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This paper aims to provide a driving behavior scoring model to decide the personalized automobile premium for each driver.

Driving behavior scoring model.

The driving behavior scoring model could effectively reflect the risk level of driver’s safe driving.

A driving behavior scoring model for UBI.

The purpose of this paper is to discuss how the configurations of short life cycle, low quality, design and price, influence customer purchase intention in fast fashion and high technology industries in China.

The traditional thinking is that products with high quality and low price will win more customers. However, the authors can notice that high quality products usually have high cost. Therefore, it is necessary to do more research on how customers can accept low quality products. The authors take fast fashion products and smart phones as empirical studies, collecting data from customer’s online survey. Based on the methodology of fuzzy set qualitative comparative analysis, the authors analyse the relationship between the factors of short life cycle, low quality, design and price and influence customer purchase intention.

The authors find that price is the most important influencing factor. Low price is a strong competitive factor in the market. As to low quality products, low price can be achieved relatively more easily than with high quality products, resulting from relatively poorer raw material or configurations. Hence the connection between quality and price may give an idea to enterprises that customers will accept low quality products with low price. Moreover, according to the research, different generations are equally affected by the low price condition, regardless of customer gender and household income.

Because the study only focuses on fast fashion and smart phones industries, future work needs to replicate this study with individual data for different industries and with alternative methods to reinforce the confidence in the research. Meanwhile , this research studied mainly the customer perspective, it would be desirable to extend the study to the enterprise perspective and find out the difficulties that limit them in using low quality products to meet market needs. This may revel some cultural differences in purchase behavior among different countries and the discussed industries can be expanded to a larger area.

The study offers a number of managerial implications. With the rapid changes in people’s aesthetic sense and developing high-tech, it is more and more necessary for companies to think about how to win more customers and earn more profits. Low quality products have advantages as they will lower companies’ costs in many dimensions, improving the speed of supply. It helps firms to take low quality products into consideration and think whether they will influence different aspects of the company assistance firms to get a deeper understanding of customer psychology and make better decisions on their products.

The paper fills the gap in the research field by exploring how consumer behavior is affected by different conditions.

This paper aims to extract the comment targets in Chinese online shopping platform.

The authors first collect the comment texts, word segmentation, part-of-speech (POS) tagging and extracted feature words twice. Then they cluster the evaluation sentence and find the association rules between the evaluation words and the evaluation object. At the same time, they establish the association rule table. Finally, the authors can mine the evaluation object of comment sentence according to the evaluation word and the association rule table. At last, they obtain comment data from Taobao and demonstrate that the method proposed in this paper is effective by experiment.

The extracting comment target method the authors proposed in this paper is effective.

First, the study object of extracting implicit features is review clauses, and not considering the context information, which may affect the accuracy of the feature excavation to a certain degree. Second, when extracting feature words, the low-frequency feature words are not considered, but some low-frequency feature words also contain effective information.

Because of the mass online reviews data, reading every comment one by one is impossible. Therefore, it is important that research on handling product comments and present useful or interest comments for clients.

The extracting comment target method the authors proposed in this paper is effective.