Charges on transport – To what extent are they passed on to users?

The paper first briefly reviews the extent to which profit maximising transport firms with identical cost functions and producing identical transport services pass-on output taxes to transport users under perfect competition, under different forms of imperfect competition and when they act as monopolists. Then the analysis is extended to derive the pass-on rates and activity reductions caused by an output tax when firms care both about profit and consumer surplus, produce symmetrically differentiated services and compete simultaneously in quantities and fare and when they collude. The pass-on rates and activity reductions are highest under collusion and lowest under Cournot competition when they produce complementary services. When they produce substitute services, the result is ambiguous and the competitive situation that yields highest pass-on depends on the firms’ objective functions and how fiercely they compete. Two important counterintuitive results are that the more intensely the firms compete and the more weight they put on consumer surplus, the higher the pass-on rates are.     

Economical welfare maximisation analysis: assessing the use of existing Park-and-Ride services

This paper assesses travellers’ responses to the use of existing Park-and-Ride (P&R) services based on an economical welfare maximisation approach. Specifically, the paper presents a modelling framework to estimate consumer surplus and producer surplus (business profits) on the basis of modal choice probabilities. The paper draws on evidence from Stated Preference surveys conducted around two P&R sites in Sapporo, Japan, where P&R services occupy a modest market space. Overall, the results suggest that business profit increases when economical welfare is maximised, as a consequence of increased demand. It is also shown that P&R choice is not only influenced by parking fees, but also by the fares and other attributes of alternative transportation modes. Accordingly, the interactions of P&R with alternative transportation modes should be taken into consideration in any strategic transportation policies oriented towards motivating sustainable transport mode choices.     

The concept and impact analysis of a flexible mobility on demand system

This paper introduces an innovative transportation concept called Flexible Mobility on Demand (FMOD), which provides personalized services to passengers. FMOD is a demand responsive system in which a list of travel options is provided in real-time to each passenger request. The system provides passengers with flexibility to choose from a menu that is optimized in an assortment optimization framework. For operators, there is flexibility in terms of vehicle allocation to different service types: taxi, shared-taxi and mini-bus. The allocation of the available fleet to these three services is carried out dynamically so that vehicles can change roles during the day. The FMOD system is built based on a choice model and consumer surplus is taken into account in order to improve passenger satisfaction. Furthermore, profits of the operators are expected to increase since the system adapts to changing demand patterns. In this paper, we introduce the concept of FMOD and present preliminary simulation results. It is shown that the dynamic allocation of the vehicles to different services provides significant benefits over static allocation. Furthermore, it is observed that the trade-off between consumer surplus and operator’s profit is critical. The optimization model is adapted in order to take into account this trade-off by controlling the level of passenger satisfaction. It is shown that with such control mechanisms FMOD provides improved results in terms of both profit and consumer surplus.     

Regulating inter-firm agreements: The case of airline codesharing in parallel networks

We compare aviation markets under conditions of competition, codesharing contracts and anti-trust immune alliances, assuming that demand for flights depends on both fares and the level of frequency offered. Using a hybrid competitive/cooperative game theoretic framework, we show that the stronger the inter-airline agreement on overlapping routes, the higher the producer surplus. On the other hand, consumer surplus and overall social welfare are maximized under limited codesharing agreements. Partial mergers appear preferable to no agreement in ‘thin’ markets, in which both demand and profit margins are relatively low. Inter-governmental agreements are also analyzed and we show that bilaterals create the least favorable market outcomes for consumers and producers. Finally, a realistic case study demonstrates that under asymmetric and uncertain demand, codesharing on parallel links may be preferable to competitive outcomes for multiple consumer types.     

A comprehensive dwelling unit choice model accommodating psychological constructs within a search strategy for consideration set formation

This study adopts a dwelling unit level of analysis and considers a probabilistic choice set generation approach for residential choice modeling. In doing so, we accommodate the fact that housing choices involve both characteristics of the dwelling unit and its location, while also mimicking the search process that underlies housing decisions. In particular, we model a complete range of dwelling unit choices that include tenure type (rent or own), housing type (single family detached, single family attached, or apartment complex), number of bedrooms, number of bathrooms, number of storeys (one or multiple), square footage of the house, lot size, housing costs, density of residential neighborhood, and commute distance. Bhat’s (2015) generalized heterogeneous data model (GHDM) system is used to accommodate the different types of dependent outcomes associated with housing choices, while capturing jointness caused by unobserved factors. The proposed analytic framework is applied to study housing choices using data derived from the 2009 American Housing Survey (AHS), sponsored by the Department of Housing and Urban Development (HUD) and conducted by the U.S. Census Bureau. The results confirm the jointness in housing choices, and indicate the superiority of a choice set formation model relative to a model that assumes the availability of all dwelling unit alternatives in the choice set.     

Commute responses to employment decentralization: Anticipated versus actual mode choice behaviors of new town employees in Kunming,China

This study examines workers’ mode-choice responses to a typical job decentralization policy implemented in China’s urban development – government job relocation (GJR) to new towns in the urban periphery. Broadly, the literature suggests that job decentralization tends to increase car commuting; however, little is known about the effects of China’s GJR initiatives on individuals’ commuting mode choices. Using Kunming as a case study, this study examines how workers’ commuting mode choices have shifted in response to the GJR policy. Our study analyzes two travel survey datasets that span the job relocation process: (1) stated preference (SP) data on workers’ anticipated mode choices after a move of workplace to a planned new town; and (2) revealed preference (RP) data on workers’ actual choices of commuting mode after their jobs were moved. The findings suggest that after job relocation, workers’ actual commuting modes shift from more sustainable modes towards cars. The determinants of workers’ mode choices differ substantially between the hypothetical and actual setting of job relocation. The anticipated mode choices are largely determined by socio-demographic characteristics whereas the actual mode choices are strongly influenced by travel time and housing locations. The evidence from this study offers two important implications for future planning practice of job decentralization. First, planners and policy-makers should be skeptical about the transportation benefits of job decentralization. Second, while SP surveys can assist planners to predict individuals’ mode-choice responses, the robustness of SP results should be carefully assessed before translating into the evidence base for informing job decentralization policy-makings.     

Measuring the benefits derived from a transportation investment — a comment

Because an expansion of roads will shift the demand curves for interdependent roads, it may appear difficult to determine the consumer surplus generated by road projects. An extensive literature discusses different measures of consumer surplus, and the conditions under which the different measures give consistent answers. Little attention, however, has been given to a more fundamental problem: under what conditions does consumer surplus measure the benefits of an investment. We discuss both these issues, and explain the close relationship between the conditions guaranteeing the uniqueness of a measure of consumer welfare, and its usefulness in evaluating road projects. No uniqueness problem arises if different roads connect the same origin and destination; consumer surplus can then be measured by use of an aggregate demand curve.     

Estimation of urban bus transit marginal cost without cost data

We develop a method to study the industrial structure of urban bus transit without using cost data. To do so, we estimate the marginal cost function under the assumption that firms compete on frequency and adjust frequency to maximize profits. Our methodology is applied to Santiago, Chile. In this case, demand is modeled with a simplified model of transit network assignment. The goal is to consider how frequency, capacity, and on-board passengers affect the bus line’s demand. The marginal cost function is estimated by using the first-order conditions of the firm’s profit maximization problem, using the results of the demand model as data. We conclude that the urban bus transit industry in Santiago exhibits increasing returns to scale for low levels of demand and that these returns are exhausted rapidly at a moderate demand level. Additionally, firms exhibit economies of network expansion, on average.     

Modeling residential location choice in relation to housing location and road tolls on congested urban highway networks

We present a reformulation of the residential location submodel of the Integrated Model of Residential and Employment Location as a network equilibrium problem, thereby making travel costs by auto endogenous. The location of housing supply is examined as a welfare maximization problem for both user-optimal and system-optimal travel costs using concepts of bilevel programming. Finally, we briefly discuss how the employment submodel can be reformulated, and the entire model solved as a variational inequality problem.     

Modal split and urban public transport management in an Eastern European country

When public transport is the main means of travel in urban areas, management and planning are easy and the main objective can be to minimise costs for the demand available, i.e. maximise profit. However when public transport faces competition from other modes of transport, and activities can be undertaken in a variety of locations, then the management and planning of public transport services is considerably more difficult.This paper examines a methodology for representing consumer behaviour when faced with alternative travel decisions, in order to identify the demand for public transport and to help operators adjust services and prices to maximise demand, when considering people's disposable income, the alternative modes and activity locations available. From this it is possible to devise criteria for maximising consumer surplus in a city, taking into account social benefits.     

On joint railway and housing development strategy

Transit Oriented Development (TOD) with railway service is recognized as a sustainable mode of development for highly dense megacities. In addition to providing safe and efficient transit services, reducing auto dependence and therefore less need for highway expansions, the improved accessibility of TOD influences commuters’ residential location choices and the resultant housing value. Traditionally, statistical approaches have been used to estimate the relationship between railway development and housing value for individual sites. To some degree, TOD has also been studied with integrated land-use transport models. While useful, they lack an analytical framework to study the region-wide impacts of TOD on residential location and travel choices and the resultant land value changes. In this study, the joint railway and housing development strategy is modeled based on a combined equilibrium formulation with the bid-rent process. The problem is formulated as a mathematical program with equilibrium constraints, in which the upper level optimizes the objective for the joint development strategy by deciding on the combination of housing supplies and railway service levels. Analytical results are obtained for a single corridor in a multi-modal transport network, which are further illustrated by sensitivity analyses. A numerical example is constructed to demonstrate the approach and compare with other separate development strategies. The results generally confirm the synergy between railway and housing developments.     

Price-based regulation of oligopolistic markets under discrete choice models of demand

We propose a framework to find optimal price-based policies to regulate markets characterized by oligopolistic competition and in which consumers make a discrete choice among a finite set of alternatives. The framework accommodates general discrete choice models available in the literature in order to capture heterogeneous consumer behavior. In our work, consumers are utility maximizers and are modeled according to random utility theory. Suppliers are modeled as profit maximizers, according to the traditional microeconomic treatment. Market competition is modeled as a non-cooperative game, for which an approximate equilibrium solution is sought. Finally, the regulator can affect the behavior of all other agents by giving subsidies or imposing taxes to consumers. In transport markets, economic instruments might target specific alternatives, to reduce externalities such as congestion or emissions, or specific segments of the population, to achieve social welfare objectives. In public policy, different agents have different individual or social objectives, possibly conflicting, which must be taken into account within a social welfare function. We present a mixed integer optimization model to find optimal policies subject to supplier profit maximization and consumer utility maximization constraints. Then, we propose a model-based heuristic approach based on the fixed-point iteration algorithm that finds an approximate equilibrium solution for the market. Numerical experiments on an intercity travel case study show how the regulator can optimize its decisions under different scenarios.

     

Nonlinear pricing for stochastic container leasing system

With the substantial upsurge of container traffic, the container leasing company thrives on the financial benefits and operational flexibility of leasing containers requested by shippers. In practice, container lease pricing problem is different from the consumer product pricing in consideration of the fair value of container, limited customer types and monopolistic supply market. In view of the durability of container and the diversified lease time and quantity, the pricing is a challenging task for the leasing company. This paper examines the monopolist’s nonlinear pricing problems in static and dynamic environments. In particular, the leasing company designs and commits a menu of price and hire quantity/time pairs to maximize the expected profit and in turn customers choose hire quantities/time to maximize their surpluses according to their hire preferences. In a static environment, closed-form solutions are obtained for different groups of customers with multiple types subject to capacity constraint. In a dynamic environment, we address two customer types and derive closed-form solutions for the problem of customers with hire time preference. Further, we show that the effect of the capacity constraint increases with time of the planning horizon when customers have the same hire time preference; while in the case with different hire time preferences, the capacity constraint has opposite effects on the low and high type customers. Last, the case of customers with hire quantity preference is discussed. We focus on the lease with alternative given sets of hire time and use dynamic programming to derive the numerical optimal hire time sequence.     

Optimal pricing for build-to-order supply chain design under price-dependent stochastic demand

Build to order (BTO) is a supply chain disruption mitigation strategy. Whereas cost minimization is an operational objective, the goal of the BTO manufacturer is to maximize its profit by using pricing as its competitive decision-making strategy. In this paper, we study a BTO manufacturer who simultaneously determines its product prices and designs its supply chain network to maximize its expected profit under price-dependent stochastic demand. We propose an L-shaped decomposition with complete enumeration to solve for optimality and show that the expanded master problem remains convex programming, although the optimality cuts are quadratic inequalities. The computational results demonstrate that stocking up on differentiated components and allocating modules appropriately to meet realized demand is a resilient policy that sustains variations in demand. Furthermore, the pricing decision balances the expected revenue and expected operating cost with an increase in expected profit. The integration of pricing and operational planning results in a higher expected profit than by individual decisions. We also demonstrate that cost minimization may not provide the same level of profit if the manufacturer overestimates or underestimates its most profitable demand.     

Developing metro-based accessibility: Three aspects of China’s Rail+Property practice

Populous Chinese cities have invested heavily in metro systems and planned proactively for transit-oriented development. Rail plus property (R+P) programs, where metro corporations engage in, and even orchestrate real estate development in or around rail station areas, have been recurrently reported among these cities. However, careful assessment of these programs is still rare in the existing literature. Built upon multiple R+P programs led by Shenzhen Metro Cooperation and/or Hong Kong Mass Transit Railway Cooperation, this article fathoms the rationale for R+P programs in Mainland China, the obstacles for oversea private investors’ participation and the balance between profit making and social goods supply. It finds that R+P programs serve as alternative funding sources for expensive metro projects. It decreases municipal governments’ cash flow contribution to those projects, which is mandated by the central government. In addition, local business environment for R+P projects has disadvantaged private sector participation, especially those private investors from overseas. Furthermore, public subsidy to local metro corporations is likely to persist as R+P programs have not been designed for economic value maximization; rather, they are in place because (1) they reduce the cash flow burden of the municipal government; (2) they are tasked by the municipal government to produce a considerable number of affordable public housing.     

Optimal funding allocation strategies for safety improvements on urban intersections

Urban intersections crashes cause significant economic loss. The safety management process undertaken by most states in the United States is referred to as Highway Safety Improvement Program and consists of three standardized steps: (i) identification of critical crash locations, (ii) development of countermeasures, and (iii) resource allocation among identified crash locations. Often these three steps are undertaken independently, with limited detail of each step at the state planning agencies. The literature review underlines the importance of the third step, and the lack of sophisticated tools available to state planning agencies for leveraging information obtained from the first two steps. Further, non-strategic approaches and unavailability of methods for evaluating policies may lead to sub-optimal funding allocation. This paper overcomes these limitations and proposes multiple optimal resource allocation strategies for improvements at urban intersections that maximize safety benefits, under budget and policy constraints. Proposed policy measures based on benefits maximization (economic competitiveness), equitable allocation (equity), and relaxation of mutually exclusiveness (multiple alternatives at one location) produce significantly different alternative and fund allocation. The proposed models are applied to selected intersections in four counties of southeast Michigan. Results reinforce the applicability of the strategies/policies and tools developed in this paper for safety project funding allocation on critical urban intersections.     

Modeling risks and uncertainties in residents’ license choice behaviors under a vehicle restriction policy

Understanding residents’ perception and reaction to vehicle restriction policies is significant for transportation management. However, few studies have examined it from a behavioral and disaggregated perspective, particularly from people’s responses to uncertainties in choices, and their consequent behaviors under potential risks. This paper proposes a multi-level nested logit method to model sequential choice behaviors considering uncertainties under a vehicle license restriction policy. Prospect theory is applied, where a novel reference point is proposed based on instances of ‘whether a risk happens’ rather than a hard number which is difficult to obtain in reality. A case study in Guangzhou, China is presented, where a vehicle restriction policy has been applied for three years. Residents’ attitudes and preferences under uncertainties and different risks are revealed, and these factors are significant in predicting people’s future decisions while policy changes.     

Electric vehicle charging station locations: Elastic demand,station congestion,and network equilibrium

Battery-only electric vehicles (BEVs) generally offer better air quality through lowered emissions, along with energy savings and security. The issue of long-duration battery charging makes charging-station placement and design key for BEV adoption rates. This work uses genetic algorithms to identify profit-maximizing station placement and design details, with applications that reflect the costs of installing, operating, and maintaining service equipment, including land acquisition. Fast electric vehicle charging stations (EVCSs) are placed across a congested city's network subject to stochastic demand for charging under a user-equilibrium traffic assignment. BEV users’ station choices consider endogenously determined travel times and on-site charging queues. The model allows for congested-travel and congested-station feedback into travelers’ route choices under elastic demand and BEV owners’ station choices, as well as charging price elasticity for BEV charging users.Boston-network results suggest that EVCSs should locate mostly along major highways, which may be a common finding for other metro settings. If 10% of current EV owners seek to charge en route, a user fee of $6 for a 30-min charging session is not enough for station profitability under a 5-year time horizon in this region. However, $10 per BEV charging delivers a 5-year profit of $0.82 million, and 11 cords across 3 stations are enough to accommodate a near-term charging demand in this Boston-area application. Shorter charging sessions, higher fees, and/or allowing for more cords per site also increase profits generally, everything else constant. Power-grid and station upgrades should keep pace with demand, to maximize profits over time, and avoid on-site congestion.     

Walking accessibility and property prices

Walking is an imperative travel mode, especially for short trips. Walking accessibility, which is defined as the ease of reaching essential destinations in the walk-in catchment area, may affect property prices because residents are more likely to be willing to pay for this attribute. In addition, different categories of public services may have varied influencing directions and magnitude. These two hypotheses are tested in this study. Taking Xiamen, China as a case study, we estimate the cumulative opportunities of public services on foot and develop a set of hedonic pricing models (more specifically, two pre-specified ordinary least squares models, four Box-Cox transformed models, and two spatial econometric models) to estimate, whether and to what extent, walking accessibility contributes to price premiums (or discounts). Using a database of 22,586 second-hand residential properties in 358 multi- or high-storey residential complexes, we find that (1) walking accessibility to public services contributes to the variations in housing prices and plays a role in determining housing prices; (2) different categories of services have vastly divergent, even opposite, influencing impacts; and (3) walking accessibility to primary schools, commercial centers, and sports and cultural centers have positive effects on house prices whereas walking accessibility to comprehensive hospitals adversely affects housing prices. Methodologically, we confirm that spatial econometric methods improve estimation accuracy and have more explanatory power relative to the standard non-spatial models. Robustness check analysis further guarantees the plausibility of this study.     

Exploring the connections among residential location,self-selection,and driving: Propensity score matching with multiple treatments

A large number of studies have investigated the association between the built environment and travel behavior. However, most studies did not explicitly quantify the contribution of residential self-selection to the connection. Using the 2006 data collected from a regional travel diary in Raleigh, NC, this study applies propensity score matching to explore the effects of the regional location of individuals’ residences on their vehicle miles driven. We found that residential location plays a more important role in affecting driving behavior than residential self-selection; and that the self-selection effect is non-trivial when we compare driving behavior between urban residents and people living in other areas. Therefore, for such comparisons, the observed influence of residential locations on driving should be appropriately discounted when we evaluate the causal impacts of the built environment on travel behavior.