An Integrated Model for Fraud Prevention Management in E-Retail
: A Case for a Big Data-Enabled Approach

  • Chiwuokem Nwoko

Student thesis: Doctoral ThesisDoctor of Philosophy


Although big data and fraud prevention have been the focus of considerable attention in research, the literature rarely acknowledges the need to evaluate how big data facilitates fraud prevention in e-retail. The evidence from existing literature suggests that there is no study on the development of clear theoretical frameworks that can be used to evaluate how big data facilitates e-retail fraud prevention. This study addresses this gap by building an integrated big data-enabled fraud prevention (IBDEFP) model that can evaluate how big data facilitates fraud prevention in e-retail, i.e., how e-retail fraud prevention can be derived from big data resources and capabilities. The model combines and extends the Practice-Based View (PBV) and the Balanced Control Theory (BCT) in a way that has not been previously done.
The study aims to critically assess how big data facilitates e-retail fraud prevention practices and controls and the theoretical and practical implications of a big data-driven approach to e-retail fraud prevention. Data was collected through semi-structured interviews with 32 expert participants dealing substantially with data in 18 e-retail firms. Combining the PBV and BCT theoretical concepts provides a novel explanatory framework that captures the causal relationship between big data resources and capabilities in e-retail, big data facilitated fraud prevention practices and controls, and their benefit dimensions.
The IBDEFP presents important and novel theoretical contributions to the field of e-retail fraud prevention management at a time when e-retail firms are faced with increasing digital fraud attacks. The IBDEFP can help fraud prevention researchers and practitioners evaluate and understand how e-retailers can create or redesign effective organisational fraud prevention processes and operations or practices by leveraging big data facilitated capabilities, and how e-retailers redesign key processes or practices and redefine corporate scope for fraud prevention from big data facilitated capabilities and insights.
Integrating the PBV and BCT provides a novel theoretical improvement that reveals understudied factors affecting the use of big data for e-retail fraud prevention. For instance, a key finding suggests that there is limited use of big data-facilitated insights for fraud awareness, training and educational programmes in e-retail. The IBDEFP presents a utility of the theoretical contribution of the study as the study explains how concepts are implemented in e-retail firms. this contribution derived from integrating and extending the PBV and BCT aligns with the position of existing literature which suggests that there is a strong correlation between the use of big data-facilitated management practices and firm performance.
Date of AwardMar 2023
Original languageEnglish
Awarding Institution
  • Coventry University
SupervisorMaureen Meadows (Supervisor) & Alexeis Garcia-Perez (Supervisor)

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