Corporate disclosure via earnings calls is a vital mechanism for financial transparency and stakeholder communication, enabling investors to evaluate firms’ performance, governance practices, and strategic direction. Yet existing approaches to assessing disclosure quality are often outdated, fragmented, or narrowly focused on sustainability, thereby neglecting the governance dimension of transparency. This study develops and validates a comprehensive, reliable, and optimized scale to measure the quality of corporate disclosure in earnings calls, integrating both sustainability and governance perspectives. Using a systematic scale-development process grounded in a robust conceptual framework, we collected data from 74 investors and analysts across multiple stages, focusing on Brazilian listed companies. Exploratory factor analysis yielded a refined three-dimensional structure comprising Analyst Disclosure, ESG (environmental, social and governance), and Artificial Intelligence. Findings indicate that investors increasingly regard artificial intelligence as central to evaluating disclosure credibility and informing investment decisions. This research advances disclosure measurement by offering a novel, empirically validated instrument that captures evolving communication dynamics. The proposed scale provides theoretical and practical contributions by strengthening the links between governance, sustainability, and financial transparency, and it establishes a foundation for future cross-market validation in emerging economies.

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Corporate disclosure,Earnings calls,Scale development,Artificial intelligence,Brazil