four countries, the prevalence of credit cards for online shopping is seen as an important obstacle 

in Germany, while other countries, especially Denmark, regard this factor as less important. An 

often mentioned obstacle is the costly integration of e commerce solutions into the existing IT 

infrastructure. US banks regard this as an important barrier, followed by Danish, German and 

French banks. On average, US banks believe they are confronted with more obstacles than 

European banks, as the average indicates. 

FIGURE 27  E banking Related Obstacles in the Banking Sector 

4

3.5

3

2.5

2

1.5

1

Need for 

Concerns 

Customers 

Finding 

Prevalence 

Costs of 

Organiza 

Our own 

Average

customer 

about data 

do not 

staff with e 

of credit 

implement 

tional 

level of 

face to face 

security

support this  commerce 

card use

ing e 

changes 

ability to use 

interaction

technology

expertise

commerce

needed

the Internet 

for business

Denmark

France

Germany

USA

Source: CRITO Global E Commerce Survey, 2002; results are weighted by total number of establishments in banking/finance 

sector by size of firm. 

E commerce output and, therefore, the impact of e commerce on business processes depend 

directly on the intensity and variety of implemented applications. As input variables for the DEA 

model, the results of seven questions are used, measuring the number of e commerce 

technologies in place as a binary variable. The variables are coded as 0 when an establishment 

uses a given e commerce technology, and 1 if it does not. The coding is equivalent to higher 

spending on the input side when e commerce is not available or the other way around: firms 

using e commerce gain benefits by reducing their processing costs. The ten output variables of 

the model are measured on a five point scale from 1 (no impact at all) to 5 (a great deal). For 

each bank, the DEA model uses a linear program to analyze the ratio between low costs of input 

(using e commerce) and the resulting output, measured as perceived impact of e commerce on 

different processes. As a result, the DEA identifies the best practice cases or the most efficient 

establishments within the sample. Firms on the so called  efficient frontier line  are relatively 

efficient users when compared to other firms below the frontier line. For a better explanation of 

the results, the average of  efficient  and  inefficient  banks is calculated. The seven input 

variables are aggregated to an Internet usage indicator, while the ten output variables are 

represented as an average e commerce impact index.  

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