Twenty-five years (1998-2023) of earnings conference calls: a bibliometric review focusing on artificial intelligence [poster]

In capital markets, information is the foundation of investment decisions. Transparent corporate disclosures are crucial for guiding investor choices, especially in strategic asset allocation (Bravo & Silva, 2006; Simões et al., 2021). Earnings disclosures and conference calls are pivotal (Healy & Palepu, 2001), allowing senior management to engage stakeholders through real-time, multimedia formats. Public companies regularly conduct quarterly earnings calls, ensuring a consistent flow of financial information. Research has explored how management’s voluntary disclosures during these calls enhance investor understanding and prevent stock underpricing (Graham et al., 2005). Over the last 25 years, this study area has evolved, reflecting technological advancements in corporate communication, such as videocasts. Recent research incorporates artificial intelligence (AI) tools like natural language processing (NLP), sentiment analysis, and audio/image recognition to analyse earnings calls (Druz et al., 2020; Aromi & Clements, 2021; Fiset et al., 2021). This poster aims to map the current research landscape on earnings calls through a bibliometric analysis, identifying trends, gaps, and future research opportunities. By utilising advanced analytical methods, this work contributes to the evolving understanding of corporate communication and its influence on market behaviour.