由決策制定過程瞭解使用者接受社群媒體決策支援系統之研究

A Study of User Acceptance of Social Media Decision Support Systems from the Decision-making Process Perspective

10.3966/207321472020061202001

洪新原(Shin-Yuan Hung)；鍾峰宜(Feng-I Chung)；李承峰(Cheng-Feng Lee)

社群媒體 ； 決策支援系統 ； 使用者接受 ； 解構式計畫行為理論 ； Social Media ； Decision Support Systems ； User Acceptance ； Decomposed TPB

商略學報

12卷2期（2020 / 06 / 01）

89 - 109

繁體中文

在網際網路技術快速發展及WEB2.0概念的帶動下，社群媒體已是提供決策參考的重要傳播媒介與角色。本研究嘗試以解構式計畫行為理論為基礎，建構假設研究模型予以檢測及驗證，解釋使用者透過社群媒體來連結決策支援系統，相較於傳統決策支援系統，更有利於提高決策行為效能之使用模式。本研究透過熱門社群媒體平台進行調查，蒐集421份問卷，有效問卷308份，樣本有效率為73.2%。研究結果顯示，娛樂性並不會影響使用者接受社群媒體決策支援系統的態度，其它外生變數皆會各別影響到態度、主觀規範及認知行為控制，而在計畫行為理論模型的部份則全部顯著，本研究最後針對研究結果，對於社群媒體決策支援系統開發人員、一般使用者、政府方面、社群媒體網站的經營者提出管理實務建議。

Recently, due to the rapid development of WEB2.0, the use of social media is becoming more important for decision makers. The aim of this research is to study the critical factors of user acceptance in the context of social media on Web-based decision support systems. In a combination of social media viewpoint and the consideration of decision support systems advantages, the critical factors that may impact on user acceptance are investigated. In line with the decomposed theory of planned behavior, this study constructs a hypothesized model for testing and verification. A well -designed Web survey was conducted. A total of 421 questionnaires were collected from online platforms such as LinkedIn, Facebook, and forum PPT, generating 308 usable replies with a total response rate of 73.2 percent. The results indicated that playfulness does not significantly affect user attitude toward acceptance of social media decision support system. The critical factors, which affect user attitude, include social interaction, task complexity, perceived risk, trust, and sense of belonging. Additionally, the eWOM, interpersonal influence and external influence that significantly affects subjective norms, and the Self-efficacy and facilitating conditions significantly affect perceived behavioral control and significantly affects user actual use. Through the empirical results, this study provides implications for the system developers, users, government, and the owners of social media decisions support systems.

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