Demand for environmentally friendly vehicles: A review and new evidence

Although the need for more environmentally friendly vehicles was recognized some decades ago, this new market has not yet established itself. Consumer behavior needs to be studied to ascertain when people will decide to purchase hybrid or electric vehicles rather than conventional ones. An in-depth review of the state-of-the-art has identified existing deficiencies and these are addressed in this paper, proposing a new approach that is applied to the case of Santander in Spain. Emphasis is placed on the role of citizens in researching the local market and their requirements with respect to such vehicles; our model assumes variability in user preferences, an utmost requirement as concluded from the literature review. Results suggest that the highest demand for cleaner vehicles would be achieved in two ways: firstly, by penalizing conventional vehicles in terms of costs/km; secondly, by providing incentives directed at lowering the purchasing price of hybrid and electric vehicles. Finally, as demand becomes more elastic, the preferred strategy should initially focus on hybrid vehicles.     

Modeling green vehicle adoption: An integrated approach for policy evaluation

This article employs an integrated discrete-continuous car ownership model to jointly forecast households’ future preferences on vehicle type, quantity and use, and to estimate greenhouse gas (GHG) emissions. The model system is estimated on a dataset collected from a web-based stated preference survey conducted in Maryland in 2014. The data contain vehicle purchase decisions and sociodemographic information of 456 households who were requested to state their future preferences over a 9-year period (2014–2022). In each time period, a respondent is faced to four alternatives that include the current vehicle, a new gasoline vehicle, a new hybrid electric vehicle, and a new battery electric vehicle. Intertemporal choices between conventional and “green” vehicles such as hybrid and electric cars capture dynamics in vehicle purchase decisions. Short run and medium-long run situations were predicted and compared based on the first 4-year data and the entire 9-year data of the dynamic panel. Vehicle GHG emissions were calculated correspondingly. We find the introduction of “green” vehicles makes a positive impact on car ownership and use, especially in a medium-long run. Two “green” taxation policies, gasoline tax and ownership tax, were proposed and their impact on vehicle use and emission reductions was evaluated. Results indicate that: (a) gasoline tax is a more effective way to reduce vehicle miles traveled and GHG emissions and (b) gasoline tax makes a higher impact on car use and emission reductions in the medium-long run, while ownership tax makes a higher impact in the short run.     

Households transport-home energy conservation strategies in response to energy price policies: A stated adaptation experiment based on portfolio choices and cross effects designs

This article explores consumer investment choice in long-term energy conservation technology and assesses trade-offs in energy saving behaviour between the housing and transportation domains. The long-term energy conservation choice problem is conceptualized as a portfolio choice problem. Consequently, to measure trade-offs between investments in housing and transport options, a cross effects choice design is developed in which respondents were shown one or more alternate ways to reduce their current energy consumption: (1) investing in new technology in the house, such as solar panels; (2) exchanging the current car for a more energy efficient car; (3) buying a new energy-efficient car, such as EV or solar car; (4) moving house to reduce current travel distances. To help respondents linking these options to their current energy consumption, a new Web-based survey system (SINA) to implement and administer stated adaptation experiments was developed. The system was used to collect two sets of data. First, data about out-of-home and in-home energy consumption, together with detailed time use data, was collected. Second, using a cross effects design, respondents were asked to select a portfolio of energy-saving strategies in response to different energy pricing policy scenarios. Results reported in this paper are based on 572 respondents who completed the survey and responded to seven adaptation questions based on their current energy expenditures. A random parameters logit model is estimated to predict the probability of choosing a particular portfolio of energy-saving options. Estimation results indicate that individuals from different socio-demographic groups exhibit varied preferences. The saving option characteristics, especially cost related characteristics have significant effects on individuals' preferences. Moreover, the results also showed significant effects of choice set composition on energy saving options. Further, the energy pricing policies had showed mixed effects on individual's preferences.     

A study on passengers' airport choice behavior using hybrid choice model: A case study of Seoul metropolitan area,South Korea

Improving explanatory power is significantly important to understand variables that affect attitudes and perceptions in the decision process. This paper estimates not only tangible attributes but also intangible perceptions and attitudes using a hybrid-choice model to study air passengers' flight choice behavior. The empirical study was conducted for the choice behavior of air passengers at Seoul Metropolitan Area, South Korea. The analysis uses a two-level Nested Logit model in order to examine which factors have more effect on passengers’ choice of airport and airline simultaneously by using airport and airline choice attributes. The study also estimated the parameters in the equations relating the latent variable by using Structural Equation Model (SEM). The results indicate that the models with latent variables have improved Goodness-of-Fit when compared to classical discrete choice models and effectively capture psychological factors that affect choice behavior of passengers.     

An examination of the factors that impact upon multiple vehicle ownership: The case of Dublin, Ireland

This paper examines the characteristics of households with multiple car ownership in Dublin, Ireland. Data from the 2006 Census of Ireland are analysed to ascertain the characteristics of these households. The analysis of multiple car ownership presented herein examines individual specific, transport availability, and household characteristics to provide an indication of the individuals most likely to have access to more than one vehicle. Understanding the characteristics of households with more than one car is important for many reasons, such as how policies for emissions reductions or pricing regimes might affect households. Ireland, like many countries, has recently launched a number of electric vehicle and car sharing schemes. Traditionally these schemes have been aimed at reducing multiple car ownership, therefore it is important to develop an understanding of the households that would most likely give up an extra car and use a car sharing scheme or an electric vehicle. Also from a sustainability point of view, greater levels of car ownership can result in unsustainable transport patterns.This paper examines the Census data using a multinomial logit regression model to determine the relationships between multiple car ownership levels and several household characteristics. The findings of the paper demonstrate that occupation, public transport availability and residential density all have an impact upon the decision to own more than one vehicle.     

A study on travelers' transport mode choice behavior using the mixed logit model: A case study of the Seoul-Jeju route

This study is to analyze passengers' choice of the mode of transportation when air transportation is in competition with high speed rail (HSR). The Seoul-Jeju route analyzed as an empirical case study, in which the construction of an undersea tunnel to connect Seoul and Jeju city by HSR has been considered. The study also included two new variables, ‘safety of transportation’ and ‘availability of duty free shopping’ in addition to traditional transport choice variables such as travel time, travel costs and frequency of service to reflect special characteristics of the market. As data gathering tools, SP techniques and mixed logit model, for analytical methodology, were utilized. The authors found that the goodness of fit of the models was improved with new variables. The models also showed that the characteristics of business passengers and leisure passengers in choosing the mode of transportation were different. Business passengers were apt to choose a safety secured mode of transportation regardless of fare while leisure passengers preferred to use duty free shops more than business passengers.     

The influence of green practices on supply chain performance: A case study approach

The main objective of this exploratory paper is to investigate the relationships between green practices of supply chain management and supply chain performance. This relationship is investigated in the context of the automotive industry. Five research propositions are suggested and tested with empirical data derived from five case studies taken from the Portuguese automotive supply chain. The data analysis identifies the most important green practices considered by managers, as well as the performance measures that are most appropriate and most widely used as means to evaluate the influence of green practices on supply chain performance. A conceptual model was derived from the data analysis and it can be used to assess the influence of green practices on supply chain performance. This model provides evidence as to which green practices have positive effects on quality, customer satisfaction and efficiency. It also identifies the practices which have negative effects on supply chain performance.     

Frequency and aircraft size dynamics in a concentrated growth market: The case of the Chinese domestic market

Despite the explosive growth of the Chinese aviation sector and the major industry reforms undertaken in recent decades, the Chinese domestic market remains highly concentrated with a significant element of regulation and governmental control in areas such as market entry and airline fleet planning. In this study, we investigate the frequency strategies and aircraft choices of airlines operating in this concentrated growth market. Our empirical investigation suggests that airlines mainly accommodate rapid traffic growth by flying more frequently, although increased aircraft size also contributes to market expansion. We also find a negative relationship between market concentration and flight frequency. Due to the more balanced market structure resulting from mergers among leading airlines since 2002, there has been a moderate reduction in market concentration at route level, contributing to a 3.7% increase in traffic volume from 2002 to 2008. The results of our study suggest that Chinese travelers have yet to fully enjoy the benefits of market liberalization, and airports should prioritize increasing capacity related to aircraft movements over the accommodation of larger aircraft.     

Analysis of the effect of charging infrastructure design on electric taxi driving profiles: A case study approach on the example of Singapore

Replacing conventional vehicle taxis with electric vehicles would be an efficient measure to reduce greenhouse gas emissions. Due to the limited range and long charging times of current battery electric vehicles, it is of utmost importance to provide sufficient charging facilities. This article analyses the impact of the placement and charging power of charging stations on potential mileage and revenue of electric taxis on the example of Singapore. Therefore, we developed an agent-based electric taxi simulation model to investigate electric taxis’ driving profiles with respect to different vehicle types and charging infrastructure designs. This model is also capable of simulating conventional taxi driving profiles. The validation of these simulation results with real taxi data showed that the model is reproducing taxi driving profiles with high accuracy in great detail. We found out that electric taxis could reach the same mileage and revenue as conventional taxis if charging with a power of 160?kW is possible. Furthermore, we discovered that waiting times for available charging stations have a stronger effect on revenue than the length of detours to reach charging stations. Based on these findings, we concluded that it is more important to reduce waiting times by placing sufficient numbers of charging stations at each location before expanding the charging network by installing small numbers of charging stations at many locations.     

Planning in feasible region by two-stage target-setting DEA methods: An application in green supply chain management of public transportation service providers

To meet green supply chain management’s requirements of a company and its transportation service providers (TSPs), it is essential to set clear, achievable, and realistic targets. This paper proposes two data envelopment analysis (DEA) approaches to find targets for two-stage network structures. The objective of proposed approaches is to plan in feasible region. The feasible region specifies bounds to ensure targets are within current operational capacity of TSPs. Applying the approaches to set targets for 24 TSPs lead to different results. However, proposed models ensure that the TSPs would be efficient in their current capacity.