Abstract

Freight forwarders play a key role in moving goods across international borders. They arrange transport, oversee customs clearance on behalf of their clients, and more generally troubleshoot issues that arise while goods are in transit. This paper reports the results from a survey of 153 freight forwarding firms in Serbia. Respondents report on firm characteristics, operational choices, and conditions at the border posts and terminals where imported goods are cleared for release. One key purpose of the study is to investigate operational trade-offs between time and cost that arise when import shipments are in transit. In three of four hypotheticals, respondents suggest that money savings dominate time savings. Responses regarding real operational decisions such as route choices reinforce this finding. Respondents also reported penalty rates for late delivery of import shipments as well as the value of a typical import shipment. From these responses, it is estimated that the contracted value of one additional (unexpected) day of delivery time in Serbia appears to be approximately 1 percent of the value of the underlying shipment. Document type: Book

Abstract

In this context, this note summarizes the findings of a recent World Bank, SACU Secretariat assessment of regional trade facilitation based on the Trade and Transport Facilitation Assessment (TTFA) methodology. The assessment looks at regional trade facilitation through the lens of value chains, with the objective to understand how the region’s trade and transport environment could be improved to facilitate more extensive and deeply integrated regional trade, linked to competitive participation in global value chains. The remainder of this note is structured as follows: section two provides a brief overview of regional trade and freight flows. This is followed in section three by a brief review of the trade and transport environment (including infrastructure and policy) across each SACU member state. Section four summarizes the findings of the detailed analysis, from a trade facilitation perspective, of the regional value chains in four key industry sectors: agro-processing; agro-processing; automotive; beef; and textiles/apparel. Section five then focuses on identifying potential solutions to three key trade and transport facilitation challenges identified through the value chain assessments. Finally, section six concludes.

Abstract

In less than fifty years, Brazil evolved from a predominantly rural society and economy to a highly urbanized country in which 85 percent of its people now live in urban areas and more than 90 percent of the country’s GDP is generated in the cities. This rapid urbanization process was characterized by a lack of planning and an enduring framework of inequality, resulting in high degrees of concentrated poverty in the urban areas. Much of this urbanization has taken place in metropolitan regions (MRs). MRs have grown more rapidly than the rest of the country, both in population and in GDP terms. In 2010, per capita GDP was higher in MRs than in the rest of the country and metropolitan economies accounted for 70 percent of GDP. At the same time, half of the Brazilian poor and 90 percent of the people living in subnormal conditions were found in metropolitan regions. The recent approval of a new framework for metropolitan governance inBrazil creates the opportunity for debate and evolution regarding several key issues. These include: a) placing metropolitan matters at the forefront of the development arena in Brazil; b) reviewing what has been learned about inter-municipal governance and service delivery; c) estimating resource mobilization needs for metropolitan development; d) coordinating metropolitan land use with transport and housing; e) including metropolitan concerns in any revision of fiscal federalism; and f) promoting environmental sustainability, social inclusion and resilience to disasters and climate change plans at the metropolitan scale. The World Bank can be a partner in addressing these issues. In responding to client demand, the Bank has been providing a range of support to Brazilian states and cities and especially their low- income populations in the areas of infrastructure, social services, slum upgrading, institutional development, river basin management, local economic development, environmental protection, water and sanitation, and transportation.

Abstract

n efficient system to transport goods domestically and internationally is a key element of the logistics chain. Road freight transport has a direct impact on poverty as it employs millions of people and generates a significant portion of Gross Domestic Product, or GDP, especially in low and middle-income countries. Trucking is the primary form of transportation for domestic, trans-border, and international cargo, in Central America. Road freight transport is now vital to production, distribution, and mobilization, driving economic, social, and environmental progress. In short, trucking is the backbone of economies around the world. In the past 20 years, the industry has advanced as technology has improved communication, management, productivity, including vehicle efficiency. Their objective in doing so is to expand markets, generate wealth on the basis of efficient specialization, introduce competition, and lower costs for production, distribution, services, and research and development. When road freight transport services are efficient, they support these objectives; when they are not they act as nontariff barriers to trade, creating delays, raising costs, worsening congestion and pollution. Such barriers prolong and destabilize delivery schedules, hinder 'just in time' inventory management and industrial processes, and impede the efficient combination of factors of production.

Abstract

Infrastructure services are significant determinants of economic development, social welfare, trade, and public health. As such, they typically feature strongly in national development plans. While governments may receive many infrastructure project proposals, however, resources are often insufficient to finance the full set of proposals in the short term. Leading up to 2020, an estimated US$836 billion - 1 trillion will be required each year to meet growth targets worldwide (Ruiz-Nunez and Wei, 2014; World Bank). Global estimates of infrastructure investments required to support economic growth and human development lie in the range of US$65-70 trillion by 2030 (OECD, 2006), while the estimated pool of available funds is limited to approximately US$45 trillion (B20, 2014). The past twenty years have also seen a shift towards decentralized infrastructure planning. Many subnational governments, regional entities, and sector agencies have been delegated responsibility for infrastructure planning promote local responsiveness, but responsibility for allocating funds often remains with a centralized finance agency (CFA). While constituencies may propose numerous projects, governments often have insufficient financial resources to implement the full suite of proposals. This report presents the IPF methodology and results of the pilot application to a select set of transport and water and sanitation projects in Panama. The report first gives background information on infrastructure prioritization in Panama, then follows with a description of the IPF in technical and implementation terms. Next, we present the results of the pilot and close with recommendations for implementing IPF to a wider set of projects.

Abstract

In this paper, we investigate the impact of travel costs, in particular toll costs, on the residential location choice of households, using a stated choice survey. Within the stated choice experiment, car drivers that frequently face traffic congestion, traded-off several trip-related (including toll costs) and house/location-related factors in their decision where to locate. If we look at the influence of different variables, toll and fuel costs seem to be important. Respondents are more sensitive to travel costs (i.e. toll and fuel costs) than to equally high (monthly) housing costs. Travel time appears to play a less important role, as indicated by a low value of time (VOT). In addition, location-related factors, such as the type of location and the number of bedrooms, turn out to be important factors as well. It can be concluded that respondents generally speaking prefer to pay higher housing costs and accept longer travel times to avoid (high) travel costs. Finally, if we look at the difference in preferences in relation to toll and fuel cost, we can conclude that toll costs are valued more negatively than fuel costs, although the differences are small. (C) 2010 Elsevier Ltd. All rights reserved.

Abstract

The transportation demand is rapidly growing in metropolises, resulting in chronic traffic congestions in dense downtown areas. Adaptive traffic signal control as the principle part of intelligent transportation systems has a primary role to effectively reduce traffic congestion by making a real-time adaptation in response to the changing traffic network dynamics. Reinforcement learning (RL) is an effective approach in machine learning that has been applied for designing adaptive traffic signal controllers. One of the most efficient and robust type of RL algorithms are continuous state actor-critic algorithms that have the advantage of fast learning and the ability to generalize to new and unseen traffic conditions. These algorithms are utilized in this paper to design adaptive traffic signal controllers called actor-critic adaptive traffic signal controllers (A-CATs controllers). The contribution of the present work rests on the integration of three threads: (a) showing performance comparisons of both discrete and continuous A-CATs controllers in a traffic network with recurring congestion (24-h traffic demand) in the upper downtown core of Tehran city, (b) analyzing the effects of different traffic disruptions including opportunistic pedestrians crossing, parking lane, non-recurring congestion, and different levels of sensor noise on the performance of A-CATS controllers, and (c) comparing the performance of different function approximators (tile coding and radial basis function) on the learning of A-CATs controllers. To this end, first an agent-based traffic simulation of the study area is carried out. Then six different scenarios are conducted to find the best A-CATs controller that is robust enough against different traffic disruptions. We observe that the A-CATs controller based on radial basis function networks (RBF (5)) outperforms others. This controller is benchmarked against controllers of discrete state Q-learning, Bayesian Q-learning, fixed time and actuated controllers; and the results reveal that it consistently outperforms them.

Abstract

This objective of this chapter was to analyze the effects of the traffic restraint policy introduced in 2001 in and by the Paris municipality, and to sketch a comparison with the policy introduced in London at about the same time – with the proviso that the geographic, economic, demographic, institutional, historic and political contexts are very different. The results do not speak highly in favor of the French policy. In both cases, the stated objectives of reducing traffic have been achieved. But success in itself is not enough. One must also see how and to what cost it has been obtained. In London, it has been achieved by means of a toll, and accompanied by an increase in motor vehicle speed, generating a time gain for car users, and also for bus users, and a small environmental gain. In Paris, the main policy instrument has been the reduction of road space for motor vehicles, which led to a decrease in motor vehicle speed, but failed to increase bus speed and patronage. The policy generated a considerable time loss for car users and for goods delivery vehicles, and even environmental losses, without gains for public transport users. The only benefit seems to have been a small one for bicycle users: 0.4 per cent of all losses. The downside for the London policy is the implementation cost, which is high, but which can be expected to decline over time.

Abstract

Abstract: Abstract We study duopolistic pricing by ports that are congestible, share the same overseas customers and have each a downstream, congestible transport network to a common hinterland. In the central set-up, local (country) governments care about local welfare only and decide on the capacity of the port and of the hinterland network. We obtain the following results. First, profit-maximizing ports internalize hinterland congestion in as far as it affects their customers. Second, investment in port capacity reduces prices and congestion at both ports, but increases hinterland congestion in the region where the port investment is made. Investment in a ports hinterland is likely to lead to more port congestion and higher prices for port use, and to less congestion and a lower price at the competing port. Third, the induced increase in hinterland congestion is a substantial cost of port investment that strongly reduces the direct benefits of extra port activities. Fourth, imposing congestion tolls on the hinterland road network raises both port and hinterland capacity investments. We illustrate all results numerically and discuss policy implications.

Abstract

This thesis presents new evidences of negative impacts of traffic congestion in São Paulo Metropolitan Area, indicating that the omission or retardation of policy to alleviate that charges society with a high cost. Besides that, we shed light on Waze application\\'s impacts, evidencing GPS-based participatory navigation is a key element of the traffic in the contemporary cities. Induced by the economic theory, one can see that traffic slowness derived from the general demand for automotive vehicles corresponds to a social cost. With the objective of translating this cost to monetary units, we developed an approach that matches the 2012 Origin-Destination survey to Google Maps data. An econometric travel mode choice model is estimated and through that we infer the Value of Time for trips. From counterfactual analysis for travel duration, we estimate the delays of the trips in relation to a hypothetic free flow situation. Joining the calculations, we estimate that 89% of the trips motivated by work in São Paulo are retarded by traffic frictions, generating an annual welfare cost that amounts to R$7.338 billions. Additionally, we analyze widespread Waze malfunctioning at 10/23/2017. Combining congestion data to the Value of Time, we estimate that the Waze bug approximatedely tripled the welfare costs in regards to a typical day, showing the magnitude of mass effects that a social navigation application is able to trigger. Esta dissertação traz novas evidências dos efeitos negativos do congestionamento do trânsito na Região Metropolitana de São Paulo, mostrando que a morosidade na implantação de soluções custa muito caro para a sociedade. Além disso, evidências empíricas dos impactos do aplicativo Waze são elucidadas, mostrando que a navegação participativa por meio de aparelhos com GPS não pode ser esquecida ao pensarmos o trânsito nas cidades contemporâneas. À luz da teoria econômica, é possível ver que a lentidão do trânsito proveniente da demanda coletiva por automóveis corresponde a um custo social. Para quantificar este custo em unidades monetárias, é desenvolvida uma abordagem que combina dados da Pesquisa de Mobilidade de 2012 com dados do Google Maps. Através de um modelo econométrico de escolha de modal de transporte, são inferidos os valores do tempo em viagem e, através da análise contrafactual da duração dos deslocamentos, é estimado o tempo de atraso das viagens em relação a uma situação hipotética de fluxo livre. Juntando os cálculos, é estimado que 89% das viagens motivadas por trabalho em São Paulo são atrasadas por fricções do tráfego, gerando um custo de bem-estar da ordem de R$7,338 bilhões por ano. Ademais, são analisados empiricamente os impactos de uma falha generalizada do Waze ocorrida em 23/10/2017. Combinando dados de congestionamento com os valores de tempo já inferidos, é estimado que a falha aproximadamente triplicou os custos de bem-estar em relação a um dia típico, dando magnitude aos efeitos de massa que um aplicativo de navegação social é capaz de provocar.