Live-stream shopping is developing rapidly, but the sales levels of live streaming products vary by different hosts. How to increase the sales volume of live streaming products has become a problem. Consumers’ purchase behavior in live streaming is determined by some subjective factors, and the persuasiveness of linguistic style affects this subjective judgment to a certain extent. Therefore, the persuasiveness of the hosts’ linguistic style will lead to changes in consumers’ purchase intentions, which will affect the sales volume of products sold in the live streaming. Based on Hovland’s persuasion model, Aristotle’s rhetoric skills, text analysis, Latent Dirichlet Allocation (LDA) topic extraction model and grounded theory, this study divides the host’s linguistic persuasive style in the social e-commerce environment into five types: appealing to personality, appealing to logic, appealing to emotion, appealing to reward, and appealing to exaggeration. Combined with the sales volume of the product, we establish a regression model, and obtain the influence results of the host’s various linguistic persuasive styles on the sales of live streaming products. The results show that: the linguistic persuasive style of appealing to personality has the greatest positive impact on the sales volume of live broadcast products, but the linguistic style of appealing to logic has a negative impact. Interestingly, the same linguistic style has different effects for different types of products: the linguistic style of appealing to exaggeration has a negative effect on the sales volume of apparel products, but it has a positive influence on the sales volume of digital electrical products. Therefore, different linguistic styles should be used for different product types.

Online shopping has developed rapidly, but recently, the sales of some online stores have suffered due to the decrease in people’s income caused by the epidemic. How to grasp the psychology and behavior of consumers and formulate effective marketing strategies is important for increasing sales. This paper puts forward a research model and eight hypotheses based on the research on the promotion situation and the types of products promoted on consumers’ impulse shopping, and uses regression analysis, t-test, stepwise regression and analysis of variance to conduct data analysis. The results show that online promotion has a significant impact on consumers’ willingness, and the anticipated regrets in different directions have totally different effect on willingness; the type of product promoted, and the impulsive characteristics of consumers play a moderating role; online promotion affects consumers’ impulsive online shopping intentions through the intermediary effect of expected regret. The influence of anticipated regrets on impulsive online shopping intention is proposed creatively, and the results also provide e-commerce merchants and customers with new insights in managing and treating online promotions. Managerial implications like controlling the duration of promotions and the number of preferential goods are put forward based on our analysis.

Operations for linguistic neutrosophic numbers (LNNs) have been receiving considerable attention. Existing LNNs operations are generally based upon Archimedean triangular norm and triangular conorm. However, the existing operations fail to consider the correlation among variables. Archimedean copulas and co-copulas can not only reveal the correlation among variables but also prevent information loss when they are used as aggregation functions in the aggregation process. Here, LNN operations are redefined based on Archimedean copulas and co-copulas. Meanwhile, some specific cases are discussed. Then, a linguistic neutrosophic improved generalized weighted Choquet Heronian mean operator is developed. According to the proposed operator, a multi-criteria decision-making method is proposed to tackle the selection problem of low-carbon suppliers. The influences of different generated functions and parameters are discussed, and the feasibility of the proposed method are validated through comparative analyses.

The behavior-based discrimination price model (BBPD) needs to collect a large amount of user information, which would spark user privacy concerns. However, the literature on BBPD typically overlooks consumer privacy concerns. Additionally, most of the existing research provides some insights from the perspective of traditional privacy protection measures, but seldom discusses the role of quality discrimination in alleviating users’ privacy concerns. By establishing a Hotelling duopoly model of two-period price-quality competition, this paper explores the impact of quality discrimination on industry profits, user surplus, and social welfare under user privacy concerns. The results show that, with the increase of user privacy cost, given weak market competition intensity, quality discrimination can increase users’ surplus and social welfare, thereby alleviating users’ privacy concerns. We then discuss the managerial implications for alleviating consumer privacy concerns. In addition, we take Airbnb as an example to provide practical implications.