A Decision Support Framework for Blockchain Pattern Selection Based on Soft Goals

• URL: http://arxiv.org/abs/2512.13239v1
• Date: Mon, 15 Dec 2025 11:54:00 GMT
• Title: A Decision Support Framework for Blockchain Pattern Selection Based on Soft Goals
• Authors: Eddy Kiomba Kambilo, Nicolas Herbaut, Irina Rychkova, Carine Souveyet,
• Abstract summary: We propose a decision support framework that combines business patterns and domain-independent soft goals with a multi-criteria decision-making approach.<n>By iteratively capturing and refining preferences, BC-TEAEM supports systematic selection of blockchain patterns.<n>We develop a prototype decision support tool implementing our method and validate it through a case study of a pharmaceutical company's supply chain traceability system.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Blockchain technology is gaining momentum across many sectors. Whereas blockchain solutions have important positive effects on the business domain, they also introduce constraints and may cause delayed or unforeseen negative effects, undermining business strategies. The diversity of blockchain patterns and lack of standardized frameworks linking business goals to technical design decisions make pattern selection a complex task for system architects. To address this challenge, we propose Blockchain--Technology-Aware Enterprise Modeling (BC-TEAEM), a decision support framework that combines ontologies of blockchain patterns and domain-independent soft goals with a multi-criteria decision-making approach. The framework focuses on the interplay between a domain expert and a technical expert to ensure alignment and traceability. By iteratively capturing and refining preferences, BC-TEAEM supports systematic selection of blockchain patterns. We develop a prototype decision support tool implementing our method and validate it through a case study of a pharmaceutical company's supply chain traceability system, demonstrating the framework's applicability. %a supply chain traceability case study.

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