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Title: Examining the lean management approach to counter fraud : a case study of the way a lean retail organisation manages incidents of fraudulent refund claims
Author: Dibia, Princely Chinwendu
ISNI:       0000 0004 8508 0491
Awarding Body: University of Portsmouth
Current Institution: University of Portsmouth
Date of Award: 2019
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This study investigates the extent to which lean management (LM) counters fraud. It is an exploratory study motivated by reports of fraud towards LM organisations, especially fraudulent refund claims by customers in lean retail organisations. There is very little academic research that investigates the fraud risks and potential flaws of LM. This is despite claims that lean thinking organisations rely on LM systems to counter fraud. Through a realist case study, this study collects and analyses empirical data on the way one LM retail organisation in the UK counters its problem of fraudulent refund claims from customers and the rationale behind their approach. The data were collected via a pilot study walk-through and observation, and then via semi-structured interviews with staff in four of the organisation’s retail stores. These data were thematically analysed. The findings indicate that the prioritisation and focus on meeting and satisfying customers’ demands can often imply a compromise in countering fraud. This study argues that LM thinking would be more complete, and management control systems more robust, if advisors and managers took into greater account the possibility of fraud by employees or customers. The problem lies in the concept of LM as a socio-technical system. Whilst the technical aspects such as visual communications and JIT are widely discussed and implemented, there appears to be a rather idealistic conception of necessarily satisfied employees and customers. However, managers and customers have been shown to exhibit negative behaviours that are inconsistent with LM thinking, including lying, theft and fraud. This has implications in terms of losses of products, time and money that may erode the cost benefits that might be expected from the implementation of LM practices.
Supervisor: Jack, Lisa Janet ; Alberti, Federica ; Graham, Alan William Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available