A mathematical framework for assessing food fraud intentions

This work presents a framework for assessing subjects’ intentions to engage in food fraud. The model demonstrated that the decision to commit fraud arises from psychological mechanisms of malicious intent (Π) and ethical fading-bounded ethicality (Ω). Based on these psychological processes, the framework utilises a survey tool to generate finite sets of binary responses, fT (theorised response set derived from governing moral notions) and fA (actual response set given by subjects). The similarity function, fT ϕ fA, maps a dichotomous variable, with arguments (p, q), to a continuous variable, f [(p, q) 7→ f ]. The model metrics have Jaccard index characteristics with a range of 0.0-1.0, where fraud intention is low when f → 0.0 and high when f → 1.0. The number of questions used in a survey indicates special characteristics of the model, for instance, its rate of change (Rf ) and the number of possible response patterns (Γ). Survey data (N=54) was used to validate the model. The results show that the f values for respondents range from 0.21-0.69 with a mean of 0.44. Indicating that the respondents have moderate to neutral inclinations towards fraud. The statistical difference between f -values obtained from Π and Ω data indicates that they have the same effect on food fraud intention (p > 0.05). The model is essential when assessing the fraud intention of an individual or population by examining and understanding factors contributing to fraud and their numerical impacts. This is a significant step towards developing a fraud prevention framework.

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Publication Details

Journal
African Scientific Reports
Published
2025-10-18
DOI
https://doi.org/10.46481/asr.2025.4.3.314
Primary Topic
Identification and Quantification in Food
Type
article
Field-Weighted Citation Impact
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article

A mathematical framework for assessing food fraud intentions

Shadreck Muyambo, Jack Urombo, Garry K. Masoha, Livingstone Jenya
African Scientific Reports
Identification and Quantification in Food
article

A mathematical framework for assessing food fraud intentions

Shadreck Muyambo, Jack Urombo, Garry K. Masoha, Livingstone Jenya
article en

Abstract

This work presents a framework for assessing subjects’ intentions to engage in food fraud. The model demonstrated that the decision to commit fraud arises from psychological mechanisms of malicious intent (Π) and ethical fading-bounded ethicality (Ω). Based on these psychological processes, the framework utilises a survey tool to generate finite sets of binary responses, fT (theorised response set derived from governing moral notions) and fA (actual response set given by subjects). The similarity function, fT ϕ fA, maps a dichotomous variable, with arguments (p, q), to a continuous variable, f [(p, q) 7→ f ]. The model metrics have Jaccard index characteristics with a range of 0.0-1.0, where fraud intention is low when f → 0.0 and high when f → 1.0. The number of questions used in a survey indicates special characteristics of the model, for instance, its rate of change (Rf ) and the number of possible response patterns (Γ). Survey data (N=54) was used to validate the model. The results show that the f values for respondents range from 0.21-0.69 with a mean of 0.44. Indicating that the respondents have moderate to neutral inclinations towards fraud. The statistical difference between f -values obtained from Π and Ω data indicates that they have the same effect on food fraud intention (p > 0.05). The model is essential when assessing the fraud intention of an individual or population by examining and understanding factors contributing to fraud and their numerical impacts. This is a significant step towards developing a fraud prevention framework.

African Scientific Reports
Harare Institute of Technology (ZW), Scientific and Industrial Research and Development Centre (ZW)
Openalex Percentile: Top 74%
Identification and Quantification in Food
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A mathematical framework for assessing food fraud intentions — Shadreck Muyambo, Jack Urombo, et al. · African Scientific Reports (2025) | TGRS Research Map | TGRS