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  2. 海運暨管理學院
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Please use this identifier to cite or link to this item: http://scholars.ntou.edu.tw/handle/123456789/26769
DC FieldValueLanguage
dc.contributor.authorChou, Kuan Chengen_US
dc.contributor.authorLee, Chiehen_US
dc.contributor.authorPerdana, Shania Andeaen_US
dc.contributor.authorTu, Mengruen_US
dc.date.accessioned2026-08-10T03:12:11Z-
dc.date.available2026-08-10T03:12:11Z-
dc.date.issued2026/6/3-
dc.identifier.issn1751-7575-
dc.identifier.urihttp://scholars.ntou.edu.tw/handle/123456789/26769-
dc.description.abstractSmall and medium enterprises (SMEs) are increasingly relying on digital technology to enhance production efficiency. For SMEs in the manufacturing industry, orders typically include the buyer's input information. As SMEs lack the capacity to enforce information consistency, input data are presented in buyer-specific input information, leading to duplicate records, data inconsistencies, and substantial manual intervention. To address this problem, this study adopts the Action Design Research (ADR) approach to design an artefact that embeds an artificial intelligence (AI)-based model in a blockchain, named Engineering-Aware and Standardisation-Integrated Entity Recognition (EASIER). Such an artefact is designed to automatically read and transform input data into the SME's own standardised format and generate data entries in their manufacturing system. We develop and evaluate the proposed artefact using a real SME's BOM dataset, and our results demonstrate that it achieves 99.77% in both accuracy and an F1-score on the final test set. For SMEs, the proposed method can significantly reduce manual intervention effort and improve input data consistency. This study contributes to both theory and practice by demonstrating how AI-enabled standardisation artefacts, supported by blockchain-based governance mechanisms, can be designed with SMEs to deliver practical, resource-efficient digital transformation solutions.en_US
dc.language.isoEnglishen_US
dc.publisherTAYLOR & FRANCIS LTDen_US
dc.relation.ispartofENTERPRISE INFORMATION SYSTEMSen_US
dc.subjectNatural language processingen_US
dc.subjectbill of materials (BOMs) recordsen_US
dc.subjectaction design researchen_US
dc.subjectDistilBERTen_US
dc.subjectblockchainen_US
dc.subjectdata managementen_US
dc.titleEASIER: a blockchain-based artificial intelligence support system for small and medium enterprisesen_US
dc.typejournal articleen_US
dc.identifier.doi10.1080/17517575.2026.2686966-
dc.identifier.isiWOS:001801021600001-
dc.relation.journalvolume20en_US
dc.relation.journalissue5��6��en_US
dc.relation.pages22en_US
dc.identifier.eissn1751-7583-
item.cerifentitytypePublications-
item.languageiso639-1English-
item.openairetypejournal article-
item.grantfulltextnone-
item.fulltextno fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
crisitem.author.deptCollege of Maritime Science and Management-
crisitem.author.deptDepartment of Transportation Science-
crisitem.author.deptNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgCollege of Maritime Science and Management-
Appears in Collections:運輸科學系
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