References

• 2020Economic uncertainty before and during the COVID-19 pandemic989 cited
• 2019Forecasting SMEs' credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach387 cited
• 2020Forecasting of Real GDP Growth Using Machine Learning Models: Gradient Boosting and Random Forest Approach259 cited
• 2020Forecasting temporal world recovery in air transport markets in the presence of large economic shocks: The case of COVID-19238 cited
• 2018Words are the New Numbers: A Newsy Coincident Index of the Business Cycle180 cited
• 2020Surveying business uncertainty169 cited
• 2021Rethinking SME default prediction: a systematic literature review and future perspectives149 cited
• 2022Forecasting SMEs’ credit risk in supply chain finance with a sampling strategy based on machine learning techniques126 cited
• 2022Digitalization of Small and Medium-Sized Enterprises and Economic Growth: Evidence for the EU-27 Countries121 cited
• 2023Exploring the role of organizational creativity and open innovation in enhancing SMEs performance97 cited
• 2023Artificial neural networks in supply chain management, a review96 cited
• 2024Machine learning in business and finance: a literature review and research opportunities96 cited
• 2022Sources of SMEs Financing and Their Impact on Economic Growth across the European Union: Insights from a Panel Data Study Spanning Sixteen Years76 cited