This study investigates the viability and sustainability of proposed landfill sites based on the uncapacitated facility location problem framework utilising the SmartPLS4 Structural Equation Modelling. Investigating the Cape Coast Metropolis, a stratified sampling method selected 400 samples out of which 320 valid respondents were used as the basis for the analysis. Through statistical analysis, significant correlations were identified among community acceptance, environmental impact, facility accessibility, site sustainability, and operational efficiency. However, no significant correlation was found between economic viability and site sustainability. Furthermore, the proposed indirect mediation pathway from operational efficiency to site sustainability via facility accessibility was also statistically insignificant. Employing the use of SmartPLS4 approach in studying the application of uncapacitated facility location problem framework, deepens the understanding of landfill viability and sustainability dynamics. This research contributes to the environmental sciences and sustainability by providing insights into landfill management strategies and emphasising the importance of community engagement and environmental performance in achieving sustainable outcomes. Future research could refine the model by including additional variables like technological advancements and regulatory frameworks, conducting longitudinal studies to track landfill dynamics over time, and undertaking comparative studies across different geographical regions. This could provide insights into management approaches’ applicability. Interdisciplinary collaborations are recommended to address the multifaceted challenges of landfill sustainability.

Sustainability is a top priority for municipal administrations, particularly in large urban centers where citizens rely on transportation for work, study, and daily errands. Public transportation faces a significant challenge beyond availability, performance, safety, and comfort: balancing the cost for the city with fare attractiveness for passengers. Meanwhile, bicycles, supported by public incentives due to their clean and healthy appeal, compete with public transit. In Curitiba, the integrated transport system has been consistently losing passengers, exacerbated by the pandemic and the rise in private vehicle usage. To address this, the city is expanding bicycle infrastructure and electric bike rental services, impacting public transit revenue, and prompting the need for financial compensation to maintain affordable fares for those reliant on public transport. Therefore, this study’s objective is to analyze the bicycle’s impact on public transportation, considering the impact of public policies on economic and social efficiency, not just ecological and environmental factors. Data from six main bus lines were collected and analyzed in two separate linear regression models to verify the effects of new bicycles in circulation, bus tariffs, and weather conditions on public transportation demand. Research results revealed a significant impact of bus tariffs and fuel prices on the number of new bicycles that are diverting passengers from public transportation. The discussion may offer a different perspective on public transport policies and improve city infrastructure investments to strategically change the urban form to address social and economic issues.

This study investigated the utilization of Artificial Intelligence (AI) in the Recruitment and Selection Process and its effect on the Efficiency of Human Resource Management (HRM) and on the Effectiveness of Organizational Development (OD) in Jordanian commercial banks. The research aimed to provide solutions to reduce the cost, time, and effort spent in the process of HRM and to increase OD Effectiveness. The research model was developed based on comprehensive review of existing literature on the subject. The population of this study comprised HR Managers and Employees across all commercial banks in Jordan, and a census method was employed to gather 177 responses. Data analysis was conducted using Amos and SPSS software packages. The findings show a statistically significant positive impact of AI adoption in the Recruitment and Selection Process on HR Efficiency, which in turn positively impacted OD Effectiveness. Additionally, the study indicated that the ease-of-use of AI technologies played a positive moderating role in the relationship between the Recruitment and Selection Process through AI and HR Efficiency. This study concludes that implementing AI tools in Recruitment is vital through improving HR Efficiency and Organization Effectiveness.

Given the eclectic and localized nature of environmental risks, planning for sustainability requires solutions that integrate local knowledge and systems while acknowledging the need for continuous re-evaluation. Social-ecological complexity, increasing climate volatility and uncertainty, and rapid technological innovation underscore the need for flexible and adaptive planning. Thus, rules should not be universally applied but should instead be place-based and adaptive. To demonstrate these key concepts, we present a case study of water planning in Texas, whose rapid growth and extreme weather make it a bellwether example. We review historic use and compare the 2002, 2007, 2012, 2017 and 2022 Texas State Water Plans to examine how planning outcomes evolve across time and space. Though imperfect, water planning in Texas is a concrete example of place-based and adaptive sustainability. Urban regions throughout the state exhibit a diversity of strategies that, through the repeated 5-year cycles, are ever responding to evolving trends and emerging technologies. Regional planning institutions play a crucial role, constituting an important soft infrastructure that links state capacity and processes with local agents. As opposed to “top-down” or “bottom-up”, we frame this governance as “middle-out” and discuss how such a structure might extend beyond the water sector. 

Research on retailers’ behavioral intention and behavior of using the omnichannel ecommerce solution (OES) used the Unified Theory of Acceptance and Use of Technology (UTAUT2) model and supplemented the other factors such as seamless supply, omnichannel integration. Research concerns about behavioral intention and behavior of using OES as this is a global trend; OES has become one of the top priorities for businesses to thrive in the rapidly changing market and retain customers; increasingly high standards are being set for digital experiences. Therefore, retailers must quickly adapt to new trends for sustainable development to keep up with the transformation and increase the use of OES. The results show that effort expectation, social influence, hedonic motive, retailers’ capacity, seamlessly connecting have a positive impact on retailers’ behavioral intention and behavior of using OES. Behavioral intention and favorable conditions have a positive impact on behavior of using OES. Meantime, omnichannel integration have a negative impact on behavior of using OES in Vietnam. This research helps managers and OES providers to develop their skills and expertise, and the study results may prove diagnostically useful to the retailers’ behavioral intention and behavior of using OES.

This study examined the role of cryptocurrencies in tourism and their acceptance across EU regions, with particular attention to the digital transformation precipitated by the COVID-19 pandemic. The analysis focuses on the relationship between cryptocurrency acceptance points and the intensity of tourism, highlighting that the acceptance of cryptocurrencies is significantly correlated with tourism services. The literature review highlighted that Web 3.0, especially blockchain technology and decentralized applications, opens new possibilities in tourism, including secure and transparent transactions, and more personalized travel experiences. The research investigated cryptocurrency acceptance points and the intensity of tourism within the EU. The study illuminates that the acceptance of cryptocurrencies significantly correlates with tourism services. The data and methodology demonstrated the analysis methods for examining the relationship between cryptocurrency acceptance points and tourism intensity, including the use of clustering neural networks and Eurostat data utilization. The results showed a positive correlation between the number of cryptocurrency acceptance points and tourism intensity in the EU, affirming the research hypothesis. According to the regression analysis results, each additional cryptocurrency acceptance point is associated with an increase in tourism intensity. The significance of the research lies in highlighting the growing role of digital payment solutions, especially cryptocurrencies, in tourism, and their potential impacts on the EU economy. The analysis supports that the intertwining of tourism and digital financial technologies opens new opportunities in the sector for both providers and tourists.