In the contemporary economic landscape, small and medium-sized enterprises (SMEs) are vital for innovation and growth but face barriers like limited capital access and digital skill gaps. This study employs Monte Carlo simulations to assess governmental incentives' economic impacts on SMEs, focusing on variables like revenue growth, employment, and R&D outputs. By evaluating profitability indices (e.g., ROI, ROS) and using synthetic-realistic data, it provides insights into optimizing assistance programs. The Monte Carlo method, in conjunction with more traditional statistical approaches, offers a sophisticated framework for modeling complex scenarios and variables, ensuring reliable and informative results for effective policymaking.
Alessandro Marrale, Lorenzo Abbate, Livan Fratini, Fabrizio Micari (2024). Assessing the Economic Impacts of Government Incentives on SMEs through Monte Carlo Simulations: A Framework for Sustainable Growth and Technological Adoption. In XXXV RSA AiIG - How AI is changing Economic Systems, Organizations, and Society (pp. 513-530). Associazione italiana Ingegneria Gestionale.
Assessing the Economic Impacts of Government Incentives on SMEs through Monte Carlo Simulations: A Framework for Sustainable Growth and Technological Adoption
Alessandro MarralePrimo
Writing – Original Draft Preparation
;Lorenzo AbbateSecondo
Writing – Review & Editing
;Livan FratiniPenultimo
Membro del Collaboration Group
;Fabrizio MicariUltimo
Supervision
2024-01-01
Abstract
In the contemporary economic landscape, small and medium-sized enterprises (SMEs) are vital for innovation and growth but face barriers like limited capital access and digital skill gaps. This study employs Monte Carlo simulations to assess governmental incentives' economic impacts on SMEs, focusing on variables like revenue growth, employment, and R&D outputs. By evaluating profitability indices (e.g., ROI, ROS) and using synthetic-realistic data, it provides insights into optimizing assistance programs. The Monte Carlo method, in conjunction with more traditional statistical approaches, offers a sophisticated framework for modeling complex scenarios and variables, ensuring reliable and informative results for effective policymaking.| File | Dimensione | Formato | |
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