| 研究生: |
孫瑋佑 Wei-yu Sun |
|---|---|
| 論文名稱: |
負面評價對於網路拍賣交易行為的影響 The Effect of Negative Feedback on Online Auction Transaction Behavior |
| 指導教授: |
何靖遠
Chin-yuan Ho |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 資訊管理學系 Department of Information Management |
| 畢業學年度: | 98 |
| 語文別: | 中文 |
| 論文頁數: | 80 |
| 中文關鍵詞: | 實徵研究 、溢價 、網路拍賣 、回饋機制 、資訊不對稱 、負面評價 |
| 外文關鍵詞: | Negative feedback, Empirical research, Price premium, Online auction, Feedback mechanism, Information asymmetry |
| 相關次數: | 點閱:7 下載:0 |
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電子商務發展相當成熟,網路拍賣已成為世界上最普遍使用的電子商務平台。因為有大量的使用者與商品出現,網路拍賣交易中買賣雙方大部分彼此都不認識,買賣雙方的資訊不對稱與信任議題是網路拍賣中最嚴重的問題,進而去影響使用者的交易意願與溢價購買。之前的研究指出網路拍賣中回饋機制可以有效降低交易中資訊不對稱的問題,藉由回饋機制中賣方負面評價的呈現來降低詐欺事件的發生。然而,很少有研究探討負面評價資訊對於消費者實際交易行為的影響。
因此,本研究透過心理學與社會學上的理論,採用網路探勘的方式蒐集台灣奇摩拍賣的交易資料,透過網頁耙取機器人“Crawler”蒐集七種不同的消費性電子產品當作樣本,使用迴歸分析的方式來討論回饋機制中負面評價資訊對於網路拍賣交易行為的影響,同時也檢驗商品價格的調節關係。研究結果發現,負面評價資訊對於交易行為中的交易成功的機率、溢價與消費者交易意願有顯著的影響,而不同商品價格對於負面評價資訊與交易行為之間產生的調節作用也不相同。
With the explosion of electronic commerce, online auction should be the most popular electronic commerce platform in the world. The most important problem in online auction may be the asymmetric information and trust issue due to the huge number of users, goods and both transacting parties who were not familiar with each others. And this problem does have an effect on buyer’s willingness to transact and price premium in online auction. Prior researches indicated that feedback mechanism can mitigate information asymmetry, and the appearance of negative feedbacks in feedback mechanism can reduce transaction-specific risk. However, there still few researches related to the topic about the relationship between negative feedbacks and buyer’s transaction behavior.
Drawing from psychological, sociological theories and using data from Yahoo! online auction website, we use automated agent “Crawler” to collect transaction data of consumer electronics products in seven categories and we adopt the simple regression to examine the relationship between negative feedbacks and buyer’s transaction behavior. In addition, the research also examines whether product price have moderate effect on the relationship between negative feedbacks and buyer’s transaction behavior. Our result shows that negative feedbacks are significantly related to the probability to transaction success, price premium and buyer’s willingness to transact in consumer’s transaction behavior, and product price have different moderate effects on those relationship.
1. Akerlof, G. A., 1970. “The Market for "Lemons": Quality Uncertainty and the Market Mechanism,” Quarterly Journal of Economics, 84(3), pp. 488-500.
2. Ba, S. & Pavlou, P. A., 2002. “Evidence of the Effect of Trust Building Technology in Electronic Markets: Price Premiums and Buyer Behavior,” MIS Quarterly, 26(3), pp. 243-268.
3. Bajari, P. & Hortaçsu, A., 2004. “Economic Insights from Internet Auctions,” Journal of Economic Literature, 42(2), pp. 457-486.
4. Bajari, P. & Hortaçsu, A., 2003. “The Winner''s Curse, Reserve Prices, and Endogenous Entry: Empirical Insights from eBay Auctions,” RAND Journal of Economics, 34(2), pp. 329-355.
5. Bapna, R., Goes, P. & Gupta, A., 2001. “Insights and Analyses of Online Auctions,” Communications of the ACM, 44(11), pp. 42-50.
6. Bapna, R., Goes, P., Gupta, A. & Jin, Y., 2004. “User Heterogeneity and Its Impact on Electronic Auction Market Design: An Empirical Exploration,” MIS Quarterly, 28(1), pp. 21-43.
7. Bell, D. E., 1982. “Regret in Decision Making Under Uncertainty,” Operations Research, 30(5), pp. 961-981.
8. Blau, P. M., 1964. “Exchange and Power in Social Life,” John Wiley & Sons, New York.
9. Brynjolfsson, E. & Smith, M., 2000. “Frictionless Commerce? A Comparison of Internet and Conventional Retailers,” Management Science, 46(4), pp. 563-585.
10. Cooley, R., Mobasher, B. & Srivastava, J., 1997. “Web Mining: Information and Pattern Discovery on the World Wide Web,” Tools with Artificial Intelligence, 1997. Proceedings., Ninth IEEE International Conference on Tools with Artificial Intelligence, pp. 558-567.
11. Cox, J. C., Smith, V. C. & Walker, J. M., 1988. “Theory and Behavior of First Price Auction,” Journal of Risk and Uncertainty, 1, pp. 61-99.
12. Dellarocas, C., 2003. “The Digitization of Word-of-Mouth: Promise and Challenges of Online Feedback Mechanisms,” Management Science, 49(10), pp. 1407-1424.
13. Elliott, R. K. & Jacobson, P. D., 1994. “Costs and Benefits of Business Information Disclosure,” Accounting Horizons, 8(4), pp. 80-96.
14. Engelbrecht-Wiggans, R, & Katok, E., 2008. “Regret and Feedback Information in First-price Sealed-bid Auctions,” Management Science, 54 (4), pp.808-819.
15. Forman, C., Ghose, A. & Wiesenfeld, B., 2008. “Examining the Relationship between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets,” Information Systems Research, 19(3), pp. 291-313.
16. Gefen, D., Karahanna, E. & Straub, D. W., 2003. “Trust and TAM in Online Shopping: An Integrated Model,” MIS Quarterly, 27(1), pp. 51-90.
17. Gregg, D. G. & Scott, J. E., 2006. “The Role of Reputation Systems in Reducing Online Auction Fraud,” International Journal of Electronic Commerce, 10(3), pp. 95-120.
18. Gregg, D. G. & Walczak, S., 2008. “Dressing Your Online Auction Business for Success: An Experiment Comparing Two eBay Businesses,” MIS Quarterly, 32(3), pp. 653-670.
19. Kauffman, R. & Wood, C., 2006. “Doing Their Bidding: An Empirical Examination of Factors that Affect a Buyer’s Utility in Internet Auctions,” Information Technology and Management, 7(3), pp. 171-190.
20. Kauffman, R. J. & Wood, C.A., 2003. “Running Up the Bid: Detecting, Predicting, and Preventing Reserve Price Shilling in Online Auctions,” Proceedings of the 5th international conference on Electronic commerce. Pittsburgh, Pennsylvania: ACM, pp. 259-265.
21. Klein, B. & Leffler, K. B., 1981. “The Role of Market Forces in Assuring Contractual Performance,” Journal of Political Economy, 89(4), 615-641.
22. Kobayashi, M. & Takeda, K., 2000. “Information Retrieval on the Web,”
ACM Computer Surveys, 32(2), pp. 144-173.
23. Kreps, D. M., 1990. “Corporate Culture and Economic Theory,” in Perspectives in Positive Political Economy, J. E. Alt and K. A. Schepsle (eds.), Cambridge University Press, Cambridge, UK.
24. Krishna, V., 2002. Auction Theory, Academic Press.
25. Kumar, N. & Benbasat, I., 2006. “The Influence if Recommendations and Consumer Reviews on Evaluations of Websites,” Information System Research, 17(4), pp. 425-439.
26. Lawrence, S. & Giles, C. L., 1999. “Accessibility of Information on the Web,” Nature, 400(6740), pp. 107-109.
27. Lee, Z., Im, I. & Lee, S. J., 2000. “The Effect of Negative Buyer Feedback on Prices in Internet Auction Markets,” in Proceedings of the Twenty-first International Conference on Information Systems, W. J. Orlikowski, S. Ang, P. Weill, H. Krcmar, and J. I. DeGross (eds.), Brisbane, Australia, pp. 286-287.
28. Leibenstein, H., 1950. “Bandwagon, Snob, and Veblen Effects in the Theory of Consumers'' Demand,” Quarterly Journal of Economics, 64(2), pp. 183-207.
29. Li, S., Srinivasan, K. & Sun, B., 2009. “Internet Auction Features as Quality Signals,” Journal of Marketing, 73(1), pp. 75-92.
30. Lucking-Reiley, D., Bryan, D., Prasad, N. & Reeves, D., 2007. “Pennies from eBay: the Determinants of Price in Online Auctions,” Journal of Industrial Economics, 55(2), pp. 223-233.
31. Matzat, U., Utz, S. & Snijders, C., 2009. “On-line Reputation Systems: The Effects of Feedback Comments and Reactions on Building and Rebuilding Trust in On-line Auctions,” International Journal of Electronic Commerce, 13(3), pp. 95-118.
32. McAfee, R. P. & McMillian, J., 1987. “Auctions and Bidding,” Journal of Economic Literature, 25(2), pp. 699-738.
33. McDonald, C. G. & Slawson Jr., V. C., 2002. “Reputation in an Internet Auction Market,” Economic Inquiry, 40(4), pp. 633-650.
34. Melnik, M. & Alm, J., 2002. “Does a Seller’s e-Commerce Reputation Matter? Evidence from eBay Auctions,” Journal of Industrial Economics, 50(3), pp. 337-349.
35. Milgrom, P. R., North, D. C. & Weingast, B. R., 1990. “The Role of Institutions in the Revival of Trade: The Law Merchant, Private Judges, and the Champagne Fairs,” Economics and Politics, 2(1), pp. 1-23.
36. Nadeau, R., Cloutier, E. & Guay, J., 1993. “New Evidence about the Existence of a Bandwagon Effect in the Opinion Formation Process,” International Political Science Review/ Revue internationale de science pol, 14(2), pp. 203-213.
37. Onur, I. & Tomak, K., 2006. “Impact of Ending Rules in Online Auctions: The Case of Yahoo.com,” Decision Support Systems, 42(3), pp.1835-1842.
38. Pavlou, P. A., 2003. “Consumer Acceptance of Electronic Commerce: Integrating Trust and Risk with the Technology Acceptance Model,” International Journal of Electronic Commerce, 7(3), pp. 101-134.
39. Pavlou, P. A. & Dimoka, A., 2006. “The Nature and Role of Feedback Text Comments in Online Marketplaces: Implications for Trust Building, Price Premiums, and Seller Differentiation,” Information Systems Research, 17(4), pp. 392-414.
40. Rao, A. R. & Monroe, K.B., 1996. “Causes and Consequences of Price Premiums,” Journal of Business, 69(4), pp. 511-545.
41. Sharma, S., Durand, R. M. & Gur-Arie, O., 1981. “Identification and Analysis of Moderator Variables,” Journal of Marketing Research (JMR), 18(3), pp. 291-300.
42. Sundaram, D. & Webster, C., 1998. “Service Consumption Criticality in Failure Recovery,” Journal of Business Research, 41(2), pp. 153-159.
43. Thibaut, J. W. & Kelly H. H., 1986. “The Social Psychology if Groups,” New York: Wiley.
44. Weinberg, B. D. & Davis, L., 2005. “Exploring the WOW in Online-auction Feedback,” Journal of Business Research, pp. 1609-1621.
45. Yu, C. & Lin, S., 2008. “Parallel Crawling and Capturing for On-Line Auction,” Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics. Taipei, Taiwan: Springer-Verlag, pp. 455-466.