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The purpose of this study is to examine whether the corruption level of a country is associated with a firm’s decision to choose Big 4 versus non-Big 4 auditors. In addition, the authors examine whether firms that are cross-listed in a country with a corruption level different from that of the home country are more likely to appoint Big 4 auditors.

Based on a sample of 185,549 firm-year observations from 78 countries over 2003-2012, panel regression analysis is used to investigate the research questions.

The authors find a negative association between corruption and the propensity to hire Big 4 auditors and that cross-listed firms are more likely to hire Big 4 auditors than their domestic counterparts. Interestingly, the authors find that when firms cross-list in less corrupt countries relative to their home countries, firms are more likely to hire Big 4 auditors. However, this tendency disappears when firms cross-list in more corrupt countries.

The authors contribute to the audit choice literature by providing evidence that the political environment, as manifested in the corruption level of a country, plays a role in the decision to choose Big 4 versus non-Big 4 auditors. The study complements the prior auditor choice literature, which focuses mostly on single countries such as the USA, by expanding the scope to 78 countries. Furthermore, the authors enhance the understanding of how the absolute and relative performance of the political environment affects cross-listed firms’ choice of auditors.

We investigate the interaction of debt covenants and tax accounting on the adoption of Financial Interpretation No. 48 (FIN 48). We examine how firms respond to the potential tightening of covenant slack upon FIN 48 adoption and whether these actions are penalized by creditors and anticipated by equity markets. We find that upon FIN 48 adoption, the majority of sample corporate borrowers increase their tax reserves and reduce equity. Firms close to debt covenant violation were even more likely to increase tax reserves upon FIN 48 adoption; however, the size of the adjustment was relatively smaller, suggesting that the FIN 48 standards limited, but did not eliminate, firms use of discretion in reporting uncertain tax positions to avoid costly covenant violations. For firms near net worth debt covenant violation, the act of decreasing equity upon FIN 48 adoption imposes real economic costs, as the average cost of debt increased by 43 basis points. Finally, we extend prior research on the market response to FIN 48 by showing how the market response to FIN 48 adoption is a function of debt covenant slack and tax aggressiveness. Specifically, the cumulative abnormal return at the FIN 48 exposure draft release date is negative only for tax aggressive firms that are close to debt covenant violation.

This study aims to provide a systematic and complete knowledge map for use by researchers working in the field of research data. Additionally, the aim is to help them quickly understand the authors' collaboration characteristics, institutional collaboration characteristics, trending research topics, evolutionary trends and research frontiers of scholars from the perspective of library informatics.

The authors adopt the bibliometric method, and with the help of bibliometric analysis software CiteSpace and VOSviewer, quantitatively analyze the retrieved literature data. The analysis results are presented in the form of tables and visualization maps in this paper.

The research results from this study show that collaboration between scholars and institutions is weak. It also identified the current hotspots in the field of research data, these being: data literacy education, research data sharing, data integration management and joint library cataloguing and data research support services, among others. The important dimensions to consider for future research are the library's participation in a trans-organizational and trans-stage integration of research data, functional improvement of a research data sharing platform, practice of data literacy education methods and models, and improvement of research data service quality.

Previous literature reviews on research data are qualitative studies, while few are quantitative studies. Therefore, this paper uses quantitative research methods, such as bibliometrics, data mining and knowledge map, to reveal the research progress and trend systematically and intuitively on the research data topic based on published literature, and to provide a reference for the further study of this topic in the future.