Distribution of new cars – no longer an issue for EU competition law?

Distribution cartels in the automotive sector used to be frequently dismantled and sanctioned by the European Commission and the EU Courts still some 15 years ago. In recent years, however, only a few cases have been reported at the national level of EU Member States. Is it because the distribution of new cars really ceased to be a competition problem as the European Commission declared when it removed this part of the automotive business from the specific Block Exemption Regulation for the automotive sector in 2010? The purpose of the present analysis is first to inspect the car distribution cases that emerged in the EU after the year 2000 and, second, to speculate somewhat whether new forms of distribution, brought by the digitalization of marketing and sales, cannot bring about also new risks to cartel agreements and other types of distortions of competition in car sales.

USED CAR PRICE PREDICTION USING MACHINE LEARNING

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

Analysis of Environmental Management Characteristics Using Network Analysis of CEO Communication in the Automotive Industry

CEO messages in CEO communication are becoming increasingly important. From a sustainable management perspective, it is imperative to study environmental, social, and governance messages. Previous studies on CEO messages have focused on financial analyses. In contrast, this study (1) extracted environment-related words in the CEO messages of automotive companies, (2) selected high- and low-performing automotive manufacturers based on car sales data, (3) compared environment-related keywords used by high-performing (upper group) and low-performing (lower group) companies, and (4) performed a structural interpretation of the keywords to analyze the characteristics of environmental management. A comparison between the upper and lower groups revealed that six keywords—society, electric, technology, standards, contribute, and global—were exclusive to the upper group. The six keywords exclusive to the lower group were sales, target, promote, energy, efforts, and system. Environmental keywords and eco-innovation factors were subjected to keyword–factor mapping and network analysis. Normative pressures, technology, and environmental managerial concerns were the key factors with the highest centrality. Accordingly, the environmental management characteristics of the upper-group corporations can be used as benchmarks by lower groups.

Impact of Key Marketing Tools on Global Car Market Development

The purpose of the proposed study was to identify the functional patterns of influence of the marketing tools on sales of cars on the global market, to be able to predict sales volumes in the future, taking into account certain marketing tools that the company may use in a particular international market. For the purpose of this research the method of correlationregression analysis is used to construct the corresponding economic and mathematical models of impact on the sales volumes of various instruments of product, price, promotion policy, etc. Using the models offered in the article, the feasibility of introducing certain measures can be determined, when entering new markets in order to increase car sales. Each instrument to which potential buyers are sensitive determines the effect of its use. Considering this effect, budgets can be set up for appropriate action.

New Characteristics and Hedonic Price Index Numbers

Changes in product characteristics on the extensive margin (the addition of new features and the removal of old ones) are an important and hitherto neglected dimension of quality change. Standard techniques for adjusting price indices for new goods cannot handle such changes satisfactorily, and this leads to an economically and statistically significant bias in the measurement of prices and real output. We combine insights from the theories of exact index numbers and demand for characteristics to develop a new method for incorporating changes on the extensive characteristic margin. Applied to U.K. data on new car sales, our method leads to revisions in estimated inflation rates for this commodity group that are both plausible and quantitatively important.

Demand Forecasting of Toyota Avanza Cars in Indonesia: Grey Systems Approach

Toyota Avanza car is a popular four-wheeler among Indonesia middle-class customers. The current study aims to forecast the demand for Toyota Avanza cars in Indonesia in the next six years using the grey forecasting model EGM (1,1, α, θ). The comparative analysis of the results obtained from the grey model with those of Linear Regression, Exponential Regression, and Exponential Triple Smoothing techniques revealed the superiority of the grey model as it produced most accurate forecasts. The accuracy was measured through the Mean Absolute Percentage Error. The results revealed, the car sales are likely to decline in the future. Although forecasts are never completely accurate, forecasting can provide a reference for developing strategy to meet future demand. The results are important for Toyota Avanza car manufacturers in Indonesia.