Please use this identifier to cite or link to this item:
Title: The joint effect of animated graphs and motion verbs on investor judgments
Authors: Chan, Ian Han Sheng
Keywords: Business::Accounting
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Chan, I. H. S. (2022). The joint effect of animated graphs and motion verbs on investor judgments. Doctoral thesis, Nanyang Technological University, Singapore.
Project: UOB Endowed Chair
Abstract: Within the context of accounting disclosures, firms often have significant control over the manner in which data is presented and the language used to present these disclosures. I examine two features of the disclosure setting. I predict that the use of animated graphs or static graphs in accounting disclosures can influence investor investment judgments, but the effect of this depends on the type of language used in the disclosure. I experimentally test my prediction using an investor day transcript in which the graphs used are either animated or static, and the language used either contains motion verbs or does not. I further add two additional control conditions in which I keep the vividness of the language low in order to examine the effects of animated or static graphs. As predicted, I find that animated graphs result in more favorable investment judgments than when static graphs are used, but only when used in conjunction with motion verbs. I run a second experiment to examine the cognitive processes that underpin the findings in Experiment One, but the results of Experiment Two suggest that the cognitive processes leading to the findings occur unconsciously. I identify a new data visualization feature in the accounting disclosure setting, the animation of graphs, and how it influences investor judgments.
DOI: 10.32657/10356/164001
Schools: Nanyang Business School 
Rights: This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:NBS Theses

Files in This Item:
File Description SizeFormat 
Thesis - Ian Chan.pdf672.91 kBAdobe PDFThumbnail

Page view(s)

Updated on Feb 27, 2024

Download(s) 50

Updated on Feb 27, 2024

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.