Policy Equity, Acceptance & Compliance

Mobility is a highly regulated human activity. Distinguishing demands arise from different social groups, interacting with service providers, through layers of policies in the complex urban system. The range of urban transport policies reflects varying and often conflicting values about efficiency, fairness, acceptance, and the limits of government control.

At JTL, we argue that the success of transport policies hinge on their compatibility with behavioral responses from the public and context-specific social norms and social goals. Successful policies must respond to users’ needs, enhance target groups’ mobility, or incentify behavioral change. At JTL, we attempt to make these normative foundations of transport policies explicit and assess whether policies actually achieve these aspirations. We emphasize the importance of three closely linked policy parameters: public perception of fairness, policy acceptance, and policy compliance.

  • Equality of opportunity in travel behavior prediction with deep neural networks and discrete choice models

    Transportation Research Part C
    (
    2021
    )

    Although researchers increasingly adopt machine learning to model travel behavior, they predominantly focus on prediction accuracy, ignoring the ethical challenges embedded in machine learning algorithms. This study introduces an important missing dimension – computational fairness – to travel behavior analysis. It highlights the accuracy-fairness tradeoff instead of the single dimensional focus on prediction accuracy in the contexts of deep neural network (DNN) and discrete choice models (DCM). We first operationalize computational fairness by equality of opportunity, then differentiate between the bias inherent in data and the bias introduced by modeling. The models inheriting the inherent biases can risk perpetuating the existing inequality in the data structure, and the biases in modeling can further exacerbate it. We then demonstrate the prediction disparities in travel behavior modeling using the 2017 National Household Travel Survey (NHTS) and the 2018-2019 My Daily Travel Survey in Chicago. Empirically, DNN and DCM reveal consistent prediction disparities across multiple social groups: both over-predict the false negative rate of frequent driving for the ethnic minorities, the low-income and the disabled populations, and falsely predict a higher travel burden of the socially disadvantaged groups and the rural populations than reality. Comparing DNN with DCM, we find that DNN can outperform DCM in prediction disparities because of DNN’s smaller misspecification error. To mitigate prediction disparities, this study introduces an absolute correlation regularization method, which is evaluated with synthetic and real-world data. The results demonstrate the prevalence of prediction disparities in travel behavior modeling, and the disparities still persist regarding a variety of model specifics such as the number of DNN layers, batch size and weight initialization. Since these prediction disparities can exacerbate social inequity if prediction results without fairness adjustment are used for transportation policy making, we advocate for careful consideration of the fairness problem in travel behavior modeling, and the use of bias mitigation algorithms for fair transport decisions.

  • Measuring policy leakage of Beijing’s car ownership restriction

    Transportation Research Part A: Policy and Practice
    (
    2021
    )

    In response to severe traffic congestion and air pollution, Beijing introduced a car ownership restriction policy to curb growth in the number of private cars in the city. However, Beijing residents can still purchase and register their cars in neighboring cities and this “leakage” may substantially reduce the policy’s effectiveness. Using city-level data collected from the CEIC China Premium Database, we aim to quantify the spill-over effect: the impact of Beijing’s policy on the growth of private car registrations in neighboring cities. We first deploy a synthetic control method to create a weighted combination of non-treated cities for each treated city. We then employ a difference-in-differences approach to estimate the policy leakage. Our models suggest that the policy resulted in additional 443,000 cars sold in the neighboring cities (within 500 km of Beijing) from 2011-2013, compared to if the policy had not been implemented. 35%-40% of the car growth reduction stipulated by the policy simply spilled over to neighboring cities. The significance of the policy leakage necessitates positioning Beijing’s urban transportation in a broader context and executing regional collaboration.

  • Parking futures: An international review of trends and speculation

    Land Use Policy
    91
    ,
    (
    2020
    )

    The explosion of low-cost, on-demand taxi services and the anticipation of an autonomous vehicle future has made transportation the center of debate and discussion for the first time since the massive expansion of the US highway system in the 1950s. Yet the realm of parking boasts innovations and developments far beyond the high-profile issues of TNCs and AVs. Rather, innovation in parking is happening in many cases quietly on a wide variety of fronts, including technology, public policy, and design. This paper serves an overview of emerging trends in parking, primarily within the US context. We identify and outline five developments and the pertinent technologies helping to catalyze change: unbundling parking costs, reducing parking minimums, pricing and allocating curb space dynamically, designing hybrid parking structures, and preparing for the autonomous era and “mobility as a service.” This paper presents these trends with illustrative examples highlighting current practices, governance challenges, and possible future scenarios.

  • Measuring Policy Leakage of Beijing’s Car Ownership Restriction in Neighboring Cities

    Transportation Research Board 99th Annual Meeting
    Washington, D.C.
    ,
    (
    2020
    )

    Beijing's license plate lottery policy was originally designed to curb the growth of local vehicle population. However, the avoidance behaviors such as local residents registering their cars in neighboring cities offsets the policy effect. Using the city-level data collected from the CEIC China Premium Database, this study quantitatively identifies the causal effect of the implementation of Beijing's car ownership restriction policy on the growth of private vehicles in neighboring cities. We first use a synthetic control method creating a weighted combination of non-treated cities for each treated city, then employ a difference in difference approach to test the policy leakage effect. The result shows a causal effect of 5.9% on average of Beijing's car ownership restriction policy on the growth of private vehicles in neighboring cities, which amounts to 549 thousand cars. The magnitude of the policy leakage declines by 7.1% every 100 km of driving distance away from Beijing within the 500 km boundary. Our result suggests that as much as 35.4% of the growth in private vehicle population that could have been reduced by the policy simply spilled over to neighboring cities. The significance of the policy leakage necessitates putting Beijing's congestion issues in a broader context and executing regional collaboration. Accordingly, we give some policy suggestions such as parking lots construction, transit system improvement and job- housing co-location.

  • Behavioral Response to Discounted Fares for Low-income Transit Riders in Boston

    Transportation Research Board 99th Annual Meeting
    Washington, D.C.
    ,
    (
    2020
    )

    As public transit agencies across the United States raise fares, transit affordability has emerged a salient equity issue on the political agenda. With few exceptions, transit agencies do not provide means-tested discounts for low-income riders (federal policy only mandates senior and disability discounts). Our research investigates how the cost of public transit influences transit use and access to goods and services among low-income riders, and whether a low-income fare policy instrument could improve the quality of life of low income transit users. A two-month randomized controlled evaluation was conducted to study the effect of providing a 50% discounted MBTA fare to low-income individuals in the Boston region. Individuals receiving food stamps (SNAP) benefits were recruited and randomly assigned to either receive a 50% discount smartcard or a regular smartcard. All participants provided daily travel diary information on the purposes of their transit trips via a custom developed automated SMS/text-based mobile-phone ChatBot software tool. Compared to the control group receiving a standard smartcard, those in the treatment group with a 50% discounted smartcard took, on average, approximately 30% more transit trips, as well as more trips to health care and social services. The research also indicates that compared to the average MBTA rider, the low-income individuals participating in the study took more of their trips during off-peak times and were more likely to pay with their smartcard using stored value (“pay as you go”) rather than purchasing seven-day or monthly passes.

  • Aptitudes for Regulating Autonomous Vehicles: A Survey of Municipal Officials

    Transportation Research Board 99th Annual Meeting
    Washington, D.C.
    ,
    (
    2020
    )

    Local governments play an important role in urban transportation through street management, zoning, right-of-way apportionment, and shared jurisdiction over ride-hailing, transit, and road pricing. While cities can harness these powers to steer the development of new transportation technologies, there is little research about what local officials think about making autonomous vehicle (AV)-related policy changes. We compile key AV-related transportation policies and conduct a large survey of municipal officials throughout the United States. In addition to exploring officials´ personal support for each policy, we examine other aspects of municipal decision-making, including the bureaucratic capacity, legal capacity, and political support for each policy. We find broad personal support among officials for regulations in the areas of land use, right-of-way, and equity, such as for increasing pedestrian street space, expanding access for low-income and disabled people, and reducing sprawl. However, officials emphasized uncertainty with regards to bureaucratic or legal capacity for city intervention outside of land use, right-of-way, and equity; and only a minority expected political support for any policy. Requiring shared vehicles and banning single occupancy vehicles evinced the lowest support of any policy across all spectrums, raising concerns about ongoing efforts to encourage a transportation system with fewer single-occupancy vehicles We identify population size and local-resident political ideology to be most strongly associated with personal and political support for most policies (officials from cities with more liberal residents are much more likely to support AV-related regulations), but local population growth is the most significant characteristic in influencing capacity to undertake policies.

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    What prompts the adoption of car restriction policies among Chinese cities

    International Journal of Sustainable Transportation
    (
    2020
    )

    Facing rapid motorization, many Chinese municipalities are implementing policies that restrict car ownership or use. However, there is significant variation in terms of which cities adopt these policies and when. This research systematically investigates what factors prompt local governments in China to adopt these car restriction policies. We collect a database of car restriction policies as well as economic, demographic, land use, and transportation indicators for 287 Chinese municipalities from 2001 to 2014. We adopt a mixed methods approach that combines a qualitative investigation of stated objectives and legislative precedent within policy documents with a quantitative duration model of policy adoption. We find that the adoption of comprehensive car ownership and use restriction policies across Chinese cities primarily responds to local air pollution and secondarily to car ownership and congestion. Policy adoption additionally responds to local subway line constructions. Local economic power and population size do not effectively explain policy adoption. Idiosyncratic effects at provincial or city levels are important, although the underlying mechanisms by which these network effects manifest remain unclear. Broadly, our findings suggest that problem solving and network effects both contribute to the adoption of car restriction policies across China’s cities and that the legal policy documents reliably illustrate the motivations of these policies.

  • Gender, Social Interaction, and Mobility Sharing

    Transportation Research Board 98th Annual Meeting
    Washington, D.C.
    ,
    (
    2019
    )

    In this paper we answered three questions: 1) Does social interaction in mobility sharing impact the usage and satisfaction level with it? 2) Is there gender deference in considering social interaction as motivation or deterrent for mobility sharing? 3) Is there gender difference in the usage and satisfaction with mobility sharing services. With a survey (n=997) in the U.S. cities where Uber or Lyft is available, we combined data of sociodemographic variables, social interaction indicators, and the usage and satisfaction with mobility sharing services. Using factor analysis and structural equation models we found that 1) positive and negative social interactions both have significant impacts on the usage and satisfaction levels of mobility sharing services, with the former increasing usage and satisfaction, and the latter one reducing them; 2) there is significant gender difference in the agreement on considering social interaction and lack of fellow passenger information as motivation or deterrents for using mobility sharing, but the gender difference is smaller among users than non-users; and 3) based on the previous two findings, there is significant indirect gender effect on the usage and satisfaction with mobility sharing. Nonetheless, this effect is canceled by the direct effect of gender on mobility sharing usage and satisfaction, and the total effect is insignificant.

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    Transportation Policymaking in Beijing and Shanghai: Contributors, Obstacles, and Process

    Case Studies on Transport Policy
    (
    2019
    )

    With continued motorization and urbanization in Chinese cities, there is a growing demand for innovative transportation policies at the city level to address the challenges of congestion, local air pollution, and greenhouse gas emissions. Using Beijing and Shanghai as case studies, this paper draws on 32 in-depth semi-structured interviews with municipal government officials, academics, and transportation professionals to explore the city-level transportation policymaking process in Chinese megacities. Across the two cities, we identify three common contributors – policy learning, data informatization, and public opinion—and four obstacles—public complaint, unilateral decision-making, inadequate coordination among relevant departments, and lack of adaptiveness in policy implementation practice—to adopting timely and appropriate transportation policies. We then introduce a processual model that connects the contributors and obstacles identified within the flow of transportation policy among key actors in city-level government. This process shows how transportation policymaking in Chinese megacities is often reactive to public outcry over a transportation problem. This problem is investigated by a technical government research center that reports to the municipal transport committee. This committee then assesses public opinion and submits a policy recommendation to city government leadership, who make the final policy decision. Based on both case studies, we discuss potential recommendations for how to better enable transportation policymaking at the city level in China through more formalized processes of policy experimentation and public participation. We conclude with a discussion of limitations and areas of future research.

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    Are cities prepared for autonomous vehicles? Planning for technological change by U.S. local governments

    Journal of the American Planning Association
    (
    2019
    )

     

    Problem, Research Strategy, and Findings: Local government policies could impact how autonomous vehicle (AV) technology is deployed. This paper examines how municipalities are planning for AVs, identifies local characteristics that are associated with preparation, and describes what impacts bureaucrats expect from the vehicles. We review existing plans of the United States’ 25 largest cities and survey transportation and planning officials from 120 cities, representative of all municipalities with populations larger than 100,000. First, we find that few local governments have commenced planning for AVs. Second, cities with larger populations and higher population growth are more likely to be prepared. Third, while local officials are optimistic about the technology and its potential to increase safety while reducing congestion, costs, and pollution, more than a third of respondents worried about AVs increasing vehicle-miles traveled and sprawl while reducing transit ridership and local revenues. Those concerns are associated with greater willingness to implement AV regulations, but there is variation among responses depending on political ideology, per-capita government expenditures, and population density.

    Takeaway for Practice: Municipal governments’ future approaches to AV preparation will likely depend on characteristics of city residents and local resources. Planners can maximize policy advancement if they work with officials in other cities to develop best practices and articulate strategies that overlap with existing priorities, such as reducing pollution and single-occupancy commuting. 

    Cited as: "Yonah Freemark, Anne Hudson & Jinhua Zhao (2019) Are Cities Prepared for Autonomous Vehicles?,Journal of the American Planning Association, DOI: 10.1080/01944363.2019.1603760"

     

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    Transportation Policy Profiles of Chinese City Clusters: A Mixed Method Approach

    Transportation Research Interdisciplinary Perspectives
    (
    2019
    )

    Chinese cities have experienced diverse urbanization and motorization trends that present distinct challenges for municipal transportation policymaking. However, there is no systematic understanding of the unique motorization and urbanization trends of Chinese cities and how physical characteristics map to their transportation policy priorities. We adopt a mixed-method approach to address this knowledge gap. We conduct a time-series clustering of 287 Chinese cities using eight indicators of urbanization and motorization from 2001-2014, identifying four distinct city clusters. We compile a policy matrix of 21 policy types from 44 representative cities and conduct a qualitative comparison of transportation policies across the four city clusters. We find clear patterns among policies adopted within city clusters and differences across clusters. Wealthy megacities (Cluster#1) are leveraging their existing urban rail with multimodal integration and transit-oriented development, while more car-oriented wealthy cities (Cluster#2) are building urban rail and discounting public transport. Sprawling, medium-wealth cities (Cluster#3) are opting for electric buses and the poorest, dense cities with low mobility levels (Cluster#4) have policies focused on road-building to connect urban cores to rural areas. Transportation policies among Chinese cities are at least partially reflective of urbanization and motorization trends and policy learning needs to account for these distinct patterns in both physical conditions and policy priorities. Our mixed-method approach (involving time-series clustering and qualitative policy profiling) provides a way for government officials to identify peer cities as role models or collaborators in forming more targeted, context-specific, and visionary transportation policies.

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    Legitimacy vs morality: Why do the Chinese obey the law?

    Law and Human Behavior
    42
    ,
    (
    2018
    )

    This study explored two aspects of the rule of law in China: (1) motivations for compliance with 4 groups of everyday laws and regulations and (2) determinants of the legitimacy of legal authorities. We applied a structural equations model, constructed from Tyler’s conceptual process-based self-regulation model with morality added as a motivation, to online questionnaire responses from 1,000 Shanghai drivers. We explored the compliance with four particular groups of laws: public disturbance; conventional traffic laws; illegal downloading; and distracted driving. The results were threefold. First, for all four groups of laws, the perceived morality influenced compliance consistently and more strongly than the perceived legitimacy of the authorities and all other motivations. The influence of perceived legitimacy of authorities was inconsistent across the four groups of laws tested. Second, the influence of perceived severity of punishment was consistent and significant across all four groups of laws, whereas perceived risk of apprehension had no significant impact on compliance. Third, evaluations of procedural fairness, not those concerning the equitable distribution of law enforcement services and effectiveness of law enforcement, were most strongly linked to legitimacy. In addition to showing that China is a law-abiding society governed by morality, these results underscore the importance of examining morality and magnitude of punishment as potential motivations for compliance in addition to legitimacy and certainty of punishment. They also illustrate the necessity to examine different groups of laws separately when studying compliance. Finally, these results challenge the linkage between legitimacy and compliance previously established in the literature.

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    An Urban Agenda for Autonomous Vehicles: Embedding Planning Principles into Technological Deployment

    Transportation Research Board 97th Annual Meeting
    Washington, D.C.
    ,
    (
    2018
    )

    The deployment of autonomous vehicles (AVs) has spawned a considerable literature on the role of national and state-level governments in regulating components of AV manufacturing, emissions, safety, licensing, and data sharing. These provide insight into how AVs can be integrated into the current transportation system. Yet the potential for local governments to shape their futures through AV policies is underexplored. This paper argues that it is both necessary and feasible for local government to adjust local mobility policies for AVs towards the goal of achieving key planning principles by disrupting the current transportation system. Local governments must leverage the ephemeral moment in advance of full-scale AV rollout to achieve the principles of equitable, environmentally sustainable, efficient, and livable cities. It is necessary to establish a new regulatory relationship with automobiles and design mobility policies to cultivate AV benefits, while responding to their potentially deleterious impacts. Local governments are capable of doing so through their already-existing regulatory mechanisms managing much of the transportation infrastructure, public transit, taxi, parking, land uses, and public data. Based on such local government power, we identify eight policy instruments that are feasible: centralized data collection and distribution; distance- and congestion-based road pricing; integration of AV and transit networks; income-based subsidies; minimum levels of service provision; zero-emission vehicles; lowered parking provision; and a rethinking of the use of street space. We explore how such instruments could be implemented in the context of existing regulatory mechanisms through the diverging lenses of indicative cases of Chicago and London.

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    Worse than Baumol’s disease: The implications of labor productivity, contracting out, and unionization on transit operation costs

    Transport Policy
    61
    ,
    (
    2017
    )

    Unit costs measured as bus operating costs per vehicle mile have increased considerably above the inflation rate in recent decades in most transit agencies in the United States. This paper examines the impact of (lack of) productivity growth, union bargaining power, and contracting out on cost escalation. We draw from a 17-year (1997–2014) and a 415-bus transit agency panel with 5780 observations by type of operation (directly operated by the agency or contracted out). We have three main findings: first, the unit cost increase in the transit sector is far worse than what economic theory predicts for industries with low productivity growth. Second, contracting out tends to reduce unit costs, and the results suggest that the costs savings from private operations can be only partly explained by lower wages in the private sector. Interestingly, we find that the cost savings from contracting out are larger when the transit agency also directly operates part of the total transit service. However, while overall unit costs are lower in contracted services, cost growth in large private bus operators is no different than cost growth in large public transit operators. Third, unique transit labor laws that lead to union bargaining power are a likely driver of the unit cost growth above inflation. Overall, these factors reflect inherent characteristics of the bus transit sector, such as the nature of low productivity growth and union legislative power related to the need for public subsidy. They drive increases in both transit fares and public subsidy at rates higher than inflation, and play an important role in the deterioration of transit agencies’ financial sustainability.

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    Distributional Effects of Lotteries and Auctions —License Plate Regulations in Guangzhou

    Transportation Research Part A: Policy and Practice
    106
    ,
    (
    2017
    )

    Lotteries and auctions are common ways of allocating public resources, but they have rarely been used simultaneously in urban transportation policies. This paper presents a unique policy experiment in Guangzhou, China, where lotteries and auctions are used in conjunction to allocate vehicle licenses. Guangzhou introduced vehicle license regulations to control the monthly quota of local automobile growth in 2012. To obtain a license, residents are required to choose between the lottery and auction method. Since the introduction of the regulations, there has been heated debates on the distributional effects of lotteries and auctions; however, the debates have not been grounded in empirical studies. We analyze the distributional effects of such mixed mode of resource allocation in a positive manner based on individual behavioral choices. We conducted a survey in January 2016 (n = 1,000 people * 12 months), and used mixed logit models to analyze how socio-economic status, including income and automobile ownership, determined people’s choices among lottery, auction, and non-participation alternatives. We find that income increased participation, but did not influence non-car owners’ choices between lotteries and auctions, which contrasts with the common notion that lotteries benefit the poor. Additionally, the positive impact of car ownership on participation indicates a car-dependent trajectory for automobile growth. The significant socio-economic differentiators between lotteries and auctions were age, gender, and education. Proxies of mobility needs were insignificant overall. The program attributes had a much larger impact than all other variables—people were more likely to choose lotteries with higher winning rates and more participants and more likely to choose auctions with higher prices and more participants. We concluded that for those who participated, the choice between lotteries and auctions did not depend on their income or mobility needs but, rather, the probability of winning plates and the opportunity for speculation. 

    Full Paper (PDF)

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    Traffic Law Compliance by Chinese Drivers: Demographics and Motivations

    Transportation Research Board 96th Annual Meeting
    (
    2017
    )

    Research on Chinese traffic law compliance is lacking compared to the West. Yet it is increasingly important because of explosive recent growth of cars in China. Although demographic attributes such as age and gender and certain driver characteristics such as experience and annual mileage have been studied in regard to traffic law compliance, normative and instrumental motivations for compliance have not been thoroughly studied. Normative motivations specifically have not been fully considered in the Chinese context. Normative motivations are particularly important because they compel people to comply without policy instruments. We investigate the motivations for traffic law compliance in China with a more inclusive framework that incorporates legitimacy and morality as normative motivations. We show that while morality was most strongly related to compliance for all groups, other motivations exerted varying degrees of influence on compliance for different groups. In particular, legitimacy influences compliance more strongly for younger drivers than for older drivers for traffic violations particular to China. In contrast, concerns about personal safety influence compliance more strongly for older drivers than for younger drivers. We also show that there exists the norms gap between distracted driving and other traffic laws. This study suggests possible strategies for policymakers to tailor enforcement and public campaigns towards different demographic groups and for particular traffic laws.

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    Gaining Acceptance by Informing the People? Public Knowledge, Attitudes, and Acceptance of Transportation Policies

    Journal of Planning Education and Research
    (
    2017
    )

    We examine the connection between public knowledge and attitudes in the context of urban transportation policies. We categorize policy knowledge into received, subjective, and reasoned knowledge, and measure them empirically using a survey of Shanghai’s residents (n=1,000) on the vehicle license auction policy. We quantify the relationship between the three types of knowledge and public acceptance and its predecessors (perceived effectiveness, affordability, and equity). We find variegated impacts of knowledge on acceptance: reasoned knowledge increases acceptance but subjective knowledge decreases it, while received knowledge has no direct impact. Public information needs to emphasize societal benefits and the underlying policy rationale.

     

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    Normative and Image Motivations for Compliance with Sustainable Transportation Policy

    Urban Studies
    (
    2016
    )

    Compliance with laws and regulations intended to protect common pool resources in the urban context is essential in tackling problems such as pollution and congestion. A high level of non-compliance necessitates an investigation into motivations behind compliance. The long-held instrumental theory emphasising the dependence of compliance on tangible deterrence measures fails to adequately explain empirical findings. More recently established compliance models incorporate normative, instrumental and image factors as motivations for compliance. We investigate the importance of normative and image motivations for transportation policy compliance, and the influence of the hukou (China’s household registration) on the composition of motivations. Through a case study of Shanghai’s license auction policy to inhibit car growth, we use a structural equation model and data from a survey (n = 1389) of policy attitudes and compliance behaviour. The results show that both locals and migrants comply because of instrumental motivation. However, for locals, normative and image motivations not only influence compliance but do so to a greater degree than instrumental motivations. This stands in stark contrast with the fact that there was no statistical relationship between normative and image motivations and compliance for migrants. The significant contribution of normative and image motivations to compliance in locals bears positive implications for compliance, but the absence of that in migrants is worrying. If only instrumental motivations matter, then the government is really constrained in how it can go about keeping social order. Compliance obtained strictly through social control indicates an unsustainable state of governance. 
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    Reducing Subway Crowding: Analysis of an Off-peak Discount Experiment in Hong Kong

    Transportation Research Record: Journal of the Transportation Research Board
    Washington, D.C.
    ,
    (
    2016
    )

    Increases in ridership are outpacing capacity expansions in a number of transit systems. By shifting their focus to demand management, agencies can instead influence how customers use the system, getting more out of the capacity they already have. This paper uses Hong Kong's MTR system as a case study to explore the effects of crowding-reduction strategies as well as methods to use automatically collected fare data to support these measures. MTR introduced a pre-peak discount in September 2014 to encourage users to travel before the peak hour and reduce on-board crowding. To understand the impacts of this intervention, existing congestion patterns were first reviewed and a clustering analysis was performed to reveal typical travel patterns among MTR users. Then changes to when users chose to travel were studied at three levels to evaluate the program’s effects. Patterns among all users were measured across both the whole system and for specific rail segments. The travel patterns of the user groups, who have more homogeneous usage characteristics, were also evaluated, revealing differing responses to the promotion among groups. The incentive was found to have small impacts on morning travel, particularly at the beginning of the peak hour and among users with commuter-like behavior. Aggregate and group-specific elasticities were developed to inform future promotions and the results were also used to suggest other potential incentive designs.

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    Modeling Saliency in Transportation Pricing: Optimal Mixture of Automobile Management Policies

    Transportation Research Board 94th Annual Meeting
    Washington, D.C.
    ,
    (
    2015
    )

    We introduce the advantage of behavioral economics into the transportation policy evaluation criteria that traditional economic approaches do not consider. To that end, we present a framework for using tax salience as a connection between the dimensions of government policy objectives (revenue, behavior change, and public acceptance) with tax instruments (car ownership charge, fuel tax, congestion tax, parking fee) meant to influence behavior. Salience is the psychological effect of paying more/less attention to something relative to its context. This paper concerns price saliency with respect to transportation, which we define as when actual cost differs from perceived cost depending on aspects of price and payment. A review of relevant literature on policy-making frameworks and tax salience reveals the connection between operational and externality costs, perceived costs to the user, and actual government-collected revenue. Salience is proposed as a modifier for adjusting how much is paid by users of the transportation system (revenue), and how much users perceive paying (internalized externality cost), whereby users can internalize the cost of the negative externalities generated by car-related behaviors, and government can attain its objectives. We reveal the ambiguity of the equity principle: should a policy be equitable with respect to its actual tax, perceived tax, or effect on behavior? We discuss incorporating into the framework technology, privacy, policy synergies, and proxy instruments. Lastly, the complexities of salience’s relationship with acceptance and technology make it unclear whether decreasing salience is always desirable.

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    The Formation of a Transport Policy Market in China: From Policy Transfer to Policy Mobility

    Transportation Research Board 93rd Annual Meeting
    Washington, D.C.
    ,
    (
    2014
    )

    Policy travel, a series of processes in which policies are transmitted and, possibly, mutated through a network of policy-making sites, plays an important role in China’s rapid transportation development. This paper examines the Chinese transport policy market framework: its formation, components and transactions. The study is based on 30in-depth interviews with politicians, technicians and academics involved in transport policy and 14 transportation policies discussed in 11 Chinese cities. The study found that policy learning, policy transfer and policy mobility are occurring in China, and have led to the formation of a policy market. The four major components of a policy market are products, traders, consumers/producers and currencies. Products include both abstract concepts and specific operational details, as well as negative lessons and inactive success, i.e. success achieved by not applying a policy available in the market. Traders include a variety of academics and students, bureaucrats and politicians, the public and the media, and consultants and industry. Consumers and producers in a transaction are matched by geography and stage of development. The market’s currencies are fiscal capacity, technical capacity and reputational capacity, which may be partly interchangeable. Chinese approaches to policy transactions may be characterized by emulation or inspiration or by an emulation/inspiration hybrid. The market includes free transactions, centralized transactions, and mixed transactions. Constraints, such as the principal-agent dilemma, may lead to market failure, and politicians' personal judgment leads to considerable uncertainty in the market. The study suggests three ways to improve the transport policy market: develop a systematic approach to policy travel, improve transparency, and encourage personal interactions between policy-makers.

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    Lotteries vs. Auctions: China’s Experiments in Managing Automobile Growth

    Asia Pacific Memo
    Vancouver
    ,
    (
    2013
    )

    The astronomical growth in the number of private cars in China has led to very visible environmental crises and congestion. But the nationwide increase conceals crucial policy differences between cities that influence effectiveness, revenue, efficiency, equity and public acceptance.  While Shanghai and Beijing each had approximately 2 million motor vehicles in 2004, by 2010 Beijing had 4.8 million versus Shanghai’s 3.1 million.  By 2011, 38% of Beijing households were vehicle owners in contrast to 18% in Shanghai.  Two decades ago Shanghai opted for a monthly license auction to control vehicle ownership, while Beijing had few controls over usage or ownership until the run up to the 2008 Olympics

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    Bidding to Drive: Car License Auction Policy in Shanghai and Its Public Acceptance

    Transport Policy
    27
    ,
    (
    2012
    )

    Increased automobile ownership and use in China over the last two decades has increased energy consumption, worsened air pollution, and exacerbated congestion. However, the countrywide growth in car ownership conceals great variation among cities. For example, Shanghai and Beijing each had about 2 million motor vehicles in 2004, but by 2010, Beijing had 4.8 million motor vehicles whereas Shanghai had only 3.1 million. Among the factors contributing to this divergence is Shanghai’s vehicle control policy, which uses monthly license auctions to limit the number of new cars. The policy appears to be effective: in addition to dampening growth in car ownership, it generates annual revenues up to 5 billion CNY (800 million USD). But, despite these apparent successes, the degree to which the public accepts this policy is unknown.

    This study surveys 524 employees at nine Shanghai companies to investigate the policy acceptance of Shanghai’s license auction by the working population, and the factors that contribute to that acceptance: Perceived policy effectiveness, affordability, equity concerns, and implementation. Respondents perceive the policy to be effective, but are moderately negative towards the policy nonetheless. However, they expect that others accept the policy more than they do. Respondents also hold consistently negative perceptions about the affordability of the license, the effects on equity, and the implementation process. Revenue usage is not seen as transparent, which is exacerbated by a perception that government vehicles enjoy advantages in obtaining a license, issues with the bidding process and technology, and difficulties in obtaining information about the auction policy. Nevertheless, respondents believe that license auctions and congestion charges are more effective and acceptable than parking charges and fuel taxes. To improve public acceptability of the policy, we make five recommendations: Transparency in revenue usage; transparency in government vehicle licensing and use, categorising licenses by vehicle type, implementation and technology improvements to increase bidding convenience, and policies that restrict vehicle usage in congested locations.

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