{"title":"Textual and contextual analysis of professionals’ discourses on XBRL data and information quality","authors":"Arif Perdana, A. Robb, Fiona H. Rohde","doi":"10.1108/IJAIM-01-2018-0003","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThe purpose of this study is to gain insight into what aspects of eXtensible Business Reporting Language (XBRL) data and information quality (DIQ) most interest professionals.\n\n\nDesign/methodology/approach\nThe authors use text analytics to examine XBRL discourses from professionals working in the domain. They explore the discussion in the three largest LinkedIn XBRL groups. Data collection covered the period 2010-2016.\n\n\nFindings\nVia the text analytics, the authors find the most appropriate XBRL DIQ dimensions. They propose an XBRL DIQ framework containing 18 relevant DIQ dimensions derived from both the accounting and IS fields. The findings of this study are expected to help direct future XBRL research into the DIQ dimensions most worthy of further empirical investigation.\n\n\nOriginality/value\nXBRL is the international standard for the digital reporting of financial, performance, risk and compliance information. Although the expectations of XBRL to produce improvements in DIQ via its applications (e.g. standard business reporting, digital data standard and interactive data visualization) are high, they remain unclear. This paper contributes to better understanding of the aspects of XBRL DIQ most relevant to professionals.\n","PeriodicalId":46371,"journal":{"name":"International Journal of Accounting and Information Management","volume":"10 1","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Accounting and Information Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/IJAIM-01-2018-0003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 4
Abstract
Purpose
The purpose of this study is to gain insight into what aspects of eXtensible Business Reporting Language (XBRL) data and information quality (DIQ) most interest professionals.
Design/methodology/approach
The authors use text analytics to examine XBRL discourses from professionals working in the domain. They explore the discussion in the three largest LinkedIn XBRL groups. Data collection covered the period 2010-2016.
Findings
Via the text analytics, the authors find the most appropriate XBRL DIQ dimensions. They propose an XBRL DIQ framework containing 18 relevant DIQ dimensions derived from both the accounting and IS fields. The findings of this study are expected to help direct future XBRL research into the DIQ dimensions most worthy of further empirical investigation.
Originality/value
XBRL is the international standard for the digital reporting of financial, performance, risk and compliance information. Although the expectations of XBRL to produce improvements in DIQ via its applications (e.g. standard business reporting, digital data standard and interactive data visualization) are high, they remain unclear. This paper contributes to better understanding of the aspects of XBRL DIQ most relevant to professionals.
期刊介绍:
The International Journal of Accounting & Information Management focuses on publishing research in accounting, finance, and information management. It specifically emphasizes the interaction between these research areas on an international scale and within both the private and public sectors. The aim of the journal is to bridge the knowledge gap between researchers and practitioners by covering various issues that arise in the field. These include information systems, accounting information management, innovation and technology in accounting, accounting standards and reporting, and capital market efficiency.