-------- Forwarded Message -------- Subject: [AISWorld] Contents of Volume 20, Issue 1 (January) Journal of the Association for Information Systems (JAIS) Date: Sun, 3 Feb 2019 04:21:21 +0000 From: JAIS JAIS@comm.virginia.edu To: aisworld@lists.aisnet.org aisworld@lists.aisnet.org

Contents of Volume 20, Issue 1 (January) Journal of the Association for Information Systems (JAIS), Official Publication of the Association for Information Systems Published: Monthly Electronically ISSN: 1536-9323 Published by the Association for Information Systems, Atlanta, USA (http://aisel.aisnet.org/jais/)

Editor-in-Chief: Professor Suprateek Sarker, University of Virginia, USA

Paper

Sleight of Hand: Identifying Concealed Information by Monitoring Mouse-Cursor Movements

Jeffrey L. Jenkins, Brigham Young University Jeffrey Proudfoot, Bentley University Joseph Valacich, University of Arizona G. Mark Grimes, University of Houston Jay F. Nunamaker, Jr., University of Arizona

Abstract

Organizational members who conceal information about adverse behaviors present a substantial risk to that organization. Yet the task of identifying who is concealing information is extremely difficult, expensive, error-prone, and time-consuming. We propose a unique methodology for identifying concealed information: measuring people’s mouse-cursor movements in online screening questionnaires. We theoretically explain how mouse-cursor movements captured during a screening questionnaire differ between people concealing information and truth tellers. We empirically evaluate our hypotheses using an experiment during which people conceal information about a questionable act. While people completed the screening questionnaire, we simultaneously collected mouse-cursor movements and electrodermal activity—the primary sensor used for polygraph examinations—as an additional validation of our methodology. We found that mouse-cursor movements can significantly differentiate between people concealing information and people telling the truth. Mouse-cursor movements can also differentiate between people concealing information and truth tellers on a broader set of comparisons relative to electrodermal activity. Both mouse-cursor movements and electrodermal activity have the potential to identify concealed information, yet mouse-cursor movements yielded significantly fewer false positives. Our results demonstrate that analyzing mouse-cursor movements has promise for identifying concealed information. This methodology can be automated and deployed online for mass screening of individuals in a natural setting without the need for human facilitators. Our approach further demonstrates that mouse-cursor movements can provide insight into the cognitive state of computer users.

To obtain a copy of the entire article, click on the link below: Available at: http://aisel.aisnet.org/jais/vol20/iss1/3

Paper

An Activity Theory Approach to Modeling Dispatch-Mediated Emergency Response

Roht Valecha, University of Texas at San Antonio Raghav Rao, University of Texas at San Antonio Shambhu Upadhyaya, Department of Computer Science and Engineering, State University of New York, Buffalo, New York Raj Sharman, State University of New York at Buffalo

Abstract

Emergency response involves multiple local, state, and federal communities of responders. These communities are supported by emergency dispatch agencies that share digital traces of task-critical information. However, the communities of responders often comprise an informal network of people and lack structured mechanisms of information sharing. To standardize the exchange of task-critical information in communities of responders, we develop a conceptual modeling grammar. We base the grammar on an activity-theory perspective and ground it in an analysis of emergency dispatch incident reports. The paper contributes to research in dispatch-mediated emergency response literature by (1) developing a framework of elements and relationships to support critical information flow within emergency communities of responders, (2) developing a conceptual modeling grammar for modeling emergency tasks in dispatch-mediated emergency response, and (3) implementing a prototype system to demonstrate the utility of the conceptual modeling grammar.

To obtain a copy of the entire article, click on the link below: Available at: http://aisel.aisnet.org/jais/vol20/iss1/2

Paper

Never, Never Together Again: How Postpurchase Affect Drives Consumer Outcomes Within the Context of Online Consumer Support Communities

Eun Hee Park, Old Dominion University Ghiyoung Im, University of Louisville Veda C. Storey, Georgia State University Richard L. Baskerville, Georgia State University; Curtin University

Abstract

Online support communities are popular for consumers of information technology products who might need help identifying or resolving a problem. Information technology products, in general, have their own needs and requirements. Prior research has focused on the intermediate benefits of online support communities to companies, such as knowledge contribution and community participation. This study, in contrast, investigates the less explored issue of value creation by online support communities with respect to consumer postpurchase outcomes. To do so, we develop an affect (emotional) process model to understand how customers’ postpurchase outcomes of information technology products are influenced through cognitive and affective processes after a product failure. Special attention is paid to the roles of affect during the recovery process. An empirical assessment of the model uses two online support communities, with a netnography methodology employed for data collection. The results suggest that consumers’ postpurchase outcomes are influenced by affect and regulation, not just cognition. Key influences emerge as the consumers’ own problem appraisals and affective experiences, the consumers’ social group, and regulation provided by company technicians and/or community experts.

To obtain a copy of the entire article, click on the link below: Available at: http://aisel.aisnet.org/jais/vol20/iss1/1

Elizabeth White Baker, PhD Production Managing Editor, Journal of the AIS jais@comm.virginia.edu

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