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Identity fraud is a growing issue for online retail organisations. The literature on this issue is scattered, and none of the studies presents a holistic view of identity fraud management practices in the online retail context. Therefore, the purpose of this paper is to investigate the identity fraud management practices and present a comprehensive set of practices for e-tail sector.

A systematic literature review approach was adopted, and the articles were selected through pre-set inclusion criteria. The authors synthesised existing literature to investigate identity fraud management in e-tail sector.

The research finds that literature on practices for identity fraud management is scattered. The findings also reveal that firms assume identity fraud issues as a technological challenge, which is one of the major reasons for a gap in effective management of identity frauds. This research suggests e-tailers to deal this issue as a management challenge and counter strategies should be developed in technological, human and organisational aspects.

This study is limited to the published sources of data. Studies, based on empirical data, will be helpful to support the argument of this study; additionally, future studies are recommended to include a wide number of databases.

This research will help e-tail organisations to understand the whole of identity fraud management and help them develop and implement a comprehensive set of practices at each stage, for effective management identity frauds.

This research makes unique contributions by synthesising existing literature at each stage of fraud management and encompasses social, organisational and technological aspects. It will also help academicians understanding a holistic view of available research and opens new lines for future research.

This paper seeks to evaluate the adoption of enterprise application integration (EAI) in healthcare organisations. In doing so, fuzzy cognitive mapping (FCM) simulation is used to demonstrate the causal inter‐relationships between the EAI adoption factors.

Several factors were analysed and tested through case study strategy that supports the adoption of EAI in healthcare organisations. Using the concepts of these factors, the paper further expanded the scope of the research by exploring the area of EAI by using the FCM simulation. The computation of the node's output is based on the combination of a summing operation followed by the use of a non‐linear transformation such as threshold function.

The research findings demonstrate the application of FCM simulation that identifies casual inter‐relationships among EAI adoption factors. This enhances the quality of the evaluation process, and highlights the importance of each factor and its inter‐relationship with other factors.

This evaluation can be used as a decision‐making tool to support the management of the healthcare organisations when taking the decision regarding the adoption of EAI. In doing so, healthcare organisations may benefit from this evaluation process.

The advantages of using FCM within this study fall into two categories. One is concerned with the technique, which offers structure through symbolic and graphical representation rather than linear layout. The second is concerned with the use of results, which offers a graphical picture of rates' understanding of appraisal decisions; information obtained is clearly communicable, and insight can be gained into the structure of information.