Abstract

PurposeThis study aims to focus on automated text analyses (ATAs) of sustainability and integrated reporting as a recent approach in empirical–quantitative research.Design/methodology/approachBased on legitimacy theory, the author conducts a structured literature review and includes 38 quantitative peer-reviewed empirical (archival) studies on specific determinants and consequences of sustainability and integrated reporting. The paper makes a clear distinction between analyses of reports due to readability, tone, similarity and specific topics. In line with prior studies, it is assumed that more readable reports with less tone and similarity relate to increased reporting quality.FindingsIn line with legitimacy theory, there are empirical indications that specific corporate governance variables, other firm characteristics and regulatory issues have a main impact on the quality of sustainability and integrated reporting. Furthermore, increased reporting quality leads to positive market reactions in line with the business case argument.Research limitations/implicationsThe author deduces useful recommendations for future research to motivate researchers to include ATA of sustainability and integrated reports. Among others, future research should recognize sustainable and behavioral corporate governance determinants and analyze other stakeholders’ reactions.Practical implicationsAs both stakeholders’ demands on sustainability and integrated reporting have increased since the financial crisis of 2008–2009, firms should increase the quality of reporting processes.Originality/valueThis analysis makes major contributions to prior research by including both sustainability and integrated reporting, based on ATA. ATAs play a prominent role in recent empirical research to evaluate possible drivers and consequences of sustainability and integrated reports. ATA may contribute to increased validity of empirical–quantitative research in comparison to classical manual content analyses, especially due to future CSR washing analyses.

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