The impact of ownership on the cost of bus service provision: an example from Italy

Abstract

This article examines the potential impact of ownership on the cost of bus service provision for a sample of 65 private and 12 public companies providing local public transit (LPT) in Piedmont (Italy) from 1998 to 2002. A translog cost frontier is estimated using the model in Battese and Coelli (1995) where inefficiency scores are allowed to vary across firms and over time. A public ownership dummy is included in the inefficiency model and it is always positive and significant. Density and scale economies and cost inefficiencies are then computed. Private companies seem to experience higher density and scale economies than public ones. Cost inefficiencies appear higher in the public sample.

Competitive tendering versus performance-based negotiation in Swiss public transport

“…1 2 For seat kilometers, see Farsi et al (2006), Cambini et al (2011), Walter (2010, 2011. For bus kilometers, see Wang Chiang and Chen (2005), Ottoz et al (2009), and Sakai and Shoji (2010).…”

Public and Private Production in a Mixed Delivery System: Regulation, Competition and Costs

“…For instance, seeFarsi, Filippini and Kuenzle (2006);Filippini and Prioni (2003);Fraquelli, Piacenza, and Abrate (2004);Matas and Raymond (1998);and Ottoz, Fornengo, and Di Giacomo (2009). The translog cost function considers cost as a function of input prices and the production level.…”

Do contractual practices affect technical efficiency? Evidence from public transport operators in China

“…(1) Output variables Output variables like vehicle-kilometres, seat-kilometres, passenger-kilometres, number of passengers and operating revenue have all appeared previously in the relevant studies (Pina and Torres, 2001;Odeck, 2008;Ottoz et al, 2009;Karlaftis and Tsamboulas, 2012). Among them, vehicle-km and seat-km are two production-oriented indicators, whereas passenger-km and number of passengers are demand-related indicators.…”

“…Technical efficiency of public transport service is evaluated mainly using two different methods, Non-parametric Analysis represented by the Data Envelopment Analysis (DEA) (Barnum et al, 2008;Odeck, 2008;Amores and Contreras, 2009;Yu and Fan, 2009;Nisha Korattyswaroopam, 2010;Zhao et al, 2011), and Parametric Analysis represented by the Stochastic Frontier Approach (SFA) (Karlaftis and McCarthy, 1999;Roy and Yvrande-Billon, 2007;Ottoz et al, 2009;Karlaftis, 2010;Boitani et al, 2013). The one approach we use in this paper is the stochastic frontier approach (SFA).…”