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The potential benefits of collaboration technologies are typically realized only in groups led by collaboration experts. This raises the facilitator-in-the-box challenge: Can collaboration expertise be packaged with collaboration technology in a form that nonexperts can reuse with no training on either tools or techniques? We address that challenge with process support applications (PSAs). We describe a collaboration support system (CSS) that combines a computer-assisted collaboration engineering platform for creating PSAs with a process support system runtime platform for executing PSAs. We show that the CSS meets its design goals: (1) to reduce development cycles for collaboration systems, (2) to allow nonprogrammers to design and develop PSAs, and (3) to package enough expertise in the tools that nonexperts could execute a well-designed collaborative work process without training.

Analyzing the learning analytics from a course provides insights that can impact instructional design decisions. This study used educational data mining techniques, specifically a longitudinal k-means cluster analysis, to identify the strategies students used when completing the online portion of an online flipped spreadsheet course. An analysis of these results showed that students did tend to follow a specific learning strategy as they completed this course. However, students also self-regulated to some degree, based on the topic and context of specific lessons. These insights not only improve our understanding about the students taking the course, but they also provide guidance for how the instructional design of the course might be improved. Of note is the practical value of this proof-of-concept study in using educational data mining to improve the instructional design of a course.

Financial fraud can have serious ramifications for the long-term sustainability of an organization, as well as adverse effects on its employees and investors, and on the economy as a whole. Several of the largest bankruptcies in U.S. history involved firms that engaged in major fraud. Accordingly, there has been considerable emphasis on the development of automated approaches for detecting financial fraud. However, most methods have yielded performance results that are less than ideal. In consequence, financial fraud detection continues as an important challenge for business intelligence technologies. In light of the need for more robust identification methods, we use a design science approach to develop MetaFraud, a novel meta-learning framework for enhanced financial fraud detection. To evaluate the proposed framework, a series of experiments are conducted on a test bed encompassing thousands of legitimate and fraudulent firms. The results reveal that each component of the framework significantly contributes to its overall effectiveness. Additional experiments demonstrate the effectiveness of the meta-learning framework over state-of-the-art financial fraud detection methods. Moreover, the MetaFraud framework generates confidence scores associated with each prediction that can facilitate unprecedented financial fraud detection performance and serve as a useful decision-making aid. The results have important implications for several stakeholder groups, including compliance officers, investors, audit firms, and regulators.

This paper describes an innovative, integrated implementation of the core Information Systems courses. While the published IS curriculum provides standards on course \"content\", it gives little direction on the \"implementation\" of the courses. At Brigham Young University, we have reengineered the traditional topics of analysis, database, design, development, networking, etc. into an integrated, 24-hour course block called the \"IS Core\". Instead of students moving from class to class, professors now rotate through integrated subjects in a common classroom environment. The IS Core has allowed the department to increase the rigor and integration between subjects so students see the entire systems process and has provided opportunities for cross-topic assignments and integrated exercises. Finally, it has resulted in unintended, additional benefits like increased student culture and student ownership of the major. (Contains 7 tables.)

The purpose of this paper is to advance theoretical understanding of the important role of both power and negotiation during online deception.  By so doing, the paper provides insight into the relationship between perpetrator and victim in Internet fraud. The growing prevalence of Internet Fraud continues to be a burden to both society and individuals. In an attempt to better understand Internet fraud and online deception, this article attempts to build an interactive model, based upon the dimensions of power and negotiation from the management and psychology literature. Using the model presented, the article examines the effects of the Internet on the communication process that takes place between perpetrator and victim. Finally, the article discusses some of the major tactics employed to appeal to each power type in predominant fraud forms, as well exploring future types of fraud.

This paper proposes an adaptive learning approach that yields decision models that can be applied by a transactions agent. This model can learn effectively with a variety of data distributions. This research uses the Semantic Web as a data access approach. The Semantic Web is a method that sellers can use to publish semantically meaningful information on Websites so automated applications can reliably access that information. We implemented a Semantic Web composed of 30 vendors' Web pages and a spider to search those pages to obtain product and vendor information. This information was used to train a learning agent, which then provided a decision model to a transaction agent. [PUBLICATION ABSTRACT]

Purpose - The purpose of this paper is to present and explain the identity theft cycle. The identity theft cycle explains how a perpetrator goes through various stages of confidence and experimentation when stealing an individual's identity.Design methodology approach - The paper takes a conceptual approach by first describing identity theft in detail and then discussing the seriousness of identity theft for consumers today. The paper then presents and explains the identity theft cycle in greater detail including the stages of discovery, action, and trial.Findings - The paper provides evidence to suggest that if identity theft is detected early, consumers can protect themselves from the vast and difficult consequences of identity theft.Originality value - This paper fulfills an important area of research by providing basic information about the nature of identity theft. This paper also discusses the various ways that perpetrators steal consumers' information, as well as teaches consumers how to proactively protect themselves from identity theft.

To better understand how fraud affects corporate strategy, the authors examine the case of John McNamara, who in the 1990s committed a $436 million fraud against General Motors (GM). They chose to highlight this case because of the significant strategic implications of the fraud as well as the applicability of the case to organizations today. Unlike most fraud incidents that are either quietly hidden or quickly dismissed by management, most of the details of the John McNamara fraud have been made public, including numerous court filings and documents. Furthermore, because the case took place more than 20 years ago, they now can look back and identify the long-term implications that the fraud had on GM. By understanding the long-term effects of the fraud, they can better understand the relationship between fraud and corporate strategy. Thus, the case allows them to illustrate the disadvantages the fraud created for GM compared to other organizations within the industry.

Abstract We use student-level online resource usage data for students in four different introductory accounting courses to explore the impact on exam performance of both student study effort and students’ revealed preferences for reading text or watching video lectures. The online learning tool tracks student study choice (read text, watch video, or skip) on a paragraph-by-paragraph level. We match these usage data with student performance on course exams. We find that students who study more material earn higher exam scores than do students who study less material. We also find that students who self-select to do relatively more of their studying through reading text score higher on exams, on average, than do students who self-select to do relatively more of their studying through watching videos. Specifically, holding the overall amount of study constant, a student who chooses to spend the highest fraction of her or his study time watching video mini lectures earns exam scores 10 percentage points lower (six-tenths of a standard deviation) than a student who chooses to spend the lowest fraction of study time watching videos. Our results demonstrate that at least for introductory accounting students, increased study effort does indeed have a positive impact on exam performance. Our evidence also suggests that the highest performing introductory accounting students choose to learn accounting proportionately more through reading than through watching. These results are a reminder that when we talk about using “technology” to help our students learn accounting, the written word is still an important technology.

This paper presents the Ethics Development Model (EDM) as a lens by which to view declining ethics in accounting and other business professions. The paper also provides a background on fraud (one type of ethical breakdown) and its causes. The EDM comprises personal ethical understanding, application of ethics to business situations, ethical courage and ethical leadership. The model is applied to declining ethics, teaching styles and educational responsibility.