Adoption of E-Commerce by SMEs in the UK

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International Small Business Journal Copyright © 2002 SAGE Publications (London, Thousand Oaks and New Delhi) [0266–2426 (200205)20:3; 253–270; 025745] Vol 20(3): 253–270

is bj

Adoption of E-Commerce by SMEs in the UK Towards a Stage Model E L I Z A B E T H DA N I E L , H U G H W I L S O N A N D ANDREW MYERS Cranfield School of Management, UK Research has shown that small and medium-sized enterprises (SMEs) are rapidly adopting the Internet and e-commerce. However, there is little systematic research into how such companies are adopting this new technology. This study addresses the research gap by seeking to understand how SMEs in the UK are adopting e-commerce, through an exploration of their level and sequence of adoption. The research, which was carried out by means of a mailed questionnaire, found four distinct clusters of adoption. These formed a set of sequential stages, through which firms appear to pass during the adoption of e-commerce. The firms in the first cluster are currently developing their first e-commerce services; the second adoption cluster are using e-mail to communicate with customers, suppliers and employees. Those at the third level of adoption have information-based websites operating and are developing on-line ordering facilities. The most advanced adopters have on-line ordering in operation and are developing online payment capabilities. The association of the adoption stage currently reached by a firm with contextual variables both at an industry and an organizational level is investigated and discussed. K E Y WO R D S :

adoption; e-commerce; SMEs; stage model

Introduction Electronic commerce is one of the most discussed topics in business today. It is already leading to the reshaping of customer and supplier relationships, the streamlining of business processes and, in some cases, even the restructuring of whole industries. Forecasts have estimated that the total value of e-commerce around the world will exceed US$400bn by 2002 (IDC, 2000). Much of the media coverage of e-commerce concentrates on ‘born to the web’ companies such as Amazon.com or eBay.com, or its adoption by large, traditional ‘bricks and mortar’ companies. However, small and medium-sized enterprises (SMEs) are also increasingly making use of the Internet. Research by Oftel (2000) has found 253

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International Small Business Journal 20(3) that 49% of SMEs in the UK are connected to the Internet and a further 20% intend to be connected in the near future. Despite this rapid take-up of the Internet by smaller companies, there is little systematic research into how such companies are adopting this new technology beyond these raw statistics on connectivity. This study addresses this gap in current research by seeking to understand how SMEs are adopting e-commerce through an exploration of their level and sequence of adoption. Drawing on previous studies, it is proposed that SMEs are likely to adopt e-commerce in a set of sequential steps or stages. At each stage they will develop certain e-commerce services from which they will gain experience and hence dissipate uncertainty and risk, which will be of benefit when they proceed to develop further services. This study will be of value to SMEs considering e-commerce and those at the early stages of adoption, since it delineates the route travelled by other similar firms. It will also be of value to those that supply services and solutions to these SMEs, since it will provide evidence on which such advice and products can be based. The article commences with a description of existing literature in this domain and presents two research propositions that guide this study. The methodology adopted is then described and the findings are presented and discussed.

E-Commerce Adoption by SMEs: Existing Literature Due to the relative youth of e-commerce, there are not yet widely agreed definitions of what is meant by this term. Kalakota and Whinston (1997) define ecommerce as ‘the buying and selling of information, products and services via computer networks’ (p. 3), the computer networks primarily being the Internet. Others (The Cabinet Office, 1999) use the term to encompass not only the buying and selling described above but also the use of Internet technologies, such as email and intranets, to exchange or share information either within the firm itself or with external stakeholders. It is this latter, wider definition of e-commerce that is used in this study. It has been observed that e-commerce is not a simple innovation; rather it is a cluster of separate innovations (Prescott and Conger, 1995; Van Slyke, 1997; White et al., 1998). Companies can choose which of these innovations they make use of and in what sequence. This view is supported by the limited number of studies that have been undertaken to date on the use of electronic commerce in the specific context of SMEs, which include Hamill and Gregory (1997), Webb and Sayer (1998), Dutta and Evrard (1999) and Poon and Swatman (1999). These studies identify a wide range of business activities for which SMEs are using ecommerce, summarized in Table 1, reinforcing the observation that e-commerce is a cluster of separate innovations. In further considering the adoption of e-commerce by SMEs, we are guided by the views of authors such as Frank (1988), Dosi (1988) and Reid and Smith (2000), who regard small firms as organizations that gain experience and knowledge in a sequence of steps or stages. Achievement of the first stage of a project 254

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Daniel et al.: Adoption of E-Commerce by SMEs in the UK Table 1. E-Commerce Activities Activity

Previous Study

Variable Name in Current Study

Providing information on company

Hamill and Gregory (1997)

COINFO

Providing information on goods or services

Webb and Sayer (1998); Dutta and Evrard (1999); Poon and Swatman (1999)

GOODSINFO

Taking orders

Webb and Sayer (1998); Dutta and Evrard (1999); Poon and Swatman (1999)

ORDERS

Receiving payment

Webb and Sayer (1998); Dutta and Evrard (1999)

PAYMENT

Delivery (of digital goods or services)

Webb and Sayer (1998)

DELIVERY

After sales service or contact


AFTERSALES

Identifying new inventory suppliers

Dutta and Evrard (1999)

INVSUPPLIERS

Ordering and payment of inventory purchasing


ORDERINVENT

Non inventory purchasing (such as travel, stationery)


NONINVENT

Communication (email) with customers or suppliers

Hamill and Gregory (1997); Dutta and Evrard (1999); Poon and Swatman (1999)

CUSTCOMM

Internal communication between employees


INTCOMM

Document and design exchange with customers or suppliers


DOCEXCH

External information search, e.g. competitors, regulations

Hamill and Gregory (1997); Dutta and Evrard (1999)

INFOSEARCH

Communication with shareholders and investors


SHARECOMM

Advertising


ADVERT

Recruitment


RECRUIT

or development allows the organization to gain experience, which it can then use to its benefit to move on to the next stage of development, at which point it will gain further experience. Stage models have been developed and applied in the fields of growth of technology-based new ventures (Drazin and Kazanjian, 1990, 255

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International Small Business Journal 20(3) 1993) and are particularly well accepted in the field of internationalization. The stage model proposed by Cavusgil (1980) states that firms progress through five stages of internationalization. This has been tested and found to be valid in small businesses by a number of authors, such as Bell (1995), Reuber and Fischer (1997) and the longitudinal study by Gankema et al. (2000). A limited number of studies have sought to measure the level of e-commerce adoption (White et al., 1998) or of other IT adoption in SMEs (Smith, 1999), but we are unaware of other studies that have demonstrated a sequence of stages of adoption in this domain.

Research Propositions In accordance with the approach adopted by Bailey and Johnson (1996), the empirical component of this article, which is inductive in nature, is structured around the exploration of two deductively derived research propositions. The observation that e-commerce is a cluster of innovations and the staged approach to the adoption of new knowledge and experience together lead us to expect that SMEs will adopt e-commerce in a sequence of stages. This leads to our first proposition: P1: The adoption of e-commerce by SMEs typically proceeds in a set of sequential stages.

It has been argued (Pettigrew, 1985) that the development of strategy by firms must be considered within the context in which the firm operates. For example, managers within different industry sectors are faced with different environmental contexts and are therefore likely to develop different strategies. Different types of organizations in terms of size, revenue and location, even within the same industry, are also expected to develop distinct strategies. We therefore expect that the current level of usage of e-commerce by SMEs, that is their stage of adoption, will depend upon contextual variables both at an industry and organizational level. This leads to our second proposition: P2: The stage of adoption currently reached by a firm will depend on contextual variables both at an industry and an organizational level.

Method Survey Instrument The research was carried out by means of a mailed questionnaire which commenced by stating a simple definition of e-commerce that we wished respondents to adopt when completing the survey. The questionnaire contained five sections. Sections 2 and 5 are relevant to the findings discussed in this study. Sections 1, 3 and 4 explore other areas of e-commerce adoption and will be analysed in future publications. Section 2 measured the extent of e-commerce adoption. In accordance with White et al. (1998) in their study of web adoption by the publishing industry, 256

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Daniel et al.: Adoption of E-Commerce by SMEs in the UK adoption is measured according to business activities undertaken on-line, rather than the technology features or platforms utilized. In order to measure the adoption variables shown in Table 1, the corresponding activity descriptions from the first column of the table were listed. Respondents were asked to indicate whether they currently did or did not use e-commerce for each activity or whether they had such a service under development. Section 5 elicited contextual information on the company, such as its market sector and size by both turnover and employee numbers. The survey instrument was piloted with 21 SMEs. This highlighted a number of issues that were addressed in the final survey design.

Population Definition The population of interest for this study is SMEs who are using or developing ecommerce services, where SMEs are defined in accordance with the UK Department of Trade and Industry (DTI, 1999), as firms with less than 250 employees. No other constraints were placed on the population, such as industry sector or geographic location. Indeed it was preferred that a wide spread in other variables could be achieved in order to ensure that results obtained have the widest applicability amongst SMEs.

Sample Selection Two samples of SMEs were used in this study. First, a database of SMEs that is held within Cranfield School of Management was used. This contains companies that have attended an executive education programme aimed at SMEs or who have made enquiries about such a programme. The database held 1500 names and company addresses, all of which were believed to have 250 or less employees. The companies covered a wide range of industry sectors and were distributed throughout the UK. Second, 5000 names and company addresses were bought from a commercial database company. Companies were chosen from their records on the basis that they had 250 employees or less. It was ensured that the sample selected covered a representative range of industry sectors and locations throughout the UK. The mailings of questionnaires to the two samples were both undertaken in March 2000 and all responses were received by the end of April 2000. It was not known from the database if the companies were using or considering e-commerce. However, since there is such a high degree of interest in this subject, it was expected that many of the companies would be. It was decided to allow companies not considering or using e-commerce to ‘de-select’ themselves from the sample. They could do this in two ways. First, and it was expected that this would be the most frequent approach, companies not interested in this subject would not complete and return the survey. Second, if they wished to return the survey they could indicate on it that they are not considering ecommerce services and give reasons for this. Responses from the two samples were analysed separately and the results compared. No significant differences were found between the two samples and so this article presents results based upon the combination of these two samples. 257

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International Small Business Journal 20(3)

Response Rate The total number of responses received was 766 (total response rate 11.8%). Of these, 46 were rejected as representing companies with more than 250 employees and a further 42 were not included since the respondents reported that their organizations were neither using e-commerce nor considering its use. Hence 678 usable responses (effective response rate 10.4%) were used as a basis for the findings of this study. Analysis of the responses received according to company size are shown in the Appendix to this article. Responses from small companies, taken here as between 6 and 50 employees represented 51% of those received and those from medium-sized companies, taken as between 51 and 250 employees, represented 43% of those received. The remaining responses were from micro firms with 5 employees or less.

Non-Response Bias The method of determining non-response bias adopted in studies such as Goode and Stevens (2000) was adopted for this study. In this method the earliest responses to be received are compared with the responses received later. The usable responses were split into two equal sets of 339 responses according to the dates on which they were received. No significant differences were found for any of the five sections contained in the survey instrument. It is therefore concluded that the responses received are unlikely to contain a non-response bias.

Findings of the Study Staged Adoption The questionnaire presented a list of activities for which e-commerce could be used. Respondents were asked to indicate for each activity whether they currently used e-commerce, had a service under development or did not use ecommerce. Cluster analysis was carried out on the responses using the complete set of activity variables according to Ward’s (1963) minimum variance method. Cluster analysis is a technique for grouping cases or entities (in this case firms) into groups that are coherent according the attributes of interest (here this is activities being undertaken by e-commerce) whilst also distinguishing each group from others that differ according to these attributes. It is inductive in that the number and characteristics of the groups are not known prior to the analysis. Clustering was carried out with three, four and five clusters and the cubic cluster criteria generated for each. A large increase in this measure at the four cluster level suggested the suitability of a four cluster solution. The four cluster solution also met a secondary criterion that there is a sufficient number of cases in each cluster to allow statistical analysis. In order to identify the adoption characteristics of the four clusters a crosstabulation of the responses by cluster for each activity was generated and is presented in Table 2. A chi-squared analysis of the responses for each activity (each row of the table) was undertaken and was found to be significant for all of the activities proposed (significance < 0.0001), demonstrating that the clustering technique adopted was able to produce clusters that are significantly distinct 258

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Table 2. Adoption of E-commerce by Cluster

COINFO

INFOSEARCH GOODSINFO ADVERT

259

Document exchange with customers or suppliers Recruitment

DOCEXCH RECRUITMENT

Receiving payment

PAYMENT

Communications with shareholders and investors After sales service or contact

SHARECOMM

Taking orders

ORDERS

Identifying new inventory suppliers Ordering and payment of inventory purchasing Non inventory purchasing

INVSUPPLIERS

Delivery (of digital goods or services)

DELIVERY

AFTERSALES

ORDERINVENT NONINVENT

Cluster 3 (N = 203)

Cluster 4 (N = 208)

Operational

Under development

Operational

Under development

Operational

Under development

Operational

Under development

15 12.8% 14 10.3% 13 17.7% 13 17.7% 12 15.1% 12 15.1% 11 12.6% 11 12.6% 11 12.6% 11 12.6% 10 10.0% 10 10.0% 10 10.0% 10 10.0% 10 10.0% 10 10.0%

21 53.8% 30 76.9% 34 87.2% 29 74.4% 33 84.6% 30 76.9% 23 59.0% 13 33.3% 12 30.8% 11 28.2% 20 51.3% 20 51.3% 13 33.3% 12 30.8% 11 28.2% 11 28.2%

177 157.0% 113 112.2% 121 189.6% 105 177.8% 118 115.9% 119 114.1% 176 156.3% 118 113.3% 112 118.9% 111 118.1% 127 120.0% 116 111.9% 127 120.0% 119 114.1% 150 137.0% 113 119.6%

18 15.9% 99 73.3% 10 10.0% 14 13.0% 80 59.3% 42 31.1% 15 11.1% 18 15.9% 14 10.4% 14 13.0% 23 17.0% 29 21.5% 16 14.4% 15 13.7% 10 17.4% 19 16.7%

128 163.1% 198 197.5% 193 195.1% 164 180.8% 181 189.2% 113 155.7% 114 156.2% 128 113.8% 119 114.4% 120 119.9% 129 114.3% 116 117.9% 131 115.3% 113 116.4% 138 118.7% 111 115.4%

10 14.9% 10 10.0% 17 13.4% 14 12.0% 17 13.4% 15 17.4% 12 15.9% 26 12.8% 49 24.1% 18 13.9% 33 16.3% 62 30.5% 19 14.4% 15 17.4% 17 18.4% 25 12.3%

169 181.3% 199 195.7% 207 199.5% 188 190.4% 201 196.6% 167 180.3% 164 178.8% 192 144.2% 157 127.4% 133 115.9% 128 161.5% 128 161.5% 161 129.3% 134 116.3% 187 141.8% 156 126.9%

12 11.0% 13 11.4% 10 10.0% 11 10.5% 13 11.4% 14 11.9% 14 11.9% 12 11.0% 14 16.7% 15 12.4% 11 10.5% 14 11.9% 17 13.4% 14 16.7% 14 11.9% 13 16.3%

Note: Responses indicating no operational or developmental service have been omitted

Chi-square value

Asymp sig (2 tailed)

164.153

0.000

485.377

0.000

423.667

0.000

335.245

0.000

411.290

0.000

211.887

0.000

162.505

0.000

174.324

0.000

162.717

0.000

126.914

0.000

122.298

0.000

164.407

0.000

150.575

0.000

125.897

0.000

163.862

0.000

141.517

0.000

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CUSTCOMM

Cluster 2 (N = 135)

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Providing information on goods or services Advertising

INTCOMM

Cluster 1 (N = 39)

Daniel et al.: Adoption of E-Commerce by SMEs in the UK

Internal communication between employees Providing information on company Communications with customers or suppliers External information search

Variable

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Activities

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International Small Business Journal 20(3) according to all of the sixteen activities listed. A description of each of the clusters, drawn from Table 2, is given below: Cluster 1 (Developers) These companies had the lowest levels of operational e-commerce services, compared to the other three clusters, but had very high levels of services under development. They are therefore referred to here as developers, that is companies who are at the very start of their e-commerce adoption and are currently developing services. The most common areas of development activity were: developing email communication with customers and suppliers (87%), providing information about the company’s products and services (85%) and the company itself (77%), for example via a website, and using the web for advertising and brand building (77%). Cluster 2 (Communicators) The companies in cluster 2 were making extensive use of email to communicate with customers and suppliers (90%) and the web to find business information (78%). They were also frequently using email for communication between employees (57%) and electronically exchanging documents and designs with customers and suppliers (56%). In this group the most common development activity is focused on the development of websites to provide company or product and service information (73% and 59% respectively). Cluster 3 (Web Presence) Companies in cluster 3 were undertaking all of the activities currently being undertaken by companies in cluster 2. That is, they were using email to communicate with customers and suppliers (95%), using the web to find external information (81%), using email between employees (63%) and electronically exchanging documents and designs (56%). They were also operating the services that cluster 2 companies were still currently developing. That is, they have websites that provide information about their company (98%) and its products and services (89%). The most common areas of development in cluster 3 companies were the taking of orders (31%) and receiving orders on-line (24%). It would therefore seem that cluster 3 contains companies that are operating information-providing websites and are currently looking to develop transactional capabilities. Cluster 4 (Transactors) Companies in cluster 4 were found to be undertaking all of the activities undertaken by cluster 3 companies but in addition they were found to be taking orders on-line (62%), providing after sales service or contact (62%) and undertaking recruitment on-line (44%). Much less development was being undertaken by this group, since they already have most of the suggested services in operation. Areas where development was being undertaken were receiving payment on-line (7%), ordering and payment of inventory purchasing (7%) and the delivery of digital goods on-line (6%). The findings also suggest that the four clusters identified represent a set of sequential stages through which SMEs pass when adopting e-commerce. First, it would appear that the activities are cumulative, that is each cluster is undertaking 260

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Daniel et al.: Adoption of E-Commerce by SMEs in the UK all of the activities of the previous cluster, plus additional ones. For example, companies in cluster 3 were undertaking the same activities as cluster 2, that is communicating with customers and suppliers via email, exchanging documents and using the web to find business information, but were in addition providing information about their companies’ products and services on-line. This interpretation of the four clusters being sequential stages is also in agreement with the observation that the areas of development for one cluster are the additional activities currently being undertaken by the subsequent cluster. For example, the majority of companies in cluster 2 are developing websites to provide company and product information. In the next cluster, cluster 3, these services are found to be in operation. Further support of the stage model is provided if the set of e-commerce activities is used to create a numerical scale of adoption (ADOPTSCALE). In accordance with Smith (1999), a sum of the responses was taken for the 16 activities listed in Table 1, where an affirmative response to use was coded as unity and zero otherwise. The maximum value of this measure is therefore 16 and the minimum zero and higher values indicate a higher level of e-commerce adoption. The findings of the analysis for each adoption are presented in Table 3. It can be seen that firms in each cluster have a progressively higher level of e-commerce adoption, lending further support to the stage model of adoption. Although compelling support for the stage model is provided by this study, which is cross-sectional in design, a longitudinal study would be required to unreservedly confirm the model. Such a study would by its nature require some considerable time to complete. The current study provides more timely advice both to those adopting and researching e-commerce adoption by SMEs and can also provide a useful foundation for further research. Hence, within the limitations of the research method adopted, the findings of the study taken together provide strong support for our first proposition, P1, that is, SMEs are adopting e-commerce in a set of sequential stages.

Contextual Variables Tables 4 and 5 show the values of the contextual variables collected by the survey instrument according to the adoption clusters or stages. It should be stressed that the variables shown in these tables were not used to construct the clusters, rather the values shown are derived after the clusters had been established as described above. Table 4 shows that professional service firms represent the highest proportion of all the stages except stage 2. It may be expected that such firms would be active

Table 3. Adoption Scale by Cluster ADOPTSCALE

Cluster 1 (N = 39)

Cluster 2 (N = 135)

Cluster 3 (N = 203)

Cluster 4 (N = 208)

F statistic (p value)

Mean Std Dev

0.59 0.88

4.46 2.33

6.33 1.78

9.48 1.98

329.608 000.000

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International Small Business Journal 20(3) Table 4. Nominal Contextual Variables by Adoption Cluster Variables

Cluster 1 (N = 39)

Cluster 2 (N = 135)

Cluster 3 (N = 203)

Cluster 4 (N = 208)

Industry sector

Manufacturing Construction/Property Retail/Hospitality IT/Communications Professional Services Public/Health/Education/ Charities

17.9 17.9 13.6 10.0 39.3 21.4

21.1 26.3 12.6 14.2 17.9 17.9

21.0 14.8 17.3 15.6 25.3 16.0

21.1 11.2 17.1 10.5 34.2 15.9

Region

London South England Central England and Wales North England and Scotland

33.3 15.4 30.7 20.5

29.6 22.2 28.1 20.0

29.5 17.5 39.5 13.5

22.2 21.2 38.4 18.2

Note: Figures are percentage of cluster total

in their use of e-commerce, since their staff are generally well educated and likely to be familiar with computers, while their offerings, being information based, are likely to be compatible with promotion and sale over the Internet. The building and civil engineering sector was found to be the most frequent in cluster 2, that is those firms that are using email to communicate with customers and suppliers and the web to find business information. Often building projects require considerable communication and exchange of documents and plans between many parties and firms in this sector may be finding electronic exchange can increase the speed and accuracy of these exchanges. The sector with the least advanced e-commerce adoption, as represented by a low incidence at stage 4, is the public, education and charitable sector. Comments made by respondents in this sector indicated that they believed that e-commerce was not relevant to them since their major tasks were either to encourage donations of money or other resources or to raise awareness of their cause. If the narrower definition of e-commerce being concerned with buying and selling via computer networks, as proposed by Kalakota and Whinston (1998), is adopted, then it may indeed not be relevant to some voluntary and charitable bodies. However, when e-commerce is defined as including information exchange as well as buying and selling, as we have here, then e-commerce is highly relevant to the voluntary sector and could be highly beneficial to them. Interestingly manufacturing firms were well represented at all stages of adoption. It is often believed that smaller manufacturing firms in the UK have been slow to embrace ecommerce, but these findings indicate that this is not the case. London was the most frequent location for firms at stages 1 and 2 of adoption while those at the later stages 3 and 4 were most often based in Central England and Wales (for definitions of regions see Daniel and Myers, 2000). An understanding of the causes of regional differences in the adoption of e-commerce would require additional research but would be of great value to regional development agencies. 262

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Daniel et al.: Adoption of E-Commerce by SMEs in the UK Table 5 shows that the primary discriminants between the stages of adoption are the extent to which firms export goods and the proportion of sales made to other businesses compared to those to consumers. Firms in the later stages of adoption tended to export their products to a greater extent than those in the earlier stages of adoption (14.8% exported for firms at stage 4 compared to just 5.0% for firms at stage 1). It is not possible to establish from this study what is cause and what is effect in the case of exports. E-commerce has been hailed as a low-cost way for firms to increase their access to a global marketplace. It may therefore be that companies interested in increasing their sales overseas have developed their e-commerce services to a greater extent so that they can benefit from this global access. However, it may be that firms that have progressed their e-commerce developments to stage 4 are now reaping the rewards from this by receiving orders for goods from overseas markets. Indeed, some of the respondents comment that after establishing websites, they had unexpectedly received orders from markets they had previously not served. Businesses in the later stages of e-commerce adoption tended to sell a greater proportion of their products and services to other businesses (74.4% for stage 4 firms compared to 53.8% for firms at stage 1). This provides an interesting contrast to the commonly held view that the majority of e-commerce initiatives Table 5. Mean Values of Ratio Contextual Variables by Adoption Cluster Variables

Cluster 1 (N = 39)

Cluster 2 (N = 135)

Cluster 3 (N = 203)

Cluster 4 (N = 208)

F statistic (p value)

Employees

Mean (Std dev)

64.8 (65.0)

60.4 (60.1)

69.6 (60.9)

70.4 (62.3)

0.844 (0.470)

Turnover

Mean (Std dev)

£7.5m (£11.4m)

£10.3m (£15.0m)

£10.5m (£14.7m)

£9.8m (£14.1m)

0.505 (0.679)

Years in Business

Mean (Std dev)

40.1 (45.6)

31.5 (32.2)

28.9 (28.2)

26.5 (32.2)

2.086 (0.101)

Percentage of sales to other businesses*

Mean (Std dev)

53.8 (44.0)

71.3 (39.3)

69.6 (42.2)

74.4 (38.5)

2.646 (0.048)

Percentage of sales to consumers*

Mean (Std dev)

46.2 (44.0)

28.7 (39.3)

30.2 (42.2)

25.1 (38.5)

2.797 (0.040)

Percentage of sales in the UK**

Mean (Std dev)

95.0 (12.7)

93.2 (18.4)

89.1 (20.4)

84.9 (24.7)

4.990 (0.002)

Percentage of sales exported**

Mean (Std dev)

5.0 (12.7)

6.8 (18.4)

10.9 (20.4)

14.8 (24.7)

4.696 (0.003)

Electronic Data Interchange (EDI)

Percentage

11.4

24.1

27.4

35.7

–

Bank Automated Clearing System

Percentage

82.9

87.0

88.4

93.0

–

* significant at the 0.05 level; ** significant at the 0.01 level

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International Small Business Journal 20(3) are consumer oriented. It may be expected that the business-to-business sales of firms in the later stages of adoption will be made both to other firms in the later stages of adoption and also to firms with more limited e-commerce experience. The use of e-commerce by these latter firms will therefore increase, and they will in turn offer services to other firms, leading to a virtuous cycle of adoption. Although Table 5 shows a variation in the number of employees, turnover and years in business across the adoption stages, these variations were not found in this study to be significant. This would suggest that these internal contextual variables do not influence the adoption of e-commerce by SMEs. This finding is counter to some of the popular myths surrounding e-commerce, such as that ecommerce has been exploited to the greatest extent by smaller, more nimble companies or that adoption has been led by younger companies since older firms are more resistant to adopting the new ways of working represented by ecommerce. Further research of a qualitative nature would provide an opportunity to investigate a richer set of internal variables, in particular organizational contexts, and their possible influence on the adoption of e-commerce. Previous experience with electronic trading was explored by asking respondents if they used electronic data interchange (EDI) or the bank automated clearing system (BACS) for payments. It was found that adoption of e-commerce was related to use of such systems with firms at stage 4 of e-commerce adoption three times more likely to be using EDI than firms at stage 1 (35.7% at stage 4 compared to 11.4% at stage 1). The adoption of BACS across the adoption clusters did not show such marked variation but did show the same relationship with e-commerce adoption, that is firms in the later stages of e-commerce adoption had a higher incidence of electronic payment systems usage. The above findings lend support to our second proposition, P2: The stage of adoption currently reached by a firm will depend on contextual variables both at an industry and an organizational level.

Summary and Conclusions This study sought to explore how small and medium-sized companies are adopting e-commerce. Previous studies have described how smaller firms ‘dissipate uncertainty’ by gaining experience and knowledge in a sequence of steps. This study suggests that an approach consistent with this is being taken with the adoption of e-commerce. Four distinct clusters of adoption were found and when the services these firms were operating and were currently developing were examined, it was found that the four clusters suggested a set of sequential steps or stages, through which firms passed during the adoption of e-commerce. The first cluster of firms were developing their first e-commerce services, those at the second stage of adoption were using e-mail to communicate with customers, suppliers and employees. Those at the third level of adoption had information-based websites operating and were developing on-line ordering facilities. The most advanced adopters had on-line ordering in operation and were developing on-line payment capabilities. The study found that the context of firms varied by adoption cluster. The 264

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Daniel et al.: Adoption of E-Commerce by SMEs in the UK industry sector with the lowest levels of operational e-commerce services was found to be the public, education and charitable sector and those with the highest levels of adoption is the professional services sector. Significant differences between firms at different stages of adoption were found to be the extent to which they export goods and the proportion of sales made to other businesses compared to those to consumers. Firms in the later stages of adoption tended to export their products to a greater extent than those in the earlier stages of adoption. Businesses in the later stages of e-commerce adoption tended to sell a greater proportion of their products and services to other businesses. It was found that the internal contextual variables, turnover, number of employees and age of the company do not influence the adoption of e-commerce. It was found that adoption of e-commerce was related to prior use of electronic trading and payment systems with firms at stage 4 of e-commerce adoption three times more likely to be using EDI than firms at stage 1. The adoption of the payments system BACS across the adoption clusters did not show such marked variation but did show the same relationship with e-commerce adoption, that is firms in the later stages of e-commerce adoption had a higher incidence of electronic payment systems usage. In terms of future research new e-commerce innovations are continuing to occur, such as interactive TV, WAP services and e-marketplaces. It is therefore expected that in the near future additional clusters of adopters will be seen that have moved on from the current stage 4 identified in this study. The study described here could be extended to a longitudinal study of a panel of small businesses to confirm the stage theory and to determine the time taken for firms to move from one stage to the next. This would mirror the study undertaken on the staged approach to internationalization of SMEs undertaken by Gankema et al. (2000). The stage model presented here could be used as a basis of further research to identify the benefits of e-commerce adoption realized by SMEs and, in particular, the variation of those benefits with adoption stage. Identification of the factors that determine successful e-commerce adoption and how these factors vary across the stages of adoption could also be usefully undertaken.

References Bailey, A. and Johnson, G. (1996) ‘Patterns of Strategy Development’, Working Paper Series, SWP1/96, Cranfield School of Management. Bell, J. (1995) ‘The Internationalization of Small Computer Software Firms: A Further Challenge to Stage Theories’, European Journal of Marketing 29(8): 60–75. Cabinet Office, The (1999) ‘[email protected]’, The Performance and Innovation Unit, UK. Cavusgil, S. T. (1980) ‘On the Internationalization Process of Firms’, European Research 8(6): 273–81. Daniel, E. and Myers, A. (2000) ‘Levelling the Playing Field: E-Commerce in SMEs’, End of award report to ESRC, December. DTI (1999) ‘Small and Medium Enterprise Statistics for the UK’, Government Statistical Service, UK.

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International Small Business Journal 20(3) Dosi, G. (1988) ‘Sources, Procedures and Microeconomic Effects of Innovation’, Journal of Economic Literature 26(3): 1120–71. Drazin, R. and Kazanjian, R. K. (1990) ‘Research Note and Communications. A Reanalysis of Miller and Friesen’s Life Cycle Data’, Strategic Management Journal 11(4): 319–25. Drazin, R. and Kazanjian, R. K. (1993) ‘Applying the DEL Technique to the Analysis of Cross Classification Data: A Test of CEO Succession and Top Management Team Development’, Academy of Management Journal 36(6): 1374–99. Dutta, S. and Evrard, P. (1999) ‘Information Technology and Organisation within European Small Enterprises’, European Management Journal 17(3): 239–51. Frank, M. Z. (1988) ‘An Intertemporal Model of Industrial Exit’, Quarterly Journal of Economics 103(2): 333–44. Gankema, H. G. J., Snuif, H. R. and Zwart, P. S (2000) ‘The Internationalization Process of Small and Medium Sized Enterprises: An Evaluation of Stage Theory’, Journal of Small Business Management 38(4): 15–27. Goode, S. and Stevens, K. (2000) ‘An Analysis of the Business Characteristics of Adopters and Non-Adopters of WWW’, Technology Information and Management 1(1): 129–54. Hamill, J. and Gregory, K. (1997) ‘Internet Marketing in the Internationalisation of UK SMEs’, Journal of Marketing Management 13(1–3): 9–28. IDC (2000) e-commerce market forecasts available at www.nua.ie/surveys Kalakota, R. and Whinston, A. (1997) Electronic Commerce: A Manager’s Guide. Reading, MA: Addison-Wesley. Oftel (2000) ‘Internet Use among Small and Medium Enterprises (SMEs)’, Q2 (Aug./Sept.), URL (consulted Nov. 2000): http: //www.oftel.gov.uk Pettigrew, A. M. (1985) The Awakening Giant. Oxford: Blackwell. Poon, S. and Swatman, P. M. C (1999) ‘An Exploratory Study of Small Business Internet Commerce Issues’, Information and Management 35(1): 9–18. Prescott, M. and Conger, S. (1995) ‘Information Technology Innovations: A Classification by IT Locus of Impact Research Approach’, The Database for Advances in Information Systems 26(2–3): 20–41. Reid, G. C. and Smith, J. A. (2000) ‘What Makes a New Business Start Up Successful?’, Small Business Economics 14(3): 165–82. Reuber, A. R. and Fischer, E. (1997) ‘The Influence of the Management Team’s International Experience on the Internationalization Behaviours of SMEs’, Journal of International Business Studies 28(4): 807– 25. Smith, J. A. (1999) ‘The Behaviour and Performance of Young Micro Firms: Evidence from Businesses in Scotland’, Small Business Economics 13(3): 185–200. Van Slyke, C. (1997) ‘The Diffusion of Technology Cluster Innovation: The Case of the Internet’, paper presented to Americas Conference on Information Systems, Indianapolis, 15–17 August, URL (consulted March 2002): http: //hsb.baylor.edu/ramsower/ als.ac.97/papers/vslyke.htm Ward, J. H. (1963) ‘Hierarchical Grouping to Optimize an Objective Function’, Journal of the American Statistical Association 58(1): 236–44. Webb, B. and Sayer, R. (1998) ‘Benchmarking Small Companies on the Internet’, Long Range Planning 31(6): 815–27. White, M. D., Abels, E. G. and Gordon-Murnane, L. (1998) ‘What Constitutes Adoption of the Web: A Methodological Problem in Assessing Adoption of the World Wide Web for Electronic Commerce’, Journal of the American Society for Information Science 35: 217–26.

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Appendix The size of the organizations participating in the survey is shown in Figures 1 and 2. Figure 1 measures company size by number of employees. Micro-businesses, taken here as organizations with 5 employees or less, represented 6% of the sample. Small businesses, that is organizations with between 6 and 50 employees, represent a slight majority in the responses, accounting for 51%. Mediumsized businesses, that is those with between 51 and 250 employees, accounted for 43% of the responses. Under 5 6% 101 to 250 22% 6 to 25 30%

51 to 100 21% 26 to 50 21% Figure 1. Number of Employees in Respondents’ Organizations

Figure 2 shows the annual turnover of the companies participating in the survey. The largest group, representing almost half of the sample have a turnover between £1 million and £5 million. The remaining businesses are evenly spread between the other categories. Over £25m Under £500k 10% 8% £550k to £1m 10% £10m to £25m 13%

£5m to £10m 17% £1m to £5m 42% Figure 2. Annual Turnover of Respondents’ Organizations

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International Small Business Journal 20(3) ELIZABETH DANIEL, BSc, PhD, MBA is a Senior Research Fellow in the Information Systems Research Centre at Cranfield School of Management. Elizabeth has a first degree and PhD in Physics and an MBA from London Business School. She has spent over ten years in industry, starting her career as a Medical Engineer at GEC and more recently working in a leading strategy management consultancy, the LEK Partnership, where she undertook assignments across a number of industry sectors. Elizabeth undertakes teaching and research in the fields of e-business and new technologies in marketing. Please address correspondence to: Information Systems Research Centre, Cranfield School of Management, Cranfield, Bedford, MK43 0AL, UK. [email: [email protected]]

HUGH WILSON, MA(Oxon), DipCompSci(Cantab), PhD, is a Visiting Fellow and Director of the Centre for e-Marketing at Cranfield School of Management. After a mathematics degree at Oxford University and a postgraduate computer science degree at Cambridge University, he spent thirteen years in the computing industry, before gaining a prize-winning PhD from Cranfield University on decision support systems for marketing planning. More recently Hugh’s research interests have included the adoption and use of e-commerce by businesses.

ANDREW MYERS, BSc, PhD is a visiting member of staff at Cranfield School of Management. Andrew’s area of expertise is in the statistical analysis and interpretation of large-scale surveys. In addition to recent work on electronic commerce in both large and small companies, Andrew has been involved in major studies in the fields of knowledge management and the future of outsourcing.

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Daniel et al.: Adoption of E-Commerce by SMEs in the UK Adoption du commerce électronique par les PME au Royaume-Uni Vers un modèle à étapes – Elizabeth Daniel, Hugh Wilson, et Andrew Myers Cranfield School of Management, Royaume-Uni Les recherches ont montré que les petites et moyennes entreprises (PME) adoptent rapidement Internet et le commerce électronique. Toutefois, peu de recherches systématiques ont été effectuées sur la façon dont ces sociétés adoptent cette nouvelle technologie. Cette étude aborde la lacune des recherches en cherchant à comprendre comment les PME au Royaume-Uni adoptent le commerce électronique, grâce à une exploration de leurs niveau et séquence d’adoption. Les recherches, qui ont été effectuées au moyen d’un questionnaire envoyé par la poste, ont trouvé quatre groupes d’adoption distincts. Ces groupes ont formé un ensemble d’étapes séquentielles, à travers lesquelles les entreprises semblent passer pendant l’adoption du commerce électronique. Les entreprises du premier groupe développent actuellement leurs premiers services de commerce électronique; le deuxième groupe d’adoption utilise le courrier électronique pour communiquer avec les clients, les fournisseurs et les employés. Ceux au troisième niveau d’adoption ont mis en place des sites web basés sur les informations et développent des moyens de commande en ligne. Les adopteurs les plus avancés ont mis en place la commande en ligne et développent des moyens de paiement en ligne. L’association de l’étape d’adoption actuellement atteinte par une entreprise à des variables contextuelles, à la fois au niveau industriel et organisationnel, est examinée et discutée. Mots clés: adoption; commerce électronique; petites et moyennes entreprises; PME; modèle à étapes

Adopción del comercio electrónico por las PYME en el RU Hacia un modelo multifásico – Elizabeth Daniel, Hugh Wilson y Andrew Myers Escuela de Gestión Administrativa de Cranfield, RU La investigación ha demostrado que las pequeñas y medianas empresas (PYME) están adoptando con mucha rapidez la Internet y el comercio electrónico. No obstante, no se ha investigado sistemáticamente hasta qué punto tales empresas han adoptado esta nueva tecnología. Este estudio procura llenar este vacío en la investigación buscando una explicación de la manera en que las PYME británicas están adoptando el comercio electrónico mediante un análisis del nivel y secuencia de la adopción. La investigación, llevada a cabo a base de encuestas por correo, encontró cuatro grupos distintos de adopción. Estos grupos forman un conjunto de fases secuenciales por las cuales las empresas parecen pasar durante la adopción del comercio electrónico. Las firmas en el primer grupo están actualmente desarrollando sus primeros servicios de comercio electrónico; el segundo grupo está utilizando el correo electrónico para comunicarse con los clientes, proveedores y empleados. Las empresas en el tercer nivel de adopción tienen sitios web de información en operación y están desarrollando servicios para el pedido en línea. En el nivel más avanzado, las empresas ya tienen en operación el pedido en línea y están desarrollando las posibilidades del pago en línea. Se investiga y discute la relación entre la fase de adopción alcanzada por una empresa y las variables contextuales, tanto a nivel industrial como organizativo. Palabras claves: adopción; comercio electrónico; pequeñas y medianas empresas; PYME; modelo multifásico

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International Small Business Journal 20(3) Die Übernahme von E-Commerce durch kleine und mittlere Unternehmen im Vereinigten Königreich Der Schritt zu einem Stufenmodell – Elizabeth Daniel, Hugh Wilson, und Andrew Myers Cranfield School of Management, Vereinigtes Königreich Untersuchungen haben gezeigt, dass kleine und mittlere Unternehmen Internet und ECommerce mit rasantem Tempo übernehmen bzw. einführen. Darüber, auf welche Weise solche Unternehmen diese neue Technik übernehmen, gibt es jedoch nur wenige systematische Untersuchungen. Die vorliegende Arbeit befasst sich mit dieser Untersuchungslücke, indem sie zu verstehen versucht, wie kleine und mittlere Unternehmen im Vereinigten Königreich den E-Commerce übernehmen. Dazu werden Ausmaß und Ablauf der Übernahme erforscht. Die Studie, die auf der Grundlage eines mit der Post versandten Fragebogens durchgeführt wurde, konnte vier deutliche Übernahmegruppen ausmachen. Die Gruppen bildeten auf einander folgende Stufen, die Firmen offensichtlich bei der Übernahme des E-Commerce durchlaufen. Die Firmen in der ersten Gruppe entwickeln gegenwärtig ihre ersten E-Commerce-Dienstleistungen, während die zweite Übernahmegruppe E-Mail für die Kommunikation mit Kunden, Lieferanten und Mitarbeitern einsetzt. Die Firmen in der dritten Übernahmestufe betreiben informationsbasierte Websites und entwickeln Möglichkeiten zur Online-Bestellung. Die am weitesten fortgeschrittenen Unternehmen arbeiten bereits mit Online-Bestellung und erarbeiten die Voraussetzungen für die Online-Bezahlung. Der Zusammenhang zwischen der von einer Firma gegenwärtig erreichten Übernahmestufe und Kontextvariablen sowohl auf Branchen- als auch auf Unternehmensebene wird untersucht und erörtert. Schlagwörter: Übernahme, Einführung, E-Commerce, kleine und mittlere Unternehmen, Stufenmodell

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