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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.

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.

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.

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.

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.

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.

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.

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 reports the results of a stated preference study investigating the willingness-to-pay (WTP) of employees at the Amsterdam Zuidas for the presence of nonshopping and shopping facilities. The Amsterdam Zuidas area, surrounding the current train–metro–tram station Amsterdam Zuid World-Trade-Centre, is the largest multifunctional land-use project currently under development in the Netherlands. For nonshopping facilities, the results show that employees have the highest WTP for the presence of day-care centres and public transport facilities, and the lowest for public and recreation facilities. The average WTP for the presence of nonshopping facilities amounts to approximately €29 per month per employee. The WTP for the presence of shopping facilities is estimated at €25 per month per employee on average, and is in absolute value highest for supermarkets and lowest for flowershops and dry cleaners.

‘Robot cars’ are cars that allow for automated driving. By allowing cars to safely drive closer together than human driven ‘normal cars’ do, robot cars raise road capacity. By allowing drivers to perform other activities in the vehicle, they lower the value of travel time delays (VOT). We investigate the social welfare effect of robot cars using a dynamic equilibrium model of congestion that captures the following mechanisms: the resulting increase in capacity, the decrease in VOT and the implications for the heterogeneity in the VOT. We do so for a number of market organizations: private monopoly, perfect competition and public supply. Increasing the share of robot cars raises average capacity, but may hurt existing robot car users as the switchers, through their altered departure time behaviour, will impose higher congestion externalities. Depending on which effect dominates, buying a robot imposes a net negative or positive externality. Numerical analysis suggests that a net positive externality is more likely; nevertheless, for a small, but still plausible, capacity effect a net negative externality results. With a positive (negative) externality, marginal cost provision under perfect competition tends to lead to an undersupply (oversupply) of robot cars, and a public supplier needs to subsidise (tax) robot car purchase in order to maximise welfare. A monopolist supplier ignores the externality and tends to add a mark-up to its price. This almost always leads to a substantial undersupply.

Advanced traveller information systems (ATIS) are likely to exhibit significant economies of scale in production and operation. Private provision would therefore typically occur under considerable market power. An important policy question is whether the resulting distortions would aggravate or reduce distortions in the transport market itself, notably external effects such as congestion. We consider such questions by presenting an integrated model that captures the interactions between a congested transport market and a monopolistic market for advanced traveller information systems (ATIS). Three market failures operate simultaneously: congestion on the road, a declining average benefit of information when information penetration rises, and monopolistic pricing by the provider of information. Some key results are as follows. Monopoly information pricing appears not to be the most attractive option from a system efficiency viewpoint. A subsidy in the information market can help realise a second-best optimum of road use. Relatively low uncertainty on the road and high information costs limit the monopolist's profit on the information market, as well as relative system efficiency. While relatively inelastic demand for mobility, counter intuitively, negatively affects the monopolist's profit, the relative social benefits from private information peak at intermediate demand elasticities. © 2005 Elsevier Ltd. All rights reserved.

A dynamic ‘car-following’ extension of the conventional economic model of traffic congestion is presented, which predicts the average cost function for trips in stationary states to be significantly different from the conventional average cost function derived from the speed-flow function. When applied to a homogeneous road, the model reproduces the same stationary state equilibria as the conventional model, including the hypercongested ones. However, stability analysis shows that the latter are dynamically unstable. The average cost function for stationary state traffic coincides with the conventional function for non-hypercongested traffic, but rises vertically at the road’s capacity due to queuing, instead of bending backwards. When extending the model to include an upstream road segment, it predicts that such queuing will occur under hypercongested conditions, while the general shape of the average cost function for full trips does not change, implying that hypercongestion will not occur on the downstream road segment. These qualitative predictions are verified empirically using traffic data from a Dutch bottleneck. Finally, it is shown that reduced-form average cost functions, that relate the sum of average travel cost and average schedule delay costs to the number of users in a dynamic equilibrium, certainly need not have the intuitive convex shape, but may very well be concave – despite the fact that the underlying speed-flow function may be convex.

This article discusses a number of issues that will become increasingly important now that the concept of marginal external cost pricing becomes more likely to be implemented as a policy strategy in transport in reality. The first part of the article deals with the long-run efficiency of marginal external cost pricing. It is shown that such prices not only optimize short-run mobility, given the shape and position of the relevant demand and cost curves, but even more importantly, also optimally affect the factors determining the shape and position of these curves in the long run. However, first-best prices are a hypothetical bench-mark only. The second part of the article is therefore concerned with more realistic pricing options. The emphasis is on the derivation of second-best pricing rules. Four types of second-best distortions are considered: distortions on other routes, in other modes, in other economic sectors, and due to government budget constraints.

Conventional economic models of traffic congestion assume that the relation between traffic flow and speed is a technical one. This paper develops a behavioural model of traffic congestion, in which drivers optimize their speeds by trading off time costs, expected accident costs and fuel costs. Since the presence of other drivers affects the latter two cost components and hence the Nash equilibrium speed, a ‘behavioural’ speed-flow relationship results for which external congestion costs include expected accident costs and fuel costs, in addition to the time costs considered in the conventional model. It is demonstrated that the latter in fact even cancel in the calculation of optimal congestion tolls. The overall welfare optimum in our model is found to be off the speed-flow function, and off the average and marginal cost functions derived from it in the conventional approach. This full optimum requires tolls to be either accompanied by speed policies, or to be set as a function of speed. Using an empirically calibrated numerical simulation model, we illustrate these qualitative findings, and attempt to assess their potential empirical relevance.

This paper investigates strategic interactions between a private highway operator and a private transit operator who uses the same highway for its services. Heterogeneity of travellers is taken into account by considering a continuous distribution of values of time. Demand elasticity arises from the inclusion of an outside virtual mode. Game theory is applied to model the possible moves taken by the operators in their interactions. Four games are formulated, representing different decision making processes, including Nash and Stackelberg (leader-follower) games. The different timings of long-run and short-run decisions are also modeled in a two-stage game. Our results indicate that the market equilibria in the four games formulated are quite different as a result of the different sequences of moves. The highway operator is considered to be in a better position in terms of profit making in most cases, while for the transit operator it will generally be more advantageous to be the follower rather than in the leader position.

This paper analyses the adoption of energy-efficiency enhancing technologies by heterogeneous firms. The fact that energy use does not only cause external environmental costs through pollution, but also directly affects the profitability of the firm and hence its behaviour on input and output markets is taken for granted. It is demonstrated that the consideration of such market processes may have important implications for the efficiency of environmental policies concerned with energy use. The analysis focuses in particular on the efficiency of the market-led adoption and diffusion process under various policy regimes. It is shown that the promotion of energy-efficiency enhancing technologies might have unexpected effects in that it could lead to an increase in energy use, while the use of energy taxes might actually reduce the attractiveness of energy-saving technologies.

This paper studies road safety and accident externalities when insurance companies have market power, and can influence road users' driving behaviour via insurance premiums. We obtain both welfare and profit maximizing marginal conditions for first- and second-best insurance premiums for monopoly and oligopoly market structures in insurance. The insurance program consists of an insurance premium, and marginal dependencies ("slopes") of that premium on speed and on the own safety technology choice. While a private monopolist internalizes accident externalities up to the point where compensations to users' benefit matches the full (immaterial) costs, in oligopolistic markets insurance firms do not fully internalize accident externalities that their customers impose upon one another. Therefore, non-optimal premiums as well as speed and technology control apply. Analytical results demonstrate how insurance firms' incentives to influence traffic safety deviate from socially optimal incentives.

Various contributions to the recent literature on congestion pricing have demonstrated that when services at a congestible facility are provided by operators with market power, the case in point often being a few airlines jointly using a congested airport, optimal congestion pricing rules deviate from the familiar Pigouvian rule that tolls be equal to the marginal external costs. The reason is that an operator with market power has an incentive to internalize the congestion effects that its customers and vehicles impose upon one-another, so that Pigouvian tolling would lead to overpricing of congestion. More recent contributions to this literature, however, have brought to the fore that when congestion at the facility takes on the form of dynamic bottleneck congestion a la Vickrey (1969), where trip scheduling is the key behavioural margin, there may exist no Nash e quilibrium in arrival schedules for oligopolistic operators also under rather plausible assumptions on parameters. This paper investigates whether in such cases, an equilibrium does exist for another congestion technology, namely the Henderson-Chu dynamic model of flow congestion. We find that a stable and unique equilibrium exists also in cases where it fails to exist under bottleneck congestion (notably when the value of schedule late exceeds the value of travel delays). Our results suggest that self-internalization with only two firms leads to a considerable efficiency gain compared to the atomistic equilibrium (83% or more of the gain from first-best pricing in our numerical exercises).

This paper studies road safety and accident externalities when insurance companies have market power, and can influence road users' driving behaviour via insurance premiums. We obtain both welfare and profit maximizing marginal conditions for first- and second-best insurance premiums for monopoly and oligopoly market structures in insurance. The insurance program consists of an insurance premium, and marginal dependencies ("slopes") of that premium on speed and on the own safety technology choice. While a private monopolist internalizes accident externalities up to the point where compensations to users' benefit matches the full (immaterial) costs, in oligopolistic markets insurance firms do not fully internalize accident externalities that their customers impose upon one another. Therefore, non-optimal premiums as well as speed and technology control apply. Analytical results demonstrate how insurance firms' incentives to influence traffi c safety deviate from socially optimal incentives.

This paper distinguishes uncertainty types that differ continuously with respect to the degree to which uncertainty affects the optimal price/price markup or optimal quantity. A monopoly example is used to show that seemingly strong assumptions on functional forms can represent a wide variety of different scenarios, while (implicit) assumptions on continuous uncertainty types can lead to quite special results. Monopoly examples of the newsboy problem type are further used to show that the optimal capacity level and the optimal composition of capacity in terms of the number and size of production units depends crucially on the type of uncertainty and the employed functional forms for utilities and costs.

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.

This paper studies urban sustainability from the perspective of externalities. We develop a general spatial equilibrium model of a monocentric city, in which two types of externalities occur. On the one hand, pollution in the industrial center leads to a spatially differentiated deterioration of the environmental quality in the residential area. On the other hand, the existence of the city is explained by agglomeration economies, represented as simple Marshallian external benefits in production. We investigate free-market versus first-best and second-best optimal spatial equilibria, and conclude that the pursuit of environmental goals may sometimes come at the expense of reduced agglomeration economies, but may actually sometimes also stimulate these economies.

This article investigates competition in a market with an emerging technology using a discrete choice model to analyze demand and welfare. We focus on industry structure and investigate the impact of different market structures on demand for the new technology and on welfare. The car market serves as a prime example of such a market, where electric vehicles (EV’s) represent the new technology competing with standard cars with internal combustion engines (ICV’s). To analyze such a market, we use a nested logit model. In contrast to earlier literature, we allow firms to be asymmetric and active in multiple nests, with different numbers of variants in each nest, which can add up to any market share. Additionally, we add to existing literature by considering the case where substitutability between firms is stronger than between technologies, by nesting products by technology instead of by firm. We find implicit analytical solutions for the equilibrium mark-ups which can be used when there are two nests in the market; within that restriction firms can be asymmetric. Numerically, we find that EV sales are higher if offered by a new entrant only selling EV’s as opposed to when it is supplied by a firm selling variants of both types. We present an index based on mark-up differences between variants in the market, which can be used to a priori determine whether a change in market structure would increase or decrease welfare. These results are general to the nested logit model, and the index can thus be used in any market, as long as the market is sufficiently accurately described by the nested logit model.

Background: The purpose of this study was to determine if there were usability and training differences between the Medtronic MiniMed Paradigm Revel™ Insulin Pump and the Tandem Diabetes Care t:slim® Insulin Pump during use by representative users, performing representative tasks, in a simulated use environment. Methods: This study utilized a between-subjects experimental design with a total of 72 participants from 5 sites across the United States. Study participants were randomized to either the Revel pump group or the t:slim Pump group. Participants were 18 years of age or older and managed their diabetes using multiple daily insulin injections. Dependent variables included training time, training satisfaction, time on task, task failures, System Usability Scale (SUS) ratings, perceived task difficulty, and a pump survey that measured different aspects of the pumps and training sessions. Results: There was a statistically significant difference in training times and error rates between the t:slim and Revel groups. The training time difference represented a 27% reduction in time to train on the t:slim versus the Revel pump. There was a 65% reduction in participants’ use error rates between the t:slim and the Revel group. The t:slim Pump had statistically significant training and usability advantages over the Revel pump. Conclusions: The reduction in training time may have been a result of an optimized information architecture, an intuitive navigational layout, and an easy-to-read screen. The reduction in use errors with the t:slim may have been a result of dynamic error handling and active confirmation screens, which may have prevented programming errors.

This paper deals with first-best and second-best congestion pricing of a stylised two-link network with probabilistic route choice of travellers. Travellers may have heterogeneous values of travel times and may differ in their idiosyncratic route preferences. We derive first-best and second-best tolls taking into account how the overall network demand responds to generalized costs including the tolls that are levied. We show that with homogeneous values of times the welfare losses of second-best pricing, of one link only, may be smaller if route choice is probabilistic. Furthermore, we show that with heterogeneous values of times, common second-best tolls and group-differentiated tolls can be very close when route choice is governed by random utility maximisation, leading to low welfare losses from the inability to differentiate tolls.

This paper presents a dynamic version of the standard static economic model of road traffic congestion, based on car-following theory. It is proven formally and illustrated numerically that the "hypercongested" equilibria found in the standard model are dynamically unstable. For arrival rates of users below the road's maximum capacity, the model reproduces the non-hypercongested stationary state outcomes found in the standard model. When the arrival rate exceeds this maximum capacity, however, the model produces outcomes consistent with Vickrey's model of bottleneck congestion. The model thus offers an integration and a generalization of these two archetype models. © 2001 Academic Press.

This paper empirically analyses the social feasibility of a wide range of transport policy measures. After a literature review, some general results of a project on the support for transport policy measures in the Netherlands are discussed. Next, a statistical analysis of opinions of various relevant subgroups of citizens is carried out. It appears that safety problems are considered most important from an individual point of view, while environmental problems are most severe from a social point of view. Measures with small direct effects on the behaviour of respondents are generally regarded as most effective by the respondents. The support for safety measures is highest, while perceived problems and effectiveness as well as personal features also influence the support for policy measures. It is concluded that the social support for transport policy measures and packages can be increased by attending to these underlying factors.

In this paper we investigate interdependencies between transport, spatial economy, and the environment in the context of policies aimed at a global environmental target. A small-scale spatial price equilibrium model is formulated and used to perform a number of numerical simulations, and to investigate market-based versus environmentally sound spatioeconomic configurations with first-best and second-best policies, and with endogenous environmental technologies. We thus present a modelling framework capable of dealing with complexities associated with the simultaneous regulation, first-best and second-best, of multiple interdependent sectors in a spatial setting.

This discussion paper resulted in a publication in the 'Journal of Urban Economics' . This paper explores the interactions between congestion pricing and a tax-distorted labor market within a monocentric urban equilibrium model. We compute the efficiency gains of various second-best policies, i.e. combinations of toll schemes and revenue recycling programs, with a predetermined level of public revenue. We find that 35% of the space-varying road tax does not reflect marginal external congestion costs, but rather functions as a Ramsey-Mirrlees tax, i.e. an efficiency enhancing mechanism allowing space differentiation of the labor tax. Such a space-varying tax adds a quite different motivation to road pricing, since it can produce large welfare gains even in the absence of congestion. We show that both a cordon toll and a flat kilometer tax achieve over 80% of these gains when combined with specific types of revenue recycling, such as labor tax cuts or public transport subsidies. Sensitivity analysis shows that the optimal type of revenue recycling depends on the level of inefficiency in the provision of public transport prior to the introduction of congestion pricing.

We consider equilibrium and optimum use of a Vickrey road bottleneck, distinguishing between long-run and short-run scheduling preferences in an otherwise stylized scheduling model. The preference structure reflects that there is a distinction between the (exogenous) 'long-run preferred arrival time', which would be relevant if consumers were unconstrained in the scheduling of their activities, versus the 'short-run preferred arrival time', which is the result of an adaptation of travel routines in the face of constraints caused by, in particular, time-varying congestion levels. We characterize the unpriced equilibrium, the social optimum as well as second-best situations where the availability of the pricing instruments is restricted. All of them imply a dispersed distribution of short-run preferred arrival times. The extent of dispersion in the unpriced equilibrium, however, is higher than socially optimal.

This discussion paper resulted in a publication in the 'Journal of Urban Economics' , 2015, 86, 1-8. Accident externalities are among the most important external costs of road transport. We study the regulation of these when insurance companies have market power. Using analytical models, we compare a public-welfare maximizing monopoly with a private profit-maximizing monopoly, and markets where two or more firms compete. A central mechanism in the analysis is the accident externality that individual drivers impose on one another via their presence on the road. Insurance companies will internalize some of these externalities, depending on their degree of market power. We derive optimal insurance premiums, and "manipulable" taxes that take into account the response of the firm to the tax rule applied by the government. Furthermore, we study the taxation of road users under different assumptions on the market structure. We illustrate our analytical results with numerical examples, in order to better understand the determinants of the relative performance of different market structures.

We consider equilibrium and optimum use of a Vickrey road bottleneck, distinguishing between long-run and short-run scheduling preferences in an otherwise stylized scheduling model. The preference structure reflects that there is a distinction between the (exogenous) 'long-run preferred arrival time', which would be relevant if consumers were unconstrained in the scheduling of their activities, versus the 'short-run preferred arrival time', which is the result of an adaptation of travel routines in the face of constraints caused by, in particular, time-varying congestion levels. We characterize the unpriced equilibrium, the social optimum as well as second-best situations where the availability of the pricing instruments is restricted. All of them imply a dispersed distribution of short-run preferred arrival times. The extent of dispersion in the unpriced equilibrium, however, is higher than socially optimal.

We derive the expected user costs of US domestic air travel delay variability taking into account scheduling behavior of travelers. Travelers do not only consider mean arrival delays, but also face scheduling costs because they arrive too early or too late at their destination. The model allows travelers to anticipate arrival delay variability by choosing an earlier flight. We show that the expected user costs of US air traffic delays are underestimated by 16% if arrival delay variability is ignored.

This paper examines congestion taxes in a monocentric city with pre-existing labor taxation. When road toll revenue is used to finance labor tax cuts, 35% of the optimal road tax in our numerical model does not reflect marginal external congestion costs, but rather functions as a Ramsey–Mirrlees tax, i.e. an efficiency enhancing mechanism allowing for an indirect spatial differentiation of the labor tax. This adds a quite different motivation to road pricing, since welfare gains can be produced even in absence of congestion. We find that the optimal road tax is non-monotonic across space, reflecting the different impacts of labor supply elasticity and marginal utility of income, which both vary over space. The relative efficiencies of some archetype second-best pricing schemes (cordon toll, flat kilometer tax) are high (84% and 70% respectively). When road toll revenue is recycled lump-sum, the optimal toll lies below its Pigouvian level. Extensions in a bimodal framework show that the optimality of using road toll revenue to subsidize public transport depends on the initial inefficiency in public transport pricing.

Participants of a large-scale, real-life peak avoidance experiment have been asked to provide estimates of their average in-vehicle travel times for their morning commute. Comparing these reported travel times to the corresponding actual travel times, we find that travel times are overstated by a factor of 1.5 on average. We test to which extent driver- and link-specific characteristics explain the overstating. Subsequently, we investigate whether the driver-specific reporting errors are consistent with the drivers' scheduling behavior in reality as well as in hypothetical choice experiments. For neither case, we find robust evidence that drivers behave as if they misperceived travel times to a similar extent as they misreported them. These results imply that reported travel times are neither an appropriate measure for representing actual nor perceived travel times, and are thus a strong caveat against the uncritical use of reported travel time data in research and policy.

This article contains an economic analysis of regulatory parking policies as a substitute to road pricing. The scope for such policies is discussed, after which a simple diagrammatic analysis is presented, focusing on the differences between the use of parking fees and physical restrictions on parking space supply. The former is found to be superior for three reasons: an information argument, a temporal efficiency argument and an intertemporal efficiency argument. Finally, a spatial parking model is developed, showing that it may be possible to overcome the difficulty of regulatory parking policies not differentiating according to distance driven by specifying the appropriate spatial pattern of parking fees, making individuals respond to (spatial) parking fee differentials.