The Relationship Between Accounting Information Quality and Corporate Governance: A Research Within the Scope of the Sectors Most Affected by The Pandemic

The presentation of accounting information in a manner that meets the needs of all stakeholders is a critical issue in the decision-making processes of businesses. At this point, accounting information quality emerges as a key indicator. In addition to the existence of various methods for measuring accounting information quality, corporate governance practices are among the primary factors influencing this quality. Although there is an established empirical view that accounting information quality is positively affected by corporate governance practices under normal conditions, it remains an open question whether this effect persists under extraordinary circumstances such as the pandemic period. Accordingly, this study aims to investigate the relationship between accounting information quality and corporate governance within the context of the sectors most affected during the COVID-19 pandemic. For this purpose, data from 2015-2025 were used for 17 companies in the most affected sectors, namely tourism, air transport, and automotive, whose shares are traded on the Borsa İstanbul (BIST). The measurement of accounting information quality was conducted within the value relevance framework using the Ohlson (1995), Ohlson t+1, and Gu & Li (2016) models, and its relationship with corporate governance indicators was examined. In the study, which employed panel regression analysis, a negative relationship was identified—within the scope of the Ohlson models—between accounting information quality and the number of board members, the number of independent board members, the number of audit committee members, and the number of executive board members. The Gu-Li (2016) model of accounting information quality has been found to be positively relationship with both ownership density and number of audit committee members. The findings contribute to the literature by indicating that under extraordinary conditions such as the pandemic period, the direction of cause-and-effect relationships may change, and that more recent models may yield different results compared to earlier approaches.