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Chauffeured car service (CCS) has developed rapidly in recent years. Although CCS brings convenience and effectiveness, it also triggers some new problems like vicious competition. This work studies the duopoly competition between CCS company and taxi company, in terms of different average cost and number of vehicles of two companies. To find the solutions like the pricing scheme to ease the vicious competition, Hotelling model is introduced. The Hotelling-type model is used to present passengers’ preferences to the companies. Besides, failing situation is taken into account in the Hotelling model to describe the situation where passenger’s demand is not satisfied in reality. This work theoretically analyzes the price scheme and equilibrium market segmentation based on the average cost and number of vehicles of each company. Furthermore, companies’ profits, passengers’ utility and social welfare in equilibrium are revealed based on the game theory. The study shows that both of companies can get optimal profits by setting effective price scheme. The company which has higher price, definitely gets less market share. In addition, moderate competition can lead to positive influence on social welfare.

PurposeThis paper aims to propose a method for dynamic product perceived quality analysis using social media data and to achieve a macro–micro combination analysis. The method enables the prioritization of perceived quality attributes and provides perception causes.Design/methodology/approachTo rationalize the macro–micro combination, ANOVA and multiple linear regression were used to identify the main factors affecting perceived quality which served as the combination basis; by using the combination basis for consumer segmentation, macro-knowledge (i.e. attribute importance and quality category of the attribute) is achieved by term frequency-inverse document frequency (TF-IDF)-based attribute importance calculation and KANO-based attribute classification, which is combined with micro-quality diagnostic information (i.e. perceived quality, perception causes and quality parameters). Further, dynamic perception Importance-Performance Analysis (IPA) is built to present the attribute priority and perception causes.FindingsThe framework was validated by the new energy vehicle (NEV) data of Autohome. The results show that price and purchase purpose are the most influential factors of perceived quality and that dynamic perception IPA can effectively prioritize attributes and mine perception causes.Originality/valueThis is one of the first studies to analyze dynamic perceived quality using social media data, which contributes to the research on perceived quality. The paper also contributes by achieving a combined macro–micro analysis of perceived quality. The method rationalizes the macro–micro combination by identifying the factors influencing perceived quality, which provides ideas for other studies using social media data.