XBRL diffusion in social media: discourses and community learning

Perdana, Arif, Robb, Alastair and Rohde, Fiona (2015) XBRL diffusion in social media: discourses and community learning. Journal of Information Systems, 29 2: 71-106. doi:10.2308/isys-50996

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Author Perdana, Arif
Robb, Alastair
Rohde, Fiona
Title XBRL diffusion in social media: discourses and community learning
Journal name Journal of Information Systems   Check publisher's open access policy
ISSN 1558-7959
0888-7985
Publication date 2015
Sub-type Article (original research)
DOI 10.2308/isys-50996
Open Access Status Not Open Access
Volume 29
Issue 2
Start page 71
End page 106
Total pages 36
Place of publication Sarasota, FL, United States
Publisher American Accounting Association
Collection year 2016
Language eng
Formatted abstract
Multiple discourses are critical in determining the success of information technology (IT) diffusion. Since its inception, such discourses also appear in the eXtensible Business Reporting Language (XBRL) diffusion sphere. To help explain XBRL diffusion, we explore the discourses relative to XBRL in social media. A case study with text mining and content analysis was conducted to address three research questions covering community discourses, polarity of viewpoint, and learning surrounding XBRL in social media. Our sample data consisted of members' posts and comments in LinkedIn XBRL groups over the period 2010 to 2013. Our analysis finds that XBRL discourses in social media have largely revolved around the dissemination of XBRL information to raise awareness among potential adopters (i.e., theorization) and to properly implement XBRL (i.e., translation). Our findings indicate that XBRL's theorization is not in doubt, while XBRL's translation remains challenging. Professionals generally view XBRL positively. Those who view XBRL less favorably are more likely to be skeptical rather than dismissive. We also observe that social media like LinkedIn is a relevant channel for communities to learn about XBRL. We discuss the findings and include several insights and implications that may be useful in augmenting the future of XBRL.
Keyword XBRL
Social media
LinkedIn
IT diffusion
Institutional theory
Community learning
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
UQ Business School Publications
 
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Created: Tue, 09 Dec 2014, 20:50:36 EST by Arif Perdana on behalf of UQ Business School