以隱私計算模型探討使用者於餐飲外送平台中自我揭露之因素

餐飲外送平台產業近年來發展迅速，加上2019新冠肺炎疫情影響，民眾減少外出與人群接觸的頻率，使餐飲外送風氣更加盛行。在使用餐飲外送平台的過程中，常會牽涉到個人隱私資訊交換議題，因此，本研究由個人隱私議題的角度出發，以隱私計算模型（Privacy Calculus Model）作為研究架構基礎，探討使用者於餐飲外送平台中自我揭露之因素，並得出以下結果： 1.折價券效果與知覺利益之間具有正向關係 2.個人化程度同時與知覺利益和知覺風險之間具有正向關係，亦即個人化會同時產生使用者自我揭露的好處和壞處，故增加個人化功能需要考慮的因素會較其他面向更為複雜 3.信任與知覺風險間具有負向關係 4.隱私顧慮與知覺風險間具有正向關係 5.認知需求會在知覺利益與自我揭露意願的正向關係中產生負向的調節效果，即使用者的認知需求愈高，其知覺利益與自我揭露意願的正向關係愈弱

關鍵字

餐飲外送平台；隱私計算模型；自我揭露；認知需求

並列摘要

Food ordering and delivery platform services have grown rapidly in recent years. Due to the impact of COVID-19, people reduced the frequency of going out and contacting with each other, and this made food delivery services more popular. In the process of using food ordering and delivery platform, personal privacy information exchange issues are often involved. Therefore, this study started with the perspective of personal privacy issues and used Privacy Calculus Model as the research framework to discuss users’ intention to disclose personal information via food ordering and delivery platform. The main conclusions are as following: 1.The effect of discount coupons is positive related to perceived benefits. 2.Personalization is positive related to perceived benefits and perceived risks. This implies that more factors should be considered when adding personalization functions. 3.Trust is negative related to perceived risks. 4.Privacy concern is positive related to perceived risks. 5.Need for cognition has a negative moderation effect on the relationship between perceived benefits and intention to disclose personal information.