An analysis of destination choice for opaque airline products using multidimensional binary logit models

We investigate how customers respond to an opaque airline product offered by a European carrier. In this opaque product design, customers are randomly assigned to travel to one of approximately ten destinations; however, for a fee they may exclude one or more destinations from the choice set (or a particular package design) prior to learning which destination they will travel to. We use a multidimensional binary logit model to predict the probability that one or more alternatives will be chosen by a customer. Results show that customers are more likely to pay to exclude destinations located close to the origin airport and destinations that speak the same language as the origin airport. Length of stay, cost of living at the destination, and measures of destination attractiveness are also found to be significant predictors for some package designs. Based on these findings, we offer general recommendations for how to design opaque packages for airline customers.     

Do parking requirements significantly increase the area dedicated to parking? A test of the effect of parking requirements values in Los Angeles County

Minimum parking requirements (MPRs) are the norm for urban and suburban development in the United States (Davidson et al., 2002). The justification for MPRs is that overflow parking will occupy nearby street or off-street parking. Shoup (1999a) and Willson (1995) provide cases where there is reason to believe that parking space requirements have forced parcel developers to place more parking than they would in the absence of parking requirements. However, to our knowledge the existing literature does not test the effect of parking minimums on the amount of lot space devoted to parking beyond a few case studies. This paper tests the hypothesis that MPRs bind for most land uses using data on suburban office, commercial, industrial and retail property sales from Los Angeles County using both direct and indirect approaches. Our indirect test of the effects of parking requirements is similar to the one used by Glaeser and Gyourko (2003). A simple theoretical model shows that the marginal value of additional parking to the sale price of a building should be equal to the cost of land plus the cost of parking construction. We estimate the marginal values of parking and lot area with spatial methods using a large data set from the Los Angeles area non-residential property sales and find that for most of the property types the marginal value of parking is significantly below that of the parcel area. In addition, we directly examine required and supplied parking and find that on average parking supplied is quite close to the required amount.     

Analysis of the effectiveness of control measures to mitigate road dust emissions in a regional network

The effectiveness of control measures to reduce road dust emissions is analyzed using a year’s data of road dust emissions collected with a mobile sampling platform and a survey of road maintenance practices in the Lake Tahoe Basin of Nevada and California US. Attributes such as sweeping practices, anti-icing, shoulder improvement, pavement condition, trackout, and abrasive material from road segments were analyzed with a feature subset selection algorithm. Street sweeping was found to be an effective means of controlling dust emissions from roads. Road dust from dirty tertiary roads served as a continuous source of suspendable material for adjacent high-speed roads in the winter time. To be most effective, emission control strategies require that not only primary roads, but all roads be swept after snow storms to recover applied abrasive material.     

The cost saving potential of carsharing in a US context

Carsharing is a vehicle sharing service for those with occasional need of private transportation. Transportation planners are beginning to see great potential for carsharing in helping to create a more diversified and sustainable transport system. While it has grown quickly in the US in recent years, it is still far from the level where it can deliver significant aggregate benefits. A key element to the potential growth of carsharing is its ability to provide cost savings to those who adopt it in favor of vehicle ownership. This research seeks to quantify these potential cost savings. The costs of carsharing and vehicle ownership are compared based on actual vehicle usage patterns from a large survey of San Francisco Bay Area residents. The results of this analysis show that a significant minority of Bay Area households own a vehicle with a usage pattern that carsharing could accommodate at a lower cost. Further research is required to indentify how these cost savings translate to the adoption of carsharing.     

Characteristics of premium transit services that affect mode choice

This research seeks to improve the understanding of the full range of determinants for mode choice behavior and to offer practical solutions to practitioners on representing and distinguishing these characteristics in travel demand forecasting models. The principal findings were that the representation of awareness of transit services is significantly different than the underlying assumption of mode choice and forecasting models that there is perfect awareness and consideration of all modes. Furthermore, inclusion of non-traditional transit attributes and attitudes can improve mode choice models and reduce bias constants. Additional methods and analyses are necessary to bring these results into practice. The work is being conducted in two phases. This paper documents the results of Phase I, which included data collection for one case study city (Salt Lake City), research and analysis of non-traditional transit attributes in mode choice models, awareness of transit services, and recommendations for bringing these analyses into practice. Phase II will include data collection for two additional case study cities (Chicago and Charlotte) with minor modifications based on limitations identified in Phase I, additional analyses where Phase I results indicated a need, and a demonstration of the research in practice for at least one case study city.     

Study on dynamic characteristics of vehicle gearbox under multi-boundary conditions

With the development of vehicle gearbox to high-power-density and high-speed, how to predict and optimize the dynamic characteristics of vehicle gearbox becomes increasingly prominent. Aiming at the vehicle gearbox, this paper comprehensively and deeply studies the dynamic characteristics under the multi-boundary conditions. The generation mechanism of the multi-source excitations triggering the gearbox vibration is analyzed firstly. The vibration transfer path of the gearbox is explored. Secondly, the engine excitation, the gear meshing excitation and the bearing support load are numerically calculated. According to the finite element method, a fluid-solid coupling finite element model of the gearbox body is established to predict the gearbox dynamic responses based on the Galerkin method and the Hamiltonian variational principle. Finally, the effects of the excitation condition, oil height and reinforcement forms on the vibration responses of the gearbox body are thoroughly studied by simulation. The analysis indicates that it not only helps to modify and improve the method of forecasting the gearbox dynamic response, and also provides the theoretical and technical guidance for the gearbox design and optimization.     

Target priority determination methods by interval-valued intuitionistic fuzzy sets with unknown attribute weights

The paper aims at the problem of multi-targets threat degree being hard to be evaluated accurately in complex air defense battlefield environments. Combined with multi-sensors information fusion and interval-valued intuitionistic fuzzy sets (IVIFS) theories, the target priority determination is studied. The score and accuracy functions of IVIFS are improved with thinking about the hesitating information in order to increase the rationality. Then, the influence factors of target priority and the nonlinear relationship between the influence factors and target priority are analyzed. Next, the algorithms for calculating the factor weights and sensor weights are given. Based on the theory of IVIFS and technique for order preference by similarity to an ideal solution (TOPSIS), two methods of target priority determination based on the IVIFS and TOPSIS are proposed. At last, an application example verifies the effectiveness and flexibility of the proposed algorithms.