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on Transport Economics |
| By: | Sanguinetti, Angela; Alston-Stepnitz, Eli; Cimene, Angelika |
| Abstract: | Consumer education regarding the costs of electric vehicles (EVs), particularly in comparison with similar gasoline vehicles, is important for adoption. However, the complexity of comparing gasoline and electricity prices, and balancing long-term return-on-investment from fuel and maintenance savings with purchase premiums for EVs, makes it difficult for consumers to assess potential economic advantages. Online vehicle cost calculators (VCCs) may help consumers navigate this complexity by providing tailored estimates of different types of vehicles costs for users and enabling comparisons across multiple vehicles. However, VCCs range widely and there has been virtually no behavioral research to identify functionalities and features that determine their usefulness in engaging and educating consumers and promoting EV adoption. This research draws on a behavioral theory, systematic review of available VCCs, and user research with three VCCs to articulate design recommendations for effective VCCs. View the NCST Project Webpage |
| Keywords: | Social and Behavioral Sciences, Electric vehicles, consumer adoption, cost calculators, usability, user experience |
| Date: | 2020–04–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt368290kp&r=all |
| By: | Katrin Heßler (Johannes Gutenberg-University Mainz, Germany) |
| Abstract: | The multi-compartment vehicle routing problem with flexible compartment sizes is a variant of the classical vehicle routing problem in which customers demand different product types and the vehicle capacity can be separated into different compartments each dedicated to a specific product type. The size of each compartment is not fixed beforehand but the number of compartments is limited. We consider two variants for dividing the vehicle capacity: On the one hand the vehicle capacity can be discretely divided into compartments and on the other hand compartment sizes can be chosen arbitrarily. The objective is to minimize the total distance of all vehicle routes such that all customer demands are met and vehicle capacities are respected. Modifying a branch-and-cut algorithm based on a three-index formulation for the discrete problem variant from the literature, we introduce an exact solution approach that is tailored to the continuous problem variant. Moreover, we propose two other exact solution approaches, namely a branch-and-cut algorithm based on a two-index formulation and a branch-price-and-cut algorithm based on a route-indexed formulation, that can tackle both packing restrictions with mild adaptions and can be combined into an effective two-stage approach. Extensive computational tests have been conducted to compare the different algorithms. For the continuous variant, we can solve instances with up to 50 customers to optimality and for the discrete variant, several previously open instances can now be solved to proven optimality. Moreover, we analyse the cost savings of using continuously flexible compartment sizes instead of discretely flexible compartment sizes. |
| Keywords: | routing, branch-price-and-cut, multi-compartment |
| Date: | 2020–04–03 |
| URL: | http://d.repec.org/n?u=RePEc:jgu:wpaper:2007&r=all |
| By: | Oshan, Taylor M. |
| Abstract: | Massive amounts of data that characterize how people meet their economic needs, interact within social communities, and utilize shared resources are being produced by cities. Harnessing these ever-increasing data streams is crucial for understanding urban dynamics. Within the context of transportation modeling it still remains largely unknown whether or not these new data sources provide the opportunity to better understand spatial processes. Therefore, in this paper, the usefulness of a recently available big transport dataset - the New York City (NYC) taxi trip data - is evaluated within a spatial interaction modeling framework. This is done by first comparing parameter estimates from a model using the taxi data to parameter estimates from a model using a traditional commuting dataset. In addition, the high temporal resolution of the taxi data provide an exciting means to explore potential dynamics in movement behavior. It is demonstrated how parameter estimates can be obtained for temporal subsets of data and compared over time to investigate mobility dynamics. The results of this work indicate that a pitfall of big transport data is that it is less useful for modeling distinct phenomena; however, there is a strong potential for modeling high frequency temporal dynamics of diverse urban activities. |
| Date: | 2020–03–09 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:gwumt&r=all |
| By: | Vinokurov, Evgeny |
| Abstract: | Countries in Northern and Central Eurasia, including its largest economies, Russia and Kazakhstan, were among early believers in the value of the Belt and Road Initiative. Over the last years, they increasingly embraced various aspects of the BRI, most importantly additional investment and rising volumes of trans-Eurasian traffic. The latter, apart from being a lucrative business on its own, should eventually lead to better internal connectivity between inner-Eurasian regions. In this article I provide data and estimates for the spectacular growth of the volumes of trans-Eurasian container transit. Then I move to explain the underlying reasons and prospects. Finally, there are important remarks on the issue of financing, the role of China, and the role of international financial institutions. |
| Keywords: | Belt and Road Initiative; Central Asia; transport corridors; Russia; international financial institutions |
| JEL: | F15 F21 F34 R41 |
| Date: | 2020–02 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:98972&r=all |