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dc.contributor.authorLu, Ming-Tsangen_US
dc.contributor.authorLin, Shi-Woeien_US
dc.contributor.authorTzeng, Gwo-Hshiungen_US
dc.date.accessioned2014-12-08T15:34:05Z-
dc.date.available2014-12-08T15:34:05Z-
dc.date.issued2013-12-01en_US
dc.identifier.issn0167-9236en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.dss.2013.06.006en_US
dc.identifier.urihttp://hdl.handle.net/11536/23428-
dc.description.abstractThe use of radio frequency identification (RFID) technology has progressed tremendously in recent years. In the healthcare industry, the decision to adopt RFID technology is a problem requiring a multi-criteria decision analysis that involves both qualitative and quantitative factors. The evaluation of this decision may be based on imprecise information or uncertain data. Furthermore, there can be significant dependence and feedbacks between the different criteria and alternatives. However, most conventional decision models cannot capture these complex interrelationships. As a result, in this study we develop a general evaluation framework for industry evaluation, improvement and adoption of RFID. We use a hybrid Multiple Criteria Decision Making (MCDM) method known as DDANPV that combines DEMATEL (decision making trial and evaluation laboratory), DANP (DEMATEL-based ANP), and VIKOR to evaluate the factors that influence the adoption of RFID. Specifically, we study the adoption of RFID in Taiwan's healthcare industry. We find that technology integration is the most influential criterion and the strongest driver in the adoption of RFID of Taiwan's healthcare industry. (C) 2013 Elsevier B.V. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectHealthcare industryen_US
dc.subjectRadio frequency identification (RFID)en_US
dc.subjectDecision making trial and evaluation laboratory (DEMATEL)en_US
dc.subjectDANP (DEMATEL-based ANP)en_US
dc.subjectMultiple criteria decision making (MCDM)en_US
dc.subjectVIKORen_US
dc.titleImproving RFID adoption in Taiwan's healthcare industry based on a DEMATEL technique with a hybrid MCDM modelen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.dss.2013.06.006en_US
dc.identifier.journalDECISION SUPPORT SYSTEMSen_US
dc.citation.volume56en_US
dc.citation.issueen_US
dc.citation.spage259en_US
dc.citation.epage269en_US
dc.contributor.department管理科學系zh_TW
dc.contributor.departmentDepartment of Management Scienceen_US
dc.identifier.wosnumberWOS:000329005000026-
dc.citation.woscount10-
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