Arif Perdana

An Integrative Review and Synthesis of XBRL Research in Academic Journals

ABSTRACT:  Extensible business reporting language (XBRL) was developed from an established markup computer language (eXtensible Markup Language, XML). XBRL facilitates data and information exchange between different information systems (IS). This important feature has attracted much research since the early 2000s. This article aims to provide a framework for XBRL researchs contributions to information systems (IS). An integrative review is needed to draw an overall picture and canvas key findings regarding the various XBRL topics examined in past studies. Such a review also identifies research opportunities and guides future XBRL research. We conducted thematic analysis using an integrative literature review. A sample of 150 XBRL articles obtained from various peer-reviewed academic journals was used to understand past XBRL studies and suggest XBRLs future research direction. This article identifies and proposes four current XBRL research streams; namely, XBRLs impact on business, XBRLs adoption, XBRL...

Experimental research and multivariate statistical analyses in business information systems research - a meta-review

Experimental research has been widely used within the information systems IS field. Using a meta-review, this study examines the use of experimental research in the IS field during the period 1990 to 2013 and investigates the utilisation of statistical techniques, particularly multivariate analyses. This study provides important information regarding the pattern of experimental research in the IS field i.e., experimental designs, treatments, tasks, incentives and participants. This study finds that multivariate analysis of variance MANOVA is frequently used as the multivariate statistical technique in experimental IS research. While the use of multivariate analyses is common in recent experimental IS research, concerns remain about the potential inappropriate use of measurements and violations of statistical assumptions required by the various multivariate analyses, for example, using ordinal scales rather than interval scales and issues surrounding the normality of data. This article is intended to offer guidelines to help future researchers be aware of the statistical issues and to mitigate the shortcomings that arise due to inappropriate use of measurements and violations of the statistical assumptions in experimental IS research.