ONEWAY EASERES RSKAUTH WTP_PUR BY BLOCKCH
/STATISTICS DESCRIPTIVES
/MISSING ANALYSIS
/CRITERIA=CILEVEL(0.95).
Oneway
Descriptives
| | N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum |
|---|
| Lower Bound | Upper Bound |
|---|
| EASERES | 0 | 153 | 5.0566 | .99103 | .08012 | 4.8984 | 5.2149 | 2.33 | 7.00 |
|---|
| 1 | 146 | 5.2146 | .99172 | .08208 | 5.0524 | 5.3768 | 2.00 | 7.00 |
|---|
| Total | 299 | 5.1338 | .99286 | .05742 | 5.0208 | 5.2468 | 2.00 | 7.00 |
|---|
| RSKAUTH | 0 | 153 | 4.9967 | .99587 | .08051 | 4.8377 | 5.1558 | 1.50 | 7.00 |
|---|
| 1 | 146 | 5.1130 | 1.05988 | .08772 | 4.9396 | 5.2864 | 2.00 | 7.00 |
|---|
| Total | 299 | 5.0535 | 1.02755 | .05942 | 4.9366 | 5.1705 | 1.50 | 7.00 |
|---|
| Willingness to Purchase (1-7) | 0 | 153 | 4.8627 | 1.52203 | .12305 | 4.6196 | 5.1059 | 1.00 | 7.00 |
|---|
| 1 | 146 | 5.1027 | 1.46560 | .12129 | 4.8630 | 5.3425 | 1.00 | 7.00 |
|---|
| Total | 299 | 4.9799 | 1.49707 | .08658 | 4.8096 | 5.1503 | 1.00 | 7.00 |
|---|
ANOVA
| | Sum of Squares | df | Mean Square | F | Sig. |
|---|
| EASERES | Between Groups | 1.864 | 1 | 1.864 | 1.897 | .169 |
|---|
| Within Groups | 291.896 | 297 | .983 | | |
|---|
| Total | 293.760 | 298 | | | |
|---|
| RSKAUTH | Between Groups | 1.010 | 1 | 1.010 | .957 | .329 |
|---|
| Within Groups | 313.634 | 297 | 1.056 | | |
|---|
| Total | 314.644 | 298 | | | |
|---|
| Willingness to Purchase (1-7) | Between Groups | 4.303 | 1 | 4.303 | 1.926 | .166 |
|---|
| Within Groups | 663.577 | 297 | 2.234 | | |
|---|
| Total | 667.880 | 298 | | | |
|---|
* Encoding: UTF-8.
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set printback=off.
Matrix
Run MATRIX procedure:
***************** PROCESS Procedure for SPSS Version 4.2 *****************
Written by Andrew F. Hayes, Ph.D. www.afhayes.com
Documentation available in Hayes (2022). www.guilford.com/p/hayes3
**************************************************************************
Model : 7
Y : WTP_PUR
X : BLOCKCH
M : RSKAUTH
W : TCHFAM
Sample
Size: 299
**************************************************************************
OUTCOME VARIABLE:
RSKAUTH
Model Summary
R R-sq MSE F df1 df2 p
.0828 .0069 1.0593 .6792 3.0000 295.0000 .5654
Model
coeff se t p LLCI ULCI
constant 5.1386 .2671 19.2395 .0000 4.6130 5.6643
BLOCKCH -.2338 .3671 -.6369 .5247 -.9564 .4887
TCHFAM -.0326 .0583 -.5591 .5766 -.1473 .0821
Int_1 .0818 .0808 1.0116 .3126 -.0773 .2408
Product terms key:
Int_1 : BLOCKCH x TCHFAM
Test(s) of highest order unconditional interaction(s):
R2-chng F df1 df2 p
X*W .0034 1.0232 1.0000 295.0000 .3126
----------
Focal predict: BLOCKCH (X)
Mod var: TCHFAM (W)
Data for visualizing the conditional effect of the focal predictor:
Paste text below into a SPSS syntax window and execute to produce plot.
DATA LIST FREE/
BLOCKCH TCHFAM RSKAUTH .
BEGIN DATA.
.0000 2.8178 5.0468
1.0000 2.8178 5.0433
.0000 4.2954 4.9986
1.0000 4.2954 5.1160
.0000 5.7731 4.9504
1.0000 5.7731 5.1886
END DATA.
GRAPH/SCATTERPLOT=
TCHFAM WITH RSKAUTH BY BLOCKCH .
**************************************************************************
OUTCOME VARIABLE:
WTP_PUR
Model Summary
R R-sq MSE F df1 df2 p
.4094 .1676 1.8782 29.8006 2.0000 296.0000 .0000
Model
coeff se t p LLCI ULCI
constant 1.9355 .4022 4.8119 .0000 1.1439 2.7271
BLOCKCH .1719 .1588 1.0823 .2800 -.1407 .4844
RSKAUTH .5858 .0774 7.5703 .0000 .4335 .7381
****************** DIRECT AND INDIRECT EFFECTS OF X ON Y *****************
Direct effect of X on Y
Effect se t p LLCI ULCI
.1719 .1588 1.0823 .2800 -.1407 .4844
Conditional indirect effects of X on Y:
INDIRECT EFFECT:
BLOCKCH -> RSKAUTH -> WTP_PUR
TCHFAM Effect BootSE BootLLCI BootULCI
2.8178 -.0020 .0936 -.1824 .1917
4.2954 .0688 .0723 -.0661 .2224
5.7731 .1395 .1188 -.0878 .3880
Index of moderated mediation:
Index BootSE BootLLCI BootULCI
TCHFAM .0479 .0533 -.0538 .1546
*********************** ANALYSIS NOTES AND ERRORS ************************
Level of confidence for all confidence intervals in output:
95.0000
Number of bootstrap samples for percentile bootstrap confidence intervals:
5000
W values in conditional tables are the mean and +/- SD from the mean.
------ END MATRIX -----
* Encoding: UTF-8.
preserve.
set printback=off.
Matrix
Run MATRIX procedure:
***************** PROCESS Procedure for SPSS Version 4.2 *****************
Written by Andrew F. Hayes, Ph.D. www.afhayes.com
Documentation available in Hayes (2022). www.guilford.com/p/hayes3
**************************************************************************
Model : 7
Y : WTP_PUR
X : BLOCKCH
M : RSKAUTH
W : TMPORIE
Sample
Size: 299
**************************************************************************
OUTCOME VARIABLE:
RSKAUTH
Model Summary
R R-sq MSE F df1 df2 p
.2174 .0472 1.0162 4.8764 3.0000 295.0000 .0025
Model
coeff se t p LLCI ULCI
constant 4.4303 .4202 10.5421 .0000 3.6032 5.2573
BLOCKCH -.8022 .6093 -1.3166 .1890 -2.0014 .3969
TMPORIE .1258 .0915 1.3740 .1705 -.0544 .3060
Int_1 .2070 .1334 1.5511 .1219 -.0556 .4696
Product terms key:
Int_1 : BLOCKCH x TMPORIE
Test(s) of highest order unconditional interaction(s):
R2-chng F df1 df2 p
X*W .0078 2.4060 1.0000 295.0000 .1219
----------
Focal predict: BLOCKCH (X)
Mod var: TMPORIE (W)
Data for visualizing the conditional effect of the focal predictor:
Paste text below into a SPSS syntax window and execute to produce plot.
DATA LIST FREE/
BLOCKCH TMPORIE RSKAUTH .
BEGIN DATA.
.0000 3.6063 4.8839
1.0000 3.6063 4.8282
.0000 4.4833 4.9942
1.0000 4.4833 5.1200
.0000 5.3602 5.1045
1.0000 5.3602 5.4118
END DATA.
GRAPH/SCATTERPLOT=
TMPORIE WITH RSKAUTH BY BLOCKCH .
**************************************************************************
OUTCOME VARIABLE:
WTP_PUR
Model Summary
R R-sq MSE F df1 df2 p
.4094 .1676 1.8782 29.8006 2.0000 296.0000 .0000
Model
coeff se t p LLCI ULCI
constant 1.9355 .4022 4.8119 .0000 1.1439 2.7271
BLOCKCH .1719 .1588 1.0823 .2800 -.1407 .4844
RSKAUTH .5858 .0774 7.5703 .0000 .4335 .7381
****************** DIRECT AND INDIRECT EFFECTS OF X ON Y *****************
Direct effect of X on Y
Effect se t p LLCI ULCI
.1719 .1588 1.0823 .2800 -.1407 .4844
Conditional indirect effects of X on Y:
INDIRECT EFFECT:
BLOCKCH -> RSKAUTH -> WTP_PUR
TMPORIE Effect BootSE BootLLCI BootULCI
3.6063 -.0327 .0996 -.2288 .1622
4.4833 .0737 .0705 -.0638 .2189
5.3602 .1800 .0986 -.0017 .3861
Index of moderated mediation:
Index BootSE BootLLCI BootULCI
TMPORIE .1213 .0794 -.0270 .2896
*********************** ANALYSIS NOTES AND ERRORS ************************
Level of confidence for all confidence intervals in output:
95.0000
Number of bootstrap samples for percentile bootstrap confidence intervals:
5000
W values in conditional tables are the mean and +/- SD from the mean.
------ END MATRIX -----
* Encoding: UTF-8.
preserve.
set printback=off.
Matrix
Run MATRIX procedure:
***************** PROCESS Procedure for SPSS Version 4.2 *****************
Written by Andrew F. Hayes, Ph.D. www.afhayes.com
Documentation available in Hayes (2022). www.guilford.com/p/hayes3
**************************************************************************
Model : 1
Y : WTP_PUR
X : BLOCKCH
W : TMPORIE
Sample
Size: 299
**************************************************************************
OUTCOME VARIABLE:
WTP_PUR
Model Summary
R R-sq MSE F df1 df2 p
.2170 .0471 2.1574 4.8602 3.0000 295.0000 .0026
Model
coeff se t p LLCI ULCI
constant 4.7859 .6123 7.8161 .0000 3.5809 5.9910
BLOCKCH -1.9213 .8878 -2.1641 .0313 -3.6686 -.1740
TMPORIE .0171 .1334 .1279 .8983 -.2455 .2796
Int_1 .4845 .1944 2.4918 .0133 .1018 .8672
Product terms key:
Int_1 : BLOCKCH x TMPORIE
Test(s) of highest order unconditional interaction(s):
R2-chng F df1 df2 p
X*W .0201 6.2090 1.0000 295.0000 .0133
----------
Focal predict: BLOCKCH (X)
Mod var: TMPORIE (W)
Conditional effects of the focal predictor at values of the moderator(s):
TMPORIE Effect se t p LLCI ULCI
3.6063 -.1740 .2405 -.7235 .4699 -.6474 .2993
4.4833 .2508 .1700 1.4757 .1411 -.0837 .5854
5.3602 .6757 .2410 2.8039 .0054 .2014 1.1500
Moderator value(s) defining Johnson-Neyman significance region(s):
Value % below % above
4.6722 56.1873 43.8127
Conditional effect of focal predictor at values of the moderator:
TMPORIE Effect se t p LLCI ULCI
1.7500 -1.0734 .5577 -1.9249 .0552 -2.1710 .0241
2.0000 -.9523 .5116 -1.8615 .0637 -1.9591 .0545
2.2500 -.8312 .4660 -1.7836 .0755 -1.7483 .0860
2.5000 -.7101 .4211 -1.6861 .0928 -1.5389 .1187
2.7500 -.5889 .3772 -1.5615 .1195 -1.3312 .1533
3.0000 -.4678 .3345 -1.3986 .1630 -1.1261 .1905
3.2500 -.3467 .2937 -1.1805 .2387 -.9246 .2313
3.5000 -.2256 .2556 -.8825 .3782 -.7285 .2774
3.7500 -.1044 .2216 -.4712 .6379 -.5406 .3318
4.0000 .0167 .1941 .0860 .9315 -.3652 .3986
4.2500 .1378 .1758 .7838 .4338 -.2082 .4839
4.5000 .2589 .1700 1.5231 .1288 -.0757 .5935
4.6722 .3424 .1740 1.9680 .0500 .0000 .6848
4.7500 .3801 .1778 2.1375 .0334 .0301 .7300
5.0000 .5012 .1976 2.5362 .0117 .1123 .8901
5.2500 .6223 .2263 2.7499 .0063 .1769 1.0677
5.5000 .7434 .2610 2.8488 .0047 .2299 1.2570
5.7500 .8646 .2995 2.8864 .0042 .2751 1.4541
6.0000 .9857 .3407 2.8934 .0041 .3152 1.6562
6.2500 1.1068 .3836 2.8856 .0042 .3519 1.8617
6.5000 1.2280 .4277 2.8711 .0044 .3862 2.0697
6.7500 1.3491 .4727 2.8541 .0046 .4188 2.2793
Data for visualizing the conditional effect of the focal predictor:
Paste text below into a SPSS syntax window and execute to produce plot.
DATA LIST FREE/
BLOCKCH TMPORIE WTP_PUR .
BEGIN DATA.
.0000 3.6063 4.8474
1.0000 3.6063 4.6734
.0000 4.4833 4.8624
1.0000 4.4833 5.1132
.0000 5.3602 4.8774
1.0000 5.3602 5.5531
END DATA.
GRAPH/SCATTERPLOT=
TMPORIE WITH WTP_PUR BY BLOCKCH .
*********************** ANALYSIS NOTES AND ERRORS ************************
Level of confidence for all confidence intervals in output:
95.0000
W values in conditional tables are the mean and +/- SD from the mean.
------ END MATRIX -----
* Encoding: UTF-8.
preserve.
set printback=off.
Matrix
Run MATRIX procedure:
***************** PROCESS Procedure for SPSS Version 4.2 *****************
Written by Andrew F. Hayes, Ph.D. www.afhayes.com
Documentation available in Hayes (2022). www.guilford.com/p/hayes3
**************************************************************************
Model : 6
Y : WTP_PUR
X : BLOCKCH
M1 : RSKAUTH
M2 : EASERES
Sample
Size: 299
**************************************************************************
OUTCOME VARIABLE:
RSKAUTH
Model Summary
R R-sq MSE F df1 df2 p
.0567 .0032 1.0560 .9566 1.0000 297.0000 .3288
Model
coeff se t p LLCI ULCI
constant 4.9967 .0831 60.1449 .0000 4.8332 5.1602
BLOCKCH .1163 .1189 .9781 .3288 -.1177 .3503
**************************************************************************
OUTCOME VARIABLE:
EASERES
Model Summary
R R-sq MSE F df1 df2 p
.3941 .1553 .8383 27.2135 2.0000 296.0000 .0000
Model
coeff se t p LLCI ULCI
constant 3.1902 .2687 11.8716 .0000 2.6613 3.7190
BLOCKCH .1145 .1061 1.0795 .2813 -.0943 .3233
RSKAUTH .3735 .0517 7.2252 .0000 .2718 .4753
**************************************************************************
OUTCOME VARIABLE:
WTP_PUR
Model Summary
R R-sq MSE F df1 df2 p
.5035 .2535 1.6900 33.4000 3.0000 295.0000 .0000
Model
coeff se t p LLCI ULCI
constant .4012 .4636 .8655 .3875 -.5111 1.3135
BLOCKCH .1168 .1509 .7738 .4397 -.1803 .4138
RSKAUTH .4062 .0796 5.1018 .0000 .2495 .5629
EASERES .4809 .0825 5.8277 .0000 .3185 .6434
************************** TOTAL EFFECT MODEL ****************************
OUTCOME VARIABLE:
WTP_PUR
Model Summary
R R-sq MSE F df1 df2 p
.0803 .0064 2.2343 1.9259 1.0000 297.0000 .1662
Model
coeff se t p LLCI ULCI
constant 4.8627 .1208 40.2402 .0000 4.6249 5.1006
BLOCKCH .2400 .1729 1.3878 .1662 -.1003 .5803
************** TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y **************
Total effect of X on Y
Effect se t p LLCI ULCI
.2400 .1729 1.3878 .1662 -.1003 .5803
Direct effect of X on Y
Effect se t p LLCI ULCI
.1168 .1509 .7738 .4397 -.1803 .4138
Indirect effect(s) of X on Y:
Effect BootSE BootLLCI BootULCI
TOTAL .1232 .0900 -.0442 .3053
Ind1 .0472 .0519 -.0502 .1581
Ind2 .0551 .0549 -.0405 .1773
Ind3 .0209 .0228 -.0235 .0683
Indirect effect key:
Ind1 BLOCKCH -> RSKAUTH -> WTP_PUR
Ind2 BLOCKCH -> EASERES -> WTP_PUR
Ind3 BLOCKCH -> RSKAUTH -> EASERES -> WTP_PUR
*********************** ANALYSIS NOTES AND ERRORS ************************
Level of confidence for all confidence intervals in output:
95.0000
Number of bootstrap samples for percentile bootstrap confidence intervals:
5000
------ END MATRIX -----