本研究使用模糊多準則決策(Multiple Criteria Decision Making; MCDM)，分析台灣銀行業在招募企業金融部門客戶關係經理人時，利用人工智慧(AI)職缺推薦系統提升媒合效率的主要影響因素。本研究之專家問卷以台灣企業金融業務排名前20家銀行的專家為對象。根據相關文獻與專家建議，建構四個主構面(履歷、媒合條件、軟體即服務及平台即服務)和十五個準則。先採用DEMATEL分析主構面之間的因果關係和自我影響效果，再利用模糊網路層級分析法(fuzzy ANP ; FANP)分別對主構面和準則進行重要性排名。實證結果顯示軟體即服務(SaaS)為企業最重視的主構面，履歷次之；排名前五的準則依序為「經歷」、「數位化程度」、「介面與資料庫系統」、「薪酬福利」和「AI API系統」。最後，VIKOR和TOPSIS的結果呈現自身「採用雲端平台服務」為優先策略方案，「強化企業AI能力」次之，而「外包AI 服務廠商」最不被青睞。

This study adopts the hybrid fuzzy multi-criteria decision-making (MCDM) method to analyze the determinant factors that affect the efficiency of the AI job openings recommendation system in matching talents for the position of relationship manager in the corporate finance departments in the Taiwan banking sector. Experts from the top twenty banks in the corporate finance business in Taiwan were interviewed. Based on a literature review and given the current situation in the industry, this study proposes an evaluation model with four dimensions (Resume, Job Attributes, Software-as-a-Service, and Platform-as-a-Service) and fifteen criteria. The DEMATEL method was employed to analyze the cause-effect relationships and self-correlation of the dimensions, and fuzzy ANP was utilized to compute the weights of the dimensions and criteria to obtain their order of importance. The empirical results indicated that Software-as-a-Service (SaaS) was the most important dimension, and that Resume was ranked second. The top five important criteria were “Experience,” “Digitalization,” “UI & Database,” “Compensation” and “AI API.” By applying the VIKOR and TOPSIS methods to rank the three alternatives, the results revealed that “Adopt Cloud Platform Services” was the priority strategy for banks, followed by “Strengthen the AI Ability of the Enterprise,” with “Outsource AI Service Vendors” being ranked last.

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