Kevin Moffitt

AIS in an Age of Big Data

An introduction is presented in which the editor discusses the accounting Information systems impact on the Big Data and mentions several topics including the examining the dashboards, less usage of eXtensible Business Reporting Language and the information system complexity analysis.

Which Spoken Language Markers Identify Deception in High-Stakes Settings? Evidence From Earnings Conference Calls

Quarterly conference calls where corporate executives discuss earnings that are later found to be misreported offer an excellent test bed for determining if automated linguistic and vocalic analysis tools can identify potentially fraudulent utterances in prepared versus unscripted remarks. Earnings conference calls from one company that restated their financial reports and were accused of making misleading statements were annotated as restatement-relevant (or not) and as prepared (presentation) or unprepared (Q&A) responses. We submitted more than 1,000 utterances to automated analysis to identify distinct linguistic and vocalic features that characterize various types of utterances. Restatement-related utterances differed significantly on many vocal and linguistic dimensions. These results support the value of language and vocal features in identifying potentially fraudulent utterances and suggest important interplay between utterances that are unscripted responses rather than rehearsed statements.

A Theoretical Justification for Using Embodied Conversational Agents (ECAs) to Augment Accounting-Related Interviews

ABSTRACT: In todays increasingly complex business environment, accounting firms face additional pressures regarding cost reduction, engagement scope, and attention to quality. This paper proposes that embodied conversational agents (ECAs) are particularly well suited to automate and augment accounting interviews to save costs, streamline the interviewing process, and maintain quality. An ECA is an autonomous computer interface capable of human-like interactions such as interviews. This paper describes how an ECA can be used to augment accounting-related interviews and the advantages and disadvantages of doing so. This paper also presents the ECA Self-Disclosure Model with propositions of how self-disclosure can be influenced by an ECA through reciprocal behavior and rapport building. The model and propositions are supported by the computers-as-social-actors (CASA) paradigm (Reeves and Nass 1996). This paper concludes by discussing limitations of ECA use in the real world and by recommending how the model...

Automated deception detection of 911 call transcripts

This study is a successful proof of concept of using automated text analysis to accurately classify transcribed 911 homicide calls according to their veracity. Fifty matched, caller-side transcripts were labeled as truthful or deceptive based on the subsequent adjudication of the cases. We mined the transcripts and analyzed a set of linguistic features supported by deception theories. Our results suggest that truthful callers display more negative emotion and anxiety and provide more details for emergency workers to respond to the call. On the other hand, deceivers attempt to suppress verbal responses by using more negation and assent words. Using these features as input variables, we trained and tested several machine-learning classification algorithms and compared the results with the output from a statistical classification technique, discriminant analysis. The overall performance of the classification techniques was as high as 84% for the cross-validated set. The promising results of this study illustrate the potential of using automated linguistic analyses in crime investigations.

Perspectives on Past and Future AIS Research as the Journal of Information Systems Turns Thirty

ABSTRACT: This paper complements a panel session pertaining to past and future AIS research that was held during the 2015 American Accounting Association Annual Meeting. There are two main parts to this commentary. First, using text mining techniques on AIS article abstracts for the period 1986–2014, we identify the top research themes across three leading AIS journals (Journal of Information Systems, International Journal of Accounting Information Systems, and Journal of Emerging Technologies in Accounting). We chart the usage of these themes over time and discuss their shifting popularity. Second, we speculate on the future of AIS research and identify a series of broad research streams that may garner greater importance over the next 30 years. A host of broad research questions accompany the discussion of emerging and anticipated research streams in order to motivate and guide future research.