When fraud becomes routine fuels exhaustion, while professional skepticism counters ethical fatigue
Adeel Qaiser & Professor Dr. Alia Ahmed
What the paper says
Purpose This research aims to investigate how routine corruption leads to fraud exhaustion among practicing accountants in the industrial segment, incorporating fraud rationalization, its motives and professional skepticism within the Theory of Corruption Normalization. Design/methodology/approach Data collected through a survey from practicing accountants in organizational settings were analyzed utilizing regression, bootstrapped mediation and moderation to examine direct, indirect and provisional influences concerning normalization, rationalization, motives, exhaustion and skepticism dimensions. Findings Corruption normalization has a direct and indirect impact on accountants’ fraud exhaustion, intensifying fraud motives. Fraud rationalization likewise leads to exhaustion, both partially mediated by motives. Professional skepticism through suspension of judgment and questioning mind moderates these relationships, weakening relations to motives and exhaustion. Therefore, normalized corruption sustains fraudulent routines while encouraging psychological exhaustion. Practical implications Organizations must encourage professional skepticism by training, strengthen principally ethical leadership and reinforce accountability structure to interrupt normalization, diminish fraudulent motives and lessen exhaustion, thus augmenting fraud prevention and accountant well-being. Originality/value This research extends the corruption normalization theory by uncovering its psychological impacts, introducing fraud exhaustion as a key result – and emphasizing professional skepticism as a vital moderator that limits motivational escalation and ethical fatigue in corrupt environments.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.