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Publicação
From Human to Machine
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Orientador(es)
Resumo(s)
Corporate disclosure through earnings calls is a crucial channel for financial communication that enables stakeholders to evaluate corporate strategies. However, current methods for assessing disclosure are outdated or focused too much on sustainability, often overlooking financial transparency. This study introduces a novel, optimised scale designed to bridge this gap by encompassing the responsibilities of a company to various stakeholders. The scale development process, grounded in a conceptual framework and exploratory factor analysis, used data from 74 investors and analysts in Brazil. The findings reveal a refined three-dimensional structure for evaluating earnings calls, incorporating Artificial Intelligence, Disclosure, and ESG. This scale contributes to advancing corporate disclosure research and improving communication practices. Additionally, the study reveals that Brazilian investor attribute equal importance to both analysts and artificial intelligence when making investment decisions through conference calls.
Descrição
Maia, R. D. R., & Bravo, J. M. (2026). From Human to Machine: Evidence that Brazilian Investors Attribute Equal Importance to Analysts and Artificial Intelligence. In 2025 5th International Conference on Electrical, Computer and Energy Technologies (ICECET), Paris, France, 2025 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICECET63943.2025.11471892
Palavras-chave
Artificial intelligence communications data science Artificial Intelligence Computer Science Applications Energy Engineering and Power Technology Renewable Energy, Sustainability and the Environment Electrical and Electronic Engineering SDG 8 - Decent Work and Economic Growth SDG 12 - Responsible Consumption and Production
Contexto Educativo
Citação
Editora
Institute of Electrical and Electronics Engineers (IEEE)