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Autonomous cars allow safe driving with a smaller headway than that required for normal human-driven cars, thereby potentially improving road capacity. To attain this capacity benefit, cooperation among autonomous cars is vital. However, the future market may have multiple car brands and the incentive for them to cooperate is unknown. This paper investigates the competition and cooperation between multiple car brands that, may provide both autonomous and normal vehicles. We develop a two-stage game-theoretic model to investigate brands’ strategic interactions and evaluate, from both policy and organizational perspectives, the implications of their cooperation incentives and pricing competition. We compare four market structures: duopoly competition, perfect competition, a public welfare-maximizing monopoly, and a private profit-maximizing monopoly. Various parameters are evaluated, including factors such as the capacity benefits from cooperation, cooperation cost and price elasticity. This evaluation provides policy insights into actions that could be considered by regulators and organizations for the operation of autonomous cars.

This paper analyzes partnerships between foreign and domestic firms as a source of signaling advantages, considering the case of virtual codesharing in aviation. Virtual codesharing is an important type of cooperative agreement between airlines that does not change any real product attributes and hence provides the opportunity to identify this signaling effect. Roughly 75% of the flights in trans-Atlantic and Pacific markets involves codesharing. Typically, the consumer buys the ticket with the domestic airline, while a foreign airline operates the flight. Analyzing individual-level choice data from a representative sample of Australian air travelers, we find that the average consumer is willing to a pay a premium between 4 and 5.5% of the ticket price when a flight by a foreign carrier is codeshared with the national carrier Qantas. When flying to a less familiar destination, risk averse consumers are willing to pay a premium about two times higher than non-risk averse consumers, suggesting that partnerships have a strong impact on consumer valuation through reducing perceived risks and uncertainties associated with alien carriers. By this mechanism, home country bias may spillover to foreign partners of domestic firms.

Travellers often combine transport services from different firms to form trip chains: e.g. first taking a train and then a bus. Integration of different forms of public and private transport into a single service is gaining attention with the concept of Mobility as a Service (MaaS). Usually the attention focuses on such things as ease of use for travellers and shifting demand away from the car. We focus on the effects of MaaS on behaviour and welfare via the market structure of transportation. In particular, we analyse three archetypical ways in which MaaS could be operationalised: Integrator, Platform, and Intermediary. We find that these models differ strongly in how consumers and firms are affected by the availability of MaaS technologies. The Integrator model seems best for consumers and social welfare. It always leads to lower prices than free competition without MaaS and therefore benefits consumers; transport firm profits can be lower or higher. The Platform model tends to lead to an outcome that is relatively close to free competition without MaaS: prices can be higher or lower, while transport firm profits are lower. Finally, the Intermediary model tends to lead to much higher prices. Regulation of the price that the MaaS firm has to pay may lower prices, but, compared to the Integrator model, the change is often small. So, even without price regulation, MaaS supply can benefit consumers by increasing competition and removing serial marginalisation, even before we consider other benefits of MaaS.

This research aims to assess the broader impact of electric mobility in urban settlements, paying attention to both electrified ground and air transport. Considering electric cars as well as electric passenger drones, often referred to as UAM (urban air mobility), we use an urban spatial computable general equilibrium model to assess the welfare and environmental impacts of a transition to electric mobility. A numerical simulation of the model shows that a transition from gasoline to electric cars yields major emission reductions, while leading to welfare losses due to tax-induced market distortions. Introducing UAM into a gasoline-car city leads to marginal overall welfare gains. Introducing UAM into a city with electric cars results in welfare losses. While introducing UAM as an alternative to gasoline cars decreases CO2 emissions, the introduction of UAM as alternative to electric cars leads to increasing emissions.

We investigate the effects of carpooling in a dynamic equilibrium model of congestion, which captures various dimensions of heterogeneity: heterogeneity in the preference for and cost of carpooling, heterogeneity in values of time and values of schedule delay. We investigate various policy scenarios: no-toll, first-best pricing, and subsidization of carpooling. The optimally differentiated subsidy equals each type of users’ marginal external benefit (MEB) of switching to m-person carpooling or carpooling, which turns out to be heterogeneous for “ratio heterogeneity”, where the ratios of the values of time and schedule delay vary, and homogeneous for “proportional heterogeneity”, where these values vary in fixed proportion over the population. If such differentiation over users is impossible, the subsidy is a weighted average of the MEB’s, with the weights reflecting the relative sensitivity of the group size of carpoolers to the subsidy. Using a numerical example, we investigate the welfare effects and distributional effects of different policies. The relative efficiency of the differentiated subsidization first increases and then falls with the degree of ratio heterogeneity, and decreases over the entire parameter range and more with the degree of proportional heterogeneity.

Hypercongestion is the situation where a certain traffic flow occurs at a combination of low speed and high density, while a more favorable combination of these could produce the same flow. The macroscopic fundamental diagram (MFD) can describe hypercongestion, but does not explicitly explain the dynamic process that leads to hypercongestion. Earlier studies of hypercongestion on single links have, however, confirmed that these processes are important to consider. The bathtub model is a model that can be used to investigate how hypercongestion can arise in urban areas, when drivers choose their departure times optimally. This paper investigates equilibrium outcomes and user costs under the realistic assumption that there is finite capacity to exit the bathtub, without which it would be hard to explain why hypercongestion would not dissolve through shockwaves originating from the bathtub exit. We find that when the exit capacity of the bathtub is lower than the attempted equilibrium exit flow from the bathtub, no additional inefficiencies arise due to hypercongestion in the bathtub. This is because the travel time losses incurred by travelers in the bathtub are exactly offset by the reductions in travel time losses in exit queues, and thus the capacity of the full system is not affected. In contrast, when the exit capacity is higher than the equilibrium exit flows from the bathtub in the central part of the peak period, hypercongestion in the bathtub produces the additional inefficiencies known from the conventional textbook description. Our results thus show that the mere observation of hypercongested speeds does not necessarily mean that there is an efficiency loss from capacity drop at the level of the full system.

Recent technological developments open up possibilities for introducing a vast number of novel mobility concepts in urban environments. One of these new concepts is urban air mobility (UAM). It makes use of passenger drones for on-demand transport in urban settings, promising high travel speeds for those willing and able to pay. This research aims to answer the question how benefits from UAM will be distributed, taking into account the spatial dimension and the differential impacts on low- and high-skilled households. We develop a framework that can more generally be used to assess the welfare impacts resulting from the introduction of novel transport modes. The development of an urban spatial computable general equilibrium model building on the polycentric modelling tradition developed by Anas and co-authors allows for an analysis of mutually dependent effects on the land, labour and product markets, triggered by changes on the transport market. Allowing for an endogenous spatial structure through the introduction of agglomeration effects and an amenity-based approach, the framework investigates the relevance of the initial spatial structure for the impact of the introduction of UAM. Incorporating different skill levels of households allows to assess location choice and travel behaviour for households with different characteristics. A numerical simulation of the model shows that the different initial spatial structures impose comparable welfare changes. Variations in UAM features like marginal cost, prices, land demand for infrastructure, vertical travel speed and access and egress times have a (much) more decisive impact on modal choice and welfare effects than the initial urban structure. Simulations show that considering households of different skill levels brings additional insights, as welfare effects of UAM introduction strongly differ between groups and sometimes even go in opposing directions.

When traveling in an autonomous car, the travel time can be used for performing activities other than driving. This paper distinguishes users’ work-related and home-related activities in autonomous cars and proposes an activity-based bottleneck model to investigate travelers’ behavior in the morning commute, shedding light on how the scope to undertake in-vehicle activities affects travelers’ trip-timing preferences and decisions, and therewith social welfare. These welfare effects can be expected to depend on the optimality of both the market for trips, and the market for vehicles. We therefore consider different supply regimes for vehicles, as well as unpriced congestion versus queue-eliminating road pricing. We reveal analytically the relationship between various in-vehicle activities and trip-timing decisions by users of autonomous and normal cars. Three supply regimes for autonomous cars are investigated: welfare-maximizing public supply, competitive marginal cost supply, and profit-maximizing private supply. Pricing rules under different supply regimes are compared analytically, and the relative efficiencies in terms of the welfare gains are compared numerically. The results show that travelers’ in-vehicle activity choices have significant impacts on travel patterns, congestion externality, supply decisions, and the associated welfare effects.

With congestion being one of the most important externalities in transportation, it remains important to investigate effective and politically feasible solutions for it. We have conducted an 8-week experiment with tradable mobility permits, specifically applied to the use of parking facilities at a Dutch employer. We combine actual mobility behaviour with trading behaviour and survey responses of participants and non-participating employees of the same company. We have analysed the choice to participate in a voluntary experiment, and the behavioural response to tradable permits. Our results provide suggestive evidence that active participants do adjust their behaviour as intended. Furthermore, participation takes less time than people anticipate, and permits are viewed as a fairer and better functioning alternative to paid parking.

Recent technological developments open up possibilities for introducing a vast number of novel mobility concepts in urban environments. One of these new concepts is urban air mobility (UAM). It makes use of passenger drones for on-demand transport in urban settings, promising high travel speeds for those willing and able to pay. This research aims to answer the question how benefits from UAM will be distributed, taking into account the spatial dimension and the differential impacts on low- and high-skilled households. We develop a framework that can more generally be used to assess the welfare impacts resulting from the introduction of novel transport modes. The development of an urban spatial computable general equilibrium model building on the polycentric modelling tradition developed by Anas and co-authors allows for an analysis of mutually dependent effects on the land, labour and product markets, triggered by changes on the transport market. Allowing for an endogenous spatial structure through the introduction of agglomeration effects and an amenity-based approach, the framework investigates the relevance of the initial spatial structure for the impact of the introduction of UAM. Incorporating different skill levels of households allows to assess location choice and travel behaviour for households with different characteristics. A numerical simulation of the model shows that the different initial spatial structures impose comparable welfare changes. Variations in UAM features like marginal cost, prices, land demand for infrastructure, vertical travel speed and access and egress times have a (much) more decisive impact on modal choice and welfare effects than the initial urban structure. Simulations show that considering households of different skill levels brings additional insights, as welfare effects of UAM introduction strongly differ between groups and sometimes even go in opposing directions.

Hypercongestion—the phenomenon that higher traffic densities can reduce throughput—is well understood at the link level, but has also been observed in a macroscopic form at the level of traffic networks; for instance, in morning rush-hour traffic into a downtown core. In this paper, we show that macroscopic hypercongestion can occur as a purely emergent effect of dynamic equilibrium behavior on a network, even if the underlying link dynamics (we consider Vickrey bottlenecks with spaceless vertical queues) do not exhibit hypercongestion.

Congestion levels remain a substantial challenge, while the traditional economic response to congestion – road pricing – remains politically infeasible in most locations. Tradable permits are likely to be a more viable alternative, because they do not require a net financial flow from road users to the government. It is therefore the right moment to design and empirically test tradable permit schemes for managing urban mobility. This paper presents and empirically tests a complete design of a market for tradable permits, both in terms of the conceptual set-up of the market as well as its technical implementation. The design is evaluated against a number of criteria, including: transparency and containment of transaction costs, stability of permit prices in relation to the dynamic equilibrium on the mobility market and the prevention of undesirable speculation and fraud. We present evidence of the empirical functioning of this market, using the results of a conducted lab-in-the-field experiment with virtual mobility behaviour and real financial incentives.

We posit and empirically test the hypothesis that airlines are able to charge a fare premium in markets that originate in their domestic country relative to similar markets that originate in foreign countries. To this end, we focus on intercontinental one-stop air travel trips for which the main, intercontinental, flight legs are identical, while the feeder legs depart from a mixture of domestic- and foreign origins. We collect a unique database of published fares for such trips and estimate reduced form fare regressions with main flight leg fixed effects. We find that trips from and to domestic airports (compared with foreign airports) are characterized by about 9.5 per cent higher fares, even after adding controls for airport dominance, trip operating costs, the competitive environment and origin catchment area characteristics. These findings demonstrate that airlines have substantial domestic market power, enabling them to raise fares at their domestic airports irrespective of aforementioned market conditions. The magnitude of this domestic country effect is large relative to the traditional airport dominance effect, suggesting that the distinction between domestic- and foreign origins is a crucial determinant of the degree of market power that airlines can exert in the international airline industry.

This paper investigates second-best congestion pricing in a monocentric city characterized by distortionary, rigid regulatory mechanisms in the housing market (building height restrictions, zoning and property taxation). The Pigouvian toll is shown to retain its optimality under any setting with quantity restrictions in the housing market. However, the extent of the quantity restriction determines the volume of the welfare gains in a non-monotonic fashion. This finding introduces a warning to cost-benefit analyses: our numerical results suggest that the actual gains of a road tax might be 40% lower than the gains predicted by a model that disregards maximum building height restrictions, and 80% higher than the gains suggested by a model that disregards zoning. In general, this implies that decision making on urban road pricing can ignore quantitative restrictions in the related markets of land, housing and labor insofar as the determination of optimal marginal tax rules is concerned; the tax levels stemming from those rules will be affected by the restrictions. However, this is not the case in the presence of a tax-induced distortion. Introducing an ad- valorem property tax on housing, we show that adjustments of the Pigouvian toll can lead to small, but not negligible welfare gains.

There has been wide interest in private supply of roads as a solution to traffic congestion. We study its efficiency under demand uncertainty: we solve for equilibrium and optimum as benchmarks, and evaluate the efficiency of possible regulatory policies for private road operators. We obtain analytic solutions for simple networks and numerical simulation results for more complex ones. For two serial links and two parallel links, self-financing still holds in expected terms for the first-best case, even though the capacity is higher than the capacity for the deterministic demand equal to the expected value. When forced to apply the second-best optimal pricing, the private supplier makes an expected loss (profit) if there is an untolled substitute (complement) in the network. In contrast to the deterministic counterpart of the problem we study, regulation by competitiv e auction cannot replicate the second-best zero-profit result. For more complex networks, when private firms adds capacity one link at a time, entry by competitive auctions performs better than free entry. For the parameter range considered in the numerical simulation, entry by generalized auction performs better than entry by patronage auction.

We study different mixes of private and public supply of roads in a network with bottleneck congestion and heterogeneous users. There are two parallel links for one origin and destination pair and two groups of travellers, where the group with the higher value of time also has higher schedule delay values. Previous scholars argued that as users become more heterogeneous, they benefit more from product differentiation, making private supply of roads more efficient. However, we find that local monopoly power might also increase if there is a ‘separating equilibrium’, which is an equilibrium where at least one group only uses one private road due to the different combinations of toll and congestion of the two roads. The private road can thus increase its toll without worrying about the competition from the other road for this group: it has a local monopoly over them. This lowers the efficiency of private supply. The problem is especially severe with flat tolls, which are constant over the peak. With fine tolls – which vary continuously over the day – there tends to be a pooling equilibrium – where both types use both roads – and competition remains intense. Flat tolling is also worse for users than fine tolling, as it has higher generalized prices.

Travelers often combine transport services from different firms to form trip chains: e.g. first train and then a bus. Integration of different forms of public and private transport into a single service is gaining attention with the concept of Mobility as a Service (MaaS). Usually, the focus is on such things as ease of use, and shifting demand away from the car. We solely focus on the effects on behavior and welfare via the market structure of transport. In particular, we analyse three archetype ways in which MaaS could be ope-rationalized: Integrator, Platform, and Intermediary. We find that these models differ strongly in how consumers and firms are affected. The Integrator seems best for consumers and social welfare. It always leads to lower prices than Free Competition without Maas and therefore benefits consumers; transport firm profits can be lower or higher. The Platform tends to lead to an outcome that is relatively close to Free Competition without Maas: prices can be higher or lower, while transport firm profits are lower. Finally, the Intermediary tends to lead to much higher prices. Regulation of the price that the MaaS firm has to pay may further lower prices, but compared to the Integrator the difference is often small. So, even without price regulation, MaaS supply can already benefit consumers by increasing competition and removing serial marginalization, even before we consider other benefits of MaaS such as information provision, ease of use and a demand shift towards public transport.

Tradable credit schemes offer a potentially efficient, revenue-neutral policy alternative to classical dynamic pricing of congestion externalities. We show in this paper that the resulting equilibrium may not be unique for particular models of congestion, including the first-best solution for the conventional Vickrey's bottleneck model. This can have substantial detrimental impacts on social welfare and social acceptance of tradable credit schemes. The reason underlying this result is that the credit supply-demand condition can be satisfied for a continuum of credit prices. This is because any marginal change in the credit price will be matched by a compensating change in queuing times, keeping user price fixed but deviating from the first-best optimum in which no queueing should occur. We find that the problem of non-uniqueness does not occur for the dynamic flow congestion model proposed by Chu. A unique equilibrium can be obtained in the bottleneck model if the buying and selling of credits with a bank is allowed, against a pre-determined price. Credits are then still tradable so that the use can deviate from the initial distribution, but the credit price is determined by the perfectly elastic demand and supply from the bank.

Congestion levels have grown substantially in recent years, while the traditional economic response to congestion – road pricing – remains politically infeasible in most locations. Tradable permits are likely to be a more viable alternative, because they do not require a net financial flow from road users to the government. It is therefore the right moment to design and empirically test tradable permit schemes for managing urban mobility. This paper presents and empirically tests a complete design of a market for tradable permits, both in terms of the conceptual set-up of the market as well as its technical implementation. The design is evaluated against a number of criteria, including: transparency and containment of transaction costs, stability of permit prices in relation to the dynamic equilibrium on the mobility market and the prevention of undesirable speculation and fraud. We present evidence of the empirical functioning of this market, using the results of a conducted lab-in-the-field experiment with virtual mobility behaviour and real financial incentives.

Tradeable credit schemes offer a potentially efficient, revenue-neutral policy alternative to classical dynamic pricing of congestion externalities. We show in this paper that the resulting equilibrium may not be unique for particular models of congestion, including the first-best solution for the conventional Vickrey’s bottleneck model. This can have substantial detrimental impacts on social welfare and social acceptance of tradable credit schemes. The reason underlying this result is that the credit supply-demand condition can be satisfied for a continuum of credit prices. This is because any marginal change in the credit price will be matched by a compensating change in queuing times, keeping user price fixed but deviating from the first-best optimum in which no queueing should occur. We find that the problem of non-uniqueness does not occur for the well-known dynamic flow congestion model proposed by Chu. A unique equilibrium can be obtained in the bottleneck model if the buying and selling of credits with a bank is allowed, against a pre-determined price. Credits are then still tradeable so that the use can deviate from the initial distribution, but the credit price is determined by the perfectly elastic demand and supply from the bank.

We investigate the impacts of in-vehicle activities of commuters in the autonomous car on aggregate travel patterns. We allow for an autonomous car to affect the utility difference between being at home and being in the vehicle differently than the utility difference between being at work and being in the vehicle, compared to the differences experienced with a normal car. This affects the relative importance of values of travel delays, schedule delays early, and schedule delays late. Hence multiple possible changes in travel patterns may occur when autonomous cars become available. Switching to an autonomous vehicle may impose a net negative or positive externality, by raising the marginal external cost of autonomous cars themselves while lowering that of normal cars. We examine three provision regimes: marginal cost pricing, second-best pricing and profit-maximizing pricing by a private monopoly. The second-best mark-up (over marginal cost) rises with the price sensitivity, due to the increasing marginal external cost. Surprisingly, for the monopoly, mark-up may rise or fall with the price sensitivity, depending on the relative strength of the externality and of market power, where the former tends to raise it, and the latter tends to reduce it. Furthermore, the difference of the mark-up between private monopoly and second-best public provision falls as the demand becomes more price-sensitive.

This paper studies first-best and second-best congestion pricing in the presence of unobserved and observed preference heterogeneity using a stylised stochastic user equilibrium choice model. Travellers choose between multiple alternatives, have heterogeneous values of travel times, and may differ in their valuation of variety. We derive first-best and second-best tolls taking into account how the overall network demand responds to expected generalized prices, including tolls. For second-best pricing, we show that with homogeneous values of times the welfare losses of second-best pricing are smaller when route choice is probabilistic than when route choice is deterministic. Furthermore, we find that with heterogeneous values of times and benefits of variety, uniform second-best tolls and group-differentiated tolls can be very close, implying potentially low welfare losses from the inability to differentiate tolls. Finally, we show that there are cases where all groups benefit from second-best congestion pricing, but that these cases are likely to be politically unacceptable because tolls are then higher for low income groups.

The traditional bottleneck model for road congestion promotes the implementation of a triangular, and time varying, charge as the optimal solution for the road congestion externality. However, cognitive and technological barriers put a practical limit to the degree of differentiation real world implementations can handle. The traditional approach to accommodate for this concern has been a step toll, with the single step coarse charge as its simplest case. In this paper the authors study how efficiency of the coarse charge can be improved by differentiating its level and timing across groups of travellers. The authors use the traditional bottleneck model to analyse how the coarse charge can be differentiated over two groups of travellers assuming inelastic peak-hour demand. The results of the authors' analysis indicate that differentiating the coarse charge across two groups of travellers considerably improves its efficiency without increasing cognitive effort and decision making costs for the individual traveller. A numeric illustration reveals a welfare gain of 69% of the first-best charge, up from 53% for the generic coarse charge. This increase is similar to what is obtained by moving from the coarse charge to a generic two step toll. Once different groups have been defined, one could in fact achieve the same gains by temporal separation of drivers, for example by use of license plate numbers. The presented charging regime has a considerable degree of flexibility with respect to the share of travellers to attribute to each scheme, which further adds to its merits in practical applicability.

This paper analyzes the effect of carrier collaboration on fleet capacity, fleet structures in terms of the number and the size of vehicles, and load factors. The model features complementary networks, scheduling, price elastic demands, and demand uncertainty. For the case of a given number of vehicles, the analysis shows that carrier collaboration increases vehicle sizes (thus, fleet capacity) if marginal seat costs are low while fleet capacity remains unchanged if marginal seat costs are high. If both vehicle sizes and vehicle numbers can be varied, then collaboration will always increase vehicle numbers and fleet capacity, while the effects on vehicle sizes and, thus, also load factors, are ambiguous and therewith hard to predict. Numerical simulations indicate that collaboration increases expected load factors also when the number of vehicles is endogenous.

We study the trip scheduling preferences of train commuters in a real-life setting. The underlying data have been collected during large-scale peak avoidance experiment conducted in the Nether- lands, in which participants could earn monetary rewards for traveling outside peak hours. The experiment included ca. 1000 participants and lasted for multiple months. Holders of an annual train pass were invited to join the experiment, and a customized smartphone app was used to measure the travel behavior of the participants. We find that compared to the pre-measurement, the relative share of peak trips decreased by 22% during the reward period, and by 10% during the post-measurement. By combining multiple complementary data sources, we are able to specify and estimate (MNL and panel latent class) departure time choice models. These yield plausible estimates for the monetary values that participants attach to reducing travel time, schedule delays, the number of transfers, crowdedness, and unreliability.

When drivers opt for carpooling, road capacity will be freed up, and this will reduce congestion. Therefore, carpooling is interesting for policy makers as a possible solution to congestion. We investigate the effects of carpooling in a dynamic equilibrium model of congestion, which captures various dimensions of heterogeneity: heterogeneity in preference for carpooling, "ratio heterogeneity" between the values of time and the values of schedule delay, and "proportional heterogeneity" that scales all values equally. We investigate three policy scenarios: no-toll, first-best pricing, and subsidization of carpooling. The optimal second-best subsidy equals each type’s heterogeneous marginal external benefit (MEB) of switching to carpooling. If such differentiation is impossible, the third-best subsidy is a weighted average of the MEBs, where the weights depend on the number of each type and their sensitivity to the subsidy. In our numerical example, we find that when increasing the degree of "ratio heterogeneity", the relative efficiency of the second-best subsidization first increases and then falls with the degree of heterogeneity and L type carpoolers benefit more than H type carpoolers. However, when increasing the degree of "proportional heterogeneity", H type users benefit more than L types for both solo drivers and carpoolers. Moreover, the relative efficiency of the second-best subsidization decreases throughout.

Economic globalization has spurred the growth of international cooperation between companies. This paper analyzes partnerships between foreign and domestic firms as a source of signaling advantages. When partnerships affect the products offered, it is not possible to isolate this signaling impact. Virtual codesharing is an important type of marketing partnership in aviation that does not change the product and hence provides the opportunity to identify the direct impact of partnerships on consumer valuation of the partnered products. Roughly 75 per cent of the flights in trans-Atlantic and Pacific markets involves codesharing. Typically, the consumer buys the ticket with the domestic airline, while a foreign airline operates the flight. Analyzing individual-level choice data from a representative panel of Australian air travelers, we find that the average consumer is willing to a pay a premium between 4 and 5.5% of the ticket price when a flight by a foreign carrier is codeshared with the national carrier Qantas. When flying to a less familiar destination, risk averse consumers are willing to pay a premium about two times higher than non-risk averse consumers, suggesting that partnerships have a strong impact on consumer valuation through quality signaling.

Earlier studies on scheduling behavior have mostly ignored that consumers have more flexibility to adjust their schedule in the long run than in the short run. We introduce the distinction between long-run choices of travel routines and short-run choices of departure times, using data from a real-life peak avoidance experiment. We find that participants value travel time higher in the long-run context, supposedly because changes in travel time can be exploited better through the adjustment of routines. Schedule delays are valued higher in the short run, reflecting that scheduling restrictions are typically more binding in the short run.

Accident externalities that individual drivers impose on one another via their presence on the road are among the most important external costs of road transport. We study the regulation of these externalities when insurance companies have market power. Some of the results we derive have close resemblance to the earlier literature on externality regulation with market power in aviation and private roads, but there are important differences, too. Using analytical models, we compare the first-best public welfare-maximizing outcome with a private profit-maximizing monopoly, and oligopoly. We find that insurance companies will internalize some of the externalities, depending on their degree of market power. We derive optimal insurance premiums, and regular parametric taxes as well as “manipulable” ones that make the companies set socially optimal premiums. The latter take into account that the firm tries to exploit knowledge of the tax rule applied by the government. Finally, we also study the taxation of road users rather than that of firms.

The famous Mohring-Harwitz theorem states that, under certain technical conditions, the degree of self-financing of congested infrastructure is equal to the elasticity of the capacity cost function in the optimum, so that under neutral scale economies exact self-financing applies. Although the theorem has been proven to remain valid for various extensions of the basic set-up for which it was originally derived, it breaks down when the infrastructure is used by operators with market power when competing in Cournot fashion, the case in point often being oligopolistic airlines at a congested airport. This paper proposes a regulatory scheme, not involving lump-sum payments or budget constraints in the optimal pricing problem, that restores self-financing for congested infrastructure for this market form. What is more, under the proposed scheme, exact self-financing applies independent of the elasticity of the capacity cost function. The result remains true both for the case where operators treat the tolls parametrically, and for 'manipulable' tolls, designed to account for the fact that operators with market power can be expected to be aware of, and exploit, the fact that toll are not truly parametric, but instead depend on their own behaviour.

We analyse congestion pricing in a road and rail network, where the two modes are imperfect substitutes. On the road there is bottleneck congestion; in each train there is crowding congestion. We model two dimensions of preference heterogeneity; these two dimensions have opposite effects on the welfare impact of congestion pricing and lead to different distributional effects. The distributional effects also differ between road and rail. On the road, pricing is generally more beneficial with a higher value of time or schedule delay. In the train, pricing has no distributional effects or is less beneficial with a higher value. © 2013 Hong Kong Society for Transportation Studies Limited.

This paper analyzes efficient pricing at a congested airport dominated by a single firm. Unlike much of the previous literature, we combine a dynamic bottleneck model of congestion and a vertical structure model that explicitly considers the role of airlines and passengers. We show that a Stackelberg leader interacting with a competitive fringe partially internalizes congestion, and that there are various toll regimes that induce the welfare maximizing outcome, widening the set of choices for regulators. In particular, charging the congestion toll that would apply for fully competitive carriers and that ignores any internalization, to both the leader and the fringe, yields the first-best outcome. © 2013 Elsevier Inc.

This paper investigates and compares airport pricing policies under various types of competition, considering both per-passenger and per-flight charges at congested airports. We show that an airport requires both pricing instruments to achieve the first-best outcome, and we distinguish their role by showing that congestion externalities need to be addressed through per-flight tolls whereas the inefficiency caused by airlines' market power exertion must be corrected with per-passenger subsidies. We also show that Bertrand competition with differentiated products, a type of behavior recently pointed out by the empirical literature as pertinent, has policy implications that diverge from analyses that assume Cournot competition. The welfare gains and congestion reductions of congestion pricing would be higher than what has been advanced before; the degree of self-financing of airport infrastructure under optimal pricing would be increased and may approach exact self-financing; and the implied differentiation of charges between (asymmetric) airlines would be significantly smaller, presumably enhancing the political feasibility of welfare maximizing congestion pricing, as the potential distributional concerns would be decreased. Finally, we numerically analyze second-best policies, and find that atomistic pricing may offer a relatively attractive alternative to first-best congestion pricing. © 2013 Elsevier B.V.

We study different mixes of private and public supply of roads in a network with bottleneck congestion and heterogeneous users. There are two parallel links for one origin and destination pair and two groups of travellers, where the group with a higher value of time also has higher schedule delay value. Previous scholars argued that as users become more heterogeneous, they benefit more from product differentiation, making private supply of roads more efficient. However, we find that local monopoly power might also increase. This may occur if one group prefers one road over the other as the two offer different combinations of toll and travel delay. The private supplier can thus increase the toll on its link without worrying that the targeted travellers will move to the other link. This can undermine the efficiency of private supply of roads. The problem is especially severe with flat tolls. With queue-eliminating tolls, both types tend to travel on both roads, and competition remains relatively intense. Flat tolling is always worse for users than time-variant tolling as it has the higher generalized prices, and it also leads to a lower welfare.

Recent empirical work has suggested that there is an important distinction between short-run versus long-run scheduling behaviour of commuters, reflected in differences in values of time and schedule delays, as well as in preferred arrival moments, for the short-run versus the long-run problem. Peer et al. (2015) for example find that the average value of time when consumers form their routines in the long-run problem may exceed by a factor 6 the short-run value that governs departure time choice given these routines. For values of schedule delay, in contrast, the short-run value exceeds the long-run value, by a factor 2. And, when forming routines, consumers in fact choose a most preferred arrival time that may deviate from the value they would choose in absence of congestion because a change in routines may mean that shorter delays will be encountered. This paper investigates whether this distinction between short-run and long-run scheduling decisions affect optimal pricing of a congestible facility. Using a stochastic dynamic model of flow congestion for describing short-run equilibria and integrating it with a dynamic model of routine formation, it is found that consistent application of short-run first-best optimal congestion pricing does not optimally decentralize the optimal formation of routines in the long-run problem. A separate instrument, next to road pricing, is therefore needed to optimize routine formation.

In the present study, we investigate the impact of real-time traffic information on traveller behaviour by using repeated day-to-day revealed-preference (RP) observations from a reward experiment. We estimate a trip scheduling model of morning peak behaviour that allows us to determine the impact of traffic information on travel behaviour. Specifically, we distinguish between the marginal impact of expected travel times versus that of deviations from this expectation upon user behaviour. We find that participants to the experiment who were given access to a smart-phone displaying real-time traffic information react to the daily variations in travel times stronger than they had done in the pre-trial period. This we interpret as evidence that provision of traffic information indeed affects behaviour. However, we also find that participants who were not given the smart-phone also respond to daily variations in travel times – suggesting that these drivers use other sources of information to help their trip planning, or were better capable of processing information available into travel time predictions.

Unreliable travel times cause substantial costs to travelers. Nevertheless, they are often not taken into account in cost-benefit analyses (CBA), or only in very rough ways. This paper aims at providing simple rules to predict variability, based on travel time data from Dutch highways. Two different concepts of travel time variability are used, which differ in their assumptions on information availability to drivers. The first measure is based on the assumption that, for a given road link and given time of day, the expected travel time is constant across all working days (rough information: RI). In the second case, expected tra- vel times are assumed to reflect day-specific factors such as weather conditions or week- days (fine information: FI). For both definitions of variability, we find that the mean travel time is a good predictor. On average, longer delays are associated with higher variability. However, the derivative of variability with respect to delays is decreasing in delays. It can be shown that this result relates to differences in the relative shares of observed traffic ‘regimes’ (free-flow, congested, hyper-congested) in the mean delay. For most CBAs, no information on the relative shares of the traffic regimes is available. A non-linear model based on mean travel times can then be used as an approximation.

Speeding is an important cause for young drivers' involvement in traffic accidents. A reduction in driving speeds of this group could result in fewer accidents. One way of reducing driving speed is offering explicit financial incentives. In collaboration with five Dutch car insurance companies, we tested the effects of a Pay-As-You-Drive insurance fee on driving speed. A group of young drivers could save money on their monthly insurance fee by keeping the speed limit. Driving speed was monitored through GPS technology during one year. Analyses showed that, relative to pre- and post-measurement, as well as a control group, the introduction of a Pay-As-You-Drive insurance fee significantly reduced speed violations of young drivers. (C) 2011 Elsevier Ltd. All rights reserved.

When analysing the effects of transport policies it is important to adequately control for heterogeneity: previous studies note that ignoring heterogeneity biases the estimated welfare effects of tolling. This paper examines the effects of tolling, in a bottleneck model, with a continuously distributed value of time. With homogeneous users, first-best public tolling has no effect on prices. With heterogeneity it does: low values of time lose, and high values of time gain. The average congestion externality decreases with the heterogeneity in the value of time. Consequently, the welfare gain of first-best tolling also decreases. The more heterogeneous the value of time is, the lower the relative efficiency of a public pay-lane. This finding contrasts with the previous literature. Earlier studies, using static flow congestion, conclude that the relative efficiency increases with this type of heterogeneity. With more heterogeneity in the value of time, the relative efficiency of a private pay-lane is also lower, while that of a public time-invariant toll is higher. Our results suggest that the welfare gains of different tolling schemes are affected differently by heterogeneity. Further, the impact of heterogeneity on the effects of a policy also depends on the type of congestion considered. © 2010 Elsevier Ltd.

This paper considers the use of 'long-run cost functions' for congested networks in solving second-best network problems, in which capacity and tolls are instruments. We derive analytical results both for general cost and demand functions and for specific functional forms, namely Bureau of Public Roads cost functions and constant-elasticity demand functions. The latter are also used in a numerical simulation model. We consider second-best cases where only a sub-set of links in a network is subject to tolling and/or capacity choice, and cases with and without a self-financing constraint imposed. We will demonstrate that, under certain assumptions, second-best long-run cost (or actually: generalized price) functions can be derived for most of the cases of interest, which can be used in an applied network model as a substitute for the conventional short-run user cost functions. Doing so reduces the dimensionality of the problem and should therefore be helpful in speeding up procedures for finding second-best optima. © 2009 Elsevier Ltd.

Urban (re-)development projects may generate various positive and negative spatial externalities to employers. The assessment of such benefits is fraught with many methodological and empirical problems. This study aims to assess the order of magnitude of expected net benefits for incumbent employers that may accrue from a large-scale development project in the Zuidas area in the South-Western part of Amsterdam, the Netherlands. This development project is planned to transform the area into a large multifunctional urban agglomeration. We employ a specific stated preference method (namely, a willingness-to-pay method) to gauge the project's net socio-economic benefits for the current firms in the area concerned, paying special attention to the benefits associated with multifunctionality.

This paper studies the regulation of an airline duopoly on a congested airport. Regulation should then address two market failures: uninternalized congestion, and overpricing due to market power. We find that first-best charges are differentiated over airlines if asymmetric, and completely drive out the least efficient airline from the market. This is not generally the case for an undifferentiated charge, which is found to be a weighted average of first-best charge rules for the two airlines, and is less-than-optimally efficient because of its inability to differentiate between them. Tradable slots may yield the first-best outcome if the congestion externality is relatively important and the market power distortion relatively unimportant, but may be less efficient than non-intervention when the reverse is true. © 2009 Elsevier Ltd. All rights reserved.

Private toll roads are now seriously considered as an alternative to public (free-access) road infrastructure. Nevertheless, complete private provision without governmental control is only rarely considered. A main consideration against private roads would be that operators would be primarily interested in maximizing profits, which - given the market power they will have - will typically not lead to welfare-maximizing tolls and capacities. An important question is whether these discrepancies can be mitigated by a proper design of auctions for concessions of private roads. This paper therefore analyses capacity choice and toll setting by private investors in a competitive bidding framework organized by the government. We develop a two-link network simulation model with an untolled alternative to determine relative efficiency effects, and analyze rules for the government to organize the bidding process such that a more desired (welfare optimal) outcome is achieved. Our results show that, depending on the design of the auction, its outcomes may vary strongly, and may approach the maximum possible (second-best) welfare gains. © 2007 Elsevier Ltd. All rights reserved.

This paper proposes an alternative, dynamic framework for estimating time-varying values of travel time savings and values of schedule delay, in which time-preferences are represented as the time-varying excess-willingness-to-pay (EWPT) to being in the one location, over being elsewhere. It is shown how the conventional linear model, with time-independent values of travel time savings and schedule delay costs, is a special case of our model, and that it is implausible particularly in that it implicitly assumes that the willingness to pay for spending a minute at home instead of being in the vehicle does not vary by time of day, even not for very early departures. The framework is applied to SP data representing the respondents' departure time choices for the morning commute. The results suggest that individuals' time-related shadow prices indeed vary strongly over the morning peak, and values of travel time savings are consequently strongly time-dependent, following plausible and intuitive patterns. © 2007 Elsevier Ltd. All rights reserved.