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The Application of Role-Based Framework in Preventing Internal Identity Theft Related Crimes: A Qualitative Case Study of UK Retail Companies

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  • Romanus Izuchukwu Okeke

    (Cardiff Metropolitan University)

  • Max Hashem Eiza

    (Liverpool John Moores University)

Abstract

This paper aims to examine the challenges of preventing internal identity theft related crimes (IIDTRC) in the UK retail sector. Using an in-depth multiple case studies of a selected number of cross-functional management teams in the UK retail companies, management roles were analysed. We used semi-structured interview as a qualitative data collection technique and used Nvivo aided thematic analysis and interpretivism underpinned by Role-Based Framework (RBF) for analysis. Our findings revealed that vagueness of roles and lack of clarity in sharing data security responsibilities are the major challenges of preventing IIDTRC in UK retail companies. We suggest an application of RBF which provides a conceptual analysis for cross-functional management team to address the challenges of preventing IIDTRC. RBF enables clarity of shared roles where both information security and crimes prevention teams work in unison is required to prevent IIDTRC to maximise internal data security. Contributions for policymakers are offered in this paper.

Suggested Citation

  • Romanus Izuchukwu Okeke & Max Hashem Eiza, 2023. "The Application of Role-Based Framework in Preventing Internal Identity Theft Related Crimes: A Qualitative Case Study of UK Retail Companies," Information Systems Frontiers, Springer, vol. 25(2), pages 451-472, April.
    • Handle: RePEc:spr:infosf:v:25:y:2023:i:2:d:10.1007_s10796-022-10326-w
    DOI: 10.1007/s10796-022-10326-w
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    References listed on IDEAS

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    Cited by:

    1. Sagar Samtani & Ziming Zhao & Ram Krishnan, 2023. "Secure Knowledge Management and Cybersecurity in the Era of Artificial Intelligence," Information Systems Frontiers, Springer, vol. 25(2), pages 425-429, April.

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