Urban delivery industry response to cordon pricing, time-distance pricing, and carrier-receiver policies in competitive markets

The paper develops a set of analytical formulations to study the behavior of the urban delivery industry in response to cordon time-of-day pricing, time-distance pricing, and comprehensive financial policies targeting carriers and receivers. This is accomplished by modeling the behavior of receivers in response to financial incentives, and the ensuing behavior of the carrier in response to both pricing and the receivers’ decisions concerning off-hour deliveries. The analytical formulations consider both the base case condition, and a mixed operation with both regular hour and off-hour deliveries; two pricing schemes: cordon time of day, and time-distance pricing; two types of operations: single-tour, and multi-tour carriers; and three different scenarios in terms of profitability of the carrier operation, which include an approximation to the best case, the expected value, and the worst case. The analyses, both theoretical and numerical, highlight the limitations of pricing-only approaches. In the case of cordon time of day pricing, the chief conclusion is that it is of limited use as a freight demand management tool because: (1) in a competitive market the cordon toll cannot be transferred to the receivers as it is a fixed cost and (2) the structure of the cost function, that only provides an incentive to the carrier to switch to the off-hours when all the receivers in the tour switch to the off-hours. The analyses of time-distance pricing clearly indicate that, though its tolls could be transferred to the receivers and provide an incentive for behavior change, the magnitude of the expected toll transfers under real life conditions are too small to have any meaningful impact on receivers choice of delivery times. In essence, the key policy implication is that in order to change the joint behavior of carrier and receivers, financial incentives—or programs that foster unassisted off-hour deliveries—should be made available to receivers in exchange for their commitment to do off-hour deliveries. As the paper proves, if a meaningful number of receivers switch to the off-hours, the carriers are likely to follow suit.     

The effects of federal transit subsidy policy on investment decisions: The case of San Francisco's Geary Corridor

In the United States, federal funding for public transit often accounts for a large proportion of a local agency's budget, especially for capital investments. For this reason, local governments can be expected to plan a portfolio of projects that maximize federal contributions. This study examines the financial effects of federal transit subsidy policy on local transit investment decisions. Data from a System Planning Study for the Geary Corridor in San Francisco are used as an illustration. It is found that federal transit subsidy policy provides financial incentives for local decision-makers to select capital-intensive investment options that may not be efficient or effective. While federal financial incentives are not the only factor influencing local investment decisions, some reform of the current subsidy policy may be necessary to reduce the incentive for ineffective use of public resources.     

Energy efficiency and time charter rates: Energy efficiency savings recovered by ship owners in the Panamax market

This paper presents the first analysis on how financial savings arising from energy efficient ships are allocated between owners and those hiring the ships. This as an important undertaking as allocation of financial savings is expected to have an impact on the incentives faced by ship owners to invest in more energy efficient vessels. We focus on the dry bulk Panamax segment as it contributes to around 50 Mt (5%) of total CO₂ emissions from shipping in 2007 and therefore its importance in terms of environmental impact should not be neglected. The time charter market represents a classical example of the principal–agent problem similar to the tenant–landlord problem in the buildings sector. We discovered that on average only 40% of the financial savings delivered by energy efficiency accrue to ship owner for the period 2008–2012. The finding that only part of the savings are recouped by shipowners affecting their incentives towards energy efficiency could consequently have implications on the type of emission reduction policies opted at both, global and regional levels.     

Renegotiating PPP Contracts: Reinforcing the ‘P' in Partnership

Abstract

The issue of renegotiation is becoming increasingly important as a tool to address uncertainty of public private partnership (PPP) projects and as a mechanism to restore its economic and financial equilibrium. This paper aims to understand how and why renegotiations occur in long-lasting PPP projects and what are the pros and cons of the renegotiation. We depart from a literature review on contract incompleteness and on the determinant factors for the renegotiation of infrastructure concessions. To illustrate the discussion, the case studies of nine European PPP projects are analysed by examining the specific exogenous and endogenous determinant factors that conduce to renegotiating contracts. The implications of contractual renegotiations are explained and summarized through a comparison of our case studies with literature. Although renegotiation, per se, is not a solution for the successful implementation of PPP projects, our findings reinforce the idea of contractual flexibility as a tool that allows adapting to uncertainty. Moreover, effective communication mechanisms allow a better response to unforeseen events, reinforcing the partners’ commitment to deliver a win–win project.     

Impact of government incentives on the market penetration of electric vehicles in Australia

Incentives to buy and use electric vehicles (EVs) may influence individuals’ decisions to do so. To examine these impacts, a latent class discrete choice model is developed to analyse consumer preferences related to EV attributes and related government incentives. Data was collected from a stated preference survey of 1,076 residents of New South Wales (NSW), Australia. According to the results, the proposed latent constructs classify respondents into five segments. The segments are then used to distinguish respondent behaviours regarding EV attributes and related government incentives. The results show that rebate on the upfront cost of an EV is the most preferred one-off financial incentive, because EVs are expected to be expensive, especially in Australia which has a very small EV market at present. Furthermore, rebates on energy bills and parking fees are also well-received, as these things are expensive in Sydney, Australia. Thus, operational incentives for discounts on energy bills and parking fees may facilitate the success of EVs in NSW.     

Incentivized vehicle relocation in vehicle sharing systems

The asymmetric demand-offer problem represents a major challenge for one-way vehicle sharing systems (VSS) affecting their economic viability as it necessitates the engagement of considerable human (and financial) resources in relocating vehicles to satisfy customer demand. In this paper, we propose a novel approach which involves user-based vehicle relocations to address supply-and-demand mismatches; in our approach, VSS users are offered price incentives so as to accept picking up their vehicle from an oversupplied station and/or to drop it off to an under-supplied station. The system incentivizes users based on the priorities of vehicle relocations among stations, taking into account the fluctuating demand for vehicles and parking places at different stations over time. A graph-theoretic approach is employed for modeling the problem of allocating vehicles to users in a way that maximizes the profit of the system taking into account the budget the VSS can afford to spend for rewarding users, as well as the users’ strategic behavior. We present two different schemes for incentivizing users to act in favour of the system. Both schemes consider budget constraints and are truthful and budget-feasible. We have extensively evaluated our approach through simulations which demonstrated significant gain with respect to the number of completed trips and system revenue. We have also validated our approach through pilot trials conducted in a free-floating e-motorbike sharing system in the framework of an EU-funded research project.     

Incentives for promoting Battery Electric Vehicle (BEV) adoption in Norway

Norway has become a global forerunner in the field of electromobility and the BEV market share is far higher than in any other country. One likely reason for this is strong incentives for promoting purchase and ownership of BEVs. The purpose of this study is to describe the role of incentives for promoting BEVs, and to determine what incentives are critical for deciding to buy a BEV and what groups of buyers respond to different types of incentives. The questions are answered with data from a survey among nearly 3400 BEV owners in Norway.Exemptions from purchase tax and VAT are critical incentives for more than 80% of the respondents. This is very much in line with previous research, which suggests that up-front price reduction is the most powerful incentive in promoting EV adoption. To a substantial number of BEV owners, however, exemption from road tolling or bus lane access is the only decisive factor.Analyses show that there are clear delineations between incentive groups, both in terms of age, gender, and education. Income is a less prominent predictor, which probably results from the competitive price of BEVs in the Norwegian market. Perhaps most interesting is the assumed relation between incentives and character of transport systems the respondents engage in.     

Optimization of incentive polices for plug-in electric vehicles

High purchase prices and the lack of supporting infrastructure are major hurdles to the adoption of plug-in electric vehicles (PEVs). It is widely recognized that the government could help break these barriers through incentive policies, such as offering rebates to PEV buyers or funding charging stations. The objective of this paper is to propose a modeling framework that can optimize the design of such incentive policies. The proposed model characterizes the impact of the incentives on the dynamic evolution of PEV market penetration over a discrete set of time intervals, by integrating a simplified consumer vehicle choice model and a macroscopic travel and charging model. The optimization problem is formulated as a nonlinear and non-convex mathematical program and solved by a specialized steepest descent direction algorithm. We show that, under mild regularity conditions, the KKT conditions of the proposed model are necessary for local optimum. Results of numerical experiments indicate that the proposed algorithm is able to obtain satisfactory local optimal policies quickly. These optimal policies consistently outperform the alternative policies that mimic the state-of-the-practice by a large margin, in terms of both the total savings in social costs and the market share of PEVs. Importantly, the optimal policy always sets the investment priority on building charging stations. In contrast, providing purchase rebates, which is widely used in current practice, is found to be less effective.     

Time use,mobility and expenditure: an innovative survey design for understanding individuals’ trade-off processes

A large amount of information is required to model the complex trade-off processes between travel activities, non-travel activities and budget assignment at the individual level. This paper describes the development of a new survey design, which incorporates components of travel surveys, time use surveys and consumer expenditure surveys in an integrated format, which is expected to deliver a richer data set allowing deeper insights into individuals’ activity and consumption patterns. The survey procedure and the incentives paid, which were necessary to obtain acceptable response rates, are also described. Results from two pilot studies using a trip-based and an activity-based diary format are presented. The paper examines to which extent the diaries have been capable of collecting the required data with high quality and response rates. The innovative “Mobility–Activity–Expenditure-Diary” is introduced and results of the main survey using this design are presented. Travel behaviour and non-travel activities were reported at high quality. Expenditures would require longer observation periods (and preferably not only telephone but also personal support in the survey process) to reduce unsystematic variations and to better capture individuals’ long term equilibrium.

     

Experimental Economics and choice in transportation: Incentives and context

This paper reviews the preconditions for successful applications of Experimental Economics methods to research on transportation problems, as new transportation and research technologies emerge. We argue that the application of properly designed incentives, the hallmark of Experimental Economics, provides a high degree of experimental control, leading to internal validity and incentive compatibility. Both of these are essential for ensuring that findings generalize to contexts outside the immediate application. New technologies, such as virtual reality simulators, can generate external validity for the experiments by providing realistic contexts. GPS and other tracking technologies, as well as smart phones, smart cards and connected vehicle technologies can allow detailed observations on actions and real-time interactions with drivers in field experiments. Proper application of these new technologies in research requires an understanding of how to maintain a high level of internal validity and incentive compatibility as external validity is increased. In this review of past applications of Experimental Economics to transportation we focus on their success in achieving external and internal validity.     

Time-dependent area-based pricing for multimodal systems with heterogeneous users in an agent-based environment

In this paper, we investigate an area-based pricing scheme for congested multimodal urban networks with the consideration of user heterogeneity. We propose a time-dependent pricing scheme where the tolls are iteratively adjusted through a Proportional–Integral type feedback controller, based on the level of vehicular traffic congestion and traveler’s behavioral adaptation to the cost of pricing. The level of congestion is described at the network level by a Macroscopic Fundamental Diagram, which has been recently applied to develop network-level traffic management strategies. Within this dynamic congestion pricing scheme, we differentiate two groups of users with respect to their value-of-time (which related to income levels). We then integrate incentives, such as improving public transport services or return part of the toll to some users, to motivate mode shift and increase the efficiency of pricing and to attain equitable savings for all users. A case study of a medium size network is carried out using an agent-based simulator. The developed pricing scheme demonstrates high efficiency in congestion reduction. Comparing to pricing schemes that utilize similar control mechanisms in literature which do not treat the adaptivity of users, the proposed pricing scheme shows higher flexibility in toll adjustment and a smooth behavioral stabilization in long-term operation. Significant differences in behavioral responses are found between the two user groups, highlighting the importance of equity treatment in the design of congestion pricing schemes. By integrating incentive programs for public transport using the collected toll revenue, more efficient pricing strategies can be developed where savings in travel time outweigh the cost of pricing, achieving substantial welfare gain.     

A latent segmentation based multiple discrete continuous extreme value model

We examine an alternative method to incorporate potential presence of population heterogeneity within the Multiple Discrete Continuous Extreme Value (MDCEV) model structure. Towards this end, an endogenous segmentation approach is proposed that allocates decision makers probabilistically to various segments as a function of exogenous variables. Within each endogenously determined segment, a segment specific MDCEV model is estimated. This approach provides insights on the various population segments present while evaluating distinct choice regimes for each of these segments. The segmentation approach addresses two concerns: (1) ensures that the parameters are estimated employing the full sample for each segment while using all the population records for model estimation, and (2) provides valuable insights on how the exogenous variables affect segmentation. An Expectation–Maximization algorithm is proposed to address the challenges of estimating the resulting endogenous segmentation based econometric model. A prediction procedure to employ the estimated latent MDCEV models for forecasting is also developed. The proposed model is estimated using data from 2009 National Household Travel Survey (NHTS) for the New York region. The results of the model estimates and prediction exercises illustrate the benefits of employing an endogenous segmentation based MDCEV model. The challenges associated with the estimation of latent MDCEV models are also documented.     

Shifting urban freight deliveries to the off-peak hours: a review of theory and practice

This paper presents a comprehensive review of the literature on off-peak hour deliveries (OPHD). The review identifies different approaches and policy levers used in the past, such as the laissez-faire approach, a road pricing approach, an incentives approach, and a regulatory approach. The paper also identifies different delivery reception schemes discussed in the literature. The authors complement the theory with a synthesis of pilot tests and the analysis of a set of interviews with practitioners (from the public sector and other organisations) in charge of OPHD programmes. The results from this review show the potential benefits that these programmes could bring about, the challenges faced in the early stages – along with potential solutions – and the significant progress that has been made in this domain in the last decade. According to the review, the results from the pilot tests tend to be positive, suggesting the importance of these programmes to reach more efficient and sustainable transportation systems.     

Estimation of a constrained multinomial logit model

Identifying the set of available alternatives in a choice process after considering an individual’s bounds or thresholds is a complex process that, in practice, is commonly simplified by assuming exogenous rules in the choice set formation. The Constrained Multinomial Logit (CMNL) model incorporates thresholds in several attributes as a key endogenous process to define the alternatives choice/rejection mechanism. The model allows for the inclusion of multiple constraints and has a closed form. In this paper, we study the estimation of the CMNL model using the maximum likelihood function, develop a methodology to estimate the model overcoming identification problems by an endogenous partition of the sample, and test the model estimation with both synthetic and real data. The CMNL model appears to be suitable for general applications as it presents a significantly better fit than the MNL model under constrained behaviour and replicates the MNL estimates in the unconstrained case. Using mode choice real data, we found significant differences in the values of times and elasticities between compensatory MNL and semi-compensatory CMNL models, which increase as the thresholds on attributes become active.     

Effectiveness of safety-based incentives in Public Private Partnerships: Evidence from the case of Spain

Many countries around the world are implementing Public–Private–Partnership (PPP) contacts to manage road infrastructure. In some of these contracts the public sector introduces economic incentives to the private operator to foster the accomplishment of social goals. One of the incentives that have been introduced in some PPP contracts is related to safety in such a way that the better the safety outcome the greater will be the economic reward to the contractor. The aim of this paper is at identify whether the incentives to improve road safety in highway PPPs are ultimately effective in improving safety ratios. To this end Poisson and negative binomial regression models have been applied using information from highway sections in Spain. The findings indicate that even though road safety is highly influenced by variables that are not much controllable by the contractor such as the Average Annual Daily Traffic and the percentage of heavy vehicles, the implementation of safety incentives in PPPs has a positive influence in the reduction of fatalities, injuries and accidents.     

Remuneration models and revenue risk mitigation in road public–private partnership projects – a case study from Serbia

As a consequence of renewed interest in attracting private financing for infrastructure investments, public–private partnership (PPP) arrangements are mostly seen as a suitable mechanism for ensuring sound and quicker delivery of transport infrastructure projects. However, a general concern is that expectations of mobilizing private-sector funds have been overestimated in a number of cases. The purpose of this paper is to contribute to the risk analysis of transport PPP projects with substantial exogenous demand risk which could serve as a rationale for choosing the appropriate PPP model. The objective of this paper is to construct an analytical cash flow-based project model to facilitate the choice of the remuneration mechanism suitable for both private investors and public sector. The model provides an indication whether the project should be implemented as a ‘users pay’, a hybrid or an ‘annuity’ PPP model. The proposed methodology is illustrated using a case study from Serbia.     

Quantifying environmental and financial benefits of using porters and cycle couriers for last-mile parcel delivery

Parcel carriers face increasingly difficult operating conditions in busy metropolitan areas due to growing consumer demand for ever faster delivery services and having to cope with traffic congestion and city authority measures that may restrict or penalise access for certain types of vehicle. This paper evaluates the potential environmental and financial benefits of switching from traditional van-based deliveries to an alternative operating model, where porters or cycle couriers undertake deliveries supported by a substantially reduced van fleet.Results using a specially-developed algorithm to model operations of a real carrier in an area of central London, UK, suggested that the carrier could reduce CO₂ emissions by 45%, NOx emissions by 33%, driving distance by 78% and curbside parking time by 45%. Overall cost savings to the carrier were estimated to be in the range 34–39%. Scaling up the modelled emissions savings to London’s Central Activities Zone, an area of approximately 30 km² and with current total annual parcel delivery distance of around 15 million km, could see annual emissions savings in the region of 2 million kg CO₂ and 1633 kg NOx if all carriers utilised porters or cycle couriers. The key operating challenges identified were related to sorting and consolidating items by weight and volume, parcel handover arrangements and how to deal with express items and failed deliveries.     

Dynamic transit scheduling under efficiency constraints

The problem of dynamic transit scheduling is addressed, and a method for transient and steady-state solutions is developed. The dynamic demand-supply formulation employed is based on previously calibrated disaggregate demand specifications. The existence and feasibility of solutions are examined, and stability conditions are derived. Numerical examples for both urban and rural conditions are given. The new methodology does not require time-series endogenous data but only initial conditions to provide long- or short-term scheduling plans. Futhermore, it takes into account passenger demand fluctuations and explicitly deals with management responsiveness and time lags in implementing scheduling decisions. Owing to its dynamic nature the methodology can be used as a design tool in transit scheduling and for assessing the effects of time-varying exogenous events such as gasoline price fluctuations, transport budget restrictions and other contingencies.     

A highway corridor planning model: QROAD

This model calculates an optimal investment plan for a highway corridor or number of corridors, subject to budget constraints. The available options include upgrading the current alignment, constructing a bypass highway over a different alignment, or various combinations. The budget constraints can be specified as a total budget restriction, or as an available budget each period. The highway system is described by K different road links. Each link consists of the current alignment which may be described by any number of sections, and a bypass section over a new alignment. The model finds the construction plan for each link that maximizes discounted benefits, subject to the financial constraints on the maintenance and capital expenditures. The problem is formulated as a large combinatorial optimization problem. A Lagrangian relaxation of the budget constraints is used, and the problem decomposes by link. A dynamic programming (DP) model is used to solve for the optimal expansion path for each link, given the dual variables. The sub-gradient dual optimization problem is a linear programming problem which is solved for the optimal dual variables. An application is presented based on the World Bank's Third National Highway Project in India, which is a US$1.3 billion project for upgrading approximately 2000 km of the Indian National Highway System. The project was approved based on results from this model.     

Effectiveness of incentives on electric vehicle adoption in Norway

Battery Electric vehicles (BEVs) shift pollution off the road and to potentially less damaging and more varied sources than petroleum. Depending on the source of electricity, a transition to electrified personal transportation can dramatically reduce greenhouse gas emissions and air pollutants. However current EVs tend to be more expensive and have shorter range, which can hinder public adoption. Government incentives can be used to alleviate these factors and encourage adoption. Norway has a long history incentivizing BEV adoption including measures such as exemption from roadway tolls, access to charging infrastructure, point of sale tax incentives, and usage of public bus use limited lanes. This paper analyzed the sales of electric vehicles on a regional and municipal basis in Norway and then cross analyzed these with the corresponding local demographic data and incentive measures to attempt to ascertain which factors lead to higher BEV adoption. It was concluded that access to BEV charging infrastructure, being adjacent to major cities, and regional incomes had the greatest predictive power for the growth of BEV sales. It was also concluded that short-range vehicles showed somewhat more income and unemployment sensitivity than long-range vehicles. Toll exemptions and the right to use bus designated lanes do not seem to have statistically significant predictive power for BEV sales in our linear municipal-level models, but this could be due to neighboring major cities containing those incentive features.