社会与工程心理学研究室知识库

本研究旨在探讨大学生在直播购物中的冲动性消费行为及其影响因素，并分析个体差异。研究采用消费心理学和情绪调节理论作为理论框架，通过Pearson

相关性分析和机器学习中的决策树算法，对直播购物活动的营销特征以及大学生的情绪因素，基础属性与冲动性消费行为之间的关系进行了深入研究。

研究目的：明确直播购物活动中哪些营销特征易引发大学生的冲动性消费行 为，并揭示哪些大学生个体特征更易导致冲动性消费。

研究方法：首先，从某直播营销平台选取 300个直播购物活动和400名大学 生作为研究样本，通过问卷调查收集数据。其次，运用 Pearson 相关性分析探讨营销特征与冲动性消费行为的相关性。再次，通过多元线性回归分析验证多个特征对大学生在直播购物中冲动性消费行为的影响，最后，采用决策树算法构建预测模型，对冲动性消费行为进行量化分析。

研究结果：直播购物活动的营销特征中，直播观看人数、下单人数、魅力特征、推荐特征、互动特征、感知信任、稀缺性与紧迫感、即刻满足感及存在低价销售与直播活动的冲动性消费潜力显著正相关。决策树模型显示，具有高互动特征、高观看人数、低价销售、以及即刻满足感的直播购物活动更容易激发冲动性购买行为。对于大学生个体而言，正向负向情绪因素均与大学生在直播活动中的冲动性消费水平显著正相关，而主动控制感则呈显著负相关；与家庭和谐氛围、父亲学历、母亲冲动性消费水平、父母较少指导存在显著正相关；与年龄存在显著负相关，与性别也存在显著的相关性，女性比男性的冲动性消费水平更高。决策树模型显示， “负向情绪因素较高”、“正向因素情绪较高”、“家庭收入较高”、“年龄较小” 的大学生群体更易在直播购物活动中产生冲动性消费。

研究结论：本研究揭示了直播购物活动中特定营销特征对大学生冲动性消费行为的影响机制，并识别出易产生冲动性消费的大学生个体特征。这些发现为高校开展大学生理性消费教育提供了科学依据，建议设计理性消费课程，实施个性化帮扶策略，并引导家长参与孩子理性消费习惯的培养。

This study aims to explore the impulsive buying behavior of college students in live shopping and its influencing factors and analyze individual differences. The study used consumer psychology and emotion regulation theory as the theoretical framework and conducted in-depth research on the marketing characteristics of live shopping activities, as well as the relationship between college students' emotional, family, and basic attributes and impulsive consumption behavior through Pearson correlation analysis and decision tree algorithms in machine learning.

Research purpose: To identify which marketing features in live shopping activities are likely to trigger impulsive consumption behavior among college students, and to reveal which individual characteristics of college students are more likely to lead to impulsive consumption.

Research methods: First, 300 live shopping activities from a specific livestreaming marketing platform and 400 college students were selected as research samples, and data were collected through questionnaires. Second, Pearson correlation analysis was used to explore the relationship between marketing characteristics and impulsive buying behavior. Third, multiple linear regression analysis was conducted to verify the impact of various characteristics on college students' impulsive buying behavior in live shopping. Finally, a decision tree algorithm was employed to construct a predictive model for quantifying impulsive buying behavior.

Research results: Among Marketing characteristics of live streaming shopping, such as viewership, orders, charm, recommendations, interaction, perceived trust, scarcity, urgency, instant gratification, and low-price sales, are significantly positively correlated with impulsive buying potential. Decision tree analysis shows that activities with high interaction, high viewership, low prices, and instant gratification are more likely to trigger impulsive buying. For university students, both positive and negative emotions positively correlate with impulsive consumption, while proactive control shows a negative correlation. Impulsiveness is positively correlated with family harmony, parental education and behaviors, and negatively correlated with age, with females being more impulsive than males. Students with higher negative or positive emotions, higher family income, and younger age are more prone to impulsive consumption in live shopping.

Research conclusion: This study unveils the mechanism by which specific marketing features in live shopping activities influence the impulsive consumption behavior of college students and identifies individual characteristics of college students who are susceptible to impulsive consumption. These findings provide a scientific basis for universities to carry out rational consumption education for college students, and suggest designing rational consumption courses, implementing personalized assistance strategies, and guiding parents to participate in the cultivation of their children's rational consumption habits.