Demand for electric vehicles in hybrid households: an exploratory analysis

Previous studies of the potential market for battery electric vehicles (BEVs) from different research streams have failed to converge on a single, robust estimate. What these previous research streams share are untested or implausible assumptions about consumer response to new transportation technology. We frame the BEV purchase decision in terms of a household's entire stock of vehicles, car purchase behavior and travel behavior. Within this framework, households which own both electric vehicles and gasoline vehicles are called ‘hybrid households’. Because nearly all consumers are unfamiliar with the characteristics of BEVs, we designed an interactive interview based on week-long travel diaries, which we call Purchase Intentions and Range Estimation Games (PIREG) to explore hypothetical hybrid household vehicle use. Our primary finding is that consumers' perceived driving range needs are substantially lower than previous hypothetical stated preference studies conclude. We find evidence of a viable market for BEVs with 60 to 100 miles driving range.     

Consumer structure in the emerging market for electric vehicles: Identifying market segments using cluster analysis

This paper presents results from a segmentation analysis of the emerging market for Electric Vehicles (EVs). Data has been sourced through the application of a self-completion household questionnaire distributed over two cities in the United Kingdom (UK). A two stage cluster analysis methodology has been followed to identify market segments in a dataset of UK drivers. Five unique segments have been identified in the analysis and are characterised by their preferences for EVs, socio-economic characteristics, current car details, and psychographic profiles. These segments hold a range of different EV preference levels, from those who appear unwilling to adopt an EV to those which are clearly attracted to EVs. Moreover, the features of these segments suggest that segments might be attracted to or repelled from EVs for different reasons. These results demonstrate that a significant degree of consumer stratification is present in the emerging market for EVs, with the possible implication being that policy interventions at the segment as opposed to market, level may prove more effective due to their ability to cater for the nuances of important segments.     

Exploring the choice of battery electric vehicles in city logistics: A conjoint-based choice analysis

Adoption of electric vehicles by transport companies remains limited although major European cities should reach CO₂-free city logistics by 2030. This paper explores therefore the vehicle choice behaviour of transport companies through a conjoint-based choice analysis.The results showed that the benefits of battery electric vehicles are less valued than their disadvantages. However, a majority of respondents agrees that authorities should encourage the use of battery electric vehicles. Based on the preferences of transporters, we conclude that the most important measures are to develop a larger charging infrastructure and implement financial incentives through subsidies or tax exemption.     

An analysis of differentiation strategies for Galician thermal centres

In the modern tourism industry, competitiveness no longer can be based solely on price; rather, it is necessary to consider other aspects that might generate competitive advantages. In particular, the provision of a wide range of products, services and activities, all of outstanding quality, may be decisive for creating greater demand. Thermal establishments are well aware of these dynamics. Accordingly, this research analyses, using quantitative techniques, whether Galician thermal establishments, including health resorts, spas and thalassotherapy centres, have achieved well-defined differentiation strategies.     

An analysis for the competitive strength of Asian major airports

This paper presents an analysis of the competitive status of major airports in the East Asia region. The analysis assesses these airports based on five factors: service, demand, managerial, facility, and spatial qualities. In order to analyze the competitive status of the selected airports, this study has applied a multi-decision criteria approach and is based on a comparison of qualitative data. The competitive status of each airport can be categorized as one of the following levels: most, more, less, or least competitive.     

Efficiency of public transport for cross-border commuting: An accessibility-based analysis in Central Europe

According to the principles of sustainable mobility, public transport (PT) is becoming a new paradigm to measure the accessibility of a region. This paper analyses PT accessibility for commuters that travel in cross-border areas of Central Europe, a region that has registered a significant growth of transnational movements in the last 20 years. A specific geographic area (i.e. the boundary between Hungary and Austria) is then deepened, according to its territorial and socio-economic peculiarities. Here, the indicators usually adopted in a gravity model (i.e. distance between origins and destinations and their number of inhabitants) do not completely match with the registered movements; rather, the average income and the work opportunities available in the destinations explain the cross-border flows better. Then, a Cross-Border Commuting PT Accessibility based on the Relative Network Efficiency Indicator is made for the main connections and compared with the Domestic Commuting PT Accessibility. This analysis highlights that 1) cross-border accessibility by PT is limited for several rural destinations that have few inhabitants but a non-negligible number of cross-border commuters; 2) the differences in PT attractiveness between domestic and transnational journeys are still very high and are mainly due to long travel times, complex multimodal chains, and unappealing fares. These results suggest the importance of an integrated approach among operators from different territories, which are called upon to bridge the existing technical, coordination and cooperation gaps.     

An analysis of dual-command operations in common warehouse designs

In a warehouse that uses dual-command operations, workers travel loaded from the pickup and deposit (P&D) point first to a location to store a pallet, then to a second location from which they pick a pallet and return to the P&D point. We develop expected travel distance expressions for such operations and use them to analyze three common warehouse designs. Our results indicate that the best of the three is – in our experience – the one least commonly found in practice. We also show that the optimal placement of a “middle cross aisle” in the most common design is, in fact, not in the middle.     

An analysis of demand uncertainty in the hotel market

This study proposes a two-step approach to investigate the impact of certain environmental variables on demand uncertainty within the hotel sector. Adopting a simultaneous-equation model and using the operation data of international tourist hotels in Taiwan, this study shows that chained hotels face less demand uncertainty than independent hotels. Additionally, hotels that are more distant from the airport or located in metropolitan areas face a significantly higher degree of demand uncertainty.     

An Exploratory analysis of flight delay propagation in China

Delay propagation is the flight departure delay caused by the arrival delay of pre-segment flight. Chinese airline market has suffered very poor on-time performance (OTP) in recent years. It is, however, unclear whether delay propagation prevails as one major source for such problem. This study first aims to empirically quantify delay propagation in the Chinese airline market. Specifically, we shed light on heterogenous levels of delay propagations across different airports and airlines. Then, the distinct delay propagation patterns in China are also discussed and compared with other developed airline markets (e.g., the US and Europe). Our estimation is based on OTP data for over 12 million Chinese flights covering the 2015–2017 period. Specifically, it is found that 10 min arrival delay of pre-segment flight within 1 hr before the departure lead to an average of 7.49 mins delay propagation for subsequent departure flight. Arrival delay of earlier pre-segments (1–2 and 2–3 hr before the departure) leads to much less delay propagation, due to longer ground buffer. Chinese airlines arrange longer ground and flight buffer than that of the US airlines to prevent the delay propagation from accumulating along the subsequent flights in a day. Thus, unlike the US market, delay propagation is not the major reason for poor OTP in China. In addition, delay propagation is less prevailing at the Chinese hub airport. This is because China has relied on point-to-point network, which does not require sophisticated schedule coordination. And the local passengers at these Chinese hub airports have higher time value such that the Chinese airlines also try to improve OTP at these hub airports to better serve these lucrative but time-sensitive local passengers. Unlike the European LCCs, Spring Airlines, the largest low-cost carrier (LCC) in China, outperforms major full-service carriers (FSCs) in controlling delay propagation. This finding may also apply to other Northeast Asian LCCs sharing common operational characteristics as Spring Airlines. Last, we find that airlines purposely tolerate moderate departure delays of up to 15 min, which is the threshold that defines delays, no matter whether the pre-segment flight arrives late or on-time. The relevant policy and managerial implications are also discussed.     

An empirical analysis of the optimal overbooking policies for US major airlines

Overbooking in the airline industry has been studied intensively. However, these studies have paid little attention to the future revenue implications of rejecting (bumping) passengers. This paper seeks the optimal overbooking policies for US major airlines by considering how denied-boarding passengers would behave after they are bumped. The results imply that overbooking improves an airline's “current” revenue, but it also reduces the airline's future revenues. The results also imply that, although there is a significant negative overbooking effect, no airline should decrease overbooking levels because the positive side of overbooking is so strong that it more than offsets its negative side.     

An intersectional analysis of barriers to cycling for marginalized communities in a cycling-friendly French City

In French cities like Grenoble, cycling is an increasingly popular form of urban mobility. Yet a lack of disaggregated modal data makes it unclear who does and who does not have access to biking. An intersectional analysis of 19 narrative and semi-structured interviews with policymakers, residents with different identities, and bike service providers demonstrate that some people perceive unique barriers to biking, related to their identities. For example, this study finds that racism, financial precarity, a lack of accessible information about services, and spatial inequalities may prevent some people from biking despite Grenoble's advanced cycling infrastructure and services and that these barriers may compound for certain people, reinforcing the preliminary body of research on intersectional barriers to urban biking. The study further finds that the lack of disaggregated demographic data on urban mobility in France might be preventing inclusive bike policy. The paper concludes by arguing that local policymakers would benefit from applying an intersectional analysis in understanding who is and is not biking, to promote everyday biking in a more inclusive way.     

Pareto efficient allocation of an in-motion wireless charging infrastructure for electric vehicles in a multipath network

Electric vehicles (EV) use an eco-friendly technology that limits the greenhouse gas emissions of the transport sector, but the limited battery capacity and the density of the battery are the major barriers to the widespread adoption of EV. To mitigate this, a good method seems to be the innovative wireless charging technology called ‘On-Line EV (OLEV)’, which is a contactless electric power transfer technology. This EV technology has the potential to charge the vehicle’s battery dynamically while the vehicle is in motion. This system helps to reduce not only the size of the battery but also its cost, and it also contributes to extending the driving range before the EV has to stop. The high cost of this technology requires an optimal location of the infrastructure along the route. For this reason, the objective of this paper is to study the problem of the location of the wireless charging infrastructure in a transport network composed of multiple routes between the origin and the destination. To find a strategic solution to this problem, we first and foremost propose a nonlinear integer programming solution to reach a compromise between the cost of the battery, which is related to its capacity, and the cost of installing the power transmitters, while maintaining the quality of the vehicle’s routing. Second, we adapt the multi-objective particle swarm optimization (MPSO) approach to our problem, as the particles were robust in solving nonlinear optimization problems. Since we have a multi-objective problem with two binary variables, we combine the binary and discrete versions of the particle swarm optimization approach with the multi-objective one. The port of Le Havre is presented as a case study to illustrate the proposed methodology. The results are analyzed and discussed in order to point out the efficiency of our resolution method.     

An analysis of the determinants of air traffic volume for European metropolitan areas

This paper examines the determinants of air traffic volume in the major European urban regions, highlighting those that depend on the metropolitan features of cities. We used homogeneous urban and airline data that make international comparisons possible. We found that GDP, the level of economic decision-power, tourism functions, and the distance from a major air market account for more than two-thirds of the variation in air service. This seems to indicate that air service remains profoundly rooted in the metropolitan features of urban regions (notably size and decision-power), even if low-cost airlines are probably less linked to the latter because they partly focus on niche markets and regional airports. Much of the remainder is probably attributable to the specificities of the urban economy, to actors’ strategies and to competition from high-speed trains.     

Processing passengers efficiently: An analysis of airport processing times for international passengers

With immense and growing pressure on stakeholders in international airport terminals to process passengers faster than previously, there is a great benefit to understanding which factors affect passenger processing times and in which situations. In addition, storing and analysing the collected data in batch is itself a difficult and time consuming task that could be made much simpler with sequential analysis. We aim to present a method for airport managers to discover which variables are important to understanding passenger processing times and identifying problematic passenger profiles without the need for high computational capacity and full historical datasets.In this paper we introduce Bayesian hierarchical models as a method of sequentially processing data, reducing computation time and obviating storage of large amounts of raw data. We use a range of exploratory models to identify which variables are important to predicting passenger processing time using a dataset from a day of operations at an international airport terminal, then compare a range of regression models. A Bayesian hierarchical regression model based on the model of best fit discovered through exploration is then applied to two subsets of data. We demonstrate that sequential updating based on daily data achieves similar results to batch processing based on full historical datasets and can therefore be used as an alternative in appropriate circumstances. Using the presented models, we find that the airline operating a flight is the most important variable to determining passenger processing time, followed by each passenger's age, sex and nationality. We demonstrate that in our dataset, the passenger profiles correlated with higher mean processing times overall were not the same as those passengers most problematic for meeting processing time targets.     

Demand for cargo airships: An analysis of mode choice decision making in the freight transport industry

Despite their potential, cargo airships currently remain a theoretical concept. This research aims to examine the factors determining the demand for their services from the perspective of transport logistics professionals. An online freight mode choice experiment is conducted, supplemented with follow-up semi-structured interviews. Across freight types the sensitivity of the modes (road, rail, sea and airship) to the attributes (price, time, reliability and frequency) varied substantially. Willingness to pay for the cargo airship mode for travel time saved is estimated to be $23/tonne/hour. It is conservatively estimated that the potential market share of cargo airships in the Australian domestic freight market varies across airship models with LMH-1 having the lowest market share of 8% while ARH50 has the largest potential market share at 25%.     

An environment-adjusted dynamic efficiency analysis of international tourist hotels in Taiwan

The paper is the first study to combine four-stage approach and dynamic data envelopment analysis (DEA) to investigate the efficiencies of 45 international tourist hotels in Taiwan during 2002–2011. Using the four-stage approach of Fried et al. [1999. Incorporating the operating environment into a nonparametric measure of technical efficiency. Journal of Productivity Analysis, 12(3), 249–267] and the dynamic DEA model by Tone and Tsutsui [2010. Dynamic DEA: A slacks-based measure approach. Omega, 38(3), 145–156], the study considers the effects of the external operating environments and carry-over activities between two consecutive terms, and calculates managerial efficiency of international tourism hotels in Taiwan. The empirical results show that dynamic DEA provides more stable pure managerial efficiencies than traditional DEA, reflecting the continuity of the links between terms. Then the study employs Tobit regression to estimate the effects of location, management style, and occupancy rate on input slacks. The location in resort area leads to less slacks of employee and room. The chain system helps reduce slacks in room and area of meal department. The slack of employee and room gets lower while occupancy rate gets higher. After controlling the three external environment variables, the efficiency scores of 28 hotels increase, 9 hotels fall, and other 8 hotels still sustain on the efficient frontier.     

Public transport accessibility accounting for level of service and competition for urban opportunities: An equity analysis for education in Santiago de Chile

Several cities around the world have changed their transportation planning paradigm, understanding that the prime goal is to provide access to opportunities for everyone. To address this goal, public transport plays a fundamental role and, therefore, it is key for developing a sustainable and equitable city.This paper proposes a methodology to analyze access to opportunities through public transport incorporating the user's valuation of attributes that impact the level of service on his/her trip and the competitiveness for urban opportunities. Using data from Santiago, Chile, we applied the proposed methodology to analyze accessibility to higher-quality public primary schools. We compare total travel time (TTT) with a proposed measure of total generalized travel time (TGTT) using simple potential and competitive accessibility indicators, accounting for the subjective valuation of walking time, travel time, waiting time, comfort and transfers, and translating them into in-vehicle time units.We find that the inclusion of competition has a more substantial impact than including the subjective valuation of the level of service in the accessibility to educational opportunities. Using competitive measures with TGTT, we found that around 20% of the zones in Santiago have at least a 50% deficit of higher-quality public education, and 71% of them are in peripheral areas. Furthermore, these zones, where medium and low-income population usually lives, can experience, on average, 1–2 transfers, 4–5 passengers per square meter, and 15-min waiting. We conclude that the proposed methodology provides a more comprehensive way to understand accessibility by incorporating the traveling experience, allowing to determine how and where to intervene to effectively improve accessibility, with a focus on urban equity.     

Air travel for private purposes. An analysis of airport access,income and environmental concern in Switzerland

As air travel is considered a relevant area of action to mitigate climate change, it is important to know its determinants. The present study examines socio-demographic, spatial and attitudinal predictors of air travel for private purposes. The analyses are based on the Swiss Environmental Survey 2007 and a subsequent computation of the respondents' environmental impact, as well as spatial data.A lognormal hurdle model indicates that persons with higher environmental concern are less likely to travel by air and if they still do, they travel less. While political orientations do not affect whether a person travels by air, the results indicate that among those who do fly, respondents voting for the Green Party cause lower emissions than those opting for other left or center parties. Furthermore, higher incomes are associated with more air travel whereas living with children is associated with less air travel. Airport access is related to air travel in the sense that living closer to airports, in particular to large ones, is correlated to more air travel. The result is robust to alterations of the accessibility measure and also upholds when population density is controlled for.     

An integrated SWOT based fuzzy AHP and fuzzy MARCOS methodology for digital transformation strategy analysis in airline industry

Driven by business strategies, digital transformation (DT) facilitates dramatic change in air passenger behavior. This study aims to determine and analyze different DT strategies (DTSs) with the help of an integrated SWOT-based fuzzy AHP-MARCOS methodology that is proposed for the first time in the literature for this purpose. This methodology is validated with a case study concerning the airline industry in Turkey. The weights of the SWOT factors are determined with the fuzzy AHP method. The fuzzy MARCOS approach is used to select the most suitable DTS. The most appropriate strategy is obtained as “focusing on differentiated digital customer experience and service quality by the adaptation of business models to DT to provide benefits”.     

An analysis of air mass effects on rail ridership in three US cities

This paper examines whether daily weather affects ridership in urban transportation systems. When examining human–weather relationships, it is often advantageous to examine air masses, which take into account the entire parcel of air over a region. Spatial synoptic classification characterizes air masses based upon numerous meteorological variables at a given location. Thus, rather than examining temperature or precipitation individually, here we compare daily ridership to synoptic air mass classifications for three urban rail systems: Chicago Transit Authority (CTA), Bay Area Rapid Transit (BART), and the Hudson–Bergen light-rail line in northern New Jersey. Air masses are found to have a significant impact on daily rail ridership, with usage typically increasing on dry, comfortable days and decreasing on moist, cool ones, particularly on weekends. Although the comfort of a particular air mass changes throughout the year, seasonality is not a significant factor with respect to the air mass–ridership relationship. The results of this study can benefit rail system managers who must predict daily ridership or in the development of cost-benefit analyses for station improvements.