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.     

Analysing Chinese citizens' intentions of outbound travel: a machine learning approach

Due to the tremendous expansion of Chinese outbound travel market, it is of great significance to identify the characteristics of potential Chinese outbound tourists so as to develop targeted marketing strategies. As both extrinsic and intrinsic characteristics of individuals are important in influencing their decision-making process, this study explores potential Chinese outbound tourists from these two aspects. Demographic and psychographic factors, as the proxy of extrinsic and intrinsic characteristics, respectively, are incorporated into this study to construct the relationship between tourists' characteristics and their intentions of outbound travel. An advanced machine learning approach, called twice-learning, is employed for modelling in this study. As an intelligent data analysis tool, this method is able to construct models that can provide insight into the ground-truth relationships hidden beneath the data in an essentially comprehensible way, without being limited by the typical assumptions held by the traditional data analysis methods. By applying this method, the important personal factors that influence Chinese citizens' intentions of outbound travel are detected, and the typical groups of potential Chinese outbound tourists are characterised. The findings would be beneficial for destination marketers to develop marketing strategies on positioning and advertising which are tailored to potential Chinese outbound travel market.     

An examination of recreational divers' underwater behaviour by attitude–behaviour theories

The increasing demand for dive tourism activities has resulted in concerns over scuba divers' incremental impacts on the underwater marine environment. Hence, there is a need to better understand the antecedents of scuba divers' underwater behaviour. This study applied theory of planned behaviour (TPB) and norm activation theory (NAT) of altruistic behaviour in examining the relationship between diving attitude, perceived behavioural control, subjective norms and personal norms (PNs) with responsible underwater behaviour among scuba divers. Using the combination of purposeful and convenience samplings, data were collected from divers (N?=?413) who visited the top five most attractive islands in Malaysia. The results supported the use of TPB as a basis for explaining the underwater behaviour of divers. Among the four constructs examined, attitude and PNs were found to be of paramount importance in influencing pro-environmental behaviour. This study also validated the exploratory dimensions that constitute the measurement constructs for scuba diving attitude and responsible underwater behaviour. Scuba diving stakeholders should emphasise continuous education and an integrated programme of marine conservation to enhance divers' attitude and personal commitment towards pro-environmental behaviour. These are crucial for the sustainability of the scuba diving industry.     

Supply chain leading models of building charging stations: Leaders,subsidy policies,and cost sharing

Consumer willingness to pay for electric vehicles (EVs) is severely limited by their driving range. The expansion of a charging network could alleviate this dilemma. This paper focuses on determining whether the manufacturer or the dealer is more suitable to extend charging network. In scenario 1 (wholesale price is exogenous), M-Investing (the manufacturer invests on charging stations) better facilitates EV adoption at the early stage of EV market. By contrast, D-Investing (the dealer invests on charging stations) better facilitates the EV adoption when the market becomes mature. However, neither of the two investors have an incentive to offer building investment. In scenario 2 (wholesale price is a decision made by the manufacturer), M-Investing is consistently better than D-Investing in terms of facilitating EV adoption. The manufacturer is voluntary even with high building costs. In addition, we address two subsidy policies: producer subsidy and consumer subsidy, to determine which is more effective in facilitating EV adoption in M-Investing and D-Investing, respectively. Moreover, we extend our model by allowing cost sharing between the manufacturer and the dealer. We observe some cases in which the profit and the EV adoption level are improved.     

Emissions and exposure costs of electric versus conventional vehicles: A case study in Texas

The emissions and human exposure impacts of electric vehicle (EV) adoption, especially in comparison to conventional gasoline- or diesel-powered engines, depend on numerous factors including geography, electricity generation, and fuel mix. Results of any analysis also vary depending on the nature of data collected and their level of aggregation by time or location. This paper combines several approaches to develop a robust estimate of these impacts specific to the state of Texas by considering marginal emissions by time of day, as well as location of vehicle and power plant emissions. The authors estimate health and other external costs of operating an EV in the state at approximately $62 per year, compared with an average of $136 for a passenger car powered by gasoline.     

Light-duty electric vehicles in the gulf? Techno-economic assessment and policy implications

We investigate the economic and technological potential for adoption of Electric Vehicles (EVs) in Abu Dhabi through a parametric assessment, a public attitude survey, and a diffusion model. Abu Dhabi, similar to fossil-fuel-rich countries in its region, features a car-dependent society and energy subsidies while being situated in hot, desert environment challenging to EVs. We compare conventional vehicles and EVs in the region accounting for the higher use of air-conditioning (AC) in the actual climatic and driving pattern conditions of Abu Dhabi developing an EV AC consumption penalty model. Average annual AC penalty in fuel consumption over normal testing conditions is 16% for conventional vehicles and 25% for EVs based on hourly weather and vehicle utilization patterns. For 250 days per year, the expected EV range is higher than 75% of the nominal value. During the five hottest days of the recorded year, it can drop to 60% but still covering the average daily driving of the majority of users with a single charge with a 25kWh battery. With partial subsidies offered for both fuel and electricity, EV adoption impacts the state in terms of opportunity costs for these fuels in addition to environmental externalities. We calculate the state and user benefits in a parametric analysis dependent on driving distance and battery costs. If the battery cost is $325/kWh, direct and internalized benefits and costs are balanced when the EV is driven 60 km/day. A diffusion scenario of 5% by 2030 results in cumulative net savings of 6.4 million barrels of oil, a reduction of 517.000 tonnes of CO₂, and a cumulative net benefit of $127 million.     

Attracting tourists to travel companies’ websites: the structural relationship between website brand,personal value,shopping experience,perceived risk and purchase intention

This article aims to examine the structural relationship between website brand, personal value, shopping experience, perceived risk and purchase intention from travel websites. Built upon the theory of consumers’ perceived risk, a theoretical model was proposed and a questionnaire was developed. The fieldwork utilized responses from 409 participants who purchased travel items from websites of Malaysian travel companies. Partial least square (PLS) path modelling approach, a variance-based structural equation modelling (VB-SEM), was used to assess the overall goodness-of-fit tests, measurement and structural model. The results highlight different aspects related to the effectiveness and attractiveness of travel companies’ websites. Its unique finding highlights the importance of personal value as a user characteristic factor that can strongly affect online purchase intention. In addition, by combining user characteristics and website characteristic and examining them in a single model, this study provides a clear multidimensional picture of causal relationship between latent constructs in an online travel purchase context. Theoretical and practical implications of study results are discussed and suggestions for future research are provided.     

Optimizing EV-based P&R subsidy policies for commuting corridor based on cross-nested logit model

The promotion of electric vehicles (EVs) is restricted by cruising range limitation and charging station deficiency. Given the mature development of Park and Ride (P&R) mode, which is used in many cities worldwide to attract more travelers to use public transit, a new travel mode, i.e., EV-based P&R is introduced as an alternative for commuters’ daily travel. This seems quite attractive to expand the use of EVs and further increase their market share. This paper aims to investigate the impact of EV-based P&R introduction on travel mode choice along commuting corridor, and further aid in the optimal subsidy policies decision for the government. A bi-level model is proposed to model the presented problem. The lower level describes commuters’ joint mode and transfer choice behavior through a cross-nested logit (CNL) model, while the upper level minimizes the system cost. A genetic algorithm is developed to solve the formulated model with a partial linearization algorithm for solving the lower level model. And a numerical example is then used to demonstrate the effectiveness of the methodology and illustrate how the network flow pattern reshapes due to the introduction of EVs into the P&R mode and the change of corresponding subsidy policies. As the results show, improving the EV hardware, applying the intelligent supporting service system, developing new technologies for EV fast charging, appropriately improving the parking space capacity, and increasing the parking fee of transfer stations near the central business district (CBD) are all helpful to save the social cost and promote the usage of EVs.     

Interplay between ethanol and electric vehicles as low carbon mobility options for passengers in the municipality of São Paulo

The Brazilian cities as well as many of the large urban centers in the world continue to expand, increasing the demand for mobility and transport, while, at the same time, the same cities are investing in greenhouse gas (GHG) mitigation to avoid climate change. Brazil's urbanization rate increased from 26% in 1940 to almost 70% in 1980. During this period, the Brazilian population tripled and the urban population multiplied by seven. In 2010, the transport sector in São Paulo accounted for 71% of the total emissions released by the energy sector. Ethanol has been considered a fuel with less greenhouse gas emissions, when compared with fossil fuels. However, ethanol production would have to double to meet the expected demand. Electric vehicles (EVs) market is expanding around the world, and is also an option to reduce the transport emissions, if powered by clean electricity. To assess whether the adoption of EVs might bring more benefits than the current ethanol, we develop prospective scenarios supported by the Long-range Energy Alternatives Planning (LEAP) simulation tool, taking a bottom-up tank-to-wheel approach to consider the CO₂ emissions of car in São Paulo. The scenario considering a substitution of 25% of gasoline-powered cars by EV in 2030 showed a reduction in energy consumption and CO₂ emissions, around 15% and 26% respectively in that year in comparison with 2015. We discuss the interplay between ethanol and EV, also considering emission coefficients from life cycle analysis conducted in Brazil, and concluded EV will have higher positive impact on climate change mitigation than ethanol.