Getting Caught “Sugar Coating”: The Behavioral Implications Of Using A Decision Aid That Detects Linguistic Manipulations In Financial Disclosures

Keywords

Decision aid to linguistic manipulations; Disclosure credibility; Linguistic manipulations; Management incentive; Willingness to invest

Abstract

Evidence from recent studies suggests that management strategically uses linguistic manipulations to “sugar coat” corporate narratives particularly when it is to their advantage. Research also suggests that investors are influenced by these manipulations and that they are not capable of detecting them on their own. Emerging technologies such as textual analysis software are capable of analyzing corporate narratives; however, their impact on investors’ decision making remains unknown. This manuscript explores the effect of these emerging technologies a priori to their availability and investigates whether providing investors with a decision aid (DA) that is capable of detecting linguistic manipulations can be an effective tool that can be used by investors. We theorize that these DAs may have an effect on investors’ judgment and decision making and that their effect may interact with other contextual factors such as management incentive to provide a more optimistic disclosure when the news is not necessarily good. More precisely, we investigate the effect of management incentive and the detection of linguistic manipulations in management’s disclosures on investors’ perceptions of disclosure credibility and willingness to invest, and whether the detection of linguistic manipulations moderates the impact of management incentive. Results show that both management incentive and detection of linguistic manipulations have a significant effect on investors’ perceptions of disclosure credibility and willingness to invest. Therefore, these DAs can be an effective tool that investors can use to detect linguistic manipulations.

Publication Date

1-1-2016

Publication Title

Journal of Emerging Technologies in Accounting

Volume

13

Issue

2

Number of Pages

169-184

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.2308/jeta-51596

Socpus ID

85011879327 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85011879327

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