Artificial Intelligence (AI) has become a pivotal force in transforming the retail industry, particularly in the online shopping environment. This study investigates the impact of various AI applications—such as personalized recommendations, chatbots, predictive analytics, and social media engagement—on consumer buying behaviors. Employing a quantitative research design, data was collected from 760 respondents through a structured online survey. The snowball sampling technique facilitated the recruitment of participants, focusing on diverse demographics and their interactions with AI technologies in online retail. The findings reveal that AI-driven personalization significantly enhances consumer purchase intentions and satisfaction. Multiple regression analysis shows that AI personalization (β = 0.35, p < 0.001) has the most substantial impact on purchase intention, followed by chatbot effectiveness (β = 0.25, p < 0.001), predictive analytics (β = 0.20, p < 0.001), and social media engagement (β = 0.15, p < 0.01). Similarly, AI personalization (β = 0.30, p < 0.001), predictive analytics (β = 0.25, p < 0.001), and chatbot effectiveness (β = 0.20, p < 0.001) significantly influence consumer satisfaction. The hierarchical regression analysis underscores the importance of ethical considerations, showing that ethical and transparent use of AI increases consumer trust and engagement. Model 1 explains 45% of the variance in consumer behavior (R² = 0.45, F = 154.75, p < 0.001), while Model 2, incorporating ethical concerns, explains an additional 10% (R² = 0.55, F = 98.25, p < 0.001). This study highlights the necessity for retailers to leverage AI technologies ethically and effectively to gain a competitive edge, improve customer satisfaction, and drive long-term success. Future research should explore the long-term impacts of AI on consumer behavior and the integration of emerging technologies such as augmented reality and the Internet of Things (IoT) in retail.

As a key factor in the macroeconomic process, the interaction between public confidence and the commodity market, especially its impact on commodity facilitation returns and macroeconomic linkages, is worth exploring in depth. This study adopts the TVP-SV-VAR model to analyze the causal linkages, dynamic characteristics, and mechanisms of the interaction, and reveals the following core findings: (1) The economic background and information shocks contribute to the variations in the effects and orientations of the economic variables, which highlight the time-varying nature of the economic interactions. (2) Consumer and investor confidence exert heterogeneous influence on the macroeconomy, and their different responses to the negative effect of interest rates and convenience gains are particularly significant in the post-crisis recovery period. (3) In the short-term perspective, the influence of public confidence on monetary policy and inflation exceeds that in the medium and long term, highlighting the immediate sensitivity of individual economic behavior. (4) Since 2015, accommodative monetary policy has accelerated market capital flows, delaying the interaction between confidence indices and inflation, revealing policy time lag effects. (5) Convenience gains exhibit complex time-varying interactions with key economic parameters (interest rates, commodity prices, and inflation), with 2011 and 2014 displaying particular patterns, mapping differences between short- and long-term mechanisms, respectively. The study highlights the central role of consumer and investor confidence in the precise tailoring of macroeconomic policies, providing a scientific basis for policy forecasting and economic regulation, and contributing to economic stability. Meanwhile, the dynamic evolution of consumer confidence deepens market trend foresight, enhances the precision of market participants’ decision-making, and reinforces the resilience and predictability of economic operations.

Social media influencer marketing has emerged as an essential marketing strategy in the online interactive environment. This study investigates the impact of influencer-consumer fit (ICF) on behavioral intentions; intention to co-create brand value (ICC) and purchase intention (PI), with the serial mediation of influencer authenticity (IA) and attitude toward brand (ATB). A self-administered questionnaire was distributed to followers of social media influencers in Pakistan. The data were collected from 421 female followers of social media influencers through survey and partial least squares—structural equation modeling was used for data analysis. The findings reveal that ICF impacts IA, while the latter impacts ATB. ATB in turn impacts behavioral intentions. The direct effects suggest that ICF impacts consumers’ PI but not the ICC. However, with the serial mediation of IA and ATB, the relationship becomes significant. The findings of this study may assist managers in building brand strategies to achieve excellence in a highly dynamic and competitive market by leveraging the power of influencer marketing.

QR code transforms the way retailers offer their shopping experiences in the current context. In response, various retailers adopted innovative approaches such as QR code-based applications to attract their consumers. A QR code-based virtual supermarket refers to a space where goods or services are traded in a virtual space using a smart app-based QR code. To fully understand the opportunities of this type of supermarket applying QR-code technology, initial research is required to assess consumers’ use intention. This study has examined the antecedents of the adoption of QR code-based virtual supermarket among Vietnam consumers using the expanded Technology Acceptance Model (TAM) and explored the moderating effect of perceived risk on the relationship between attitude and consumers’ intention to use QR code-based virtual supermarket. A questionnaire was used to collect data from a sample of 335 consumers in Vietnam. The findings revealed that the antecedents are effective in predicting consumers’ attitudes and intentions toward QR code-based virtual supermarket adoption. The results showed the negative moderation effects of perceived risk for the effect of attitude on consumers intention. In addition, practical implications are supported for the application of new shopping technology and are likely to stimulate further research in the area of virtual supermarket shopping.

With the continuous development of network has also greatly developed, exploring the role of social network relationships and attachment emotions on consumer intention helps community managers to promote community purchases for more consumer. As another core component of social e-commerce, social media influencer also has a significant influence on consumer intention. This study systematically analyzed the effects of social network relationships and social media influencer characteristics on consumer purchase intentions. Introduced consumer attachment and perceived value as mediating variables to construct the research framework of this study. This article adopts quantitative analysis methods to test the research hypotheses proposed. This article collected 600 first-hand data in the form of a survey questionnaire and analyzed the data using AMOS and SPSS statistical software. The empirical analysis in this article confirms that social network relationships has a significant impact on consumer purchase intentions; social media influencer characteristics has a significant impact on consumer purchase intentions; consumer attachment has a significant impact on perceived value;  consumer attachment plays a mediating role in the effect of social network relationships on consumers purchase intentions; perceived value plays no mediating role in the effect of social media influencer characteristics on consumer purchase intentions; perceived value plays a mediating role in the effect of consumer attachment on consumer purchase intentions; consumer attachment and perceived value have a chain mediating role between social network relationships and consumer purchase intentions.