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Multidimensional Analysis of Consumer Experience of Cigarette Products and Identification of Key Influencing Factors

Year: 2025
Type: article
Study design: Observational Study
Abstract: This study constructs a multi-dimensional evaluation system based on consumer behavior theory and the principles of sensory evaluation. Using the entropy weight method to determine indicator weights, and employing correlation analysis and multiple linear regression analysis, this study explores the key factors influencing consumers' experience with cigarette products. The results indicate that the overall consumer acceptance of the tested cigarette products is high. Among specific indicators, the durability of the cigarette aroma scores the highest, while the strength of the cigarette and the stimulation of the flavor are particularly prominent, and the richness of the flavor and oral comfort receive relatively lower scores. Correlation analysis shows that each dimension of experience is significantly positively correlated with consumer satisfaction, with the strength of the cigarette and the richness of the flavor displaying the highest correlation coefficients. Regression analysis identifies five key influencing factors: the richness of the flavor, the intensity of the flavor, the strength of the cigarette, the durability of the cigarette aroma, and the stimulation of the flavor, with the durability of the cigarette aroma having the most significant impact on consumer experience. Heterogeneity analysis reveals that consumers with high experience focus more on the smoothness of inhalation and the authenticity of the aroma. Young consumers are particularly sensitive to the durability of the aroma, the richness of the flavor, and the intensity of the flavor, while middle-aged consumers place greater emphasis on the authenticity of the aroma, the strength of the cigarette, and the stimulation of the flavor. This study provides decision-making support for cigarette companies in optimizing product quality and accurately meeting consumer demands.
Authors: PanYue Wang, JingZhong Li, Yang Shen, LiWei Fu, Yan Zhang
Language: English
Subfield: Food Science
Open Access status: hybrid
OpenAlex ID: W4414392136
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