The Two‐Mode Problem: Second‐Best Pricing and Capacity

Arnott, Richard; Yan, An

doi:10.1111/j.1467-940x.2000.00077.x

Cited by 79 publications

(37 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Note that a differentiation in price by distance is more attractive if destination choice is included as well; otherwise the model would overestimate the revenue from long-distance travellers, some of whom would try to travel shorter distances. Our model also ignores issues of income distribution (Dodgson and Topham, 1987;Mayeres and Proost, 1997), heterogeneity in the value of time savings (Verhoef and Small, 2004) and that road capacity may also be endogenous (De Borger and Wouters, 1998;Arnott and Yan, 2000), all dimensions that are promising venues of further research for the analysis of marginal cost pricing and optimal public transport design including congestion and crowding externalities. Finally, regarding the number of seats as a variable, the bus operator cost structure could include differences in capital and maintenance costs due to alternative standing and seating configurations.…”

Section: Discussionmentioning

confidence: 99%

Multimodal pricing and optimal design of urban public transport: The interplay between traffic congestion and bus crowding

Tirachini

Hensher

Rose

2014

Transportation Research Part B: Methodological

162

View full text Add to dashboard Cite

Citation: Tirachini, A., Hensher, D. A., Rose, J. M., 2014. Multimodal pricing and optimal design of public transport services: the interplay between traffic congestion and bus crowding. Transportation Research Part B, forthcoming. AbstractThe interplay between congestion and crowding externalities in the design of urban bus systems is identified and analysed. A multimodal social welfare maximisation model with spatially disaggregated demand is developed, in which users choose between travelling by bus, car or walking in a transport corridor. Optimisation variables are bus fare, congestion toll, bus frequency, bus size, fare collection system, bus boarding policy and the number of seats inside buses. We find that optimal bus frequency results from a trade-off between the level of congestion inside buses, i.e., passengers' crowding, and the level of congestion outside buses, i.e., the effect of frequency on slowing down both buses and cars in mixed-traffic roads. A numerical application shows that optimal frequency is quite sensitive to the assumptions on crowding costs, impact of buses on traffic congestion, and overall congestion level. If crowding matters to users, buses should have as many seats as possible, up to a minimum area that must be left free of seats. If for any other reason planners decide to have buses with fewer seats than optimal (e.g., to increase bus capacity), frequency should be increased to compensate for the discomfort imposed on public transport users. Finally, the consideration of crowding externalities (on both seating and standing) imposes a sizeable increase in the optimal bus fare, and consequently, a reduction of the optimal bus subsidy.

show abstract

Section: Discussionmentioning

confidence: 99%

Multimodal pricing and optimal design of urban public transport: The interplay between traffic congestion and bus crowding

Tirachini

Hensher

Rose

2014

Transportation Research Part B: Methodological

162

View full text Add to dashboard Cite

show abstract

“…Crowding as a factor that affects the users' utility and generalised cost of travelling has been recognised by several authors in the analysis of public transport pricing and supply policy (Jansson, 1979;Kraus, 1991;Jansson, 1993;Arnott and Yan, 2000;Huang, 2002;Pedersen, 2003;Pels and Verhoef, 2007;Parry and Small, 2009). The basic idea is that when a person boards a bus or a train, they may impose a crowding externality on everyone else on board, which is especially noticeable when there are passengers standing.…”

Section: Effect On Optimal Public Transport Supply and Farementioning

confidence: 99%

Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand

Tirachini

Hensher

Rose

2013

Transportation Research Part A: Policy and Practice

226

153

View full text Add to dashboard Cite

The effects of high passenger density at bus stops, at rail stations, inside buses and trains are diverse. . This paper examines the multiple dimensions of passenger crowding related to public transport demand, supply and operations, including effects on operating speed, waiting time, travel time reliability, passengers' wellbeing, valuation of waiting and invehicle time savings, route and bus choice, and optimal levels of frequency, vehicle size and fare. Secondly, crowding externalities are estimated for rail and bus services in Sydney, in order to show the impact of crowding on the estimated value of in-vehicle time savings and demand prediction. Using Multinomial Logit (MNL) and Error Components models, we show that alternative assumptions concerning the threshold load factor that triggers a crowding externality effect do have an influence on the value of travel time (VTTS) for low occupancy levels (all passengers sitting); however, for high occupancy levels, alternative crowding models estimate similar VTTS. Importantly, if demand for a public transport service is estimated without explicit consideration of crowding as a source of disutility for passengers, demand will be overestimated if the service is designed to have a number of standees beyond a threshold, as analytically shown using a MNL choice model. 2

show abstract

“…Such practice is dubbed "naïve cost benefit analysis". Arnott and Yan (2000) show that in the standard static model, naïve CBA leads unambiguously to overestimation of the benefit from expansion and hence to excessive investment. Indeed, they show using a plausible numerical example that the capacity chosen using naïve CBA can exceed second-best optimal capacity by more than second-best capacity exceeds first-best capacity.…”

Section: Congestion Pricing and Investmentmentioning

confidence: 99%

“…But because underpricing of congestion results in greater usage, the direct benefit of a capacity expansion is higher than in the first best. The net effect of these opposing forces has been investigated extensively in the literature; Arnott and Yan (2000) provide an insightful review and synthesis. One result is that if a toll is reduced slightly below the first-best level, optimal capacity rises because the increase in the positive direct effect dominates the increase in the negative indirect effect.…”

Section: Congestion Pricing and Investmentmentioning

confidence: 99%