1. 淡江大學 資管碩二 鄭佳容 淡江大學 資管碩二 李依倫 報告日期： 100.06.03 Predicting and explaining the adoption of online trading: An empirical study in Taiwan Lee, M. C. (2009). Predicting and explaining the adoption of online trading: An empirical study in Taiwan. Decision Support Systems, 47(2), 133-142.

2. Author 2 李明錡 Ming-Chi Lee 現任：國立屏東商業技術學院 副教授 學歷：淡江大學資訊工程博士： 1990-1994 淡江大學資訊工程碩士： 1988-1990 專長：電子商務、決策支援系統、專家系統 聯絡信箱： lmc@npic.edu.tw

3. Abstract 3 This study investigates how stock investors perceive and adopt online trading in Taiwan 這篇研究是在調查台灣的股票投資者對線上交易的認知與 採用 We developed a research model which integrates perceived risk, perceived benefit and trust, together with technology acceptance model (TAM) and theory of planned behavior (TPB) perspectives to predict and explain investors' intention to use online trading 作者發展了一套整合 TAM 、 TPB 的理論中，已知風險、已 知利益、與信任等構面的模型，來預測並解釋投資者使用 線上交易的意圖

4. Abstract 4 The model is examined through an empirical study involving 338 subjects using structural equation modeling techniques 文中利用了結構方程模組，以 338 個樣本進行實證研究 The results provide support for the proposed research model and confirm its robustness in predicting investors' intentions to adopt online trading 研究結果顯示支持其假設模型，並確認它在預測投資者採 用線上交易的意圖 In addition, this study provides some useful suggestions and/or implications for the academician and practitioners in the area of online trading 此外，本篇研究也提供了未來發展給線上交易這塊領域的 學術研究者與實作人員作參考

5. Introduction 5 In December 2005, only 13.2% of the total market turnover value was conducted online and 19% of total investor accounts were online accounts A comprehensive model describing the factors that drive customers to accept online trading would be useful for both academics and practitioners

6. Introduction 6 This paper integrate two important streams of literature under the nomological structure of the theory of reasoned action (TRA) (a) the technology acceptance model (TAM) as well as the theory of planned behavior (TPB) (b) the literature on benefit, risk and trust

7. Introduction 7 Online trading has lot of advantages, such as faster trading speed better information transparency lower operating cost It is expected that a stock investor will choose to adopt online trading if they perceive that doing so will provide greater benefits than existing methods.

8. Introduction 8 However, according to the risk theory of consumer behavior, Bauer indicated that benefits are often accompanied with risks First, there is the risk of monetary loss due to transaction error or stock account misuse Second, there is the risk of loss of privacy due to Internet fraud or hacker intrusion

9. Introduction 9 Trust has long been regarded as a catalyst for buyer–seller transactions that can provide consumers with high expectations of satisfying exchange relationships Perceived risk is also an important element of B2C e- commerce that is likely to affect consumer behavior

10. Introduction 10 The purpose of this study is as follows: 1. To investigate whether trust, perceived risk, and perceived benefit significantly impact investors' behavioral intention to adopt online trading adoption 2. To clarify which factors are more influential and relevant with regard to affecting investors' decision whether or not to trade online 3. To evaluate whether the integration of TAM with TPB provide a solid theoretical basis for examining the adoption of online trading

11. Basic concepts and research background 11 Trust Trust is an expectation that others one chooses to trust will not behave opportunistically It is one's belief that the other party will behave in a dependable, ethical, and socially appropriate manner

12. Basic concepts and research background 12 Perceived benefit Compared with traditional off-line (phone-based) trading methods, the direct advantages of online trading are illustrated as follows First, in order to attract more customers to online trading, online stock brokerage companies often offer lower brokerage fees Second, online trading can save transaction time and facilitate the stock trading process Third, during the transaction, online trading allows traders to monitor contractual performance at any time or to confirm delivery automatically

13. Basic concepts and research background 13 Perceived risk Peter and defined perceived risk as a kind of subjective expected loss Featherman and Pavlou also defined perceived risk as the possible loss when pursuing a longed for result

14. Basic concepts and research background 14 Technology acceptance model (TAM) The technology acceptance model (TAM) is an adaptation of the theory of reasoned action (TRA) by Fishbein and Ajzen Theory of planned behavior (TPB) It is designed to explain almost any human behavior and has been proven successful in predicting and explaining human behavior across various application contexts

15. Research model and hypotheses development 15 TAM and TPB H1. Perceived usefulness has a positive effect on intention to trade online H2. Attitude has a positive effect on intention to trade online H3. Perceived behavioral control has a positive effect on intention to trade online H4. Subjective norm has a positive effect on intention to trade online H5. Perceived usefulness has a positive effect on attitude to trade online H6. Perceived ease of use has a positive effect on attitude to use online trading H7. Perceived ease of use has a positive effect on perceived usefulness to trade online

16. Research model and hypotheses development 16 Trust and TAM

17. Research model and hypotheses development 17 Trust and TPB

18. Research model and hypotheses development 18 Perceived benefit

19. Research model and hypotheses development 19 Perceived risk

20. Research methods 20 Questionnaire development The instrument was designed to include a two-part questionnaire as presented in Appendix A Before conducting the main survey, we performed a pre-test to validate the instrument The pre-test involved 10 respondents who have used online trading for more than 3 years

21. Research methods 21 Sample and data collection This study conducted a web-based survey to allow respondents to feel anonymous and to overcome time and place constraints This online survey, which yielded 356 responses, was conducted for one month, with incomplete responses and missing values deleted, resulting in a sample size of 338 users for an overall response rate of 95.2%.

22. Research methods 22 Common method bias In this study, because we collected the data for the independent and dependent variables from the same respondents, concerns about common method bias could arise We conducted Harmon's one-factor test to assess the potential common method variance bias in this study

23. Results This study first developed the measurement model by conducting confirmatory factor analysis Conducting confirmatory factor analysis (CFA) 驗證性因素分析 The SEM was then estimated for hypotheses testing Structural equation model (SEM) 結構方程模式 The models were assessed by the maximum likelihood method using AMOS 5.0 Maximum likelihood method (MLE) 最大概似估計法 2011/4/29 23

24. Results 24 Analysis of the measurement model A Chi-square value of 984.5 with 418 degrees of freedom (p<0.001). The size exceed 200 respondents. This approach obtained a value of 2.35,which falls within the suggested value of 5 or below.

25. Results 25

26. Results 26

27. Results 27

28. Discussion 28

29. Discussion 29 The result shows that the intention to use online trading is adversely affected primarily by perceived risk.

30. Implications 30 Practical implications This study reveals that perceived risk is a more important influential factor than perceived benefit in online trading decision making. this study also finds that trust is a critical cue that affects customers' intention to trade online. Theoretical implications this study include both a negative factor (perceived risk) and positive factors (trust and perceived benefits) simultaneously. This unified model may be also appropriate for the analysis of other e-commerce applications

31. Conclusions and future research 31 The objective of this study is to develop a theoretical. Research is systematically sampled from a more dispersed sample in future. It is important to recognize the cultural and national limitations of these findings. In contrast to Korea's high adoption rate of about 54% for online trading, Taiwan has a much lower adoption rate only about 20%. The conclusions drawn from our study are based on cross sectional data.

32. 32 Predicting and explaining the adoption of online trading: An empirical study in Taiwan 簡報結束 敬請指教 淡江大學 資管碩二 鄭佳容 淡江大學 資管碩二 李依倫