Computational analysis demonstrates faster stabilization of corruption models, suggesting effective intervention strategies.
Corruption behaves like a social contagion that evolves through interaction, influence, and institutional memory. To capture this complexity, we develop a deterministic corruption‐transmission model governed by a piecewise fractional framework that combines the Caputo and modified Atangana–Baleanu–Caputo (mABC) derivatives. This dual‐operator structure describes both short‐term and long‐term memory effects within a unified formulation. Analytical results confirm the existence and stability of solutions, while numerical experiments reveal faster stabilization and smoother convergence compared with classical and single‐fractional models. The findings demonstrate that the proposed piecewise mABC framework offers a realistic and flexible mathematical tool for predicting corruption behavior and designing effective intervention strategies.
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Rahman et al. (2026) studied this question.
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