In this paper, we measure the standard cost of light metro (LM) and heavy metro (HM) Italian services based on the cost model provided by Avenali et al., (2018). The cost model takes into account technological characteristics that may drive cost differentials, such as the degree of automatism of the rolling stock, wheels technology and hourly peak capacity. Specifically, we focus on three case studies: (i) not automatic railway steel technology with heavy capacity; (ii) not automatic railway steel technology with light capacity; (iii) automatic rubber-tyred technology with light capacity. Data have been gathered by means of questionnaires sent to companies producing 100% of train revenue kilometers (TRK) in Italy in 2012. We perform a simulation study in order to highlight the marginal impact of efficiency gains obtained by manipulating cost-driving variables both under the control of the operators (trains and drivers productivity) and of the Local Authority who assigns the service (number of TRK assigned within the service contract and the number of opening hours per station). These examples show how the Local Authority should allocate extra-resources if it wants to increase the quality-quantity mix of metro services.
Standard cost of italian metro services: The influence of automatism, wheels technology and capacity / Avenali, A.; Catalano, G.; D'Alfonso, T.; Matteucci, G.. - 182:(2019), pp. 49-59. (Intervento presentato al convegno 24th International Conference on Urban Transport and the Environment, 2019 tenutosi a Aveiro; Portugal) [10.2495/UT180051].
Standard cost of italian metro services: The influence of automatism, wheels technology and capacity
Avenali A.
;Catalano G.
;D'alfonso T.
;Matteucci G.
2019
Abstract
In this paper, we measure the standard cost of light metro (LM) and heavy metro (HM) Italian services based on the cost model provided by Avenali et al., (2018). The cost model takes into account technological characteristics that may drive cost differentials, such as the degree of automatism of the rolling stock, wheels technology and hourly peak capacity. Specifically, we focus on three case studies: (i) not automatic railway steel technology with heavy capacity; (ii) not automatic railway steel technology with light capacity; (iii) automatic rubber-tyred technology with light capacity. Data have been gathered by means of questionnaires sent to companies producing 100% of train revenue kilometers (TRK) in Italy in 2012. We perform a simulation study in order to highlight the marginal impact of efficiency gains obtained by manipulating cost-driving variables both under the control of the operators (trains and drivers productivity) and of the Local Authority who assigns the service (number of TRK assigned within the service contract and the number of opening hours per station). These examples show how the Local Authority should allocate extra-resources if it wants to increase the quality-quantity mix of metro services.File | Dimensione | Formato | |
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