Vehicle Sales Research Articles

Sport utility vehicles and willingness-to-downsize: A mixed-method exploration of functional, symbolic, and societal consumer perceptions in Canada

The growing share of sport utility vehicles (SUVs) in the passenger market is challenging various sustainability and decarbonization goals. In our case study of Canada, SUVs and pickup trucks made up 80% of new vehicle sales in recent years. In this paper, we explore what motivates consumer interest in purchasing SUVs, and their “willingness-to-downsize” to a car. We employ a framework that considers functional, symbolic, and societal perceptions of SUVs. Our mixed-methods approach includes quantitative insights from a survey of Metro Vancouver citizens (n = 986), and qualitative insights from a subset of those individuals via six focus groups (n = 37). We find that SUV drivers view their vehicles as functionally superior to smaller cars in terms of safety, space for lifestyle, handling, and fun. Symbolically, SUVs are seen as a “status symbol” that can communicate a number of images, such as being “successful”. SUV drivers are more likely to see these vehicles as common and “approved” in their social networks, and tend to downplay any negative societal impacts such as increased GHG emissions. Across respondents intending to buy an SUV, willingness-to-downsize to a smaller vehicle was highest under financial incentives (for buying or using a car) or disincentives (for buying or using an SUV). Multivariate analysis confirms that SUV interest and willingness-to-downsize are associated with functional, symbolic, and societal perceptions of SUVs. Results provide insights into the physical and social entrenchment of SUVs among drivers. Changing this trend will be difficult, and likely requires the use of strong policies.

Electric vehicle batteries for a circular economy: Second life batteries as residential stationary storage

By 2030 the sales of electric vehicles (EV) are set to increase 6 to 30 folds compared to the levels of 2019 thereby leading to an increase of discarded EV batteries. This creates a challenge to sustainably handle the waste by repurpose and recycling the EV batteries. In this paper, a method to analyze the usage of EV batteries throughout their life cycle in light of their contributions to a circular economy is proposed. The study is divided into two stages which are modelled with mixed-integer linear optimization. Stage 1 considers the optimal charging strategy for an EV and stage 2 represents the second-life of the EV battery as stationary energy storage in a residential building. Six scenarios were created for both stages; stage 1 includes smart charging and/or Vehicle to Grid (V2G) and stage 2 adds demand side management and/or PV self-consumption maximization to stage 1. A sensitivity analysis is performed to assess the impact of electricity prices. The results are analysed to assess the operational lifetime and economic savings for an EV owner. The results show that using second-life batteries in a residentail building can extend the lifetime of an EV battery by 3–5 years while allowing savings above 23%.

Impact of regional temperature on the adoption of electric vehicles: an empirical study based on 20 provinces in China.

The development of electric vehicles (EVs) is not only a necessary path for China to move from a big country to a powerful country in automobile industry, but also a strategic measure to achieve the goal of "peak carbon dioxide emissions" and "carbon neutrality." However, in the low and high temperature environment, EVs may face problems such as a large reduction in cruising range, slow charging and poor safety, which decrease the attractiveness of EVs to consumers and hinder the EV adoption. However, existing research rarely pays attention to the impact of temperature on the EV adoption. Based on the panel data of electric vehicle sales in 20 Chinese provinces from 2010 to 2018, this paper uses interaction fixed effect (FE) model to test the effect of temperature on the EV adoption and explains the causes of regional differences in EV adoption. The study has the following findings. Firstly, EV sales show an inverted U-shaped trend with the change of temperature. Secondly, compared to extreme high temperature, extreme low temperature has a greater negative impact on the EV adoption. Thirdly, the negative impact of extreme temperature on battery electric vehicles (BEVs) is greater than that of plug-in hybrid electric vehicles (PHEVs). Finally, temperature will make consumers' behavior adaptive by affecting their expectations. These findings can provide policy makers, department of urban planning and building, EV technology and quality inspection department, non-governmental organizations, and EV manufacturer, aiming at accelerating the market proliferation of EVs, with theoretical basis and targeted insights.

Selling electric vehicles: Experiences from vehicle salespeople in Sweden

Electric vehicles are capturing ever larger market shares of the new vehicle market in several large vehicle markets such as Europe and China. However, electric vehicles still only make up a small fraction of the total vehicle fleet. Much research has been focused on the perspective of existing or prospective adopters of Electric Vehicles. Less emphasis has been placed on intermediaries such as vehicle salespeople, who could be important mediators in the product matching process by providing helpful information, facilitating direct experience and directly influencing vehicle buyers' adoption decisions. This paper addresses this research gap using a qualitative investigation of vehicle salespeople at OEMs who sell both Electric Vehicles and Internal Combustion Engine Vehicles on the Swedish market. Fifteen interviews with vehicle salespeople at leading OEMs were conducted in the fall of 2017. The results reveal that the sales process of vehicles is mainly focused on the sales of Internal Combustion Engine Vehicles. Electric Vehicles are treated as niche products which often require the vehicle buyer to initiate the sales process. It can be concluded that OEMs, dealerships and vehicle salespeople have taken relatively few steps to influence mainstream buyers to consider Electric Vehicles as an alternative to Internal Combustion Engine Vehicles at the point of sale. Possible reasons for the bias towards Internal Combustion Engine Vehicles can be found in the apparent lack of training and experience regarding Electric Vehicles among vehicle salespeople, more extended sales and delivery times for Electric Vehicles and a commission structure that often favours Internal Combustion Engine Vehicles.

Improvement of the Theoretical Model for Evaluating Evaporative Emissions in Parking and Refueling Events of Gasoline Fleets Based on Thermodynamics.

Evaporative emissions from gasoline vehicles are known as an emission source of volatile organic compounds that are the precursors of tropospheric ozone and secondary organic aerosols. We formulated new estimation models based on thermodynamics for two main evaporation processes, namely diurnal breathing loss (DBL) and refueling loss (RFL) from gasoline vehicles. The models enable us to evaluate real-world evaporative emissions using the fuel composition and environmental temperature as input parameters. The proposed models well replicated the experimental results of the canister breakthrough emission from DBL (DBLb) and RFL obtained in previous experimental studies. The evaporative DBLb and RFL emissions in Japan in 2015 were then estimated using the new models. The evaporative emission from DBLb was approximately 8800 t/y, and that from RFL was 73,300 t/y. In addition, we estimated the variation in fuel evaporative emissions due to the market penetration of zero-emission vehicles. Even if the sale of gasoline vehicles is banned from 2035, the evaporative emissions of DBLb and RFL from gasoline vehicles will only be halved after 2040. The two models proposed for estimating the DBLb and RFL in this study are expected to be applied in the evaluation of the emission inventories of volatile organic compounds in future work.

When will China's passenger vehicle sector reach CO2 emissions peak? A life cycle approach based on system dynamics

The Chinese automobile industry is taking steps to reduce sectoral carbon dioxide (CO 2 ) emissions by electrifying the passenger vehicle fleet in light of the carbon emission peak commitment. As most studies either focus on the fuel use or apply static inputs, there is a lack of dynamic fleet-based analysis considering every life-cycle phase. In this study, a hybrid life-cycle assessment is combined with a system dynamics model to simulate changes in the number of vehicles in different life-cycle phases in order to produce a more accurate estimation of sectoral CO 2 emissions and the peak time for the passenger vehicle sector. The detailed data on vehicle sales, in use, and disposal is collected, and a scenario analysis is constructed, considering two crucial factors: the future market share of electric vehicles (EV) and projected improvements in fuel consumption. The results indicate that for different market shares, peak time is estimated to be between 2029 and 2031, with sectoral CO 2 emissions peak ranging from 1196 to 1253 million tons. However, if fuel consumption does not improve as in the real world, the passenger vehicle sector will be unable to reach the CO 2 emissions peak within the simulation period, ending up with 1513 million tons by 2035, despite the sectoral CO 2 emissions curve appearing smooth in the simulation period's final years. These findings suggest that the market share of EVs has a modest impact on CO 2 emissions, and fuel consumption is more crucial for achieving the peak. There is a need to establish a public platform to monitor the gap between certified and real-world fuel consumption.

The projection of electric vehicle population growth considering scrappage and technology competition: A case study in Shanghai

Electric vehicles (EV) are expected to see a rapid growth in next decades as a substantial measure to achieve global climate goal. This course will be an unprecedented event in the industry history, and it will inevitably influence and change the power grid and the transportation network. The projection of EV population is the basis to coordinate the development of EV and urban systems. This paper proposes a modified Bass diffusion model to fulfill this task. Firstly, advantages of Bass diffusion model are analyzed, while car scrappage and technology competition with internal combust engine vehicle (ICEV) are involved to improve the model. Secondly, performance of the proposed model is evaluated with actual data during 2006–2020, and the EV stock up to 2050 is projected with the assessment of uncertainties. Thirdly, the policy on license plate quota and the ban on ICEV sales are discussed through experiment simulation. In a standard growing mode, EV is expected to dominant the new sales market by 2030 in Shanghai, and to completely replace ICEV before 2050. This research can provide a reference for urban power-transportation integrated system planning, renewable energy consumption, and carbon reduction path design. • The Bass diffusion model is modified with car scrappage and technology competition. • Effects of the license plate quota and the fuel vehicle sales ban are discussed. • Data of a pilot city for electric vehicle applications are collected for modeling. • The EV population growth up to 2050 is described with discussion of uncertainties.

THE IDENTIFICATION OF INCOME CONTINGENT TRANSACTION IN LOCAL GOVERNMENT ENTITIES

This study is intended to identify contingent income transactions in local government entities. The research was conducted using qualitative methods through in-depth interviews and field observations. The key informants in this study were BPKAD staff in East Luwuk district. The results show that the local government revenue account indicated as a contingent transaction is due to a formal engagement through a contract or engagement. Recognition of revenue that is tied to the contact requires that new revenue be recognized if the engagement is fulfilled, but if it is not fulfilled, it cannot be recognized as revenue. The income transactions in question are; Road Lighting Tax Revenues, Land and Building Rights Acquisition Tax Revenues, Non-Rock Minerals Tax, Retribution Revenues, Other Legitimate Revenues include sales of official vehicles, late fees, receipt of health insurance), income Central transfer of funds for Special Allocations and Other Legislative income under regional grant agreements. The results of the identification are expected to be the basis of prudence for the management of regional assets transactions in recognizing income transactions in order to avoid future uncertainties which result in the resulting financial statements knowing the element of uncertainty

Power Quality Improvement for Vehicle-to-Grid and Grid-to-Vehicle Technology in a Microgrid

The demand for electric vehicles continues to grow, as evidenced by global sales of electric vehicles reaching 2.2 million in 2019 and more than doubling to 6.6 million in 2021. The rapid growth of renewable energies and electric vehicles (EVs) necessitates the use of microgrids, which are a promising solution to the problem of integrating large-scale renewables and EVs into the electric power system. Besides, the essential policy support provided by the government is an increase in the availability of public charging infrastructure for EVs. This research employs a fast-charging configuration of an off-board charger with DC energy transfer. Implementation of DC energy transfer for vehicle-to-grid and grid-to-vehicle technology in a microgrid due to DC charging’s unrestricted charger-rated power and rapid power transfer. However, the integration of EVs in the Microgrid system creates some operational challenges, which in this research are power quality issues such as harmonics in power systems that affect both utilities and consumers. The design models using the PI controller and the fuzzy controller based on MATLAB software are simulated to determine the control system’s effectiveness. These simulations assess the control system’s performance, and both approaches help improve the system’s performance power quality by minimizing the system’s total harmonic distortion (THD). According to the results, the fuzzy logic controller exceeded the traditional PI controller as demonstrated by minimizing the THD and also in terms of improving the waveform quality which achieved high accuracy with good performance. This research also utilized the fuzzy logic controller to control the power transfer between EVs and the microgrid, which differs from other research work, to achieve high system efficiency for the benefit of consumers.

Lithium production, electricity consumption, and greenhouse gas emissions: An imperious role of economic globalization

China has resorted to electric vehicles to tackle the Greenhouse gas emissions engendered through the transport sector. Despite the coronavirus pandemic in 2020, electric vehicle sales in China were 1.3 million, which accounts for an increment of 8% in comparison with 2019. It will attain a peak point in 2030, causing an incredible increase in electricity usage. Hence, this increase has sparked a new debate among energy management and environmental economics scholars, as China produces 65% of its electricity through coal. The on-hand investigation revealed the imperative impact of lithium production, electricity usage, and economic globalization on the carbon footprints calculated in China. Moreover, the environmental Kuznets curve (EKC) is also tested in this framework. The study found the imperious role of electricity usage and economic globalization in Greenhouse gas emissions in China. However, lithium production reported weak and inconsequential findings. Detailed policy inferences and long-term policy implications are discussed in the discussion and conclusion section, respectively.

Forecasting the development trend of new energy vehicles in China by an optimized fractional discrete grey power model

As an effective technology to reduce traffic pollution emissions, the new energy vehicle industry has developed rapidly in recent years, and the sales of new energy vehicles have doubled in 2021. Accurately forecasting methods provide important references for industrial policy deployment, infrastructure construction and energy demand estimation. In order to predict the development trend of China's new energy vehicle industry under the limited data samples, this paper proposes an optimized discrete grey power model to fit the nonlinear relationship between grey information factor and temporal factor. Firstly, the grey differential equation and its discrete form are directly constructed by using power accumulated data, which simplifies the integral solution process of the traditional grey power model. Secondly, fractional accumulation operator is introduced into the discrete model to ensure the new information priority of the original data. Then, the heuristic algorithm is used to accurately estimate the new parameters of the proposed model. Thirdly, the proposed discrete model is the unified form of two existing discrete grey power models, which expands the scope of modeling and has higher adaptability. Simulation experiments and two numerical cases are used to verify the effectiveness of the proposed method. Finally, the proposed method is used to predict the annual sales and ownership of new energy vehicles in China. The predicted results show that by 2025, China's new energy vehicle sales will reach 8.84 million, accounting for about 24% of the total vehicle sales, surpassing the industry development target (20%) set by the Chinese government.

Intelligent Vehicle Sales Prediction Based on Online Public Opinion and Online Search Index

Intelligent vehicles refer to a new generation of vehicles with automatic driving functions that is gradually becoming an intelligent mobile space and application terminal by carrying advanced sensors and other devices and using new technologies, such as artificial intelligence. Firstly, the traditional autoregressive intelligent vehicle sales prediction model based on historical sales is established. Secondly, the public opinion data and online search index data are selected to establish a sales prediction model based on online public opinion and online search index. Then, we consider the influence of KOL (Key Opinion Leader), a sales prediction model based on KOL online public opinion andonline search index is established. Finally, the model is further optimized by using the deep learning algorithm LSTM (Long Short-Term Memory network), and the LSTM sales prediction model based on KOL online public opinion and online search index is established. The results show that the consideration of the online public opinion and search index can improve the prediction accuracy of intelligent vehicle sales, and the public opinion of KOL plays a greater role in improving the prediction accuracy of sales than that of the general public. Deep learning algorithms can further improve the prediction accuracy of intelligent vehicle sales.

Reduce Transportation Costs Using the Milk-run System and Dynamo Stages in the Vehicle Manufacturing Industry

The vehicle manufacturing industry is one of the automotive industries in Indonesia that produces four-wheeled vehicles with the main product being cars. The vehicle manufacturing industry has several sub-companies including Vehicle Manufacturers (VM) and Vehicle Sales (VS). The VM industry is experiencing problems with rising transportation operating costs. The same thing is also experienced by the corporate company such as VS. In 2020, transportation operational costs incurred by the company exceed the target, which can cause losses for the company. The purpose of this study is to find the cause of the problem and improve the transportation operational costs that continue to increase so that the company gets a reduction in transportation costs. The implementation of the improvement concept is carried out using the Dynamo++ stages starting from pre-study until the implementation of improvements. Through improvements to the milk-run system, it was found that vehicle manufacturers and vehicle sales benefited from a reduction in transportation costs of 77,861 USD or a decrease of 79.3%.

Analyzing Factors Affecting Purchase Intention of Electric Vehicle in Indonesia; Moderation Role of Personal Innovativeness on Those Factors

Electric vehicles as a sustainable innovation have the potential to reduce CO2 emissions and fossil fuels consumption, it is expected to reduce greenhouse gas emissions caused by burning fossil energy. However, the reality is that until 2021 sales of electric vehicles in Indonesia have not reached the desired target. This study identified the factors that influence consumer intentions to adopt electric vehicles in Indonesia using the Combined Theory Acceptance Model-Theory of Planned Behavior (C-TAM-TPB). The result is perceived usefulness does not directly affect the purchase intention of electric vehicles but can affect indirectly together with perceived of ease of use and price value through attitudes. Attitudes, subjective norms, perceived behavioral control, environmental self-image, price value, and personal innovativeness positively as well as can decrease perceived risk to intention to buy electric vehicle and perceived risks and infrastructure barrier, negatively can affect the intention to buy electric vehicles in Indonesia. Keywords: electric vehicle; consumer behaviour; Theory Acceptance Model, Theory of Planned Behaviour, purchase intention

Recent Developments and Research Avenues for Polymers in Electric Vehicles.

Plastics have been an indispensable material of choice in automobiles with wide range of applications such as interior, exterior, under the hood, and lighting/wiring applications. The prime motive of inclusion of these materials is increase in fuel efficiency and reduction in carbon footprint by replacing the energy intensive metallic counterparts. The current decade i. e., the 2020s has seen a recent surge in the sales of electronic vehicles. Although these numbers are promising, the growth in the rest of the parts of the world is not encouraging. It is primarily due to the skepticism involving battery life and efficiency, profitability, and environmental footprint when compared to conventional and hybrid vehicles. Also, a more concerted effort is needed in the lagging areas in order to install the required infrastructure. The emergence of plastics in the development and acceptance of e-vehicles is going to be pivotal especially when the efficiency and profitability are considered as they give the required freedom to the engineers for the design and development of various parts and sizes by replacing the bulkier and more dense materials. Also, the research on bionanocomposites has received great interest from the research community due to their versatility in application along with their eco-friendly nature throughout the lifecycle starting from feedstock up to end-of-life treatment. This review paper will be one of its kind to present a critical review of the recent developments of polymers suitable for use in e-vehicles. Also, a comprehensive discussion comprising of newer research areas for polymers in their use for e-vehicles will be presented.

Empirical analysis of the depreciation of electric vehicles compared to gasoline vehicles

The depreciation pattern of passenger vehicles is an important input parameter for economic considerations of buyers and other stakeholders such as financial insti-tutions. Due to their technical specifications and uncertainties in their degradation and life expectancy, it seems plausible that electric vehicles depreciate differently to conventional vehicles. This paper contributes to existing research in the economics of electric vehicles by analyzing the depreciation of electric vehicles along several countries and segments and compares it to gasoline vehicles by empirical analysis of public available data of 24,000 used vehicle sales. The results show that vehicles have a degressive depreciation relationship over the age of the vehicle, but that elec-tric vehicles have a substantially higher depreciation of 1.16% per month (13.9% per annum) compared to gasoline vehicles with 0.87% per month (10.4% per annum). Consequently, research into the economics of vehicles and budgeting considerations should apply a different depreciation rate for electric vehicles than for conventional vehicles. The resulting difference in depreciation to gasoline vehicles imply adapta-tion in economic models of insurance and leasing companies and gives governments the opportunity to adapt subsidies for electric vehicles to become more efficient.

Let There Be Charge: Using Streetlights to Enable Vehicle Electrification

As electric vehicle (EV) adoption continues to grow, a significant investment in public charging infrastructure is needed. And investment in charging infrastructure is underway in parts of the country following targets set by the Biden Administration and American automakers for EVs to comprise up to 50 percent of new vehicle sales by 2030. This is in addition to the Infrastructure Investment and Jobs Act funding, which allocates $7.5 billion for programs and grants focused on expanding EV charging infrastructure, with a goal of reaching 500,000 public electric chargers in the United States.

Appropriate Taxes and Covid-19 Tax Insentives do Affect Purchasing Power of New Car?

This research based on increasing vehicle sales in South Tangerang Indonesia. The sample in this study was determined based on purposive sampling. The type of data used using primary data. The analysis used is multiple linear regression analysis. Regression testing shows that value added tax, sales tax on luxury goods, motor vehicle tax progressive rates and tax incentives have a simultaneous effect on consumer purchasing power. Partially, the value added tax and sales tax on luxury goods have no effect, while the progressive rate motor vehicle tax and tax incentives have an effect on consumer purchasing power. The influence of the two dependent independent variables on the variable as much as 27.8%, this needs to be added variables in further research.

How Has Covid-19 Impacted Mobility Preferences?

Abstract: Background: COVID19 has slowed down businesses, changed consumer behaviour, and shifted regulatory trends, bringing public life to a halt. It has had a substantial influence on mobility, as public transportation ridership has decreased and vehicle sales have decreased. As a result, the goal of this research is to determine whether there has been a shift in mobility preferences. Because discretionary users are more prone to demonstrate shifts, the focus of this report is on them. Methods: Potential respondents were sent a questionnaire with themes related to pre and post COVID travel choices, reduced trip frequency, and perceptions of various transportation modes via WRI's social media page and email. (n= 229) Limitations: Due to travel restrictions, the survey had to be conducted online. The sample is, hence, skewed towards high income, and salaried employees

The possibilities of GPF Surface modification in the aspect of micro-contaminants removal

The European Union Fit For 55 program plans to cease the production and sales of vehicles with the internal combustion engines in 2035, although fuel powered vehicles will remain on the road for many more years to come.The micro-contaminants (MC) in gasoline exhaust such as Polycyclic Aromatic Hydrocarbons (PAHs) and their derivatives, ions, metals and metalloids are highly toxic and carcinogenic.The gasoline particulate filter (GPF) is the most commonly used solution for solid particulate emission control. Studies show that use of the metals such as Cu, Co, Fe, Ni or Mn improves oxidation of MCs. The aim of this study is to review the knowledge about the gasoline particulate filters, their mechanisms of pollutants removal and to highlight the probable insufficiency in avoiding of hazardous micro-contaminants emission. The work also reviews some more important and relevant publications to the subject.