A new scale for evaluating disclosure in earnings calls on emerging markets

dc.contributor.authorMaia, R. dos R.
dc.contributor.authorBravo, J. M.
dc.date.accessioned2026-02-02T10:58:51Z
dc.date.available2026-02-02T10:58:51Z
dc.date.issued2026
dc.date.updated2026-02-02T10:56:53Z
dc.description.abstractCorporate 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 Yet existing approaches to assessing disclosure quality are often outdated, fragmented, or narrowly focused on sustainability, thereby neglecting the governance dimension of transparency.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.eng
dc.description.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.citationMaia, R. dos R., & Bravo, J. M. (2026). A new scale for evaluating disclosure in earnings calls on emerging markets. Emerging Science Journal, 10(1), 247-275. https://doi.org/10.28991/ESJ-2026-010-01-012
dc.identifier.doi10.28991/ESJ-2026-010-01-012
dc.identifier.issn2610-9182
dc.identifier.urihttp://hdl.handle.net/10071/36186
dc.language.isoeng
dc.number1
dc.pagination247 - 275
dc.peerreviewedyes
dc.publisherItal Publication
dc.relationinfo:eu-repo/grantAgreement/FCT/Avaliação UID 2023%2F2024/UID%2F04152%2F2025/PT
dc.relationinfo:eu-repo/grantAgreement/FCT/Concurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017%2F2018) - Financiamento Base/UIDB%2F00315%2F2020/PT
dc.relationinfo:eu-repo/grantAgreement/FCT/Avaliação UID 2023%2F2024 PRR/UID%2FPRR%2F04152%2F2025/PT
dc.rightsopen access
dc.subjectCorporate disclosureeng
dc.subjectEarnings callseng
dc.subjectScale developmenteng
dc.subjectArtificial intelligenceeng
dc.subjectBrazileng
dc.titleA new scale for evaluating disclosure in earnings calls on emerging marketseng
dc.typearticle
dc.volume10
dspace.entity.typePublicationen
iscte.identifier.cienciahttps://ciencia.iscte-iul.pt/id/ci-pub-116096
iscte.journalEmerging Science Journal

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