This research examines the influence of virtual community platform attributes on luxury consumers’ purchase intentions, with a specific focus on the role of policy innovation in digital infrastructure. The study aims to 1) identify key factors affecting purchase intentions toward luxury products in virtual environments; 2) develop and validate a structural equation model to analyze these intentions; and 3) provide actionable insights for luxury goods marketers to refine their strategies within these platforms. Utilizing a structural equation model, the study investigates the interactions among various determinants of consumer behavior in virtual communities, highlighting the impact of policy innovation. Data was collected through purposive sampling from 1142 respondents in China’s top 10 high-spending cities on luxury goods, ensuring data relevance. The findings emphasize the significance of knowledge sharing, interactive communication, and leaders’ opinions in virtual communities in building consumer trust and shaping perceptions of online reviews. These elements influence purchase intentions directly and indirectly, with consumer trust serving as a crucial mediator. The study reveals the substantial impact of virtual community attributes on fostering consumer trust and shaping buying decisions for luxury items, underlining the contribution of social development processes. Moreover, the role of policy innovation is found to be significant in enhancing these virtual community dynamics, suggesting that regulatory changes can positively influence consumer engagement and trust. The conclusions offer valuable implications for marketers, proposing strategies to boost consumer engagement and drive sales in virtual settings. This research contributes to the theoretical understanding of digital consumer behavior and provides practical strategies for innovation and growth within the luxury goods sector, emphasizing the critical role of policy innovation in shaping these dynamics.

The aim of this study was to make a quantitative contribution to the impact of COVID-19 and Mental on consumer behavior. For this purpose, the data in the Scopus and WoS databases until 5 February 2024 were examined using bibliometric analysis. The data obtained within the scope of this study were classified and analyzed using the VOSviewer program developed for scientific mapping analysis. In the evaluations, 180 studies in the Web of Science database and 371 documents in the Scopus database were identified, and when duplicate studies were combined, 426 studies were included in the analysis. According to the results of the analysis, the journal with the highest number of publications is “Journal of Retailing and Consumer Services”; the organization with the highest number of publications is “Department of management sciences, University of Okara” and “North-West University”; the authors with the highest number of publications and citations are “Wang, Xueqin” and “Yuen, Kum Fai”; and the most cited studies are “Laato et al.” and “Goolsbee and Syverson”. This study provides a comprehensive analysis of the studies on the impact of COVID-19 and mental factors on consumer behavior and makes a qualified contribution to the literature with an important opening.

This study systematically examines the literature of electric vehicle (EV) purchase intention and consumer behavior using a bibliometric method to unveil three main research questions: 1) identifying influential publications, authors, and journals; 2) analyzing the thematic evolution of research over time; and 3) identifying emerging research directions. The main objective is to provide a comprehensive understanding of the current state of knowledge and to guide future research in this evolving field. A comprehensive bibliometric analysis was conducted, using Scopus statistics analysis, R-Studio Biblioshiny and VOSviewer, comprising 687 publications authored by 1743 researchers representing 34 different countries with the dataset sourced from the Scopus database from 2010 to 2023. To achieve a nuanced understanding of the research landscape, a multifaceted approach was adopted, including detailed citation analysis, author co-citation analysis, keyword analysis, and thematic mapping. Through meticulous analysis, this study identifies the most influential publications, authors, and journals in the domain of EV purchase intentions and consumer behaviors. It also traces the evolution of themes over time and identifies emerging research directions, providing valuable insights into the trajectory and future avenues of inquiry within this field. The findings contribute to a deeper understanding of the dynamics shaping research in the realm of EVs. The insights gained contribute significantly to advancing knowledge in this crucial domain, offering theoretical insights and practical implications for policymakers, businesses, manufacturers, and academics.

Consumers, particularly women, pursue beauty and health in order to uphold their image within society, which has contributed to consistent demand for cosmetics. The cosmetics market, driven by globalization and cultural exchange, sees Thai cosmetics gaining popularity among Chinese women. There has been a significant rise in the popularity of Thai cosmetics, known for their natural ingredients and innovative formulations. With a growing interest in cross-cultural consumer behaviour, particularly in the context of skincare and make-up products, understanding how different age groups perceive and choose Thai cosmetics is crucial for effective marketing strategies. The main issue is the development of consumer preferences over time among Chinese women who have only recently been given the opportunity to choose among many brands. This qualitative study explores the intergenerational differences in Chinese female consumers’ preferences for Thai cosmetics, aiming to uncover rich insights into their perceptions, attitudes, and behaviours. The target population is female Chinese who have visited Thailand and purchased or used Thai-branded cosmetics. Key themes emerge regarding the perception of product efficacy, the cultural authenticity and the role of digital media and trends in influencing product choices. Findings highlight nuanced generational preferences, with older cohorts emphasizing trust and familiarity with established brands, while younger cohorts prioritize innovation, sustainability, and personalized beauty experiences. These insights provide valuable implications for marketers seeking to tailor strategies and product offerings to engage effectively diverse generational segments within the competitive cosmetics market.

Noise pollution in construction sites is a significant concern, impacting worker health, safety, communication, and productivity. The current study aims to assess the paramount consequences of ambient noise pollution on construction activities and workers’ productivity in Peshawar, Pakistan. Noise measurements have been recorded at four different construction sites in Peshawar at different times of the day. Statistical analysis and Relative Importance Index (RII) are employed to evaluate the data Risk variables, such as equipment maintenance, noise control, increased workload, material handling challenges, quality control issues, and client satisfaction. The results indicated that noise levels often exceeded permissible limits, particularly in the afternoon, posing significant worker risks. In addition, RII analysis identified communication difficulties, safety hazards, and decreased productivity as significant issues. The results show that noise pollution is directly linked with safety risks, decreased performance, and client dissatisfaction and needs immediate attention by authorities. This paper proposes a strategic policy framework, recommending uniform hand signals and visual communication methods without noise for workers, worker training about safety, and using wearable devices in noisy settings. Communication training for teams and crane operators, proactive quality control, and customer-oriented project schedules are also proposed. These recommendations aim to mitigate the adverse effects of noise pollution, enhance construction industry resilience, and improve overall operational efficiency, worker safety, and client satisfaction in the construction sector of Peshawar, aligning with policy and sustainable development objectives.

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.