commerce experience, such as the
ones surveyed in this paper, are able to determine what works better and what does not
by exploring, experimenting, examining market and performance feedback, and
learning from the experiences of others throughout a period of time (Kauffman et al.,
2002). Their feedback reinforces the importance of the variables under study and more
importantly, the confirmation on the value creation of e-commerce usage in terms of
improved business performance.
In short, the results suggest that e-commerce usage, back-end integration and
experience in e-commerce, and business performance are closely linked. These will
have implications on the firms planning to use or enhance utilization of their
e-commerce technology. The results imply that the potential of e-commerce technology
and usage towards improved business performance should not be overlooked. The
firms should realize that the focus is no longer on whether to deploy e-commerce but
how to deploy it profitably. As e-commerce experience plays a significant role towards
improved firm performance, younger firms cannot afford to delay their e-commerce
development and utilization due to the reason of size. In this respect, the government
and industry associations can play a more pivotal role by creating awareness and
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180
rendering assistance to the firms. For SMEs, some associations such as the Malaysian
Association of Hotels provide services on developing online businesses and providing
training to its members. By participating in these activities, the investment cost can be
minimized for greater benefits.
For firms that are at the advanced stage of e-commerce implementation, it is of
paramount importance that they continuously assess the suitability of their e-commerce
initiatives. The firms must be willing to invest in technological infrastructure,
particularly in hardware, software, and integration of the systems as well as human
competencies by hiring IT personnel with appropriate knowledge and skills to develop
e-commerce applications. These personnel ought to be sent for frequent technical
trainings in order to ensure that their knowledge and skills are kept up-to-date.
Both key suppliers and customers require significant attention from the firms. Many
customers aretech-savvy today and they are increasingly relying on transactions madeon
the internet. As such, equal emphasis must be given to both the front-end functionalities
and back-end integration by keeping in mind the needs of the key suppliers, distributors,
and customers. This will undoubtedly help to boost the performance of the firms.
Conclusion and suggestions for future research
This paper has advanced knowledge by addressing the potential of e-commerce usage
and its relation to business performance from multi-dimensional perspectives through
the use of an integrative model. In many instances, the paper found support from prior
research conducted across different industries in different countries and therefore,
generalizability is not so much of an issue. As such, it is not only useful to the tourism
industry but also other service-based industries which intend to venture into
e-commerce initiatives. It provides useful guides to the click and mortar companies to
evaluate their current e-commerce initiatives and to determine the areas that need to be
re-engineered in the process of profiting from their e-commerce investments. In
addition, it also encourages brick and mortar companies to embark into e-commerce. In
this hypercompetitive world, firms should react fast to the changing business
environment. They should grab the opportunities and take the risk to change the
internet space for business on the internet (Paynter and Lim, 2001).
Future research should consider bigger sample size. Ideally a larger sample size
would provide a clearer understanding of the relationships between the variables. A
retest of the survey instrument with different industry groups and sectors and/or in
different countries may yield interesting insights as well as lead to greater
generalizability of the results obtained. Since e-commerce implementation is time
dimensional and that business performance needs to be measured over time, a
longitudinal rather than a cross-sectional study is warranted to grasp the details.
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Corresponding author
Siong Choy Chong can be contacted at: scchong@iputra.edu.my
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