Forging a Sustainable Future in G20 Economies: The Transformative Role of Technological Innovation, Green Finance and Higher Education Amid Globalization and Entrepreneurial Growth

Sustainability, Journal Year: 2025, Volume and Issue: 17(8), P. 3321 - 3321

Published: April 8, 2025

Environmental degradation poses a significant global challenge which necessitates innovative strategies to achieve sustainability. This study investigates the impact of technological innovation (TCN), higher education (EDU), green finance (GRF), globalization (GLI), and entrepreneurship (ENT) on environmental quality (EQ) in G20 countries. The uses panel data from 2000 2020 investigate relationships between variables. Among various diagnostic tests conducted, Variance Inflation Factor (VIF) confirms that multicollinearity is not present. Furthermore, cross-sectional dependence (CSD) test identifies interdependence among Moreover, slope homogeneity (SL) indicates heterogeneity data. For stationarity check, Cross-Sectional Augmented Im–Pesaran–Shin (CIPS) mixed results. Finally, Cross-Sectionally Autoregressive Distributed Lag (CS-ARDL) Generalized Method Moments (GMM) for long- short-run analysis outcomes CS-ARDL indicate GLI has negative EQ, hence causing deterioration economies. On other hand, TCN, EDU, GRF, ENT show positive impacts therefore enhancing outcomes. Additionally, Dumitrescu–Hurlin causality reveals bidirectional causality, highlights interconnected relationship TCN with EQ. However, demonstrate unidirectional takeaway focuses importance policies promoting innovation, resource efficiency, sustainable practices advance within

Language: Английский

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Designing a novel technique for evaluation of tourism informatization in scenic spots from a big data perspective

PeerJ Computer Science, Journal Year: 2025, Volume and Issue: 11, P. e2807 - e2807

Published: April 18, 2025

In recent years, tourism has become a significant driver of many countries’ economies. To maximize revenue from tourism, it is crucial to prioritize the effective management scenic spots and tourist attractions, also raise awareness about these places. Social media platforms have played pivotal role in promoting as users frequently share videos reviews related tourism. Analyzing managing essential for understanding tourists’ opinions specific destinations. this study, we evaluated spot by analyzing sentiments. Data was collected popular social sites such TripAdvisor Twitter using web scraping API. The raw data preprocessed remove irrelevant information redundancies properly annotated further processing. We applied two approaches analyze sentiments tourists. First, vectorized text representing sentiment term frequency-inverse document frequency (TF-IDF) utilized big analytics extract meaningful insights. Secondly, employed pre-trained large language model, bidirectional encoder representations transformers (BERT), with linear classifier classify results were compared those BERT previously proposed methods. outperformed other machine learning models, achieving an average accuracy 83.5% on test set. These insights are valuable evaluating informatization spots, destination management, hospitality, overall attractions.

Language: Английский

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Tourism economic resilience and its influence factors in China’s three major urban agglomerations based on threshold effect

Humanities and Social Sciences Communications, Journal Year: 2025, Volume and Issue: 12(1)

Published: May 5, 2025

Language: Английский

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The impact of digital economy on carbon emissions: Insights from the G-20 energy transition and environmental governance

Energy Strategy Reviews, Journal Year: 2024, Volume and Issue: 57, P. 101612 - 101612

Published: Dec. 27, 2024

Language: Английский

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