基於決策實驗室之網路流程法預測科技產品接受模式

Predictions of the Acceptance Model of Technology Products by Using the DEMATEL based Network Process

林怡凡

指導教授 ： 黃啟祐

國立臺灣師範大學/科技學院/工業科技教育學系/碩士(2011年)

摘要

智慧型手機近年來於市場中嶄露頭角，並躍升為最受歡迎的消費電子產品之一，因此，分析和預測消費者對智慧型手機的購買行為並滿足消費者的需求，已成為高科技產業中行銷經理人的重要任務。然而，由於消費性電子產品的技術發展快速，使得預測更加困難。在智慧型手機市場中，主要的市場領導者包含Apple，宏達電，諾基亞，RIM…等。這些市場領導者於同一市場區隔中提供類似的產品使得競爭環境更為激烈。此外，作業系統為影響消費者購買智慧型手機的主要考量，未來也將由一至兩種作業系統瓜分市場。因此，預測消費者對智慧型手機與作業系統的接受率成為近年來重要且困難的工作。為了準確分析影響消費者接受智慧型手機之因素與接受率，本研究將以基於先驅使用者法的科技接受模式(Technology Acceptance Model, TAM)為基礎進行分析與預測，首先以並比較先驅使用者(Lead User)與一般大眾需求的差異。本研究將以決策實驗室網路流程法(DEMATEL-based Network Process, DNP)與結構方程模型(Structural Equation Model, SEM)分析先驅使用者與一般大眾之意見。首先，藉由文獻探討蒐集影響消費者之準則，並透過修正式德菲法取得專家之意見，再以決策研究室分析法之網路流程(SEM)預測影響先驅使用者對科技產品接受率之因子，透過決策研究室分析法(DEMATEL)導出要素間的因果關係與架構，並利用決策研究室分析法之網路流程(DNP)計算出準則要素的權重。同時，本研究亦將導入結構方程模式(SEM)分析影響一般大眾接受科技產品時其考量因素之路徑係數與因素負荷量，加以分析比較先驅使用者與一般大眾間之差異，最後，並比較兩大作業系統(Android與iOS)使用者之差異。本研究將以智慧型手機為實證分析驗證決策實驗室網路流程法(DNP)與結構方程模型(SEM)之可行性。本研究之結果指出一般大眾(包含Android與iOS)與使用iOS之先驅使用者皆將知覺易用性視為重要準則，使用Android之先驅使用者則將知覺有用性視為重要準則，同時，Android之使用者較能代表先驅使用者之偏好。本研究之研究方法可做為高科技產業行銷經理人擬訂策略之基準，並可用於分析預測其他高科技產品之消費者行為。

關鍵字

智慧型手機 ； 先驅使用者(LUM) ； 作業系統 ； 科技接受模式（TAM） ； 使用者接受率 ； 決策實驗室分析法(DEMATEL) ； 決策研究室分析法之網路流程(DNP) ； 結構方程模型（SEM） ； 多準則決策分析(MCDM)

並列摘要

The Smart Phone emerged recently as one of the most popular consumer electronics devices. Consequently, analyzing and predicting the consumer purchasing behaviors of Smart Phones for fulfilling customers‟ needs has become an indispensable task for marketing managers of IT (information technology) firms. However, the predictions are not easy. The consumer electronics technology evolved rapidly. Market leaders including Apple, HTC, Nokia, RIM, Samsung etc. are also competing in the same segmentation by providing similar products which further complicated the competitive situation. Besides, the key feature of Smart Phones is the operating system, the market ultimately settling on one or two dominant systems. Consequently, how the consumers‟ acceptance of novel Smart Phones and the operating system can be analyzed and predicted have become an important but difficult task. In order to accurately analyze the factors influencing consumers‟ acceptance of Smart Phones and predict the consumer behavior, the Technology Acceptance Model (TAM) and the Lead User Method will be introduced. Further, the differences in the factors being recognized by both lead users as well as mass users will be compared. Afterwards, the differences between Android and iOS users will also be compared. The possible customers‟ needs will first be collected and summarized by reviewing literature on the TAM. Then, the causal relationship
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between the factors influencing the consumer behaviors being recognized by both the lead users as well as the mass customers will be derived by the DEMATEL based network process (DNP) and the Structural Equation Modeling (SEM) respectively. An empirical study based on the Taiwanese Smart Phone users will be leveraged for comparing the results being derived by the DNP and the SEM. By and large, the empirical indicate that both of iOS lead users and mass users (including Android and iOS) regard the ease of use as an important factor. Contrarily, the Android lead users emphasize on usefulness, it‟s also could be the representative of lead users. The research results can serve as a basis for IT marketing managers‟ strategy definitions. The proposed methodology can be used for analyzing and predicting customers‟ preferences and acceptances of high technology products in the future.

並列關鍵字

Smart Phone ； Operating System ； Technology Acceptance Model (TAM) ； Decision Making Trial and Evaluation Laboratory (DEMATEL) ； Lead User Method (LUM) ； Structural Equation Modeling (SEM) ； DEMATEL Network Process (DNP) ； Multiple Criteria Decision Making (MCDM)

參考文獻

Hsu, C. Y., Chen, K.T. ＆ Tzeng, G.H. (2007). FMCDM with Fuzzy DEMATEL Approach for Customers’ Choice Behavior Model. International Journal of Fuzzy Systems, 9(4), 236-246.

Satty, T. L. (2005), Theory and Applications of the Analytic Network Process. Pittsburg, PA: RWS Publications.

Agarwal, R. ＆ Prasad, J. (1997). The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Sciences, 28 (3), 557–582.

Agarwal, R. ＆Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies. Decision Sciences, 30 (2), 361–391.

Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckman (Eds.), Actions-control: From cognition to behavior, Heidelberg, 11-39.