* 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_PAY
X : BLOCKCH
M : INVORIE
W : TCHFAM
Sample
Size: 299
**************************************************************************
OUTCOME VARIABLE:
INVORIE
Model Summary
R R-sq MSE F df1 df2 p
.2323 .0539 1.9857 5.6067 3.0000 295.0000 .0009
Model
coeff se t p LLCI ULCI
constant 3.5827 .3657 9.7972 .0000 2.8630 4.3023
BLOCKCH .5048 .5027 1.0043 .3161 -.4844 1.4941
TCHFAM .1209 .0798 1.5145 .1310 -.0362 .2780
Int_1 .0142 .1107 .1286 .8978 -.2036 .2320
Product terms key:
Int_1 : BLOCKCH x TCHFAM
Test(s) of highest order unconditional interaction(s):
R2-chng F df1 df2 p
X*W .0001 .0165 1.0000 295.0000 .8978
----------
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 INVORIE .
BEGIN DATA.
.0000 2.8178 3.9233
1.0000 2.8178 4.4683
.0000 4.2954 4.1020
1.0000 4.2954 4.6680
.0000 5.7731 4.2806
1.0000 5.7731 4.8676
END DATA.
GRAPH/SCATTERPLOT=
TCHFAM WITH INVORIE BY BLOCKCH .
**************************************************************************
OUTCOME VARIABLE:
WTP_PAY
Model Summary
R R-sq MSE F df1 df2 p
.2511 .0630 2.5869 9.9564 2.0000 296.0000 .0001
Model
coeff se t p LLCI ULCI
constant 2.9163 .3002 9.7142 .0000 2.3255 3.5071
BLOCKCH -.2445 .1896 -1.2895 .1982 -.6176 .1286
INVORIE .2924 .0659 4.4398 .0000 .1628 .4220
****************** DIRECT AND INDIRECT EFFECTS OF X ON Y *****************
Direct effect of X on Y
Effect se t p LLCI ULCI
-.2445 .1896 -1.2895 .1982 -.6176 .1286
Conditional indirect effects of X on Y:
INDIRECT EFFECT:
BLOCKCH -> INVORIE -> WTP_PAY
TCHFAM Effect BootSE BootLLCI BootULCI
2.8178 .1593 .0848 .0125 .3437
4.2954 .1655 .0675 .0526 .3177
5.7731 .1716 .0858 .0292 .3623
Index of moderated mediation:
Index BootSE BootLLCI BootULCI
TCHFAM .0042 .0353 -.0647 .0768
*********************** 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_PAY
X : BLOCKCH
M : INVORIE
W : TMPORIE
Sample
Size: 299
**************************************************************************
OUTCOME VARIABLE:
INVORIE
Model Summary
R R-sq MSE F df1 df2 p
.2050 .0420 2.0107 4.3142 3.0000 295.0000 .0054
Model
coeff se t p LLCI ULCI
constant 3.3898 .5911 5.7344 .0000 2.2264 4.5532
BLOCKCH 1.4889 .8571 1.7371 .0834 -.1979 3.1757
TMPORIE .1597 .1288 1.2401 .2159 -.0937 .4131
Int_1 -.2087 .1877 -1.1120 .2670 -.5782 .1607
Product terms key:
Int_1 : BLOCKCH x TMPORIE
Test(s) of highest order unconditional interaction(s):
R2-chng F df1 df2 p
X*W .0040 1.2366 1.0000 295.0000 .2670
----------
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 INVORIE .
BEGIN DATA.
.0000 3.6063 3.9657
1.0000 3.6063 4.7018
.0000 4.4833 4.1057
1.0000 4.4833 4.6588
.0000 5.3602 4.2458
1.0000 5.3602 4.6158
END DATA.
GRAPH/SCATTERPLOT=
TMPORIE WITH INVORIE BY BLOCKCH .
**************************************************************************
OUTCOME VARIABLE:
WTP_PAY
Model Summary
R R-sq MSE F df1 df2 p
.2511 .0630 2.5869 9.9564 2.0000 296.0000 .0001
Model
coeff se t p LLCI ULCI
constant 2.9163 .3002 9.7142 .0000 2.3255 3.5071
BLOCKCH -.2445 .1896 -1.2895 .1982 -.6176 .1286
INVORIE .2924 .0659 4.4398 .0000 .1628 .4220
****************** DIRECT AND INDIRECT EFFECTS OF X ON Y *****************
Direct effect of X on Y
Effect se t p LLCI ULCI
-.2445 .1896 -1.2895 .1982 -.6176 .1286
Conditional indirect effects of X on Y:
INDIRECT EFFECT:
BLOCKCH -> INVORIE -> WTP_PAY
TMPORIE Effect BootSE BootLLCI BootULCI
3.6063 .2152 .0899 .0606 .4069
4.4833 .1617 .0658 .0521 .3067
5.3602 .1082 .0792 -.0243 .2863
Index of moderated mediation:
Index BootSE BootLLCI BootULCI
TMPORIE -.0610 .0608 -.1848 .0560
*********************** 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 : 14
Y : WTP_PAY
X : BLOCKCH
M : INVORIE
W : TMPORIE
Sample
Size: 299
**************************************************************************
OUTCOME VARIABLE:
INVORIE
Model Summary
R R-sq MSE F df1 df2 p
.1914 .0366 2.0085 11.2884 1.0000 297.0000 .0009
Model
coeff se t p LLCI ULCI
constant 4.1089 .1146 35.8628 .0000 3.8835 4.3344
BLOCKCH .5509 .1640 3.3598 .0009 .2282 .8736
**************************************************************************
OUTCOME VARIABLE:
WTP_PAY
Model Summary
R R-sq MSE F df1 df2 p
.2834 .0803 2.5565 6.4167 4.0000 294.0000 .0001
Model
coeff se t p LLCI ULCI
constant 4.5971 1.4278 3.2197 .0014 1.7871 7.4072
BLOCKCH -.2151 .1889 -1.1387 .2558 -.5869 .1567
INVORIE -.2736 .3179 -.8609 .3900 -.8992 .3519
TMPORIE -.3761 .3141 -1.1975 .2321 -.9943 .2420
Int_1 .1255 .0694 1.8078 .0717 -.0111 .2622
Product terms key:
Int_1 : INVORIE x TMPORIE
Test(s) of highest order unconditional interaction(s):
R2-chng F df1 df2 p
M*W .0102 3.2680 1.0000 294.0000 .0717
----------
Focal predict: INVORIE (M)
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 .1791 .0892 2.0068 .0457 .0035 .3547
4.4833 .2892 .0655 4.4140 .0000 .1602 .4181
5.3602 .3993 .0896 4.4536 .0000 .2228 .5757
Moderator value(s) defining Johnson-Neyman significance region(s):
Value % below % above
3.5905 14.7157 85.2843
Conditional effect of focal predictor at values of the moderator:
TMPORIE Effect se t p LLCI ULCI
1.7500 -.0540 .2005 -.2691 .7881 -.4486 .3407
2.0000 -.0226 .1842 -.1225 .9026 -.3851 .3399
2.2500 .0088 .1681 .0525 .9582 -.3220 .3396
2.5000 .0402 .1522 .2641 .7919 -.2594 .3398
2.7500 .0716 .1368 .5234 .6011 -.1976 .3408
3.0000 .1030 .1218 .8453 .3987 -.1368 .3427
3.2500 .1344 .1076 1.2488 .2127 -.0774 .3461
3.5000 .1657 .0944 1.7555 .0802 -.0201 .3515
3.5905 .1771 .0900 1.9681 .0500 .0000 .3542
3.7500 .1971 .0828 2.3809 .0179 .0342 .3601
4.0000 .2285 .0735 3.1101 .0021 .0839 .3731
4.2500 .2599 .0674 3.8551 .0001 .1272 .3926
4.5000 .2913 .0655 4.4450 .0000 .1623 .4202
4.7500 .3227 .0682 4.7337 .0000 .1885 .4568
5.0000 .3540 .0748 4.7307 .0000 .2068 .5013
5.2500 .3854 .0846 4.5554 .0000 .2189 .5520
5.5000 .4168 .0965 4.3177 .0000 .2268 .6068
5.7500 .4482 .1099 4.0775 .0001 .2319 .6645
6.0000 .4796 .1243 3.8585 .0001 .2350 .7242
6.2500 .5110 .1393 3.6669 .0003 .2367 .7852
6.5000 .5424 .1549 3.5016 .0005 .2375 .8472
6.7500 .5737 .1708 3.3596 .0009 .2376 .9098
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/
INVORIE TMPORIE WTP_PAY .
BEGIN DATA.
2.9365 3.6063 3.6615
4.3779 3.6063 3.9196
5.8194 3.6063 4.1778
2.9365 4.4833 3.6549
4.3779 4.4833 4.0717
5.8194 4.4833 4.4886
2.9365 5.3602 3.6483
4.3779 5.3602 4.2238
5.8194 5.3602 4.7994
END DATA.
GRAPH/SCATTERPLOT=
INVORIE WITH WTP_PAY BY TMPORIE .
****************** DIRECT AND INDIRECT EFFECTS OF X ON Y *****************
Direct effect of X on Y
Effect se t p LLCI ULCI
-.2151 .1889 -1.1387 .2558 -.5869 .1567
Conditional indirect effects of X on Y:
INDIRECT EFFECT:
BLOCKCH -> INVORIE -> WTP_PAY
TMPORIE Effect BootSE BootLLCI BootULCI
3.6063 .0987 .0653 -.0095 .2455
4.4833 .1593 .0666 .0513 .3065
5.3602 .2200 .0900 .0719 .4166
Index of moderated mediation:
Index BootSE BootLLCI BootULCI
TMPORIE .0692 .0477 -.0072 .1782
*********************** 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 -----
ONEWAY WTP_PUR WTP_PAY WTP_MORE INVORIE 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 |
|---|
| 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 |
|---|
| Willingness to Pay (1-7) | 0 | 153 | 4.1176 | 1.65012 | .13340 | 3.8541 | 4.3812 | 1.00 | 7.00 |
|---|
| 1 | 146 | 4.0342 | 1.66677 | .13794 | 3.7616 | 4.3069 | 1.00 | 7.00 |
|---|
| Total | 299 | 4.0769 | 1.65601 | .09577 | 3.8885 | 4.2654 | 1.00 | 7.00 |
|---|
| % More Willing to Pay (1-5) | 0 | 153 | 2.3660 | 1.13990 | .09216 | 2.1839 | 2.5481 | 1.00 | 5.00 |
|---|
| 1 | 146 | 2.4178 | 1.21914 | .10090 | 2.2184 | 2.6172 | 1.00 | 5.00 |
|---|
| Total | 299 | 2.3913 | 1.17755 | .06810 | 2.2573 | 2.5253 | 1.00 | 5.00 |
|---|
| Investment Orientation (Mean) | 0 | 153 | 4.1089 | 1.39382 | .11268 | 3.8863 | 4.3316 | 1.00 | 7.00 |
|---|
| 1 | 146 | 4.6598 | 1.44130 | .11928 | 4.4241 | 4.8956 | 1.00 | 7.00 |
|---|
| Total | 299 | 4.3779 | 1.44146 | .08336 | 4.2139 | 4.5420 | 1.00 | 7.00 |
|---|
ANOVA
| | Sum of Squares | df | Mean Square | F | Sig. |
|---|
| 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 | | | |
|---|
| Willingness to Pay (1-7) | Between Groups | .520 | 1 | .520 | .189 | .664 |
|---|
| Within Groups | 816.711 | 297 | 2.750 | | |
|---|
| Total | 817.231 | 298 | | | |
|---|
| % More Willing to Pay (1-5) | Between Groups | .200 | 1 | .200 | .144 | .704 |
|---|
| Within Groups | 413.017 | 297 | 1.391 | | |
|---|
| Total | 413.217 | 298 | | | |
|---|
| Investment Orientation (Mean) | Between Groups | 22.672 | 1 | 22.672 | 11.288 | .001 |
|---|
| Within Groups | 596.511 | 297 | 2.008 | | |
|---|
| Total | 619.183 | 298 | | | |
|---|
* 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_PAY
X : BLOCKCH
W : TMPORIE
Sample
Size: 299
**************************************************************************
OUTCOME VARIABLE:
WTP_PAY
Model Summary
R R-sq MSE F df1 df2 p
.2211 .0489 2.6349 5.0531 3.0000 295.0000 .0020
Model
coeff se t p LLCI ULCI
constant 4.9184 .6767 7.2682 .0000 3.5866 6.2501
BLOCKCH -3.4482 .9812 -3.5144 .0005 -5.3792 -1.5172
TMPORIE -.1778 .1474 -1.2062 .2287 -.4679 .1123
Int_1 .7524 .2149 3.5015 .0005 .3295 1.1753
Product terms key:
Int_1 : BLOCKCH x TMPORIE
Test(s) of highest order unconditional interaction(s):
R2-chng F df1 df2 p
X*W .0395 12.2604 1.0000 295.0000 .0005
----------
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 -.7347 .2658 -2.7640 .0061 -1.2579 -.2116
4.4833 -.0749 .1879 -.3988 .6903 -.4446 .2948
5.3602 .5849 .2663 2.1961 .0289 .0607 1.1091
Moderator value(s) defining Johnson-Neyman significance region(s):
Value % below % above
4.0297 36.4548 63.5452
5.2295 74.9164 25.0836
Conditional effect of focal predictor at values of the moderator:
TMPORIE Effect se t p LLCI ULCI
1.7500 -2.1315 .6163 -3.4585 .0006 -3.3444 -.9186
2.0132 -1.9335 .5627 -3.4360 .0007 -3.0409 -.8260
2.2763 -1.7355 .5098 -3.4045 .0008 -2.7387 -.7322
2.5395 -1.5375 .4577 -3.3594 .0009 -2.4382 -.6368
2.8026 -1.3395 .4068 -3.2930 .0011 -2.1400 -.5389
3.0658 -1.1415 .3576 -3.1924 .0016 -1.8451 -.4378
3.3289 -.9435 .3109 -3.0349 .0026 -1.5552 -.3317
3.5921 -.7454 .2680 -2.7816 .0058 -1.2729 -.2180
3.8553 -.5474 .2311 -2.3690 .0185 -1.0022 -.0927
4.0297 -.4162 .2115 -1.9680 .0500 -.8323 .0000
4.1184 -.3494 .2034 -1.7179 .0869 -.7498 .0509
4.3816 -.1514 .1891 -.8009 .4238 -.5235 .2207
4.6447 .0466 .1911 .2437 .8076 -.3295 .4226
4.9079 .2446 .2090 1.1702 .2429 -.1667 .6559
5.1711 .4426 .2392 1.8499 .0653 -.0283 .9134
5.2295 .4865 .2472 1.9680 .0500 .0000 .9730
5.4342 .6406 .2778 2.3056 .0218 .0938 1.1874
5.6974 .8386 .3218 2.6061 .0096 .2053 1.4718
5.9605 1.0366 .3692 2.8079 .0053 .3101 1.7631
6.2237 1.2346 .4188 2.9477 .0035 .4103 2.0589
6.4868 1.4326 .4701 3.0477 .0025 .5075 2.3577
6.7500 1.6306 .5224 3.1214 .0020 .6025 2.6587
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_PAY .
BEGIN DATA.
.0000 3.6063 4.2771
1.0000 3.6063 3.5424
.0000 4.4833 4.1212
1.0000 4.4833 4.0463
.0000 5.3602 3.9653
1.0000 5.3602 4.5502
END DATA.
GRAPH/SCATTERPLOT=
TMPORIE WITH WTP_PAY 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 : 14
Y : WTP_PAY
X : BLOCKCH
M : INVORIE
W : LUXATT
Sample
Size: 299
**************************************************************************
OUTCOME VARIABLE:
INVORIE
Model Summary
R R-sq MSE F df1 df2 p
.1914 .0366 2.0085 11.2884 1.0000 297.0000 .0009
Model
coeff se t p LLCI ULCI
constant 4.1089 .1146 35.8628 .0000 3.8835 4.3344
BLOCKCH .5509 .1640 3.3598 .0009 .2282 .8736
**************************************************************************
OUTCOME VARIABLE:
WTP_PAY
Model Summary
R R-sq MSE F df1 df2 p
.3060 .0936 2.5195 7.5920 4.0000 294.0000 .0000
Model
coeff se t p LLCI ULCI
constant 2.9339 .6928 4.2351 .0000 1.5705 4.2972
BLOCKCH -.2619 .1872 -1.3988 .1629 -.6303 .1066
INVORIE .1350 .1516 .8906 .3739 -.1633 .4334
LUXATT .1083 .2248 .4816 .6304 -.3342 .5508
Int_1 .0218 .0437 .4983 .6186 -.0643 .1079
Product terms key:
Int_1 : INVORIE x LUXATT
Test(s) of highest order unconditional interaction(s):
R2-chng F df1 df2 p
M*W .0008 .2483 1.0000 294.0000 .6186
----------
Focal predict: INVORIE (M)
Mod var: LUXATT (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/
INVORIE LUXATT WTP_PAY .
BEGIN DATA.
2.9365 1.7757 3.5084
4.3779 1.7757 3.7588
5.8194 1.7757 4.0092
2.9365 3.2428 3.7611
4.3779 3.2428 4.0576
5.8194 3.2428 4.3541
2.9365 4.7100 4.0139
4.3779 4.7100 4.3565
5.8194 4.7100 4.6991
END DATA.
GRAPH/SCATTERPLOT=
INVORIE WITH WTP_PAY BY LUXATT .
****************** DIRECT AND INDIRECT EFFECTS OF X ON Y *****************
Direct effect of X on Y
Effect se t p LLCI ULCI
-.2619 .1872 -1.3988 .1629 -.6303 .1066
Conditional indirect effects of X on Y:
INDIRECT EFFECT:
BLOCKCH -> INVORIE -> WTP_PAY
LUXATT Effect BootSE BootLLCI BootULCI
1.7757 .0957 .0633 -.0129 .2361
3.2428 .1133 .0585 .0209 .2494
4.7100 .1309 .0799 .0079 .3155
Index of moderated mediation:
Index BootSE BootLLCI BootULCI
LUXATT .0120 .0287 -.0398 .0754
*********************** 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_PAY
X : BLOCKCH
M : INVORIE
W : LUXATT
Sample
Size: 299
**************************************************************************
OUTCOME VARIABLE:
INVORIE
Model Summary
R R-sq MSE F df1 df2 p
.4460 .1989 1.6814 24.4157 3.0000 295.0000 .0000
Model
coeff se t p LLCI ULCI
constant 2.7854 .2545 10.9434 .0000 2.2844 3.2863
BLOCKCH .6180 .3665 1.6860 .0929 -.1034 1.3393
LUXATT .4287 .0751 5.7068 .0000 .2808 .5765
Int_1 -.0597 .1032 -.5787 .5632 -.2628 .1434
Product terms key:
Int_1 : BLOCKCH x LUXATT
Test(s) of highest order unconditional interaction(s):
R2-chng F df1 df2 p
X*W .0009 .3349 1.0000 295.0000 .5632
----------
Focal predict: BLOCKCH (X)
Mod var: LUXATT (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 LUXATT INVORIE .
BEGIN DATA.
.0000 1.7757 3.5465
1.0000 1.7757 4.0585
.0000 3.2428 4.1755
1.0000 3.2428 4.5998
.0000 4.7100 4.8044
1.0000 4.7100 5.1411
END DATA.
GRAPH/SCATTERPLOT=
LUXATT WITH INVORIE BY BLOCKCH .
**************************************************************************
OUTCOME VARIABLE:
WTP_PAY
Model Summary
R R-sq MSE F df1 df2 p
.2511 .0630 2.5869 9.9564 2.0000 296.0000 .0001
Model
coeff se t p LLCI ULCI
constant 2.9163 .3002 9.7142 .0000 2.3255 3.5071
BLOCKCH -.2445 .1896 -1.2895 .1982 -.6176 .1286
INVORIE .2924 .0659 4.4398 .0000 .1628 .4220
****************** DIRECT AND INDIRECT EFFECTS OF X ON Y *****************
Direct effect of X on Y
Effect se t p LLCI ULCI
-.2445 .1896 -1.2895 .1982 -.6176 .1286
Conditional indirect effects of X on Y:
INDIRECT EFFECT:
BLOCKCH -> INVORIE -> WTP_PAY
LUXATT Effect BootSE BootLLCI BootULCI
1.7757 .1497 .0770 .0185 .3179
3.2428 .1241 .0579 .0285 .2520
4.7100 .0984 .0655 -.0075 .2474
Index of moderated mediation:
Index BootSE BootLLCI BootULCI
LUXATT -.0175 .0285 -.0753 .0410
*********************** 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
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Model : 4
Y : WTP_PAY
X : BLOCKCH
M : INVORIE
Sample
Size: 299
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OUTCOME VARIABLE:
INVORIE
Model Summary
R R-sq MSE F df1 df2 p
.1914 .0366 2.0085 11.2884 1.0000 297.0000 .0009
Model
coeff se t p LLCI ULCI
constant 4.1089 .1146 35.8628 .0000 3.8835 4.3344
BLOCKCH .5509 .1640 3.3598 .0009 .2282 .8736
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OUTCOME VARIABLE:
WTP_PAY
Model Summary
R R-sq MSE F df1 df2 p
.2511 .0630 2.5869 9.9564 2.0000 296.0000 .0001
Model
coeff se t p LLCI ULCI
constant 2.9163 .3002 9.7142 .0000 2.3255 3.5071
BLOCKCH -.2445 .1896 -1.2895 .1982 -.6176 .1286
INVORIE .2924 .0659 4.4398 .0000 .1628 .4220
************************** TOTAL EFFECT MODEL ****************************
OUTCOME VARIABLE:
WTP_PAY
Model Summary
R R-sq MSE F df1 df2 p
.0252 .0006 2.7499 .1890 1.0000 297.0000 .6641
Model
coeff se t p LLCI ULCI
constant 4.1176 .1341 30.7142 .0000 3.8538 4.3815
BLOCKCH -.0834 .1919 -.4347 .6641 -.4610 .2942
************** TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y **************
Total effect of X on Y
Effect se t p LLCI ULCI
-.0834 .1919 -.4347 .6641 -.4610 .2942
Direct effect of X on Y
Effect se t p LLCI ULCI
-.2445 .1896 -1.2895 .1982 -.6176 .1286
Indirect effect(s) of X on Y:
Effect BootSE BootLLCI BootULCI
INVORIE .1611 .0670 .0506 .3093
*********************** 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 -----