Volume 11, 2011

 

The Impact of XBRL: A Delphi Investigation Amelia A. Baldwin and Brad S. Trinkle Published January 2011
This project attempts to add to the extant research by presenting the results of a future forecasting Delphi study that addresses the impacts of XBRL in the second decade of the new millennium. The future impacts of XBRL [eXtensible Business Reporting Language] on financial reporting were studied using the Delphi technique. The Delphi panel suggests that XBRL is very likely to impact corporations, financial reporting, users of financial reports and auditing. The most likely impacts of XBRL include: increased accessibility of financial reports, easier regulatory compliance, enhanced availability of financial reports, facilitation of continuous reporting, and improved efficiency in investment and business decision making.
The impact of Accounting Information Systems (AIS) on performance measures: empirical evidence in Spanish SMEs Elena Urquía Grande, Raquel Pérez Estébanez and Clara Muñoz Colomina Published March 2011
This research study is aimed, based on empirical evidence, at measuring the relationship between the use of the Accounting Information Systems (AIS) by the Small and Medium Sized Enterprises (SMEs) in Spain, and firms’ improved performance indicators and productivity. This empirical study is based on a survey carried out among small and medium-sized firms to ascertain the extent to which development and implementation of accounting information systems had taken place, and subsequently an analysis was made as to how much this introduction may impact on improvement in outcome indicators and productivity. As interesting results we have found that there is a positive relationship among the SMEs that use AIS for fiscal and bank management and better performance measures. This research provides value added in accounting literature given the scarcity of works dealing with the relationship between the application and use of AIS and performance and productivity indicators in SMEs in Spain.
Adopting XBRL in Italy: Early evidence of fit between Italian GAAP Taxonomy and current reporting practices of non-listed companies Diego Valentinetti and Michele A. Rea Published May 2011
XBRL (eXtensible Business Reporting Language) will soon be the leading means of corporate financial reporting. A key feature of its adoption relies on well-defined standard taxonomies, which should adequately reflect both the accounting standards and the reporting practices of firms. This study considers this issue, following the concept of ―taxonomy fit‖ proposed by Bovee et al. (2002; 2005) and Bonsón et al. (2009a). The aim is to fill a specific gap in the previous literature, by analyzing the applicability of XBRL in the context of template-based accounting standards. Specifically, we assess the fit between the XBRL Italian GAAP Taxonomy and the traditional annual reports of Italian non-listed companies, which are required to file their financial statements in XBRL. The results show an almost perfect fit but with significant differences among the financial statements analyzed. In addition, the degree of misfit, when it occurs, depends on the sector, the size and the level of disaggregation of information provided by the companies.
Cluster Analysis for Anomaly Detection in Accounting Data: An Audit Approach Sutapat Thiprungsri and Miklos A. Vasarhelyi Published July 2011
This study examines the application of cluster analysis in the accounting domain, particularly discrepancy detection in audit. Cluster analysis groups data so that points within a single group or cluster are similar to one another and distinct from points in other clusters. Clustering has been shown to be a good candidate for anomaly detection. The purpose of this study is to examine the use of clustering technology to automate fraud filtering during an audit. We use cluster analysis to help auditors focus their efforts when evaluating group life insurance claims. Claims with similar characteristics have been grouped together and small-population clusters have been flagged for further investigation. Some dominant characteristics of those clusters which have been flagged are large beneficiary payment, large interest payment amounts, and long lag between submission and payment.
From Emerging to Connected E-Government: The Effects of Socioeconomics and Internal Administration Characteristics Luis Rodríguez-Domínguez, Isabel María García Sánchez and Isabel Gallego Álvarez Published September 2011
The aim of this study is to explain the development of e-government using a new measure of the content, presentation, navigability and interaction of the websites created by public administrations as illustrated in the United Nations 2008 report, Services Delivery by Stages. These results differ from previous empirical analyses, showing that citizens‟ economic and education levels are not the main factors driving the development of digital administration. On the contrary, the sophisticated design of e-government seems to be linked strongly to the idea of a new public management defined by organizations such as OECD, as well as a North American style of economic development.
S&P 500 Index Direction Forecasting from 1976 to 2010: A Fuzzy System Approach Cesar Duarte Souto-Maior, José Alonso Borba and Newton C. A. da Costa Jr. Published November 2011
Investors are not always completely rational and they do not always work only with numbers. Sometimes, they use linguistic concepts to make their decisions. Fuzzy logic is helpful in handling such situations. This article differs from other studies in this area by applying fuzzy logic for forecasting the direction/sign of stock market indexes. The article also presents a model for forecasting the direction/sign of stock market indexes using a fuzzy system, and this model is applied in the prediction of the S&P 500 Index. The rules of the model were established between 1970 and 2009, and the test period was from 1976 to 2010. Despite the fact that the estimated model produced a linguistic output, it was possible to delineate a statistically significant investment strategy, which outperformed a buy-and-hold one. In addition, the success rate calculated was also statistically significant. Another difference from other studies is that the proposed model does not return an exact output, but a probabilistic one of linguistic variables. The proposed model, with its probabilistic output, can be used as a support for investment decisions. In other words, the linguistic output does not force the investor to blindly follow the proposed strategy.