新冠疫情延續多年並多次變異，使防疫資訊的有效獲取與應用成為影響防疫成效的核心課題。基於任務科技配適理論，本研究探討防疫任務與疫情資訊系統的契合程度，並檢驗不同決策型態在配適度與使用績效間的調節效果。研究透過網路問卷調查曾使用疫情資訊系統的民眾，共回收408份有效樣本。分析結果顯示，疫情嚴重性認知對配適度無顯著影響；然而，有效性認知、系統公信力與資料整合能力皆能正向提升配適度。進一步發現，分析型決策型態加強了配適度與績效間的正向關係，而直覺型決策型態則削弱此關係。研究據此建議，應著重提升系統可信度與資料整合功能，並引導使用者採取分析導向思維，以強化疫情資訊的應用價值與防疫成果。

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The COVID-19 pandemic, characterized by its prolonged duration and recurrent mutations, has underscored the critical role of acquiring and applying epidemic-related information in enhancing prevention effectiveness. Drawing on Task-Technology Fit (TTF) theory, this study explores the relationship between epidemic prevention tasks and the use of epidemic information systems, while further examining the moderating influence of decision styles. Data were collected through an online survey of individuals with experience using epidemic information systems, yielding 408 valid responses. The findings indicate that perceived severity does not significantly influence TTF, whereas perceived benefits, system credibility, and information integration exert positive effects. Moreover, an analytical decision style strengthens the relationship between TTF and performance, while an intuitive decision style weakens it. These results highlight the importance of enhancing system credibility and information integration, as well as guiding users toward an analytical decision style, in order to optimize the utilization of epidemic information and ultimately improve prevention outcomes.

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