A structural and semantic approach to similarity measurement of logistics processes

Abstract

Abstract: The increased individuation and variety of logistics processes has spurred a strong demand for a new process customization strategy. Indeed, to satisfy the increasingly specific requirements and demands of customers, organizations have been developing more competitive and flexible logistics processes. This trend not only has greatly increased the number of logistics processes in process repositories but also has resulted processes for business decision making hard. Organizations, therefore, have turned to process reusability as a solution. One such strategy employs similarity measurement as a precautionary measure limiting the occurrence of redundant processes. This paper proposes a structure-and semantics-based approach to similarity measurement of logistics processes. Semantic information and semantic similarity on logistics processes are defined based on logistics ontology, available in the supply chain operation reference (SCOR) model. By combining similarity measurement based on both structural and semantic information of logistics processes we show that our approach improves the previous approaches in terms of accuracy and quality.