Relevant bibliographies by topics / Car price

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Car price'

Author: Grafiati
Published: 30 May 2022
Last updated: 31 May 2022

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Journal articles on the topic "Car price"

1

Gupta, Vaibhav, Sharma M.L, and Tripathi K.C. "USED CAR PRICE PREDICTION." International journal of multidisciplinary advanced scientific research and innovation 1, no. 10 (December 14, 2021): 256–62. http://dx.doi.org/10.53633/ijmasri.2021.1.10.005.

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Cars have become a necessity in this modern world. Every middle class family needs a vehicle or a mode of transport in order to move from one place to another. Not everyone is able to afford a new vehicle as they are costly and there’s an added cost of taxes and various other expenses by both the provider/company of the car as well as the government. Moreover, not every customer is sure of spending a sum of their wealth on a certain car. The product might not meet their needs. The solution to this problem of having a car despite not being able to afford one is met by buying and selling second hand cars. It has become its own market now. There are already numerous companies and websites and app based services that serve as a mediator or a platform for the dealing of second hand or used cars and other vehicles. Establishment of such places is easy but there is another problem that still remains- How to price the used car appropriately at a price comfortable for both the seller and the buyer? Luckily, the Used Car Price Prediction systems exist and can be developed. Users might think that it’s easy to determine the price of a used car, and whether there is even a need to have such a system. In truth, there are a lot of factors that are important in determining the price of a second hand vehicle. The quality of a vehicle deteriorates with age1 of course but that is not all. Every single vehicle is different even when it is manufactured and sold as a new product and even more so when the same vehicle is used over time. Different people may use their vehicles more or less depending on their everyday activity, making kilometers driven as one of the important factors for the price prediction. It is obvious that a vehicle which is driven for 2000 kilometers in 1 year would be priced less than a vehicle which has been driven for only 500 kilometers in 2 years. This is just one of the factors that determine the price of a used car. In our Car Price Prediction System, we have used the Year of Manufacturing (used to determine the age of the vehicle by subtracting this from the date of selling), the original maximum retail price of the vehicle (the price at which the vehicle was sold at from the manufacturing company/garage), the fuel type of the vehicle (Petrol, Diesel, CNG, Electric ; This affects the pricing severely as different fuel type engines have different prime performance periods and different rates of deterioration), Seller Type (Individual or Dealership), Transmission (Manual or Automatic), Number of past owners of the vehicle. Using all these factors2, we are going to determine which model is best to determine a price for the used vehicle. For the Car Price Prediction System, Regression models3are used since these models give the results as a continuous curve instead of a categorized value as a result. Due to this, we can use the continuous curve to determine an accurate price for each and every scenario which won’t be possible if the results obtained were in the form of a range. The final model of the system will implement the best suited algorithm and have a UI (User Interface) which make it possible for a user to be able to enter the values of these deciding factors and the system will predict the price for them. Keywords: Car price prediction, machine learning, regression analysis, linear regression, correlation analysis
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Dahiya, Himanshu, Chetan Aggarwal, Shubh Goyal, and Mini Agarwal. "USED CAR PRICE PREDICTION USING MACHINE LEARNING." International journal of multidisciplinary advanced scientific research and innovation 1, no. 10 (November 6, 2021): 246–51. http://dx.doi.org/10.53633/ijmasri.2021.1.10.002.

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Cars are an important asset and their importance has increased exponentially in our life. With the increase in the demand and growing needs, the production of cars has also increased. But due to inflation in the prices of new cars, there are people who still can only afford a used car due to their financial conditions. This whole process has given rise to the used car market, which is outperforming many other industries and is rising every day. The rising market for the used car has also resulted in a great increment in sales of Used Cars. Used Car Sales are on a global increase. But, determining the appropriate listing price of a used car is a challenging task, due to the many factors that drive prices of a used vehicle in the market. And that is why there is an urgent need for a system which can accurately predict the price of a used car. considering all the factors that affect the price of a used car. Keywords: Used Car Price Prediction, Linear Regression, XGBoost, Decision Tree
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Prieto, Marc. "Do Amateur Sellers Adopt The Professionals Price Ending Formats? Lessons From The Used Car Market." Journal of Applied Business Research (JABR) 30, no. 2 (February 27, 2014): 387. http://dx.doi.org/10.19030/jabr.v30i2.8408.

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This study investigates the differences between professional retailers and amateur resellers in their adoption of different price ending formats. We conduct our analysis on a 1,700 ads car pool representative of the French used car market to demonstrate how seller profiles and car attributes impact price ending formats adoption. The results reveal that amateur sellers are more likely to use round ending prices than professionals, especially for expensive and high mileage cars. Furthermore, product attributes (extras) and obsolescence indicators significantly moderate the choices of price ending formats.
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Yadav, Anu, Ela Kumar, and Piyush Kumar Yadav. "Object detection and used car price predicting analysis system (UCPAS) using machine learning technique." Linguistics and Culture Review 5, S2 (November 3, 2021): 1131–47. http://dx.doi.org/10.21744/lingcure.v5ns2.1660.

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The highly interesting research area that noticed in the last few years is object detection and find out the prediction based on the features that can be benefited to consumers and the industry. In this paper, we understand the concept of object detection like the car detection, to look into the price of a second-hand car using automatic machine learning methods. We also understand the concept of object detection categories. Nowadays, the most challenging task is to determine what is the listed price of a used car on the market, Possibility of various factors that can drive a used car price. The main objective of this paper is to develop machine learning models which make it possible to accurately predict the price of a second-hand car according to its parameter or characteristics. In this paper, implementation techniques and evaluation methods are used on a Car dataset consisting of the selling prices of various models of car across different cities of India. The outcome of this experiment shows that clustering with linear regression and Random Forest model yield the best accuracy outcome. The machine learning model produces a satisfactory result within a short duration of time compared to the aforementioned self.
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NEVEZHIN, V. P. "DETERMINING THE AVERAGE PRICE OF NEW CARS IN RUSSIA USING A DYNAMIC MODEL." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 1, no. 3 (2020): 32–38. http://dx.doi.org/10.36871/ek.up.p.r.2020.03.01.005.

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The article deals with the issues of sales in the passenger car market and the factors that influence these sales. The main trends of the automotive market of new cars are studied. The reasons that contribute to the growth of prices for new cars are determined. On the basis of statistical data on car prices for the last four years, an econometric model of the time series is constructed, taking into account seasonal changes in sales. The obtained model and its application possibilities for obtaining a forecast of the average price of a middle-class passenger car in the short term are considered. Based on this model, a forecast of the average price for four periods is made, which is confirmed by the actual values of prices for middle-class cars in 2019.
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Hayes, John. "What price the green car?" Reinforced Plastics 34, no. 4 (April 1990): 48. http://dx.doi.org/10.1016/0034-3617(90)90045-g.

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Salim, Fadzilah, and Nur Azman Abu. "A Novel S-Regression Model on an Auto Price." International Journal of Engineering & Technology 7, no. 2.29 (May 22, 2018): 912. http://dx.doi.org/10.14419/ijet.v7i2.29.14282.

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A simple linear regression model is useful in a prediction model. A general linear regression beyond a single independent variable is still not popular. A nonlinear regression can be easily produced a better predictive model but it is difficult to construct. The objective of this paper is to propose a technique for predicting the price of used cars in Malaysia using S-shaped curve model. In this paper, the S-shaped Membership Function [SMF] is used as the basis to develop a novel S-Regression model. Comparisons between linear regression, cubic regression and S-Regression have been made on the used car prices. The mean squared error of S-Regression model is found to be closer to cubic regression than the linear regression. S-Regression model is found to be quite suitable to represent the relationship between the price of a used car and the make year of a car. The result demonstrates that the S-Regression model gives better and practical estimate of the price of a used car in Malaysia.
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Taylor, Christina J., and Sharon M. Dawid. "Bargaining for a New Car: The Knowledgeable versus the Naive Consumer." Psychological Reports 59, no. 1 (August 1986): 284–86. http://dx.doi.org/10.2466/pr0.1986.59.1.284.

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A field experiment was conducted on the use of bargaining strategies for a new car. Confederates (3 men, 5 women) behaved as either knowledgeable or naive consumers in obtaining an initial price offer on a new Ford Mustang. In the knowledgeable consumer condition, confederates carried a price guide and asked the salesperson for a price offer on a Mustang with a specific set of options. In the naive consumer condition, the confederates did not carry a price guide and they asked the salesperson to review the available options. Each confederate obtained three price offers in each condition. As predicted, the prices obtained in the knowledgeable consumer condition were significantly lower than in the naive consumer condition.
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Jiang, Pingjun. "Exploring the Price Efficiency within Automotive Markets - An Application of Data Envelopment Analysis." International Journal of Market Research 51, no. 3 (January 2009): 1–18. http://dx.doi.org/10.1177/147078530905100305.

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Using a non-parametric data envelopment analysis (DEA) approach, this paper compares the price of each car model in a segment of the personal car market with the best possible price in view of the technology available given its particular combination of characteristics. In this approach, a car model is defined as price efficient if it offers customers the highest value per dollar spent for that set of characteristics. Likewise, a car model is inefficient if there is some other car model with a lower price having equivalent or higher quality, whereby a measure of the price efficiency is determined by the price reduction needed to make a car model efficient. The data set covers 141 different year 2002 car models. The vehicles that are listed by Edmunds.com as consumers’ most wanted are compared with those at the top of our efficiency list. It is found that the majority of cars at the top of the list are also listed as most wanted by Edmunds.com. Evidently, consumers who usually make decisions based on price and quality information will naturally employ a heuristic such as ‘buy car models at the top of price efficiency list’ if this list is made available to them.
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Setiadi, Jeremi Francis, and Tommy Setiawan Ruslim. "Pengaruh Citra Merek terhadap Niat Beli Konsumen (Studi pada Toyota Agya)." Jurnal Manajerial Dan Kewirausahaan 2, no. 3 (October 9, 2020): 603. http://dx.doi.org/10.24912/jmk.v2i3.9572.

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The purpose of this study is to determine whether 1) brand image significantly influences the consumer price of Toyota Agya cars. 2) brand image significantly influences the perceived quality of consumers of Toyota Agya cars. 3) perceived price significantly influences the purchase intention of Toyota Agya car consumers. 4) perceived quality significantly influences the purchase intention of Toyota Agya car consumers. 5) brand image significantly influences the purchase intention of Toyota Agya car consumers mediated by perceived price. 6) brand image significantly influences the purchase intention of Toyota Agya car consumers mediated by perceived quality. Sample was selected by convenience sampling method with a total of 100 samples. And the results of this study indicate that the brand image has a positive and significant effect on the perceived price and perceived quality of Toyota Agya car consumers, the perceived price has a positive but not significant effect on the purchase intention of Toyota Agya car consumers, perceived quality has a positive and significant effect on the purchase intention of Toyota car consumers Agya, brand image has a positive but not significant effect on consumer purchase intentions mediated by perceived prices, and brand image has a positive and significant effect on consumer purchase intentions mediated by perceived qualityTujuan dari penelitian ini adalah untuk mengetahui apakah 1) Brand image berpengaruh secara signifikan terhadap perceived price konsumen mobil Toyota Agya. 2) Brand image berpengaruh secara signifikan terhadap perceived quality konsumen mobil Toyota Agya. 3) Perceived price berpengaruh secara signifikan terhadap purchase intention konsumen mobil Toyota Agya. 4) Perceived quality berpengaruh secara signifikan terhadap purchase intention konsumen mobil Toyota Agya. 5) Brand image berpengaruh secara signifikan terhadap purchase intention konsumen mobil Toyota Agya yang dimediasi oleh perceived price. 6) Brand image berpengaruh secara signifikan terhadap purchase intention konsumen mobil Toyota Agya yang dimediasi oleh perceived quality. Sampel dipilih dengan metode convenience sampling dengan jumlah sebanyak 100 sampel. Dan hasil penelitian ini menunjukkan bahwa brand image berpengaruh positif dan signifikan terhadap perceived price dan perceived quality konsumen mobil Toyota Agya, perceived price berpengaruh positif tetapi tidak signifikan terhadap purchase intention konsumen mobil Toyota Agya, perceived quality berpengaruh positif dan signifikan terhadap purchase intention konsumen mobil Toyota Agya, brand image berpengaruh positif tetapi tidak signifikan terhadap purchase intention konsumen yang dimediasi oleh perceived price, dan brand image berpengaruh positif dan signifikan terhadap purchase intention konsumen yang dimediasi oleh perceived quality
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Dissertations / Theses on the topic "Car price"

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Castellucci, Davide. "Model for car brand classification and estimation of price tag." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022.

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Nowadays Machine Learning and Deep Learning are becoming more and more important for several problems in many fields. For this reason, we decide to use them for improving the results and the efficiency of different tasks as view understanding on cars, car’s brand and model classification, and price estimation. Behind defining and modifying the correct model for each problem we obtained very good results for each of them. This thesis will present them in detail and will point out possible future improvements.
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Shi, Zijun. "Airport charge, traffic volume and car rental price : empirical evidence at US airports." Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/48604.

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This paper examines the interaction among airport aeronautical charge, traffic volume, and car rental service charge by employing a cross-section dataset covering 337 airports in the United States. Other determinants of the aeronautical charge are also examined. Using the method of three stage least squares, the main empirical findings are: (1) Car rental price has no significant impact on passenger volume, indicating that rental cost, which is an important cost category of airport concessional goods, does not affect passenger volume of airport. (2) Car rental price has no significant effect on aeronautical charge. (3) Only rental price at airports with a very low transfer rate responds positively to passenger volume. Overall, rental price does not respond to passenger volume or aeronautical charge. (4) Aeronautical charge has a significant negative effect on passenger volume, but it has no significant effect on car rental price.
Business, Sauder School of
Graduate
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wood, warren. "A Look at How Timing Affects Price of Used Car Auctions on eBay Motors." Scholarship @ Claremont, 2015. http://scholarship.claremont.edu/cmc_theses/1079.

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This study looked at 7194 completed listing from eBay Motors. Each observation contained a make, model, year, mileage, seller feedback rating, selling price, time of day ended, day of the week auction ended, auction duration, number of bidders, and number of bids for a car that had been sold on eBay Motors between March 16th and April 5th. Using this information this study looked at how timing affected the selling price of each vehicle, while holding the other variables constant. The observations are split up into four different time periods of the day (times are in Pacific Standard Time): morning (3am-8:59pm), midday (9am-2:59pm), evening (3pm-8:59pm), and night (9pm-2:59am). The regression results show that the midday time period increases the selling price of the vehicle by an average of $1445.41 for this data set. This is likely because the demand and supply side of the eBay Motors market are most equivalent during this time period compared to the other time periods.
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Mertens, Yves. "Price discrimination and the effects of trade restrictions in the European car market, 1970-1985." Thesis, London School of Economics and Political Science (University of London), 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320718.

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Jiang, Jinyi. "An Econometric Analysis of Auction Price Results of the Shanghai Car License Plate from 2004 to 2018." Scholarship @ Claremont, 2019. https://scholarship.claremont.edu/cmc_theses/2207.

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This paper studies the effects of auction mechanisms on the average price of auction results of Shanghai car license plate from 2004 to 2018. We construct two linear regression models and find that an iterated multi-unit auction has a lower efficiency than a seal-bid discriminatory multi-unit auction. We also find that the pre-set price-ceiling is positively correlated with the average winning price. These results suggest that the government can potentially manipulate auction results through the design of the auction mechanism, and through the setting of warning price as a price ceiling.
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Pristachová, Lívia. "Marketingový mix prodejce a servisu automobilů Alcor Motors, s.r.o." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2015. http://www.nusl.cz/ntk/nusl-224953.

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The thesis is focused on the suggestion of using suitable tools of marketing mix for the car dealer and service Alcor Motors, s.r.o. It specifies concepts needed for understanding this issue. It analyzes recent situation on the market and in the surrounding of an organization. It evaluates an actual condition of Alcor Motors and present usage of marketing tools. Suggestions are also analyzed from the financial point of view.
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Малік, Тимур Імтіазович. "Статистична модель прогнозування вартості автомобіля за даними автомобільного ринку України." Bachelor's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/37545.

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Дипломна робота містить: 117 с., 13 табл., 29 рис., 2 дод. та 46 джерел. Об’єктом дослідження є вибірка даних вторинного автомобільного ринку України за 2020 рік. Предметом дослідження є методи інтелектуального аналізу даних на основі регресії з використанням дерев рішень. Програмною мовою обрано Python. Метою роботи є визначення найкращої моделі для виконання прогнозу ціни автомобіля використовуючи дані вторинного автомобільного ринку України. В роботі проведено дослідження застосування дерев рішень та різних методів, що засновуються на них в розглядаємій задачі при прогнозуванні на основі існуючих даних 2020 року. Виділено основні фактори, які впливають на ціну. У ході дослідження було встановлено, що метод випадкових лісів дає хороші результати на досліджуваних даних. Планується розвивати роботу у напрямку дослідження застосування даного методу з метою подальшого зменшення похибки прогнозування у різних задачах, пов’язаних з прогнозуванням цін не лише автомобілів, але і інших транспортних засобів.
The bachelors work consists of: 117 p., 13 tables, 29 fig., 2 add. and 46 references. The object of the study is a sample of data from the secondary automotive market of Ukraine for 2020. The subject of research is methods of data mining based on regression using decision trees. Python is selected as the programming language. The aim of the work is to determine the best model for forecasting the price of a car using data from the secondary car market of Ukraine. The study of the application of decision trees and various methods based on them in this problem in forecasting based on existing data for 2020. The main factors that affect the price are highlighted. In course of the study, it was found that the method of random forests gives good results on the studied data. It is planned to develop work in the direction of research on the application of this method in order to further reduce the forecasting error in various tasks related to forecasting the prices not only of cars but also of other vehicles.
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Brožová, Dominika. "Vyvíjí se prodeje nových osobních automobilů procyklicky? Analýza determinant korporátní a retailové poptávky v ČR a SR." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-201856.

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The thesis is focused on verifying the pro-cyclical relationship of sales of new passenger cars in the Czech Republic and Slovakia and the subsequent evaluation of the impact of macroeconomic variables in the period from the first quarter of 2005 to the third quarter of 2015. In total, there are four different models estimated of multiple linear regressions of car sales, where for the Czech R. the estimation of different sectors of households and firms is available as well. By comparing the Czech R. and Slovakia regarding aggregate sales, fuel prices and gross domestic products are especially crucial and the pro-cyclical relationship is successfully verified. The economic crisis at the turn of 2008-2009 hit especially Slovakia, while the effect in the Czech R. was offset by a positive shock to fuel prices. For the model of households the procyclical relationship is denied unlike from the model of firms, shock to GDP therefore only deviate sales to firms. For Czech R. is also confirmed a significant relationship of the sales with interest rate or population growth.
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Al, Rahahleh Naseem. "Analyzing frequent acquires in emerging markets and futures markets linkage." ScholarWorks@UNO, 2009. http://scholarworks.uno.edu/td/915.

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The first chapter of this dissertation examines the returns to frequent acquirers from emerging markets and analyzes the cross-country variations in cumulative abnormal returns. The sample consists of 5,147 transactions carried out by firms from 17 common and civil-law countries during the period of January 1985 to June 2008. I find that the cumulative abnormal returns decline over the deal order and it is more pronounced in civil-law countries than in common-law countries. There is also evidence that the premiums paid by acquirers from civillaw countries with a first successful acquisition are higher than those from common-law countries. These findings are consistent with agency problems and the hubris hypothesis, first introduced by Roll (1986). The second chapter examines the information links across futures markets in different nations, using Vector Autoregressive (VAR)-Dynamic Conditional Correlation (DCC) model. The data comprise a large set of commodity and financial futures traded in U.S., U.K., China, Japan, Canada, and Brazil during the period from August 1998 to December 2008. The primary finding is that market interactions are relatively high for commodities for which information production generally is more diverse (metal commodities), while moderate for commodities for which information is more concentrated (agricultural commodities). Furthermore, the strength and persistence of interactions among futures markets decline after excluding the most informative markets. These findings indirectly support the breadth of information being a relevant factor in the extent of information linkage. The results also indicate that the dynamic correlation in futures markets is high in most commodity and financial futures if there is a significant bi-directional return and volatility spillover. Additionally, I estimate a market’s contribution to the price discovery process. In general, the market that has a stronger price impact and a stronger volatility spillover tends to be the market that has greater contribution or leadership in price discovery.
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Fuentes, Andrés. "Abolishing Stockholm’s Public Transport Fares." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-332459.

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The decrease of car emission levels has stagnated in the latter years in Stockholm, Sweden. Since the city’s publictransit system is highly developed via its large access to areas located in the city’s outskirts, it could serve as a tool topartially replace the city's car traffic and reduce emissions. This study therefore aims to examine expected travelbehavior changes from a fare-free public transport system and investigate potential limitations when increasing thepublic transport travel degree in Stockholm. The theoretical background consists of the mode choice theory thatdissects the reasons behind travel habits, and the zero-price effect which explains the effects from abolishing priceswhen purchasing a service product. The methodological approach was conducted through a random probabilitysurvey conducted in a face-to-face mix mode survey interviews in outdoor environments and via computer-assistedtelephone interviewing. The data was then analyzed through MS Excel and SPSS to extract patterns and correlations.The results thereafter implicated preferences from the survey participants implying their desire to primarily reduce orabolish the public transport fares, which would lead to significant travel habits changes among the majority ofrespondents. This would result in a high number of both frequent car drivers and frequent public transit commutersthat would commute more by public transit and drive less.
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Books on the topic "Car price"

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Ken, Buttolph, ed. Car memorabilia price guide. 2nd ed. Iola, WI: Krause Publications, 1997.

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Ken, Buttolph, ed. Car memorabilia price guide. Iola, WI: Krause Publications, 1996.

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Seton, Tony. Right car, right price. Carmel, Calif: Jamon Press, 1989.

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Earnest, Brian. 2016 collector car price guide. Iola, WI: Krause Publications, 2015.

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Earnest, Brian. 2015 collector car price guide. Iola, WI: Krause Publications, 2014.

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Izquierdo, Mario. Car quality improvements and price indices in Spain. [Madrid]: Banco de España, Servicio de Estudios, 2001.

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Pedal car restoration and price guide. Iowa, WI: Krause Publications, 1996.

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A, Clark John. HO slot car identification and price guide. Gas City, IN: L-W Book Sales, 1995.

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Goldberg, Pinelopi Koujianou. The evolution of price discrimination in the European car market. Cambridge, MA: National Bureau of Economic Research, 1998.

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Goldberg, Pinelopi Koujianou. The evolution of price discrimination in the European car market. Berlin: Wissenschaftszentrum für Sozialforschung, 1999.

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Book chapters on the topic "Car price"

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Tsagris, Michail, and Stefanos Fafalios. "Advanced Car Price Modelling and Prediction." In Contributions to Economics, 479–94. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85254-2_29.

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Ahtesham, Maida, and Javairia Zulfiqar. "Used Car Price Prediction with Pyspark." In Digital Technologies and Applications, 169–79. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-01942-5_17.

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Bouckaert, Jan, and Frank Verboven. "Price Differences and Price Setting in the European Car Market." In The Economic and Business Consequences of the EMU, 301–28. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-1383-4_12.

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Watts, Jonathan. "How Scratched Car Revealed the Price of a Peasant’s Life." In Performance and the Contemporary City, 26–27. London: Macmillan Education UK, 2010. http://dx.doi.org/10.1007/978-1-137-12006-9_2.

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Blankart, Charles B., and Jörg Finsinger. "Regulation-induced Price Instability in Swiss Motor Car Liability Insurance." In The Economics of Insurance Regulation, 200–211. London: Palgrave Macmillan UK, 1986. http://dx.doi.org/10.1007/978-1-349-18397-5_7.

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Morel, Stéphane, Nabila Iken, and Franck Aggeri. "Setting Internal Price of Environmental Criteria, the Good Way to Transform Organization?" In Towards a Sustainable Future - Life Cycle Management, 183–92. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77127-0_17.

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AbstractIn this communication, we present some lessons learned on the construction of an internal carbon price by businesses, based on the four-dimensional framework of the Carbon Disclosure Project. We illustrate the scheme with the example of a car manufacturer. Based on grey literature and the conclusions of exchanges with various companies, we discuss the different dimensions of the CDP framework within the scope of the automotive sector. We also analyse the various risk and success factors associated with the carbon pricing tool at organizational, tooling, business and cultural levels within a car manufacturer. We conclude that the carbon pricing tool requires many design choices and a reflection on the company’s objective regarding climate change mitigation.
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Abou-el-Enein, Mohamed, and Jordan Gauthier. "The Value of CAR-T-cell Immunotherapy in Cancer." In The EBMT/EHA CAR-T Cell Handbook, 231–34. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94353-0_46.

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AbstractThe development of genetically modified chimeric antigen receptor (CAR) T-cells to target cancer by conferring tumour antigen recognition has tremendously improved the fight against the disease and broadened treatment options for haematological malignancies (Elsallab et al. 2020b). However, in contrast to conventional drugs that patients can easily access, the implementation of CAR-T-cell therapy in routine clinical practice poses significant challenges. Access to CAR-T-cell products is currently limited to specific certified centres meeting the requirements set up by manufacturers and regulatory agencies. There are also issues regarding insurance coverage, reimbursement, affordability, and pricing, which have critical impacts on broadening patient access to these novel therapies (Abou-El-Enein et al. 2016a, b). Current list pricing ranges between $373,000 and $475,000 per one-time infusion for the four CAR-T-cell therapies currently approved by the FDA (tisagenlecleucel, Kymriah®; axicabtagene ciloleucel, Yescarta®; brexucabtagene autoleucel, Tecartus®; lisocabtagene maraleucel, Breyanzi®). In addition to the cost of the CAR-T-cell product, patient preparation (leukapheresis and/or lymphodepletion), product infusion, pre- and post-infusion patient management, and monitoring for side effects (Wagner et al. 2021) significantly add to the final price tag. There are calls for restructuring the current payment and reimbursement models to allow better access to CAR-T-cell therapies (Abou-El-Enein et al. 2014). However, this would only be possible after examining the strength of clinical evidence generated during product development (Abou-El-Enein and Hey 2019; Elsallab et al. 2020a) and, most importantly, by determining the value of CAR-T-cell therapy.
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Ruhnau, Thomas, and Thomas Peisl. "Risk Management through Flexible Capacity Allocation and Price Control – Auctions in the New Car Sales Process." In Supply Chain Safety Management, 357–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-32021-7_22.

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Homer, Alex. "Car Prices and Quotations." In Pro ASP.NET Web Forms Techniques, 429–70. Berkeley, CA: Apress, 2004. http://dx.doi.org/10.1007/978-1-4302-0662-0_10.

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Kriescher, Michael, Sebastian Scheibe, and Tilo Maag. "Development of the Safe Light Regional Vehicle (SLRV): A Lightweight Vehicle Concept with a Fuel Cell Drivetrain." In Small Electric Vehicles, 179–89. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65843-4_14.

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AbstractThe safe light regional vehicle (SLRV) concept was developed within the DLR project next-generation car (NGC). NGC SLRV addresses the safety concern of typical L7e vehicles. The SLRV is therefore specifically designed to demonstrate significant improvements to the passive safety of small vehicles. Another important goal of the NGC SLRV concept is to offer solutions to some of the main challenges of electric vehicles: to provide an adequate range and at the same time a reasonable price of the vehicle. In order to address these challenges a major goal of the concept is to minimize the driving resistance of the vehicle, by use of lightweight sandwich structures. A fuel cell drivetrain also helps to keep the overall size and weight of the vehicle low, while still providing sufficient range.
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Conference papers on the topic "Car price"

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Zhao, Yu, Yu Zhang, and Chunjie Qi. "The Interaction between Chinese Export Price and World Import Price of Tangerines." In 2009 International Asia Conference on Informatics in Control, Automation and Robotics (CAR). IEEE, 2009. http://dx.doi.org/10.1109/car.2009.36.

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Chen, Chuancan, Lulu Hao, and Cong Xu. "Comparative analysis of used car price evaluation models." In MATERIALS SCIENCE, ENERGY TECHNOLOGY, AND POWER ENGINEERING I: 1st International Conference on Materials Science, Energy Technology, Power Engineering (MEP 2017). Author(s), 2017. http://dx.doi.org/10.1063/1.4982530.

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Verdat Pazarlioglu, M., and M. Gunes. "The hedonic price model for fusion on car market." In Proceedings of the Third International Conference on Information Fusion. IEEE, 2000. http://dx.doi.org/10.1109/ific.2000.862707.

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Ramirez, Elmer. "Economic Model to Determine Electric Car Price Through Incentives." In 2018 IEEE ANDESCON. IEEE, 2018. http://dx.doi.org/10.1109/andescon.2018.8564696.

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Chen, Yufei, Chenle Li, and Minglu Xu. "Business Analytics for Used Car Price Prediction with Statistical Models." In 2021 3rd International Conference on Economic Management and Cultural Industry (ICEMCI 2021). Paris, France: Atlantis Press, 2021. http://dx.doi.org/10.2991/assehr.k.211209.090.

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Wang, Feng, Xusong Zhang, and Qiang Wang. "Prediction of Used Car Price Based on Supervised Learning Algorithm." In 2021 International Conference on Networking, Communications and Information Technology (NetCIT). IEEE, 2021. http://dx.doi.org/10.1109/netcit54147.2021.00036.

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Yin, Xuyang, Luyao Liu, Xuefan Xu, and Wendong Xiao. "Used-Car Price Evaluation Using Mean Encoding and PCA based DeepFM." In 2021 China Automation Congress (CAC). IEEE, 2021. http://dx.doi.org/10.1109/cac53003.2021.9728102.

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Chen, Silin, and Zhipeng Liu. "Application of data mining technology in second-hand car price forecasting." In 2022 3rd International Conference on Electronic Communication and Artificial Intelligence (IWECAI). IEEE, 2022. http://dx.doi.org/10.1109/iwecai55315.2022.00058.

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Chen, Jian, Fangfang Li, Jing Xu, Qing Wang, Qingzhen Han, and Ming Yan. "Comparisons of different methods used for second-hand car price prediction." In 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022), edited by Chi-Hua Chen, Xuexia Ye, and Hari Mohan Srivastava. SPIE, 2022. http://dx.doi.org/10.1117/12.2638739.

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Yang, Hongtai, Jingying Wang, Yinan Lin, Guocong Zhai, Xiaohan Liu, and Siyu Tao. "Effect of Average Car Price On City-Level Private Car Ownership: A Study Based On Panel Data Analysis." In 2019 5th International Conference on Transportation Information and Safety (ICTIS). IEEE, 2019. http://dx.doi.org/10.1109/ictis.2019.8883721.

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Reports on the topic "Car price"

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Goldberg, Pinelopi Koujianou, and Frank Verboven. The Evolution of Price Dispersion in the European Car Market. Cambridge, MA: National Bureau of Economic Research, November 1998. http://dx.doi.org/10.3386/w6818.

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Sallee, James, Sarah West, and Wei Fan. Do Consumers Recognize the Value of Fuel Economy? Evidence from Used Car Prices and Gasoline Price Fluctuations. Cambridge, MA: National Bureau of Economic Research, July 2015. http://dx.doi.org/10.3386/w21441.

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Goldberg, Pinelopi, and Frank Verboven. Market Integration and Convergence to the Law of One Price: Evidence from the European Car Market. Cambridge, MA: National Bureau of Economic Research, July 2001. http://dx.doi.org/10.3386/w8402.

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Vélez-Velásquez, Juan Sebastián. Banning Price Discrimination under Imperfect Competition: Evidence from Colombia's Broadband. Banco de la República de Colombia, December 2020. http://dx.doi.org/10.32468/be.1148.

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Economic theory is inconclusive regarding the effects of banning third-degree price discrimination under imperfect competition because they depend on how the competing firms rank their market segments. When, relative to uniform pricing, all competitors want higher prices in the same market segments, a ban on price discrimination will reduce profits and benefit some consumers at the expense of others. If, instead, some firms want to charge higher prices in segments where their competitors want to charge lower prices, price discrimination increases competition driving all prices down. In this case, forcing the firms to charge uniform prices can increase their profits and reduce consumer surplus. We use data on Colombian broadband subscriptions to estimate the demand for internet services. Estimated preferences and assumptions about competition are used to simulate a scenario in which firms lose their ability to price discriminate. Our results show large effects on consumer surplus and large effects on firms’ profits. Aggregate profits increase but the effects for individual firms are heterogeneous. The effects on consumer welfare vary by city. In most cities, a uniform price regime causes large welfare transfers from low-income households towards high-income households and in a few cities, prices in all segments rise. Poorer households respond to the increase in prices by subscribing to internet plans with slower download speed.
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Kim, Changmo, Ghazan Khan, Brent Nguyen, and Emily L. Hoang. Development of a Statistical Model to Predict Materials’ Unit Prices for Future Maintenance and Rehabilitation in Highway Life Cycle Cost Analysis. Mineta Transportation Institute, December 2020. http://dx.doi.org/10.31979/mti.2020.1806.

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The main objectives of this study are to investigate the trends in primary pavement materials’ unit price over time and to develop statistical models and guidelines for using predictive unit prices of pavement materials instead of uniform unit prices in life cycle cost analysis (LCCA) for future maintenance and rehabilitation (M&R) projects. Various socio-economic data were collected for the past 20 years (1997–2018) in California, including oil price, population, government expenditure in transportation, vehicle registration, and other key variables, in order to identify factors affecting pavement materials’ unit price. Additionally, the unit price records of the popular pavement materials were categorized by project size (small, medium, large, and extra-large). The critical variables were chosen after identifying their correlations, and the future values of each variable were predicted through time-series analysis. Multiple regression models using selected socio-economic variables were developed to predict the future values of pavement materials’ unit price. A case study was used to compare the results between the uniform unit prices in the current LCCA procedures and the unit prices predicted in this study. In LCCA, long-term prediction involves uncertainties due to unexpected economic trends and industrial demand and supply conditions. Economic recessions and a global pandemic are examples of unexpected events which can have a significant influence on variations in material unit prices and project costs. Nevertheless, the data-driven scientific approach as described in this research reduces risk caused by such uncertainties and enables reasonable predictions for the future. The statistical models developed to predict the future unit prices of the pavement materials through this research can be implemented to enhance the current LCCA procedure and predict more realistic unit prices and project costs for the future M&R activities, thus promoting the most cost-effective alternative in LCCA.
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Taylor, Colin, Bruce Hedman, and Amelie Goldberg. State Approaches to Demand Reduction Induced Price Effects: Examining How Energy Efficiency Can Lower Prices for All. Office of Scientific and Technical Information (OSTI), December 2015. http://dx.doi.org/10.2172/1331049.

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Zettelmeyer, Florian, Fiona Scott Morton, and Jorge Silva-Risso. Cowboys or Cowards: Why are Internet Car Prices Lower? Cambridge, MA: National Bureau of Economic Research, December 2001. http://dx.doi.org/10.3386/w8667.

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Baulch, Bob, and Rosemary Botha. Can a maize price band work in Malawi? Washington, DC: International Food Policy Research Institute, 2020. http://dx.doi.org/10.2499/p15738coll2.133939.

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Novy-Marx, Robert. How Can a Q-Theoretic Model Price Momentum? Cambridge, MA: National Bureau of Economic Research, February 2015. http://dx.doi.org/10.3386/w20985.

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Collington, Rosie, and William Lazonick. Pricing for Medicine Innovation: A Regulatory Approach to Support Drug Development and Patient Access. Institute for New Economic Thinking Working Paper Series, January 2022. http://dx.doi.org/10.36687/inetwp176.

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The United States represents the world’s largest market for pharmaceutical drugs. It is also the only advanced economy in the world that does not regulate drug prices. There is no upper threshold for the prices of medicines in the United States. List prices are instead set by manufacturers in negotiation with supply-chain intermediaries, though some federal programs have degrees of discretion in price determinations. In practice, this deregulated system means that drug prices in the United States are generally far higher than in other advanced economies, adversely affecting patient accessibility and system affordability. In this paper, we draw on the “theory of innovative enterprise” to develop a framework that provides both a critique of the existing pricing system in the United States and a foundation for developing a new model of pricing regulation to support safety and effectiveness through drug development as well as accessibility and affordability in the distribution of approved medicines to patients. We introduce a regulatory approach we term “Pricing for Medicine Innovation” (PMI), which departs dramatically from the market-equilibrium assumptions of conventional (neoclassical) economics. The PMI approach recognizes the centrality of collective investments by government agencies and business firms in the productive capabilities that underpin the drug development process. PMI specifies the conditions under which, at the firm level, drug pricing can support both sustained investment in these capabilities and improved patient access. PMI can advance both of these objectives simultaneously by regulating not just the level of corporate profit but also its allocation to reinvestment in the drug development process. PMI suggests that although price caps are likely to improve drug affordability, there remain two potential issues with this pricing approach. Firstly, in an innovation system where a company’s sales revenue is the source of its finance for further drug development, price caps may deprive a firm of the means to invest in innovation. Secondly, even with adequate profits available for investment in innovation, a firm that is run to maximize shareholder value will tend to use those profits to fund distributions to shareholders rather than for investment in drug innovation. We argue that, if implemented properly, PMI could both improve the affordability of medicines and enhance the innovative performance of pharmaceutical companies.
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