This study explores the factors that affect consumer adoption of reusable packaging in South Korea’s food delivery market. Adopting a mixed-method that includes interviews and an online survey of 137 consumers aged 18 to 30, the analysis, using an ordered probit model, reveals key drivers of the likelihood of switching to food delivery services using reusable packaging. Positive influences include environmental concerns, intention to take action on disposable packaging, willingness to pay extra, and awareness that reusable packaging does not require washing. However, challenges such as hygiene concerns and higher delivery fees deter consumers from switching to reusable package option. Demographic factors like living arrangements and gender show minimal impact. In response to the findings, the study suggests strategic solutions, including a pilot program, to overcome barriers and effectively demonstrate the benefits of reusable containers.

This research explores the intricate relationship between digitalization, economic development, and non-cash payments in the ASEAN-7 countries over a ten-year period from 2011 to 2020. Focusing on factors such as commercial bank branches, broad money, and inflation, the study employs panel data regression analysis to investigate their impact on automated teller machine (ATM) usage. The findings reveal that commercial bank branches significantly influence ATM usage, emphasizing the role of accessibility, services, and technological preferences. Broad money also shows a significant impact on ATM transactions, reflecting the interplay between fund availability and non-cash transactions. However, inflation does not exhibit a direct influence on ATM usage. The research underscores the importance of maintaining service quality and security in the banking sector to enhance digital financial inclusion. Future research opportunities include exploring diverse non-cash payment methods and extending studies to countries with significant global economic impacts. This research contributes valuable insights to policymakers aiming to enhance digital financial inclusion policies, ultimately fostering economic growth through the digital economy in the ASEAN-7 region.

The use of infrastructure as a catalyst for Indonesia’s economic growth faces significant challenges. One example is the construction projects, which have not reached the intended goal and have led to an increase in investment cost compared to the original plan. Additionally, the interaction between the government and companies involved in toll-road construction projects under the public-private partnerships (PPP) mechanism has yet to produce good quality project governance and expected project performance. This study aimed to find empirical data on the determination of project intellectual capital and project ownership structure through good project governance on toll-road project performance in Indonesia. This study adopted a quantitative approach that involved data collected through a survey conducted among toll-road projects from 2015 to 2019. The data was analyzed with Structural Equation Modeling Partial Least Square (SEM-PLS). The results showed that project intellectual capital and project ownership structure significantly affected good project governance. Good project governance Practices significantly affected project performance. Project intellectual capital and project ownership structure influenced project performance through the mediation of good project governance. Conversely, two hypotheses were not supported by the data, i.e., the effect of project intellectual capital and project ownership structure on project performance. The findings of this research contributed to the literature regarding the implementation of collaborative governance in PPPs toll road development projects in Indonesia by providing a framework and assessment tools, which could be valuable for researchers and policymakers in analyzing and evaluating the governance and performance of toll road construction PPP projects.

Public open spaces, such as squares, parks, and sports fields, serve as crucial hubs during and after disasters, fostering a sense of normalcy and community, promoting social cohesion, and facilitating community recovery. Additionally, they offer opportunities for promoting physical and mental well-being during such crises. This study aims to enhance the responsiveness of public open spaces to disasters by prioritizing disaster resilience in their planning and design. This study consists of two main stages. Firstly, a literature review is conducted to explore the current trends in research on public open space planning and design and the incorporation of disaster resilience. Results indicate that the primary focus of the current research on planning and designing public open spaces centers around sociocultural, psychological, environmental, and economic benefits. There is limited emphasis on integrating disaster resilience into public open space planning and design, leading to a lack of clear guidance for planners and architects. The emphasis on disaster resilience in public open space planning and design mainly began after 2010, with a notable increase observed in the last six years (2017–2023). This emphasis notably centers on climate change impacts, followed by floods, and then earthquakes. Secondly, drawing on the pivotal role of public open spaces during disasters, the importance of urban planning and design, and the existing gap in incorporating disaster resilience in current research on public open space planning and design, this study develops a novel framework for enhancing public open spaces’ responsiveness to disasters through resilient urban planning and design, based on four main disaster resilience criteria: multifunctionality, efficiency, safety, and accessibility. The insights gleaned from this study offer invaluable guidance to planners, architects, and decision-makers, empowering them to develop public open spaces that can effectively respond to various circumstances, ultimately contributing to bolstering community resilience and sustainability.

Land use changes have been demonstrated to exert a significant influence on urban planning and sustainable development, particularly in regions undergoing rapid urbanization. Tehran Province, as the political and economic capital of Iran, has undergone substantial growth in recent decades. The present study employs sophisticated Geographic Information System (GIS) instruments and the Google Earth Engine (GEE) platform to comprehensively track and analyze land use change over the past two decades. A comprehensive analysis of Landsat images of the Tehran metropolitan area from 2003 to 2023 has yielded significant insights into the patterns of land use change. The methodology encompasses the utilization of GIS, GEE, and TerrSet techniques for image classification, accuracy assessment, and change detection. The Kappa coefficients for the maps obtained for 2016 and 2023 were 0.82 and 0.87 for four classes: built-up, vegetation cover, barren land, and water bodies. The findings suggest that, over the past two decades, Tehran Province has undergone a substantial decline in ecological and vegetative areas, amounting to 2.4% (458.3 km2). Concurrently, the urban area and the barren lands have expanded by 287.5 and 125.5 km2, respectively. The increase in water bodies during this period is likely attributable to the reduction of vegetation cover and dam construction in the region. The present study demonstrates that remote sensing and GIS are excellent tools for monitoring environmental and sustainable urban development in areas experiencing rapid urbanization and land use changes.

Objective: This study synthesizes current evidence on the role of Artificial Intelligence (AI) and, where relevant, Open Science (OS) practices in enhancing Human Resource Management (HRM) performance. It focuses on recruitment processes, ethical considerations, and employee participation. Methodology: A systematic literature review was conducted in Scopus covering the period 2019–2024, following PRISMA guidelines. The initial search yielded 1486 records. After de-duplication and screening using Rayyan, 66 studies (≈ 4.4%) met the inclusion criteria, which targeted peer-reviewed works addressing AI-supported HR decision-making. A combined content and bibliometric analysis was performed in R (Bibliometrix) to identify thematic patterns and conceptual structures. Results: Analysis revealed four thematic clusters: 1) Implementation and employee participation emphasizing human-in-the-loop approaches and effective change management; 2) ethical challenges including algorithmic bias, transparency gaps, and data privacy risks; 3) data-driven decision-making delivering higher accuracy, fewer errors, and personalized recruitment and performance assessment; 4) operational efficiency enabling faster workflows and reduced administrative workloads. AI tools consistently improved selection quality, while OS practices promoted transparency and knowledge sharing. Implications: The successful adoption of AI in HRM requires employee engagement, strong ethical safeguards, and transparent data governance. Future research should address the long-term cultural, organizational, and well-being impacts of AI integration, as well as its sustainability.