Analysis of the State of E-Commerce Adoption by the SMEs in Northern Malaysia

and Factors that Might Hinder its Adoption: An Empirical Study

By

LIEW VOON KIONG

Bachelor of Science (Hons) University of Malaya

1981

Master of Management University of Malaya

2001

International Graduate School of Management Division of Business and Enterprise

University of South Australia

Submitted in the year 2004 for the partial requirements of the degree of

Doctor of Business Administration

II

Acknowledgements

I wish to convey a special thank to my supervisor, Associate Professor Dr. Mark Goh K.H for

his invaluable guidance and assistance in helping me to complete this research. I am very

much indebted to him for helping me to overcome many challenges and obstacles during the

course of working on this research paper.

I would also like to extend my thanks to all those lecturers from UniSA who have selflessly

shared their knowledge and provided the necessary guidance and assistance during the course

of doing my DBA.

Besides, I wish to express my gratitude to the Staff of ITD and IGSM of UniSA for their

assistance in providing me the necessary information and resources crucial for my research

work. Special thank also to be extended to the Staff of the UniSA online library who have

done an excellent job in setting up such a complete resource centre. The online library is

extremely important for an overseas student like me as I could access all the necessary

information without having to be physically present at the library.

Last but not least, I would like to express my heartfelt gratitude to my beloved wife and

children for their patient and constant support. Without them, I might not have the motivation

to complete the course.

III

Contents Page Acknowledgements II

Table of Contents III

Abstract V

Chapter 1: Introduction. 1

1.1 Overview of the study 1

1.2 Objectives of the study 4

Chapter 2: Literature Review 5

2.1 Types of e-commerce applications 5

2.2 Stages of e-commerce adoption 7

2.3 Benefits realized through e-commerce adoption 9

2.3.1 Benefits of e-commerce adoption in the B2B area 9

2.3.2 Benefits of e-commerce adoption in the B2C area 14

2.4 Factors hindering the adoption of e-commerce 19

2.5 Conceptual model and hypotheses 22

Chapter 3: Research Design and Methodology 27

3.1 Measurements development 27

3.1.1 Measurement of e-commerce usage 27

3.1.2 Measurement of e-commerce benefits 29

3.1.3 Measurement of factors hindering the adoption 31

of e-commerce

3.2 Research Method 32

3.3 Population and Sample 32

3.4 Data Analysis 34

Chapter 4: Analysis and Findings 36

4.1 Profile of the organizations 36

4.2 Usage of electronic commerce applications 37

IV

4.2.1 Electronic marketing 37

4.2.2 Electronic advertising 37

4.2.3 Customer support service 38

4.2.4 Order and delivery 38

4.2.5 Payment system 38

4.3 Benefits realized through adoption of e-commerce 41

4.4 Factors hindering the adoption of e-commerce applications 42

4.5 Discussion of the findings 48

Chapter 5: Conclusions, Implications and Future Research 50

5.1 Conclusions 50

5.2 Implications 51

5.3 Limitations of the study 52

5.4 Recommendations for future research 52

References 53

Appendix A Questionnaire A1 – A5

Appendix B Coding form B1 – B5

V

Abstract

The purpose of this study is to assess the state of e-commerce adoption by the SMEs in

Northern Malaysia and to examine the factors that might hinder the adoption. The

methodology employed in this study was questionnaire survey. Questionnaires were sent to

the SMEs in Northern who were listed in the latest official business directory of SMI

association of Malaysia as well as other sources. Analysis of the data obtained found that the

general usage of e-commerce among the SMEs in Northern Malaysia is low; most firms

seemed to have implemented only basic e-commerce applications and do not adopt advance

e-commerce applications. For example, the most used e-commerce application is email

whereas the least used application is online payment system. Furthermore, while a substantial

number of the SMEs have implemented web sites, they were used merely to display products

and company information rather than having advanced features such as providing online

transactions and online payment services. Analysis of benefits realized found that most of the

SMEs in Northern Malaysia, which have adopted e-commerce, only gained some of the

benefits of e-commerce. Benefits realized were in the areas of customer service, market

expansion, and back-end efficiency and inventory management. On the other hand, the SMEs

who have adopted e-commerce seemed incapable of improving their overall performance and

profitability. Examination of the factors that might hinder the adoption of e-commerce by the

SMEs in Northern Malaysia were initially identified through factor analysis as environmental

barriers, financial barriers, governmental barriers, organizational barriers, technical barriers

and behavioural barriers. However, correlation analysis showed that only factors related to

organizational, governmental and environmental barriers have some negative influence on the

extent of e-commerce usage. Out of the three factors, only the factor associated with

environmental barriers has a significant correlation with the extent of e-commerce adoption.

Regression analysis confirmed that the factor related to environmental barriers has significant

negative influence on the extent of e-commerce adoption. Therefore, it was concluded that

while many factors could be hindering the adoption of e-commerce by the SMEs in Northern

Malaysia, only the factor pertaining to environmental barriers has significant negative

influence on its adoption.

1

Chapter 1: Introduction

1.1 Overview of the study

Electronic commerce has accelerated at an incredibly fast pace in recent years (Kardaras &

Papathanassiou, 2000). The value of the e-commerce market in Europe is predicted to

increase from $6 billion to $230 billion by the year 2005, while in the US the figure will

skyrocket from $31 billion to $291 billion within the same period. Worldwide e-commerce

transaction was $474 billion in 2001 and it is estimated to reach $2400 billion by 2004

(Daniel, 2003). The revenue for worldwide B2B e-commerce in the year 2002 was $823

billion and is predicted to reach $1400 billion by 2003 (BizReport, 2003). These figures

indicated that e-commerce has survived the shake-up of the dot-com companies and is

proceeding to show positive growth.

Electronic commerce refers to conducting business transactions over the Internet, which

includes exchange of information of value in the form of products and services as well as

payments, using web-based technologies (Fraser, Fraser & MacDonald, 2000). The

emergence of electronic commerce is expected to change traditional business practices. The

great impact on businesses is anticipated as the advent of the World Wide Web has created

electronic or virtual marketplaces where trading could be conducted without any

geographical and time barriers. Electronic markets, which have the advantages of greater

reach and richness than the traditional markets (Tse & Soufani, 2003) has enabled firms to

contact more potential customers and exchange much more detailed information with them.

Indeed, e-commerce has already redefined relationship between suppliers and customers

(Daniel & Wilson, 2002). Rapid changes brought about by e-commerce have offered new

opportunities as well as threats for business organizations (Fraser et al., 2000). Kardaras et al.

(2000) suggested that many companies were making use of the opportunities to explore new

ways of doing business in order to deal more effectively with the increasingly competitive

environment. It is believed that electronic commerce will provide new sources of revenues

and prospects for companies that have well designed strategies.

The emergence of e-commerce has profound impact on industries as well as individual firms

in terms of the nature of competition as well as sources of competitive advantage (Pitts &

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Lei, 2000). Earlier researches have shown that electronic commerce has an impact on

competitive forces that affect the industries as well as the value chain of firms. According to

Haynes, Becherer and Helms (1998), the Internet has resulted in an increased number of

competitors as geographical barriers have broken down. One of the effects of e-commerce is

the levelling of strengths among competitors, as smaller firms are able to compete with larger

firms in terms of quality and accessibility. Javalgi and Ramsey (2001) argued that e-

commerce has created a large impact on businesses by improving distribution of resources,

relationships and efficiency of economies as well as increasing competitiveness and

diminishing costs. Fillis, Johansson and Wagner (2003) examined the adoption of e-

commerce by SMEs and found that SMEs could gain competitive advantage through

adopting e-commerce as it could improve their market performance by having better access

to the market. Evidently, e-commerce has the potential to help SMEs to achieve cost savings

by streamlining business processes by nature of its ability to handle information

electronically which enables faster and more efficient information processing over the

Internet and private networks, thereby reducing costs in areas such as searching and acquiring

customers, matching suppliers and buyers and reduction in the use of paper (Daniel et al.,

2002). Moreover, new communication technologies could transform the competitive

environment of all firms, irrespective of their sizes (Hughes, Golden & Powell, 2003).

Although electronic commerce was already well established in developed countries like the

US, Japan and the European countries, the concept of electronic commerce is relatively new

in Malaysia, especially in the smaller towns. While the use of electronic commerce

applications is on the rise in Malaysia, the level of adoption is not high. According to

McKinsey (2001), most Asian companies are slow in adopting electronic commerce as only

about 8% of the Asian companies have adopted e-commerce applications. Khatibi,

Thyagarajan and Seetharaman (2003) found that e-commerce is not well established in most

Asian countries as only a small percentage (23.7%) of the worldwide Internet users were

from the Asia-pacific region. Out of the total Internet population in the Asia-Pacific region,

the Malaysian wired population only constituted 1.2%, which is extremely low compared to

developed nations such as the USA (30%) and even other developed Asian countries such as

Singapore (14%). A recent research by Sulaiman (2000) revealed that although there was an

encouraging trend of e-commerce adoption among Malaysian businesses, the usage is still

limited. For example, while 71% of the companies surveyed use e-mail for communication

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purposes, only 16% conduct research on suppliers online and less than 7% engaged in online

payment such as the use of smart card.

The usage of e-commerce applications among the SMEs in Malaysia is even lower.

According to a recent report (Economist Intelligence Unit, 2001), only about 30% of the

Malaysian SMEs have adopted e-commerce applications, which is certainly low compared to

the approximately 80% in Europe. While the above statistics could provide some insight

about the usage of e-commerce in Malaysia, more current and detailed information regarding

commerce adoption especially among the SMEs is required as e-commerce is a rapidly

changing phenomenon. Therefore, there is a need to carry out additional research to obtain

the latest trend and statistics in the above area. The reason why SMEs are of particular

interest here is because SMEs form an important sector of a nation’s economy (Daniel et al.

2002; Tse et al. 2003) and any radical change in the way businesses are conducted in this

sector would have profound a impact on a nation’s economic growth

In view of the low usage of e-commerce among the SMEs in Malaysia, there is a need to

examine factors that could have contributed to the low e-commerce adoption among the

SMEs in Malaysia. Sulaiman (2000) and Khatibi et al.(2003) attempted to explore the

possible reasons by examining barriers that might hinder the adoption of e-commerce among

businesses in Malaysia. However, both papers were merely exploratory in nature without any

in-depth study regarding the hindering factors of e-commerce adoption. Besides, they

examined e-commerce adoption among firms in general without focusing on the SMEs. In

another study, Paynter and Lim(2001) examined the drivers and impediments to e-commerce

in Malaysia, but it focused only on the Internet users rather than the firms, although some

insights might be drawn surrounding the trend of Internet shopping, it did not provide much

clues with respect to the barriers to e-commerce implementation faced by firms in Malaysia,

particularly the SMEs.

This study will attempt to fill the gap by exploring the factors that might hinder the adoption

of electronic commerce applications among the small and medium enterprises in Northern

Malaysia. It could provide insights regarding the status of e-commerce adoption among

SMEs in this region. The reason why SMEs in Northern Malaysia were chosen is because this

region constitutes some of the most developed states in Malaysia and no research in similar

4

area has been conducted in this particular region. The above preliminary review and

arguments lead to the following research questions:

Research question 1: What is the extent of e-commerce adoption among the SMEs in

Northern Malaysia?

Research question 2: What are the benefits realized by SMEs in Northern Malaysia by

adopting e-commerce?

Research question 3: What factors could be hindering the adoption of e-commerce among the

SMEs in Malaysia?

1.2 Objectives of the study

The first objective of the research is to study the extent of e-commerce adoption among the

small and medium enterprises in Northern Malaysia.

The second objective is to assess benefits realized by SMEs in Northern Malaysia by

adopting e-commerce.

The third objective is to examine the factors that could be hindering the adoption of e-

commerce among the small and medium enterprises in Northern Malaysia.

It is hoped that the research findings would provide useful insight for academicians to

understand current state of e-commerce usage among SMEs in Northern Malaysia, which

includes the extent of adoption and benefits realized, as well as to identify factors that might

be hindering its adoption. It is also expected that the results will help SMEs as well as the

government in this region to overcome barriers and speed up the rate of e-commerce

adoption.

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Chapter 2: Literature Review

2.1 Types of e-commerce applications

According to Daniel et al. (2002), not many researches have been conducted to explore the

adoption of e-commerce by SMEs compared to studies on larger organizations in the same

area. However, based on the handful of previous studies on adoption of e-commerce

applications by SMEs as summed up by Daniel et al. (2002), usage of e-commerce could be

categorized into the following areas: communication, researching for information, marketing,

business with suppliers and business with customers. On the other hand, Martin and Matlay

(2003) found that the main applications of e-commerce are related to marketing activities. It

is suggested that common e-commerce applications such as email and websites could be

employed as cost-effective marketing tools in terms of information dissemination,

advertising, customers support and servicing as well as brand building (Auger & Gallaugher,

1996, Korgaonkar & Wolin, 2002). Further, Tetteh and Burn (2001) suggested that SMEs

could employ Internet infrastructure to develop a virtual community or rather a virtual

marketplace that could encourage interaction between manufacturers, service providers,

suppliers and customers through exchange of information via websites.

Website usage can be categorized into commerce, promotion, content, corporate information

and search agents (Hsieh & Lin 1998). According to Michalak and Jones (2003), the main

product of online commerce is information. Other e-commerce applications are online

transactions, which includes internet-based order processing and fulfilment (Phau & Poon,

2000) and supply chain management, which includes e-procurement and the use of EDI

(Murilo, 2001). Research by Hoffman, Novak and Chatterjee (1995) found that the basic

usage by commercial websites is in the area of marketing communication. Study by

Sulaiman (2000) in the Malaysian context suggested that e-commerce applications could be

categorised as electronic marketing, electronic advertising, customer support services,

ordering and delivery and online payment. Based on the above studies, the usage of e-

commerce could be summarised as:

(a) Marketing communication such as using email and websites to advertise products and

services as well as other information

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(b) Online transactions which include order processing and fulfilment as well as payment

facilitation

(c) Relationship management which includes customer support and service such as

providing web-based FAQ and auto-feedback

(d) Supply chain management such as online procurement, which includes the use of

EDI.

Although there are many possible uses of e-commerce, empirical studies showed that most

SMEs have not fully adopted e-commerce applications. According to a research conducted

by Poon and Swatman (1997), small businesses normally use Internet as a communication

tool and the most popular Internet-based communication tool is email. However, even e-mail

usage by SMEs was still very much lower than the usage of conventional communication

tools. A study by Chapman, Moore, Szczygiel and Thompson (2000) found that the usage of

Internet tools such as email by small and medium enterprises was lagging behind the larger

firms. The reasons that SMEs lagged behind in e-commerce usage could be because they

have less resources and expertise in implementing e-commerce applications.

Besides, most companies surveyed by Poon et al. (1997) did not implement advanced e-

commerce applications such as online order processing, electronic payments and so on.

Instead, empirical evidences showed that many firms have adopted basic web applications.

For example, according to a study by Kardaras et al. (2000) in Greece, a large number of

organizations were using Internet to provide information about products and services such as

prices, availability and new features. A survey study by Poon et al. (1997) found that many

firms use e-mail as a communication tool because it could enable asynchronous and

multimedia communication, and it is more cost effective. In fact, most SMEs surveyed by

Poon et al. (1997) were using the Internet for communication.

Mackay, Gemino, Igbaria and Reich (2001) in an empirical research in British Columbia

found that the majority of the SMEs use websites to share information with suppliers as well

as clients but only a handful of SMEs have adopted advanced e-commerce usage such as

online retailing and information sharing with their staff. This report is supported by a separate

study by Haynes et al. (1998) where it was discovered that Internet usage by most of the

companies is still relatively low. Besides, a survey by Mackay et al. (2001) also shows that

7

online transactions are rarely used by SMEs. From the above findings, the most commonly

used Internet applications were found to be e-mail and websites. On the other hand, there was

evidence that most businesses especially the SMEs are not keen to use Internet to access their

suppliers, contrary to the opinions of many researchers who believe that Internet could offer a

cost-effective supply chain management.

In addition, many other studies also showed that many firms have not made full use of

advanced Internet-based technologies such as relationship marketing to gain competitive

advantage. For example, LaMonica in 1999 (cited in La and Kandampully, 2002) pointed out

that many websites are slow to response or do not even response to inquiries from users. The

discrepancies between suggested usage and actual usage might be due to certain factors,

which could influence the extent of usage of e-commerce by SMEs. These factors are

explored in another section of this study.

2.2 Stages of e-commerce adoption

Although the previous section shows that SMEs have adopted many types of e-commerce

applications, they might be at different stages of adopting those applications in accordance

with the level of complexity. Therefore, it is important to examine the state of e-commerce

adoption among the SMEs. In order to study different stages of e-commerce adoption, a

conceptual framework is needed. One of the earliest models with respect to the usage of e-

commerce was proposed by Ho (1997) who has used this model to evaluate the value of the

commercial websites from different parts of the world. In his study, he categorised usage of

e-commerce into promotion of products and services, provision of data and information and

processing of business transactions. This model was then adapted and merged with the

Internet business models (APT, 1997) by Burgess and Cooper (1998) and developed into a

graphical model of e-commerce adoption which was labelled as Internet e-commerce staged

model. This model was later developed further by Lawson, Alcock, Cooper and Burgess

(2003) but without much modification to study the adoption of e-commerce by SMEs in

Australia. This model was termed as Model of Internet commerce adoption (MICA) and it

basically describes the three stages of e-commerce adoption proposed by Ho (1997) in

graphical form. Details of the three stages of e-commerce adoption are shown in Table 1.

8

Table 1: Stages of e-commerce adoption suggested by Lawson et al. (2003)

Stages Descriptions

Promotion Promotion of products and services

Provision Online enquiry, technical information, FAQ and value-added links.

Processing Online sales, online ordering and payments, order status enquiry, Links

warehouse and links distributors.

In addition, another adoption model known as the IBM model of stages and states suggested

by Stone (2003) categorises e-commerce adoption into the early stage, the integrating stage

and the advanced stage and these three stages again subdivided into six states as described in

Table 2.

Stone’s IBM model and MICA are similar. Beside these two models, there is yet another

model which was proposed by Rao, Metts and Monge (2003). It divides the stages of e-

commerce development into presence, portals, transactions integrations and enterprises

integrations. This model is summarised in Table 3.

Table 2: Stages and states of e-commerce suggested by Stone (2003, p.349)

Stages States Descriptions

Access Uses the web for email and support a simple web page.

Publish Maintains a multi-age web site and use it for email and

communication or publication of business information.

Early

Transact Enables customers to conduct one-way or two-way transactions.

Integrate

internally

Uses the web to integrated core business processes within the

organization.

Integrating

Integrate

externally

Uses the web to integrate business processes across enterprises

Advanced

Adapt

dynamically

Uses the web as the foundation for existing in a digital

community.

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Table 3: Stages of e-commerce suggested by Rao et al. (2003)

Stages Descriptions

Presence - Use web site to display information on products and services

- One way communication

- No integration with internal and external processes

Portals - Uses website for two-way communication with suppliers and customers

- Provide services such as ordering, product feedback, product survey and

customisations but without financial transactions

Transactions

integration

- Online financial transactions and order fulfilments

- Low level collaborations and e-marketplaces

Enterprises

integration

- Complete B2B and B2C integrations across value chains

- Implementation of CRM and SCM and full collaborations

2.3 Benefits realised through e-commerce adoption

Many theoretical and empirical studies have provided sufficient evidence that e-commerce

adoption can help firms to improve their performance and reap benefits. This section

examined whether these benefits have been realised by SMEs through e-commerce adoption

in the business-to-business area as well as in the business to consumer area.

2.3.1 Benefits of e-commerce adoption in B2B area

According to Subramaniam and Shaw (2002), the most important function in a business-to-

business trading is the procurement of products and services, which incurs the highest

expenditure among firms’ activities. Therefore, the analysis focused mainly on benefits

derived through improved procurement process enabled by web technologies. As e-

commerce is picking up its momentum, more suppliers could be accessed online, enabling

firms to have more options to select their suppliers (Haynes et al., 1998). With the availability

of more choices, the bargaining power has shifted to the purchasing firms over the suppliers.

In fact, according to Stone (2003), the value chains have become so open that buyers could

obtain real-time information such as prices and hence could bargain for better terms. Indeed,

10

the shift of bargaining power has enabled small firms to improve some of its value adding

functions such as improved cost control as well as getting better services from the vendors.

The implementation of electronic supply chain management was started with the use of EDI

via the Intranet in the 1970s (Murillo, 2001). However, supply chain management within e-

commerce via Internet-based EDI has begun to take shape in recent years. Gebauer and

Segev (2001) suggested that Internet and web technologies could help to improve the

procurement process by enabling access to pre-purchase information and facilitating

automations in many of its activities such as inventory management, making payment and

contract checking. It is found that web-based technologies such as Internet-based EDI is

particularly useful for SMEs by offering a cheaper way in supply chain management in

particular and adoption of e-commerce in general than the traditional more expensive

networks such as VAN. For example, web-based applications could automate many activities

in supply chain management such as providing online products related information including

pricing, online ordering and purchasing and exchange of documents. Wyld (2002) estimated

that companies could significantly cut down procurement costs by conducting purchasing

through the Internet directly.

Smaller firms could better manage their supply chains using e-commerce technologies

through shortening lead-time and better and more accurate order processing. Haynes et al.

(1998) argued that e-commerce could help smaller firms to manage their value chains

strategically, a thing that formerly only the larger corporations had the capability to

accomplish. Therefore, e-commerce has allowed smaller firms to gain some competitive

advantage over their suppliers. Fraser et al. (2000) study on e-commerce leads to the

suggestion of four sources of competitive advantage; among them is the effect on supply

chain management. It was said that E-commerce allows cost savings in purchasing activities

by cutting down time and effort in performing these activities.

Furthermore, smaller firms could also improve supply chain management through the web in

terms of reduced lead times and quicker and more precise order-processing abilities.

(Hoffman et al., 1995). By having easier access to the markets, small firms are able to skip

over parts of the value chain that traditional suppliers had depended on for competitive

advantage. As firms are now less dependent on particular suppliers, the bargaining power has

11

tilted from the suppliers to the purchasing firms. Gupta and Dubelaar (2000) observed that e-

commerce could streamline the procurement process by enabling electronic transactions and

standardisation of the trading process, thus allowing firms to focus on searching for suppliers

and bargain for better deals and reduced cost, which indirectly shifts the bargaining power to

the purchasing firms. The procurement benefits can be measured in terms of various cost

savings resulting from improved procurement activities. Organizational performance

variables can be measured by inventory level, inventory carrying cost, stock outs, order cycle,

fill rate, price and availability (Leonard & Cronan, 2002), which can be classified as

inventory management, costs savings as well as improved efficiency.

The above benefits could be summarised into a few categories. The first category of benefits

is related to improved searching capability enabled by e-commerce thus reducing search

costs. This in turn contributes to the reduction in transaction costs. Moreover, the Internet

enables firms to have more vendor choices as argued earlier; they could save purchasing costs

by bargaining for the best price. The second category of benefits were derived from improved

order processing involving electronic documents and information handling, therefore

reducing labour cost by eliminating the need to carry out those jobs manually (Subramaniam

et al., 2002). This will contribute to lower transaction costs. Web-based procurement system

can also cut data entry errors and this will also result in lower transaction costs. By having

automatic products request and order placement, it can also help to reduce transaction cycle

time. Reduction in transaction cycle time will lead to a more efficient inventory management

thus lowering inventory costs.

The last category of benefits is cost savings through better co-ordination between the

purchasing firms and their suppliers enabled by e-commerce technologies. These

technologies allow both firms to communicate and exchange information with their suppliers

more efficiently and in real-time, thus reducing communication costs as well as cycle time.

These will contribute to the reduction of transaction and inventory costs. Based on the above

analysis, the benefits brought about by B2B e-commerce are improved inventory

management, cost reduction as well as back-end efficiency, which is in line with the

measures proposed by Zhuang and Lederer (2003). The benefits of e-commerce could be

summarised in Table 4. The measures used to define e-commerce benefits match the items

listed in Table 5.

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Table 4: Summary of potential benefits of B2B e-commerce

Inventory management • Reduced lead-time (Fraser et al., 2000)

• Lower inventory costs (Subramanian et al., 2002)

Back-end efficiency • Better and more accurate order processing (Haynes et al., 1998; Subramanian et al., 2002)

Cost reduction • Reduced search costs (Subramanian et al., 2002)

• Reduced product price (Gupta et al., 2000)

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Table 5: Measures of electronic commerce benefits adapted from Zhuang and Lederer (2003)

E-commerce Benefits Items Sources Cronbach’s

Alpha

1. Back-end Efficiency

• Facilitated order entry processing

• Facilitated billing

• Facilitated electronic auditing

• Improved control of data

• Improved operational efficiency

• Facilitated shipment tracing

• Improved operational effectiveness

• Hansen & Hill (1989)

• Hansen & Hill (1989)

• Lee & Clark (1996-1997)

• Hansen & Hill (1989)

• Zhuang et al. (2003)

• Hansen and Hill (1989)

• Zhuang et al. (2003)

0.89

2. Market Expansion

• Provided access to new markets

• Provided opportunities to niche marketing

• Increased customer awareness of products/ services

• Provided customers with better information about products and services

• Increased sales

• Permitted differentiation of products/services

• Provided better information for management decision Making

• Zhuang et al. (2003)

• Zhuang et al. (2003)

• Zhuang et al. (2003)

• Zhuang et al. (2003)

• Zhuang et al. (2003)

• Zhuang et al. (2003)

• Zhuang et al. (2003)

• Hansen and Hill (1989)

0.86

3. Inventory

Management

• Streamlined the inventory replenishment

• Streamlined the procurement process

• Reduced the time required to repackage products/services

• Reduced inventory costs

• Zhuang et al. (2003)

• Zhuang et al. (2003)

• Zhuang et al. (2003)

• Zhuang et al. (2003)

0.88

4. Cost Reduction

• Reduced administrative costs

• Reduced customer support costs

• Reduced marketing costs

• Reduced information processing costs

• Zhuang et al. (2003)

• Zhuang et al. (2003)

• Zhuang et al. (2003)

• Hansen, and Hill (1989)

0.86

5. Customer Service

• Permitted better interaction with customers

• Provided customer intimacy

• Permitted better understanding of customers

• Helped maintain current customers.

• Zhuang et al. (2003)

• Zhuang et al. (2003)

• Zhuang et al. (2003)

• Zhuang et al. (2003)

0.79

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2.3.2 Benefits of e-commerce adoption in B2C area

Auger et al. (1997) found that the use of Internet helped businesses to gain better access to a

wider range of customers, due to the borderless nature of the Internet. Ritchie and Brindley

(2000) suggested that the Internet offers the opportunity for the smallest enterprises to

conduct businesses on a global scale, thus enabling the SMEs to compete with larger

organizations. Tetteh et al. (2001) advocated that Internet business offers a very attractive

choice for SMEs to broaden their market into a global scale without high expenditure. The

study by OECD (1998) found that electronic commerce could provide a better prospect for

SMEs to reach out to new markets on a global scale.

Quantitative data show that the Internet enables businesses to disseminate information at a

much lower cost than traditional media such as the print media (Auger et al., 1997). This

implies that small and medium enterprises could take this cost advantage to use the web as an

alternate or additional marketing channel such as placing online advertisements, catalogue,

support material and other information. Businesses are able to gather more information over

the Internet more easily as much more resources are readily accessible online than traditional

resources (Auger et al., 1997). This improved information gathering capability also applies

to smaller companies as the Internet enables them to gain access to a vast information

infrastructure and thus enabling them to communicate extensively with customers just as

efficiently as any large business organization (Poon et al., 1997).

Besides, Hoffman et al. (1995) also suggested that the web technologies enable firms to

conduct market research by gathering useful information related to customers’ preferences

and buying behaviours. This will enable firms to obtain more accurate information regarding

the needs and demands of the market (Reynolds, 1997), which will then help them to design

better marketing strategies. The above market research, which can also be termed as

customized research is normally monopolized by larger organizations, as the smaller firms do

not have enough resources to conduct such research (Haynes at al, 1998). However, Haynes

et al. (1998) suggested that the Internet would enable SMEs to overcome this through

examining customers’ comments and feedback over the web, which does not incur a very

high cost.

15

.

The development of electronic commerce has amplified competitiveness in the marketplace

to an extent that companies have to focus more on long-term relationship building in order to

retain loyal customers (Papadopoulou, Andreou, Kanellis & Martakos, 2000). Relationship

management includes business-to-business and business-to-customer relationship

management. In the business-to-business sector, trading between customers and suppliers has

long been conducted over private electronic networks such as EDI networks. However, e-

commerce technologies have greatly enhanced relationship between customers and suppliers

through interactive collaborations in new product development, integration of important

processes and cross-functional information sharing (Mclvor, Humphyeys and Huang, 2000).

One new phenomenon brought about by e-commerce was the development of new marketing

and sale strategies known as mass-customisation and personalised marketing enabled by

Internet technologies. These have great impact on the relationship between buyers and sellers

as they could revolutionise the way firms deal with their customers (Bloch, Pigneur & Segev

1996; Tse et al. 2003). The above strategies were made possible through the use of Internet

technologies to gather information on customers’ buying habits, preferences as well as taste.

Regarding this development, Wang, Head and Archer (2000) have provided a relationship

marketing model in the e-commerce context which comprises database marketing, interaction

marketing and network marketing. Traditional relationship marketing focuses mainly on

business-to-business marketing rather than business-to-customer marketing mainly due to

limitations in communication and data collection techniques and the high cost of

implementation.

Papadopoulou et al. (2000) also indicated that conventional customer relationship

management is very costly. However, Wang et al. (2000) suggested that these limitations are

greatly reduced in the Internet marketplace because the new innovations of advanced

Information and network technologies such as data warehousing and data mining have

enabled online user interaction and more effective data collection and analysis. Additionally,

Korgaonkar et al. (2002) suggested that e-commerce enables firms to develop and manage a

close bond with countless customers at the same instant through the Internet at a much lower

cost than conventional media. Therefore it becomes feasible to conduct relationship

marketing in the business-to-customer market over the Internet.

16

Wang et al. (2000) further suggested that web-based relationship management has enable

customers to acquire more thorough, custom-made, and up-to-date information. The

interactive nature of the web environment could significantly improve processes such as

information exchange, buying activities and after-sales services. Customers could exchange

information easily in the web environment therefore enhancing long-term relationship

building. Research by Hoffman et al. (1995) found that the web enables firms to manage and

improve customers’ relationship than traditional media. Web technologies also help to

enhance relationship between firms and their customers (Maes, Guttman & Moukas, 1999).

Besides, response time to inquiry from customers could be greatly reduced through electronic

dissemination of information enabled by the web technology (Auger et al., 1997). These

mean customers would be able to search for information faster and more accurately online.

Tang, Powell, Worlock & Bingham (2000) examined the impact of e-commerce and found

that Internet could facilitate quicker responses to customer needs and the changing nature of

the marketplace. By providing better customer support through more efficient handling of

customer feedback, businesses could greatly enhance their relationship with the customers.

In another study, Haynes et al. (1998) found that web tools such as FAQ (Frequently Asked

Questions) provides a low cost mean for smaller firms to build and maintain relationships

with their customers. Besides, the web has the potential to facilitate customer interaction,

enable relationship marketing and improve customer support (Hoffman et al., 1995). Tse et

al. (2003) research found that smaller firms are better in carrying out the activities with

respect to customers’ relationship management especially in relation to niche markets as they

have more flexibility. This will lead to collaboration between SMEs and their customers in

product development. By involving customers in the product development process will allow

customers to have more bargaining power thus forcing firms to improve customer support

and service and lead to better relationship between firms and customers.

In the context of SMEs, the emergence of new relationships between suppliers, firms and

buyers brought by e-commerce has a great impact on their value adding activities. According

to Filis et al. (2003), the Internet has permitted SMEs to obtain information from an

information infrastructure much bigger than those that belong to many big business

organizations. Better access to information and improved communication with their suppliers

as well as customers and business partners has enabled smaller firms to boost their value

17

adding activities within the value chain such as new product development and improvement

in service quality. Indeed, e-commerce has enabled SMEs to enhance relationship with their

suppliers and customers, as electronic networks such as the Internet is able to transmit rich

information between all parties in an electronic market. Through the Internet, even small

firms are able to reach suppliers and customers without being limited by physical barriers

such as the distance between markets. Therefore, it could be seen that SMEs are also

following the trend of getting into a more collaborative relationship with their suppliers as

well as customers in an effort to develop better products as well as providing better services.

The benefits of e-commerce adoption could also be gained through a process called

disintermediation. Firms could now omit parts of the value chain and have direct access to the

end users. In doing so they are bypassing the intermediaries (Allen & Fjermestad 2000; Stone

2003, Hoffman et al., 1995). Besides, Hooft and Stegwee (2001) argued that Internet

technologies could facilitate direct connection between different levels of the supply chain

without going through the intermediaries, hence making the e-market more transparent. Tse

et al. (2003) suggested that intermediaries have become irrelevant because everyone could

communicate with each other through the Internet. By not engaging the traditional

intermediaries to perform part of the functions in their value chain, firms are able to save

considerable transaction costs (Javalgi et al., 2001).

Chopra and Mieghem (2000) have provided a comprehensive analysis on the benefits of e-

commerce from the perspectives of cost and revenue. First of all, it was pointed out that firms

could boost their earnings by selling directly to the buyers enabled by disintermediation. E-

commerce could also streamline marketing management through online information

dissemination about products and services as well other relevant information. By having

online promotions, time to market is greatly reduced. Furthermore, the online nature of e-

commerce permits firms and customers to discuss price, service and products thereby

resulting in product and price customisation and thus enabling better support and service for

the customers. Another advantage of e-commerce is that it allows firms to reach potential

customers irrespective of geographical and time barriers, thus providing an excellent prospect

for market expansion and increased profits. Finally, Chopra et al. (2000) suggested e-

commerce could help to reduce order-processing costs as well streamlining order fulfilment

process and costs.

18

Based on the above literature on the impact of B2C e-commerce, the adoption of e-commerce

applications could help firms including the SMEs to improve their business performances

through lower information dissemination costs, better access to wider range of customers and

prospect to increase market share. Besides, the use of e-commerce applications could also

enable firms to provide better service and support to customers by managing customer

relationship more efficiently, better understanding of customers’ needs and preferences

through low cost market research, lower search costs as well as opportunities to develop new

products through collaborative efforts with the customers. Putting the above benefits

together, they could be fitted into the categories suggested by Zhuang et al. (2003), namely

market expansion, customer service, and back-end efficiency and cost reduction. They are

summarised in Table 6.

Table 6: Summary of potential benefits of B2C e-commerce

E-commerce benefits

Measures

Market expansion • Prospect to increase market share (Fraser et al., 2000)

• Better access to wider range of customers (Auger et al., 1997)

• New sources of revenues (Fraser et al., 2000)

• Better access to information (Fillis et al., 2003)

• Faster time to market (Chopra et al., 2000)

Customer service • Better support and service through CRM (Hoffman et al,

• 1995

• Better interaction with customers (Korgaonkar et al, 2002)

• Better understanding of customers’ needs and preferences (Reynolds, 1997)

• Faster response time to enquiry (Auger et al., 1997)

Back-end efficiency • Improved operational efficiency (Zhuang et al., 2003)

•

Cost reduction • Lower information dissemination costs customers (Auger et al., 1997)

• Lower marketing costs (Auger et al., 1997; Haynes et al., 1998)

19

2.4. Factors hindering the adoption of e-commerce

Many factors could be responsible for the low usage of e-commerce among the SMEs in

Malaysia. MITI (1999) suggested that the barriers behind the low adoption of Internet

applications among the SMEs in Malaysia could be due to lack of understanding about e-

commerce, doubts about its benefits, lack of qualified IT human resources, high

implementation cost and worry about security. Furthermore, Economist Intelligence Unit

(2001) also reported that credit card users in Malaysia are not willing to buy through the

Internet due to security concerns. This might explain the slow adoption of e-commerce usage

among businesses in Malaysia.

The preceding reports seem to match a study done by OECD (1998) on hindrances to e-

commerce adoption in OECD countries. The study suggested that those hindrances are lack

of understanding and awareness about e-commerce benefits, security concern, lack of

products suitable for e-commerce, set-up cost and lack of Internet legal system. A more up-

to-date survey by OECD (2002) showed that barriers to e-commerce among businesses

remain basically unchanged, where slackness in Internet security is the main concern.

However, the report did indicate that there exist some differences between small and large

firms regarding the barriers of e-commerce, where larger firms are more concern about

security than smaller firms and smaller firms rate the cost factor as a greater obstacle in e-

commerce adoption than the larger firms.

The above findings were more or less consistent with some of the inhibitors of e-commerce

adoption by SMEs in Australia listed by Pease and Rowe (2003) as lack of awareness and

understanding of e-commerce, lack of skill and time to implement e-commerce, resistance to

technological changes, cost of implementation, lack of awareness of the benefits associated

with the adoption of e-commerce, worry about security and privacy, lack of suitable software

standards, lack of easily accessibility and bandwidth and infrastructure issues. On the other

hand, telecommunication infrastructure issues could be linked to insufficient support from the

government. For example, Michalak et al. (2003) suggested that one of the reasons that e-

commerce in Canada was lagging behind the USA is because of slower bandwidth as most

telephones lines could only support the connection speed of 56.6 kbps. This situation is not

20

expected to change as the Canadian government has delayed the project to enable broadband

access for majority of the Canadian population.

Research by Raymond (2001) found that adoption of innovative technologies could be

influenced by environmental and organizational factors. One of the organizational factors is

the lack of resources. In addition, Auger et al. (1997) identified the following factors that

might hinder the adoption of e-commerce, namely, the problem in tracking online users,

security issues, bandwidth problem, insufficient company resources – in terms of availability

of qualified IT personnel and suitability of products that could be marketed online. In a

separate study, Clarke (1999) also suggested that reluctance to change and poor infrastructure

and slackness in technology as barriers to implementation of business-to-business e-

commerce. Besides, earlier study by Hoffman et al. (1995) asserted that the main obstacle

related to e-commerce adoption is Internet accessibility problem, which includes issues such

as insufficient bandwidth, security and privacy and technological issues

Useful insight about the hindering factors on e-commerce usage among SMEs could also be

drawn from a study on obstacles that might affect the adoption of EDI among the small firms

in the US by Jun and Cai (2003) as EDI and e-commerce have similar characteristics because

both involve in business transactions over electronic networks. EDI is B2B electronic

commerce conducted over a private network. Jun et al. (2003) proposed that hindering factors

are issues related to managerial support, costs and benefits, technical complexity, human

resource management, relationship with trading partners, security risks and legal problems. In

addition, a research about the impact of e-commerce on the competitiveness of SMEs in EU

highlighted barriers surrounding the adoption of e-commerce by SMEs as cost constraints,

lack of IT expertise and lack of management foresight (STOA, 2000).

One of the major issues that could hinder e-commerce implementation is the perceived

security risks and trust issues related to business dealings over the Internet (Labuschagne &

Eloff, 2000). It was suggested that two kinds of risks could be encountered in the electronic

market, namely business risks and technological risks. Some of the business risks are IT

crimes, over-dependence on technology, a rapidly changing or volatile business and

technological environment and lack of qualified information-security personnel. On the other

hand, examples of technological risks are difficulties in ensuring security over the Internet

21

due to its vastness and complexity, rising hacking activities due to easy access to hacking

tools, and difficulties in the prevention of hackers’ attack due to unpredictability associated

with Internet technologies. In a separate study, Furnell and karweni (1999) also stressed that

security has not been fully established for trading over the Internet. Although currently two

systems are employed to handle secured online transactions, namely Secure Sockets Layer

(SSL) developed by Netscape and Secure Electronic Transaction (SET) developed by major

credit companies, they have not provided complete solutions to online security and trust

issues. Indeed, the empirical study by Furnell et al. (1999) found out the main factors that

deter people who were not shopping on the Internet were insecure Internet infrastructure and

perceived dishonesty of the merchant.

Problems associated with trust in the electronic market can be non-technical in nature but

rather has something to do with branding. According to a study by Boston Consulting Group

in 2000(Reynolds, 2000), trust is an important element in establishing brand in the electronic

market. Indeed, Reynolds (2000) suggested that trust is more important in e-commerce than

conventional market because consumers are comparatively unfamiliar with the Internet

environment and the many new online brands. Furthermore, trust is vital in B2B e-commerce,

as it is one of the important characteristics of vendors with respect to electronic transactions

(Swaminathan, Lepowska-White & Rao, 1999). In addition, lack of trust could be due to the

perceived risks of the products offered in the electronic market as online customers cannot

touch and feel the products physically (La et al., 2002). Empirical studies found that most

consumers still have no trust in online stores (Jarvenppa & Tractinsky, 1999).

In addition, a big concern about e-commerce is the use of certain e-commerce technologies

such as cookies that could potentially threaten individual privacy and confidentiality

(Whysall, 2000). Besides, intellectual property may not be well protected, as there are many

pirated versions of well-known brands such as McDonald and Levi’s. In Malaysia, the study

by Sulaiman (2000) indicated that the reasons for low adoption of e-commerce applications

among Malaysian firms are insufficient security, sales and marketing which required high

human interaction and the high costs of setting up e-commerce. Malaysian companies listed

hindrances of e-commerce adoption as problems keeping up with changing technology, lack

of skill workers, uncertainties about its operations and legal aspects as well as high switching

costs (Khatibi et al., 2003).

22

2.5 Conceptual model and hypotheses

Research concerning factors affecting adoption of e-commerce especially among the SMEs is

still at an exploratory stage, as e-commerce is still a relatively new business practice.

Therefore, a conceptual framework was developed in this study to examine the factors that

might hinder the adoption of e-commerce by SMEs in Northern Malaysia.

The conceptual model was built by adapting a model developed by Love, Irani, Li, Cheng

and Tse (2001) as well as findings from other studies, including literature reviewed earlier. In

this model, Love et al. (2001) classified the barriers under four categories, namely

organizational, technical, financial and behavioural barriers. This model is shown in Figure 1.

Figure 1: Barriers to adoption e-commerce illustrated by Love et al. (2001, p.37)

Most of the past researches seemed to match the barriers’ groupings suggested by this model,

although some barriers suggested by other researches could not properly fit into it. For

instance, a study by Wirtz and Wong (2001) on B2B e-commerce found that the main barriers

affecting e-commerce implementation among non-adopters were security issues, customers as

well as firms not ready for e-commerce, and lack of in-house competence. Besides, the study

further pointed out that in addition to the above barriers, firms who were interested in

adopting e-commerce also cited the high set-up cost as another obstacle to e-commerce

implementation. From the above study, the security issues could be classified as technical

barriers, firms not ready for e-commerce could be classified as an organizational barrier, set-

Technical Organizational

Barriers

Behavioural Financial

Change

Uncertainty

Risk

Knowledge

23

up and maintenance costs could be categorized as the financial barriers and lack of in-house

competency could be put under the organizational barriers. However, customers’ and

suppliers’ readiness could not be suitably classified under any of the categories. As these two

factors are external to organization, it is suggested that they be put under a new category,

which could be named as the business environment.

Moreover, some of the items from one category could be merged with another category. For

example, all the items under behavioural could be moved to the organizational category as

these barriers are related to employees’ attitudes in the organization. Therefore, regrouping

of the item seems to be necessary. Combining Love et al.’s model and other literatures would

produce the model required in this study. For example, Lawson et al. (2003) classified the

barriers into technical and social. It was suggested that slackness in telecommunication

infrastructure and lack of security in online transactions could be considered the technical

barriers while lack of trust in ICT, lack of knowledge about e-commerce and lack of IT skills

as well as lack of awareness could be grouped under the social barriers. These barriers could

fit quite nicely into Love et al.’s model except that the social barriers need to be put under the

organizational category.

On the other hand, Gibbs, Kraemer and Dedrick (2003) examined two types of macro-level

factors that might influence the adoption of e-commerce, namely national environment and

national policy. According to Gibbs et al. (2003), national environmental factors are factors

related to demographics, economic and financial resources, information infrastructure,

industrial structure and competition, organizational environment as well as social and culture.

National policy is related to issues such as liberalization of telecommunication and ICT

markets, government support in promoting e-commerce activities as well as e-commerce

legislation. Further more, Lawson et al. (2003) also found that the lack of government

incentives as one of the barriers to e-commerce adoption. Therefore, two new categories of e-

commerce barriers were added here, which are environmental and governmental factors.

Putting these two new categories into Loves’ model formed the conceptual as illustrated in

figure 2.

24

Figure 2: The conceptual model to examine factors that hinder the adoption of e-commerce

The technical barriers were described by Love et al. (2001) as problems related to acquiring

suitable technologies to meet business requirements, lack of education and expertise about

the system requirements and risks related to security and authentication. These barriers could

prevent firms especially the smaller businesses to adopt e-commerce applications. Indeed, a

number of studies indicated that technical issues especially those related to security risks

were hindering the adoption of e-commerce (Lawson et al. 2003; Sulaiman 2000; Furnell et

al. 1999; Nambisan & Wang 1999). The preceding discussions led to the first hypothesis:

H1: Factor related to technical barriers has negative influence on e-commerce adoption

According to Love et al. (2001), the financial barriers to e-commerce adoption are those

issues related to the set-up and maintenance cost of the e-commerce system as well as

investment risk, training cost and cost incurred because of market uncertainty. It was pointed

out that without sufficient investment in ICT, small firms will not be able to gain any benefits

from e-commerce (Love et al., 2001). Many previous studies suggested that the high cost

requirements in setting up e-commerce system have prevented businesses particularly the

SMEs to adopt e-commerce applications (Sulaiman 2000; Khatibi et al. 2003; Fillis et al.

2003; Lawson et al. 2003). Therefore, the factor related to financial barriers could be a

roadblock to the adoption of e-commerce by the SMEs. The above arguments led to the

following hypothesis:

Technical barriers

Organizational barriers

Extent of e-commerce

adoption

Governmental barriers

Financial barriers

Environmental barriers

Behavioural barriers

25

H2: Factor related to financial barriers has negative influence on e-commerce adoption

The organizational barriers that could discourage the adoption of e-commerce by firms

especially the SMEs are issues such as lack of employee knowledge, lack of an IT

infrastructure, reluctance to collaborative partnership (Love et al., 2001), lack of managerial

support and organizational readiness (Jun et al., 2003). A number of studies (Chau & Hui

2001; Lawson et al. 2003; Khatibi et al. 2003) found that the lack of employee skill and

knowledge particularly in IT was found to be a significant barrier to adoption of e-commerce.

The above arguments led to the formulation of the next hypothesis:

H3: Factor related to organizational barriers has negative influence on e-commerce adoption

Lawson et al. (2003) found that one of the main barriers to e-commerce adoption by the

SMEs in Australia was the lack of government incentives. In contrast, it was found that the

adoption of e-commerce by businesses in Singapore was very encouraging because the

government has played an important role in promoting and supporting the use of Internet

(Chan & Al-Hawamdeh, 2002). Additionally, Gibbs et al. (2003) argued that the government

could play a crucial role in driving e-commerce adoption through the establishment of

various policies such as deregulation of the telecommunication sector and the legislation of

cyber law, as well as its initiatives in promoting the use of Internet among the business

sectors by providing training and funding. Therefore, it could be assumed that the

government is vital in spearheading the adoption of e-commerce among businesses,

especially the SMEs. Conversely, the lack of government support and effort would mean that

adoption of e-commerce would be slow. Indeed, the study by Michalak et al. (2003) showed

that Canadian businesses were much slower in e-commerce adoption than their USA

counterparts as there was lack of support from the government. The preceding discussions led

to the following hypothesis:

H4: Factor related to governmental barriers has negative influence on e-commerce adoption

A study by Gibbs et al. (2003) showed that the environmental factors such as the

characteristics of a market that include demographics and consumer preferences, as well as

organizational environment, could encourage or inhibit e-commerce adoption by firms. For

26

example, the preceding study found that countries with low IT literacy and underdeveloped

telecommunication infrastructure have low diffusion of e-commerce both in the B2C and

B2B areas. On the other hand, issues related to the organizational environment such as

readiness of trading partners could affect the adoption of e-commerce (Jun et al., 2003). If

trading partners such as the suppliers have not adopted e-commerce, it would be difficult for

firms to perform e-commerce transactions. The above arguments led to the following

hypothesis:

H5: Factor related to environmental barriers has negative influence on e-commerce adoption

The behavioural barriers to e-commerce adoption are related to attitudinal issues involving

people in an organization. E-commerce development has brought about rapid changes in the

way business is conducted. However, many people are reluctant to change themselves in

order to adapt to the new working routines, and they are worry about the need to participate

in extra staff development and training programme to improve their skills (Love et al., 2001).

Thus, the negative behaviour of its staff could prevent a firm from adopting e-commerce.

However, there is need to test the following hypothesis in order to confirm or reject the above

assumption.

H6: Factor related to behavioural barriers has negative influence on e-commerce adoption

27

Chapter 3: Research Design and Methodology

3.1 Measurements development

3.1.1 Measurement of e-commerce usage

The conceptual models discussed earlier had provided a comprehensive picture about the

stages of e-commerce adoptions and a basis for the development of measures of e-commerce

usage. However, due to the facts that the adoption of e-commerce among firms especially

among the SMEs in Malaysia was low (Sulaiman, 2000; Khatibi et al., 2003), a simpler

adoption model is needed. In fact, Sulaiman classified e-commerce applications into five

categories namely electronic marketing, electronic advertising, customer support services,

order and delivery and online payment. The model developed in this study used all the stages

of e-commerce adoption in MICA and some of the stages in the IBM model and the model

proposed by Rao et al. (2003), as well as some of the e-commerce applications mentioned in

the studies by Sulaiman (2000) and Khatibi (2003). The proposed conceptual model of e-

commerce adoption is illustrated in Figure 3. However, this model will not be used to test any

hypothesis. Instead, it will be used to measure the state of e-commerce adoption by the SMEs

in Malaysia. It is suggested that a firm will be placed in a certain stage as long as it has

adopted one of the applications in that stage.

Figure 3: Conceptual model of stages of e-commerce adoption

Stage 1: Promotion

. Email . Simple web page . Electronic advertising

Stage 2: Provision . FAQ . Online Enquiries . Value added info . Customer support services . Electronic

Stage3: Transaction

. Online sales

. Online orders . Order fulfilments . Online payments . Order status

Stage 4: Integration . Linked warehouse . EDI . SCM

28

Additionally, the measurement of e-commerce usage will be adapted from the measures used

by Sulaiman (2000) who categorized the usage of e-commerce into electronic marketing,

electronic advertising, customer support service, order and delivery and payment system. The

detail items under each category were adapted from the measures used in the e-commerce

research by the National Productivity Corporation (2000). These measures are shown in

Table 7.

Table7: Usage of electronic commerce

E-commerce Applications

Electronic Marketing

Research on consumers preferences

Research and evaluation of new suppliers

Research on Competitors

Electronic Advertising

Displaying company information and products/services offered

Web site hosted by another company

Web site hosted by own server

Advertising on third party web site

Electronic catalogues

Customer Support Service

Online help- Frequently Asked Questions

Online help- products updates

Handling customers feedback/queries online

Personalised email communication

Online application/registration

Order and Delivery

Processing sales order from customers online

Coordinating procurement with suppliers online

Tracking incoming and outgoing goods delivery

Electronic Data Interchange (EDI)

Payment System

Electronic Fund Transfer (EFT)

Online credit card processing

Smart card

Prepaid card

29

3.1.2 Measurement of e-commerce benefits

The conceptual model of e-commerce benefits was built based on a model proposed by

Subramaniam et al. (2002), which laid down constructs that could be applied to measure the

benefits of e-commerce and other literatures. This model attempts to assess the impact of e-

commerce on firms’ business processes that are related to supply chain management and to

examine whether the improvement in those processes might lead to increased companies’

performance. However, the model was only focusing on the business-to-business

transactions while ignoring the B2C area. As many SMEs are also involve in B2C

transactions, a model that is used to evaluate the benefits of e-commerce should also examine

its effects on the value-adding activities in the business to consumers’ area. To investigate the

impact of B2C e-commerce, a number of prior researches were reviewed and the study by

Zhuang et al. (2003) was selected because an instrument for measuring the business benefits

of e-commerce retailing was available in this paper. Therefore, the proposed conceptual

model was developed based on the model constructed by Subramaniam et al. (2002) and the

measures of B2C e-commerce benefits suggested by Zhuang et al. (2003), as well as other

literatures that have presented some kinds of measures on benefits of e-commerce such as the

model on impact of e-commerce on organizational performance by Leonard et al. (2002).

In this model, the firm performance is measured in terms of productivity, sales, profitability,

competitive position and overall performance (Powell & Dent-Micallef, 1997). In another

study, Leonard et al. (2002) suggested that the firm performance is normally quantified as

return on investment, return on assets and market share, which are financial indicators related

to profitability. Besides, the model also shows the benefits that could be realized through e-

commerce adoption. These benefits are improvement in back-end efficiency, market

expansion, and inventory management, cost reduction as well as customer service, which

could contribute to the improvement in firm performance. The model is depicted in Figure 4.

The above model will not be used to test any hypothesis but to develop measures for the

purpose of assessing benefits of e-commerce adoption. The measures of e-commerce benefits

will be adapted from the instrument developed by the National Productivity Corporation of

Malaysia, which was used to conduct nation-wide e-commerce research in Malaysia in 1999.

This instrument was selected because the measures used matched those suggested in the

30

model and fewer items were used compared to that proposed by Zhuang et al. (2003). The

survey instrument with fewer items was necessary as the respondents might find it difficult

and time consuming to answer the items if there are too many of them in the questionnaire.

Besides, the instrument was used in the survey in the Malaysian context. These measures,

which comprise 12 items, are listed in Table 8.

Figure 4: The conceptual model to assess the benefits of e-commerce adoption

Table 8: Measures of e-commerce benefits

No. Benefits of e-commerce Items

1. Market expansion Increase in market share Enhance company brand and corporate image

2. Customer service Improved customer service Increased accessibility to the end-users

Increased responses from end-users

Increased customer loyalty and retention

3. Back-end efficiency Improved business processes flow

4. Cost Reduction Reduce in cost

5. Inventory management Increase in efficiency in dealing with suppliers

6. Firm performance Increase in profit Increase in productivity

Increase in Return on Investment

Firm Performance 1. Productivity 2. Sales 3. Profitability 4. Competitive position 5. Overall performance

Powell et al. (1997), Zhuang et al. (2003)

Cost Reduction

Market

Expansion

Customer

Service

Back-end

Efficiency

Inventory

Management

31

3.1.3 Measurement of factors hindering the adoption of e-commerce

Measures of e-commerce barriers were adapted from the instrument developed by the

National Productivity Corporation of Malaysia, which was used to conduct nation-wide e-

commerce research in Malaysia in 1999 (National Productivity Corporation, unpub.). These

measures are the independent variables of the conceptual model that was developed earlier

pertaining to factors hindering the adoption of e-commerce. These measures are categorized

in Table 9. The dependent variable, extent of e-commerce adoption was computed by adding

the number of e-commerce applications adopted by the SMEs.

Table 9: Measures of e-commerce barriers

Barriers Items Item label

Financial Cost of setting up e-commerce is high V1

Need additional staff to manage e-commerce applications V2

Difficult to justify the cost with desired benefits V3

Environmental Information from e-commerce is not useful V4

Market potential of e-commerce users is too small V5

E-commerce is not as effective as traditional channel V7

Most suppliers do not have access to e-commerce V8

Insufficient qualified vendors for developing applications V12

It will upset existing distribution channels V9

Organizational Our sales/marketing requires high degree of human interaction V6

Lack of skilled workers to handle or maintain e-commerce V13

Lack of knowledge about the potential applications of e- V14

Weak support from top management V18

Technical Insufficient security for online credit payment and transactions V10

Insufficient security to prevent hacking and viruses V11

Governmental Lack of standards/regulations from government on e-commerce V15

Telecommunication infrastructure is not adequate V16

Lack of government leadership V17

Behavioural Keeping up with changing technology V19

Mindset shift towards using e-commerce V20

32

3.2 Research Method

The survey method was chosen in this study. This approach was used because the study

attempted to gather information from a large number of respondents who are spread widely

geographically. Besides, it intended to test several hypotheses empirically. The questionnaire

was adapted from the research instrument designed by the National Productivity Corporation

–University of Malaysia research team. This was validated and used in a nationwide e-

commerce research in Malaysia in 1999(National Productivity Corporation, unpub.).

The first part of the questionnaire consists of dichotomous questions that require the

respondent to indicate types of e-commerce applications they are using as well as those that

are not being used. These questions are categorized into electronic marketing, electronic

advertising, and customer support service, order and delivery and payment system. The

second part of the questionnaire consists of mostly Likert scale type of questions. There are

20 items on a 5-point Likert scale questions that require respondents to rate the hindrances of

e-commerce where 5 indicates very high hindrance while 1 indicates very low hindrance. The

third part of the questionnaires consists of Likert scale items that measure benefits of e-

commerce for those who have adopted e-commerce, where 1 indicates very high profit while

5 indicates virtually no benefit. The last part of the questionnaire consists of questions about

the profile of the firm that includes questions like what sector the firm is in, type of industry

or business involved, sales turnover, amount of investment in electronic commerce and so on.

3.3 Population and Sample

The population of this study comprised SMEs of Northern Malaysia. SMEs are often defined

based on certain quantitative measures such as the number of staff, the amount of capital, the

amount of assets and sales turnover. In Malaysia, the more commonly accepted definition is

the one given by the Ministry of International Trade and Industry of Malaysia and Hashim

(1999, p41), stated as follows:

‘i. A small-sized firm is a firm with less than 50 full-time employees, and with an annual

turnover of not more than RM10 million.

ii. A medium-sized firm is a firm with between 51 and 150 employees, and with an annual

turnover of between RM10 million and RM25 million.’

33

Therefore, the definition of SME is defined as a firm with no more than 150 employees and

an annual sales turnover of no more than RM25 million. Although this definition could be

used for the purpose of this research, discretion and flexibility need to be exercised. The

reason is that this definition might not sufficiently classify firms that could only fulfill one of

the conditions. For example, a firm with an employee of more than 150 but with an annual

turnover of much less than RM25 million might still need to be considered as SMI although it

could fulfill one of the stated conditions. This is true especially for labour intensive

industries. On the other hand, a firm with only 50 employees but with an annual turnover of

more than RM25 might not be considered as SMI. In order to solve the above problem, all the

firms in the chosen sampling frames would be classified as SMEs even though they might not

fulfill the conditions perfectly, as long as the discrepancy is not too great.

Northern Malaysia is an area that includes the four northern states of Perlis, Kedah, Penang

and Perak with a total area of 32253 km2. The total population of the four states is 5, 218,891,

which make up 22.4 % of the total population of Malaysia. The largest state is Perak in terms

of area as well as population but Penang has the highest urban population. The smallest state

is Perlis both in terms of population and area as well as the urban population. The above

figures were obtained from census of the year 2000 released by the statistical department of

Malaysia. Details of the statistics are listed in Table 10.

Table 10: Statistics of the area and population of Perak, Penang, Perlis and Kedah

Perak Penang Perlis Kedah Total

Area (km2) 21002 1031 795 9425 32253

Population 2,051,236 1,313,449 204,450 1,649,756 5,218,891

% of National Population

8.8 5.6 0.9 7.1 22.4

Urban Population 58.7% 80.1% 34.3% 39.3%

Source: Malaysian Statistical Department

34

Two sampling frames were used in the study. The first sampling frame comprises 424 small

and medium enterprises of Northern Malaysia who were listed in the latest official business

directory of SMI Association of Malaysia, which was compiled in the year 2002. The second

sampling frame was a list which comprises 167 firms compiled by the Penang Development

corporation from various sources of industrial associations such as SAMENTA, Malaysian

Plastic Manufacturers Association (MPMA), Credit Guarantee Corporation website and SMI

directory. The questionnaires were mailed to the respondents in the sample frame.

3.4 Data Analysis

As the first part of the paper is to assess the state of e-commerce adoption among the SMEs

in Northern Malaysia surveyed in this study, frequency distributions will be used to describe

the number as well the types of e-commerce applications being implemented. Besides, the

study will also use frequency distributions to evaluate the stage of e-commerce adoption by

the respondents in the sample obtained.

Descriptive statistics will be used to evaluate the benefits realized by the SMEs surveyed in

this research. Means for each benefit will be obtained using the SPSS software. As the Likert

scale used to measure the benefits is 1 for very high profit and 5 for virtually no profit, a

mean with value less than 3 will imply that that particular benefit has been realized while

those with means more than or equal to 3 will imply that those benefits have not been

realized.

To analyse the factors that might hinder the adoption of e-commerce, a number of statistical

methods will be used. First of all, factor analysis with varimax rotation will be employed to

reduce the variables that are used to measure hindrance of e-commerce into fewer numbers of

factors. The factors will be categorized based on suitable factor loadings depending on the

sample size. The grouping of variables into various factors will be used to compare the

factors that were categorized under the proposed conceptual model. Reliability analysis will

also be performed to examine whether the factors obtained above were reliable measures or

not. Any factor with Cronbach’s alpha less than 0.7 will be discarded, as it will not be

considered reliable (Hair, Anderson, Tatham & Black, 1998). The above analysis will be

done using the SPSS software.

35

Next, correlation analysis will be used to examine whether there is any association between

each of the factors and the extent of e-commerce adoption. The extent of e-commerce

adoption will be computed by adding the number of e-commerce applications being adopted

by the respondents, which means that the higher the score, the higher the adoption and vice

versa. Lastly, in order to examine whether the factors have any influence on the extent of e-

commerce adoption, that is to test the hypotheses formulated earlier, regression analysis will

be used. For the purpose of regression analysis, the extent of e-commerce adoption is the

dependent variable while the factors are the independent variables. It will be performed using

the SPSS software.

36

Chapter 4: Analysis and Findings

A sample of 65 responses was obtained from the first sampling frame, out of which 61 were

usable; this gave a response rate of 14.3 percent. The sample size was further reduced to 53

after rejecting four public listed companies and five of them with more than 300 employees.

The questionnaires were later sent to the second list of 167 firms and a sample consists of 15

usable responses were obtained, which gave a response rate of about 9 %.

The low response rates could be explained by the growing trend that people are reluctant to

response to random questionnaire survey (Bryman, 1989). In order to assess the differences

between the two samples, t-tests were conducted using key variables such as the usage of e-

commerce, paid-up capital, investment in IT and websites. It was found that no significant

differences exist between the two samples and so the two samples were combined to make a

single sample, which comprises 68 respondents. Although the sample size is not very big, a

sample size of more than 30 could be considered sufficient for most research (Sekaran, 2000).

4.1 Profile of the organizations

Most of the firms participated in the survey are in the manufacturing sector as shown in Table

11. Out of the total valid sample, 86.4 % of the firms are involved in the manufacturing

sector, while the rest of the firms are in other sectors.

Table 11: Classification of firms by business sector

Sector Frequency Percentage Valid Percentage

Construction 1 1.5 1.5 Wholesale 2 2.9 3.0 Retail 2 2.9 3.0 Manufacturing 57 83.8 86.4 Others 4 5.9 6.1 Total 66 97.1 100.0 Missing data 2 2.9

68 100.0

37

4.2 Usage of electronic commerce applications

Initial results from Table 12 indicated that most SMEs in Northern Malaysia are at a fairly

high state of e-commerce adoption. Out of the firms surveyed, 11.4% of them have not

adopted any e-commerce application, 2.9% are at the promotion level, 29.4% are at the

provision stage, 27.9% are at the transaction stage while as high as 27.9% have moved on to

the integration stage. However, the figures might not be very accurate as the firms were

classified in a certain stage as long as they have adopted one of the applications in that stage.

Therefore, it is also important to examine percentage of usage in each individual e-commerce

application.

Table 12: State of E-commerce adoption

Adoption stage Frequency Percentage

Non-adopter 8 11.8

Promotion 2 2.9

Provision 20 29.4

Transaction 19 27.9

Integration 19 27.9

Total 68 100.0

4.2.1 Electronic marketing

From the statistics obtained (Table 13), the extent of usage in this area is considered low as

only 26.5 % of the surveyed firms have implemented research about their customers’

preferences, 29.4 % of them are carrying out research and evaluation on their suppliers and

slightly less are doing research on competitors (20.6%).

4.2.2 Electronic advertising

The adoption rate in this area among the companies surveyed is considerably higher than in

the electronic marketing. Out of the sample, 58.8% of the companies are displaying their

corporate as well as products or services information online. However, most of the websites

are hosted by other companies (61.8%), only very few companies are having their own web

38

servers (11.8%). In addition, not many firms are advertising on third party web site (16.2%)

or using electronic catalogues (20.6 %).

4.2.3 Customer support service

This is an area that is related to relationship management. It is apparent that most companies

are providing some support services to their customers through the Internet as 77.9 % of them

are using personalized email to communicate with their customers. However, besides using

email, not many companies have implemented web-based support services. Out of the total

number of companies surveyed, only 14.7% are providing FAQ (frequently asked questions)

service while 23.5% of them are displaying products updates over the web. In addition,

30.9% of them are handling customers’ feedback online and 28.6 % of them provide online

application as well as registration. The main reasons behind this phenomenon could be due to

the cost constraints and the lack of technical expertise. It is much easier and cheaper to use

email than web-base technologies.

4.2.4 Order and delivery

This area comprises two very important functions of the companies, namely order processing

and fulfillment. However, not many companies are capitalizing on Internet technologies in

this area. While quite many companies (35.3%) are processing sales order from customers

online, only 25.0 % of them are involved in online procurement and much fewer companies

engage in online orders tracking (17.6%). In addition, EDI seems to be the least use

application in this area (10.3%). The above facts could again be explained by cost constraints

and lacking in technological know-how.

4.2.5 Payment system

It is apparent that the usage of online payment system is very much lower compared to the

other e-commerce applications. From the data obtained, only 16.2% of the sampled

companies are using EFT (electronic fund transfer) and 13.2 % of them provide online credit

card processing while much fewer are using smart card (7.4 %) and prepaid card (5.9 %).

39

Table 13: Usage of e-commerce applications by SMEs

Percentage (%) E-commerce Applications

In use Not in use

Electronic Marketing

Research on consumers preferences 26.5 73.5

Research and evaluation of new suppliers 29.4 70.6

Research on Competitors 20.6 79.4

Electronic Advertising

Displaying company information and products/services offered 58.8 41.2

Web site hosted by another company 61.8 38.2

Web site hosted by own server 11.8 88.2

Advertising on third party web site 16.2 83.8

Electronic catalogues 20.6 79.4

Customer Support Service

Online help- Frequently Asked Questions 14.7 85.3

Online help- products updates 23.5 76.5

Handling customers feedback/queries online 35.3 64.7

Personalised email communication 77.9 22.1

Online application/registration 30.9 69.1

Order and Delivery

Processing sales order from customers online 35.3 64.7

Coordinating procurement with suppliers online 25.0 75.0

Tracking incoming and outgoing goods delivery 17.6 82.4

Electronic Data Interchange (EDI) 10.3 89.7

Payment System

Electronic Fund Transfer (EFT) 16.2 83.8

Online credit card processing 13.2 86.8

Smart card 8.6 91.4

Prepaid card 7.1 92.9

40

The above results obtained have adequately answered the first research question raised in this

study, which is to find out the extent of e-commerce adoption. Although initial results

indicated that SMEs in Northern Malaysia are at a fairly high state of e-commerce adoption,

subsequent statistical analyses show evidence that the general level of e-commerce usage

among the SMEs in Northern Malaysia is low. This was confirmed by examining each and

every e-commerce applications as listed in Table 8. The result is further supported by

splitting the sample into high usage and low usage group based on the number of applications

being adopted where those firms which are using less than 10 applications are classified as

low usage group while those firms with more than 10 applications are considered as high

usage group. It was found that 88.2 % belong to the low usage group while only 11.8 %

belong to the high usage group (Table 14).

Table 14: Extent of e-commerce usage

Frequency Percentage

Valid Percentage

Low usage 60 88.2 88.2 High usage 8 11.8 11.8 Total 68 100.0 100.0

On the other hand, most firms have implemented company websites but many of them are not

fully functional as most of them do not provide online sales processing and order tracking,

online procurement and online payment. In fact, one of the least used e-commerce application

is online credit card payment (13.2%). On the other hand, the top application being

implemented by most companies is personalized email communication (77.9 %). The

preceding findings could also be reflected by the amount of investment in websites and the

number of IT personnel the firms employed. About 42.9 % of the firms did not invest in web

sites at all and only 3.2% of them have invested more than RM50, 000 in web sites (Table

15). With respect to IT personnel, 52.4 % of the firms do not employ any IT personnel while

up to 95.2 % employed two or less IT personnel (Table 16).

The results are almost similar to the situation in Australia, where most small firms were using

email (75%) but only 13% of them provide online payment facility (Jones, Hecker & Holland

2003, p.287). The statistics obtained are also consistent with findings of previous research

such as by Lawson et al. (2003) Poon et al. (1997), Haynes et al. (1998), Chapman et al.

41

(2000), Mackay et al. (2001) and Zwass (1998) where they found that advanced Internet

usage by most companies especially the SMEs was low and the most used application was

email while the least used application is the online payment system.

Table 15: Investment in web site

Percentage

Cumulative Percentage

No investment

42.9 42.9

<RM10000 34.9 77.8 <RM20000 15.9 93.7 <RM30000 3.2 96.8 >=RM50000 3.2 100.0

Table 16: Number of IT personnel

Number of IT personnel Percentage Cumulative Percentage

0 52.4 52.4 1 23.8 76.2 2 19.0 95.2 4 1.6 96.8 5 1.6 98.4

10 1.6 100.0

4.3 Benefits realized through adoption of e-commerce

To analyse the realized benefits of e-commerce, the sample size was reduced to 45 by

omitting the non-adopters as well as missing data. As the sample size is only 45, factor

analysis was not performed, as the minimum sample size required for factor analysis is

50(Hair et al., 1998). Therefore, only descriptive statistics were used.

First of all, the means of all the benefits were computed. Out of the 12 benefits of e-

commerce, only half of them were considered realized benefits based on the means (<3.0) as

the scales for measuring benefits were coded 1 for very high benefit while 5 coded for no

benefit. Another half of the benefits (with mean>3) were considered not realized. From Table

17, the realized benefits were improved customer service, increased accessibility to end-

users, increased responses from end-users, increased efficiency in dealing with suppliers,

enhanced company brand and image and improved business processes flow. One the other

42

hand, the unrealized benefits of e-commerce adoption were increase in market share, increase

in profit, increase in productivity, reduce in cost, increase in ROI and increased customers’

loyalty and retention.

Table 17: Realized benefits of e-commerce

E-commerce benefits Mean

Improved customer service 2.78

Increased accessibility to end-users 2.73

Increased responses from end-users 2.84

Increased efficiency in dealing with suppliers 3.00

Enhance company brand and image 2.78

Improved business processes flow 2.80

Table 18: Unrealized benefits of e-commerce

E-commerce benefits Mean

Increase in market share 3.29

Increase in profit 3.40

Increase in productivity 3.38

Reduce in cost 3.42

Increase in ROI 3.40

Increased customer loyalty and retention 3.13

The preceding findings showed that SMEs in Northern Malaysia have realized some of the

benefits proposed in the conceptual model by adopting e-commerce applications. Benefits

realized were in the areas of customer service, market expansion, back-end efficiency and

inventory management. However, despite so many realized benefits, SMEs who have adopted

e-commerce did not to improve its overall performance and profitability as cost reduction,

increase in productivity and increased in ROI were not achieved. Although the findings have

basically answered research question 2, further research need to be carried out to find out the

reasons why some of those benefits of e-commerce adoption were not realized.

4.4 Factors hindering the adoption of e-commerce applications

Before examining the factors that might hinder the adoption of e-commerce applications by

SMEs in Northern Malaysia, the sample size was further reduced from 68 to 64 as four

respondents failed to provide answers for the items that measure those factors. To have an

43

initial feel about barriers to e-commerce adoption, a frequency table was obtained for all the

items that were used to measure those barriers. Out of the twenty items, only two items gave

a mean of less than 3 while the rest returned a mean of more than three. This implied that the

respondents considered eighteen of the measures are barriers to e-commerce adoption. From

the results, insufficient security to prevent hacking and viruses was the top perceived barrier

(mean =4.03). The second barrier most concerned by the respondents was the need to have

additional staff to manage e-commerce (mean=3.91). Three subsequent barriers were sales

and marketing requires high degree of human interaction (mean=3.88), cost of setting up e-

commerce is high (mean=3.84), difficult to justify cost with desired results (mean=3.73). The

top ten barriers are listed in Table 19.

Table 19: Top ten barriers perceived by SMEs in Northern Malaysia

No. Barriers Mean

1 Insufficient security to prevent hacking and viruses 4.03

2 Need to have additional staff to manage e-commerce 3.91

3 Sales and marketing requires high degree of human interaction 3.88

4 Cost of setting up e-commerce is high 3.84

5 Difficult to justify cost with desired results 3.73

6 Most suppliers do not have access to electronic commerce 3.72

7 Insufficient security for online credit payment and transactions 3.64

8 Lack of skilled workers to handle or maintain e-commerce system 3.59

9 Lack of standards/regulations from government on e-commerce issues 3.55

10 Keeping up with changing technology 3.53

These findings closely coincided with other studies such as that by Lawson et al. (2003)

which found that the top four barriers were concern about security and privacy of

transactions, cost of consultants, lack of government incentives as well as lack of IT expertise

of staff, only in different orders. The results were also similar to the studies by Sulaiman

(2000), Love et al.(2001) as well as Khatibi et al.(2003).

Although the preceding results have provided useful information pertaining to barriers to e-

commerce adoption by the SMEs in Northern Malaysia, these barriers needed to be

categorized into a smaller set of variables, as some of the items might be interrelated or

44

interdependent. Besides, they did not adequately show any relationship between those

barriers and the level of e-commerce adoption. Therefore, further and more sophisticated

statistical analyses need to be performed to achieved the two proposes. The two statistical

analyses adopted here were factor analysis and regression analysis.

The main objective of factor analysis is to analyse the structure comprising a large number of

variables and group them into a set of factors, thus achieving the purposes of data reduction

and summarization. Factor analysis is suitable for both confirmatory as well as exploratory

studies (Hair et al., 1998). In this study, it was exploratory in nature as there are no

established theories related to barriers of e-commerce adoption by SMEs. The issue of sample

size was addressed in this study, as the sample did not achieve the number of variables to

sample size ratio of 1:5 because the number of variables is 20 and the sample size is 64.

However, factor analysis could be used for sample size of more than 50(Hair et al., 1998).

Moreover, correlation matrix obtained using SPSS indicated existence of substantial number

of significant correlations (with significance level at 0.05) among the variables. Besides,

Barlett test of sphericity revealed that some of the variables are significantly correlated. In

addition, the value of Kaiser-Meyer-Olkin (KMO) computed was more than 0.5. Therefore,

the use of factor analysis was deemed appropriate for this study.

Principal components factor analysis was performed using SPSS with Varimax rotation. The

initial number of factors extracted was 6 by looking at latent roots or eigenvalues that have

values more than 1. However, the significance of factor loadings in relation to sample size

needed to be examined before the final set of factors was determined. According to Hair et al.

(1998), for a sample size of 50, a factor loading of 0.75 is necessary for significance, for a

sample size of 60, factor loading of 0.7 is necessary for significance and the factor loading for

a sample size of 70 is 0.65. As the number of respondents in this study was 64, a factor

loading between 0.65 and 0.7 was used to group the variables into the factors. Based on the

preceding criteria, the number of extracted factors was 6(Table 20).

45

Table 20: The resulting factors derived from factor analysis

Factors

Environmental Governmental Financial Organizational Technical Behavioural

V1 .670 V2 .799 V3 V4 .709 V5 .788 V6 V7 V8 .698 V9 V10 .773 V11 .828 V12 V13 .824 V14 .785 V15 V16 .767 V17 .739 V18 V19 .744 V20 .825

The six factors were subsequently categorized and labeled as environmental, governmental

financial, organizational, technical and behavioural based on the variables that were loaded to

each of the factors. Variables that were loaded in each category closely resembled the

measures that were proposed in relation to the conceptual framework. For example, items V4,

V5 and V8 were loaded to factor 1, which was categorized as environmental barrier, were

grouped under the same category in the proposed measures, although three other variables

were excluded, as their loadings were not significant. Other variables also fit in exactly as the

proposed categorization of the e-commerce barriers. Therefore, the results of the factor

analysis have more or less confirmed that the conceptual framework could indeed be used to

explain the factors that were considered barriers to e-commerce by the SMEs in Northern

Malaysia.

Although the factor analysis had identified factors that were perceived by SMEs in Northern

Malaysia as barriers to e-commerce adoption, it did not examine the associations between

these barriers and the extent of e-commerce adoption. Therefore, tests of associations using

correlation and regression analyses were performed to analyse the relationship between these

46

factors and the adoption of e-commerce by the SMEs. The scores of the e-commerce

adoption were obtained by computing the number of electronic commerce applications

adopted by the respondents. The summated scales were also obtained for all the factors by

adding all the variables that were significantly loaded to each of the factors. All the factors

were also tested for reliability. The values of Cronbach’s Alpha were displayed in Table 21.

As financial and behavioural factors were having Cronbach’s alpha less than 0.7, they were

considered unreliable measures and thus were dropped for subsequent analysis.

Table 21: Reliability of factors

Factor Cronbach’s Alpha

Environmental 0.7097

Governmental 0.7198

Financial 0.5847

Organizational 0.7129

Technical 0.7342

Behavioural 0.6053

Correlation coefficients between each factor and the extent of e-commerce adoption were

computed; the results are shown in Table 22. From the table, environmental, governmental

and organizational factors were negatively correlated to the extent of usage, indicated that the

higher the barriers related to the above factors, the lower the extent of e-commerce adoption

and vice versa. The results seemed to favour the acceptance of Hypotheses H3, H4, and H5.

However, out of the three factors, only environmental factor is significantly correlated to the

extent of e-commerce adoption, which implied that the environmental factor is the main

barrier to e-commerce adoption by the SMEs in Northern Malaysia. As for technical factor, it

was positively correlated to extent of e-commerce adoption, which seemed illogical. One

possible reason is that many SMEs might not be aware of the technical barriers especially

those related to security risks of e-commerce, as most have only adopted basic e-commerce

applications based on earlier statistics pertaining to e-commerce usage, where security risks

were not the main concern. Conversely, it could be that the more extensive the usage of e-

commerce applications, the more the users is aware of the security problems. Therefore, the

level of awareness of Internet security risks could be a moderating factor, which could have

contributed to the above discrepancy. This moderating factor needs to be studied in future

47

research. As there was positive correlation between the extent of e-commerce usage and the

technical factor, the hypothesis that the extent of e-commerce is affected by factor related to

technical barriers was rejected. The above results indicated that only factors related to

organizational, governmental and environmental barriers have some negative influence on the

extent of e-commerce usage.

Table 22: Correlations between the factors and the extent of e-commerce adoption

Environmental Governmental Organizational Technical

Extent of e-commerce adoption

Pearson Correlation -.275(*) -.051 -.107 .138

Sig. (2-tailed) .028 .690 .399 .276

N 64 64 64 64

* Correlation is significant at the 0.05 level (2-tailed).

The correlation analysis only showed that there existed some form of association among the

variables, without specifying which is the dependent variable and which are the independent

variables that could be used to predict the dependent variable. Therefore, regression analysis

was performed in order to find out whether the extent of e-commerce adoption is influenced

by the factors that are related to various barriers. The dependent variable of the model is the

extent of e-commerce adopted, which is the total number of e-commerce applications being

adopted. The only independent variable worth considered here is the factor related to

environmental barriers, as the rest of the factors were excluded because these measures have

low reliabilities or low correlation with the extent of e-commerce adoption. Therefore, only

simple regression was performed. The results are shown in Table 23. From the analysis, the

regression model could be written as

Extent of e-commerce adoption = 10.70–0.528 factor related to environmental barriers

The model indicated that the factor related to environmental barriers has significant (p

=0.028) negative influence on the extent of e-commerce adoption. Therefore, the hypothesis

(H5) that the factor related to environmental barriers has negative influence on the extent of

e-commerce adoption was accepted. Hence, after performing correlation and regression

48

analysis, only the above hypothesis was accepted, while the rest of the hypotheses were

rejected.

Table 23: Simple regression analysis

Model Unstandardized

Coefficients Standardized Coefficients t Sig.

B Std. Error Beta

1 (Constant) 10.701 2.226 4.808 .000

Environmental -.528 .234 -.275 -2.250 .028

4.5 Discussion of the findings

The results of the study indicated that most SMEs in Northern Malaysia have adopted some

form of e-commerce applications. However, most have only implemented basic e-commerce

applications such as email and simple web sites. Most of the web sites do not provide online

order processing and payments facilitations. Moreover, not many SMEs seemed to have the

capabilities to perform online procurement and order tracking. The preceding findings

showed that the adoption of e-commerce is still low among the SMEs in Northern Malaysia.

These findings matched the results in similar studies conducted by Sulaiman (2000) and

Khatibi et al. (2003) in Malaysia.

Although many studies suggested that firms could gain a lot of benefits through the adoption

of e-commerce, this study found that SMEs in Northern Malaysia were not reaping many of

the benefits advocated by previous studies. While most SMEs who have adopted e-commerce

did realized some benefits in the areas of customer service, market expansion, back-end

efficiency and inventory management, they did not seemed to gain much benefits in terms of

improved company performance such as profitability and productivity. The reasons why

some these benefits were not realized could be due to the facts that most SMEs have only

adopted simple e-commerce applications, therefore they were not able to fully capitalized on

the many advantages of e-commerce, hence failing to gain those benefits.

Initial analysis of the reasons surrounding the low adoption of e-commerce by the SMEs in

Northern Malaysia found that the factors related to environmental, governmental, financial

organizational, technical and behavioural barriers. However, further analysis showed that

49

only the factor related to environmental barriers have significant negative influence on the

adoption of e-commerce by the SMEs in Northern Malaysia. The findings seemed to imply

that most SMEs have overcome other barriers particularly those that are technological and

financial in nature. In addition, there was also evidence that the government has done enough

to help the SMEs in this region to adopt of e-commerce applications. The preceding findings

are good news for the SMEs and policy makers, because it means that the SMEs only need to

deal with environmental barriers to increase the level of e-commerce adoption and the policy

makers need to just maintain the present level of support for the SMEs in terms of e-

commerce adoption.

50

Chapter 5: Conclusions, Implications, Limitations and Future Research

5.1 Conclusions

The objectives of this empirical study were to examine the state of e-commerce adoption

(which includes the extent of adoption and benefits realized) among the SMEs in Northern

Malaysia as well as to determine factors that might hinder its adoption. A conceptual model

was developed to assess the possible influence of various factors on the adoption of e-

commerce by the SMEs. The model was designed based on the study by Love et al. (2001)

and other literatures. The research method was questionnaire survey where the questionnaires

were mailed to all the respondents in the designated sampling frame. The data gathered were

then analysed using various statistical tools in order to provide answers to research questions

that were raised earlier. The research questions were (a) what is the level of e-commerce

adoption among the SMEs in Northern Malaysia, (b) what are the benefits realized through

the adoption of e-commerce by the SMEs in Northern Malaysia and (c) what factors might be

hindering the e-commerce adoption among the SMEs in Northern Malaysia.

Pertaining to the extent of e-commerce adoption, the results showed that most SMEs in

Northern have adopted some form of e-commerce applications, but the adoption level was not

high, as majority of them have only adopted basic applications. Indeed, the adoption of

advanced applications like online payment system, order processing as well as EDI is at a

relatively low level. The results have indeed adequately answered the first research question.

The findings implied that more efforts are needed to help and encourage SMEs in Northern

Malaysia to speed up e-commerce adoption, particularly the more advanced applications.

Regarding the second research question, only descriptive statistical analysis was performed,

as the sample was too small. Based on the mean scores of the benefits, it could be concluded

that SMEs in Northern Malaysia that have adopted e-commerce have gained some of the

benefits of e-commerce, particularly in the areas of customer service, market expansion,

back-end efficiency and inventory management. On the other hand, despite the benefits

realized, adoption of e-commerce did not seemed to help SMEs to improve their overall

performance and profitability as cost reduction, increase in productivity and increased in ROI

were not achieved. The above findings have basically answered the research question.

51

With respect to the third research question, a few statistical analyses were performed.

Descriptive statistics based on the mean scores showed that the top four barriers to e-

commerce adoption were insufficient security to prevent hacking and viruses, the need to

have additional staff to manage e-commerce, a high degree of human interaction is required

in sales and marketing and the high cost of setting up e-commerce. The above findings were

found to be similar to most previous studies on e-commerce adoption. For example, precious

studies in Malaysia revealed that the main barriers to e-commerce adoption were lack of

security and privacy high set up cost, lack of skilled staff to manage e-commerce as well as

business required personal touch and interaction (Sulaiman 2000; Khatibi et al. 2003). Factor

analysis successfully grouped the barriers into six factors, which were labeled as

environmental, governmental, financial, organizational, technical and behavioural barriers.

The grouping was found to match the proposed conceptual model in this study.

However, correlation analysis showed that only factors related to organizational,

governmental and environmental barriers have some negative influence on the extent of e-

commerce adoption. Among the three factors, only the factor related to environmental

barriers have significant negative influence on the extent of e-commerce adoption.

Regression analysis confirmed that the only the factor that has significant negative influence

on the extent of e-commerce adoption is the one related to environmental barriers. The above

results showed that although only factor related to environmental barriers has significant

influence on the extent of e-commerce adoption by the SMEs in Northern Malaysia, other

factors also have some influence on the extent of its adoption. The findings have sufficiently

answered the second research question.

5.2 Implications

The implication of the preceding findings means that the SMEs need to examine the reasons

why they are not making profit from adopting e-commerce. Perhaps they should need to

consider investing in more advanced e-commerce applications as well as redesign their

marketing strategies in order to reap profit out of the adoption of the above applications. The

government could lend a helping hand in terms of e-commerce investment by giving out

loans to the SMEs.

52

Additionally, since the environmental barriers were identified as the main obstacles to e-

commerce adoption, the SMEs in Northern Malaysia need to work together to overcome the

above barriers. The SMEs could prevail over those barriers by helping each other to be e-

commerce-ready, for example, by setting up advanced communication networks such as the

web-based EDI. Besides, the SMEs could share market information so that they could design

more effective marketing strategies, thereby achieving monetary gains. The government

should also play a more active in supporting the SMEs in this region in terms of training and

consultancy as well as the provision of more advanced telecommunication infrastructure.

5.3 Limitations of the study

Although the study has provided some meaningful answers to the research questions, a few

limitations needed to be addressed. First of all, the sample size is only 64, which is not big

enough. An ideal sample size for factor analysis is 100 so that the results will be more

significant. The problem of small sample size also affected the generalizability of the findings

in this study. The second limitation is that some moderating variables such as the level of

awareness of security risks might have some influence on the accuracy and significance of

the results, and they were not identified here.

The third limitation is that the study did not take the motivating factors into consideration in

assessing the level of e-commerce adoption. The motivating factors might have strong

enough positive influence on e-commerce adoption that they might offset the negative

influence of the limiting factors or barriers, which mean that the regression model may not be

sufficient to explain the influence of the barriers on the adoption level, as the adoption level

could be dependent on both type of factors.

5.4 Recommendations for future research

Because of the existence of the above limitations, future research needs to address the above

limitations in order to obtain more convincing results. First of all, future research should

attempt to obtain a bigger sample; preferably with a sample size of more than 100 so that

statistical analyses such as factor analysis will be more meaningful. Secondly, future research

needs to find out the reasons why SMEs (particularly those in Northern Malaysia) did not

53

realized some of the important benefits like improved profitability through e-commerce

adoption. Thirdly, future research should try to identify the moderating factors and take their

influence into considerations so as to minimize the confounding effects. Furthermore, future

research should include all the motivating factors or drivers of e-commerce adoption so that

the results of statistical analyses especially multiple regressions will be more accurate. Lastly,

future researchers could consider using qualitative research such as case study or other

methods in order to gain a richer picture of e-commerce adoption by the SMEs.

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1

Appendix A Questionnaire

SECTION 1 ELECTRONIC COMMERCE APPLICATIONS

Please √ against the following electronic commerce applications that are relevant to your organization: In use Not

in use 1. Electronics Marketing i. Research on consumers’ preferences � � ii. Research and evaluation of new suppliers � � iii. Research on competitors’ � � 2. Electronic Advertising i. Displaying company information and the � � products/services offered ii. Web site hosted by another company � � iii. Web site hosted by own server � � iv Advertising on third party website. � � v Electronic catalogues � � 3. Customer Support Service i. Online help- Frequently Asked Question (FAQ) � � ii. Online help- products updates � � iii. Handling customers feedback/queries on-line � � iv. Personalised email communication � � v. Online application/registration � � 4. Order and Delivery i. Processing sales order from customers’ online � � ii. Coordinating procurement with suppliers online � � iii. Tracking incoming and outgoing goods delivery � � (shipment, courier service online) iv. Electronic Data Interchange (EDI) � � 5. Payment System i. Electronic Fund Transfer (EFT) � � ii. Online credit card processing � � iii. Smart cards � � iv. Prepaid cards � �

A-

2

SECTION 2: To what extent the followings hinder your organization from using or using more electronics e-commerce applications? (Please circle only ONE appropriate score on the scale 1 to 5)

1. Cost of setting up electronic commerce is high 1 2 3 4 5 2. Need additional staff to manage electronic commerce 1 2 3 4 5 applications 3. Difficult to justify the cost with desired benefits 1 2 3 4 5 4. Information from the electronic commerce is not useful 1 2 3 4 5 5. Market potential of electronic commerce users is 1 2 3 4 5 too small 6. Our sales/marketing requires high degree of 1 2 3 4 5 human interaction 7. Electronic commerce is not as effective as traditional 1 2 3 4 5 marketing channel 8. Most suppliers do not have access to electronic 1 2 3 4 5 commerce 9. It will upset existing distribution channels 1 2 3 4 5 10. Insufficient security for online credit payment 1 2 3 4 5 transactions. 11. Insufficient security to prevent hacking and viruses 1 2 3 4 5 12. Insufficient qualified vendors for developing applications 1 2 3 4 5 13. Lack of skilled workers to handle or maintain electronic 1 2 3 4 5 commerce system 14. Lack of knowledge about the potential applications 1 2 3 4 5 of electronic commerce 15. Lack of standards/regulations from government on 1 2 3 4 5 electronic commerce issues 16. Telecommunication infrastructure is not adequate 1 2 3 4 5 17. Lack of government leadership 1 2 3 4 5 18. Weak support from top management 1 2 3 4 5 19. Keeping up with changing technology 1 2 3 4 5 20. Mindset shift towards using electronic commerce 1 2 3 4 5

Strongly Strongly Disagree Agree

A-

3

If you are not using any e-commerce applications, please omit section 3

SECTION 3: BENEFITS OF ELECTRONIC COMMERCE

How would you rate the benefits received from electronic commerce? Please circle only ONE appropriate score on the scale 1 to 5 )

Very High

High Medium Low

Virtually no

Benefits

1. Increase in market share 1 2 3 4 5

2. Increase in profit 1 2 3 4 5

3. Increase in productivity 1 2 3 4 5

4. Reduce in cost 1 2 3 4 5

5. Increase in Return On Investment(ROI) 1 2 3 4

5

6. Improved of customer service 1 2 3 4 5

7. Increase accessibility to the end-users 1 2 3 4

5

8. Increase responses from end-users 1 2 3 4 5

9. Increase the efficiency in dealing with suppliers 1 2 3 4

5

10. Enhance company brand and corporate image 1 2 3 4

5

11. Increase customer loyalty and retention 1 2 3 4

5

12. Improve business processes flow 1 2 3 4

5

A-

4

SECTION 4: PROFILE OF THE ORGANISATION We need some information about your organization to enable meaningful interpretations of

the study. Please be assured that this information will be treated with strict confidence.

Please √ �or fill in the blanks where appropriate 1. In which sector/sub-sector is your organization Classified: � Agriculture � Transport � Construction � Tourist and leisure services � Wholesale � Finance � Retail � Information Technology � Manufacturing � Education � Others, Please Specify: 2. Year established: ________________________ 3. Major products/services i ____________________ ii ____________________ iii. _____________________ 4. Ownership of the Organization: � Sole Proprietor � Partnership

� Private Limited � Others, Please Specify:____________

5. Total number of employees in your organization: 6. Paid-up capital: ����Less than RM100, 000 � RM500, 000-RM2, 499,999 ����RM100, 000 - RM499, 999 �Above RM2, 500,000 7. Annual sales turnovers or revenue: ����Less than RM500, 000 � RM 2,000,000- RM4, 999,999 ����RM500, 000- RM999, 999 � RM5, 000,000- RM9, 999,99 ����RM1, 000,000- RM1, 999,999 � Above RM10, 000,000

5

8. IT investment in the last three years: ����Less than RM50, 000 � RM500, 000-RM749,999 ����RM50, 000-RM249, 999 � RM750, 000-RM999, 999 ����RM250, 000-RM499, 999 � More than RM1, 000,000 9. Investment in electronic commerce in the last three years Expenditure (RM) i. Hardware _____________ ii. Software _____________ iii. Website development fees _____________ iv Consultancy fees _____________ 10. Who provides the system support for maintenance of the electronic commerce infrastructure? � Own IT department � Vendors � others, please specify: 11. Total number of IT personnel: 12. Do you send your staff for electronic commerce related training? � Yes � No 13. Types of electronic commerce training :(You may select more than one) � On-the-job training � Local vendors � In-house training � overseas training � Local institutes 14. Company Name & Address: _____________________________________ ______________________________________ _______________________________________

A-

6

A-

1

Appendix B: Coding form

Question

Number

Label Description Code Value

Section 1 Electronic Commerce Applications

A

Usage of e-commerce applications

1=In use 0=Not in use

1. Electronic Marketing

i em1 Research on consumers preferences

ii em2 Research and evaluation of new suppliers

iii em3 Research on Competitors

2. Electronic Advertising

i ea1 Displaying company information and

ii ea2 Web site hosted by another company

iii ea3 Web site hosted by own server

iv ea4 Advertising on third party web site

v ea5 Electronic catalogues

3. Customer Support Service

i css1 Online help- Frequently Asked Questions

ii css2 Online help- products updates

iii css3 Handling customers feedback/queries online

iv css4 Personalized email communication

v css5 Online application/registration

4. Order and Delivery

i od1 Processing sales order from customers online

ii od2 Coordinating procurement with suppliers

iii od3 Tracking incoming and outgoing goods

iv od4 Electronic Data Interchange (EDI)

5. Payment System

I ps1 Electronic Fund Transfer (EFT)

ii ps2 Online credit card processing

iii ps3 Smart card

iv ps4 Prepaid card

B-

2

Section 2 Hindrance to E-commerce Usage

1 v1 Cost of setting up e-commerce is high 1-Strongly disagree

2 v2 Need additional staff to manage e-commerce applications

2-Disagree

3 v3 Difficult to justify the cost with desired benefits

3- Neutral

4 v4 Information from e-commerce is not useful 4- Agree

5 v5 Market potential of e-commerce users is too small

5- Strongly agree

6 v6 E-commerce is not as effective as traditional channel

7 v7 Most suppliers do not have access to e-commerce

8 v8 Insufficient qualified vendors for developing applications

9 v9 It will upset existing distribution channels

10 v10 Our sales/marketing requires high degree of human interaction

11 v11 Lack of skilled workers to handle or maintain e-commerce system

12 v12 Lack of knowledge about the potential applications of e-commerce

13 v13 Weak support from top management

14 v14 Insufficient security for online credit payment and transactions

15 v15 Insufficient security to prevent hacking and viruses

16 v16 Lack of standards/regulations from government on e-commerce issues

17 v17 Telecommunication infrastructure is not adequate

18 v18 Lack of government leadership

19 v19 Keeping up with changing technology

20 v20 Mindset shift towards using e-commerce

Section 3 Benefits of E-commerce 1=very high

1 b1 Increase in market share 2=high

2 b2 Increase in profit 3=medium

3 b3 Increase in productivity 4=low

4 b4 Reduce in cost 5= virtually no benefits

5 b5 Increase in Return on Investment (ROI)

6 b6 Improved customer service

B-

3

7 b7 Increased accessibility to the end-users

8 b8 Increased responses from end-users

9 b9 Increase the efficiency in dealing with

10 b10 Enhance company brand and corporate image

11 b11 Increased customer loyalty and retention

12 b12 Improved business processes flow

Section 4 Profile of the organization

1. sector in which sector is the organization classified 1. Agriculture 2.Transport 3.Construction 4. Tourism & Leisure 5. Wholesale 6. Finance 7. Retail 8. IT 9. Manufacturing 10. Others

2. year Year established

3. Major products/services

p1

p2

p3

4. owner Ownership of the organization 1= sole proprietor 2= partnership 3=private limited 4=public listed

5. tne Total number of employees

6. capital Paid-up capital x=capital

1: x<RM100, 000

2: RM100, 000≤x< RM500, 000

3: RM500, 000≤x< RM2, 500,000

4: x≥ RM2, 500,000

7. sales Annual sales turn over y=sales

1:y<RM500, 000

2: RM500, 000≤y< RM1, 000,000

3: RM1, 000, 000≤y< RM2, 000,000

4: RM2, 000, 000≤y< RM5, 000,000

5: RM5, 000, 000≤y< RM10, 000,000

6:y≥ RM10, 000,000

B-

4

8. invest IT investment in last 3 years t=investment

1: t<RM50, 000

2: RM50, 000≤t< RM250, 000

3: RM250, 000≤t< RM500, 000

4: RM500, 000≤t< RM750, 000

5: RM750, 000≤t< RM1, 000, 000

6: t≥ RM1, 000,000

9. Investment in e-commerce in last 3 years

i hard Hardware 0=no investment

ii soft Software 1: <RM10, 000

iii web Website 2: <RM20, 000

iv consult Consultancy 3: <RM30, 000

4: <RM40, 000

5: <RM50, 000

6: ≥RM50, 000

10. maintain Who provide e-commerce infrastructure maintenance

1=own IT dept 2=vendors 3= Others

11. itp Total number of IT personnel

12 training Do you send your staff for e-commerce training

1= yes 2= no

13 type Types of e-commerce training

t1 On the job training

t2 In-house training

t3 Local institutes

t4 Local vendors

t5 Overseas training

14 location 1=Penang 2=Perak 3=Perlis 4=Kedah

Computed Variables

em em=em1+em2+em3

ea ea=ea1+ea2+ea3+ea4+ea5

css css=css1+css2+css3+css4

od od=od1+od2+od3+od4

ps ps=ps1+ps2+ps3+ps4

B-

5

totaluse totaluse=em+ea+css+od+ps (Measure extent of e-commerce usage)

stage Stage of e-commerce adoption 1=stage 1 2=stage 2 3=stage 3 4= stage 4

B-