Search Results (194)

Climate change-induced monsoon variability increasingly threatens the economic viability of renewable energy systems in Southeast Asia. While solar–wind hybrid systems are considered a promising solution, their economic resilience under dynamic monsoon conditions remains poorly understood—a critical research gap for climate-adaptive energy planning in monsoon-affected regions. This study aims to develop an integrated climate–technology–economics framework to assess the economic resilience of solar–wind hybrid systems under projected monsoon variability. The framework combines ERA5 reanalysis data, CMIP6 climate projections, techno-economic optimization via HOMER Pro, and a quantitative resilience assessment covering resistance (ΔLCOE%), robustness (CV~NPV~), and adaptive potential. The methodology is applied to representative ASEAN regions—Vietnam, Thailand, the Philippines, and Indonesia—to evaluate how monsoon-induced changes in solar and wind resources affect system performance. Results indicate that intensified monsoon variability reduces photovoltaic output during the rainy season by up to 15%, increases the levelized cost of energy (LCOE) by an average of 12.5%, and extends project payback periods by 2–4 years. Inland areas exhibit significantly higher vulnerability than coastal regions. However, optimized system configurations—particularly adjustments to the solar–wind capacity ratio and integration of battery energy storage—improve economic resilience by more than 20%. These findings provide quantitative evidence and actionable guidance for climate-resilient renewable energy planning in monsoon-affected ASEAN countries. Full article

This study examines how banks navigate the dual strategic imperatives of securing market power and optimizing multidimensional operational efficiency—technical, scale, and allocative efficiency—within emerging and transitional banking systems. Focusing on business model diversification and financial stability, this study also accounts for the conditioning roles of governance quality, institutional complexity, credit risk, and digitalization. Using bank-level data from Association of Southeast Asian Nations (ASEAN) and Middle East and North Africa (MENA) countries, the analysis applies Partial Least Squares Structural Equation Modeling (PLS-SEM) and multi-group analysis to assess direct, mediating, and moderating relationships. The results indicate that diversification and financial stability significantly strengthen market power, while their effects on efficiency are largely negative across efficiency dimensions. Governance quality partially mediates the stability–market power relationship, whereas institutional complexity weakens this linkage. Digital transformation maturity and market digitalization condition the diversification–efficiency nexus, with effects varying across efficiency types and regions. Overall, the findings reveal a strategic trade-off between competitive positioning and operational efficiency, emphasizing the importance of governance structures and digital capabilities in shaping bank performance across heterogeneous institutional contexts. Full article

Air transport networks function as strategic infrastructure whose structural evolution reflects broader geopolitical and economic forces. This study introduces a network-based interpretive framework for Geoeconomics in Air Transport by integrating complex network analysis with geoeconomic perspectives. It conceptualizes air transport networks as strategic economic infrastructure in which network topology encodes market access, power asymmetries, and resilience under geopolitical uncertainty. Using global civil aviation data, this paper constructs air transport networks at both the global level and across major regions—including the United States, Europe, the Middle East, ASEAN, China, and Japan—and compares passenger and cargo connectivity before (2019) and after (2023) the COVID-19 pandemic. Standard network metrics, such as centrality, topology, and connectivity, are used to quantify structural changes, which are subsequently interpreted through a geoeconomic lens. Global connectivity increased by approximately 8% in the post-pandemic period. In contrast, the United States—maintaining the most structurally resilient national air transport network—expanded by about 12%, while connectivity across Asian countries contracted, either domestically, internationally, or both. These patterns reflect a combination of intentional strategic responses and unintended structural adjustments. North American and European networks remain large-scale, meshed, and structurally resilient, whereas regions outside these core areas exhibit stronger hub-and-spoke dependence, both internally and in their connections with core regions. Such dependence signals persistent geoeconomic asymmetries and increased exposure to external shocks, despite higher traffic volumes per route. Betweenness centrality shifted markedly from European and North American hubs toward the Middle East, indicating the emergence of a geoeconomic intermediary region capable of sustaining connectivity across increasingly fragmented markets. The findings further demonstrate that, despite the United Kingdom’s withdrawal from the European Union, institutional and strategic realignments can enhance air transport network resilience in ways not anticipated by conventional geoeconomic interpretations of regional integration. By linking quantitative network outcomes with geoeconomic interpretation, this study provides reproducible insights into the strategic reconfiguration of global air transport systems under rising geopolitical uncertainty. Full article

This paper re-examines the role of trade and FDI inflows in accelerating the process of industrial growth involving countries belonging to the “Association of Southeast Asian Nations (ASEAN)” region. Trade openness and foreign direct investment (FDI) have improved the growth performance of numerous economies and regions over the years. However, the specific role of both trade openness and FDI inflows in advancing the industrial growth process of economies has yet to be investigated in the case of economies belonging to ASEAN. This study analyzes data from 2000 to 2023 and employs several relevant econometric tools, including the “Pooled Ordinary Least Squares (POLS)”, “Fixed Effects Filter (FEF)”, “Feasible Generalized Least Squares (FGLS)” and “Two Stages Least Squares (TSLS)”, to assess the specific impact of both trade openness and FDI inflows on industrial growth. Our findings show that both trade openness and FDI have advanced the industrial growth of ASEAN member economies. In terms of relative importance, the impact of trade openness is higher as compared to FDI inflows on the industrial sector. Similarly, the results demonstrate that the industrial growth of ASEAN economies could be explained positively by increased domestic investment and government expenditures. Moreover, our results indicate that the inflation rate and the natural resource sector have adversely impacted industrial growth. Finally, the labor force has not had the desirable positive impact on the industrial progress of ASEAN economies. The obtained results are robust across alternative specifications and estimation techniques. Therefore, our results have important policy implications for ASEAN economies. Full article

This study examines global econo-environmental capability for 118 countries over 1995 to 2024 using a five-lens framework covering productive capacity (PC), developmental momentum (DM), resource efficiency (RE), degradation and depletion ratio (DDR), and remaining development potential (RDP). Using pooled k-means, a stable four archetype typology is identified and shown to persist over time. The analysis assesses how archetypes characterize country–year outcomes (RQ1), whether cross-sectional fairness is changing and relates to frontier slowdown (RQ2), and how archetypes, distance, and regional context shape transition probabilities and club convergence (RQ3). Inequality in five-dimensional capability declines slightly over the period (Gini from 0.109 to 0.092 and Palma from 1.563 to 1.464), implying modest convergence rather than increasing polarization. Average capability also improves, with larger gains for initially distant countries and smaller gains near the frontier, which is consistent with mild club convergence. Regionally, high capability cases are concentrated in Western Europe and North America, while sustained upgrading is observed in parts of Eastern Europe, mixed stability is observed in East and Central Asia, and selective advances are observed in ASEAN. Policy implications should be based on a country’s archetype and its distance to the capability ideal. Lagging countries should prioritize diffusion of proven high efficiency options and basic capability building, while frontier countries should priorities innovation, structural change, and deeper decarbonization. Policy emphasis should be updated as countries move within the capability space over time. Full article

Global economic developments are currently facing economic fluctuations and the climate change crisis, which demand a development approach that integrates growth with environmental sustainability. Although participation in Global Value Chains (GVCs) has become the backbone of the global economy, many countries, including Indonesia and most ASEAN countries, are still in upstream positions with high carbon intensity and low added value. This condition hinders sustainable economic growth and contributes to increased global emissions. This study aims to analyze how the position of the industrial sector in the GVCs can drive sustainable green economic growth. Using data from five ASEAN countries for the 2010–2023 period, this study employed the Generalized Method of Moments (GMMs) dynamic panel model to address the issues of endogeneity and individual heterogeneity. The results show that movements to upstream positions in GVCs, FDI, and political stability have a significant and positive impact on green economic growth. These findings highlight the need for tailored policies to encourage the development of green industries and improve global competitiveness. Full article

This study investigates the influence of board characteristics—specifically board tenure and board-specific skills—on the quality of ESG reporting among listed firms in five ASEAN countries (Indonesia, Malaysia, Singapore, Thailand, and the Philippines) from 2021 to 2023. Using panel data of 609 firms (1827 firm-year observations) obtained from Refinitiv Eikon, ESG reporting is measured through the reporting score, while board tenure is proxied by the average years of directors’ service and board-specific skills by the proportion of directors with financial or industry expertise. The analysis employs fixed-effects regression with firm-level clustered standard errors to account for unobserved heterogeneity and robust inference. The findings reveal that board tenure has no significant effect on ESG reporting, suggesting that accumulated experience does not necessarily enhance disclosure. In contrast, board-specific skills exhibit a positive and significant impact, highlighting the importance of technical competence in driving transparency. Control variables show that firm age contributes positively to ESG disclosure, while robustness checks confirm the stability of results across alternative specifications and clustering dimensions. Sub-sample country analyses further indicate institutional variations, with board expertise mattering more in Singapore and Indonesia, and firm age in Malaysia, Thailand, and the Philippines. The study offers theoretical and policy implications for strengthening governance reforms and advancing ESG transparency in emerging markets. Full article

Dengue fever is one of the most important mosquito-borne diseases worldwide. The Association of Southeast Asian Nations (ASEAN) region is a high-incidence area for dengue fever and a primary source of imported cases in China. Based on the Global Burden of Disease (GBD) data, this study statistically analyzed the spatiotemporal distribution of the age-standardized incidence rate (ASR) of dengue fever in ten ASEAN countries from 1990 to 2021. Joinpoint regression was used to analyze long-term trends, and future trends from 2022 to 2031 were predicted. In 2021, the ASR of dengue fever varied widely among ASEAN countries. Singapore had the highest ASR (8715 cases per 100,000 persons). After 2000, countries, such as Brunei Darussalam, experienced short-term outbreaks. From 1990 to 2021, seven countries showed a significant upward trend in the ASR (AAPC > 0, p < 0.05). Predictions indicate that the Philippines will continue to see a rising ASR from 2022 to 2031, and the dengue fever situation in ASEAN countries is severe and heterogeneous. We recommend differentiated control measures according to the ASR level of the source country in China. The results can support the development of Sino-ASEAN collaborative strategies for dengue fever prevention and control. Full article

After the carbon neutrality goal was proposed, the question of how to achieve low-carbon and green development has become the focus of ASEAN countries. The digital economy will play an important role in promoting carbon emission reduction in ASEAN countries. This paper measures the digital economy index of ASEAN countries and explores the impact of the digital economy on carbon emission intensity across 10 ASEAN countries from 2011 to 2020. The results show that the digital economy can reduce the intensity of carbon emissions in ASEAN countries. In addition, the impact of the digital economy on carbon emission intensity will vary depending on the level of economic development, resource endowment, and government financial support capacity. The mechanism analysis shows that the digital economy can ultimately reduce the intensity of carbon emissions by promoting industrial structure upgrading, stimulating technological innovation, and promoting the transformation of energy consumption structure. Based on the above conclusions, specific recommendations are proposed for the digital economy to realize carbon reduction in ASEAN countries. Full article

Global warming is recognized as a climate crisis that extends beyond a mere increase in the Earth’s temperature, triggering rapid and widespread climatic changes worldwide. In particular, the frequency and intensity of extreme rainfall events have increased in Korea and the Association of Southeast Asian Nations (ASEAN) region, leading to a significant increase in flood damage. The growing number of large-scale hydrological disasters underscores the urgent need for accurate and rapid flood-forecasting systems that can support disaster preparedness and mitigation. Compared with conventional physics-based forecasting systems, artificial intelligence (AI) models can provide faster predictions using limited observational data. In this study, a river water-level prediction model was constructed using real-time observation data and a long short-term memory (LSTM) algorithm, which is a recurrent neural network-based deep learning approach suitable for hydrological time-series forecasting. A repeated k-fold cross-validation technique was applied to enhance model generalization and prevent overfitting. In addition, water-level differencing was employed to convert nonstationary water-level data into stationary time-series inputs, thereby improving the prediction stability. Water-level observation stations in the Philippines, Indonesia, and the Republic of Korea were selected as study sites, and the model performance was evaluated at each location. The differenced LSTM model achieved a root mean square error of 0.13 m, coefficient of determination (R²) of 0.866, Nash–Sutcliffe efficiency (NSE) of 0.844, and Kling–Gupta efficiency of 0.893, thus outperforming the non-differenced baseline by approximately 17%. The repeated k-fold validation approach was particularly effective when the training data period was short or the number of input variables was limited. These results confirm that ensuring temporal stationarity and applying repeated cross-validation can significantly enhance the predictive accuracy of real-time flood forecasting. The proposed framework exhibits strong potential for implementation in regional early warning systems across data-limited flood-prone areas in the ASEAN region. Ongoing studies that apply and verify this approach in diverse hydrological contexts are expected to further improve and expand AI-based flood prediction models. Full article

Accessible tourism is a critical aspect of sustainable development, yet many Southeast Asian destinations lack sufficient infrastructure and services for elderly and disabled travelers. This study develops a Mixed-Integer Linear Programming (MILP) framework to optimize travel itineraries, balancing cost, accessibility, and cultural–environmental priorities. A national accessibility database for Thailand was created, encompassing airports, hospitals, public transport nodes, cultural landmarks, and natural attractions. Compared to baseline conventional itineraries—defined as standard travel routes planned without specific accessibility considerations or optimization techniques—the MILP-optimized routes reduce average travel time by 15–20% and improve accessibility scores by 25%. Sensitivity analyses reveal trade-offs between economic efficiency, inclusivity, and infrastructure capacity, while a schematic accessibility network highlights structural fragmentation among airports, hospitals, and secondary attractions. Scenario analyses show that stricter accessibility thresholds improve inclusivity (index: 0.65 to 0.80) but restrict destination options, whereas high-demand scenarios increase costs and reduce inclusivity. A survey of 30 smart wheelchair users indicates high satisfaction with individualized programs and GPS connectivity. These findings underscore the need for investment in multimodal integration, accessibility upgrades, and a national database to enhance inclusive tourism planning. The framework is transferable to other ASEAN countries, contributing to SDG 3, 8, and 11. Overall, this study should be viewed as a prototype or exploratory contribution, with limitations in real-time applicability, generalizability, and implementation of environmental and ethical aspects. Full article

The rapid growth of electric vehicle (EV) adoption in Malaysia is projected to generate substantial volumes of end-of-life lithium-ion batteries, creating both environmental challenges and opportunities for repurposing into second-life batteries (SLBs). This study investigates the technical, economic, and regulatory feasibility of deploying SLBs for photovoltaic (PV) energy storage in petrol stations, an application aligned with the nation’s energy transition goals. Laboratory testing of Nissan Leaf ZE0 battery modules over a 120-day operation period demonstrated stable cycling performance with approximately 7% capacity fade, maintaining state-of-health (SOH) above 47%. A case study of a 12 kWp PV–SLB hybrid system for a typical Malaysian petrol station shows 45 kWh of usable storage, capable of offsetting a daily electricity demand of 45 kWh, reducing capital cost by 30–50% compared to new lithium-ion systems, and achieving 70–80% lifecycle CO₂ emission reductions. The proposed architecture leverages SLBs’ suitability for slower, steady discharge to provide reliable nighttime operation and grid load relief, particularly in semi-urban and rural stations. Beyond technical validation, the paper evaluates economic benefits, environmental impacts, and Malaysia’s regulatory readiness, identifying gaps in certification standards, reverse logistics, and workforce skills. Strategic recommendations are proposed to enable large-scale SLB deployment and integration into hybrid PV–petrol station systems. Findings indicate that SLBs can serve as a cost-effective, sustainable energy storage solution, supporting Malaysia’s National Energy Transition Roadmap (NETR), advancing circular economy practices, and positioning the country as a potential ASEAN leader in battery repurposing. Full article

Bangkok is the largest city in Thailand and the second largest city in Southeast Asia. Due to the rapid urbanization and upgrading of economic structures, the real estate market in Bangkok is not only constrained by domestic factors but also fluctuates with international economic cycles. Bangkok’s long history, diverse culture, developed economy, and incomplete land infrastructure make the formation of housing prices particularly complex. In this study, we collected 13,175 residence transaction data from 2076 different neighborhoods in Bangkok and explored multiscale effects of various land infrastructure factors on housing prices in Bangkok at the neighborhood level. Our analysis not only supports land planning departments of Bangkok to make more reasonable facility planning but also provides new insights into driving mechanisms of housing prices in other cities of Thailand and ASEAN countries. Full article

Sustainable tourism development has emerged as a strategic priority across ASEAN countries, yet the role of green innovation and environmentally responsible investment in shaping tourism outcomes remains underexplored. Existing studies often overlook the spatial interdependencies that characterize regional integration and cross-border environmental dynamics. This study investigates how green patents and green foreign direct investment (FDI) influence sustainable tourism development, both within and across ASEAN nations. Drawing on endogenous growth theory, ecological modernization, and FDI spillover frameworks, the analysis employs a Spatial Durbin Model (SDM) using panel data from 2000 to 2023. The findings reveal that green innovation and green FDI significantly enhance tourism development, with notable spatial spillover effects that benefit neighboring countries. These effects are most pronounced in leading ASEAN economies, where institutional capacity and absorptive readiness amplify the impact of green practices. The relationship is further shaped by economic growth, human capital, and political stability, while environmental degradation and inflation pose constraints. The study underscores the nonlinear and regionally heterogeneous nature of green tourism development, offering policy insights for fostering inclusive, resilient, and environmentally sustainable tourism strategies across ASEAN. Full article

This study examines the long-run relationship between carbon dioxide (CO₂) emissions and key macroeconomic and sectoral drivers in ten ASEAN economies from 1995 to 2023. Employing Driscoll–Kraay standard errors, Prais–Winsten regression, heteroskedastic panel-corrected standard errors, Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR) estimators, the analysis accounts for cross-sectional dependence, slope heterogeneity, and endogeneity. Results indicate that GDP exerts a more-than-unitary positive effect on emissions, with a negative GDP-squared term supporting the Environmental Kuznets Curve. Agriculture raises emissions through land-use change and high-emission cultivation practices, while tourism shows a negative association likely reflecting territorial accounting effects. Trade openness increases emissions, highlighting the carbon intensity of export structures, whereas foreign direct investment exerts no significant net effect. These results suggest that ASEAN economies must accelerate renewable energy adoption, promote climate-smart agriculture, embed enforceable environmental provisions in trade policy, and implement rigorous sustainability screening for FDI to achieve low-carbon growth trajectories. Full article