When Data Become Ubiquitous, What Becomes of Accounting and Assurance?

2017 ◽  
Vol 31 (3) ◽  
pp. 1-4 ◽  
Author(s):  
A. Faye Borthick ◽  
Robin R. Pennington

ABSTRACT Big Data and the data analytical software for analyzing it have developed far enough that some trends have emerged. People are clever. Leave them alone with resources and they will do interesting things with them, giving both intended and unintended consequences. This commentary stems from the 2016 Journal of Information Systems Research Conference (JISC2016) on Big Data. It highlights the landscape of Big Data, including how organizations are starting to use data in different ways. While it is true that some of what this commentary offers does not, strictly speaking, require Big Data with respect to volume, diversity, and structure, the connotations that Big Data bestowed have prompted new ways to stage and use data. For example, “70% of firms now say that big data is of critical importance to their firms” (Malone 2016). The articles in this issue were presented as papers at JISC2016. They treat different aspects of the growing availability and use of data in organizations.

2019 ◽  
Vol 8 (4) ◽  
pp. 219
Author(s):  
Jaime L. Grandstaff ◽  
Lori L Solsma

This study analyzes the knowledge and methods used in information systems (IS) journals in the area of financial statement fraud. The purpose of this analysis is to provide tools and ideas to support interdisciplinary research in accounting and information systems for financial statement fraud topics. The study presents an analysis of five top ranking IS journals (MIS Quarterly, Information Systems Research, Communications of the ACM, Management Science, and Journal of MIS) and five top ranking IS conferences [International Conference on Information Systems (ICIS), Hawaii International Conference on System Sciences (HICSS), International Federation for Information Processing (IFIP), International Conference on Decision Support Systems (DSS), and Decision Sciences Institute National Conference (DSI)]. The literature found from these sources are categorized and presented by year, journal, contribution, type of study, methodology, data set usage, and research design. Although the literature varies, a common thread in many studies is the use of data mining and/or machine learning models to detect fraud.


Author(s):  
Charlotte P. Lee ◽  
Kjeld Schmidt

The study of computing infrastructures has grown significantly due to the rapid proliferation and ubiquity of large-scale IT-based installations. At the same time, recognition has also grown of the usefulness of such studies as a means for understanding computing infrastructures as material complements of practical action. Subsequently the concept of “infrastructure” (or “information infrastructures,” “cyberinfrastructures,” and “infrastructuring”) has gained increasing importance in the area of Computer-Supported Cooperative Work (CSCW) as well as in neighboring areas such as Information Systems research (IS) and Science and Technology Studies (STS). However, as such studies have unfolded, the very concept of “infrastructure” is being applied in different discourses, for different purposes, in myriad different senses. Consequently, the concept of “infrastructure” has become increasingly muddled and needs clarification. The chapter presents a critical investigation of the vicissitudes of the concept of “infrastructure” over the last 35 years.


1997 ◽  
Vol 26 (4) ◽  
pp. 69-74
Author(s):  
Sushil Jajodia ◽  
Daniel Barbará ◽  
Alex Brodsky ◽  
Larry Kerschberg ◽  
Ami Motro ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document