Purpose

This study aims to investigate whether and how the disclosure of key audit matters (KAMs) or critical audit matters (CAMs) affects stock market reaction by examining the association between goodwill-related KAMs and stock price crash risk (SPCR) in the Chinese context.

Design/methodology/approach

The authors use ordinary least squares (OLS) regression to estimate the impact of goodwill-related to KAMs disclosure on SPCR based on a sample of 26,593 firm-year observations from Chinese A-share companies listed on the Shanghai and Shenzhen Stock Exchanges from 2016 to 2023. To check the consistency of the findings, the authors use propensity score matching (PSM), alternative measure of goodwill-related KAMs, control for the extreme impact of the COVID-19 pandemic and the two-way cluster-robust standard errors.

Findings

The findings of this study indicate a negative association between goodwill-related to KAMs disclosure and SPCR, suggesting that auditors’ increased disclosure of goodwill as a KAM reduces corporate opacity and constrains managerial discretion in avoiding the recognition of goodwill impairment. Such proactive disclosure enhances audit quality and the transparency of the auditor’s work, thereby improving investors’ perceptions of risk and ultimately contributing to a reduction in SPCR. Finally, the findings remain consistent across a variety of robustness checks.

Practical implications

This paper provides valuable insights for regulators, standard setters, investors and auditors. For example, this research provides a deeper understanding of the economic impacts of KAMs, offering valuable insights for regulators and standard setters.

Originality/value

To the best of the authors’ knowledge, this unique paper has built upon existing research on the specific account-related KAMs disclosure by offering new insights into the impact of goodwill-related KAM disclosures from the perspective of SPCR. Moreover, the results provide new evidence contributing to the recent inconclusive literature that investigates stock market reactions to KAMs. Finally, the findings confirm standard setters’ expectations regarding the importance of KAMs reporting in enhancing the informative value of audit reports to investors.

Purpose

The main purposes of this article are twofold: (1) to investigate the unexplored connections among destination gender personality, destination stereotypes, brand attachment and destination brand love and (2) to examine the moderating role of destination involvement in the association between destination stereotypes and destination brand attachment (DBA).

Design/methodology/approach

The conceptual model is evaluated using qualitative methods (i.e. three focus groups, six academic experts and a pilot study). In addition, using an empirical study with 610 international travelers who visited Egypt selected by systematic random sampling, 8 hypotheses were analyzed and tested using structural equation modeling (SEM) by AMOS 23, confirmatory factor analyses and exploratory factor analyses.

Findings

The study’s results suggest that destination gender plays a vital role in enhancing stereotypes, stereotypes positively affect attachment and DBA positively affects destination brand love. Finally, the results show that destination involvement moderates the dual influence of the warmth and competence of stereotypes on destination attachment.

Practical implications

The research supports the contention that social perception mechanisms are crucial in destination brand perception. It offers new understandings of the association between customers' destination brand perceptions and their responses to destinations.

Originality/value

This paper contributes to the travel literature by analyzing a novel model of destination gender personality, stereotypes, DBA and destination brand love using both social role (SR) theory and a stereotype content model (SCM). Besides attempting this task, it explores the moderating role of destination involvement in the association between stereotypes and destination attachment using the elaboration likelihood model.