Is audit committee expertise connected with increased readability of integrated reports: Evidence from EU companies

  • Received January 23, 2018;
    Accepted March 29, 2018;
    Published April 20, 2018
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  • Article Info
    Volume 16 2018, Issue #2, pp. 23-41
  • Cited by
    34 articles

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

This study contributes to the recent “managerial ability” literature and analyses the impact of audit committees’ financial and sustainability expertise (i.e. combined and separately as individuals) on the readability of integrated reports. Analyses were conducted with data on a sample of European Union (EU) public interest entities (PIE) from the Examples Database of the International Integrated Reporting Council (IIRC) for the fiscal years 2014–2016 (i.e. 215 firm-year observations). Correlation and regression analyses were conducted to evaluate possible links between either financial or sustainability expertise and combined financial and sustainability expertise in audit committees and the readability of integrated reports, as measured by the Flesch Reading Ease and Gunning Fog indices. While audit committees’ financial and sustainability expertise has a positive impact on the readability of integrated reports, combined expertise has a stronger effect compared with either financial or sustainability expertise. This finding is in line with the idea that, to combine financial and sustainability information in integrated reports, audit committees need to have more diverse expertise. Companies, regulators and researchers could be significantly affected by the finding that managerial ability variables such as audit committee expertise can have a considerable impact on integrated reporting.

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    • Table 1. Survey sample
    • Table 2. Financial and sustainability expertise on the audit committee
    • Table 3. Flesch reading ease score
    • Table 4. Variables of the study
    • Table 5. Development of the integrated reporting readability (IR)
    • Table 6. Descriptive statistics
    • Table 7. Pearson correlation matrix
    • Table 8. Regression analysis (Flesch Reading Ease index)
    • Table 9. Robustness checks (Fog index)