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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