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題名：結構方程模式於社會行為科學之應用
作者：鄭青展 引用關係
作者(外文)：Ching-Chan Cheng
校院名稱：中華大學
系所名稱：科技管理學系(所)
指導教授：蔡明春
學位類別：博士
出版日期：2008
主題關鍵詞：社會行為科學；結構方程模式；互動電視；線上遊戲成癮；social behavior sciences；structural equation modeling；nteractive television；online-game addiction
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過去探討社會行為科學研究中，常利用相關分析、線性迴歸模式或多層級線性模式進行分析，但這些方法僅能探討一組自變項對一個依變項的影響關係，且研究變項必須為可直接衡量的觀察變項。在此條件限制下，造成部份社會行為科學之研究無法有效且具體的驗證。然而，結構方程模式(SEM)是結合路徑分析與因素分析的一種多變量分析方法，可處理潛在變項之間的因果關係，使社會科學中的許多行為理論皆能夠獲得驗證。雖然SEM在社會行為科學領域中已被廣泛的應用，但目前對於SEM之觀念與相關應用一體系的探討與介紹仍付之闕如。因此，本研究將針對SEM之觀念、方法與相關應用研究進行系統化的整合與歸納，並提出實例說明，以作為未來研究者在應用SEM探討社會行為科學議題之參考。
本研究彙整過去相關研究，於結論中提出SEM之使用程序與操作建議，並根據互動電視潛在消費者行為與線上遊戲行為等兩篇實例分析結果得知，SEM確實能有效驗證社會行為科學模式，且能詳細地將模式中各變數間的路徑關係予以呈現，研究者可根據分析之結果，提出相關決策因應。而目前在行銷管理、人力資源管理與組織行為、心理學及教育行為等議題研究，SEM的應用皆獲得良好的實證結果。最後，其他社會行為科學之相關議題亦可建議利用SEM或結合其他統計技術來進行實證研究，甚至將過去實務上重要且尚未被可驗證的相關影響變數納入分析，以提升整體行為模式的解釋能力，讓社會行為科學之研究能獲得更詳盡的驗證。
Among the previous studies and researches on social behavior sciences, most of then were frequently made of the correlation analysis, linear regression model, or hierarchical linear modeling to conduct the analysis; however, those methods were only able to explore the correlation between a set of independent variables to a dependent variable, and the researching variable should be the observed variables that could be directly measured. Under the limit of such condition, it has made the researches on social behavior sciences to unable ineffectively and specifically be verified. However, the structural equation modeling (SEM) is one of the Multivariate Analysis which has not only combined the path analysis with factor analysis, but also be able to deal with the casual relationship between latent variables; as a result, it could possibly make many behavioral theories of the social sciences to be verified. Although SEM has been comprehensively applied in the field of social behavior sciences, the exploration and introduction of the system for the concept and related application of SEM are still insufficient. Therefore, this study is focused on the concept, method and related application of such research to process the systematized integration and generalization, as well as proposed the explanation with some actual examples as the reference for the follow-up researchers to apply SEM to explore the issues that related to social behavior sciences.
This study has collected and compiled many previous related researches, and proposed the using procedures and suggestions of SEM in the section of conclusion. In addition, according to the result of the analysis of two actual examples on the behavior of potential consumers of interactive television and the online-game addiction of university students, SEM not only has specific models to effectively verify the social behavior sciences, but it also able to particularly express the path relationship between variables of models. Follow-up researchers can adopt the results of those aforesaid analyses to propose related decisions to make proper responses. At present, among those researches on the issues about the marketing management, human resource management and organizational behavior, psychology and educational behavior, etc., all applications of SEM have acquired good empirical results. In conclusion, it has also suggested using SEM or combining other statistic technologies to conduct the empirical researches on other issues that related to social behavior sciences; moreover, adopt those correlative variables into the process of analysis that have not yet been verified but very important to the empirical practice previously to upgrade the explanatory capability of the entire behavioral model, and obtain more explicit verification for those researches on social behavior sciences.
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