With the popularity of smartphones, consumers’ daily lives and consumption patterns have been changed by using multi-functional apps. Convenience store operators have developed membership apps as a platform to promote their brands to consumers to create the benefits of “membership economy”. This study examined consumer behavior towards convenience store membership apps using UTAUT2. Consumers who have installed the convenience store membership apps were recruited as the target population. SPSS 23.0 was used to conduct item analysis and reliability analysis in the pretest questionnaires. The formal questionnaires were distributed online by convenience sampling method, with 375 valid questionnaires collected. Smart PLS 3.0 was conducted by analyzing the confirmatory factor analysis and structural equation model analysis. The results of the study, “performance expectancy”, “social influence”, “price value” and “habit” of convenience store member app users showed positive and significant effects on “behavioral intention”. “Facilitating conditions”, “habit” and “behavioral intention” have positive and significant effects on “actual use behavior”. “Gender” affects “habit” to have a significant moderating effect on “use behavior”. “Use experience” affects “habit” to have a significant moderating effect on “behavioral intention”. Based on the study results, the further suggestions of marketing management implications and feasible recommendations are proposed for convenience store operators to refer to in the implementation of membership app marketing management.

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.

This paper critically reviews the prevailing generalizations in current research on Generation Z (Gen-Z) travel behavior. While various studies have characterized Gen-Z’s transportation preferences as leaning towards sustainable and technology-integrated modes of transport, this paper argues that the findings are largely based on observations from developed countries and may not accurately reflect behavior in developing countries. This paper is written using a narrative literature study approach. Through a comprehensive literature review, the paper highlights the differences in Gen-Z travel patterns across different geographical regions, emphasizing the need for context-specific analysis. The paper addresses often overlooked factors such as economic limitations, infrastructure challenges, and cultural nuances that shape mobility choices. The aim is to dissect the cohort effect and look at its validity across different socio-economic landscapes through existing literature. As such, the paper provides nuanced insights into the heterogeneity of Gen-Z travel behavior and suggests cautioning against over-generalization, as well as advocating for a more localized approach in transportation policy and planning. The paper also encourages similar research in developing countries to gain a more comprehensive understanding of Gen-Z travel behavior globally.

This study examines the impact of digitally curated museum exhibitions on visitor behavior, with a particular focus on university students from China and Hungary (n = 308). Using PLS-SEM analysis, the research finds that visitors’ experiences during digital curation visits significantly influence their behavior, and this influence is mediated by perceived value and satisfaction. It is recommended that museums consider the following constructive considerations to facilitate their future development: expanding the application of digital curation, utilizing cutting-edge technologies, implementing data-driven curatorial optimization, enhancing social experiences, integrating education and entertainment, and promoting cultural preservation and environmental stewardship. These insights will help guide museums toward more engaging and sustainable experiences.

This study conducts research on retailers’ behavioral intentions and behavior in adopting e-commerce platforms (ECPs) and uses the unified theory of acceptance and use of technology (UTAUT2) model as well as add other factors such as Personalization Platform, Seamless Interaction. The findings show that Effort Expectancy, Social Influence, Hedonic Motivation, Retailers’ Capacity, Integration Strategies have a positive impact on retailers’ behavioral intention of adopting ECPs and Performance Expectancy has a negative impact on retailers’ behavioral intention of adopting ECPs. At the same time, Behavioral Intention, Facilitating Conditions have a positive impact on retailers’ behavior adopting ECPs and Seamless Interaction has a negative impact on retailers’ behavior adopting ECPs. With important implications, these findings are proposed to relevant parties, helping retailers and ECPs suppliers identify factors affecting retailers’ behavioral intention and behavior in adopting ECPs in Vietnam.

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.