本研究主要探討Netflix影音平台的使用者在Netflix禁止共享帳號的新政策下的影音觀看習慣與訂閱方案選擇，並探究何種因素會影響Netflix影音串流平台的使用者滿意度和持續使用意圖，而在目前的OTT使用者的研究中，較少有以心流的三階段模型探討使用者行為意向之研究，此外亦較少有探討OTT使用者知覺風險之相關研究，因此本研究以科技接受模型為基礎，結合心流的三階段模型與資訊系統持續使用模式，對Netflix的資訊品質、系統品質、服務品質、感知易用性、感知有用性、心流體驗、價格認知、知覺風險對使用者滿意度和持續使用意向之影響進行評估。本研究採用問卷調查法，總共收到 352份問卷回覆，扣除受訪者之無效樣本 41 份，有效樣本總數為 301份。本研究結果證實 Netflix的資訊品質和系統品質會正向影響用戶的感知有用性和感知易用性，而服務品質則不具有顯著的影響效果。而在本研究中作為影響心流的主要前提因素的感知易用性和感知有用性等構面，亦證實會對使用者的心流有顯著的正向影響，而使用者的心流亦會對其滿意度有正向影響進而影響其持續使用意向，所以Netflix等影音平台業者可以著重在如何提升用戶觀看的心流體驗方面進行更多的開發與研究，例如提高觀看畫質、增加影片的類型與豐富程度等，以提升用戶的滿意度與持續使用意向。此外，本研究亦證實用戶的知覺風險對於用戶的滿意度具有負向的影響效果，因此Netflix等影音平台業者應思考如何降低用戶的知覺風險，進而提升用戶的滿意度。對於過往的以科技接受模式探討線上影音平台使用者的研究中，本研究提供了一個更完整的研究架構，結合心流的三階段理論模型與資訊系統成功模式的品質變數，從另一個角度探討線上影音平台使用者的滿意度與持續使用意向，期望本研究模型能對後續在此方面的研究者與研究能具有啟發意義與貢獻。

This study primarily examines the viewing and subscription behavior of Netflix users under the Netflix's new policy of prohibiting user sharing accounts. The study also investigates the factors influencing user satisfaction and intention to continue using the Netflix platform. Among the current studies of OTT users, few studies have explored the three-stage model of flow on user behavioral intention. This study confirmed that Netflix's information quality and system quality will positively affect users' perceived usefulness and perceived ease of use, while service quality has no significant impact users' perceived usefulness and perceived ease of use. In this study, research variables such as perceived ease of use and perceived usefulness, which are the main antecedent factors affecting flow, have also been confirmed to have a significant positive impact on the user's flow, and the user's flow will also conduct a positive impact on their satisfaction, which in turn affects their continuance intention. Therefore, OTT companies such as Netflix can focus on how to improve users’ flow experience, such as improving viewing quality and increasing video types and richness in order to improve users’ satisfaction and continuance intention.
In addition, this study also confirms that users' perceived risk has a negative impact on user satisfaction. Therefore, OTT companies such as Netflix should consider how to reduce users' perceived risk and improve users’ satisfaction. Compared with previous studies that used technology acceptance models to explore OTT users’ behavior, this study provides a more complete research framework, combining the three-stage flow model and the quality variables of information system success models, exploring the satisfaction and continuance intention of OTT users from another perspective. We hoped that the proposed model in this study can make the research studies of OTT users' behavior more completed, and can be inspiring and contributing to future researchers and studies in this field.

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