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研究生: 蘇仲琦
Su, Chung-Chi
論文名稱: 網路知覺風險、折扣幅度、下標人數對消費者參與網路集殺態度及購買意願的影響
The Effect of Online Perceived Risk, Discount Level, and Number of Bidders on Attitude toward Engaging in Group Buy and Purchase Intention
指導教授: 賴孟寬
Lai, Meng-Kuan
學位類別: 碩士
Master
系所名稱: 管理學院 - 企業管理學系
Department of Business Administration
論文出版年: 2006
畢業學年度: 94
語文別: 英文
論文頁數: 85
中文關鍵詞: 下標人數折扣數參與網路集殺態度購買意願網路知覺風險網路集殺網路集購
外文關鍵詞: Group Buy, Attitude toward Engaging in Group Buy, Discount Level, Purchase intention, Online Perceived Risk, Number of Bidders
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  • 網路集殺就是網路集體殺價的意思,透過網路集結消費者,只要湊足目標人數就可以打破市場行情的最低價格購買集殺商品。集體殺價不僅可以讓消費者低價購買商品,對賣家來說也可在短時間內確定商品需求數量,減低存貨成本。

    本研究主要探討網路知覺風險、折扣數及下標人數等變數對消費者參與集殺態度的影響。由於網路集殺實質運作上,折扣數的多寡取決於下標人數的多寡,而為了檢視折扣數與下標人數對消費者的各別影響效果,因此本研究細分為兩研究進行,研究一主要探討網路知覺風險與折扣數對消費者參與態度的影響,研究二則著重在下標人數對消費者參與態度的影響,研究結果如下所示:

    1.網路知覺風險低的受測者對於參與網路集殺持較正面的態度。

    2.當折扣數到達對低折扣-75折時,消費者參與網路集殺的態度反應較好。

    3.對於網路知覺風險高的受測者而言,知覺風險對於態度所帶來的負面影響將隨著折扣數的降低而減低。

    4.由於網路知覺風險低的受測者較可能在網路上購物,因此下標人數對此類受測者而言,是正向、重要且具參考性的訊息。

    5.當受測者對於參與網路集殺持較正面的態度時,其購買意願也相對較高。

    The purpose of the study is to investigate consumers’ attitude toward the new way of online purchasing—Group Buy-- individual buyers bid on ones own, but bargain as a group. Two studies were carried out to test the hypotheses. Study I focuses on investigating the impacts of online perceived risk, discount level.

    A 2 (discount level: high discount vs. low discount) x 2 (perceived risk: high vs. low) factorial design was used. Study II is to examine the effect of number of bidders. A 2 (perceived risk: high vs. low) x 2 (number of bidders: high vs. low) factorial design was used.

    The results are as following.

    First, respondents with low online perceived risk would generate more positive attitude toward engaging in Group Buy, compared to high online perceived risk respondents.

    Second, when the Group Buy price has reached its maximum discount--25% off (in Study I)--, respondent would be more willing to engage in it.

    Third, for respondents with high online perceived risk, the impact of online perceived risk would be lessen when the discount increase.

    Fourth, number of bidders is positive influential information for respondents with low online perceived risk, who is more likely to shop online. Finally, respondents who possess more positive attitudes toward engaging in Group Buy will also have greater purchase intention.

    CHPATER I INTRODUCTION 1 CHPATER II LITERATURE REVIEW 6 Group Buy 6 Study One 7 Online Perceived Risk 7 Price Discount 10 Attitude toward Group Buy and Purchase Intention 12 Study One Conceptual Model 14 Study Two 15 Number of Bidders 15 Contrast Effect and Assimilation Effect 16 Study Two Conceptual Model 18 CHPATER III METHODOLOGY 19 Product Selection 19 Operational Definition of Variables 20 Independent Variables 20 Moderating Variable 23 Dependent Variables 24 Research Design 27 Study One 27 Study Two 28 Pretest 28 Sample 28 Procedure 29 Results 29 Experimental Material Modifications 31 Formal Data Collection 37 Sampling 37 Procedures 37 Measurements 37 CHPATER IV RESULTS AND DISCUSSION 38 Study I 38 Data Processing 38 Data Coding 39 Reliability and Validity 41 Hypotheses Testing 46 Conclusions 55 Study II 58 Data Processing 58 Data Coding 59 Reliability and Validity 61 Hypotheses Testing 64 Conclusions 71 CHPATER V GENERAL DISSCUSSIONS 73 Conclusions 73 Empirically Tested Model 75 Research Contributions 76 Limitations and Suggestions for Future Research 80 REFERENCE 82

    Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50 (2), 179-211.

    Alford, B. L. & Biswas, A. (2002). The effects of discount level, price consiciousness and sale proneness on consumers’ price perception and behavioral intention. Journal of Business Research, 55, 775-783.

    Baron, R M. & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.

    Bhatnagar, A. & Ghose, S. (2004). Segmenting consumers based on the benefits and risks of Internet shopping. Journal of Business Research, 57, 1352-1360.

    Biswas, A., Pullin, C., Krishnan, B.C. & Burton, S. (1999). Consumer evaluation of Reference Price Advertisements: Effects of Other Brands’ Prices and Semantic Cues. Journal of Public Policy & Marketing, 18(1), 52-65.

    Chandrashekaran, R. & Grewal D. (2003). Assimilation of advertised reference prices: The moderating role of involvement. Journal of Retailing, 79 (1), 53-62.

    Chen, J., Chen, X. & Song, X. (2002). Bidder’s Strategy Under Group-Buying Auction on the Internet. IEEE Transactions on System, Man and Cybernetics-part A: Systems and Humans, 32(6), 680-690.

    Chen, Z. & Dubinsky, A. J. (2003). A conceptual model of perceived customer value in e-commerce: A preliminary investigation. Psychology &Marketing, 20(4), 323-347.

    Corbitt, B. J., Thanasankit, T. & Yi, H. (2003). Trust and e-commerce : A study of consumer perceptions. Electronic Commerce Research and Applications, 2, 203-215.

    Darke, P. R. & Chung, Cindy M. Y. (2005). Effects of pricing and promotion on consumer perceptions: It depends on how you frame it. Journal of Retailing, 81(1), 35-47.

    DeVellis, R. F. (1991). Social Development: Theory and Applications, Newbury Park , CA: Sage.

    Dholakia, U. M. & Soltysinski, K. (2001). Coveted or overlooked? The psychology of bidding for comparable listings in digital auctions. Marketing Letters, 12(3), 225-237.

    Doolin, B., Dillon, S., Thompson, F. & Corner, J. L., (2005). Perceived risk, the Internet shopping experience and online purchasing behavior: A New Zealand perspective. Journal of Global Information Management, 13(2), 66-88.

    Dowling, G. R. (1986). Perceived risk: The concept and its measurement. Psychology & Marketing, 3(3), 193-210.

    Drozdenko, R. & Fensen M., (2005). Risk and maximum acceptable discount level. Journal of Product & Brand Management, 14(4), 264-270.

    Forsythe, S. M. & Shi, B., (2003). Consumer patronage and risk perceptions in Internet shopping. Journal of Business Research, 56, 867-875.

    Garbarino, E. & Strahilevitz, M. (2004). Gender differences in the perceived risk of buying online and the effects of receiving a site recommendation. Journal of Business Research, 57, 768-775.

    Guo, C. (2001). A Review on Consumer External Search: Amount and Determinants. Journal of Business and Psychology, 15(3), 505-519.

    Jacoby, J. & Kaplan, L.B. (1972). The components of perceived risk. Annual Conference of the Association for Consumer Research, M. Venkatesan, ed. Chicago: Association for Consumer Research, 382-393.

    Jarvanpaa, S. L. & Todd, P. A. (1996). Consumer reactions to electronic shopping on the World Wide Web. International Journal of electronic Commerce, 1(2), 59-88.

    Levin, A. M. (2002). Contrast and assimilation processes in consumers’ evaluation of dual brands. Journal of Business and Psychology, 17 (1), 145-154.

    Lim, H. & Dubinsky, A. J. (2005). The theory of planned behavior in e-commerce: Making a case for Interdependencies between salient beliefs. Psychology & Marketing, 22(10), 833-855.

    Lim, N. (2003). Consumer’ perceived risk: sources versus consequences. Electronic Commerce Research and Application, 2, 216-228.

    Matsuo, T., & Ito, T. (2003). A Group Formation Support System Based on Substitute Goods in Group Buying. Systems and Computers in Japan, 35(10), 762-772.

    Meyers-Levy, J. & Tybout, A. M. (1997). Context effects at encoding and judgment in consumption settings: The role of cognitive resources. Journal of Consumer Research, 24(1), 1-14.

    Miyazaki, A. D., & Fernandez (2001). Consumer perceptions of privacy and security risks for online shopping. The Journal of Consumer Affairs, 35 (1), 27-44.

    Monsuwe, T. P. y, Dellaert, B. G.. C. & Ruyter, Ko de (2004). What drives consumers to shop online? A literature review. International Journal of service Industry Management, 15(1), 102-121.

    Park, J., Lee, D. and Ahn, J. (2004). Risk-focused e-commerce adoption model: Across-country study. Journal of Global Information Technology Management, 7(2), 6-30.

    Roselius, T. (1971). Consumer rankings of risk reduction methods. Journal of Marketing, 35, 56-61.

    Sharma, S. (1996). Applied Multivariate Techniques. New York:J. Wiley.

    Sherif, M. and Hovland, C. (1961). Social judgment: Assimilation and Contrast effects in communication and attitude change. New Haven, CT: Yale University Press.

    Stern, B.B. & Stafford, M.R. (2006). Individual and social determinants of winning bids in online auctions. Journal of Consumer Behavior, 5, 34-55.

    Strader, T. J. & Shaw, M. J. (1999). Consumer cost difference for traditional Internet markets. Internet research: Electronic Networking Applications and Policy, 9(9), 82-92.

    Tan, S. J. (1999). Strategies for reducing consumers risk aversion in Internet shopping. Journal of consumer Marketing, 16(2), 163-180.

    Taylor Nelson Sofres Interactive. (2002, June 6). E-Tailers Fail To Persuade Users To Buy Online Global Survey Findings. Retrieved July 6, 2006 form http://www.tns-global.com/corporate/Doc/0/LSQLFB70TNT471UITF13B6B261/590.htm

    Tepper, K., Lichtenstein, D. R. & Green, C. (1996). Influences on consumer response to preferred consumer programs. Pricing strategy &Practice, 4(4), 14-24.

    Thaler, R. (1985). Mental accounting and consumer choice. Marketing science, 4(3), 199-214.

    Ueltschy, L. C., Krampf, R. F. & Brock,P. Y. (2004). A cross-national study of perceived consumer risk towards online purchasing. The Multonational Business Review, 12(2), 59-82.

    Wood, C. M. & Scheer, L. K. (1996). Incorporating perceived risk into models of consumer deal assessment and purchase Intent. Advances in Consumer Research, 23, 399-404.

    Zaichowsky, J. L. (1985). Measuring the Involvement construct. Journal of Consumer research, 12 (December), 341-352.

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