This research explores the factors influencing consumers’ intentions and behaviors toward purchasing green products in two culturally and economically distinct countries, Saudi Arabia and Pakistan. Drawing on Ajzen’s Theory of Planned Behavior (TPB), the study examines the roles of altruistic and egoistic motivations, alongside environmental knowledge, in shaping green consumer behavior. Altruistic motivation, driven by concern for societal well-being and environmental sustainability, is found to have a stronger impact on green purchase intention and behavior in both countries, particularly in Pakistan. Egoistic motivation, which focuses on personal benefits like health and cost savings, also contributes but with a lesser influence. The research employs a cross-sectional survey design, collecting data from 1000 respondents (500 from each country) using a stratified random sampling technique. The collected data were analyzed using structural equation modeling (SEM) to examine the relationships between variables and test the moderating effects of environmental knowledge. The results reveal that environmental knowledge significantly moderates the effect of both altruistic and egoistic motivations on green purchase intention, enhancing the likelihood of eco-friendly consumption. These findings underscore the importance of environmental education in promoting sustainable consumer behavior. The originality of this study lies in its comparative analysis of green consumerism in two distinct contexts and its exploration of motivational factors through the TPB framework. Practical implications suggest that policymakers and marketers can develop strategies that appeal to both altruistic and egoistic drivers while enhancing consumer knowledge of environmental issues. The study contributes to the literature by expanding TPB to include the moderating role of environmental knowledge in understanding green consumption behavior across diverse cultures.
The menace of road traffic accidents (RTAs) has become a major constraint to development in most developing countries because of driving behaviour. This study examines the effects of road users’ education programmes on driving behaviour toward RTA reduction in Nigeria. Data for the study were collected by random sampling of 287 respondents. The respondents comprising road safety officers and drivers were selected at six (6) zonal headquarters of the Federal Road Safety Commission. The questionnaire presented seventeen (17) statements in a 5-point Likert scale for the respondents to rank in order of importance as they have influenced driving behaviour. The data collected were analysed using exploratory factor analysis to identify the most significant effects of road user education on driving behaviour. The study found that road user education programmes have influenced driving behaviour by improving bad driving acts, maintaining good vehicle conditions, and obeying road communication signs. The finding implies that appropriate driving behaviour will reduce road traffic accidents.
This study conducted a systematic literature review on current and emerging trends in the use of artificial intelligence (AI) for community surveillance, using the PRISMA methodology and the paifal.ai tool for the selection and analysis of relevant sources. Five main thematic areas were identified: AI technologies, specific applications, societal impact, regulations and public policy. Our findings revealed exponential growth in the development and implementation of AI technologies, with applications ranging from public safety to environmental monitoring. However, this advancement poses significant challenges related to privacy, ethics and governance, driving a debate on the need for appropriate regulations. The analysis also highlighted the disparity in the adoption of these technologies among different communities, suggesting a need for inclusive policies to ensure equitable benefits. This study contributes to the understanding of the current scenario of AI in community policing, providing a solid foundation for future research and developments in the field.
As an important type of knowledge, standards are key factors in economic development and technological innovation. To analyze the impact of participation in standards development on enterprise performance, this study takes China’s high-tech industry as an example. We use the operating data of listed enterprises in the industry in 2019 and conduct the propensity score matching method matching analysis on the entire sample and the classification. The conclusion shows: From an overall point of view, the participation of enterprises in the development of standards has a positive impact on the enterprise’s return on total assets. Specifically, participating in the development of over three standards can also improve the return on total assets. Large enterprises can increase the return on total assets of the enterprise and the return on invested capital. The state-owned enterprises have a positive effect on the return on total assets of the enterprise. Enterprises in the western, central, and eastern region enterprises can increase their net profit, enterprise value and net profit, return on total assets and enterprise value respectively. The enterprises in Beijing-Tianjin-Hebei region, Guangdong-Hong Kong-Macao Greater Bay Area can improve their return on invested capital and enterprise value, average rate of return respectively. The participation in the development of national standards, industry standards and local standards can help increase their return on total assets, the return on total assets and enterprise value, enterprise value respectively. Finally, we suggestions are put forward to enhance enterprises’ enthusiasm to take part in standards development.
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