Ceris-Cnr, W.P. N° 12/2001

to public-owned or private-owned firms. In particular, the indirect management through
the resort to the special company institute has undoubtedly represented the most
recurring model. Traffic data (number of buses, service workers and passengers) during
the years 1985-1995 certainly highlights a progressive relevance of the private sector.
Nevertheless, the weight of the local public-owned companies continues to be decisive,
especially in terms of the number of passengers (85 percent public versus 15 percent
private, during 1995).

2.3. Costs and productivity trend
The Italian system, when compared to European standards, presents inadequate
tariff levels, but mainly differs with respect to the structure of costs, that are too high,
given the poor level of productivity reached by the sector.
Table 1 (ISOTOPE Project of the European Commission, 1998), shows the main
efficiency indicators for Italy, “Other European Countries” and United Kingdom.6 In
terms of labour productivity, the Italian sector shows lower performance (14.77 vehiclekms for each service worker) against the other European realities (19.38 for the “Other
European Countries” and 20.39 for the United Kingdom). The data concerning the
operating costs per vehicle-km (3.02 ECU against 2.16 for the “Other European
Countries” and 1.44 for the United Kingdom) points to the same direction.
Table 1. Efficiency indicators for the urban bus service in Europe (yearly values)
Vehicle-kms (thousands)
/service worker

Operating costs (Ecu)
/vehicle-km

Italy

14.77

3.02

“Other European Countries”
(France, Denmark,
Finland, Sweden)

19.38

2.16

United Kingdom

20.39

1.44

Country

Source: European Commission (1998)

On the other hand, a recent study carried out by CNR (1999) underlines that, in
the period from 1992 to 1997, the gap between costs and proceeds grew by a further 13
percentage points, in spite of the positive dynamics of the tariffs level.

6

Statistics were obtained through the experimental data (relative to urban bus service) of the
information base developed inside the project. Data refer to a sample of 108 European towns.

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