隨著電腦網路與資訊科技的發達，電子商務正日益蓬勃的發展中。電子商務中的C2C商業模式，即線上拍賣，是越來越多人使用的一個購物平台，然而，目前在台灣的線上拍賣網站交易環境中，仍由於線上拍賣詐騙的問題，使得許多人在這個平台上交易時，不信任對方而在交易的過程上產生猶豫及憂慮，。
本研究針對線上拍賣詐騙議題，利用e3-value methodology，從價值與控制的觀點，建立一新型線上拍賣架構，欲藉以預防線上拍賣詐騙行為的發生。研究中將此架構以雛型系統的方式呈現，並操作一項實驗。透過實驗中蒐集的問卷資料進行資料分析，從資料分析的結果來驗證該架構是否能夠促進買家更信任線上拍賣網站上的賣家以及是否更願意使用線上拍賣網站。本研究的實驗結果簡述如下：
1. 使用Escrow Services作為付款工具，能夠增加買家對於賣家的信任及更願意在線上拍賣網站上做交易。
2. 本研究提出的新線上拍賣架構，相較於只提供Escrow付款服務的線上拍賣網站，能夠提升更多買家對線上拍賣網站上賣家的信任。

Customer-to-customer (C2C) electronic commerce is getting a major purchase channel as development of information technology, especially online auction. However, consumers still hesitate to use online auction in Taiwan because of the problem of online auction fraud. Many consumers can not trust trading partner and then worry to be suffered by trading partners’ opportunistic behaviors. This study try to propose a revised process model of online auction from the perspective of value and control based on e3-value methodology. This model focuses on preventing transaction from non-delivery and misrepresentation fraudulent events. This study expected to explore the effectiveness of this revised process model from the perspective of trust transference. This study proposed that online consumers will trust trading partners and be willing to do online auction if they think the mechanism of online auction process is worth being trusted. This study conducted an experiment for collecting data. Results are as below:
1. The mechanism of escrow service increase buyers’ trust in and transaction intention with sellers of the online auction website.
2. The improved level of buyers’ trust in sellers of prototype built based on our proposed process model is higher than of online auction website which only provide Escrow payment services.

目錄
第1章 緒論 1
1.1 研究背景 1
1.2 研究動機 3
1.3 研究目的 4
1.4 研究範圍 5
1.5 研究流程 6
第2章 文獻探討 7
2.1 線上拍賣詐騙 7
2.2 預防線上拍賣詐騙的機制 11
2.2.1 評價系統 (Feedback System) 11
2.2.2 保險或保障 (Insurance or Guarantee) 13
2.2.3 交易履約保障服務 (Escrow Services) 16
2.3 e3-value methodology 19
2.3.1 e3-value 19
2.3.2 e3-control 20
2.3.3 Control Mechanism 21
2.3.4 Control Patterns 24
2.4 制度型信任 26
2.4.1 信任之建立 27
2.4.2 信任轉移 29
第3章 預防線上拍賣詐騙行為之架構設計 32
3.1 架構建立 32
3.2 流程說明 39
3.3 差異性比較 41
第4章 雛型系統分析與設計 43
4.1 雛型系統分析－使用者案例 (Use Case) 43
4.2 類別圖 (Class Diagram) 45
4.3 循序圖 (Sequence Diagram) 47
4.4 系統架構 51
4.5 雛型系統功能需求 52
4.6 雛型系統畫面 54
第5章 探索性分析 63
5.1 實驗設計 63
5.2 研究模型 64
5.3 問卷設計 66
5.4實驗流程 70
5.4.1 環境A 71
5.4.2 環境B 72
5.4.3 環境C 74
5.5資料分析 77
5.5.1 信度與效度分析 80
5.5.2 變異數分析 84
5.5.3 成對樣本T檢定 91
5.5.4 共變數分析 94
第6章 結論與未來研究方向 103
6.1 討論 106
6.1.1 目前台灣的線上拍賣網站交易方式 106
6.1.2 新線上拍賣架構的優勢 111
6.1.3 淘寶網、ezPay及本研究之比較 115
6.2 研究貢獻 119
6.3 研究限制 121
6.4 未來研究方向 122
圖目錄
圖1 1、研究流程 6
圖2 1、買賣雙方的價值交換 19
圖2 2、交易過程可能發生的問題 20
圖2 3、買家透過Escrow付錢 21
圖2 4、透過信任的物流運送貨物 22
圖2 5、Control Patterns － “Pre-execution” 24
圖2 6、消費者初始信任模型 27
圖3 1、預防詐騙線上拍賣架構（一） 32
圖3 2、預防詐騙線上拍賣架構（二） 34
圖3 3、預防詐騙線上拍賣架構（三） 35
圖3 4、預防詐騙線上拍賣架構（四） 38
圖3 5、預防詐騙線上拍賣架構 － 流程的觀點 39
圖4 1、雛型系統之使用案例 44
圖4 2、類別圖 － 拍賣網站 45
圖4 3、類別圖 － Escrow 46
圖4 4、類別圖 － 物流 46
圖4 5、預防詐騙線上拍賣流程（循序圖） 47
圖4 6、預防詐騙線上拍賣流程 － 退款（循序圖） 49
圖4 7、雛型系統架構 51
圖4 8、雛型系統畫面（一） 54
圖4 9、雛型系統畫面（二） 54
圖4 10、雛型系統畫面（三） 55
圖4 11、雛型系統畫面（四） 55
圖4 12、雛型系統畫面（五） 56
圖4 13、雛型系統畫面（六） 56
圖4 14、雛型系統畫面（七） 57
圖4 15、雛型系統畫面（八） 57
圖4 16、雛型系統畫面（九） 58
圖4 17、雛型系統畫面（十） 58
圖4 18、雛型系統畫面（十一） 59
圖4 19、雛型系統畫面（十二） 60
圖4 20、雛型系統畫面（十三） 60
圖4 21、雛型系統畫面（十四） 61
圖4 22、雛型系統畫面（十五） 61
圖5 1、研究模型 66
圖5 2、實驗流程 70
圖5 3、環境A之操作流程圖 71
圖5 4、環境B之操作流程圖 73
圖5 5、環境C之操作流程圖 75
圖6 1、ezPay與買家、賣家及線上拍賣網站關係之架構 116
表目錄
表2 1、線上拍賣詐騙種類 8
表2 2、評價系統與拍賣詐騙相關文獻整理 12
表3 1、預防詐騙線上拍賣架構與其他線上拍賣網站的比較 41
表5 1、各構念之題項及參考資料來源（一） 67
表5 2、各構念之題項及參考資料來源（二） 68
表5 3、構念之操作性定義 69
表5 4、樣本次數交叉表 78
表5 5、樣本次數表（系所） 79
表5 6、構念信度分析結果 80
表5 7、構念效度分析結果（一） 82
表5 8、構念效度分析結果（二） 83
表5 9、ANOVA分析結果（一） 84
表5 10、ANOVA分析結果（二） 87
表5 11、成對樣本T檢定分析結果 91
表5 12、受試者間效應項的檢定（一） 95
表5 13、受試者間效應項的檢定（二） 96
表5 14、誤差變易量的Levene檢定等式 97
表5 15、受試者間效應項的檢定 98
表5 16、事後比較結果（一） 99
表5 17、事後比較結果（二） 100
表5 18、事後比較結果（三） 100
表6 1、本研究與其他線上拍賣網站優勢比較表 118

英文部分
[1] Antony, S., Lin, Z. and Xu, B., “Determinants of escrow service adoption in consumer-to-consumer online auction market: An experimental study,” Decision Support Systems, 42, 3, pp. 1889-1900, 2006.
[2] Ba, S., Whinston, A.B. and Zhang, H., “Building trust in online auction markets through an economic incentive mechanism,” Decision Support Systems, 35, pp. 273–286, 2003.
[3] Bywell, C.E. and Oppenheim, C., “Fraud on Internet auctions,” Aslib Proceedings, 53, 7, pp. 265-272, Jul/Aug 2001.
[4] Chau, D.H. and Faloutsos, C., “Fraud detection in electronic auction,” In European Web Mining Forum at ECML/PKDD, 2005.
[5] Clemons, E.K., “An empirical investigation of third-party seller rating systems in E-Commerce: The case of buySAFE,” Journal of Management Information Systems, 24, 2, pp. 43-71, 2007.
[6] Doney, P.M. and Cannon, J.P., “An examination of the nature of trust in buyer-seller relationships,” Journal of Marketing, 61, pp. 35-51, 1997.
[7] Fan, M., Tan, Y. and Whinston, A.B., “Evaluation and design of online cooperative feedback mechanisms for reputation management,” IEEE Transactions on Knowledge and Data Engineering, 17, 2, pp. 244-254, 2005.
[8] Gavish, B. and Tucci, C.L., “Fraudulent auctions on the Internet,” Electronic Commerce Research, 6, pp. 127-140, 2006.
[9] Gefen, D., “E-commerce: the role of familiarity and trust,” Omega, 28, pp. 725-737, 2000.
[10] Gordijn, J. and Akkermans, J.M., “Value-based requirements engineering: Exploring innovative e-commerce ideas,” Requirements Engineering, 8, pp. 114–134, 2003.
[11] Gregg, D.G. and Scott, J.E., “A typology of complaints about eBay sellers,” Communications of the ACM, 51, 4 April 2008.
[12] Gregg, D.G. and Scott, J.E., “The role of reputation systems in reducing on-line auction fraud,” International Journal of Electronic Commerce, 10, 3, pp. 95-120, Spring 2006.
[13] Hu, X., Lin, Z., Whinston, A.B. and Zhang, H., “Hope or hype: On the viability of escrow services as trusted third parties in online auction environments,” Information Systems Research, 15, 3, pp. 236-249, 2004.
[14] Kartseva, V., Gordijn, J. and Tan, Y.-H., “Toward a modeling tool for designing control mechanisms for network organizations,” International Journal of Electronic Commerce, 10, 2, pp. 57–84, Winter 2005–6.
[15] Kartseva, V., Hulstijn, J., Tan, Y.-H. and Gordijn, J., “Towards value-based design patterns for inter-organizational control,” 19th Bled Electronic Commerce Conference, Bled, Slovenia, June 2006.
[16] Lee, H.-M. and Wang, C.-W., “A profiled malicious bidder behavior model based on SOM algorithm,” The 3rd Intetnational Conference on Innovative Computing Information and Control, 00, pp. 157, 2008.
[17] Lim, K., Sia, C.L., Lee, M.K.O. and Benbasat, I., “Do I trust you online, and if so, will I buy? An empirical study of two trust-building strategies,” Journal of Management Information Systems, 23, 2, pp. 233-266, Fall 2006.
[18] McKnight, D.H. and Chervany, N.L., “What trust means in e-commerce customer relationships: An interdisciplinary conceptual typology,” International Journal of Electronic Commerce, 6, 2, pp. 35-59, Winter 2001-2002.
[19] McKnight, D.H., Choudhury, V. and Kacmar, C., “Developing and validating trust measures for e-commerce: An integrative typology,” Information Systems Research, 13, 3, Sep 2002a.
[20] McKnight, D.H., Choudhury, V. and Kacmar, C., “The impact of initial consumer trust on intentions to transact with a web site: a trust building model,” Journal of Strategic Information Systems, 11, pp. 297-323, 2002b.
[21] Milliman, R.E. and Fugate, D.L., “Using trust-transference as a persuasion technique: An empirical field investigation,” The Journal of Personal Selling & Sales Management, 8, 2, pp. 1-7, 1988.
[22] Morzy, M. and Jezierski, J., “Cluster-based analysis and recommendation of sellers in online auctions,” Computer Systems Science and Engineering, 22, 5, pp. 279-287, 2007.
[23] Morzy, M., “New algorithms for mining the reputation of participants of online auctions,” Algorithmica, 52, pp. 95-112, 2008.
[24] Pandit, S., Chau, D.H., Wang, S. and Faloutsos, C., “Netprobe: A fast and scalable system for fraud detection in online auction networks,” Proceedings of the 16th international conference on World Wide Web, pp. 201-210, 2007.
[25] Pavlou, P.A. and Gefen, D., “Building effective online marketplaces with institution-based trust,” Information Systems Research, 15, 1, pp. 37-59, March 2004.
[26] Rubin, S., Christodorescu, M., Ganapathy, V., Giffin, J.T., Kruger, L. and Wang, H., “An auctioning reputation system based on anomaly detection,” Proceedings of the 12th ACM Conference on Computer and Communications Security, pp. 270-279, 2005.
[27] Trevathan, J. and Read, W., “Detecting collusive shill bidding,” Proceedings of the International Conference on Information Technology, pp. 799-808, 2007.
[28] Wang, J.-C. and Chiu, C.-C., “Recommending trusted online auction sellers using social network analysis,” Expert Systems with Applications, 34, 3, pp. 1666-1679, 2008.
[29] Wingreen, S. and Baglione, S.L., “Untangling the antecedents and covariates of e-Commerce trust: Institutional trust vs. knowledge-based trust,” Electronic Markets, 15, 3, pp. 246-260, 2005.
[30] Xu, H. and Cheng, Y.-T., “Model checking bidding behaviors in internet concurrent auctions,” Computer Systems Science and Engineering, 22, 4, pp. 179-191, 2007.
[31] Xu, H., Shatz, S.M. and Bates, C.K., “A framework for agent-based trust management in online auctions,” Proceedings of the Fifth International Conference on Information Technology: New Generations, pp. 149-155, 2008.
[32] Zhang, B., Zhou, Y. and Faloutsos, C., “Toward a comprehensive model in internet auction fraud detection,” Proceedings of the 41st Hawaii International Conference on System Sciences, pp. 79, 2008.
[33] Zhang, H. and Li, H., “Factors affecting payment choices in online auctions: A study of eBay traders,” Decision Support Systems, 42, pp. 1076-1088, 2006.
[34] Zhang, H., Lin, Z. & Hu, X., “The effectiveness of the Escrow model: An experimental framework for dynamic online environments,” Journal of Organizational Computing and Electronic Commerce, 17, 2, pp. 119-143, 2007.
[35] Zucker, L.G., “Production of trust: Institutional sources of economic structure, 1840-1920,” Research in Organization Behavior, 8, pp. 53-111, 1986.