The name is absent



b

a


denotes the number of employees needed to serve 1000 customers in all services offering price
reductions in the interval
[a,b] . In this case the ratio E/L is calculated according to the formula
(2.2)

R[d] = Φ [pr] Ψ[ "'] dwdpr
0           W[ pr,d]

A numerical simulation making use of the result in (2.2) is shown in Figure 5.


Figure 5

Fractions of Employment/Labor as a
function of traveling distance
d to CBD

The construction above ignores the
possibility of multipurpose shopping.
Conveniently rephrasing the problem,
however, we are able to include
multipurpose shopping within the
same setup. Consider the situation
shown in Table 1.

F1

F2

F3

#Employees/1000customers

10

30

20

Savings

$10,00

$50,00

$60,00

Together with F1 only

40 %

10 %

30 %

Together with F2 only

20 %

60 %

20 %

Together with F3 only

30 %

10 %

40 %

F1, F2 and F3

10 %

20 %

10 %

Table 1: Savings/shopping frequencies

As shown in Table 1, the customers will sometimes take advantage of more than one service at the
time. The idea is now simply to view a shopping combination as a new service. So we introduce new
combinations
F4=(F1,F2), F5=(F1,F3), F6=(F2,F3) and F7=(F1,F2,F3). Using the conditional
frequencies from Table 1, we get the accumulated savings shown in Table 2. In Table 2 we really
consider, e.g., the service F
1 as the service provided when the customers take advantage of service 1
only. Hence only 4, i.e., 40% of the 10 employees are needed for this particular service. All the other
employees are split according to this pattern.



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