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題名 網路市集賣家影響下的評價分數與評論取向
Rating Score and Comment Orientation under the Influence of Online Marketplace Sellers
作者 謝宜廷
貢獻者 管郁君<br>林淑瓊
謝宜廷
關鍵詞 網路評價系統
評價分數
評論取向
評價操弄
Online evaluation system
Rating score
Comment orientation
Manipulation
日期 2012
上傳時間 1-Oct-2013 11:59:22 (UTC+8)
摘要 網路市集中，網路評價系統扮演著重要角色在於買、賣雙方之間的信任建立，消費者往往仰賴網路評價系統協助購買決策的制訂，因此網路賣家必需認真看待買家給予的評價。然而，我們也不意外各式各樣的評價操弄行為開始出現於許多的網路市集中。僅管大多數操弄方式以隨機方式出現並且迅速的消失，其中一種具系統化且時常出現的操弄方式為賣家透過公告提醒事項試圖影響買家的評價，透過這些提醒事項去誘導買家留下正面評價或是禁止負面評價的產生。此研究提出一個研究設計用來檢視賣家的操弄行為對於評價系統之評價分數與評論取向的影響，而所提出研究架構將賣家的操弄行為分成三類分別為利誘、拒絕與無操弄。本研究選擇中國最大的網路市集─ 淘寶網用來衡量研究架構。
研究結果顯示在賣家的操弄下，僅有評價分數會受到影響進而在三組間造成顯著差異，然而，賣家的操弄與買家經驗的交互作用會影響評論取向與好評率，在賣家的操弄的三種類型中產生顯著差異。由此可知，買家經驗確實在賣家的操弄與買家評價之間有調節的作用。僅管研究結果顯示賣家的操弄確實影響了評價分數，但也更突顯出評論內容可能包含了更具價值的資訊，因此消費者不僅可以依據評價分數更可參考評論內容選擇賣家進行購買。
Online evaluation systems play an important role in creating trust between sellers and buyers in online marketplaces. Consumers often rely on these evaluations when making purchase decisions. As a result, sellers need to take buyers’ evaluations seriously. However, evaluation manipulation occurs in many online marketplaces. Various types of manipulation are apparent. Although most appear to be spurious and disappear rather quickly, many sellers engage in systematic evaluation manipulation by constantly posting reminders to influence buyers’ evaluations. The reminders generally aim to prompt a positive rating or prohibit a negative rating. This study examines the influence of seller manipulation on rating scores and comment orientation in an evaluation system. The research framework categorizes three types of seller manipulation: allurement, rejection and none. Taobao.com, the largest online marketplace in China, is used to evaluate the proposed model.
The results show that seller manipulation only influences rating scores. However, the interaction between seller manipulation and buyer experience influences both the orientation of comments and the percentage of positive ratings, which leads to significant differences among the three types of seller manipulation. Buyer experience mediates the relationship between seller manipulation and buyer evaluation. Although rating scores are influenced by seller manipulation, comments tend to contain much more valuable information. It is thus suggested that consumers rely on rating scores and comments when making purchase decisions.
參考文獻 淘寶論壇-小昭(2012年12月7日)。人民日報：淘寶首例“惡意差評師”案告破 7人涉嫌敲詐被捕【線上論壇】。取自 http://bbs.taobao.com/catalog/thread/508895-259867086.htm?spm=0.0.0.228.dy7IRn
About Taobao.com. Taobao.com, Retrieved 12 30, 2012, from http://www.taobao.com/about/intro.php?spm=0.0.21637.8.iev5J2
Akerlof, G. A. (1970, 8). The Market for "Lemons": Quality Uncertainty and the Market Mechanism. The Quarterly Journal of Economics, 84(3), pp. 488-500.
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.
Bagozzi, R. P., & Yi, Y. (1988). On the Evaluation of Structural Equation Models. Academy of Marketing Science, 16(1), pp. 74-94.
Bolton, G. E., Katok, E., & Ockenfels, A. (2004). How effective are electronic reputation mechanisms? An experimental investigation. Management Science, 50(11), pp. 1587-1602.
Company Overview, Alibaba group, Retrieved 01 04, 2013, from, http://news.alibaba.com/specials/aboutalibaba/aligroup/index.html
Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal Of Applied Psychology, 78(1), pp. 98-104.
David, A. G. (1984). What does "product quality" really mean? Sloan Management Review (Pre-1986), 26(1), p. 25.
Dellarocas, C. (2003). The digitization of word of mouth: Promise and challenges of online feedback mechanisms. Management Science, 49(10), pp. 1407-1424.
Dini, F., & Spagnolo, G. (2009). Buying reputation on eBay: Do recent changes help? International Journal of Electronic Business, 7(6), pp. 581-598.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 328-388.
Gregg, D. G., & Scott, J. E. (2006). The role of reputation systems in reducing on-line auction fraud. International Journal of Electronic Commerce, 10(3), pp. 95-120.
Gregg, D. G., & Scott, J. E. (2008). A TYPOLOGY of COMPLAINTS ABOUT EBAY SELLERS. Association for Computing Machinery. Communications of the ACM, 51(4), pp. 69-74.
Hair, Joseph F., Tatham, Ronald L., Anderson, Rolph E., Black, William. (1998). Multivariate Data Analysis. 5th edition, Prentice-Hall, NJ, USA.
Hinkin, T. R. (1998). A brief tutorial on the development of measures for use in survey questionnaires. Organizational Research Methods, 1(1), 104-121.
Ho, H.-h. (1998). Hong Kong, Mainland China & Taiwan: Chinese Character Frequency A Trans-Regional, Diachronic Survey. Retrieved 11 26, 2012, from http://humanum.arts.cuhk.edu.hk/Lexis/chifreq/
Hu, N., Bose, I., Gao, Y., & Liu, L. (2011, 2). Manipulation in digital word-of-mouth: A reality check for book reviews. Decision Support Systems, 50(3), pp. 627-635.
Hu, N., Bose, I., Koh, N. S., & Liu, L. (2012). Manipulation of online reviews: An analysis of ratings, readability, and sentiments. Decision Support Systems, 52(3), pp. 674-684.
Hu, N., Liu, L., & Sambamurthy, V. (2011, 2). Fraud detection in online consumer reviews. ecision Support Systems, 50(3), pp. 614-626.
Huang, Y., Chen, J., & Lu, W. (2011). Effects of seller reputation on success at online auctions: An empirical study. International Journal of Management, 28(3), pp. 621-629.
iResearch. (2012, 7 27). 艾瑞咨询：2012Q2中国网络购物市场交易规模2683.7亿元 增长超预期. Retrieved 10 14, 2012, from iResearch: http://www.iresearch.com.cn/View/177754.html
Kim, J., & Gupta, P. (2012, 7). Emotional expressions in online user reviews: How they influence consumers’ product evaluations. Journal of Business Research, 65(7), pp. 985-992.
Kusumasondjaja, S., Shanka, T., & Marchegiani, C. (2012). Credibility of online reviews and initial trust: The roles of reviewer’s identity and review valence. Journal of Vacation Marketing, 18(3), pp. 185-195.
Li, C.-F. (2010, 4). Understanding effects of seller’s and bidder’s characteristics on Internet auction applications. Expert Systems with Applications, 37(4), pp. 3462-3467.
MacInnes, I., Li, Y., & Yurcik, W. (2005). Reputation and dispute in eBay transactions. International Journal of Electronic Commerce, 10(1), pp. 27-54.
Malicious poor ratings Division gang crime law experts: three extortion can be admitted criminal, VentureData.org, Retrieved 01 04, 2013, from, http://www.venturedata.org/?i448761_Malicious-poor-ratings-Division-gang-crime-law-experts-three-extortion-can-be-admitted-criminal
Maxwell, J. G., & Hudson, M. (2011, 12). Multi-channel shopping: The future is now. Retrieved 10 14, 2012, from PwC: http://www.pwc.com/gx/en/retail-consumer/retail-consumer-publications/global-multi-channel-consumer-survey/2011-multi-channel-survey.jhtml
McDonald, C. G., & Slawson, V. C. (2002). Reputation in an internet auction market. Economic Inquiry, 40(4), pp. 633-650.
Melnik, M. I., & Alm, J. J. (2002). Does a Seller’s eCommerce Reputation Matter? Evidence from eBay Auctions. Journal of Industrial Economics, 50(3), pp. 337-349.
Oberholzer-Gee, F., & Wulf, J. M. (2009, 1 6). Alibaba’s Taobao (A). http://www.cases.nccu.edu.tw/harvard/tw/02/product01.aspx?ppno=9-709-456.
Park, C., & Lee, T. M. (2009). Information direction, website reputation and eWOM effect:. Journal of Business Research, 62, pp. 61-67.
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.
Pitney BowesInc. (2011, 11 10). Global Online Shopping Survey White Paper. Retrieved 10 24, 2012, from Pitney Bowes: http://news.pb.com/article_download.cfm?article_id=4896
Post, A., Shah, V., & Mislove, A. (2011). Bazaar: Strengthening user reputations in online marketplaces. Proc. of the 8th Symposium on Networked Systems Design and Implementation (NSDI’11). Boston, MA.
Purohit, D., & Srivastava, J. (2001). Effect of Manufacturer Reputation, Retailer Reputation, and Product Warranty on Consumer Judgments of Product Quality: A Cue Diagnosticity Framework. Journal of Consumer Psychology, 10(3), pp. 123-134.
Resnick, P., & Zeckhauser, R. (2002). Trust among strangers in internet transactions: Empirical analysis of eBay’ s reputation system. Advances in Applied Microeconomics, 11, pp. 127-157.
Resnick, P., Zeckhauser, R., Friedman, E., & Kuwabara, K. (2000). Reputation Systems. Communications of the ACM, 43(12), pp. 45-48.
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Steiner, D., 2003. Survey: How do users feel about eBay’s feedback system? Auction bytes-update, Number 87.
Utz, S., Matzat, U., & 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), 95.
Ye, Q., Li, Y., Kiang, M., & Wu, W. (2009). The impact of seller reputation on the performance of online sales: Evidence from TaoBao buy-it-now (BIN) data. 40(1), pp. 12-19.
Zaichkowsky, J. L. (1994). The personal involvement inventory: Reduction, revision. Journal of Advertising, 23(4), p. 59.
Zhou, M., M., D., & Windle, R. J. (2008). Online reputation systems: Design and strategic practices. Decision Support Systems, 44(4), pp. 785-797.
描述 碩士
國立政治大學
資訊管理研究所
100356033
101
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0100356033
資料類型 thesis
dc.contributor.advisor 管郁君<br>林淑瓊zh_TW
dc.contributor.author (Authors) 謝宜廷zh_TW
dc.creator (作者) 謝宜廷zh_TW
dc.date (日期) 2012en_US
dc.date.accessioned 1-Oct-2013 11:59:22 (UTC+8)-
dc.date.available 1-Oct-2013 11:59:22 (UTC+8)-
dc.date.issued (上傳時間) 1-Oct-2013 11:59:22 (UTC+8)-
dc.identifier (Other Identifiers) G0100356033en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/61183-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊管理研究所zh_TW
dc.description (描述) 100356033zh_TW
dc.description (描述) 101zh_TW
dc.description.abstract (摘要) 網路市集中，網路評價系統扮演著重要角色在於買、賣雙方之間的信任建立，消費者往往仰賴網路評價系統協助購買決策的制訂，因此網路賣家必需認真看待買家給予的評價。然而，我們也不意外各式各樣的評價操弄行為開始出現於許多的網路市集中。僅管大多數操弄方式以隨機方式出現並且迅速的消失，其中一種具系統化且時常出現的操弄方式為賣家透過公告提醒事項試圖影響買家的評價，透過這些提醒事項去誘導買家留下正面評價或是禁止負面評價的產生。此研究提出一個研究設計用來檢視賣家的操弄行為對於評價系統之評價分數與評論取向的影響，而所提出研究架構將賣家的操弄行為分成三類分別為利誘、拒絕與無操弄。本研究選擇中國最大的網路市集─ 淘寶網用來衡量研究架構。
研究結果顯示在賣家的操弄下，僅有評價分數會受到影響進而在三組間造成顯著差異，然而，賣家的操弄與買家經驗的交互作用會影響評論取向與好評率，在賣家的操弄的三種類型中產生顯著差異。由此可知，買家經驗確實在賣家的操弄與買家評價之間有調節的作用。僅管研究結果顯示賣家的操弄確實影響了評價分數，但也更突顯出評論內容可能包含了更具價值的資訊，因此消費者不僅可以依據評價分數更可參考評論內容選擇賣家進行購買。		zh_TW
dc.description.abstract (摘要) Online evaluation systems play an important role in creating trust between sellers and buyers in online marketplaces. Consumers often rely on these evaluations when making purchase decisions. As a result, sellers need to take buyers’ evaluations seriously. However, evaluation manipulation occurs in many online marketplaces. Various types of manipulation are apparent. Although most appear to be spurious and disappear rather quickly, many sellers engage in systematic evaluation manipulation by constantly posting reminders to influence buyers’ evaluations. The reminders generally aim to prompt a positive rating or prohibit a negative rating. This study examines the influence of seller manipulation on rating scores and comment orientation in an evaluation system. The research framework categorizes three types of seller manipulation: allurement, rejection and none. Taobao.com, the largest online marketplace in China, is used to evaluate the proposed model.
The results show that seller manipulation only influences rating scores. However, the interaction between seller manipulation and buyer experience influences both the orientation of comments and the percentage of positive ratings, which leads to significant differences among the three types of seller manipulation. Buyer experience mediates the relationship between seller manipulation and buyer evaluation. Although rating scores are influenced by seller manipulation, comments tend to contain much more valuable information. It is thus suggested that consumers rely on rating scores and comments when making purchase decisions.		en_US
dc.description.tableofcontents CHAPTER 1 INTRODUCTION 1
CHAPTER 2 LITERATURE REVIEW 6
2.1 Online Marketplaces 6
2.2 Evaluations and Evaluation Systems 8
2.3 Evaluation Manipulation 11
2.4 Percentage of Positive Ratings and Comment Orientation 17
2.5 Buyer Experience 18
CHAPTER 3 RESEARCH METHOD 20
3.1 Hypotheses and Research Model 20
3.2 Data Collection and Sampling 24
3.3 Measurement 26
3.3.1 Research Variables and Definition 27
3.3.2 Measurement of Buyer Experience 27
3.3.3 Constructing a Preliminary Scale 28
3.4 Data Analysis 29
3.5 Pretesting and initial item reduction 31
CHAPTER 4 RESULTS 35
4.1 Sampling Data 35
4.1.1 Seller Evaluation Data 35
4.1.2 Coder Recruitment 37
4.2 Measurement Model 42
4.3 Hypothesis Testing 44
4.3.1 MANOVA and ANOVA analysis 45
4.3.2 ANOVA analysis results 47
4.3.3 PERCENTAGE OF POSITIVE RATINGS 47
4.3.4 COMMENT ORIENTATION 51
4.4 Discussion 55
CHAPTER 5 CONCLUSION 59
5.1 Conclusion and Management Implications 59
5.2 Limitations and Future Research 61
APPENDIX A 64
APPENDIX B 67
APPENDIX C 70
REFERENCES 72		zh_TW
dc.format.extent 1463159 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0100356033en_US
dc.subject (關鍵詞) 網路評價系統zh_TW
dc.subject (關鍵詞) 評價分數zh_TW
dc.subject (關鍵詞) 評論取向zh_TW
dc.subject (關鍵詞) 評價操弄zh_TW
dc.subject (關鍵詞) Online evaluation systemen_US
dc.subject (關鍵詞) Rating scoreen_US
dc.subject (關鍵詞) Comment orientationen_US
dc.subject (關鍵詞) Manipulationen_US
dc.title (題名) 網路市集賣家影響下的評價分數與評論取向zh_TW
dc.title (題名) Rating Score and Comment Orientation under the Influence of Online Marketplace Sellersen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 淘寶論壇-小昭(2012年12月7日)。人民日報：淘寶首例“惡意差評師”案告破 7人涉嫌敲詐被捕【線上論壇】。取自 http://bbs.taobao.com/catalog/thread/508895-259867086.htm?spm=0.0.0.228.dy7IRn
About Taobao.com. Taobao.com, Retrieved 12 30, 2012, from http://www.taobao.com/about/intro.php?spm=0.0.21637.8.iev5J2
Akerlof, G. A. (1970, 8). The Market for "Lemons": Quality Uncertainty and the Market Mechanism. The Quarterly Journal of Economics, 84(3), pp. 488-500.
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.
Bagozzi, R. P., & Yi, Y. (1988). On the Evaluation of Structural Equation Models. Academy of Marketing Science, 16(1), pp. 74-94.
Bolton, G. E., Katok, E., & Ockenfels, A. (2004). How effective are electronic reputation mechanisms? An experimental investigation. Management Science, 50(11), pp. 1587-1602.
Company Overview, Alibaba group, Retrieved 01 04, 2013, from, http://news.alibaba.com/specials/aboutalibaba/aligroup/index.html
Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal Of Applied Psychology, 78(1), pp. 98-104.
David, A. G. (1984). What does "product quality" really mean? Sloan Management Review (Pre-1986), 26(1), p. 25.
Dellarocas, C. (2003). The digitization of word of mouth: Promise and challenges of online feedback mechanisms. Management Science, 49(10), pp. 1407-1424.
Dini, F., & Spagnolo, G. (2009). Buying reputation on eBay: Do recent changes help? International Journal of Electronic Business, 7(6), pp. 581-598.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 328-388.
Gregg, D. G., & Scott, J. E. (2006). The role of reputation systems in reducing on-line auction fraud. International Journal of Electronic Commerce, 10(3), pp. 95-120.
Gregg, D. G., & Scott, J. E. (2008). A TYPOLOGY of COMPLAINTS ABOUT EBAY SELLERS. Association for Computing Machinery. Communications of the ACM, 51(4), pp. 69-74.
Hair, Joseph F., Tatham, Ronald L., Anderson, Rolph E., Black, William. (1998). Multivariate Data Analysis. 5th edition, Prentice-Hall, NJ, USA.
Hinkin, T. R. (1998). A brief tutorial on the development of measures for use in survey questionnaires. Organizational Research Methods, 1(1), 104-121.
Ho, H.-h. (1998). Hong Kong, Mainland China & Taiwan: Chinese Character Frequency A Trans-Regional, Diachronic Survey. Retrieved 11 26, 2012, from http://humanum.arts.cuhk.edu.hk/Lexis/chifreq/
Hu, N., Bose, I., Gao, Y., & Liu, L. (2011, 2). Manipulation in digital word-of-mouth: A reality check for book reviews. Decision Support Systems, 50(3), pp. 627-635.
Hu, N., Bose, I., Koh, N. S., & Liu, L. (2012). Manipulation of online reviews: An analysis of ratings, readability, and sentiments. Decision Support Systems, 52(3), pp. 674-684.
Hu, N., Liu, L., & Sambamurthy, V. (2011, 2). Fraud detection in online consumer reviews. ecision Support Systems, 50(3), pp. 614-626.
Huang, Y., Chen, J., & Lu, W. (2011). Effects of seller reputation on success at online auctions: An empirical study. International Journal of Management, 28(3), pp. 621-629.
iResearch. (2012, 7 27). 艾瑞咨询：2012Q2中国网络购物市场交易规模2683.7亿元 增长超预期. Retrieved 10 14, 2012, from iResearch: http://www.iresearch.com.cn/View/177754.html
Kim, J., & Gupta, P. (2012, 7). Emotional expressions in online user reviews: How they influence consumers’ product evaluations. Journal of Business Research, 65(7), pp. 985-992.
Kusumasondjaja, S., Shanka, T., & Marchegiani, C. (2012). Credibility of online reviews and initial trust: The roles of reviewer’s identity and review valence. Journal of Vacation Marketing, 18(3), pp. 185-195.
Li, C.-F. (2010, 4). Understanding effects of seller’s and bidder’s characteristics on Internet auction applications. Expert Systems with Applications, 37(4), pp. 3462-3467.
MacInnes, I., Li, Y., & Yurcik, W. (2005). Reputation and dispute in eBay transactions. International Journal of Electronic Commerce, 10(1), pp. 27-54.
Malicious poor ratings Division gang crime law experts: three extortion can be admitted criminal, VentureData.org, Retrieved 01 04, 2013, from, http://www.venturedata.org/?i448761_Malicious-poor-ratings-Division-gang-crime-law-experts-three-extortion-can-be-admitted-criminal
Maxwell, J. G., & Hudson, M. (2011, 12). Multi-channel shopping: The future is now. Retrieved 10 14, 2012, from PwC: http://www.pwc.com/gx/en/retail-consumer/retail-consumer-publications/global-multi-channel-consumer-survey/2011-multi-channel-survey.jhtml
McDonald, C. G., & Slawson, V. C. (2002). Reputation in an internet auction market. Economic Inquiry, 40(4), pp. 633-650.
Melnik, M. I., & Alm, J. J. (2002). Does a Seller’s eCommerce Reputation Matter? Evidence from eBay Auctions. Journal of Industrial Economics, 50(3), pp. 337-349.
Oberholzer-Gee, F., & Wulf, J. M. (2009, 1 6). Alibaba’s Taobao (A). http://www.cases.nccu.edu.tw/harvard/tw/02/product01.aspx?ppno=9-709-456.
Park, C., & Lee, T. M. (2009). Information direction, website reputation and eWOM effect:. Journal of Business Research, 62, pp. 61-67.
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.
Pitney BowesInc. (2011, 11 10). Global Online Shopping Survey White Paper. Retrieved 10 24, 2012, from Pitney Bowes: http://news.pb.com/article_download.cfm?article_id=4896
Post, A., Shah, V., & Mislove, A. (2011). Bazaar: Strengthening user reputations in online marketplaces. Proc. of the 8th Symposium on Networked Systems Design and Implementation (NSDI’11). Boston, MA.
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