Building resilient infrastructure, supporting sustainable industrialization, and fostering innovation (SDG 9) in selected European countries: spatial and taxonomic analysis

Sustainable Development Goals (SDGs) consist of 17 goals and 169 targets to be met by the end of 2030. Since the European Union (EU) members are also included in the 2030 Agenda for Sustainable Development set by the United Nations (UN) countries, it is vital to analyze the Sustainable Development performance of the EU economies. This paper focuses on SDG 9, which aims to build resilient infrastructure, support inclusive and sustainable industrialization, and foster innovation. This research analyzes the industry, innovation and infrastructure indicators in selected European economies. The main aim of this paper is to assess the performance of the European economies in SDG 9 and to verify whether there are any spatial dependencies among countries. Applying the taxonomic measure of development and its spatial version to the group of 29 countries from Europe shows that Sweden and Denmark were the leading countries in SDG 9 in 2013 and 2019. Eastern and South-Western Europe was characterized by the lowest level of SDG 9 in 2013 and 2019. The level of SDG 9 increased over the period 2013–2019

Delivering together for inclusive development : digital access to Information and knowledge for persons with disabilities

This report focuses on digital inclusion as it relates to four of the 17 Goals for the 2030 Sustainable Development Agenda: SDG 9 - Innovation, Industry, and Infrastructure, SDG 16 - Peace, Justice, and Strong Institutions, SDG 17 - Partnerships for the Goals, SDG 4 - Quality Education. For each of the goals, a number of major challenges and key recommendations are defined. Finally, general recommendations are given for improving global digital inclusion overall

A multi‐methods approach for assessing how conserving biodiversity interacts with other sustainable development goals in Nepal

Achieving the sustainable development goals (SDGs) requires a context-specific understanding of how actions to achieve one goal interact with others. We analyzed statistical data, and conducted online surveys and interviews with conservation professionals to understand how terrestrial conservation goals (SDG 15: Life on land) influence and are influenced by other goals in Nepal. Our findings suggest that SDG 15 synergized with economic growth (SDG 8), gender equality (SDG 5), water access (SDG 6), sustainable production and consumption (SDG 12), and climate action (SDG 13), but traded off with food security (SDG 2), energy access (SDG 7), poverty alleviation (SDG 1), and infrastructure development (SDG 9). Increased multi-sectoral collaboration between conservation and development stakeholders is urgently needed to address the negative impacts of other goals on SDG 15. Additionally, conservation measures in Nepal can benefit from being more people-focused, participatory, and contextualized to mitigate negative impacts on socioeconomic goals

SDG 9 - Industry, Innovation and Infrastructure: Impact on the digital sphere discussion

[EN] The research carried out analyzes more than 5 million tweets on Sustainable Development Goals (SDGs), in general, and more than 17,000 tweets on SDG 9 (Industry, Innovation and Infrastructure) , in particular, in the three-year period 2020-2022. After using Social Network Analysis and Semantic Analysis techniques, the results obtained show that SDG 9 has generated less interest in the social network Twitter than the other SDGs in the last three years, and the number of tweets about it has been decreasing. Moreover, the private sector does not play a key role in any of the main communities generated. Nevertheless, it is considered necessary to improve the communication strategy of SDG 9 and make it mainstream.Zarrabeitia-Bilbao, E.; Rio-Belver, R.; Jaca-Madariaga, M.; Álvarez-Meaza, I. (2023). SDG 9 - Industry, Innovation and Infrastructure: Impact on the digital sphere discussion. Editorial Universitat Politècnica de València. 35-36. http://hdl.handle.net/10251/201704353

Phase transitions in the sdgsdg interacting boson model

A geometric analysis of the $sdg$ interacting boson model is performed. A coherent-state is used in terms of three types of deformation: axial quadrupole ($\beta_2$), axial hexadecapole ($\beta_4$) and triaxial ($\gamma_2$). The phase-transitional structure is established for a schematic $sdg$ hamiltonian which is intermediate between four dynamical symmetries of U(15), namely the spherical ${\rm U}(5)\otimes{\rm U}(9)$, the (prolate and oblate) deformed ${\rm SU}_\pm(3)$ and the $\gamma_2$-soft SO(15) limits. For realistic choices of the hamiltonian parameters the resulting phase diagram has properties close to what is obtained in the $sd$ version of the model and, in particular, no transition towards a stable triaxial shape is found.Comment: 19 pages, 5 figures, submitted to J. Phys.

PROGRAM KAMPUNG PANGAN BERSERI DALAM MEWUJUDKAN SUSTAINABLE DEVELOPMENT GOALS (SDGs) BERBASIS MASYARAKAT DI KOTA BALIKPAPAN

Kota Balikpapan, dengan pertumbuhan penduduk yang signifikan, menghadapi berbagai tantangan keberlanjutan termasuk munculnya kawasan permukiman kumuh. Program Kampung Pangan Berseri, sebuah inisiatif CSR dari Pertamina IT Balikpapan, bertujuan mengatasi masalah ini melalui pendekatan berbasis masyarakat. Penelitian ini menggunakan metode kualitatif deskriptif untuk menganalisis pelaksanaan program di Kelurahan Muara Rapak dan Mekarsari, serta hubungannya dengan beberapa poin Sustainable Development Goals (SDGs). Hasil menunjukkan bahwa program ini berhasil meningkatkan ketahanan pangan, kesehatan, pendidikan, pengelolaan sampah, dan pemberdayaan ekonomi lokal. Program ini juga berdampak positif terhadap SDG 1 (Tanpa Kemiskinan), SDG 2 (Tanpa Kelaparan), SDG 3 (Kesehatan yang Baik dan Kesejahteraan), SDG 4 (Pendidikan Berkualitas), SDG 8 (Pekerjaan Layak dan Pertumbuhan Ekonomi), SDG 9 (Industri, Inovasi, dan Infrastruktur), SDG 11 (Kota dan Komunitas yang Berkelanjutan), dan SDG 12 (Konsumsi dan Produksi yang Bertanggung Jawab). Program ini menunjukkan pentingnya kolaborasi multi-sektor dalam mencapai tujuan pembangunan berkelanjutan di Balikpapan

The impact of social protection and poverty elimination on global tuberculosis incidence: a statistical modelling analysis of Sustainable Development Goal 1.

BACKGROUND: The End TB Strategy and the Sustainable Development Goals (SDGs) are intimately linked by their common targets and approaches. SDG 1 aims to end extreme poverty and expand social protection coverage by 2030. Achievement of SDG 1 is likely to affect the tuberculosis epidemic through a range of pathways. We estimate the reduction in global tuberculosis incidence that could be obtained by reaching SDG 1. METHODS: We developed a conceptual framework linking key indicators of SDG 1 progress to tuberculosis incidence via well described risk factor pathways and populated it with data from the SDG data repository and the WHO tuberculosis database for 192 countries. Correlations and mediation analyses informed the strength of the association between the SDG 1 subtargets and tuberculosis incidence, resulting in a simplified framework for modelling. The simplified framework linked key indicators for SDG 1 directly to tuberculosis incidence. We applied an exponential decay model based on linear associations between SDG 1 indicators and tuberculosis incidence to estimate tuberculosis incidence in 2035. FINDINGS: Ending extreme poverty resulted in a reduction in global incidence of tuberculosis of 33·4% (95% credible interval 15·5-44·5) by 2035 and expanding social protection coverage resulted in a reduction in incidence of 76·1% (45·2-89·9) by 2035; both pathways together resulted in a reduction in incidence of 84·3% (54·7-94·9). INTERPRETATION: Full achievement of SDG 1 could have a substantial effect on the global burden of tuberculosis. Cross-sectoral approaches that promote poverty reduction and social protection expansion will be crucial complements to health interventions, accelerating progress towards the End TB targets. FUNDING: World Health Organization

Osiąganie celów zrównoważonego rozwoju w warunkach racjonalnych oczekiwań poprzez osiągnięcie równowagi interesów edukacji i produkcji w zakresie przemysłu lekkiego w trudnych czasach pandemii i wojny

The article presents a comprehensive analysis of the global consequences caused by the development of light industry for achieving the Sustainable Development Goals. The ecological context allows us to focus on how light industry affects climate change, resource depletion, waste generation and water pollution. It is emphasized that the impact of light industry can create significant challenges for sustainable development related to SDG 13 (Climate action), SDG 6 (Clean water and sanitation), SDG 12 (Responsible consumption and production), SDG 14 (Life below water) and SDG 15 (Life on land). The article also examines the socio-economic context, discusses how light industry leads to persistent inequality, loss of traditional skills and cultural heritage, as well as trade imbalance. In terms of social responsibility, light industries have a history of violations of working conditions and labour rights. The socio-economic impacts considered may hinder the achievement of SDGs such as SDG 5 (Gender equality), SDG 8 (Decent work and economic growth), SDG 9 (Industry, innovation and infrastructure), SDG 10 (Reduced inequalities), SDG 11 (Sustainable cities and communities) and SDG 12 (Responsible consumption and production), SDG 17 (Partnerships for the goals). The theory of rational expectations is used to predict the development of light industry and its subsequent impact on sustainable development in the post-pandemic period. The prospects of applying the theory in the training of specialists for light industry are substantiated. The impact of the consequences of the pandemic and the war in Ukraine on the decision-making processes in light industry and their alignment with the sustainable development goals, taking into account civilizational challenges, is considered. In the process of research, an econometric model has been developed to determine the desired balance of interests between education and production based on rational expectations in a sustainable development environment.  It advocates harmony between these two aspects, based on rational expectations, to promote sustainable development. This balance is crucial for achieving SDG 4 (Quality Education), SDG 9 (Industry, Innovation and Infrastructure) and SDG 17 (Partnerships for the goals). The properties of the model provide a wide range of applications, allowing to estimate the impact of a variety of factors on sustainable development in light industry. The developed model can be applied to estimate the values of the dependent variable for individual countries or regions, as well as to analyse the influence of independent and control variables on changes in its value. As a planning tool, the model can be adapted to develop context-sensitive sustainability strategies in light industries. The article offers ideas and practical solutions for using the potential of light industry in the pursuit of sustainable development in conditions of rational expectations.W artykule przedstawiono kompleksową analizę globalnych konsekwencji rozwoju przemysłu lekkiego w kontekście osiągania Celów zrównoważonego rozwoju środowiskowego. Kontekst ekologiczny pozwala nam skupić się na wpływie przemysłu lekkiego na zmiany klimatyczne, wyczerpywanie się zasobów, wytwarzanie odpadów i zanieczyszczenie wody. Podkreśla się, że wpływ przemysłu lekkiego może stworzyć istotne wyzwania dla zrównoważonego rozwoju związane z SDG 13 (Działania klimatyczne), SDG 6 (Czysta woda i kanalizacja), SDG 12 (Odpowiedzialna konsumpcja i produkcja), SDG 14 (Życie pod wodą). i SDG 15 (Życie na lądzie). W artykule dokonano także analizy kontekstu społeczno-gospodarczego, omówiono, w jaki sposób przemysł lekki prowadzi do utrzymujących się nierówności, utraty tradycyjnych umiejętności i dziedzictwa kulturowego, a także nierównowagi handlowej. Jeśli chodzi o odpowiedzialność społeczną w kontekście przemysłu lekkiego, odnosi się ona do naruszeń warunków pracy i praw pracowniczych. Uwzględnione skutki społeczno-gospodarcze mogą utrudnić osiągnięcie celów zrównoważonego rozwoju, takich jak cel zrównoważonego rozwoju 5 (równość płci), cel zrównoważonego rozwoju 8 (godziwa praca i wzrost gospodarczy), cel zrównoważonego rozwoju 9 (przemysł, innowacje i infrastruktura), cel zrównoważonego rozwoju 10 (zmniejszenie nierówności), cel zrównoważonego rozwoju 11 (Zrównoważone miasta i społeczności) oraz SDG 12 (Odpowiedzialna konsumpcja i produkcja), SDG 17 (Partnerstwo dla osiągnięcia celów). Teoria racjonalnych oczekiwań służy do przewidywania rozwoju przemysłu lekkiego i jego późniejszego wpływu na zrównoważony rozwój w okresie popandemicznym. Udowodniono perspektywy zastosowania teorii w kształceniu specjalistów przemysłu lekkiego. Rozważany jest wpływ skutków pandemii i wojny na Ukrainie na procesy decyzyjne w przemyśle lekkim i ich dostosowanie do celów zrównoważonego rozwoju, z uwzględnieniem wyzwań cywilizacyjnych. Opracowano model ekonometryczny umożliwiający określenie pożądanej równowagi interesów pomiędzy edukacją a produkcją w oparciu o racjonalne oczekiwania w środowisku zrównoważonego rozwoju. Opowiada się za harmonią między tymi dwoma aspektami, opartą na racjonalnych oczekiwaniach, w celu promowania zrównoważonego rozwoju. Ta równowaga jest kluczowa dla osiągnięcia SDG 4 (Jakość edukacji), SDG 9 (Przemysł, innowacje i infrastruktura) oraz SDG 17 (Partnerstwo dla osiągnięcia celów). Właściwości modelu zapewniają szerokie spektrum zastosowań, pozwalając na ocenę wpływu różnorodnych czynników na zrównoważony rozwój przemysłu lekkiego. Opracowany model można zastosować do szacowania wartości zmiennej zależnej dla poszczególnych krajów lub regionów, a także do analizy wpływu zmiennych niezależnych i kontrolnych na zmiany jej wartości. Jako narzędzie planowania model można dostosować do opracowania kontekstowych strategii zrównoważonego rozwoju w branżach lekkich. W artykule przedstawiono pomysły i praktyczne rozwiązania wykorzystania potencjału przemysłu lekkiego w dążeniu do zrównoważonego rozwoju w warunkach racjonalnych oczekiwań

Modeling PLN Inc. Customer Receivables Based on Geographically Weighted Regression Approach

PLN Inc. implements a postpaid service that has resulted in many customer receivables issues. Customer receivables disrupt PLN Inc.'s cash flow, requiring the government to inject funds from the state budget. If the state budget experiences a deficit, it can increase the national debt. National debt impacts the achievement of SDG goals, namely sustainable economic growth (SDG 8), reducing inequalities (SDG 10), and financing infrastructure that supports development (SDG 9). The largest receivables occur on the island of Java, where many companies have high electricity consumption, while outside Java, electricity consumption is lower due to the scarcity of companies. This indicates a spatial influence on the size of PLN Inc.'s customer receivables, so this research was conducted using the Geographically Weighted Regression (GWR) method. The study found that the best weighting was fixed Gaussian with an R² value of 96.94%, which is better than the global regression value of 44.34%.PLN Inc. implements a postpaid service that has resulted in many customer receivables issues. Customer receivables disrupt PLN Inc.'s cash flow, requiring the government to inject funds from the state budget. If the state budget experiences a deficit, it can increase the national debt. National debt impacts the achievement of SDG goals, namely sustainable economic growth (SDG 8), reducing inequalities (SDG 10), and financing infrastructure that supports development (SDG 9). The largest receivables occur on the island of Java, where many companies have high electricity consumption, while outside Java, electricity consumption is lower due to the scarcity of companies. This indicates a spatial influence on the size of PLN Inc.'s customer receivables, so this research was conducted using the Geographically Weighted Regression (GWR) method. The study found that the best weighting was fixed Gaussian with an R² value of 96.94%, which is better than the global regression value of 44.34%