2011 ( ) ( ) ( ) ( ) 1. 2. 3. Abstract Due to the market of online shopping has became competitive to threaten the market of traditional shopping way in the recent years, retail industries and shopping malls both run all kinds of sales promotions to achieve better sales in a short period of time, in order to inspire more purchase intention. However, the method of doing online shopping is different from the traditional shopping way, consumers can not touch the products and the intangible payments also have risk in terms of uncertainty. Would the attitudes of consumers taking the risk can be an influential factor of purchase intention? Additionally, do consumers think over again and again when they toward many kinds of sales promotions? The study aims to explore the issue that customers only research product information from sellers or they also consider the information which come from celebrity, bloggers, and BBS so as to be a crucial factor to consumers? Does the information help consumers to choose products, reducing the risk of online shopping? The conclusions are: 1.There is a positive correlation between product information and purchase intention of online shopping. 2. The relationship of risk attitude and purchase intention of online shopping is inverse correlated. 3. Impulse buying and purchase intention of online shopping is positive correlated. Key words: risk Attitude, impulse buying, product information, purchase intention 1
2011 63.9% 26.4% 2010 9,816 1 3,864 2010 41.9% 53% 2009 67.6% 70.9% e Hur, Ko, and Valacich, 2007 1-1 2010 2 1,866 0.6% 3G 3.7% 82.3% 3G 1-1 2010 Gartner 1-1 2007 3 2 3 2012 4 9 9 2
2011 1-1 2007 2012 2007 2012 93% 97% 54% 77% 76% 81% 59% 74% 57% 75% 54% 77% / 2010 Hagel Armstrong 1998 64.9% MSN Facebook 50.3% Hansen et al., 2004 Allport 1937 Garble Joo 2000 3
2011 90.4% 1-2 25.3% 1-2 2010 90.4% 63% 25.3% 16.9% 17.6% 389 2009 61 1,397 260 1,418 1,727 Tan Thoen 2001 Cox 1967 1 2 Cunningham 1967 Cox Cunningham 4
2011 Rook 1987Beatty Ferrell 1998 50% Lawton, Kleban, Rajogopal & Dean, 1992;McConatha et al., 1994; Siegel, 1985 Kacen & Lee, 2002 Rook & Gardner, 1993 Hoch & Loewenstein, 1991; Thompsonet al., 1990 Hoch & Loewenstein, 1991; Rook, 1987; O Guinn & Faber, 1989 2003 2004 l 2 3 4 2004 1 2 3 4 5 6 7 8 9 1. 2. 3. 5
2011 6
2011 Dowling Staelin 1994 Kolesar & Galbraith, 2000Vijayasarathy Jones 1999 Chu, Choi, & Song, 2005 Roselius 1971 11 Crane Lynch 1988 Kotler 1997 Kotler 2006 Kolesar Galbrith 2000 H 1 Dholakia 2000 Shiv Fedorikhin 1999 Piron, 1991; Agee & Martin, 2001 2004 7
2011 2006 1 2 3 H 2 Chen & Tan, 2004 Kotler 1988 Koppelman Salomon Proussaloglou 1991 Schiffman Kanuk 2000 Dodds Monroe Grewal 1997 Engel Kollat Miniard 1995 Liebermann Flint-Goor 1996 Fishbein Ajzen 1975 8
2011 Lynch Ariely 2000 H 3 McKnight Choudhury Kacmar 2002 Lee Tan 2003Forsythe Shi 2003 expected utility theory prospect theory Kahneman & Tversky, 1979 S Garretson Clow 1999 Olsen 1998 Dikanpar Manash 1997 H 4 9
2011 Stem 1962 Beatty Ferrell 1998 Wood 1998 Mowen 1990 Nancarrow Bayley 1998 瀞 2006 Dholakia 2000 H 5 401 SPSS 12.0 Amos18 4-1 50.9 49.1 10
2011 ATM 18 18 18 18 21 73.3 22 25 83.3 15.7 BBS 359 89.5% 18 21 0~30 95.3 30 1~3 73.1% 4~6 20.7% 100~300 33.9% 400~600 30.4% 700~900 1000 22.4% 13.2% 4-1 197 49.1 204 50.9 18~21 294 73.3% 22~25 73 18.2% 26~29 23 5.7% 30 11 2.7% 63 15.7% 334 83.3% 4 1% 1 2% 4 1% 11
2011 2 0.5% 18 4.5% 359 89.5% 1 0.2% 16 4% 0~30 382 95.3% 31~60 14 3.5% 61~91 2 0.5% 100 3 0.7% 1~3 293 73.1% 4~6 83 20.7% 7~9 22 5.5% 10 3 0.7% 100~300 136 33.9% 400~600 122 30.4% 700~900 90 22.4% 1,000 53 13.2% Kaiser 1974 Kaiser-Meyer-Olkin measure of sampling adequacy ; KMO KMO KMO 0.5 4-2 KMO Bartlett 4-2 KMO Bartlett KMO Bartlett 0.669 0.000 0.658 0.000 0.853 0.000 12
2011 KMO Bartlett 0.717 0.000 Kaiser 1 Promax Method 4-9 4-3 2. 0.828 4. 1.907 0.775 6. 0.788 1. 0.78 2. 0.788 2.573 4.! 0.828 5. 0.811 2. 0.79 3. 0.787 4. 0.733 3.147 5. 0.843 6. 0.809 1. 0.782 2.527 2. 0.667 13
2011 3. 0.849 4. 0.865 4-10 Cronbach s α 0.8922~0.7943 0.7 Fornell Larcker 1981 0.5 0.849~0.711 0.5 Cronbach s α DeVeillis 1991 George Mallery 2003 Cronbach's α 0.7 Cronbach's α 0.5 Cronbach s α 0.7 4-4 Cronbach's α 0.8922 0.6237 0.711 0.8366 0.5648 0.810 0.8621 0.6126 0.849 0.7943 0.5657 0.799 4-5 0.181-0.167-0.072 H 1-0.122 14
2011 Agee Martin 2001 Dholakia 2000 H 2 4-5 -0.072 0.160-0.122* 0.021 *** <0.001 ** <0.01 * <0.05 4-6 -0.372 0.163 0.096 0.179 Chen and Tan 2004 Schiffman Kanuk 2000 H 3 McKnight Choudhury Kacmar 2002Forsythe Shi 2003 H 4 Beatty and Ferrell 1998Dholakia 2000 H 5 4-6 -0.372*** 0.000 0.163*** 0.000 0.096* 0.030 *** <0.001 ** <0.01 * <0.05 15
2011 T 16
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