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dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.contributor.advisorLaw, Wing-cheung (ISE)en_US
dc.contributor.advisorChoy, King Lun (ISE)en_US
dc.creatorPun, Kim Ping-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/12010-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic Universityen_US
dc.rightsAll rights reserveden_US
dc.titleHybrid-fuzzy multi-criteria decision supporting model for vendor evaluation process to building facility maintenance and renovation in Hong Kongen_US
dcterms.abstractBuilding facilities management, repairs, maintenance, alterations and additions play a vital role in the sustainable development of buildings, covering safety, technical, economic and environmental aspects. At the same time, procurement is a critical process in identifying the best-value vendors, improving resource allocation efficiency, maintaining equipment reliability and availability, and thus enhancing facility conditions, thereby reducing business risk, attracting tenants, increasing assets and creating value. Therefore, the payback and return on investment (ROI) can be incredibly beneficial by enabling relevant decisions to achieve their strategic goals in a cost-effective, efficient and effective manner. Even though technological advancements have been considered to simplify internal processes by digitizing the transfer of information into a digital format, the procurement process is still managed manually without any decision support system. Maintenance knowledge and expertise are usually very subjective in the current process, and traditional methods are insufficient to systematically interpret judgment and evaluation criteria. In addition, decision-making in most organizations today is still in a centralized direction.en_US
dcterms.abstractIn many cases, decisions made "at the top" cascade down the organizational chart, and frontline employees are expected to execute those orders neatly. Group decision support is less explored in the supplier and contractor selection literature despite its benefits. It leads to the lack of validation of the importance and applicability level of criteria and sub-criteria faced by frontline maintenance personnel even though they have a lot of understanding of the products, processes, machines, customers and clients in real-life applications. Additionally, there is a lack of quantitative measures to incorporate linguistic selection criteria for maintenance personnel and domain experts into the decision-making process to improve the current supply base's competitive advantage, competitiveness, and capability assessment. Quantitative and qualitative multi-criteria analysis and associated performance feedback also lack decision-making to support a strategic approach.en_US
dcterms.abstractTherefore, in this study, a hybrid fuzzy multi-criteria decision support model (HFMCDSM) is developed for the vendor selection process by integrating Fuzzy Set Theory, Analytic Hierarchy Process (AHP) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) to provide decision support under a consensus approach. The model can provide a framework to capture the uncertainty and imprecision associated with human cognitive processes, such as inherent knowledge, experience, and reasoning.en_US
dcterms.abstractA case study was conducted showing how (i) Aggregated decision preferences can be applied at different levels of stakeholders to set criteria weights and (ii) Incorporate expert and management decisions into the procurement process for contract award analysis, and (iii) Make reliable decisions using objective tools to identify the best-value vendors to improve analytical performance. This approach enables establishing a value-driven procurement strategy rather than the traditional lowest price selection strategy. Purchasing personnel can develop adaptation plans based on the recommended results.en_US
dcterms.extentxiv, 170 pages : color illustrationsen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2022en_US
dcterms.educationalLevelEng.D.en_US
dcterms.educationalLevelAll Doctorateen_US
dcterms.LCSHDecision support systemsen_US
dcterms.LCSHFacility management -- China -- Hong Kongen_US
dcterms.LCSHBuilding management -- China -- Hong Kongen_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsrestricted accessen_US

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/12010