• Journal of Service Research and Studies
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• v.13 no.3
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• pp.105-126
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• 2023

The domestic used car market continues to grow along with the used car online platform service. The used car online platform service discloses vehicle specifications, accident history, inspection history, and detailed options to service consumers. Most of the preceding studies were predictions of used car prices using vehicle specifications and some options for vehicles. As a result of the study, it was confirmed that there was a nonlinear relationship between used car prices and some specification variables. Accordingly, the researchers tried to solve the nonlinear problem by executing a Machine Learning model. In common, the Regression based Machine Learning model had the advantage of knowing the actual influence and direction of variables, but there was a disadvantage of low Cost Function figures compared to the Decision Tree based Machine Learning model. This study attempted to predict used car prices of six domestic brands by utilizing both vehicle specifications and vehicle options. Through this, we tried to collect the advantages of the two types of Machine Learning models. To this end, we sequentially conducted a regression based Machine Learning model and a decision tree based Machine Learning model. As a result of the analysis, the practical influence and direction of each brand variable, and the best tree based Machine Learning model were selected. The implications of this study are as follows. It will help buyers and sellers who use used car online platform services to predict approximate used car prices. And it is hoped that it will help solve the problem caused by information inequality among users of the used car online platform service.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.27-43
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• 2024

The market share of online platform services in the used car market continues to expand. And The used car online platform service provides service users with specifications of vehicles, accident history, inspection details, detailed options, and prices of used cars. SUV vehicle type's share in the domestic automobile market will be more than 50% in 2023, Sales of Hybrid vehicle type are doubled compared to last year. And these vehicle types are also gaining popularity in the used car market. Prior research has proposed a used car price prediction model by executing a Machine Learning model for all vehicles or vehicles by brand. On the other hand, the popularity of SUV and Hybrid vehicles in the domestic market continues to rise, but It was difficult to find a study that proposed a used car price prediction model for these vehicle type. This study selects a used car price prediction model by vehicle type using vehicle specifications and options for Sedans, SUV, and Hybrid vehicles produced by domestic brands. Accordingly, after selecting feature through the Lasso regression model, which is a feature selection, the ensemble model was sequentially executed with the same sampling, and the best model by vehicle type was selected. As a result, the best model for all models was selected as the CBR model, and the contribution and direction of the features were confirmed by visualizing Tree SHAP Value for the best model for each model. The implications of this study are expected to propose a used car price prediction model by vehicle type to sales officials using online platform services, confirm the attribution and direction of features, and help solve problems caused by asymmetry fo information between them.

• Journal of Digital Convergence
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• v.18 no.1
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• pp.129-135
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• 2020

This study examined the consumer response of the current O2O service between service types. Previous studies mainly focused on the quality factor of O2O service or Technology Acceptance Model or extended TAM, This study is different from the fact that there are differences in factors that consumers consider important and consumer reactions by service type. It is also significant that we compared between representative food delivery services and car sharing services that are actively used among O2O services. As O2O service is closely related to consumer's life, this study chose three factors that the issue of personal information security and trust of intermediary platform companies, and finally subjective norm based on individuals and groups who are aware of new O2O service. To test hypotheses, data were collected and analyzed for 301 samples, focusing on delivery and car sharing service, As a result, the delivery service among the O2O services was more positive to attitude toward service in the consumer group with lower personal information security, trust in platform, and subjective norm than car sharing service. Based on these results, implications and future research directions were presented.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.20-38
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• 2023

Recently, car sharing has shown the most remarkable growth among sharing economy services. In the process of analyzing the intention to reuse the car sharing service, this study tried to reflect the unique characteristics of the service, which consists of non-face-to-face self-service, such as reservation, approval, handover, inspection, and return of the vehicle. Specifically, in addition to the perceived benefits and the perceived risks, we considered 'information quality' as a platform characteristic and 'self-efficacy' as a personal characteristic. To collect data, an online survey was conducted on adults with experience in car sharing, and a total of 320 responses were used for analysis. As a result of analyzing the structural equation model, it was found that information quality and self-efficacy increased the perceived benefits of services, and the higher the information quality, the higher the self-efficacy. On the other hand, the role of information quality and self-efficacy in lowering perceived risks was insignificant, and the intention to reuse services was more affected by perceived benefits than perceived risks. As a result of further analysis using Process Macro, it was found that the effect of self-efficacy on reuse intention was mediated by perceived benefits. It was analyzed that the indirect effects of information quality on reuse intention through perceived benefits or self-efficacy were all significant. These results suggest that providing timely, sufficient, and easy-to-understand information required by users on the platform improves self-efficacy and increases service reuse intention. In order to increase the number of service users, it is important for service providers not only to provide promotional activities such as offering attractive prices, but also to provide high-quality information so that users can use it more easily.