493 2020 Ajzen 275 (SEM) (PLS) 1. 1.1 2020 ( 2007) 2006ErnstYoung 700 734 2005 14% 2010 1,000 (2007 ) 2002 2008 97 460 ( 2007) 2006 (2006)... TPB Ajzen(1985) (Theory of Planned Behavior, TPB) 1.2
2. 2.1 2.1.1 (biotechnology) Karl Ereky1917 ( 20052006) (The Convention on Biological Diversity) ( 2006) 1984 (Office of Technology Assessment,OTA) 1998OTA (Monoclonal Antibody) ( 2003) (2007) (biologic process) (cell) (molecule) ( 2003) 1. 2. 3. 4. 5. 6. 7. 8. ( 2.1 ( 2007) ( ) ( ) ( ) 494
2.1.2 2.1 (2001) (2005) 2.2 2.2.1 (TPB)(Ajzen, 1985) (Theory of Planned Behavior, TPB)Ajzen(1985) (TRA) (TPB) (Ajzen, 1988) (attitude toward the behavior, AT) (subjective norm, SN) (PBC) 2.2 2.2.2 AT SN BI PBC 2.2 Ajzen(1988) (Rousseau, Sitkin, Burt, & Camerer, 1998Gambetta, 1998) (2002) Hosmer(1995) 495 B
(2.1) 2.1 Hosmer(1995) (Doney & Cannon, 1997) (Hosmer, 1995) 2.2.3 (perceived risk) Bauer(1960) (perceived risk) (Risk taking) (2005) Bauer (Mitchell, 1999Stone & Gronhaug, 1993)Cox (1967) Cunningham(1967) (hierarchy) Cox (1967) Cunningham (1967) (Dowling & Staelin, 1994) 3. 3.1 Azjen(1985) 3.1 496
3.1 H2 H1 H3 H4 H5 H1 H2 H3 H4 H5 3.1 3.1 3.2 298 11 ( ) 25 275 41 234 85.51% 3.3 3.3.1 Urala Lahteenmaki(2004) (2006) (1) (2) (3) 3.3.2 ( ) SchiffmanKanuk(2000) (primary group) (secondary group) ( ) 3.3.3 Taylor Todd(1995) (self-efficacy) (facilitating conditions) (Self-Efficacy) 497
(Ajzen, 1989) ( 2004) (2004) 3.3.4 Ganesan(1994) (cerdibility) (benevolence) ( 2004) Ganesan(1994) 3.3.5 Roselius(1971) ( ) 11 6 3.3.6 ZeithamlBerry Parasuraman (1996) (loyalty) (sewitch) (pay more) (external response) (internal (2004) 3.4 3.4.1 (descriptive analysis) ( ) ( ) ( ) ( ) ( ) ( ) 3.4.2 (Structural Equation Modeling, SEM) (Byrne,1994) SEM SEM (path anaysis) ( 2007)SEM SEM 1970 (Joreskog, 1973Keesling, 1972Wiley,1973) 1980 (Hoyle, 1995)SEM (structural) (hypothesized equation) (modeling) 498
SEM ( 2007)(1) (hypothesis -testing) (2) (structural confirmatory) (3) (modeling analysis and comparison) AMOS (SEM) AMOS AMOS AMOSSPSS 3.4.3 (Partial Least Squares regression, PLS) (partial least squares regression, PLS) 20 60 Wold 90 PLS (ordinary least squares regression, OLS) OLS ( 2002) PLS PLS ( 2007)PLS ( R 2 ) PLS (Composite Reliability; CR) (average variance extracted; AVE) CR 0.7 AVE 0.5 (Fornell & Larcker,1981) R 2 (path coefficients) 4. 4.1 ( ) ( ) ( ) 11 1 25 234 2008228 2008412 234 (43.59%) (25.64%) (21.37%) (19.66%) / (15.38%) (14.10%) / (12.82%) (10.26%) Oligo (8.12%) / (5.13%) (4.70%) / (3.42%) (0.85%) 5 1 10 1 Oligo 4 30 499
4 4.2 4.2.1 ( X1X2X3) ( X4X5X6) ( X7X8X9) X3X4X9(1) SMC 0.58~0.78 (SMC0.4) CR 0.79~0.81 (CR 0.6) VE 0.66~0.68 (VE0.5) 9 (X1~X9) X3X4 X9 (2) 2 / 5.39 1.97( 2 / 3)GFI0.94 0.98(GFI0.9)AGFI0.85 0.94(AGFI0.8)CFI0.95 0.99(CFI 0.9)RMSEA 0.14 0.06(RMSEA 0.1) X3X4X9 (X1X2X5 X6X7X8) 4.2.2 ( X10X11X12) ( X13X14X15) X13(1) SMC 0.45~0.82 (SMC0.4) CR 0.84~0.87 (CR0.6) VE 0.64~0.76 (VE0.5) 6 (X10~X15) X13 (2) 2 / 24.97 2.17( 2 / 3)GFI0.83 0.99(GFI0.9)AGFI0.49 0.95(AGFI0.8)CFI0.80 0.99(CFI0.9)RMSEA 0.32 0.07(RMSEA 0.1) X13 (X10X11X12X14X15) 4.2.3 ( X16X17X18) ( X19X20X21) (1) SMC 0.51~0.77 (SMC0.4) CR 0.83~0.85 (CR0.6) VE 0.61~0.65 (VE0.5) 6 (X16~X21) (2) 2 / 5.84 1.44( 2 / 3)GFI 0.93 0.99(GFI0.9)AGFI0.83 0.96(AGFI0.8)CFI0.94 0.99(CFI0.9)RMSEA 0.15 0.04(RMSEA 0.1) (X16~X21) 4.2.4 ( X22X23X24X25X26) ( X27X28X29) ( X27X28X29) SMC 0.59~0.76 (SMC0.4) CR 0.91(CR0.6) VE 0.67(VE0.5) 8 (X22~X29) (X27X28X29) 4.2.5 ( X30X31X32 X33X34X35) SMC 0.50~0.79 (SMC 500
0.4) CR 0.89(CR0.6) VE 0.68(VE0.5) 6 (X30~X35) X33X34 4.2.6 X36X37X38X39 X39 SMC 0.50~0.88 (SMC0.4) CR 0.90(CR0.6) VE 0.75(VE0.5) 4 (X36~X39) X39 4.3 4.1 2 P =0.00 Chin and Todd(1995) 2 / 2 2.29( 2 / 3) GFI 0.8AGFI 0.76 CFI 0.91 RMSEA 0.07 AGFI(0.76) MacCallum and Hong(1997) (AGFI0.8) 4.1 2 817.79(P0.01) 2 / 2.29 3 GFI.80 0.80 AGFI.76 0.80 CFI.91 0.90 RMSEA.07 0.1 SEM ( ) R 2 =0.64 5 5 4.2 4.2 C.R. P.69.13.90.58 -.10 -.07.94 -.49.40.31.76.31 0.5.08.93.04.61.44.70.52 ( ) (0.36) ( ) PLS RingleWende Will(2005) SmartPLS PLS (partial least squares regression, PLS) SmartPLS 2.0 SmartPLS 2.0 1. 4.3 CR Fornell and Larcker(1981) CR 0.6 CR 0.7 AVE 0.5 R 2 0.626 Cronbachs Alpha 0.7 501
AVE 4.3 Composite Reliability R Square Cronbachs Alpha 0.626 0.892 0.855 0.734 0.932 0.910 0.654 0.919 0.894 0.758 0.926 0.893 0.822 0.933 0.626 0.891 0.639 0.914 0.887 2. 4.1 =0.05 1 3 5 135 1.262 2.598** R 2 =0.626 2.325* 0.567 6.040** 5. 4.1 (T ) SEM PLS [1] 2007 [2] 2007 2007 502
[3] 38(8 [4]PLS 19(2)pp. 76-7 [5] 2005 [6] 200 [7] 2003 2003 [8] - 22 2001 [9] 2004 [10] PLS 457pp. 13-232007 [11] SPSS 2007 [12] 4pp. 33-462005 [13] - 23(3) pp. 22-242006 [14] -SPSS 200 [15] 2007 [16] 2002 [17] 2006 [18] 2003 [19] - 2004 [20] 1998 [21] 2007 7 20 http://tie.tier.org.tw/tie/index.jsp [22] 2007 7 25 http://www.biopharm.org.tw/ [23] 20072007 10 9 http://www.healthliving.com/product/bp1-00.htm [24] 20052007 8 29 http://www.functionalfood.org.tw/ [25]Ajzen, I., From intentions to actions: A theory of planned behavior, in J. Kuhl & J. Beckmann(eds.), Action-control: from cognition to behavior(springer series in social psychology), Heidelberg: Springer, pp. 11-39, 1985. [26]Ajzen, I., Attitude, personality, and behavior, Milton Keynes: Open University Press, 1988. [27]Bauer, R. A., Consumer behavior as risk taking, in R. S. Hancock( ed.), Dynamic Marketing for a Changing World, Chicago: America Marketing Association, pp. 389-398, 1960. [28]Byrne, B. M., Structural equation modeling with EQS and EQS/Windows, Newbury Park, CASage, 1994. [29]Chin, W. W. and P. Todd, On the use, usefulness, and ease of use of structural equation modeling in MIS research: A note of caution, MIS Quarterly, Vol. 19, No. 2, pp. 237-246, 1995. [30]Cox, D. F., Risk handling in consumer behavior-an intensive study of two cases, in Donald F. Cox (ed.), Risk taking and information handling in consumer behavior, Boston: Harvard University Press, pp. 34-81, 1976. [31]Cunningham, S. M., The major dimension of perceived risk, in Donald F. Cox (ed.), Risk Taking and Information Handling in Consumer Behavior, Boston: Harvard University Press, pp. 82-108, 1976. [32]Doney, P. M. and J. P. Cannon, An Examination of the Nature of Trust in Buyer-Seller Relationship, Journal of 503
Marketing, Vol. 61, pp. 35-51, 1997. [33]Dowling, G. R. and R. Staelin, A model of perceived risk and risk-handling activities, Journal of Consumer Research, Vol.21, No. 6, pp. 119-134, 1994. [34]Fornell, C. and D. F. Larcker, Evaluating structural equation models with unobservableand measurement errors, Journal of Marketing Research, Vol. 18, pp. 39-50, 1981. [35]Ganesan, S., Determinations of Long-term Orientation in Buyer-Seller Relationships, Journal of Marketing, Vol. 58, pp. 1-19, 1994. [36]Hosmer, L. T., Trust: The connecting link between organizational theory and Philosophical Ethics, The Academy of Management Review, Vol. 20, No. 2, pp. 399, 1995. [37]Joreskog, K. G., A general method for estirmating a linear structural equation system. In A. S. Goldberger & O. D. Duncan(Eds.), Structural equation models in the social science (pp. 85-112). New YorkAcademic, 1973. [38]Keesling, J. W., Maximum likelihood approaches to causal analysis. Unpublished doctiral dissertatition. University of Chicago, 1972. [39]MacCallum, R. C. and S. Hong, Power analysis in covariance structure modeling using, Multivariate Behavioral Research, Vol. 32, No. 2, pp. 193-210, 1997. [40]Mitchell, V., Consumer perceived risk: Conceptualizations and models, European of Marketing, Vol.33, No.1/2, pp. 163-195, 1999. [41]Rousseau, D., S. B. Sitkin, R. Burt, and C. Camerer, Not so Different After All: A Cross-Discipline View of Trust, The Academy of Management Review, Vol.23, No. 3, pp. 393-404, 1998. [42]Roselius, T., Consumer rankings of risk reduction methods, Journal of Marketing, Vol.35, No1, pp. 56-61, 1971. [43]Ringle, C. M., S. Wende, and A. Will, SmartPLS Version 2.0, Universit at Hamburg, Hamburg, 2005. [44]Stone, R. N. and K. Gronhaug, Perceived risk: Further considerations for the marketing discipline, European Journal of Marketing, Vol.27, No. 3, pp. 39-50, 1993. [45]Schiffman, L. G. and L. L. Kanuk, Consumer Behavior, 7 th ed, New Jersey: Prentice Hall, Inc, 2000. [46]Taylor, S. and P. Todd, Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions, International Journal of Research in Marketing, Vol. 12, pp. 137-155, 1995. [47]Urala, N. and L. Lahteenmaki, Attitudes behind consumers willingness to use functional foods, Food Quality and Preference, Vol. 15, No. 7-8, pp. 793-803, 2004. [48]Wiley, D. E., The identification problem for structural equation models with unmeasured variables. In A. S. Goldberger & O. D. Duncan(Eds.), Structural equation models in the social science (pp. 69-83). New YorkAcademic, 1973. [49]Zeithaml, V. A., L. L. Berry, and A. Parasuraman, The Behavioral Consequences of Service Quality, Journal of Marketing, Vol.60, pp.33-46, 1996. 504