Artificial intelligence and sustainable development during urbanization: Perspectives on AI R&D innovation, AI infrastructure, and AI market advantage

Sustainable Development, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 27, 2024

Abstract This study explores the impact of artificial intelligence (AI) on sustainable development across 51 countries during urbanization. Using panel data, examines AI's effects through three dimensions: R&D innovation, infrastructure, and market advantage. The results demonstrate that AI promotes development, with innovation exerting strongest influence, followed by whereas advantage has smallest impact. Additionally, uncovers regional heterogeneity in impacts. In upper middle levels (60%–70% quantiles), promoting effect is strongest. Moreover, urbanization plays a threshold role relationship between development. When below threshold, infrastructure promote inhibit it. Conversely, when exceeds this inhibits becomes insignificant, begin to recommends governments should consider level crafting policies utilizing AI.

Language: Английский

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The effects of industrial robots on firm energy intensity: From the perspective of technological innovation and electrification

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 203, P. 123373 - 123373

Published: April 13, 2024

Language: Английский

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From Brown to green: Exploring asymmetric nexus between green finance and carbon footprint in BRICS+6 alliance

Borsa Istanbul Review, Journal Year: 2024, Volume and Issue: 24(2), P. 363 - 375

Published: Jan. 23, 2024

Green finance is the beacon of hope in a world striving for sustainability, where financial growth and environmental responsibility go hand hand. The BRICS, containing five emerging economies (Brazil, Russia, India, China, South Africa), recently announced Iran, Egypt, Argentina, Ethiopia, Saudi Arabia, UAE as six potential new members. This expansion offers promising prospects advancing sustainability through green finance, which can be an excellent tool. In this respect, research examines how affects carbon footprint BRICS+6 economies. Earlier studies used panel data techniques to probe association between these variables but overlooked that certain countries still needed possess such link separately. Hence, adopts Quantile-on-Quantile approach, provides holistic universal view customized findings each country. outcomes display improves quality by diminishing at distinct quantiles distribution.

Language: Английский

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Does artificial intelligence affect the ecological footprint? –Evidence from 30 provinces in China

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 370, P. 122458 - 122458

Published: Sept. 12, 2024

Language: Английский

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Nexus between green technology innovation and climate policy uncertainty: Unleashing the role of artificial intelligence in an emerging economy

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 209, P. 123820 - 123820

Published: Oct. 22, 2024

Language: Английский

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Industrial Robotics, Resource Efficiency, Energy Transition, and Environmental Quality: Designing a Sustainable Development Goals Framework for G7 Countries in the Presence of Geopolitical Risk

Sustainability, Journal Year: 2025, Volume and Issue: 17(5), P. 1960 - 1960

Published: Feb. 25, 2025

In recent years, the integration of industrial robotics has emerged as a powerful tool in reshaping industries by enhancing production efficiency, reducing waste generation, and optimizing resource utilization. However, robotics, particularly manufacturing production, require significant energy that can potentially impact on environmental quality. Despite growing adoption artificial intelligence (AI)-based there is paucity literature ecological footprint (EF), context advanced economies. this context, study aims to investigate transition, geopolitical risk EF G7 countries from 1993 2021. The employed econometric techniques, including Kernel-based Regularized Least Squares (KRLS) Artificial Neural Network (ANN) machine learning methods. results unveiled significantly curtail degradation impeding EF. Resource efficiency transition posed negative Geopolitical risks economic growth exacerbate Based results, proposes important policy implications for achieving sustainable development.

Language: Английский

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Industrial Robots and Urban Carbon Emissions: Exploring Mechanisms and Implications

Sustainable Development, Journal Year: 2025, Volume and Issue: unknown

Published: March 3, 2025

ABSTRACT Urbanization, a dominant trend in global development, is integral to economic growth and social transformation but remains primary driver of carbon emissions, threatening ecological stability climate goals. This study investigates the potential industrial robots mediate nexus between urban expansion aligning with SDG 9, 11, 13, which focus on industry innovation, sustainable cities, action. Using comprehensive dataset spanning 61 countries, we employ panel data threshold regression models examine how influence dynamics. Our findings highlight that while urbanization tends increase both total per capita can significantly mitigate these effects under specific conditions. Notably, application intensity plays critical role: when robot utilization exceeds levels, exacerbating impact emissions shifts mitigative one, underscoring transformative capacity robotics for low‐carbon development. However, facilitating decarbonization accompanied by several challenges. Addressing challenges essential ensuring are not only tools development also environmentally their lifecycle usage. provides novel insights into role as moderating force decarbonization, emphasizing need policies address drawbacks.

Language: Английский

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Analyzing the Nexus between AI Innovation and Ecological Footprint in Nordic Region: Impact of Banking Development and Stock Market Capitalization using Panel ARDL method

Journal of Environmental Science and Economics, Journal Year: 2024, Volume and Issue: 3(3), P. 41 - 68

Published: Sept. 1, 2024

This study investigates the impact of Artificial Intelligence (AI) innovation on ecological footprint in Nordic region from 1990 to 2020, alongside effects banking development, stock market capitalization, economic growth, and urbanization. Utilizing STIRPAT model, incorporates cross-sectional dependence slope homogeneity tests, revealing issues heterogeneity dependence. The analysis employs both first second-generation panel unit root confirming that variables are free problems. Panel cointegration tests demonstrate cointegrated long run. To explore short- long-term relationships, utilizes Autoregressive Distributed Lag (ARDL) model. ARDL results indicate urbanization positively correlate with short Conversely, AI development negatively footprint. validate estimations, robustness checks performed using Fully Modified OLS, Dynamic Fixed Effects all which support initial findings. Furthermore, D-H causality test identify causal relationships. show a unidirectional relationship between innovation, urbanization, In contrast, bidirectional exists growth footprint, as well

Language: Английский

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Advancements in Agricultural Ground Robots for Specialty Crops: An Overview of Innovations, Challenges, and Prospects

Plants, Journal Year: 2024, Volume and Issue: 13(23), P. 3372 - 3372

Published: Nov. 30, 2024

Robotic technologies are affording opportunities to revolutionize the production of specialty crops (fruits, vegetables, tree nuts, and horticulture). They offer potential automate tasks save inputs such as labor, fertilizer, pesticides. Specialty well known for their high economic value nutritional benefits, making particularly impactful. While previous review papers have discussed evolution agricultural robots in a general context, this uniquely focuses on application crops, rapidly expanding area. Therefore, we aimed develop state-of-the-art scientifically contribute understanding following: (i) primary areas robots' crops; (ii) specific benefits they offer; (iii) current limitations; (iv) future investigation. We formulated comprehensive search strategy, leveraging Scopus

Language: Английский

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Harnessing artificial intelligence‐driven industrial robotics for sustainability: Insights from leading green economies

Natural Resources Forum, Journal Year: 2024, Volume and Issue: unknown

Published: May 17, 2024

Abstract In 2023, global temperatures witnessed an alarming escalation, reaching unprecedented 1.46°C above preindustrial levels, marking it as the hottest year on record. Simultaneously, atmospheric carbon dioxide surpassed 420 ppm, exceeding a stability maintained for over 6000 years by more than double. This troubling surge in CO 2 intensifies warming, leading to increased frequency of extreme weather events and contributing 24% deaths attributed environmental concerns. These challenges demand urgent attention implementation innovative policies. Responding this imperative, study examines impact artificial intelligence‐based industrial robotics (AIIR) other control variables such green energy, finance, energy investment emissions economies supporting initiatives, including Canada, Denmark, China, Japan, New Zealand, Norway, Sweden, Switzerland. Using monthly data from 2008 2021 novel nonlinear autoregressive distributed lag approach, results indicate that AIIR significantly reduces sample economies. Additionally, also decrease emissions. The study's outcomes bear policy implications decision‐makers sampled economies, offering tangible insights effective management.

Language: Английский

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