Information Technology Reference
In-Depth Information
To give an example of the data and formalization process we use this existence
need as an illustration. The basic idea is that costs, range and charging time are crucial
factors determining agent satisfaction. Whereas a limited range and longer charging
time of an electric car will result in little disutility for an agent with short urban trips,
an agent frequently making long trips will be more satisfied with a fuel car due to the
longer range and short charging (fueling) time. Hence the transportation behavior of
the agent influences his vehicle choices and has to be parameterized. For this we use a
following question: “Indicate how often you make a trip of the following distance on
a single day”, and “how many kilometers a year do you expect to drive with your next
car?” This resulted in the following tables 2 and 3:
Table 2.
Frequency distribution of various daily trips (N=2533 for each row)
Once, or few
times a week
Once, or few
times a month
Once, or few
times a year
(almost) never
0 (not in use)
909
1187
336
101
1 -10 km
445
1531
445
112
10-50 km
109
1523
791
110
50-100 km
231
596
1150
556
100-200km
422
235
786
1090
200-500km
883
66
274
1310
> 500km
1642
13
39
839
Table 3.
Frequency distribution of expected yearly mileage of a next car (N=2974)
Frequency
%
below 5.000 km/year
164
5.51
5.000 to 10.000 km/year
729
24.51
10.000 to 15.000 km/year
882
29.66
15.000 to 20.000 km/year
539
18.12
20.000 to 25.000 km/year
301
10.12
25.000 to 30.000 km/year
120
4.03
30.000 to 35.000 km/year
80
2.69
35.000 to 40.000 km/year
47
1.58
40.000 to 45.000 km/year
30
1.01
45.000 to 50.000 km/year
43
1.45
50.000 to 100.000 km/year
23
0.77
Do not know
16
0.54
Total
2974
100.00
