A Context-Aware Framework for Modeling ERP Business Process Adaptation Under National Legal Requirements

Shkëlqim Miftari; Azir Aliu; Artan Luma

doi:10.3991/ijim.v20i13.62041

Authors

Shkëlqim Miftari South East European University, Tetovo, North Macedonia https://orcid.org/0009-0004-8299-5925
Azir Aliu South East European University, Tetovo, North Macedonia
Artan Luma South East European University, Tetovo, North Macedonia https://orcid.org/0000-0002-1889-8651

DOI:

https://doi.org/10.3991/ijim.v20i13.62041

Keywords:

adaptive learning, ERP adaptation, legal compliance automation, multilingual NLP, ontology-based reasoning

Abstract

Traditional enterprise resource planning (ERP) systems struggle to adapt to rapidly evolving legal environments because of their static architectures and dependence on manual updates, particularly in developing economies. This study addresses this limitation by proposing a context-aware, artificial intelligence (AI)-driven framework that enables ERP systems to interpret and adapt to evolving legal requirements. The framework integrates ontology-based reasoning, natural language processing (NLP), and adaptive learning to transform legislative changes into machine-interpretable rules and executable process updates, supported by human validation to ensure accuracy and accountability. Designed using a design-oriented research approach, the framework establishes a structured architecture that supports continuous, traceable, and adaptive compliance. The findings demonstrate the framework’s potential to enhance regulatory alignment, improve transparency, and reduce dependence on manual system updates. The study contributes to the development of intelligent and explainable ERP systems capable of sustaining real-time compliance in dynamic regulatory environments.

Author Biographies

Shkëlqim Miftari, South East European University, Tetovo, North Macedonia

Shkëlqim Miftari is a PhD candidate at South East European University specializing in software engineering, enterprise systems, and AI-driven digital solutions. His research focuses on ERP architectures, intelligent business process adaptation, and enterprise digitalization.

Azir Aliu, South East European University, Tetovo, North Macedonia

Azir Aliu is a Full Professor of Computer Science at South East European University. His research interests include artificial intelligence, machine learning, digital transformation, and cloud-based systems. He has extensive academic and institutional experience in digitalization and technology-driven innovation.

Artan Luma, South East European University, Tetovo, North Macedonia

Artan Luma is a Professor of Computer Science at South East European University. His research interests include cryptography, information security, computer security, and system architecture. He has contributed to research projects and academic publications in computer science.

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