傳統的金融機構對於中小企業 (Small and Medium Enterprises, 簡稱SMEs) 面臨Covid-19疫情的大封鎖，以及供應鏈斷鏈造成金融機構違約增加和信貸緊縮相當憂心，再加上新競爭對手Google、Amazon、Alibaba等科技巨獸試圖運用雲端計算、人工智慧和機器學習等金融科技技術搶進原有的供應鏈金融市場，造成傳統的金融機構市場占有率不斷流失。過去的研究主要著重於技術提升，或是偏重在供應鏈效率的優化；有關傳統金融機構如何建構一個決策模型來評估其供應鏈金融的金融科技策略，現有文獻中幾無具體的指導方針。

本研究主要混合了BWM (Best-Worst Method) 和Modified-VIKOR方法來建構「HMCDM決策模型」，它將用來產生傳統金融機構導入供應鏈金融金融科技策略的替代方案優先排序，以提供高階主管進行決策制定。此外，本研究從現有的文獻和實務中總結出五種可行的金融科技策略，並且強調區塊鏈策略的優勢，未來它將逐步發展。

在評估階段，本研究以臺灣一家國內中小企業金融機構作為研究個案。為了避免專家對於測試項目猜測，設計了明確 (Crisp)、模糊 (Fuzzy)、信心加權 (Confidence Weighted) 和信心加權模糊 (Confidence Weighted Fuzzy) 的問卷來進行評估，以提升整體問卷的信效度。

研究結果顯示區塊鏈供應鏈金融的「領導運營商」應是該金融機構的理想選擇。「HMCDM決策模型」還揭示了每個評估因素的重要程度，為金融機構導入金融科技服務提供了全新的想法。這些發現有助於金融機構發展金融科技的供應鏈融資業務，供應鏈的成員也可能受益於縮短貸款的審核時間以加快其營運效率。

Incumbent financial institutions are quite worried about the increase in bank defaults and credit crunch caused by SMEs (Small and Medium Enterprises) facing the blockade of the Covid-19 epidemic and supply chain disruptions, coupled with their competitors Google, Amazon, Alibaba and other tech giants trying to use Fintech such as cloud computing, artificial intelligence and machine learning have entered the original supply chain financial market, causing the market share of Incumbent financial institutions to gradually lose. Past research has mainly focused on technological improvements, or on the optimization of supply chain efficiency; there are few specific guidelines on how incumbent financial institutions can develop a holistic model to evaluate their fintech strategies for supply chain finance.

This study mainly hybrids the BWM (Best-Worst Method) and Modified-VIKOR methods to construct the "HMCDM Decision Model", which will be used to generate the incumbent financial institutions to adpot prioritization of alternatives to supply chain financial Fintech strategies to provide the top managements with decision-making. In addition, this study summarizes five feasible fintech strategies from existing literature and practice, and emphasizes the advantages of blockchain-based strategies, which will be gradually developed in the future.

In the evaluation stage, this study takes a domestic SME financial institution in Taiwan as a case study. In order to avoid experts' guesses, the Crisp, Fuzzy, Confidence Weighted and Confidence Weighted Fuzzy questionnaires were designed for evaluation to improve the reliability and validity of the overall questionnaire.

The findings show that the "leading operator" of blockchain-based supply chain finance should be the ideal choice for the financial institution. The "HMCDM Decision Model" also reveals the importance of each evaluation factor, and provides a new idea for financial institutions to adopt Fintech services. These findings not only help financial institutions to develop Fintech supply chain financing business, but also members of the supply chain may also benefit from shortening loan approval times to speed up their operational efficiency.

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