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 study explores how Jordanian telecom companies can balance Internet of Things (IoT) driven automation with maintaining genuine consumer-brand connections. It seeks strategies that blend IoT automation with personalized engagement to foster lasting consumer loyalty. Employing qualitative research via semi-structured interviews with IT and customer service managers from Jordanian telecom companies. IoT-driven automation in Jordan’s telecom sector revolutionizes consumer-brand relationships by enabling data-driven personalization. It emphasizes the importance of IoT proficiency, transformed marketing strategies, and the need to balance personalization with consumer privacy. Interviews stress the significance of maintaining authentic human connections amidst automation. Strategies for Jordanian telecom firms include integrating IoT data into CRM systems, employing omnichannel marketing, balancing automation with human interaction, adopting a consumer-centric approach, mitigating security risks, and leveraging IoT insights for adaptive services. These approaches prioritize consumer trust, personalized engagement, and agile service adaptation to meet dynamic consumer preferences. This research provides actionable strategies for telecom firms on effective IoT integration, emphasizing the need to maintain genuine consumer relationships alongside technological advancements. It highlights IoT’s transformative potential while ensuring lasting consumer loyalty and business success. Future research avenues could explore longitudinal studies and the interplay between AI and IoT in telecom services.

Objective: This study investigates the influence of tobacco prices on consumption habits among 200 smokers in Lisbon, Portugal, focusing on generational preferences and perceptions of tobacco taxes. Methods: A cross-sectional survey was conducted using a quantitative approach. Participants were categorized by generational cohort, and data on tobacco consumption types, awareness of tobacco taxes, and opinions on tax increases were collected. Statistical analyses were used to explore relationships and predictors. Results: Findings reveal that 46.5% of participants favored heated tobacco, 37.0% smoked cigarettes, and 16.5% consumed other types like roll-your-own tobacco and electronic cigarettes. Significant generational differences were observed, with older cohorts predominantly smoking cigarettes (51.5%), while Generation Z showed a preference for heated tobacco (55.2%). Most smokers (79.5%) were aware of tobacco taxes, with diverse opinions on their purpose: revenue generation (44.0%), consumption reduction (44.5%), and indifference (11.5%). Despite this awareness, 60.5% reported no change in consumption habits due to tax increases. Conclusion: The study underscores the complexity of tobacco consumption behaviors influenced by price and generational factors. While heated tobacco gains popularity among younger smokers, traditional cigarettes remain prevalent among older cohorts. The findings highlight challenges in tobacco control policies, suggesting a need for comprehensive strategies integrating price measures with targeted educational and cessation interventions to effectively reduce tobacco use across different generations.

In the era of artificial intelligence, smart clothing, as a product of the interaction between fashion clothing and intelligent technology, has increasingly attracted the attention and affection of enterprises and consumers. However, to date, there is a lack of focus on the demand of silver-haired population’s consumers for smart clothing. To adapt to the rapidly aging modern society, this paper explores the influencing factors of silver-haired population’s demand for smart clothing and proposes a corresponding consumer-consumption-need theoretical model (CCNTM) to further promote the development of the smart clothing industry. Based on literature and theoretical research, using the technology acceptance model (TAM) and functional-expressive-aesthetic consumer needs model (FEAM) as the foundation, and introducing interactivity and risk perception as new external variables, a consumer-consumption-need theoretical model containing nine variables including perceived usefulness, perceived ease of use, functionality, expressiveness, aesthetics, interactivity, risk perception, purchase attitude, and purchase intention was constructed. A questionnaire survey was conducted among the Chinese silver-haired population aged 55–65 using the Questionnaire Star platform, with a total of 560 questionnaires issued. The results show that the functionality, expressiveness, interactivity, and perceived ease of use of smart clothing significantly positively affect perceived usefulness (P < 0.01); perceived usefulness, perceived ease of use, aesthetics, and interactivity significantly positively affect the purchase attitude of the silver-haired population (P < 0.01); perceived usefulness, aesthetics, interactivity, and purchase attitude significantly positively affect the purchase intention of the silver-haired population (P < 0.01); functionality and expressiveness significantly positively affect perceived ease of use (P < 0.01); risk perception significantly negatively affects purchase attitude (P < 0.01). Through the construction and empirical study of the smart clothing consumer-consumption-need theoretical model, this paper hopes to stimulate the purchasing behavior of silver-haired population’s consumers towards smart clothing and enable them to enjoy the benefits brought by scientific and technological advancements, which to live out their golden years in comfort, also, promote the rapid development of the smart clothing industry.

The global increase in organic food consumption underscores the need for in-depth research to understand the determinants of consumer purchase intentions towards organic products. Hence, this study aims to investigate the factors influencing the consumer purchase intentions towards organic food through an analysis involving 274 participants. Additionally, it also explores the mediating and moderating effects of attitudes and environmental concerns on the purchasing intentions towards organic food, providing insights in how these psychological and environmental factors influence consumer behavior. Using a quantitative method, data was gathered from the South Korean cities of Jinju and Changwon. However, analysis was performed through Partial Least Squares Structural Equation Modeling. The research findings illustrate that subjective norm, perceived behavioral control, and ethical consciousness significantly influence attitudes towards purchase intentions of organic foods. Moreover, the results indicate that attitude positively influenced consumer purchase intention towards organic food. Results reveal that attitude serves as a mediator in the relationship between subjective norms and consumer purchase intentions for organic food. Similarly, Likewise, attitude mediates the connection between perceived behavioral control and consumer purchase intention towards organic food. Additionally, the results indicate that attitude mediates the relationship between ethical consciousness and consumer purchase intention towards organic food. Furthermore, environmental concerns are found to significantly moderate the association between attitude and consumer purchase intention towards organic foods. The insights garnered from this study shed light on consumer intentions to purchase organic foods, equipping stakeholders such as marketers, retailers, and producers with valuable insights for creating effective marketing strategies aiming at promotion of these products. This research serves as a pivotal resource for developing targeted approaches to enhance the market share and consumption of organic foods.