Interactive data visualisation for accounting information: a three-fit perspective. Issue 1 (2nd January 2019)

• Record Type: Journal Article
• Authors: Perdana, Arif; Robb, Alastair; Rohde, Fiona
• Is Part Of: Behaviour & information technology. Volume 38:Issue 1(2019)
• Page Start: 85
• Page End: 100
• Publication Date: 2019-01-02
• Subjects: Interactive media -- data visualisation -- cognitive theories -- task-technology fit -- information visualisation -- visual analytics; Electronic data processing -- Periodicals; Human engineering -- Periodicals; Information technology -- Periodicals; 303.4833
• DOI: 10.1080/0144929X.2018.1514424
• Languages: English
• ISSNs: 0144-929X

Abstract

ABSTRACT: The volume of freely available accounting information is rapidly becoming overwhelming. To be useful, information needs to be delivered to users in a suitable, relevant, and understandable form. Interactive data visualisation (IDV) can help address this need for useful information by organising accounting information, especially financial reports, into forms with these qualities. Given both their prevalence and their likelihood of being future users of IDV, the purpose of this research is to examine the appropriateness of IDV for non-professional investors' use when they access accounting information. This research uses a 2 × 2 experimental approach involving 404 participants representing non-professional investors from diverse demographic backgrounds. This research suggests that IDV mitigates non-professional investors' restricted investment capabilities by presenting information that is more salient, thus reducing non-professional investors' cognitive effort. This combination allows such investors to better perform both simple and multipart investment tasks. By integrating three information systems' fit perspectives (i.e. task technology, information quality, and cognitive), this research explains IDV's suitability and fit within the accounting domain. We also discuss how the findings can inform practice and span interdisciplinary research into data and information visualisation.