On the problems of applying Ramsey Pricing to the railroad industry with uncertain demand elasticities

Ramsey Pricing, or the Inverse Elasticity Rule (IER), has recently been proposed as a pricing strategy to improve the fortunes of the railroad industry under Interstate Commerce Commission regulation. According to the theory of Ramsey Pricing as articulated by Baumol and Bradford, rail rates would be set so that the deviation of price from marginal costs for each product or service is inversely proportional to the elasticity of demand. This paper first demonstrates that “Baumol and Bradford Ramsey Pricing” is not a practical approach to railroad ratenaking chiefly because the resulting rate structure is unduly sensitive to small changes in highly uncertain demand elasticities. Under such cirucmstances, the purported consumers' surplus benefits of Ramsey Pricing are likely to be modest and highly uncertain as well. The rail industry's proposed cure for the defects of Baumol and Bradford Ramsey Pricing, “Bayesian Ramsey Pricing”, does not provide an attractive alternative.     

Efficiency and equity issues in special fees for financing transportation infrastructure

Theoretically, charges for building and operating facilities and services should be efficient (proportional to one's use of or benefit derived from the service) and equitable (proportional to one's ability to pay). A number of “innovative” financing techniques have been used recently, whereby the private sector (developers, property owners, businesses, and users) pays entirely or partially for the cost of building and operating transportation facilities or services. These techniques are particularly popular when the impact from the land use developments on the transportation system is such that substantial improvements are warranted in order to avoid serious congestion problems. The purpose of this paper is to investigate special fee assessments (a popular sub-set of “innovative” financing techniques) used for financing highway and mass transportation in order to determine their efficiency and equity implications. The need for such an investigation arises from the fact that everyone residing or doing business in a particular area does not benefit equally from a given transportation system, and neither is everyone able to contribute equally toward that system's building and operation. This paper presents some of the most commonly used special fee assessment techniques and suggests fee structures that are “optimal” on the basis of the benefits that contributors derive from the given transportation system, as well as their ability to pay for it.     

The evolution of U.S. rail freight pricing in the post-deregulation era: revenues versus marginal costs for five commodity types

There have now been over three decades of experience with rate-making freedom for all modes of intercity freight transport in the United States. Most evidence suggests that regulatory change has been beneficial for the rail industry and its users. Despite evidence of positive impacts of regulatory reform of U.S. freight transport, there is limited evidence related to long-term pricing trends by commodity in the deregulated era. Moreover, U.S. shipper groups have called for increased regulation of U.S. railroads, citing increased rates and profits, and monopoly pricing to “captive shippers.” This study estimates U.S. railroad revenue-marginal cost ratios for seven different commodities between 1986 and 2008. Interestingly, we find no significant increase in revenue-cost margins for commodities thought to be “most captive” (coal and chemicals), while finding large increases for some commodities thought to be “non-captive.” These results may provide insight into the impacts of regulatory reform in other countries, where there are similar concerns of equitable pricing and financial viability. They suggest that a move toward a more market-based pricing system can enhance railroad viability without harming those with fewer transport options.     

Logistics as a driving force for development under the Belt and Road Initiative – the Chinese model for developing countries

ABSTRACT

An important objective of “the Belt and Road Initiative” is to promote the economic growth of countries in the region. China’s successful development experience, proposed in the initial stage of reform, can be summarised as “Looking for development, building the highway first”. This study is the first to evaluate whether logistics infrastructure has indeed contributed to economic growth by employing an error correction model with panel data from 2003 to 2014. In addition, we compare the influence levels of different sectors of logistics infrastructure in different regions, i.e. developed and developing regions. We focus on developing regions as they represent good development experiences for developing countries in the Silk Road Economic Belt. For developing regions, we find that the most influential factors are telecommunication and airway transportation, which should be the foci of attention in order to promote economic growth and reduce inter-region economic inequalities. The research confirms that logistics is indeed a driving force for economic growth in China, and that the contributions of specific sectors can be a useful reference for developing countries to determine prioritisation of investment in different logistics sectors across regions.     

Ridesharing in North America: Past,Present, and Future

Since the late 1990s, numerous ridematching programmes have integrated the Internet, mobile phones, and social networking into their services. Online ridematching systems are employing a range of new strategies to create “critical mass”: (1) regional and large employer partnerships, (2) financial incentives, (3) social networking to younger populations, and (4) real-time ridematching services that employ “smartphones” and automated ridematching software. Enhanced casual carpooling approaches, which focus on “meeting places”, are also being explored. Today, ridesharing represents approximately 8–11% of the transportation modal share in Canada and the USA, respectively. There are approximately 638 ridematching programmes in North America. Ridesharing's evolution can be categorized into five phases: (1) World War II car-sharing (or carpooling) clubs; (2) major responses to the 1970s energy crises; (3) early organized ridesharing schemes; (4) reliable ridesharing systems; and (5) technology-enabled ridematching. While ridesharing's future growth and direction are uncertain, the next decade is likely to include greater interoperability among services, technology integration, and stronger policy support. In light of growing concerns about climate change, congestion, and oil dependency, more research is needed to better understand ridesharing's impacts on infrastructure, congestion, and energy/emissions.     

Uncertain socioeconomic projections used in travel demand and emissions models: could plausible errors result in air quality nonconformity?

A sensitivity analysis of plausible errors in population, employment, fuel price, and income projections is conducted using the travel demand and emissions models of the Sacramento, CA, USA, region for their transportation plan. The results of the analyses indicate that plausible error ranges for household income and fuel prices are not a significant source of uncertainty with respect to the region's travel demand and emissions projections. However, plausible errors in population and employment projections (within approximately one standard deviation) may result in the region's transportation plan not meeting the conformity test for nitrogens of oxides (NO_x) in the year 2005 (i.e., an approximately 16% probability). This outcome is also possible in the year 2015 but less likely (within approximately two standard deviations or a 2.5% probability). Errors in socioeconomic projections are only one of many sources of error in travel demand and emissions models. These results have several policy implications. First, regions like Sacramento that meet their conformity tests by a very small margin should rethink new highway investment and consider contingency transportation plans that incorporate more aggressive emissions reduction policies. Second, regional transportation planning agencies should conduct sensitivity analyses as part of their conformity analysis to make explicit significant uncertainties in the methods and to identify the probability of their transportation plan not conforming. Third, the US Environmental Protection Agency (EPA) should clarify the interpretation of “demonstrate” conformity of transportation plans; that is, specify the level of certainty that it considers a sufficient demonstration of conformity.     

Scheduling railway freight delivery appointments using a bid price approach

This paper proposes a method for establishing aggressive but achievable delivery appointment times for railroad shipments, taking into account individual customer needs and forecasted available train capacity. The concept of scheduling appointment times is directly patterned after current motor carrier industry practice, so that customers can plan for rail or truck deliveries in the same way.A shipment routing problem is decomposed into a deterministic “dynamic car scheduling” (DCS) process for shipments already accepted and a stochastic “train segment pricing” (TSP) process for forecasting future demands which have not yet called in and for which delivery appointments have yet to be scheduled. Both are formulated as multi-commodity network flow (MCNF) problems, where each shipment is treated as a separate commodity. Gain coefficients represent recapture probabilities that a specific customer will accept a carrier’s service offer.A comparison with a widely used revenue management formulation is given. A Lagrangian heuristic for obtaining a primal solution is also described. The problem is solved within a 1% gap using the subgradient algorithm.     

基于城市轨道交通衔接规划的方法研究

文章在调研广州轨道交通衔接规划开展情况的基础上,分析广州轨道交通衔接的必要性及轨道交通衔接规划的主要研究内容,提出了衔接方式一体化、区域差别化及站点功能层级化等交通衔接规划的研究方法,为其他城市开展轨道交通衔接规划研究提供参考。     

Evaluation of congestion trends on chicago expressways

The growth in congestion on Chicago area expressways has had a major effect on almost all aspects of the region's economy, travel behavior and land-use development patterns. The objective of this study was to evaluate congestion trends on Chicago's expressways during the last decade (1980 to 1989) by quantifying the magnitude and tendencies of congestion for the various expressways. This study concentrated on an analysis of the minute-miles of congestion (MMC), a measure that provides an averaged section congestion during a given time period and that is continuously collected by the Illinois Department of Transportation for all Chicago-area expressways. The MMC offers a relatively accurate and unbiased estimate of the quantity and duration of congestion. In order to compare congestion trends on the area's ten major expressways in the 1980's it was decided to evaluate the yearly Cumulative Distribution Function of congestion. This analysis was conducted for both the inbound and outbound directions and for the A.M. and P.M. daily peak periods. The magnitude of congestion was found to increase considerably with the years from 1980 to 1989. The increase in congestion for “reverse commuting”, trips to the suburbs in the morning peak and from the suburbs in the evening peak, grew more substantially than the increase in the regular “city commute.” The reason for this phenomenon was the rise in job opportunities in the suburbs, resulting partially from increased congestion and reduced accessibility. Additional analysis showed that the duration of the peak period, defined by the time in which congestion exceeded a predetermined threshold level, was generally longer for the “city commuting” than for the “reverse commuting.” Comparison of congestion among seasons, showed that the most congested season was usually the spring (May 1 to June 15). The system analysis showed that the by 2000, the expected system congestion will be more than twice the 1980 system congestion.     

Decomposition analysis of energy-related carbon emissions from the transportation sector in Beijing

In the process of rapid development and urbanization in Beijing, identifying the potential factors of carbon emissions in the transportation sector is an important prerequisite to controlling carbon emissions. Based on the expanded Kaya identity, we built a multivariate generalized Fisher index (GFI) decomposition model to measure the influence of the energy structure, energy intensity, output value of per unit traffic turnover, transportation intensity, economic growth and population size on carbon emissions from 1995 to 2012 in the transportation sector of Beijing. Compared to most methods used in previous studies, the GFI model possesses the advantage of eliminating decomposition residuals, which enables it to display better decomposition characteristics (Ang et al., 2004). The results show: (i) The primary positive drivers of carbon emissions in the transportation sector include the economic growth, energy intensity and population size. The cumulative contribution of economic growth to transportation carbon emissions reaches 334.5%. (ii) The negative drivers are the transportation intensity and energy structure, while the transportation intensity is the main factor that restrains transportation carbon emissions. The energy structure displays a certain inhibition effect, but its inhibition is not obvious. (iii) The contribution rate of the output value of per unit traffic turnover on transportation carbon emissions appears as a flat “M”. To suppress the growth of carbon emissions in transportation further, the government of Beijing should take the measures of promoting the development of new energy vehicles, limiting private vehicles’ increase and promoting public transportation, evacuating non-core functions of Beijing and continuingly controlling population size.     

Canadian transportation regulation: Trends and issues

Transportation - In Canada, transportation regulation has evolved in response to the country's unique economic and demographic conditions—a land mass larger than that of the U.S.A. with...     

About the possibilities of using the renewable energy power sources on railway transport

Several electrification systems based on renewable energy power sources (first of all, solar energy) are discussed in respect to their applicability to railway transport and, in particular, to suburban electric trains. Two systems are considered with basic technical details and economic estimation, both including the onboard bank of batteries and the photovoltaic converters (PVC) of solar energy for compensation of energy expenses, which could be positioned either on stations or on wagon's roofs. Sun‐tracking systems and their effect on the solar energy conversion efficiency are discussed in application to stationary and moving PVC platforms. An analysis made shows that introduction of the “green” systems discussed will not only have positive ecological impact, but also can bring a notable economical effect even with today's components, while it could be considerably greater with the usage of new PVCs, which are being developed by the authors. Copyright © 2011 John Wiley & Sons, Ltd.     

Tradable credits scheme and transit investment optimization for a two‐mode traffic network

This paper proposes an optimization model to minimize the “system costs” and guide travelers' behavior by exploring the optimal bus investment and tradable credits scheme design in a bimodal transportation system. Travelers' transport mode choice behavior (car or bus) and the modal equilibrium conditions between these two forms of transport are studied in the tradable credits scheme. Public transport priority is highlighted by charging car travelers credits only. The economies of scale presented by the transit system under the tradable credit scheme are analyzed by comparing the marginal cost and average cost. Numerical examples are presented to demonstrate the model. Furthermore, the effects of tradable credits schemes on bus investment and travelers' modal choice behavior are explored based on scenario discussions. Copyright © 2016 John Wiley & Sons, Ltd.     

Stochastic dynamic switching in fixed and flexible transit services as market entry-exit real options

The first analytical stochastic and dynamic model for optimizing transit service switching is proposed for “smart transit” applications and for operating shared autonomous transit fleets. The model assumes a region that requires many-to-one last mile transit service either with fixed-route buses or flexible-route, on-demand buses. The demand density evolves continuously over time as an Ornstein-Uhlenbeck process. The optimal policy is determined by solving the switching problem as a market entry and exit real options model. Analysis using the model on a benchmark computational example illustrates the presence of a hysteresis effect, an indifference band that is sensitive to transportation system state and demand parameters, as well as the presence of switching thresholds that exhibit asymmetric sensitivities to transportation system conditions. The proposed policy is computationally compared in a 24-hour simulation to a “perfect information” set of decisions and a myopic policy that has been dominant in the flexible transit literature, with results that suggest the proposed policy can reduce by up to 72% of the excess cost in the myopic policy. Computational experiments of the “modular vehicle” policy demonstrate the existence of an option premium for having flexibility to switch between two vehicle sizes.     

Dynamic process model of mass effects on travel demand

Whereas transportation planners commonly predict the negative impacts of mass transportation, there is increasing empirical evidence of the existence of positive mass effects, whereby increased use of a mode by the ‘mass’ will generally increase its attractiveness for future travellers. In this paper we consider the dynamic impact of such an effect on the problem of travel demand forecasting, with particular regards to social network effects. Our proposed modelling approach is inspired by literature from social physics, evolutionary game theory and marketing. For simplicity of exposition, our model is specified for a scenario in which (a) there is a binary choice between two mobility lifestyles, referred to as car-oriented and transit-oriented, and (b) there are two population groups, where one is the “leading” or “innovative” population group and the other the “following” or “imitating” population group. This latter distinction follows the rather well-known Bass model from the marketing literature (1969). We develop the transition probabilities and transition dynamics. We illustrate with a numerical case study that despite lower intrinsic utility for the transit lifestyle, significant changes towards this lifestyle can be achieved by considering congestion, service improvements and mass effects. We further illustrate that mass effects can be positive or negative. In all cases we explore the sensitivity of our conclusions to the assumed parameter values.     

“两山”理念在湖北十淅高速公路中的实践研究

本文从高速公路建设项目的角度出发就“绿水青山就是金山银山”理念的内涵及时代要求进行了论述,分析了当前“绿色交通”理念下的绿色公路建设施工与管理中存在的主要问题,同时结合“绿水青山就是金山银山”理念的具体内涵,以十淅高速公路(湖北段)项目为例,从施工管理、设计、施工技术等方面阐述了绿色交通理念在公路建设过程中的具体实践,为公路建设的绿色发展提供了借鉴意义。     

Road project appraisal in Tanzania: A review of the working figures

This paper examines the project appraisal methodology and working figures of road studies in Tanzania. The latter are geared at establishing some broad “standard” guides in road project selection and evaluation. The commonly used appraisal tools such as rates of discount, the time horizon, the multipliers and shadow prices of foreign exchange and labour are examined, as well as the rationale of practitioner's rules of thumb in this regard. Cost-benefit analysis could, it is argued, be supplemented by people's participation and public accountability of road planners in setting road priorities. This could check parochialism in road provision and ensure the most “cost-effective” road provision and use.     

Forecasting current and next trip purpose with social media data and Google Places

Trip purpose is crucial to travel behavior modeling and travel demand estimation for transportation planning and investment decisions. However, the spatial-temporal complexity of human activities makes the prediction of trip purpose a challenging problem. This research, an extension of work by Ermagun et al. (2017) and Meng et al. (2017), addresses the problem of predicting both current and next trip purposes with both Google Places and social media data. First, this paper implements a new approach to match points of interest (POIs) from the Google Places API with historical Twitter data. Therefore, the popularity of each POI can be obtained. Additionally, a Bayesian neural network (BNN) is employed to model the trip dependence on each individual’s daily trip chain and infer the trip purpose. Compared with traditional models, it is found that Google Places and Twitter information can greatly improve the overall accuracy of prediction for certain activities, including “EatOut”, “Personal”, “Recreation” and “Shopping”, but not for “Education” and “Transportation”. In addition, trip duration is found to be an important factor in inferring activity/trip purposes. Further, to address the computational challenge in the BNN, an elastic net is implemented for feature selection before the classification task. Our research can lead to three types of possible applications: activity-based travel demand modeling, survey labeling assistance, and online recommendations.