Determinants of strategy disclosure quality: empirical evidence from Germany

  • Received August 5, 2019;
    Accepted November 11, 2019;
    Published November 19, 2019
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/ppm.17(4).2019.09
  • Article Info
    Volume 17 2019, Issue #4, pp. 104-120
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Strategy reporting is of high interest to investors and can be seen as decision-useful information. The focus of this study is to analyze the determinants of the quality of voluntary strategy disclosure in German management reports of capital market-oriented companies. Based on a theoretical analysis, hypotheses are formulated to investigate the determinants of the quality of voluntary strategy disclosure. In order to test the hypotheses, a number of statistical tests are performed, especially multiple regression analyses. It is based on a unique hand-collected dataset with a self-constructed scoring model, which measures the quality of voluntary strategy disclosure. The sample comprises 110 largest companies in Germany for the period between 2014 and 2018. The results indicate that firm size, firm growth and capital intensity determine voluntary strategy disclosure significantly and positively. Conversely, firm age, financial leverage, ownership structure and profitability do not have a significant relationship with voluntary strategy disclosure. The results are robust to different statistical analysis. This research provides insights into a neglected topic in academia and helps decision-makers in practice and regulators to better understand voluntary strategy disclosure of capital market-oriented companies.

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    • Table 1. Sample selection procedure
    • Table 2. Descriptive statistics of metric variables
    • Table 3. Pearson and spearman correlation matrix
    • Table 4. Results of multiple regression models
    • Table 5. Robustness check 1: regression models by year
    • Table 6. Robustness check 2: regression models with different proxies for firm size without control variables
    • Table 7. Robustness check 3: regression models with different proxies for firm size including control variables
    • Table A1. Data collection instrument