{"title":"Optimizing public investments: A Sustainable Economic, Environmental, and Social Investment Multi-criteria Decision Model (SEESIM)","authors":"","doi":"10.1016/j.rspp.2024.100140","DOIUrl":"10.1016/j.rspp.2024.100140","url":null,"abstract":"<div><div>One of the most important aspects for the economic and social growth of a country is high efficiency of public investments. This imperative has never been more critical, especially in the context of Europe and Italy, where the integration of environmental, economic, and social goals is essential to address the multifaceted challenges of the 21st century. This research introduces the Sustainable Economic, Environmental, and Social Investment Model (SEESIM), a novel multi-criteria decision-making framework designed to ensure the sustainability of projects as their validity over time, especially from a National Recovery and Resilience Plan perspective. Utilizing the Analytic Hierarchy Process (AHP), SEESIM integrates environmental, economic, and social criteria as useful tool to evaluate a project in the post-funding phase, ensuring a balanced approach to efficiency and sustainability. The model is adaptable to various regional contexts, providing a transparent and replicable methodology for assessing the impacts and costs of public investments. An experimental scenario demonstrates SEESIM’s utility in guiding investment decisions, highlighting its potential to significantly enhance the effectiveness of public resources in achieving long-term sustainability goals. SEESIM represents a pivotal advancement in sustainable development strategies, offering a comprehensive tool for integrating multi-dimensional sustainability criteria into public investment decisions.</div></div>","PeriodicalId":45520,"journal":{"name":"Regional Science Policy and Practice","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142359327","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":"What drives tax morale in selected North African economies? Empirical evidence from Algeria, Morocco and Tunisia using simulated ARDL and GMM quantile regressions","authors":"","doi":"10.1016/j.rspp.2024.100141","DOIUrl":"10.1016/j.rspp.2024.100141","url":null,"abstract":"<div><div>This study attempts to analyze the driving factors of tax morale in selected North African countries over the period 1984–2022. For this purpose, we use simulated ARDL and Frequency Domain Causality for time-series analysis and GMM-QR for dynamic panel analysis. According to long-run empirical estimations, educational growth positively contributes to enhancing tax morals in Algeria, Morocco, and Tunisia, whereas GDP and corruption contribute negatively. However, this relationship fluctuates in the short term. In addition, all independent variables positively and significantly maintain causality for tax morals. Furthermore, the dynamic estimation confirms the above relationship in the long-run in the panel. Although education and GDP maintained the same relationship in the GMM-QR estimation, corruption levels remained insignificant during the quantile period. Considering the pioneering study of the area, this study suggests some key factors that should be given more attention for enhancing tax morals in the region and ultimately improving the tax-to-GDP ratio.</div></div>","PeriodicalId":45520,"journal":{"name":"Regional Science Policy and Practice","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142358789","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":"Mapping obesity in women and chronic malnutrition in children across the municipalities of Bolivia: Spatial clusters and regionalization","authors":"","doi":"10.1016/j.rspp.2024.100129","DOIUrl":"10.1016/j.rspp.2024.100129","url":null,"abstract":"<div><div>This paper investigates the spatial distribution of two nutritional variables: obesity prevalence in women and chronic malnutrition prevalence in children across 339 municipalities in Bolivia in 2016. Using data from the Municipal Atlas of the Sustainable Development Goals Bolivia 2020, the study employs spatial analysis methods such as geographic distribution, spatial dependence, and regionalization to comprehend the role of space in nutritional challenges. The findings reveal strong spatial dependence for both obesity prevalence in women and chronic malnutrition prevalence in children in Bolivia. Specifically, high rates of obesity in women are observed in eastern municipalities and their neighboring areas, while a concentrated cluster of chronic malnutrition in children is identified in the western regions. Considering these differences, this investigation argues that, using cluster analysis, Bolivia can be regionalized into eighteen geographical zones based on the distribution of these two nutritional variables. Limitations and future research avenues are discussed.</div></div>","PeriodicalId":45520,"journal":{"name":"Regional Science Policy and Practice","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1757780224003408/pdfft?md5=c870d68762f2b29f1b5ecade250bdda6&pid=1-s2.0-S1757780224003408-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142311346","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":"Are there Marshallian industrial districts in Portugal? revisiting the canello and pavone algorithm","authors":"","doi":"10.1016/j.rspp.2024.100132","DOIUrl":"10.1016/j.rspp.2024.100132","url":null,"abstract":"<div><p>The present study maps and classifies industrial districts in Portugal, identifying the features of specialization and the current capacity of industrialization. It employs an adaptation of the algorithm developed by Canello and Pavone (2016) in 308 Portuguese municipalities based on six phases. In terms of methodological innovation, a new concentration ratio was introduced, making it possible to identify homogeneity in the industrial structure and to consider different sizes of companies, regarding the classification of Industrial Districts. It provides guidelines for policymakers in order to promote cross-fertilized industrial districts, considering the specificities of low-density industrial regions.</p></div>","PeriodicalId":45520,"journal":{"name":"Regional Science Policy and Practice","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1757780224003433/pdfft?md5=aaea98651b83880b2036aae07fe36a03&pid=1-s2.0-S1757780224003433-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142243533","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":"Estimating urban sprawl standards by means of the Urban Metric System","authors":"","doi":"10.1016/j.rspp.2024.100131","DOIUrl":"10.1016/j.rspp.2024.100131","url":null,"abstract":"<div><p>This article emphasizes the radically original character of the Urban Metric System: use of vector fields, a single parameter, several types of urban areas, a single input (the distribution of populations and jobs), no political boundaries taken into account and no density as input, abandonment of urban-rural distinctions and of the \"commuting\" criterion to distinguish the central city and its metropolitan area, and estimation of the centers, boundaries and densities of urban areas as outputs. The genesis of this approach is presented here for the first time. It leads not only to the calculation of a synthetic urban sprawl criterion (average distance to the center), but also to the estimation of four functions for calculating urban sprawl standards for central Canada, which was the authors’ ultimate research objective in terms of policy and planning.</p></div>","PeriodicalId":45520,"journal":{"name":"Regional Science Policy and Practice","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1757780224003421/pdfft?md5=2afb4397eca851fb8d81746ea5d888dd&pid=1-s2.0-S1757780224003421-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142233840","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":"Modeling and spatialization of biomass and carbon stock using unmanned Aerial Vehicle Lidar (Lidar-UAV) metrics and forest inventory in cork oak forest of Maamora","authors":"","doi":"10.1016/j.rspp.2024.100127","DOIUrl":"10.1016/j.rspp.2024.100127","url":null,"abstract":"<div><p>Recently, the concerns about climate change have heightened the need for effective methods for estimating and mapping Biomass and Carbon stock at local, national, continental, and global scales. Reliable Biomass and Carbon stock quantification and spatialization is a challenge, especially in degraded Mediterranean Cork oak forest. To estimate and map Biomass (B<sub>tree−Total</sub>) and Carbon stock (C<sub>st−total</sub>), we explored an improved approach using extracted metrics collected by Lidar-UAV (unmanned aerial vehicles Lidar), combined with forest inventory data. We approach three types of models for data analysis: Simple linear regression, multiple linear regressions, and stepwise multiple linear regression. The best Biomass and Carbon stock model fit is the Stepwise multiple linear regressions, involving the following metrics: maximum elevation, canopy cover and point cloud density and intensity. Our finding provides a quantification and spatialization Biomass and Carbon stock model based on Lidar-UAV metrics in Cork Oak Mediterranen forest and the results confirm the degraded state of Maamora Forest with a Biomass and Carbon stock relatively medium to low.</p></div>","PeriodicalId":45520,"journal":{"name":"Regional Science Policy and Practice","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S175778022400338X/pdfft?md5=d6c380b4a7c65e5fc24cbf226c99997a&pid=1-s2.0-S175778022400338X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142098562","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":"Old wisdom and the New Economic Geography: Managing uncertainty in 21st century regional and urban development","authors":"","doi":"10.1016/j.rspp.2024.100124","DOIUrl":"10.1016/j.rspp.2024.100124","url":null,"abstract":"<div><p>The New Economic Geography (NEG) has over the past decades become a leading paradigm in regional science and geography. This paper seeks to provide a retrospective and prospective look into its achievements and current challenges. Clearly, regions are not oases of tranquility. Uncertainty and shocks in regional and urban development are omnipresent and call for adaptive and resilient strategies on spatial dynamics. The spatial arena is governed by many factors; this is mapped out in the present paper by means of a ‘<em>Pentagon</em>’ model of critical territorial capital inputs which form interdependent anchor points for policy and action based on the principle of <em>confluence</em>. The space-economy is multi-faceted and three prominent challenges in particular, are highlighted in this study: (i) the influence of digital technology on the standard NEG framework; (ii) the livability and proximity conditions in urban agglomerations, critically assessed through the lenses of the currently popular 15-minute city framework; (iii) the implications of social wellbeing and happiness motives for regional and urban planning in an NEG context. The conclusion of the study is that the NEG legacy and principles continue to be prominent signposts for regional and urban analysis and policy, conditional upon a flexible adaptivity of this legacy to new framework conditions in the ever-changing space-economy.</p></div>","PeriodicalId":45520,"journal":{"name":"Regional Science Policy and Practice","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1757780224003354/pdfft?md5=506ee2739636055aecfa5417fee755b5&pid=1-s2.0-S1757780224003354-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142088852","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":"Economic growth and regional disparities: A long-term perspective for the state of Sergipe, Brazil","authors":"","doi":"10.1016/j.rspp.2024.100125","DOIUrl":"10.1016/j.rspp.2024.100125","url":null,"abstract":"<div><p>This paper aims to build and evaluate long-term scenarios within the economy of the state of Sergipe so as to identify sectors with a greater capacity to leverage the state's economic growth and mitigate regional disparities. We use a dynamic and inter-regional CGE model, calibrated for the year 2015 and 41 sectors. Our simulations capture he effects of sectorial shocks in the state and explore the direct and indirect effects of such shocks throughout the economy. The main results show that sectors such as Agriculture, Transport, Financial intermediation, and Public Utility Industrial Services all have an above average impact on the state’s GDP and contribute to a reduction in regional disparities.</p></div>","PeriodicalId":45520,"journal":{"name":"Regional Science Policy and Practice","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1757780224003366/pdfft?md5=d7b579065b4ff97ede388b4e1fd471e2&pid=1-s2.0-S1757780224003366-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142040367","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":"Exploring managerial intentions to implement ESG Activities: The role of facilitating conditions in the UTAUT2 framework","authors":"","doi":"10.1016/j.rspp.2024.100126","DOIUrl":"10.1016/j.rspp.2024.100126","url":null,"abstract":"<div><p>This research investigates the factors influencing managers' willingness to adopt Environmental, Social, and Corporate Governance (ESG) practices in small and medium-sized enterprises (SMEs) in Bosnia and Herzegovina. As these practices are becoming increasingly important, it is crucial to understand what factors can increase managers' acceptance of them for both theory and practice. Our analysis was conducted on a sample of 306 managers from Bosnia and Herzegovina. Anchored in the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), we tested three models to identify predictors of intention to adopt ESG practices and to explore the moderating role of facilitating conditions (FC) on the relationship between performance expectancy and intention to adopt ESG practices. Our findings indicate that there are consistent factors that predict the managers’ intention of adopt ESG practices, including Performance Expectancy (PE), Social Influence (SI), and Habitual Tendency (HT). We found that the FC negatively moderate the link between PE and intention to adopt social and governance practices within ESG framework. We argue that the nature of each domain within ESG, ceiling effect, and resource constraints and trade-offs might be possible explanations for these results.</p></div>","PeriodicalId":45520,"journal":{"name":"Regional Science Policy and Practice","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1757780224003378/pdfft?md5=2ba04c17f23ca8bac20b1defbe984a9e&pid=1-s2.0-S1757780224003378-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141985779","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}