A STRUCTURAL AND SEMANTIC APPROACH TO SIMILARITY MEASUREMENT OF LOGISTICS PROCESSES
Cited 0 times inCited 0 times in
- A STRUCTURAL AND SEMANTIC APPROACH TO SIMILARITY MEASUREMENT OF LOGISTICS PROCESSES
- Yahya, Bernardo Nugroho; Bae, Hyerim; Bae, Joonsoo
- Business Process; Logistics process; Precautionary measures; Process customizations; SCOR; Semantic information; Similarity measurements; Supply chain operation references
- Issue Date
- UNIV CINCINNATI INDUSTRIAL ENGINEERING
- INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE, v.20, no.1-2, pp.47 - 59
- 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.
Appears in Collections:
- SBA_Journal Papers
- Files in This Item:
- There are no files associated with this item.
can give you direct access to the published full text of this article. (UNISTARs only)
Show full item record
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.