Cross-border infrastructure projects offer significant economic and social benefits for the Asia-Pacific region. If the required investment of $8 trillion in pan-Asian connectivity was made in the region’s infrastructure during 2010–2020, the total net income gains for developing Asia could reach about $12.98 trillion (in 2008 US dollars) during 2010–2020 and beyond, of which more than $4.43 trillion would be gained during 2010–2020 and nearly $8.55 trillion after 2020. Indeed, infrastructure connectivity helps improve regional productivity and competitiveness by facilitating the movement of goods, services and human resources, producing economies of scale, promoting trade and foreign direct investments, creating new business opportunities, stimulating inclusive industrialization and narrowing development gaps between communities, countries or sub-regions. Unfortunately, due to limited financing, progress in the development of cross-border infrastructure in the region is low.

This paper examines the key challenges faced in financing cross-border projects and discusses the roles that different stakeholders—national governments, state-owned enterprises, private sector, regional entities, development financing institutions (DFIs), affected people and civil society organizations—can play in facilitating the development of cross-border infrastructure in the region. In particular, this paper highlights the major risks that deter private sector investments and FDIs and provides recommendations to address these risks.

Fire hazard is often mapped as a static conditional probability of fire characteristics’ occurrence. We developed a dynamic product for operational risk management to forecast the probability of occurrence of fire radiative power in the locally possible near-maximum fire intensity range. We applied standard machine learning techniques to remotely sensed data. We used a block maxima approach to sample the most extreme fire radiative power (FRP) MODIS retrievals in free-burning fuels for each fire season between 2001 and 2020 and associated weather, fuel, and topography features in northwestern south America. We used the random forest algorithm for both classification and regression, implementing the backward stepwise repression procedure. We solved the classification problem predicting the probability of occurrence of near-maximum wildfire intensity with 75% recall out-of-sample in ten annual test sets running time series cross validation, and 77% recall and 85% ROC-AUC out-of-sample in a twenty-fold cross-validation to gauge a realistic expectation of model performance in production. We solved the regression problem predicting FRP with 86% r² in-sample, but out-of-sample performance was unsatisfactory. Our model predicts well fatal and near-fatal incidents reported in Peru and Colombia out-of-sample in mountainous areas and unimodal fire regimes, the signal decays in bimodal fire regimes.

This study provides an evaluation of the environmental impact and economic benefits associated with the disposal of mango waste in Thailand, utilizing the methodologies of life cycle assessment (LCA) and cost-benefit analysis (CBA) in accordance with internationally recognized standards such as ISO 14046 and ISO 14067. The study aimed to assess the environmental impact of mango production in Thailand, with a specific focus on its contribution to global warming. This was achieved through the application of a life cycle assessment methodology, which enabled the determination of the cradle-to-grave environmental impact, including the estimation of the mango production’s global warming potential (GWP). Based on the findings of the feasibility analysis, mango production is identified as a novel opportunity for mango farmers and environmentally conscious consumers. This is due to the fact that the production of mangoes of the highest quality is associated with a carbon footprint and other environmental considerations.  Based on the life cycle assessment conducted on conventional mangoes, taking into account greenhouse gas (GHG) emissions, it has been determined that the disposal of 1 kg of mango waste per 1 rai through landfilling results in an annual emission of 8.669 tons of carbon. This conclusion is based on comprehensive data collected throughout the entire life cycle of the mangoes. Based on the available data, it can be observed that the quantity of gas released through the landfilling process of mango waste exhibits an annual increase in the absence of any intervening measures. The cost benefit analysis conducted on the life cycle assessment (LCA) of traditional mango waste has demonstrated that the potential benefits derived from its utilization are numerous. The utilization of the life cycle assessment (LCA) methodology and the adoption of a sustainable business model exemplify the potential for developing novel eco-sustainable products derived from mango waste in forthcoming time.

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.

“This paper’s purpose l is to determine whether certain firm-specific factors have an influence on the catering theory of dividend in the MENA region.” The catering theory of dividend related to the dividend policy by the different companies used in our paper to explain the decision by managers. The sample includes 600 non-financial firms listed stocks in the Stock Exchange of 6 countries from MENA region during the years 2010–2019. Catering theory explains why managers initiate (continue) to distribute dividends. A high dividend premium encourages managers to increase the level of dividend payment and explains why firms pay dividends or do not pay them thereafter. Investors should increase their demand for dividends to push managers to comply. Investors show their preference for dividend to self control, satisfaction and increase their profit. “This could be the catering incentive of the firm to decide to pay dividends”. Even although the result Investor preference for dividend is explained by different factors related to the firms characteristics from each firms is different from markets, it can be the evidence supporting the catering theory of dividend, not only in well-developed markets, but also in emerging markets such as our country.