叙述的
显著性(神经科学)
判决
心理学
证券交易所
词汇
可读性
语言学
拼写
谈判
公司治理
会计
利润(经济学)
库存(枪支)
语调(文学)
收入
社会心理学
文档
股东价值
叙述性探究
内容分析
无知
错误
突出
认知心理学
精算学
经济
作者
Tim Alexander Herberger,Alina Alexenko
标识
DOI:10.1108/jfra-04-2025-0267
摘要
Purpose This study aims to investigate how narratively conveyed salience is expressed by Financial Times Stock Exchange (FTSE) companies when describing financial results that may intentionally or unintentionally emphasize desirable business developments and hide undesirable ones by using unbalanced language (“biased tone”) in shareholder letters and strategic reports (management commentary). Design/methodology/approach The 2019 and 2024 annual reports of FTSE companies listed on the London Stock Exchange were used as the sample. A mixed-methods approach – combining qualitative and quantitative content analysis – was used to develop a detailed system of codes (word lists) and analyze the frequency of code co-occurrences in the narrative presentation of information in annual reports. Findings The results show that, on average, more “positive connoted” and “attention-focusing” words (communicating higher salience) are used by companies to report positive (desirable) revenue and profit results. At the same time, this study did not confirm that more “attention-diverting” modality words (words that communicate lower salience) are used to report negative (undesirable) business developments in revenue and profit. The results are consistent across the periods considered. Originality/value This study contributes to the literature on narrative tone by proposing a more detailed view of tone characteristics, focusing on salience vocabulary as well as positive and negative tone. This work also differs methodologically from previous econometric studies in that it does not use stochastic correlations, but instead counts the co-occurrence of coded words in the given sentence and analyzes the number of such co-occurrences. Furthermore, the narrative salience of good or bad financial performance can be analyzed with a given coding system, largely independent of the language used (or the slight differences can be explained).
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