Bibliometric analysis of literature on narrative discourse in corporate annual reports (1990–2019)

Yubin Qian () and Ya Sun ()
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Yubin Qian: University of Chinese Academy of Sciences
Ya Sun: University of International Business and Economics

Quality & Quantity: International Journal of Methodology, 2022, vol. 56, issue 2, No 4, 429-446

Abstract: Abstract This article presents a bibliometric analysis of prior studies on narratives in corporate annual reports (CARs) between 1990 and 2019. It is found that studies in the past longitudinally follow an ascending trend with uneven distribution across disciplines and nations. Their primary data source is the entire CAR or its components. Usually based on the content or textual analytical approaches, they aim to uncover the mapping of narrative discourse onto the corporate performance. Their hotspots include CARs’ readability, financial reporting aggressiveness, firm disclosure genres, firm disclosure content, and corporate impression management. They rely heavily upon the theoretical or methodological frameworks involving corporate governance, dictionary, machine learning, and statistical modeling. Findings of the present research point to five under-investigated areas that need future research.

Keywords: Narrative; Discourse; Annual report; Non-financial information; Bibliometric analysis (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11135-021-01135-5

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