Asia-Pacific Journal of Regional Science最新文献

{"title":"Measuring vulnerability to energy poverty in archipelagic regions: a composite index approach from Indonesia","authors":"Eva Fauzyah Rahmah,&nbsp;Eka Intan Kumala Putri,&nbsp;Hania Rahma","doi":"10.1007/s41685-026-00436-7","DOIUrl":"10.1007/s41685-026-00436-7","url":null,"abstract":"<div><p>This study aimed to develop a regionally adapted composite index to measure vulnerability in energy poverty across Indonesia’s provinces and to analyze spatial disparities using a multidimensional vulnerability framework. The central research question was: <i>How can geographic</i>,<i> socio-economic</i>,<i> and institutional characteristics be integrated into a composite index to identify and systematically compare regional vulnerability in energy poverty across Indonesia?</i> The Regional Vulnerability to Energy Poverty Index (RVEPI) integrated 15 indicators across three Intergovernmental Panels on Climate Change (IPCC)-based dimensions: exposure, sensitivity, and adaptive capacity. Unlike previous indices, RVEPI included context-specific variables such as the island-to-land area ratio and multi-hazard risk to capture the geographic fragmentation and disaster vulnerability unique to archipelagic nations. The study was guided by the hypothesis that <i>regions with high exposure and sensitivity and low adaptive capacity will exhibit the highest energy poverty levels</i>. The RVEPI was constructed using both dimension-weighted and variable-weighted aggregation schemes. Validation through Spearman’s rank correlation (ρ = 0.99) and mean absolute deviation confirmed the index’s robustness. K-means clustering revealed three typologies of regional vulnerability: severe multidimensional, moderate structural, and low vulnerability with strong adaptive capacity. Findings highlighted a persistent east–west divide, with provinces in Eastern Indonesia, such as Papua, Maluku, and East Nusa Tenggara, ranking highest in vulnerability due to remoteness, limited infrastructure, and weak governance capacity. The RVEPI offers a spatially sensitive, policy-relevant diagnostic tool to inform equitable energy planning in fragmented geographies. It also supports the just implementation of Sustainable Development Goal 7 (SDG 7) in Indonesia and provides a replicable framework for other island nations facing similar challenges </p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"10 3","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148349756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uneven smartness: assessing infrastructure capabilities and size-class disparities in India’s Smart Cities Mission","authors":"Iman Banerjee,&nbsp;Ratnadeep Dutta","doi":"10.1007/s41685-026-00426-9","DOIUrl":"10.1007/s41685-026-00426-9","url":null,"abstract":"<div><p>A smart city agenda is commonplace across countries of the Global South and is very often regarded as imperative to enhance urban quality of life by popular urban discourse. The present research initiated an intensive examination of cities selected under the ‘Smart Cities Mission’ (SCM) in India, at a time when the mission is yet to reach completion. This study evaluated the infrastructure capabilities and performance variations across 96 cities selected under India's SCM to address two critical questions: In what way does the urban size-class hierarchy reproduce performance inequalities among cities selected under the SCM? And to what extent do regional disparities shape uneven patterns of smart infrastructure development and practices across Indian cities? We employed a multi-criterial analysis framework encompassing 7 domains and 56 indicators drawn from the AMPLIFI 2.0 platform and official government reports. The Dimension Index Method was used for data normalization, followed by Pearson’s correlation and ANOVA tests to examine size-class paradoxes. The results revealed striking inter-city variations in composite smartness scores, ranging from 1.351 (Shillong) to 4.283 (Pune). Statistical analysis further confirmed a significant positive correlation (r = 0.425, p &lt; 0.01) between city size and performance, with larger metropolitan cities substantially outperforming smaller urban centers. In addition, cities from North-Eastern States and Union Territories demonstrated notably lower composite scores. The findings expose a persistent size-class paradox where resource-scarce smaller cities, despite policy intentions of inclusive development, remain disadvantaged in accessing and implementing smart technology-driven governance alternatives. These findings add robust empirical grounding to broader critiques of territorial justice in India’s urban policy framework.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"10 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s41685-026-00426-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148172905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Carbon mitigation, population structure and renewable energy in China: mitigation amidst aging and urban populations","authors":"Edmund Ntom Udemba,&nbsp;Nazakat-Ullah Khan,&nbsp;Ceren Demir,&nbsp;Xuhui Peng,&nbsp;Fengyi Yang","doi":"10.1007/s41685-026-00434-9","DOIUrl":"10.1007/s41685-026-00434-9","url":null,"abstract":"<div><p>The focus of this study is on the environmental implication of aging population -population above 65(PO65), and the mitigating power of renewable energy. The aging population and urban population in China have a disaggregated impact on its carbon mitigation goals. Therefore, it is essential to investigate and explain how different population structures, specifically the aging population and urbanization, impact China’s environmental development, and the ability of renewable energy to achieve its carbon mitigation goals. In line with China’s climate agenda, it is necessary to evaluate the drivers of its carbon emissions on the basis of the disaggregated pattern of the population structure and draw a roadmap on how to improve China’s environmental quality. The study selected and applied the following variables for empirical analysis of the topic: aging population (population above 65), urban population, income (GDP), renewable energy, and investment (FDI). China’s time series and secondary data for the period between 1979 and 2024 were applied for the empirical analyses of this study. To estimate the strength of connections among these factors, we employed the dynamic autoregressive distributed lag (DARDL) methodology for the analysis of the short-run and long-run relationships. Additional tests (fully modified ordinary least squares (FMOLS) and causality methods) were applied as robustness to the main test. All things being equal, results from both estimations revealed that aging population and renewable energy positively impact China’s environmental development through the reduction of carbon emissions, while economic growth, urban population, and FDI negatively impact China’s environmental development through an increase in carbon emissions. In conclusion, China can achieve its carbon goal by framing its climate policy around renewable energy sources.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"10 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148172904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probabilistic vulnerability analysis of converted rice fields in the mamminasata urban area","authors":"Ahmad Firman Ashari,&nbsp;Risma Neswati,&nbsp;Samsu Arif","doi":"10.1007/s41685-026-00433-w","DOIUrl":"10.1007/s41685-026-00433-w","url":null,"abstract":"<div><p>In rice-dependent regions of Asia—including Indonesia, where rice is a primary staple—urban expansion increasingly drives the conversion of irrigated rice fields, posing risks to food security and environmental sustainability. This study analyzed the vulnerability of rice fields to conversion in the Mamminasata Urban Area of Indonesia and identified the factors influencing this vulnerability using a machine learning approach based on the Random Forest Algorithm. Sentinel-2 satellite imagery from 2016 to 2024 was employed for land use classification and change detection, while various demographic and agronomic spatial variables served as predictors. Variable selection was performed using the Variance Inflation Factor (VIF) to minimize multicollinearity. Hyperparameter optimization was executed through RandomizedSearchCV with 5-fold cross-validation. The model was trained on balanced data using the Synthetic Minority Over-sampling Technique (SMOTE) and evaluated based on accuracy and classification metrics. The results indicated that most rice fields exhibit low vulnerability to conversion. However, significant areas with moderate to high vulnerability existed, particularly near rapidly developing urban zones. The primary factors influencing land conversion were assessed land value and distance to secondary roads, highlighting the dominant role of economic and infrastructure considerations over agronomic factors. The resulting vulnerability probability map serves as a crucial spatial decision-making tool for urban planners and policymakers. We recommend reinforcing land protection policies in designated agricultural zones to mitigate uncontrolled land conversion and promote sustainable urban development.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"10 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148009108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resource–growth nexus in the Association of Southeast Asian Nations and South Asia: spatial dependence and regional heterogeneity","authors":"Tennyson Pangambam","doi":"10.1007/s41685-026-00427-8","DOIUrl":"10.1007/s41685-026-00427-8","url":null,"abstract":"<div><p>This paper examines the resource–growth nexus in the Association of Southeast Asian Nations (ASEAN) and South Asia regions through a spatial econometric framework. Building on the resource curse–blessing debate, I use annual panel data for fifteen countries spanning 1996 to 2021. The baseline specification uses a pooled Ordinary Least Squares (OLS) regression with Gross Domestic Product per capita growth as the dependent variable and natural resource rents, foreign direct investment, trade, and population growth as explanatory variables. To capture cross-border interdependencies often overlooked in conventional models, I extend the analysis by using the Spatial Durbin Model (SDM) with a k-nearest neighbor spatial weights matrix (k = 2). This allows identification of both direct domestic effects and indirect spatial spillover effects. The pooled regression finds the negative impact of natural resource rents on economic growth, consistent with the resource curse hypothesis. The SDM confirms and strengthens this evidence by revealing significant negative spatial spillovers. Increases in resource dependence in one country reduce growth both domestically and in neighboring economies. Overall, across multiple model specifications, the findings provide robust evidence in support of the resource curse hypothesis for the combined ASEAN and South Asia sample. Further, regional heterogeneity is also evident. ASEAN countries exhibit a strong resource curse with negative domestic and cross-border effects, while South Asia shows signs of a resource blessing domestically but without significant spatial spillovers. Population growth exerts consistently negative effects across specifications. These results underscore the importance of managing resources within a spatially interdependent regional context with policy implications for cooperative resource governance, diversification strategies, and demographic management.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"10 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147938700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatio-temporal heterogeneity effect of digital talent mobility on economic growth: evidence from urban agglomerations in China","authors":"Yuanfang Chen,&nbsp;Wee-Yeap Lau,&nbsp;Lim-Thye Goh","doi":"10.1007/s41685-026-00430-z","DOIUrl":"10.1007/s41685-026-00430-z","url":null,"abstract":"<div><p>This study examines the spatio-temporal heterogeneity impacts of digital talent mobility on economic growth across five major Chinese urban agglomerations. Based on panel data analysis using the Geographically and Temporally Neural Network Weighted Regression (GTNNWR) model, our findings show first, overall digital talent flow has sustained positive effects in advanced regions. Second, intra-regional flows generate more stable growth than inter-regional flows. Third, while inflows promote growth, outflows reduce innovation in developed areas but ease labor imbalances in periphery cities. As a policy implication, this study advocates region-specific talent strategies to optimize mobility and support balanced development.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"10 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147938766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nexus between growth trajectories and carbon dioxide emissions: re-examining the environmental Kuznets curve for Asian countries","authors":"Puja Biswas,&nbsp;Saddam Hossain Mondal","doi":"10.1007/s41685-026-00428-7","DOIUrl":"10.1007/s41685-026-00428-7","url":null,"abstract":"<div>\u0000 \u0000 <p>This study examined the growth patterns of carbon dioxide (CO₂) emissions for 29 selected Asian countries from 1990 to 2022. The growth patterns of per capita emissions of carbon dioxide for different countries were estimated by applying the trend-stationary or difference-stationary process. The growth rates of per capita CO₂ emissions for most Asian countries were either medium or high over the study period. The shape of the Environmental Kuznets curve was N-shaped for a few selected countries on the continent. Most countries maintained an expensive negative decoupling relationship between emissions of CO₂ and economic growth. The study also used the panel Autoregressive Distributed Lag Model (ARDL) method for the estimation of long-run and short-run relationships between emissions of CO₂ and a few environment-related indicators of selected Asian countries. The panel unit root test and Pedroni cointegration tests established evidence in favor of a long-run relationship between emissions of CO₂ and its determinants. In conclusion, the emissions of CO₂ in most of the selected countries can be reduced with improvements in increases in forest area and higher use of renewable energy.</p>\u0000 </div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"10 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147797156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Population aging and total factor productivity: empirical evidence from China","authors":"Hongyu Ding,&nbsp;Hongmei Shao,&nbsp;Zizhou Ding,&nbsp;Boan Zhao","doi":"10.1007/s41685-026-00431-y","DOIUrl":"10.1007/s41685-026-00431-y","url":null,"abstract":"<div><p>Acceleration and deepening of population aging pose substantial challenges to global economic growth. Enhancing total factor productivity (TFP) has emerged as a pivotal strategy to mitigate these challenges and sustain long-term economic development. This paper examines the impact, mechanisms and spatial effects of population aging on TFP using data from 30 Chinese provinces between 2006 and 2019. The results indicate that population aging significantly hinders the improvement of TFP. The primary mechanisms through which population aging hinders TFP growth include constraining factor structure optimization, impeding technological innovation and reducing factor allocation efficiency. This paper also reveals that the negative impact of population aging on TFP is most prominent in the Northern Coastal Economic Zone and the Middle Yangtze River Economic Zone. Moreover, the impact of gradual population aging on TFP is not significant, but when population aging enters an accelerated period, it can have a significant negative impact on TFP. Further analysis shows that population aging does not have significant spatial spillover effects on TFP in neighboring regions, and its negative impact mainly exists within the local regions. In conclusion, the impact of population aging on TFP provides more direct empirical evidence and decision-making references for China to actively respond to population aging and improve TFP from both theoretical and empirical perspectives.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"10 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147797155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prioritization of risks associated with mining permit restrictions in Indonesia’s new capital region: analytic hierarcy process and fuzzy-analytic hierarcy process approach","authors":"Agus Miswanto,&nbsp;Umar Dani,&nbsp;David Candra Birawidha,&nbsp;Kusno Isnugroho,&nbsp;Ridwan Sutriadi,&nbsp;Muhammad Ihsan Yudanto,&nbsp;Anandhika Arifianto,&nbsp;Meisha Putra Dewan,&nbsp;Amelia Andriani,&nbsp;Hendra Prasetia,&nbsp;Gyan Prameswara,&nbsp;Himawan Tri Bayu Murti Petrus","doi":"10.1007/s41685-026-00432-x","DOIUrl":"10.1007/s41685-026-00432-x","url":null,"abstract":"<div><p>The relocation of the capital of Indonesia to East Kalimantan has introduced a policy restricting the expansion of mining business permits as part of the sustainable development agenda. While aligned with long-term environmental and governance objectives, this policy generates potential risks for government institutions, industry, and local communities. This study applied the Analytic Hierarchy Process (AHP) combined with Fuzzy AHP to identify and prioritize these strategic risks. A hierarchical framework was constructed based on four main criteria—economic, regulatory, social and environmental—further elaborated into 21 sub-criteria validated through literature review and expert consultation. The sub-criteria were derived using a multi-stage process involving literature synthesis and expert judgment to establish content validity prior to the AHP–Fuzzy AHP analysis. Data were collected via structured expert questionnaires and analyzed using triangular fuzzy number weighting and ratio consistency testing. The results indicated that economy risks, particularly reduced investment and rising compliance costs, hold the highest priority weight (0.302), followed by social risk (0.274) and regulation risks (0.240). Environmental risks (0.184), while comparatively lower in aggregate weight, remained critical in relation to reclamation obligations and pollution management. These findings provide a basis for evidence-based mitigation strategies and support a just and orderly transition in mining governance during the establishment of the new capital region.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"10 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147797157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the role of environmental, social and governance factors in enhancing bank profitability in South Asia","authors":"Masud Rana,&nbsp;Md. Kamruzzaman,&nbsp;Md. Abdullah Al Mamun,&nbsp;Md. Kamal Hossain,&nbsp;S. M. Shahedul Alam,&nbsp;Sutap Kumar Ghosh","doi":"10.1007/s41685-026-00429-6","DOIUrl":"10.1007/s41685-026-00429-6","url":null,"abstract":"<div><p>This study examined the impact of Environmental, Social and Governance (ESG) factors on banking-sector profitability in South Asia, focusing on Return on Assets (ROA) and Return on Equity (ROE). Using a balanced annual panel of eight South Asian countries—Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan and Sri Lanka—spanning 1999–2023, we analyzed the roles of ESG factors alongside bank-specific (capital adequacy and non-performing loans) and macroeconomic controls (gross domestic product growth and inflation). Employing a suite of econometric techniques, including Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), Augmented Mean Group (AMG), Common Correlated Effects Mean Group (CCEMG), Dynamic Panel Generalized Method of Moments (GMM) (Arellano–Bond estimator), and the Fixed Effects (FE) regression model, we uncovered nuanced insights into long-run and dynamic relationships. The results revealed that social factors consistently enhance profitability, while environmental factors positively influenced operational performance of ROA but showed limited effect on ROE. Governance factors exhibited heterogeneous effects, with FMOLS indicating short-term compliance costs that may reduce profitability, whereas AMG and CCEMG highlighted cross-country heterogeneity in ESG impacts. Bank capitalization and lagged profitability were robust drivers of performance, whereas non-performing loans and inflation played a minor role. Overall, ESG integration emerges as a viable strategy for financial performance in South Asian banks. These findings suggest that policymakers should strengthen environmental regulations, promote social infrastructure, and improve governance frameworks to facilitate ESG adoption, aligning profitability with sustainable growth.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"10 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147737652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}