Increasing accountability through user-interface design artifacts : A new approach to addressing the problem of access-policy violations

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review

70 Scopus Citations
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Author(s)

  • Anthony Vance
  • Paul Benjamin Lowry
  • Dennis Eggett

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)345-366
Journal / PublicationMIS Quarterly: Management Information Systems
Volume39
Issue number2
Early online date3 Mar 2015
Publication statusPublished - Jun 2015

Abstract

Access-policy violations are a growing problem with substantial costs for organizations. Although training programs and sanctions have been suggested as a means of reducing these violations, evidence shows the problem persists. It is thus imperative to identify additional ways to reduce access-policy violations, especially for systems providing broad access to data. We use accountability theory to develop four user-interface (UI) design artifacts that raise users' accountability perceptions within systems and in turn decrease access-policy violations. To test our model, we uniquely applied the scenario-based factorial survey method to various graphical manipulations of a records system containing sensitive information at a large organization with over 300 end users who use the system daily. We show that the UI design artifacts corresponding to four submanipulations of accountability can raise accountability and reduce access policy violation intentions. Our findings have several theoretical and practical implications for increasing accountability using UI design. Moreover, we are the first to extend the scenario-based factorial survey method to test design artifacts. This method provides the ability to use more design manipulations and to test with fewer users than is required in traditional experimentation and research on human-computer interaction. We also provide bootstrapping tests of mediation and moderation and demonstrate how to analyze fixed and random effects within the factorial survey method optimally.

Research Area(s)

  • Accountability theory, Awareness of monitoring, Expectation of evaluation, Factorial survey method, Identifiability, Information security policy violations, Mediation, Moderation, Social presence, Unauthorized access, User-interface design

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