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Will subsidies drive electric vehicle adoption? Measuring consumer preferences in the U.S. and China
... Therefore, it is equally important to include the effect of such variables on user benefit estimation for better policy formulation. Different types of electric vehicles such as battery electric vehicles (BEVs), plug-in hybrid electric vehicles (PHEVs), and hybrid electric vehicles (HEVs) have been investigated by past researchers to understand consumer preferences for the attributes of electric vehicles [12][13][14]. For a typical Indian context, the present investigation is carried out with reference to plug-in hybrid electric vehicle (PHEV). ...
... respectively). Helveston et al. [13] conducted stated choice experiment to analyze consumer preferences for HEVs, PHEVs, and BEVs in U.S. and China. The results of ML model estimates show that US consumers have substantially lower relative preference towards BEVs, and are willing to pay less for acceleration, operating cost, and fast charging capability for both BEVs and PHEVs as compared to Chinese consumers. ...
... Hence, it could be inferred that further reduction in fuel cost would eventually attract commuters with higher education to purchase PHEV in Indian context. The findings of heterogeneity with respect to income and education are in line with Helveston et al. [13], where Chinese respondents who have higher income and higher education were found to be more sensitive to fuel cost saving than those who have low income and are less educated. In Model ML5, the average commuting trip length was also found to substantially influence WTP estimates for fuel cost reduction. ...
The present study investigates commuters’ willingness-to-pay (WTP) for the attributes of plug-in hybrid electric vehicle (PHEV) in a typical Indian context. A stated preference discrete choice experiment was designed to collect choice responses from potential users of PHEV in Kolkata, India. The collected data were analyzed by developing multinomial logit (MNL) and mixed logit (ML) models to estimate overall commuters’ WTP for a set of key attributes of PHEV namely purchase price, fuel cost reduction, battery range, public charging station, battery recharging time, battery warranty and tailpipe emission. Additionally, in ML model, heterogeneity around the mean of random parameters with respect to sociodemographic characteristics such as age, monthly family income, car ownership, home-based parking facility and education, and trip characteristics such as average commuting trip length were examined, and WTP estimates were evaluated for different population sub-groups. The model estimation results indicate that ML models are overall statistically superior and represent the data better than MNL model. The results also highlight that the high purchase price of PHEV as compared to conventional vehicle (CV) could be one of the major deterrents towards the purchase of PHEV in Indian context. The WTP estimates indicate that commuters perceive battery warranty as the major determinant influencing the choice of PHEV followed by battery recharging time and tailpipe emission. The potential users’ income, availability of home-based parking facility, education, and average commuting trip length also substantially influenced their WTP for several attributes of PHEV in Indian context.
... Regarding body type, while some studies have excluded it from their SP analysis (e.g. Helveston et al., 2015), some have considered detailed categorisation including pick-up trucks or luxury sedans (e.g. Higgins et al., 2017). ...
... Unlike previous papers where regular recharge time is studied, we consider fast recharge capacity. This technology allows full battery charge in around 15 min (Helveston et al., 2015). ...
... Different methods are used to capture the taste heterogeneity, including using a mixed logit formulation with random parameters (e.g. Helveston et al., 2015), latent class choice methods (e.g. Ghasri and Vij, 2021), and defining interactive terms to explain the heterogeneity based on demographic attributes (e.g. ...
Cities globally are moving toward electrified public and private transport. Metropolitan areas are now seeking ways to mitigate emission and are heading towards sustainable ways of using clean/ green energy sources by integrating and implementing new technology and science innovations into the transport systems. This study explores consumer preferences for installing photovoltaic solar cells on electric vehicles. In this paper, we have applied a double hurdle model to account for the low market penetration of electric cars in Australia and dealt with the high non-purchase choice. Data are obtained from nearly 1,900 individuals from eight major cities in Australia to explore consumer preferences regarding electric vehicles with photovoltaic solar cells option. The proposed model specification accounts for the panel impact generated from multiple tasks for each respondent, and the correlation between the two decisions on electric vehicle purchase and selecting the photovoltaic add-on. Furthermore, the systematic taste heterogeneity towards price variables is considered by introducing interactive sociodemographic terms to the utility functions. This study provides insights into the willingness-to-pay values for different features of electric vehicles and the solar panel add-on. The results show on average consumers are willing to pay a premium of $18.13 on purchase price for every daily additional kilometre in driving range generated by solar panels. The average willingness to pay for the solar panel to match the colour of vehicle is $1,021.09 for women, and $1,803.92 for men. This study informs policymakers and industries about the feasibility of such an emerging technology.
... The stated choice experiment has been widely used for estimating market share in various disciplines due to its ability to simplify and summarize the choices made by individuals into a clear reflection of the behavior of a society [12]. The stated choice experiment has been used in many studies that aim to predict electric mobility market share or adoption [13][14][15][16][17]. However, the findings vary among geographical locations. ...
... Musti and Kockelman [22] defines operational cost as cost per 100 km, Mabit and Fosgerau [38] defines operational cost as the combination of energy cost or fuelsaving cost and Hess et al. [16] includes routine maintenance cost while excluding energy cost in the operational cost. As expected, a considerable amount of these studies [14,[34][35][36][37] suggest that the lower operational cost for EV compared to conventional vehicles is a key factor that drives EV adoption. ...
... While the gap between EV and ICE purchase costs is getting narrow, driven by the technological advancement of batteries [57], subsidy for EV purchase can be critical in the short term. Countries such as the US [14,56], India [60], Norway [61] or China [59,62] have been experiencing a surge in EV use after implementing this policy. With the current EV tax subsidy scheme in Indonesia, there is room for a more aggressive limited-time subsidy to be closely reviewed and assessed in consideration of any decrease in EV vehicle cost. ...
The Bali Government has made the implementation of the electric vehicle (EV) policy a high priority considering its attractiveness for emission and air pollution reduction to maintain the sustainability of Bali’s nature and tourism sector. Considering the uniqueness of the tourism sector in Bali and the mobility it generates, this study aims to investigate the factors that influence EV use by tourists based on several scenarios for estimating EV share target and the emission reduction contributed. For those purposes, the stated choice questionnaire was distributed online and offline to tourists in Bali and analyzed using the multinomial logit (MNL) model. While the study done during pandemic times, where the number of the tourist is significantly decreasing and the travel behavior influenced by mobility restriction imposed by the government, the data collection still covered mobility of both international and domestic tourist. The survey found that rental cost and accessibility, as well as the quality of charging stations are factors that affect EV use by tourists. Motorcycle parking cost was also found to influence EV use. These findings align with previous studies, and interventions such as fiscal incentives for rental companies and infrastructure development are suggested similar to EV incentives implemented in China, India, or the US. The development of the low emission zone (LEZ) is also proposed to manage parking fares similar to what was implemented in London, specifically to push the shift from internal combustion engine (ICE) to EV. Based on emission inventory calculation, 1.9 million kg of potential annual CO2 can be prevented with the implementation of these policies by the government.
... This article is dedicated to identifying the factors that influence the sales of EVs and the huge gap between the sales of EVs in FST cities and TFT cities. tention for EVs was limited to consumers in metropolises, provincial capitals, or pilot cities, such as Beijing, Shanghai, Guangzhou, Shenzhen, and Tianjin [17][18][19]. Helveston et al. [20]) conducted a comparative analysis of adoption intentions in Beijing, Shanghai, Shenzhen, Chengdu, and American cities; however, the existing studies still have some deficiencies. First, the factors influencing the adoption intention of EVs in TFT cities have not yet been well explored. ...
... Previous research on the adoption intention for EVs was limited to consumers in metropolises, provincial capitals, or pilot cities, such as Beijing, Shanghai, Guangzhou, Shenzhen, and Tianjin [17][18][19]. Helveston et al. [20]) conducted a comparative analysis of adoption intentions in Beijing, Shanghai, Shenzhen, Chengdu, and American cities; however, the existing studies still have some deficiencies. First, the factors influencing the adoption intention of EVs in TFT cities have not yet been well explored. ...
... Huang and Ge [16] suggested that in Beijing the attitude, perceived behavior control, cognitive state, product concern, and monetary incentive policy had positive effects on the adoption intention for EVs, and subjective norms and non-monetary incentive policy had insignificant effects. Helveston et al. [20] used the data from Beijing, Shanghai, Shenzhen, and Chengdu, to compare the adoption intention for EVs in these cities with the United States. Xiong et al. [38] found that the acquisition subsidy was most effective in cities with a low consumption ability, whereas the acquisition tax relief was most effective in cities with a medium consumption capacity, but was not effective in cities with a high and low consumption capacity. ...
The popularization of electric vehicles (EVs) is beneficial to the sustainable development of energy and the environment. China’s promotion and development strategy for EVs will serve as a model for other countries. EV ownership has a significant difference between first/second-tier (FST) cities and third/fourth-tier (TFT) cities and there is a huge growth potential for the EV market in those TFT cities. This paper aims to explore the factors influencing the adoption intentions for EVs in FST and TFT cities under a subsidy deduction and to make a comparative analysis of their regional heterogeneity. Based on the extended theory of planned behavior (TPB) model, the structural equation model is used to compare the factors affecting the adoption intention for EVs of 858 respondents in China. The results show that attitude, subjective norms, novelty seeking, non-financial incentive, product cognition, and environmental concerns are positively related to intention in FST and TFT cities; however, infrastructure development only has a positive significant impact in the TFT cities. Additionally, the subsidy deduction has a more negative impact on the adoption intentions in FST cities. Our findings provide vital insights for formulating government regulations and marketing strategies depending on the diverse sizes and attributes of Chinese cities.
... Following past work on willingness to pay estimation (see, e.g. Brownstone & Train, 1998;Brownstone et al., 2000;Daziano et al., 2017;Helveston et al., 2015;Kolarova et al., 2019), the VTTS, which is a measure of willingness to pay (Hensher et al., 2005), was estimated with the use of mixed logit (random parameter) models. These models can account for the influence of unobserved heterogeneity by estimating different parameters across observations, according to some predicted distribution (McFadden & Train, 2000;Washington et al., 2011). ...
... For respondents who answered that the driving range of an EV is a very or extremely important factor, the likelihood that they would drive on ERs as soon as they are available was high, since range anxiety is considered an essential barrier for adopting electro-mobility (Carley et al., 2013;Chorus et al., 2013;Diamond, 2009;Hackbarth & Madlener, 2013;Helveston et al., 2015;Hidrue et al., 2011;Higueras-Castillo et al., 2021;Junquera et al., 2016;Valeri & Danielis, 2015;Wilmink, 2015), and ERs are perceived to overcome this barrier. Similar interpretations can be given to the results for the other variables that are included in the shortterm intention model and relate to opinions about EVs, such as: charging time (Bockarjova et al., 2014;Carley et al., 2013;Chorus et al., 2013;Junquera et al., 2016), financial incentives and rebates (Abotalebi et al., 2019;Gallagher & Muehlegger, 2011;Glerum et al., 2014;Hoen & Koetse, 2014;Potoglou & Kanaroglou, 2007;Sovacool et al., 2019;Tran et al., 2013), and operational cost (Hackbarth & Madlener, 2013;Molin et al., 2012;Musti & Kockelman, 2011;Rasouli & Timmermans, 2016). ...
Dynamic charging has the potential to overcome the barriers to electric vehicle (EV) adoption by converting road segments into powered lanes (electric roadways or ERs). This paper focuses on examining public acceptance by determining the factors that affect the short-term and long-term intention to purchase an EV and drive on ERs; identifying the clusters of the technology acceptance; and assessing the value of travel time savings (VTTS) for driving on ERs, in general, and for different clusters. A survey was conducted in Los Angeles, California and distributed online, gathering 600 responses. The results showed that respondents’ innovativeness, lifestyle and environmental consciousness significantly affect the intention to drive on ERs in the short- and long-run. Public acceptance, in general, seems to be related to charging patterns, safety of commute route, and safety concerns for ERs, among other factors, and depends on the implementation time of the technology. Higher VTTS were found for electrified lanes exclusive for EVs on interstate and arterial roads. People who were classified as positive toward ERs had higher VTTS for ERs followed by those who were neutral and those who were concerned about ERs. This paper can help policymakers and transport operators devise strategies to accelerate EV adoption by appropriately implementing the ER technology.
... However, Jensen et al. (2013), argued that the adverse impact of limited range on customer intentions might be anticipated by their imprecise perceptions toward BEVs. The government policies, preferential tax, free parking, financial subsidies, and driving privileges were shown as factors that positively influence BEVs adoption (Hackbarth & Madlener, 2016;Helveston et al., 2015;Zhang et al., 2011). Burgess et al. (2013) found the practical experience as an essential factor in transforming the consumers' skepticism to a positive attitude toward acceptance. ...
... Concern, appearance, Facilitating Condition, range, price value, charging time, car for the environment, innovation, independence on fossil fuel Plug-In Electric Vehicles Dumortier et al. (2015) Driving range, Battery costs Electric Vehicles Egbue and Long (2012) Technological level, driving range, environment effect, safety, charging infrastructure Electric Vehicles Gallagher and Muehlegger (2011) Governmental tax incentives, Environmental Concern, fuel prices Hybrid Vehicles Cost minimization, vehicle adaptation demands, vehicle confidence, environmental Concern, impression management, and awareness of electric cars Hydrogen Fuel Cell Vehicles (HFCV) Hackbarth and Madlener (2013) Fuel economy, driving range, charging infrastructure, emission reduction Electric Vehicles Hackbarth and Madlener (2016) Charging time, driving range, charging infrastructure, environmental effect, fuel cost, government policy Electric Vehicles Helveston et al. (2015) Subsidy policies, battery range J o u r n a l P r e -p r o o f Ko and Hahn (2013) Policy incentives, charging infrastructure, swappable battery Electric Vehicles Klockner (2013) The consciousness of need, perceived behavioral control, accountability, planning ability, personal norms, attitudes, intentions awareness Full Electric Vehicles Klockner et al. (2014) Ascription of responsibility, awareness of need, social influence, descriptive norm, interjected norm, personal norm (Innovativeness), perceived behavioral control, awareness of consequences, attitude, intention Full Electric Vehicles Lai et al. (2015) Economic benefits, high energy efficiency, policy, cheap electricity In Malaysia, transportation is the main sector identified to produce carbon dioxide emissions (Sundram, Hashim, Shariff, Pujiati & Ardiansari, 2021). By estimation, the amount of carbon dioxide produced in 2020, was more than 60 percent upsurge compared to the year 2000 (Nurgazina, Ullah, Ali, Koondhar & Lu, 2021). ...
Electric cars are relatively in the early stage of acceptance in Malaysia, the purpose of the current research was to determine the factors affecting the adoption of battery electric vehicles in Kuala Lumpur, Malaysia. This research utilized a quantitative method to gather and analyze the data and proposed a novel theoretical framework to explain the acceptance of battery electric vehicles. 500 surveys were distributed and 322 were gathered. Respondents of the study were University lecturers, postgraduate students, and employees in private companies. The results of SEM analysis indicated that the developed model provides a good fit for constructs used for this research. The result showed that social influence, facilitating conditions, environmental concern, and perceived enjoyment have positive effects on the adoption of BEVs. However, respondents indicated anxiety about the battery range. In conclusion, this study has contributed additional variables such as range anxiety and driving experience to the electric vehicle's acceptance literature. The findings are significant to electric car producers and policy makers who have environmental concerns to understand consumer prospective in this field.
... Their estimated results show that younger males and environmentally conscious potential car buyers have a higher preference for HFCVs and BEVs. Other studies have concentrated on the diffusion of the AFV market by investigating the impacts of consumer preferences and explaining the impacts of sociodemographic and economic variables [21][22][23]. ...
... It examined the direct and moderating effects of policy mix characteristics on EV purchase intention using the proposed TPB model [27]. Further, ref. [21] examined whether subsidies influenced the purchase of electric vehicles in the US and China. This study revealed that Chinese respondents have a significantly higher willingness to pay for BEV technology than US respondents. ...
This study analyzes consumer preferences in South Korea for alternative fuel vehicles (AFVs), including battery electric vehicles (BEVs) and hydrogen fuel cell vehicles (HFCVs), instead of conventional fuel vehicles. A survey targeting 1500 potential car buyers in three years was conducted wherein the subjects stated their preferences depending on the varying conditions of AFV attributes and charger accessibility. Cluster-based multinomial logit and mixed logit models were developed to identify influential factors affecting consumer preferences. The models incorporated the sociodemographic characteristics of users, attitudinal perceptions, and vehicle attributes to capture their interactive impacts. The results of the estimated models suggest that a reduction in purchase price can substantially boost AFV sales, particularly those of HFCVs, with a direct elasticity of 1.78. Additionally, the models demonstrated that attitudinal perceptions, such as perceived environmental and economic benefits are significant factors. Moreover, potential car buyers who plan to buy one vehicle within one year showed the least preference for purchasing BEVs, indicating the importance of technology maturity in the BEV market. These findings can provide reasonable guidelines for establishing marketing strategies and stronger support to achieve the targeted market penetration of AFVs in a city or country.
... This is an important way to achieve carbon neutrality and establish a green economic system. To accelerate the establishment of the recycling system, most governments encourage resource recycling through various subsidies [2][3][4][5][6]. For example, China encourages step-by-step recycling of electric vehicle batteries and has established waste sorting and recycling systems in major cities [7][8][9]. ...
... Scholars have studied the impact of subsidies on the supply chain of different channels and the impact of different subsidy models on recycling channels [2][3][4][5][6]. However, scholars rarely study the impact of subsidy models based on recycling propaganda on recycling channels. ...
The recycling of waste products is an important way to achieve global sustainable development. To analyze the impact of different objects of government subsidies on single-channel recycling based on recycling propaganda, four theory game models of single-channel recycling based on government subsidies and recycling propaganda are established. By comparing and analyzing the effects of different subsidies and propaganda strategies on the recycling of waste products in the four models, this article mainly draws the following conclusions: the government selecting different objects to subsidize has the same effect on the unit recycling price, quantity, and revenue of waste products; when the government subsidizes the processors, the consigned recycling price of waste products will increase, but when the government subsidizes recyclers, it will decrease; when the propagandist is determined, the optimal value of propaganda is related to the sensitivity of residents to the unit recycling price of waste products, the unit propaganda of waste products, and the expenses of propagating waste products.
... This will lead to the shortening of the service life of charging piles, and the slow or even negative growth of the number of charging piles. The demand for EVs will incentivize further technological development by automobile manufacturing enterprises, which was also the conclusion of Helveston et al. (2015). In the pursuit of maximum profits, enterprises will make adjustments to their production based on the changes in market demand. ...
... Identifying the tensions among consumer preferences, government incentives, and social welfare can help to solve the problems in the implementation of specific policies (Helveston et al. 2015). The key factor influencing consumers' willingness to drive GVs or EVs is not the cost of vehicle purchase (Habich-Sobiegalla et al. 2019). ...
In recent years, various countries have put forward Banning Gasoline Vehicle Sales Policy (BGVSP), and the degree of public support for BGVSP is crucial to its design and implementation. Taking China as an example, this study built a policy support index using network crawler technology and natural language processing technology. Then, multi-spatial convergence cross-mapping technology was used to study the interaction between public support and air pollution, electric vehicle (EV) infrastructure, EV technology, and use cost. The results showed that air pollution has a significant impact on public support; public support has a significant impact on the construction of the EV infrastructure and the level of EV technological research, and the use cost of traditional gasoline vehicles has a significant impact on public support. This study investigated the correlations between public support and the factors influencing public support, and the results can be used as a reference for the design and implementation of BGVSP in newly industrialized countries.
... Policymakers in different nations are sensitive to the formulation of policies that aim towards the speedy and easy adoption of BEVs (Brady and O'Mahony, 2011;DeShazo, 2015;Zhou et al., 2015). Several studies conducted in different parts of the world point to the positive effects of offering 'incentives' on BEV inclusion (Helveston et al., 2015;Lieven et al., 2011;Lin et al., 2012;Yang et al., 2019;Zhang et al., 2011). For example, Lieven et al. (2011) conducted a study on incentives (financial and non-financial) in 20 countries and concluded that BEV customers showed preferences for financial incentives. ...
Although necessary, there are a large number of complex factors involved in making mass adoption of Battery Electric Vehicles in a developing country like India, a reality. This qualitative study encompasses exploration of the drivers for, barriers to, and support mechanisms involved in making this transition successful. 41 in-depth interviews across multiple stakeholders such as automobile manufacturers, suppliers, academicians & consultants, BEV owners, potential customers, and government officials were conducted. Inclination of the government towards investment in R&D and offering financial & non-financial benefits were identified as major drivers. Poor infrastructure and prevalent product related technical issues, high cost of manufacturing due to raw material imports in the country, and insufficient legislative support around incentives offered to customers came up as major barriers. Impactful awareness and promotional campaigns by govt and industry, increased collaboration between industry and academia, continuous testing and improvisation of vehicular performance could serve as support mechanisms.
... The researchers in the previous studies used several methods for motivation, such as the agent-based model [47], cohort estimation for vehicle survival [48], time series models, and the consumer choice model [49][50][51][52]. Consumer survey-based choice modeling is often used to understand the primary factors influencing and motivating consumer choices, price, comfort, fuel consumption, safety, reliability, and brand name [53]. ...
The transport sector is the leading source of growing greenhouse gas (GHG) emissions globally. To consider environmental degradation aspects due to transport, electric vehicles (EVs) have the prospect to lead road transport to electric mobility from conventional petroleum vehicles. Despite various eco-friendly benefits, the EV market penetration ratio is very low, especially in developing countries. The primary reason for low penetration is consumer limited motivation and knowledge about the EVs features. This paper uses a unified theory of acceptance and technology (UTAUT) model to assess consumer motivation and environmental knowledge towards EVs. This research used convenience random sampling to collect data and analyzed the results using the Partial Least Squares (PLS) method on the example of 199 respondents from Malaysia. The study results revealed that factors identified in the motivational context significantly influence consumer intentions to purchase EVs. Perceived environmental knowledge and technophilia have been included in UTAUT from a motivational perspective. Furthermore, a significant relationship between effort expectancy, social influence, technophilia, perceived environmental knowledge, and purchase intention towards electric vehicles has been observed, without performance expectancy. The study findings serve to inform policymakers and automakers to formulate effective marketing strategies to enhance consumer motivation, knowledge, and value creation for EVs in a sustainable era. Ultimately, the policies will help to encourage consumers to buy eco-friendly vehicles that will help reduce transport carbon emissions and attain sustainable development goals (SDGs).
... Past literature vindicates that vehicle ownership represents individuals' social status among their peers (Helveston et al., 2015) and has a direct impact on their travel behavior (Nielsen & Haustein, 2018;Zmud et al., 2016). The literature also highlights the link between the information received from individuals' social networks (Cheung et al., 2014;Venkatesh et al., 2003;X. ...
Connected and autonomous vehicles (CAVs) have the potential to revolutionize the daily travel modes, in terms of personal, public, or shared mobility, because of their potential of technology-assisted driving and hence minimizing errors caused by humans. In addition to safety, CAVs will provide additional benefits in terms of ability to multitask during travel, flexibility in travel (relocating the house to farther and more convenient location), reduced parking and running costs, travel time savings due to the reduction in congestion and accessibility to elder and non-license holder individuals. However, such benefits will also come at the cost of numerous anticipated barriers like accident liabilities, data safety concerns, the addition of new infrastructure, and increased emissions because of the increase in vehicle miles traveled. In the US, 22 states including Tennessee have already passed legislation for operating CAVs on public roads. However, until the CAVs meet the perceptions, demands, beliefs, and needs of end-users at a justified cost, their adoption is uncertain. Adoption research from non-transportation-related innovation suggests that social network plays a pivotal role in deciding whether to adopt, defer, or not to adopt. The objective of this research is to understand, model, and predict CAV market penetration in Tennessee over time based on residents' social networks.
... The review also indicates that the majority of the existing researches have aimed at understanding the potential demand of electric vehicles in developed countries such as in US (Hidrue et al., 2011;Musti & Kockelman, 2011;Hess et al., 2012;Guerra & Daziano, 2020), Canada (Ewing & Sarigöllü, 2000;Potoglou & Kanaroglou, 2007;Ferguson et al., 2018), Norway (Dagsvik et al., 2002), Belgium (Lebeau et al., 2012), Germany (Achtnicht, 2012;Hackbarth & Madlener, 2013;Rommel & Sagebiel, 2021;Ziegler, 2012), Netherlands (Hoen & Koetse, 2014), South Korea (Ahn et al., 2008;Byun et al., 2018;Jung et al., 2021), Japan (Ito et al., 2013), Italy Giansoldati et al., 2020), Spain (Rahmani & Loureiro, 2019), Australia (Gong et al., 2020) and countries where electric vehicles are already a popular alternative mode such as China (Li et al., 2020;Nie et al., 2018;Qian et al., 2019). Several studies also conducted a cross-country comparative study on the potential demand for electric vehicles such as between US and Canada (Axsen et al., 2009), US and Japan (Tanaka et al., 2014), and US and China (Helveston et al., 2015). However, it was found that there is a lack of research efforts on estimating consumers' WTP for the attributes related to electric vehicles in general and PHEV in specific in developing countries such as India. ...
This paper reports an investigation to assess consumer preferences towards Plug-in Hybrid Electric Vehicle (PHEV) in a typical Indian context. A stated preference survey was designed to collect choice responses from current owners of conventional vehicles (CVs) in two Indian megacities namely Delhi and Kolkata. The data collected from the two cities were analyzed in two stages by developing Mixed Logit (ML) models. In the first stage, consumers’ perceived benefit towards PHEV-related attributes were estimated in terms of Willingness to Pay (WTP) values. In the second stage, the potential demand shift from CV to PHEV was estimated by developing demand models. The results indicate the need for an added emphasis on PHEV-specific attributes such as charging time and battery warranty and attribute for general vehicle use such as advance vehicle technology (AVT) option by vehicle manufacturers to make PHEV attractive to consumers in Indian megacities. High purchase price is identified as a major bottleneck for the penetration of PHEV in Indian market. Policy interventions from government in terms of higher subsidy, availability of public charging infrastructure, and environmental education and awareness among consumers are necessary to effectively promote PHEV in Indian context.
... Thus, the purchasing power control factor appeared to be the major consideration for deciding to purchase healthy food products or not to (Mai & Hoffmann, 2012). The government interventions in terms of policy and regulations support consumers' EV purchase behaviors and their willingness to pay more for an EV (Helveston et al., 2015;Oreg & Katz-Gerro, 2006;Sang & Bhet, 2015). They are thus important predictors of green consumption behavior and have been confirmed to have a positive relationship with EV purchase intention (Egbue et al., 2017). ...
This study conducted an in-depth analysis of the factors affecting consumers' intention to purchase and willingness to pay more for an electric vehicle (EV) in the developing-country context, extending the theory of planned behavior with two new variables: environmental concern and willingness to pay (WTP) a premium. Survey data were collected from 358 responses and were analyzed using partial least squares structural equation modeling. Multi-group analysis was conducted, and the moderating role of gender was examined. The findings showed the significant effects of the theory-of-planned-behavior variables and environmental concern on EV technology purchase intention. The present study provides theoretical contributions and policy guidelines concerning high (vs. low)-sensitivity consumer attitudes toward EV technology that marketers and automobile manufacturers can make use of when designing and strategizing their pricing strategies.
... To obtain the SNI (Indonesian National Standard), rigorous testing of domestically manufactured parts and imported parts and compliance with product quality standards are necessary to obtain the SNI (Indonesian National Standard). While the Presidential Regulation Number 50 Year 2019 has determined that domestically produced EV must be made of 35% locally-made parts by 2021, 40% by 2023, and 60% by 2030, our respondent claimed to have reached 80% and aimed for 90%. The biggest hurdle of independent development of EV parts is the battery due to Indonesia's absence of a domestic battery industry. ...
As a net oil importer since 2004, Indonesia’s success in developing fuel economy and infrastructure for electric vehicles would be vital to ensuring energy security and decarbonization from the transport sector. Following the Presidential Regulation on the Acceleration Program for battery-based EV for Road Transportation in 2019, the Indonesian government provides incentives for the domestic production of EVs. However, as EV technology is relatively new for the domestic automotive industry in Indonesia, it needs to go through stages of development to achieve full readiness in society. This study analyses the key stakeholders’ perceptions of EV industries using the Japanese technology readiness assessment (J-TRA) to better understand the current readiness level of EVs in Indonesia. Primary data are collected through interviews with an EV start-up company, experts in the EV field, government officials in charge of the national EV projects, and EV end-users. Extensive literature related to success stories of EV adoption in other countries was conducted as the basis for this study. The results showed that key stakeholders agree that EV technology has reached a high readiness level in technology development. Most of the stakeholders voted that the readiness bottleneck is commercialization, safety, and integration parameters. Furthermore, an elaborate policy recommendation gathered from both literature reviews and interviews with related stakeholders is presented.
... In a study on Dutch private car owners using choice experiments, Hoen and Koetse (2014) find that the availability of models in the market positively affects EV acceptance but to a significantly lesser extent. Moreover, among other factors, brand image, perception, and loyalty influence car buyers' purchasing process (Devaraj et al., 2001;Helveston et al., 2015;Hirsh et al., 2016). A consumer survey analysis on Chinese consumers' willingness to pay for a car brand based on its country of origin reckoned that Chinese people mostly prefer cars manufactured in Germany. ...
Electrification of vehicles is one of the most promising measures for decarbonising the transport system. Several countries worldwide have implemented policy incentives to promote mass electric vehicle (EV) adoption to mitigate the environmental and energy-related challenges caused by the increased demand for road transportation. As a result, the number of EVs on the road is growing in several countries. However, despite the growing demand, many consumers are still sceptical about EVs. The aim of this study is to evaluate consumers' EV repurchase intention by using an extended theory of planned behaviour (TPB). Studies on EV adoption have found TPB determinants of intention to be relevant. Additionally, this study argues that the effects of satisfaction should be considered in addition to the TPB elements to better understand repurchase intentions. Consequently, this study includes EV users' satisfaction with relevant aspects such as range-recharge, environmental attributes, cost, availability, symbolic attributes, and use-based policy measures. A structural equation model (SEM) was established to analyse a survey dataset consisting of 278 Norwegian EV owners. To assess satisfaction with EV use and the behavioural intention of EV repurchases, only the responses from actual EV users were studied. This is important because consumers with no prior experience with EVs tend to inaccurately portray their interest in a new product or service. The findings are of interest for both policymakers and EV manufacturers seeking to gain actionable insights into EV owners' needs and perceptions concerning EV attributes, thus developing and implementing better strategies to increase EV attractiveness and performance.
... The literature on capturing the impact of WOM on consumer preferences is prolific (see Table A.1 in supplementary material for a summary of 40+ such studies). Specific to the transportation sector, structural equation models (Kwon et al., 2020;Thøgersen and Ebsen, 2019), discrete choice models (He et al., 2014;Helveston et al., 2015;Jansson et al., 2017), agent-based models (Kieckhäfer et al., 2017), exploratory factor analysis (Ozaki and Sevastyanova, 2011), regression analysis (Barth et al., 2016;Du et al., 2018;Moons and De Pelsmacker, 2012), text mining (Ma et al., 2019), theory of reasoned action (Alzahrani et al., 2019), and Bass model (Hong et al., 2020) have been used to model WOM and social network effects in the adoption of green or electric vehicles (EVs). Specific to AVs, Ghasri and Vij (2021) explored the influence of WOM on the consumer preferences using discrete choice. ...
Due to the unavailability of prototypes, the early adopters of novel products actively seek information from multiple sources (e.g., media and social networks) to minimize the potential risk. The existing behavior models not only fail to capture the information propagation within the individual's social network, but also they do not incorporate the impact of such word-of-mouth (WOM) dissemination on the consumer's risk preferences. Moreover, even cutting-edge forecasting models rely on crude/synthetic consumer behavior models. We propose a general framework to forecast the adoption of novel products by developing a new consumer behavior model and integrating it into a population-level agent-based model. Specifically, we extend the hybrid choice model to estimate consumer behavior, which incorporates social network effects and interplay between WOM and risk aversion. The calibrated consumer behavior model and synthetic population are passed through the agent-based model for forecasting the product market share. We apply the proposed framework to forecast the adoption of autonomous vehicles (AVs) in Nashville, USA. The consumer behavior model is calibrated with a stated preference survey data of 1,495 Nashville residents. The output of the agent-based model provides the effect of the purchase price, post-purchase satisfaction, and safety measures/regulations on the forecasted AV market share. With an annual AV price reduction of 5% at the initial purchase price of $40,000 and 90% of satisfied adopters, AVs are forecasted to attain around 85% market share in thirty years. These findings are crucial for policymakers to develop infrastructure plans and manufacturers to conduct an after-sales cost-benefit analysis.
... The price of EV is on the higher side as compared to the existing fossil fuel cars (Adepetu and Keshev, 2017). Hence, there is a need for government intervention to boost the EV adoption intentions (Sang and Bekhet, 2015;Helveston et al., 2015). The government can provide financial incentives and other benefits like subsidies, tax benefits, and free toll. ...
The total number of vehicles is expected to be 2.5 billion by the year 2050. To stabilize the impact on environment, the automobile sector has shown various innovations by shifting from conventional vehicles to electric vehicles (EVs). However, there is less acceptance of electric cars in India, so this research paper explores the various factors affecting EV adoption intention. The key factors studied are price, environmental concern, infrastructure requirement, and knowledge of EV. This paper also shows that government policies act as a mediator between factors like price, knowledge of EV, and infrastructure requirement on adoption intention of EVs. This research paper presents insights for the decision-makers to understand the determinants and design the strategies for increased adoption intention of EVs.
... Based on a choice experiment with 3029 car buyers in the U.S., they observed that respondents valued a charging time reduction by one hour in the order of $425 to $3250 when purchasing a new vehicle. However, Bockarjova and Steg (2014) and Helveston et al. (2015) are among the very few studies that explicitly distinguish between slow and fast charging and find specifically stronger time preferences for fast charging stations. Figure 5 shows the results for four contextual determinants affecting BEV acceptance. ...
Battery electric vehicles (BEV) are essential in most countries’ transition towards an efficient, cleaner and low-carbon transport system. BEV technology has been making rapid progress, but low market uptake poses major challenges for governments and industry. Based on the PRISMA framework (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), we assessed 94 studies published in the era of BEVs becoming visible market products between 2010 and 2019. The main goal is to understand what we know about attitudes and behaviour of consumers/citizens towards BEVs. In contrast to the conventional wisdom that we know the key facilitators and obstacles in this area, we find that few studies are designed to identify causal effects of facilitators and obstacles, and findings on widely presumed key determinants are surprisingly mixed and context-dependent. We conclude that we still lack robust evidence on the facilitators of BEV uptake and prospective ownership. Moreover, and particularly alarming from a scientific viewpoint, many existing studies cannot be replicated because the respective data is unavailable, neither publicly accessible nor on request. Given the saliency of the issue, the main implication of our assessment is that a concerted, internationally coordinated effort in this area is needed, based on pre-registration of study designs and full accessibility of replication data.
... Conventional transport such as public transit highly relies on capital and operating subsidies from federal, state, and local sources. Recent research has been paying attention to the governmental incentives for emerging transportation technology such as electric vehicles (EVs) [60], car-sharing [90], and emerging connected and automated vehicles (CAVs) [81]. For example, despite the low market penetration rate, the total cost of EV subsidies is substantial. ...
This thesis studies incentive contracts in multi-agent systems with applications to transportation policy. The early adoption of emerging transportation systems such as electric vehicles (EVs), peer-to-peer ridesharing, and automated vehicles (AVs) relies on governmental incentives. Those incentives help achieve a specific market share target, prevent irregular behaviors, and enhance social benefit. Yet, two challenges may impede the implementation of such incentive policies. First, the government and subsidized organizations must confront the uncertainty in a market; Second, the government has no access to the organizations' private information, and thus their strategies are unknown to it. In the face of these challenges, a command-and-control incentive policy fails. In Chapter 2, we revisit the primary setting in which a government agency incentivizes the OEM for accelerating the widespread adoption of AVs. This work aspires to offset the negative externalities of AVs in the ``dark-age'' of AV deployment. More specifically, this chapter designs AV subsidies to shorten the early AV market penetration period and maximize the total expected efficiency benefits of AVs. It seeks a generic optimal AV subsidy structure, so-called ``two-threshold'' subsidy policy, which is proven to be more efficient than the social-welfare maximization approach. In Chapter 3, we develop a multi-agent incentive contracts model to address the issue of stimulating a group of non-cooperating agents to act in the principal's interest over a planning horizon. We extend the single-agent incentive contract to a multi-agent setting with history-dependent terminal conditions. Our contributions include: (a) Finding sufficient conditions for the existence of optimal multi-agent incentive contracts and conditions under which they form a unique Nash Equilibrium; (b) Showing that the optimal multi-agent incentive contracts can be solved by a Hamilton-Jacobi-Bellman equation with equilibrium constraints; (c) Proposing a backward iterative algorithm to solve the problem. In Chapter 4, we obtain the optimal EV and charging infrastructure subsidies through the multi-agent incentive contracts model. Widespread adoption of Electric Vehicles (EV) mostly depends on governmental subsidies during the early stage of deployment. The governmental incentives must strike a balance between an EV manufacturer and a charging infrastructure installer. Yet, the current supply of charging infrastructure is not nearly enough to support EV growth over the next decades. We model the joint subsidy problem as a two-agent incentive contract. The government observes two correlated processes -- the EV market penetration and the charging infrastructure expansion. It looks for an optimal policy that maximizes the cumulative social benefit in the face of uncertainty. In our case study, we find that the optimal dynamic subsidies can achieve 70% of the target EV market share in China by 2025, and also maintains the ratio of charging stations per EV. Chapter 5 ends the thesis with conclusions and promising future research directions. In summary, this thesis provides a new approach to appraise transportation and energy policies against exogenous and endogenous risks.
... The financial subsidy can stimulate investments to drive industry growth, and reduce the initiation period. The rapid growth of EV adoption occurs in this phase [4,18,41]. The industrialization and commercialization of Chinese electric vehicles nationwide are gradually realized [9]. ...
The dual-credit policy advances the process of vehicle electrification; however, few studies have reviewed the policy preferences and development trends of the Chinese new energy vehicle industrial policy at different stages from the development angle of the dual-credit policy. This article reviews the policy evolution of the Chinese new energy vehicle industrial policy based on the 2T model (time and types) and evaluates the policy intensity of different industrial policies by PI index. The results find that the Chinese new energy vehicle industry policy is divided into three development periods: 2004–2008—promotion policy and technological policy; 2009–2013—financial policy; and 2014–2020—charging infrastructure policy. The early policy preference for new energy vehicles was not found to be significant. Financial policies have significantly stimulated the development of the new energy vehicle industry, and the implementation of the charging infrastructure policy is late. The policy intensity of the promotion policy is the strongest, followed by the technological policy, and the policy intensity of the charging infrastructure is the weakest. The policy intensity of the financial policy will weaken in the later period. The promulgation of the dual-credit policy reflects the continuity and synergy of policy development.
... A strategy involving subsidies is one of the most effective means to promote the development of authorized remanufacturing enterprises [31][32][33][34][35]. A subsidy strategy aims to improve low-carbon enterprises' R&D level [36], increase remanufacturing activities [37,38], and influence consumer preferences [39]. Government subsidies stimulate the demand for energy and the profit of energy service companies [40]. ...
Authorized remanufacturing is an important means to achieve green manufacturing and carbon neutrality. In this study, a game theory model between a manufacturer and a remanufacturer was constructed to analyze the impact of government subsidies and carbon tax policies on authorized remanufacturing. Based on the game theory model, the effects of two government policies on the optimal solution, namely, the unit cost of remanufacturing product authorization and the waste product recovery rate, were compared and analyzed. This analysis could provide a reference for the government to improve and formulate relevant remanufacturing policies. The main results are as follows: government subsidy policies may increase the unit cost of remanufacturing product authorization and the rates of waste product recovery; government carbon tax policies may not affect the unit cost of remanufacturing product authorization, and increase the rates of waste product recovery; the government subsidy policy may not affect the unit retail price of new products, and reduces the unit retail price of remanufactured products; the government subsidy and carbon tax policies may reduce sales of new products and increase sales of remanufactured products; the government subsidies may increase the revenue of the original equipment manufacturer (OEM) and the remanufacturer; and the government carbon tax policies may increase the revenue of the remanufacturer. However, government carbon tax policies increase the revenue of the OEM only when the new product carbon tax amount is higher than a certain threshold. The impact of the two policies on the environment is related to the ratio of the two products’ impact on the environment, i.e., the quota ratio between the unit government carbon tax of the new product and the unit government subsidy of the remanufactured product. Finally, the consumer surplus is maximized when the government adopts the subsidy policy and lowest when the government adopts the carbon tax policy.
... (2) Longer charging time is predominantly negatively associated with BEV attitudes (Hackbarth and Madlener, 2016;Higueras-Castillo et al., 2020;Kim et al., 2020;Šč asný et al., 2018). While only few studies explicitly distinguish between slow and fast charging, when they do, results indicate that fast-charging stations play a more important role in shaping attitudes (Bockarjova and Steg, 2014;Helveston et al., 2015). Similarly, the availability of charging infrastructure has a predominantly positive effect on attitudes towards BEVs (Danielis et al., 2020). ...
Battery electric vehicles (BEV) are widely regarded as crucial to decarbonising the transport sector and achieving the Paris Agreement goals. Yet, there is much political controversy over how to accelerate the uptake of BEVs, which is currently still rather slow in most countries. The most important controversy concerns the extent to which consumer-oriented policy measures, such as purchase price subsidies, tax breaks and subsidised charging infrastructure are needed. Based on a large-scale (n = 1′021) choice experiment, we examined the relevance of a broad set of potential obstacles and drivers of BEV uptake from a consumer perspective. Obstacles include purchase price, energy costs, maintenance costs, warranty, and range. Potential policy measures for overcoming such obstacles include, e.g., free public transportation tickets and car exchanges, government subsidies, warranty periods, and charging infrastructure. Our main finding is that current key obstacles to BEV uptake are primarily economic and technical. It implies that disruptive measures such as banning fossil-fuel cars as well as supply-side policy interventions could help push the car industry into rapid technological innovation, and that economies of scale in BEV production may be more effective than governmental measures aimed at incentivising BEV uptake.
... Additional wind power capacity would be installed within 5 years, followed by nuclear power plants. All The diffusion of EVs is of national-level interest, and the deployment of charging infrastructure is an important parameter to be considered (Hardman et al., 2018;Ji & Huang, 2018), along with charging price policies, standardisation of charging infrastructure (Ahmad, Khan, Saad Alam, & Khateeb, 2018;Foley, Winning, & Gallachóir, 2010), the upgradation of the electricity supply system (Dai & Liu, 2017) and incentives such as subsidies for EV adaption (Breetz & Salon, 2018;Crist, 2012;Helveston et al., 2015;Holtsmark & Skonhoft, 2014;Masiero, Ogasavara, Jussani, & Risso, 2016). The environmentally-friendly energy mix, using more renewable energy, is an important determinant for the adoption of electric vehicles (H. ...
Business Model Innovation (BMI) is a way for companies to develop its competitive advantage. The upstream-supply of technologies and products, in parallel to the development of key infrastructures are indispensable for a company to build the value network of a new business model. However, the development of innovation ecosystems is dependent to the factors external to the company and to the managers.Companies face varying constraints to achieve BMI when the development of relevant innovation ecosystem remains uncertain. The thesis focuses on the pre-stage of a BMI: the phase when the technology or the product required to achieve a BMI is not yet available. How do managers deal with this pre-stage situation?The research uses a case-study analysis of a start-up based in Bangalore that was the first company in India to use Electric Vehicles (EVs) to provide Corporate Employee Transport (CET) services. The company aims to scale-up its service line-up beyond CET service before other potential market players in order to build a first-mover’s advantage. However, appropriate EV models required for service diversification are not yet available since the innovation ecosystem of EV remains under development. The thesis suggests that a clear recognition of the pre-stage of BMI is critical to better understand the BMI process, especially because the organizational capabilities required during the pre-stage differ from those of post-pre-stage such as Dynamic Capabilities: capabilities to execute a BMI.
... To encourage enterprises to take actions in accordance with the national goals of carbon peak and carbon neutrality, the Chinese government has adopted the carbon cap-and-trade mechanism as one of the common carbon emission reduction policies by imposing a carbon quota on enterprises, in such a way to push enterprises to take carbon reduction actions. Other government initiatives include carbon tax policies [4][5][6][7][8][9][10][11], carbon subsidies [12][13][14][15][16][17][18][19][20][21], take-back regulation [22][23][24], carbon trade market [25][26][27][28][29][30][31][32][33][34], and carbon emission constraints [35][36][37][38][39][40][41][42]. Carbon emission constraint reflected as carbon quota is a policy formulated by the government to limit the excessive carbon emissions of enterprises [42][43][44][45][46]. ...
Carbon emission reduction has been a consensus goal for most countries to achieve environmental sustainability. The use of carbon emission trading policies has been generally considered by the governments. Remanufacturing, as an effective way to reduce carbon emission, is incorporated together with the tool of carbon emission policy to construct a low-carbon supply chain in this paper. We analyze the carbon emission reduction and profit maximization problem among enterprises of original equipment manufacturers (OEMs) and their outsourcing remanufacturers, integrating the impact of the carbon emission constraint policy and the carbon market. Considering consumer preferences on low-carbon products and recycling rates of waste products, we construct a Stackelberg game model (dominated by the OEM) and analyze the impact of a carbon emission constraint policy on sales price, volume, carbon emission, and revenue of new and remanufactured products in the supply chain system. The results suggest that the upper bound set by the government on carbon emission for enterprises positively affects sales volume of new products and negatively affects sales prices of both products. Moreover, the discount rate of carbon emission constraint negatively affects sales volume of new products and positively affects sales prices of both products. Notably, the carbon emission constraint policy has impacts on the production decisions of both manufacturers on an economic scale. When the upper bound of carbon emission is equal to a certain threshold, the OEM could obtain the greatest revenue. The results provide a new perspective for the government to attain the goal of carbon emission reduction and not sacrifice economic growth. Managers in outsourcing remanufacturers and OEMs could also be implicated from our results to collaborate in allocating remanufacturing orders to achieve win-win opportunities between them.
... This is a crucial issue in our study because the subject of distributional equity can be politically sensitive, and some respondents may be less forthcoming about their true preferences as a result. In the case of EV incentives, other scholars have also used conjoint experiments and explored how consumers' willingness to purchase EV is shaped by the presence of incentives (Ko and Hahn, 2013;Helveston et al., 2015;Lieven, 2015) and which type of incentives (e.g., charging, driving, registering, purchasing) the public prefers (Li et al., 2020). ...
This paper explores whether perceptions about distributive inequity shape public support for energy transition policies. The introduction of electric vehicles (EVs) is an important policy priority for the decarbonization of road transportation. Because high sticker prices restrict EV sales, governments offer consumers EV subsidies. However, some are concerned that subsidies may favor certain groups and industries. Using a conjoint experiment, we examine the public preference for EV subsidies in the U.S. and Japan.,. In the U.S., there is a concern that EV subsidies help the high-income (i.e., individual-focused concerns), while the prevailing concern in Japan is whether they favor foreign companies which are the first movers in the EV industry (i.e., industry-focused concerns). We embed a vignette experiment within the conjoint experiment to prime the respondents with individual- and industry-focused distributional concerns. In both countries, regardless of the priming they received, our respondents favor universalistic subsidies that are inclusive of the high-income and luxury/foreign cars to subsidies that are more progressively targeted (i.e., exclusive of the rich and luxury cars) or favoring domestic firms. As such, recent EV policy discourse centering on distributional politics does not appear to reflect public opinion.
... Besides, the monthly household income and the expected income from V2G [27,28] as well as the users' specific needs regarding the car [29] have a significant influence on user acceptance. Whereas, potential customers (in the US) with a high income are more willing to buy a BEV [30], owners of BEVs with high income levels perceive less utility regarding V2G than those with a low income [28]. ...
... The choice experiment method conducted by Cherchi [27] contained several EV attributes (two policy attributes and two dummy attributes) to analyze the influence degree of individuals on EV preferences, but the coverage of vehicle-specific attribute is incomplete. Helveston et al. [28] modeled consumer preferences for conventional vehicles, hybrid EVs, plug-in hybrid EVs, and battery EVs in China and the U.S. by using data from choice-based conjoint surveys carried out in 2012-2013. Beck and Rose [29] creatively combined the best-worst scaling and choice experiment method. ...
Social conformity, a psychological phenomenon commonly shared by most individuals, has long been ignored by studies focusing on influencing preferences for shared electric vehicles (SEVs). To fill this gap, this paper divides social conformity into informational conformity and normative conformity, and analyzes their effects on individuals’ choice of SEVs. Respondents were selected randomly in Jiangsu Province, and the data were collected by the choice experiment method. The data were further analyzed by logit models. Results show that social conformity has a significant positive impact on individuals’ choice of SEVs, and informational conformity has a much more profound impact than normative conformity. The driving cost and the convenience of picking up and returning a vehicle also influence consumers’ preferences. In addition, social conformity cannot totally dispel the negative impact of poor experience. Finally, some targeted policy recommendations are proposed.
... To promote a thriving remanufacturing industry, countries adopt a wide range of intervention policies to facilitate the production of low-carbon products by both OEMs and remanufacturers [28]. Specific policies include production support policies such as government subsidies [29][30][31][32][33][34][35][36][37][38], return policies [39][40][41], and carbon emissions intervention policies such as carbon trade [3,4], carbon taxes [42][43][44][45][46] and carbon regulation [47]. Scholars have compared the impacts of different policies [48], including carbon tax and carbon trade [4,49], carbon taxes and government subsidies [50][51][52][53][54], carbon tax and take-back legislation [55], take-back and carbon emission capacity regulations [47], and government subsidies and carbon regulation [22]. ...
Outsourcing remanufacturing is an important way to achieve resource recycling, green manufacturing and carbon neutrality goals. To analyze the impact of carbon trade on manufacturing/remanufacturing under outsourcing remanufacturing, this article builds a game model between an original equipment manufacturer (OEM) and a remanufacturer under the carbon trade policy. In the outsourcing remanufacturing model, this article compares the impact of the carbon trade policy on the unit retail price, sales volume, revenue, environmental impact, and consumer surplus of new and remanufactured products. The research mainly draws the following conclusions: (1) Carbon trade increases the prices of both new and remanufactured products and the cost of outsourcing. Only when certain conditions are met can increased carbon trade prices increase revenue. (2) The carbon trade policy helps reduce the adverse impact on the environment, but only when the carbon trade price is greater than a certain threshold can it increase consumer surplus. (3) Consumer preferences and carbon emissions of the unit product affect manufacturers’ profits. Increased consumer preference for remanufactured products and reduced carbon emissions of remanufactured products contribute to increased sales and revenues.
Under the goal of carbon peak and carbon neutrality, developing battery electric vehicles (BEVs) is an important way to reduce carbon emissions in the transportation sector. To popularize BEVs as soon as possible, it is necessary to study selection strategies for BEVs from the perspective of consumers. Therefore, the Latent Dirichlet Allocation (LDA) model based on fine-grained sentiment analysis is combined with the multi-criteria decision-making (MCDM) model to assess ten types of BEV alternatives. Fine-grained sentiment analysis is applied to find the vehicle attributes that consumers care about the most based on the word-of-mouth data. The LDA model is suggested to divide topics and construct the indicator system. The MCDM model is used to rank vehicles and put forward the corresponding optimization path to increase consumer purchases of BEVs in China. The results show that (a) via the LDA model based on fine-grained sentiment analysis, attributes that consumers care most about are divided into five topics: dynamics, technology, safety, comfort, and cost; (b) based on the DEMATEL technique, the dimensions in the order of importance are as follows: safety, technology, dynamics, comfort, and cost; (c) the price is the most important criteria that affect customers’ satisfaction by the DANP model; and (d) based on the VIKOR model, the selection strategies present that Aion S is highlighted as the best choice, and the optimization path is discussed to promote the performance of BEVs to increase customers’ satisfaction. The findings can provide a reference for improving the sustainable development of the automobile industry in China. The proposed framework serves as the basis for further discussion of BEVs.
The purchase subsidy policy for electric vehicles (EVs) has considerably stimulated the purchase preferences of price-sensitive consumers and helped to increase the penetration rate of EVs in China. However, the purchase subsidy also brings increased financial burdens to governments; therefore, it is viewed as a short-term policy and will phase out. Considering the price sensitivity of different consumer categories, this paper aims to investigate the impact of several substitutional incentive policies to continue stimulating the adoption preference of EVs after the purchase subsidy phase-out. A latent class binary logit (LCBL) model is established to explore consumers’ EV adoption preferences in different price-sensitive categories. Four substitutional incentive policies, including mileage subsidy, congestion fee discount, parking fee discount, and bus lane driving permission, are proposed to cope with the abolishment of purchase subsidy. The results show that the incentive effect of the purchase subsidy policy on price-sensitive consumers is 1.6 times that of price-insensitive consumers. To avoid the reduction in EV adoption rate caused by the abolishment of purchase subsidy, mileage subsidy, parking fee discount, or congestion fee discount should be set at 0.93 CNY/km, 4.43 CNY/hour, or 16.09 CNY/time, respectively.
The study aims to operationalize and test the extended ‘Technology Acceptance Model’ (TAM) with perceived risk and financial incentives policy based on the integrative approach of ‘beliefs-attitude-intention’ in order to understand and predict consumers’ intention to adopt electric vehicles (EVs). The research model also seeks to examine the mediating role of attitude towards EVs and the moderation of financial incentives policy in the context of an emerging sustainable transportation market. The model was empirically tested by structural equation modeling using online survey from Indian respondents. The findings reveal that adoption intention for EVs is directly and indirectly influenced by the predictor variables of attitude, perceived usefulness, perceived ease of use, and perceived risk, with the moderation of financial incentives policy. All the direct hypotheses were accepted, except the relationship between perceived risk and attitude. In addition, the findings also confirm that attitude partially mediate the effects of usefulness and ease of use on the adoption intention, however, no mediating effect of attitude has been found between risk and adoption intention. The discussion and implications offer deeper insights for policymakers and marketers on promoting EVs in the direction of future research in the sustainable transportation.
Many governments have begun to adopt aggressive targets for electric vehicles. However, studies of the drivers of electric vehicle (EV) adoption are scarce. Social media interactions can provide a new data-driven vantage point to explore such drivers. This study uses data from 36,000 public posts on Facebook to investigate inter-sectionality in EV-communication as per the Political, Economic, Social, Technological, Legal and Environmental (PESTLE) categories. A computational social science methodology was adopted using a mixed-method application of social network analysis and machine learning-based topic modelling through Latent Dirichlet Allocation algorithm on a 600,000-text corpus extracted from the Facebook posts. Results showed that political, economic, and legal posts had dense clusters around the technology policy of EV, the institutional discourse of electrifi-cation of the federal vehicle fleet, and tax and credit framework politics. The environmental and social dimensions had a higher discourse for social justice, clean air, and better health and well-being. A market shift towards EV as a service industry was observed in the technology and economics-related posts. These findings can help policymakers, and planners design contextualised energy policy for influencing EV adoption in the U.S. and other countries.
As one of the strategic emerging industries, the new energy vehicle (NEV) industry receives strong support from the Chinese government. The Chinese government has formulated a large number of policies to promote the development of NEV industry. Evaluating and analyzing the NEV policies are of great significance for improving policy formulation. In this study, we comprehensively analyze 253 NEV policy texts by employing quantitative and qualitative methods. We present the policy instrument types and semantic structure characteristics of policy texts based on the content analysis. The advantages and disadvantages of policy texts are identified by using a quantitative evaluation model. Our results show that the most frequently used policy instrument is regulatory, and the main policy objective is the demand-pull. The policies with higher scores are more comprehensive. Three suggestions are put forward to improve NEV policies.
The increasing popularity of electric vehicles (EVs) leads to heightened demand for the charging infrastructure. More and more EV drivers install private charge posts, which can now be shared with others through certain mobile apps. This emerging phenomenon is becoming a prominent part of the sharing economy. To examine the impacts of post sharing on EV charging market, this study establishes game theory models on consumer choices among private, public, and shared options. Such peer-to-peer sharing and collaborative consumption redistribute the installation and operation costs of private charge posts in proportion to their increased utilization. Numerical analyses suggest that the sharing mode provides a win-win solution for charge post owners and non-owner consumers, as well as electricity distributors and public charging infrastructure operators. In the case of China, the estimated saving for charge post owners is between 20% and 50%, which can be translated into more non-government investment in the EV industry chain. The findings provide supporting evidence for policy-makers to promote private charge post sharing, especially with certain consumer subsidization at a reasonable level.
To overcome the environmental side effects of over-utilizing fossil fuels and road traffic emissions, Alternative Fuel Vehicles (AFVs) are alternative power engines. However, as AFVs have not yet penetrated the automotive market in Iran, using the choice experiment model, this study considers the heterogeneous preference for Electric Vehicles (EVs) in four megacities of Iran. Therefore, 1000 respondents are interviewed and are asked to choose their preferred vehicle between hybrid electric vehicles (HEVs), battery electric vehicles (BEVs), and internal combustion engine vehicles. Furthermore, this study contributes to the literature by employing the Policoric correlation matrix, not Pearson, to investigate the influence of psychological factors besides the macro, micro, and product factors in adopting Evs. The latent class and mixed logit model reveal the monetary factors negatively affected consumers' willingness to pay for HEVs and BEVs. In contrast, the charging availability and non-monetary policies are positively connected to the acceptance rate of BEVs, While risk-aversion and normative-face perspectives reduce it. Furthermore, the class membership variable shows that the younger tend to purchase HEVs, and high-income groups are the most significant potential buyers of HEVs and BEVs. Therefore, the younger and high-income groups could be considered the target group in Iran's early penetrating EVs.
This chapter reviews the history of how humans became a species that creates and uses technology along with some important milestones. The key features of Homo sapiens include our brains, and our ability to use them to form abstractions through language, as well as the extraordinary dexterity of our hands as enablers of technological evolution. We argue that the replacement or augmentation of human and animal strength with machines, such as the steam engine, was one of those key milestones. We review several technological revolutions, including electrification starting in the nineteenth century and the information age which started in the twentieth century. We briefly discuss the role of national identity and conflicts in claiming or accelerating technological progress and speculate on what humanity’s next technological revolution might be in the future.
Vehicle automation, along with vehicle electrification and shared mobility, may transform the existing transportation if they are handled properly. However, they may create unintended consequences if the current market dominance of fossil fuel and privately-owned vehicles persists, and travel patterns and transportation policies remain unchanged. The extent of these potential benefits and unintended consequences depends on the expected AV adoption process, people’s preferred vehicle powertrain, and AV-related policy and infrastructural support. This paper seeks to understand the impacts of attitudinal factors and roadway designs on people’s intention to use AVs and to purchase battery-electric AVs (EAVs) and gasoline-powered AVs (GAVs) under travel and user heterogeneity. Fourteen latent attitudinal factors related to the perceptions and attitudes towards AV and EV technologies, driving, the environment, and personal innovativeness were considered. An EAV-enabled urban design environments were created, featuring dedicated AV lanes, wireless charging for EAVs, and AV pick-up/drop-off zones. Using a stated preference survey data of over 1,300 responses in the U.S., Multiple Indicators and Multiple Causes models are estimated to understand the relationship among various latent variables and capture heterogeneities within the population based on their sociodemographic and behavioral characteristics. The model estimation results show that the respondents’ perception of AVs and EAVs advantages, road safety improvement potential, compatibility with their lifestyles and travel needs, and their attitudes towards driving are key factors of their intention to use AVs and purchase EAVs. Furthermore, some segments of the population based on their sociodemographic and travel behavior characteristics are more likely to have a higher intention to use AVs and buy EAVs. The model estimation results and study insights can be used by policymakers to develop road network design guidelines and policies to nudge consumers towards more sustainable transportation options, minimize the unintended consequences of vehicle automation, and maximize its benefits.
An often used policy instrument to promote climate change mitigation and adaptation action are subsidies. Yet, it remains unclear to what extent subsidies are effective in motivating behavioural change. Subsidies are effective if they lead to adoption of the behaviour by individuals different from those who would adopt otherwise. On the bases of two theoretical frameworks, we examine the effectiveness of two subsidy schemes in the Netherlands. In Study 1 (n = 151), we applied the Transtheoretical Model and argued that a subsidy for climate adaptation measures is effective if it not only attracts those in the action and preparation stages of the model, but also people in the precontemplation and contemplation stage. In Study 2 (n = 367), we applied the Diffusion of Innovations Theory and argued that a subsidy for electric vehicles is effective if it attracts not only innovators and early adopters, but also early and late majority adopters. In both studies, we examined the extent to which subsidies remove financial barriers and serve as a cue to action. In Study 1, we found that the subsidies primarily attracted people who were in the action and preparation stages. In Study 2, we found that a subsidy for electric vehicles did not attract more early and late majority adopters compared to those who adopted an electric vehicle without a subsidy. In both studies we found that the subsidy mainly served as a cue to action, and was less likely to remove financial barriers.
This paper discusses how to promote stable new energy vehicle (NEV) diffusion and how to alleviate the related financial pressure faced by governments. First, indirect evolutionary game theory is applied to examine the interaction mechanism of complex behaviors between local governments and auto manufactures, with and without consideration of subsidy policy phase-outs. Second, we define the ideal event and analyze the impacts of key factors on the dynamic evolution process. On this basis, the empirical analysis method is used to verify the game models and primary conclusions. Finally, the sensitivity analysis of selected parameters is discussed in details. Results demonstrate that: (1) subsidy policy phase-outs can help to develop the NEV industry; (2) the probability of an ideal event is positively correlated with the vehicle purchase tax, additional benefits for NEV manufacturers, penalties for fossil vehicle manufacturers and the coverage ratio of public charging piles, and it is negatively correlated with the phase-out rate; (3) NEV evolutionary dynamic factors can be divided into three priority levels and optimization of the parameters design is discussed, which can provide useful decision-making tools for governments and enterprises.
Subsidies are crutial for the development of China's New Energy Vehicle (NEV) market. With the country's ambitious goal to achieve carbon neutrality in 2060, NEV is playing a growing role in decarbonising the transport sector. This paper empirically evaluates the effectiveness of three main forms of subsidies: fiscal policy, preferential tax, and government procurement. Specifically, we pay attention to financing issues and use an event study approach to investigate how the capital market responds to these policies. Results show that both preferential tax and government procurement policies have significant positive impacts on NEV stock prices. Relative to lithium-ion battery and NEV manufacturers, charging pile companies benefit less from preferential tax or government procurement. For fiscal subsidy policies, their impacts on NEV stock prices are ambiguous, depending largely on the specific policy contents. An increase in targeted subsidies for those technology-oriented NEV firms has a positive impact on the stock market. However, subsidies falling short of expectations due to frequent policy changes and the removal of local government subsidies are associated with significant negative effects. At this critical stage when the Chinese government is re-designing subsidy policies on NEVs, special attention should be paid to setting a transparent schedule and reducing the potential negative effect caused to the stock market.
India is exceptionally backward in public acceptance and diffusion of electric vehicles. Therefore, considering the perspective of the Indian people, policymakers, automakers, and marketers, the primary aim of this study was to develop an effective model comprising selective influencing variables that were relevant in the Indian context and capable of revealing the true intention of Indian people to use electric vehicles (EVs). The structural equation modeling was applied to validate the proposed model. Consistently significant results derived from the three separate studies confirmed that the intention to use electric vehicles in India could be explained as being most significantly related to purchase price, perceived behaviour control, personal norms, environmental concerns, sustainable behaviour, driving range, household income, respectively, among all significant influencing factors. The findings covered the literature gaps by confirming the consistently and comparatively strong partial mediating effect of environmental concerns on the relationship between sustainable behaviour and EVs usage intention, personal norms and EVs usage intention, and the mediating effect of the purchase price on the relationship between the driving range and EVs usage intention. The findings also confirmed a moderating effect of age on the relationship between perceived behaviour control and EVs usage intention. The study propounds some important implications for policymakers, automakers, marketers, and other stakeholders, reflecting on the development of strategies for wide-scale acceptance of EVs in India in the coming years.
The real-time dispatch of electricity grids faces two new challenges: the volatility of renewable energy power generation and the impact caused by the large-scale charging demand of electric vehicles (EVs). Under the premise that China's renewable energy power generation is a prior connection to the grid, this article aims to guide the coordinated charging of EVs through the design of the time-of-use charging price mechanism and to help achieve valley-filling. The peak and valley hours were divided according to the load of baseload units that do not include renewable energy power generation. A nationwide discrete choice experiment has been conducted to investigate the willingness to pay of 2637 Chinese consumers for charging at different times and to analyse the influence of heterogeneous factors. Finally, the power economic dispatch model has been used to simulate the effect of the charging time-of-use pricing on the cost and load of the regional power system. Policy recommendations are provided based on consumers' willingness to pay for charging at public charging stations and home chargers at different times on weekdays and weekends. The simulation shows that under the EV charging time-of-use price mechanism with a 50% price increase during peak hours and a 50% price reduction during valley hours, the total power cost of Beijing-West Inner Mongolia power systems is reduced by 302.3 million CNY compared with the current scenario. The average peak-valley difference of thermal power output can also be reduced by 11.7% on weekdays.
In China, the high demand for electric vehicles (EVs) has led to a rapid increase in power lithium-ion battery (LIB) production, which has subsequently given rise to an explosive increase in the number of spent power LIBs. Comprehensive recycling, including recovery and reuse, is a promising development direction to obtain the maximum utilization of spent power LIBs. This article aims to review the current situation of the comprehensive recycling of spent LIBs in China. First, the valuable components of LIBs and issues involved in spent power LIBs are summarized to clarify the necessity for spent power LIB recycling. After that, the recycling process of spent power LIBs is discussed in three parts: pretreatment of spent power LIBs, recovery of separated materials, and reuse of spent power LIBs. The recovery of cathode material is fully discussed due to its higher recovery value compared to other components. Several technologies are examined in every step to explore the promising route in terms of environmental protection, technological innovation, and economic feasibility. Finally, an alternative recycling mode is proposed based on the comprehensive analysis of the challenges facing battery recycling.
We analyze households’ preferences for electric and hybrid cars in Istanbul. We apply an adaptive choice-based conjoint approach that adjusts the survey in real time according to respondents’ initial responses. We find a low potential for electric cars but a significant latent demand for hybrid cars. Among the three urban policies considered, it is more effective to subsidize parking of electric cars and bridge and tunnel crossing fees of hybrid cars. Respondents’ valuations of these policies are about $2,070 in the life cycle of a car. We estimate that respondents are willing to pay $3.4, $14.8, and $20.7 to increase the driving range by 1 km for hybrid, conventional, and electric cars, respectively. They are willing to pay about $258 to decrease the recharge time of an electric car by 1 min or to make recharge stations more common so that their detour time to reach stations decreases by 1 min.
Hydrogen and fuel cells are getting increasing attention, and they are more widely used in the transportation sector. Meanwhile, hydrogen fuel cell heavy-duty trucks are also attracting people's attention. In this paper, people's tendency to adopt and the influencing factors of willingness-to-pay for hydrogen fuel cell heavy trucks are studied based on a choice experiment, and customers' willingness to pay is also analyzed. The results show that customers are not very willing to buy hydrogen fuel cell heavy-duty trucks, but the purchase price, fuel cost, environmental awareness, and the number of heavy-duty trucks purchased have a significant impact on the choice of participants. People's willingness to pay is 116,099–131,579 USD, more than 50% higher than diesel heavy trucks, and they are willing to pay no more than 1548 USD a year for maintenance. Based on this, the research will provide references for the formulation of manufacturers' production strategies, government subsidies policies and distributors' marketing plans.
Electric vehicles are expected to reduce transportation emissions. We design and allocate rebates and charging infrastructure investments to induce electric vehicle adoption and achieve emission reduction targets. A nonlinear mixed-integer mathematical model is proposed to optimize the investment allocation over a planning horizon. Logistic functions describe the vehicle demand driven by capital and ownership costs and network externalities. A simulated annealing algorithm is used to solve the nonlinear programming problem that is applied using data representative of the United States market. Our analysis indicates that rebates should be provided earlier than chargers due to neighborhood effects of electric vehicle adoption and the minimization of expenditure; availability of home charging influences consumers choice and the drivers electrified travel distance; rebates are more effective for modest drivers while charging stations should be prioritized for frequent drivers; network externalities should be further investigated because of their impact on electric vehicle demand.
Electrified vehicles have become a solution to greenhouse gas emissions. However, the diffusion of this sustainable transportation is slow, and consumer innovativeness is suggested to have a weak predictive power on electrified vehicle adoption. The aim of this study was to understand how consumer innovativeness and involvement may affect customers’ electrified vehicle purchase behavior. The results indicate that consumer innovativeness has less ability to predict electrified vehicle adoption. This finding offers insights for the formulation of marketing strategies on facilitating electrified vehicle adoption, which should focus on highly involved consumers with a high level of consumer innovativeness. This study highlights the importance of the role of personality traits and supports the proposition that of distinction between consumer innovativeness and involvement. This study focuses on the role of personality traits on consumers’ actual electrified vehicle adoption behavior rather than purchase intention.
The phenomenon of rise and fall in the ocean waters, called tides, is due to the attractive forces between the celestial bodies; Sun, Earth and the Moon. When the ocean water rises to a maximum extent, it is called spring tide and when they fall off to the lowest possible extent, it is called neap tide. With progress in technology, the usage of electric and electronic devices is exponentially increasing and there is a need to produce extra power other than the existing, in order to meet the future demands. Tidal energy can be considered as one of the best existing source of renewable energies. Unlike the wind, solar, thermal energy etc., tidal energy is something that has a long term perspective and it can be forecasted more accurately. Tidal energy is clean and not depleting. Because of these features it is unique and suitable to use it as a power generating source in the future. There are various types of tidal power plants across the world with varying tidal elevation. Also, the method of conversion of tidal energy into electrical energy is site specific. But generally, the method followed for extracting energy from tides is similar to the conventional hydroelectric power plants. In this paper, the tides at some locations across the world and along the Indian coast, tidal power plants across the world, resource allocation of tidal power plants, advantages and disadvantages of tidal power will be reviewed from the literature.
Keywords: Tidal energy, tidal barrage, tidal stream, electrical energy.
The promotion of hybrid and electric vehicles (EVs) has been proposed as one promising solution for reducing transport energy consumption and mitigating vehicular emissions in China. In this study, the energy and environmental impacts of hybrid and EVs during 2010-2020 were evaluated through an energy conversion analysis and a life cycle assessment (LCA), and the per-kilometer energy consumptions of gasoline, coal, natural gas (NG), oil, biomass, garbage and electricity for EVs and HEVs were estimated. Results show that the EVs and HEVs can reduce the energy consumption of vehicles by national average ratios of 17%-19% and 30%-33%, respectively. The study also calculated the detailed emission factors of SO2, NOX, VOC, CO, NN3, PM10M, PM2.5, OC, EC, CO2, N2O, CH4, Pb and Hg. It is indicated that the HEVs can bring significant reductions of NOX, VOC and CO emissions and lesser decreases of SO2 and CO2 for a single vehicle. The EVs could decrease many of the VOC, NN3, CO and CO2 emissions, but increase the SO2, NOX and particles by 10.8-13.0, 2.7-2.9 and 3.6-11.5 times, respectively. In addition, the electricity sources had significant influence on energy consumption (EC) and emissions. A high proportion of coal-fired energy resulted in large ECs and emission factors. The total energy consumption and pollutants emission changes in 2015 and 2020 were also calculated. Based on the energy use and emission analysis of HEVs and EVs, it is suggested that EVs should be promoted in the regions with higher proportions of hydropower, natural gas-fired power and clean energy power, while HEVs can be widely adopted in the regions with high coal-fired power ratios. This is to achieve a higher energy consumption reduction and pollutant emission mitigation. Moreover, the results can also provide scientific support for the total amount control of regional air pollutants in China.
This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum simulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. No other book incorporates all these fields, which have arisen in the past 20 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
The scaling approach is a statistical estimation method which allows for differences in the amount of unexplained variation in different types of data which can then be used together in analysis. In recent years, this approach has been tested and recommended in the context of combining Stated Preference and Revealed Preference data. The paper provides a description of the approach and a historical overview. The scaling approach can also be used to identify systematic differences in the variance of choices within a single Stated Preference data set due to the way in which the hypothetical choice situations are presented or the responses are obtained. The paper presents the results of two case studies — one looking at rank order effect and the other at fatigue effect. Scale effects appear to exist in both cases: the amount of unexplained variance is shown to increase as rankings become lower, and as the number of pairwise choices completed becomes greater. The implications of these findings for the use of SP ranking tasks and repeated pairwise choice tasks are discussed.
In models with unobserved taste heterogeneity, distributional assumptions can be placed in two ways: (1) by specifying the
distribution of coefficients in the utility function and deriving the distribution of willingness to pay (WTP), or (2) by specifying the distribution of WTP and deriving the distribution of coefficients. In general the two approaches are equivalent, in that any mutually compatible
distributions for coefficients and WTP can be represented in either way. However, in practice, convenient distributions, such as normal or log-normal, are usually
specified, and these convenient distributions have different implications when placed on WTP’s than on coefficients. We compare models that use normal and log-normal distributions for coefficients (called models in
preference space) with models using these distributions for WTP (called models in WTP space). We find that the models in preference space fit the data better but provide less reasonable distributions of WTP than the models in WTP space. Our findings suggests that further work is needed to identify distributions that either fit better when applied in
WTP space or imply more reasonable distributions of WTP when applied in preference space.
Discrete choice models estimated using hypothetical choices made in a survey setting (i.e., choice experiments) are widely used to estimate the importance of product attributes in order to make product design and marketing mix decisions. Choice experiments allow the researcher to estimate preferences for product features that do not yet exist in the market. However, parameters estimated from experimental data often show marked inconsistencies with those inferred from the market, reducing their usefulness in forecasting and decision making. We propose an approach for combining choice-based conjoint data with individual-level purchase data to produce estimates that are more consistent with the market. Unlike prior approaches for calibrating conjoint models so that they correctly predict aggregate market shares for a "baseline" market, the proposed approach is designed to produce parameters that are more consistent with those that can be inferred from individual-level market data. The proposed method relies on a new general framework for combining two or more sources of individual-level choice data to estimate a hierarchical discrete choice model. Past approaches to combining choice data assume that the population mean for the parameters is the same across both data sets and require that data sets are sampled from the same population. In contrast, we incorporate in the model individual characteristic variables, and assert only that the mapping between individuals' characteristics and their preferences is the same across the data sets. This allows the model to be applied even if the sample of individuals observed in each data set is not representative of the population as a whole, so long as appropriate product-use variables are collected that can explain the systematic deviations between them. The framework also explicitly incorporates a model for the individual characteristics, which allows us to use Bayesian missing-data techniques to handle the situation where each data set contains different demographic variables. This makes the method useful in practice for a wide range of existing market and conjoint data sets. We apply the method to a set of conjoint and market data for minivan choice and find that the proposed method predicts holdout market choices better than a model estimated from conjoint data alone or a model that does not include demographic variables.
We assess the economic value of life-cycle air emissions and oil consumption from conventional vehicles, hybrid-electric vehicles (HEVs), plug-in hybrid-electric vehicles (PHEVs), and battery electric vehicles in the US. We find that plug-in vehicles may reduce or increase externality costs relative to grid-independent HEVs, depending largely on greenhouse gas and SO(2) emissions produced during vehicle charging and battery manufacturing. However, even if future marginal damages from emissions of battery and electricity production drop dramatically, the damage reduction potential of plug-in vehicles remains small compared to ownership cost. As such, to offer a socially efficient approach to emissions and oil consumption reduction, lifetime cost of plug-in vehicles must be competitive with HEVs. Current subsidies intended to encourage sales of plug-in vehicles with large capacity battery packs exceed our externality estimates considerably, and taxes that optimally correct for externality damages would not close the gap in ownership cost. In contrast, HEVs and PHEVs with small battery packs reduce externality damages at low (or no) additional cost over their lifetime. Although large battery packs allow vehicles to travel longer distances using electricity instead of gasoline, large packs are more expensive, heavier, and more emissions intensive to produce, with lower utilization factors, greater charging infrastructure requirements, and life-cycle implications that are more sensitive to uncertain, time-sensitive, and location-specific factors. To reduce air emission and oil dependency impacts from passenger vehicles, strategies to promote adoption of HEVs and PHEVs with small battery packs offer more social benefits per dollar spent.
Vehicles that can run on both electricity and gasoline—so-called plug-in hybrid electric vehicles (PHEVs)—are proposed as both a near-term technology to achieve energy and environmental goals and a transitional step toward viable all-electric vehicles addressing many of the same goals. Whether PHEVs meet any of their goals depends not only on their design and performance on standardized drive cycles, but also on drivers’ travel and refueling/recharging behaviors. To replace assumptions with observations of potential PHEV drivers’ behavior in market and impact analyses, we conducted an internet-based survey of 2,373 new car-buying households in the United States. The instrument was implemented in three separate pieces, requiring multiple days for households to answer questions, conduct a review of their own driving and parking patterns, and then complete a sequence of PHEV design exercises. In this paper, we draw five conclusions from the resulting data. First, most new vehicle buyers are unaware of PHEVs in particular and are confused about electric-drive terminology commonly used by experts. Second, at least half of our target population is already equipped for at-home vehicle recharging, but currently have little opportunity for recharging at their workplace or other locations. Third, we observed widely varied interests in four possible PHEV attributes—fuel economy in both charge-depleting (CD) and charge sustaining (CS) operation, blended vs. all-electric operation, the distance over which the vehicle is in CD mode, and recharging speed. Still, the appeal of increased fuel economy appears to be highest and that of faster recharging to be lowest. Further, there is little interest in all-electric operation. Fourth, given the previous two points, we estimate that about a third of the target population has both the infrastructure to recharge a PHEV and interest in a vehicle with plug-in capabilities. Fifth, our recharge scenarios de
This paper develops new techniques for empirically analyzing demand and supply in differentiated products markets and then applies these techniques to analyze equilibrium in the U.S. automobile industry. Our primary goal is to present a framework which enables one to obtain estimates of demand and cost parameters for a broad class of oligopolistic differentiated products markets. These estimates can be obtained using only widely available product-level and aggregate consumer-level data, and they are consistent with a structural model of equilibrium in an oligopolistic industry. When we apply the techniques developed here to the U.S. automobile market. we obtain cost and demand parameters for (essentially) all models marketed over a twenty year period.
The 2002 Annual Energy Review published by Japan Energy Society consists of 81 articles covering the following subjects: present situation in energy supply and demand, including trends in energy supply and demand, trends in businesses related to energy supply and demand, energy conversion (petroleum refining, electric power generation, city gas, LPG, and cokes), energy consuming industries (metallurgy, petrochemistry, transportation, cement manufacture, and paper pulp production); trends in development and study of methods of using energy resources, such as petroleum, coal, natural gas, atomic power, natural energy (hydro-, solar, geothermal, wind, ocean, and biomass), energy from waste materials, and secondary energy sources, such as hydrogen and alcohol; trends in development and studies of energy conversion techniques, including combustion theory (solid, liquid, and gas combustion), trends in boilers (boilers for steam power generation, general industrial boilers, and marine boilers), trends in industrial furnaces, trends in engines, trends in heat energy systems ( co-generation and heat pump), and trends in highly efficient electric power generation, including MHD generator, fuel cells (phosphoric acid fuel cells, high temperature fuel cells, solid high-molecular fuel cells), fluidized bed combustion, gas turbine power generation, super-critical pressure power generation, electric power transmission and storage; environment, including environmental problems trends in global and national scales and trends in developing environment protection techniques; energy related standards (JIS and ISO); and list of national meetings related to energy and environment.
The global locus of manufacturing has been changing dramatically over the last three decades, driven by industrializing nations, most prominently China. Classical economics suggests that global productivity gains achieved by shifting the location of manufacturing will outweigh the losses ( 1 ). But shifts in the global locus of manufacturing may affect not just production costs, but the nature and pace of technological change.
We assess existing and potential charging infrastructure for plug-in vehicles in US households using data from the American Housing Survey and the Residential Energy Consumption Survey. We estimate that less than half of US vehicles have reliable access to a dedicated off-street parking space at an owned residence where charging infrastructure could be installed. Specifically, while approximately 79% households have off-street parking for at least some of their vehicles, only an estimated 56% of vehicles have a dedicated off-street parking space – and only 47% at an owned residence. Approximately 22% vehicles currently have access to a dedicated home parking space within reach of an outlet sufficient to recharge a small plug-in vehicle battery pack overnight. Access to faster charging, required for vehicles with longer electric range, will usually require infrastructure investment ranging from several hundred to several thousand dollars, depending on panel and construction requirements. We discuss sensitivity of results to uncertain factors and implications for the potential of mainstream penetration of plug-in vehicles.
Recent Chinese economic and energy policies recognize the transportation sector as a key element in the nation's effort to meet its energy and air quality goals. The development of alternative fuel vehicle (AFV) has been considered as a particularly promising strategy. AFV-related policies can be traced back to the eighth Five-Year Plan period (i.e., 1991–1995). All the work during the last twenty years has cumulatively prompted the transition of AFV development from policy-making to actual implementation and from research and development (R&D) to mass production. The year of 2009 is significant for the AFV industry in China in that the central government announced the “Plan on Shaping and Revitalizing the Auto Industry”. This Plan launched a demonstration program of electric vehicle (EV) deployment in 13 Chinese cities and set the national goal of manufacturing 0.5 million AFVs in three years. To better understand the current status, problems and uncertainties existed in the EV deployment in China, this paper reviewed the relevant policies and reported a survey with the pilot cities during the summer of 2009. Based on the survey findings, this paper developed a number of recommendations to help address the issues found in the demonstration program to date.
Previous models of auto-type choice have not been able to disentangle very much of the structure of the household's auto-choice decision: the models assumed that very few auto characteristics affect choice, and often these few parameters were estimated with low precision. Hence the models had only limited use in forecasting the effects of government policies to influence transportation energy consumption. The present paper introduces a multinomial logit model for the type of car that households will choose to buy. The model includes a large variety of auto characteristics as explanatory variables, as well as a large number of characteristics of the household and the driving environment. The model fits the data quite well, and all of the variables enter with the correct signs and plausible magnitudes.
In this paper, we develop a methodology for estimating marginal emissions of electricity demand that vary by location and time of day across the United States. The approach takes account of the generation mix within interconnected electricity markets and shifting load profiles throughout the day. Using data available for 2007 through 2009, with a focus on carbon dioxide (CO2), we find substantial variation among locations and times of day. Marginal emission rates are more than three times as large in the upper Midwest compared to the western United States, and within regions, rates for some hours of the day are more than twice those for others. We apply our results to an evaluation of plug-in electric vehicles (PEVs). The CO2 emissions per mile from driving PEVs are less than those from driving a hybrid car in the western United States and Texas. In the upper Midwest, however, charging during the recommended hours at night implies that PEVs generate more emissions per mile than the average car currently on the road. Underlying many of our results is a fundamental tension between electricity load management and environmental goals: the hours when electricity is the least expensive to produce tend to be the hours with the greatest emissions. In addition to PEVs, we show how our estimates are useful for evaluating the heterogeneous effects of other policies and initiatives, such as distributed solar, energy efficiency, and real-time pricing.
The Transportation Energy Data Book: Edition 30 is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Program. Designed for use as a desk-top reference, the Data Book represents an assembly and display of statistics and information that characterize transportation activity, and presents data on other factors that influence transportation energy use. The purpose of this document is to present relevant statistical data in the form of tables and graphs. The latest edition of the Data Book is available to a larger audience via the Internet (cta.ornl.gov/data). This edition of the Data Book has 12 chapters which focus on various aspects of the transportation industry. Chapter 1 focuses on petroleum; Chapter 2 energy; Chapter 3 highway vehicles; Chapter 4 light vehicles; Chapter 5 heavy vehicles; Chapter 6 alternative fuel vehicles; Chapter 7 fleet vehicles; Chapter 8 household vehicles; Chapter 9 nonhighway modes; Chapter 10 transportation and the economy; Chapter 11 greenhouse gas emissions; and Chapter 12 criteria pollutant emissions. The sources used represent the latest available data. There are also three appendices which include detailed source information for some tables, measures of conversion, and the definition of Census divisions and regions. A glossary of terms and a title index are also included for the reader s convenience.
This study investigates how the introduction of electric vehicles may influence the usage of existing cars. A survey of 250 households in South Korea, Korea is used to analyze a future automobile market that includes electric vehicles taking into account the heterogeneity of consumer preferences and usage patterns. Based on consumer preferences, the future market share of various vehicles is estimated and the impact of promoting the usage of electric vehicles by government subsidization and tax incentives is analyzed.
Previous conjoint choice design construction procedures have produced a single homogeneous design that is administered to all study participants. In contrast, this article proposes to construct a limited set of different designs. The principle of heterogeneous designs is applicable to a variety of types of models. This article illustrates this principle for Bayesian designs, taking into account prior uncertainty about the parameter values, and for mixed logit designs that accommodate respondent heterogeneity. The authors develop and investigate a computational procedure that enables quick and easy implementation. Although the number of different designs in the optimal set is small, the authors use a Monte Carlo study to demonstrate that their heterogeneous design achieves substantial gains in efficiency compared with homogeneous designs.
Plug-in hybrid electric vehicles (PHEVs) are being developed for mass production by the automotive industry. PHEVs have been touted for their potential to reduce the US transportation sector's dependence on petroleum and cut greenhouse gas (GHG) emissions by (1) using off-peak excess electric generation capacity and (2) increasing vehicles energy efficiency. A well-to-wheels (WTW) analysis - which examines energy use and emissions from primary energy source through vehicle operation - can help researchers better understand the impact of the upstream mix of electricity generation technologies for PHEV recharging, as well as the powertrain technology and fuel sources for PHEVs. For the WTW analysis, Argonne National Laboratory researchers used the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model developed by Argonne to compare the WTW energy use and GHG emissions associated with various transportation technologies to those associated with PHEVs. Argonne researchers estimated the fuel economy and electricity use of PHEVs and alternative fuel/vehicle systems by using the Powertrain System Analysis Toolkit (PSAT) model. They examined two PHEV designs: the power-split configuration and the series configuration. The first is a parallel hybrid configuration in which the engine and the electric motor are connected to a single mechanical transmission that incorporates a power-split device that allows for parallel power paths - mechanical and electrical - from the engine to the wheels, allowing the engine and the electric motor to share the power during acceleration. In the second configuration, the engine powers a generator, which charges a battery that is used by the electric motor to propel the vehicle; thus, the engine never directly powers the vehicle's transmission. The power-split configuration was adopted for PHEVs with a 10- and 20-mile electric range because they require frequent use of the engine for acceleration and to provide energy when the battery is depleted, while the series configuration was adopted for PHEVs with a 30- and 40-mile electric range because they rely mostly on electrical power for propulsion. Argonne researchers calculated the equivalent on-road (real-world) fuel economy on the basis of U.S. Environmental Protection Agency miles per gallon (mpg)-based formulas. The reduction in fuel economy attributable to the on-road adjustment formula was capped at 30% for advanced vehicle systems (e.g., PHEVs, fuel cell vehicles [FCVs], hybrid electric vehicles [HEVs], and battery-powered electric vehicles [BEVs]). Simulations for calendar year 2020 with model year 2015 mid-size vehicles were chosen for this analysis to address the implications of PHEVs within a reasonable timeframe after their likely introduction over the next few years. For the WTW analysis, Argonne assumed a PHEV market penetration of 10% by 2020 in order to examine the impact of significant PHEV loading on the utility power sector. Technological improvement with medium uncertainty for each vehicle was also assumed for the analysis. Argonne employed detailed dispatch models to simulate the electric power systems in four major regions of the US: the New England Independent System Operator, the New York Independent System Operator, the State of Illinois, and the Western Electric Coordinating Council. Argonne also evaluated the US average generation mix and renewable generation of electricity for PHEV and BEV recharging scenarios to show the effects of these generation mixes on PHEV WTW results. Argonne's GREET model was designed to examine the WTW energy use and GHG emissions for PHEVs and BEVs, as well as FCVs, regular HEVs, and conventional gasoline internal combustion engine vehicles (ICEVs). WTW results are reported for charge-depleting (CD) operation of PHEVs under different recharging scenarios. The combined WTW results of CD and charge-sustaining (CS) PHEV operations (using the utility factor method) were also examined and reported. According to the utility factor method, the share of vehicle miles traveled during CD operation is 25% for PHEV10 and 51% for PHEV40. Argonne's WTW analysis of PHEVs revealed that the following factors significantly impact the energy use and GHG emissions results for PHEVs and BEVs compared with baseline gasoline vehicle technologies: (1) the regional electricity generation mix for battery recharging and (2) the adjustment of fuel economy and electricity consumption to reflect real-world driving conditions. Although the analysis predicted the marginal electricity generation mixes for major regions in the United States, these mixes should be evaluated as possible scenarios for recharging PHEVs because significant uncertainties are associated with the assumed market penetration for these vehicles. Thus, the reported WTW results for PHEVs should be directly correlated with the underlying generation mix, rather than with the region linked to that mix.
Stated choice surveys are used extensively in the study of choice behaviour across many different areas of research, notably in transport. One of their main characteristics in comparison with most types of revealed preference (RP) surveys is the ability to capture behaviour by the same respondent under varying choice scenarios. While this ability to capture multiple choices is generally seen as an advantage, there is a certain amount of unease about survey length. The precise definition about what constitutes a large number of choice tasks however varies across disciplines, and it is not uncommon to see surveys with up to twenty tasks per respondent in some areas. The argument against this practice has always been one of reducing respondent engagement, which could be interpreted as a result of fatigue or boredom, with frequent reference to the findings of Bradley & Daly (1994) who showed a significant drop in utility scale, i.e. an increase in error, as a respondent moved from one choice experiment to the next, an effect they related to respondent fatigue. While the work by Bradley & Daly has become a standard reference in this context, it should be recognised that not only was the fatigue part of the work based on a single dataset, but the state-of-the-art and the state-of-practice in stated choice survey design and implementation has moved on significantly since their study. In this paper, we review other literature and present a more comprehensive study investigating evidence of respondent fatigue across a larger number of different surveys. Using a comprehensive testing framework employing both Logit and mixed Logit structures, we provide strong evidence that the concerns about fatigue in the literature are possibly overstated, with no clear decreasing trend in scale across choice tasks in any of our studies. For the data sets tested, we find that accommodating any scale heterogeneity has little or no impact on substantive model results, that the role of constants generally decreases as the survey progresses, and that there is evidence of significant attribute level (as opposed to scale) heterogeneity across choice tasks.
This paper empirically examines the determinants of the demand for alternative energy sources and propulsion technologies in vehicles. The data stem from a stated preference discrete choice experiment with 598 potential car buyers. In order to simulate a realistic automobile purchase situation, seven alternatives were incorporated in each of the six choice sets, i.e. hybrid, gas, biofuel, hydrogen, and electric as well as the common fuels gasoline and diesel. The vehicle types were additionally characterized by a set of attributes, such as purchase price or motor power. Besides these vehicle attributes, our study particularly considers a multitude of individual characteristics, such as socio-demographic and vehicle purchase variables. The econometric analysis with multinomial probit models identifies some population groups with a higher propensity for alternative energy sources or propulsion technologies in vehicles, which can be focused by policy and automobile firms. For example, younger people and people who usually purchase environment-friendly products have a higher stated preference to purchase biofuel, hydrogen, and electric automobiles than other population groups. Methodologically, our study highlights the importance of the inclusion of taste persistence across the choice sets. Furthermore, it suggests a high number of random draws in the Geweke-Hajivassiliou-Keane simulator, which is incorporated in the simulated maximum likelihood estimation and the simulated testing of statistical hypotheses.
This paper examines the effects of the Corporate Average Fuel Efficiency standards (CAFE) on the automobile product mix, prices and fuel consumption First a discrete choice model of automobile demand and a continuous model of vehicle use are estimated using micro data from the Consumer Expenditure Survey for 1984-1990. Next, the demand side model is combined with a model of oligopoly and product differentiation on the supply side. After estimating the demand and supply parameters, the effects of the CAFE regulation are assessed through simulations and compared to the effects of alternative policy instruments such as a powerful gas guzzler tax and an increase in the gasoline tax. Our results are as follows: Vehicle use is in the short run unresponsive to fuel cost changes; vehicle purchases, however, respond to both car prices and fuel cost. These results taken together imply that (1) contrary to the CAFE opponents' claims, higher fleet fuel efficiency is not neutralized by increased driving, and (2) policies to reduce fuel consumption by shifting the composition of the car fleet towards more fuel efficient vehicles are more promising than policies that target utilization. Policies with compositional effects operate through two channels: changes in vehicle prices and in operating costs. Contrary to environmental groups' claims, our results do not indicate the existence of consumer myopia. Still, we find the gasoline tax increase necessary to achieve fuel consumption reductions equivalent to the ones currently achieved through CAFE is 780%; whether an increase of this size is politically feasible is questionable. Our results indicate that the CAFE regulation reduced fuel consumption but shifts in the classification of products as domestic vs. imports weakened the effectiveness of the standards.
We develop a consumer-level model of vehicle choice to shed light on the erosion of the U.S. automobile manufacturers' market share during the past decade. We examine the influence of vehicle attributes, brand loyalty, product line characteristics, and dealerships. We find that nearly all of the loss in market share for U.S. manufacturers can be explained by changes in basic vehicle attributes, namely: price, size, power, operating cost, transmission type, reliability, and body type. U.S. manufacturers have improved their vehicles' attributes but not as much as Japanese and European manufacturers have improved the attributes of their vehicles.
There is growing interest in reducing emissions from electricity generation in the United States (U.S.). Renewable energy, energy efficiency, and energy conservation are all commonly suggested solutions. Both supply- and demand-side interventions will displace energy-and emissions-from conventional generators. Marginal emissions factors (MEFs) give a consistent metric for assessing the avoided emissions resulting from such interventions. This paper presents the first systematic calculation of MEFs for the U.S. electricity system. Using regressions of hourly generation and emissions data from 2006 through 2011, we estimate regional MEFs for CO(2), NO(x), and SO(2), as well as the share of marginal generation from coal-, gas-, and oil-fired generators. Trends in MEFs with respect to system load, time of day, and month are explored. We compare marginal and average emissions factors (AEFs), finding that AEFs may grossly misestimate the avoided emissions resulting from an intervention. We find significant regional differences in the emissions benefits of avoiding one megawatt-hour of electricity: compared to the West, an equivalent energy efficiency measure in the Midwest is expected to avoid roughly 70% more CO(2), 12 times more SO(2), and 3 times more NO(x) emissions.
In this paper, we develop a general random utility framework for analyzing data on individuals’ rank-orderings. Specifically, we show that in the case with three alternatives one can express the probability of a particular rank-ordering as a simple function of first choice probabilities. This framework is applied to specify and estimate models of household demand for conventional gasoline cars and alternative fuel vehicles in Shanghai based on rank-ordered data obtained from a stated preference survey. Subsequently, the framework is extended to allow for random effects in the utility specification to allow for intrapersonal correlation in tastes across stated preference questions. The preferred model is then used to calculate demand probabilities and elasticities and the distribution of willingness-to-pay for alternative fuel vehicles.
Using coal to produce transportation fuels could improve the energy security of the United States by replacing some of the demand for imported petroleum. Because of concerns regarding climate change and the high greenhouse gas (GHG) emissions associated with conventional coal use, policies to encourage pathways that utilize coal for transportation should seek to reduce GHGs compared to petroleum fuels. This paper compares the GHG emissions of coal-to-liquid (CTL) fuels to the emissions of plug-in hybrid electric vehicles (PHEV) powered with coal-based electricity, and to the emissions of a fuel cell vehicle (FCV) that uses coal-based hydrogen. A life cycle approach is used to account for fuel cycle and use-phase emissions, as well as vehicle cycle and battery manufacturing emissions. This analysis allows policymakers to better identify benefits or disadvantages of an energy future that includes coal as a transportation fuel. We find that PHEVs could reduce vehicle life cycle GHG emissions by up to about one-half when coal with carbon capture and sequestration is used to generate the electricity used by the vehicles. On the other hand, CTL fuels and coal-based hydrogen would likely lead to significantly increased emissions compared to PHEVs and conventional vehicles using petroleum-based fuels.
We compare multinomial logit and mixed logit models for data on California households' revealed and stated preferences for automobiles. The stated preference (SP) data elicited households' preferences among gasoline, electric, methanol, and compressed natural gas vehicles with various attributes. The mixed logit models provide improved fits over logit that are highly significant, and show large heterogeneity in respondents' preferences for alternative-fuel vehicles. The effects of including this heterogeneity are demonstrated in forecasting exercises. The alternative-fuel vehicle models presented here also highlight the advantages of merging SP and revealed preference (RP) data. RP data appear to be critical for obtaining realistic body-type choice and scaling information, but they are plagued by multicollinearity and difficulties with measuring vehicle attributes. SP data are critical for obtaining information about attributes not available in the marketplace, but pure SP models with these data give implausible forecasts.
We describe and apply choice models, including generalizations of logit called "mixed logits, " that do not exhibit the restrictive "independence from irrelevant alternatives" property and can approximate any substitution pattern. The models are estimated on data from a stated-preference survey that elicited customers ’ preferences among gas, electric, methanol, and CNG vehicles with various attributes. ACKNOWLEDGEMENTS: David Bunch and Tom Gollob collected the data and conducted preliminary analyses upon which our analysis relies. We are grateful to them for allowing us to use the data. They are not, of course, responsible for any errors or representations that we make
This paper brings together several research streams and concepts that have been evolving in random utility choice theory: (1) it reviews the literature on stated preference (SP) elicitation methods and introduces the concept of testing data generation process invariance across SP and revealed preference (RP) choice data sources; (2) it describes the evolution of discrete choice models within the random utility family, where progressively more behavioural realism is being achieved by relaxing strong assumptions on the role of the variance structure (specifically, heteroscedasticity) of the unobserved effects, a topic central to the issue of combining multiple data sources; (3) particular choice model formulations incorporating heteroscedastic effects are presented, discussed and applied to data. The rich insights possible from modelling heteroscedasticity in choice processes are illustrated in the empirical application, highlighting its relevance to issues of data combination and taste heterogeneity.