4.1. Demographic Characteristics
The data were collected from the majority of the respondents who were female (59.3%). A total of 23.2% of the respondents were below 21 years old. The majority of the respondents were between 21–25 years old (61.7%). Respondents between 26–30 years old were 8.9%, 31–35 years were 2%, and the remaining were 36–40 years. The majority of the respondents were single (92.3%), and the remaining were married. The following are the percentage for education level: the majority of the respondents completed their bachelor’s degree or equivalent (49.5%), secondary school level (19.3%), diploma or technical school level (28.5%), master level (2.5%), and the remaining completed their doctoral level. The following are the percentage for income: monthly income of less the RM2,500 (76.1%), income between RM2,501-RM5,000 (16.3%), income between RM5,001-RM7,500 (4.2%), income between RM7,501-RM10,000 (1.8%), and the remaining have an income of more than RM10,000. The majority of the respondents live in urban areas (87.8%). The following are the percentage for the place of origin: Chinese origin (74.6%), Malaysian (6.3%), Indian origin (5.4%), and other origins (13.7%). About 88.3% of respondents do not have ES, and the remaining respondents have ES.
Table 1
Demographic Characteristics
| N | % | | | N | % |
Gender | | | | Marital Status | | |
Male | 531 | 40.7 | | Single | 1206 | 92.3 |
Female | 775 | 59.3 | | Married | 96 | 7.4 |
Total | 1306 | 100.0 | | Divorced | 4 | 0.3 |
| | | | Total | 1306 | 100.0 |
Age Group | | | | | | |
Below 21 years | 303 | 23.2 | | Education | | |
21–25 years | 806 | 61.7 | | Secondary school certificate | 252 | 19.3 |
26–30 years | 116 | 8.9 | | Diploma/technical school certificate | 372 | 28.5 |
31–35 years | 26 | 2.0 | | Bachelor degree or equivalent | 646 | 49.5 |
36–40 years | 55 | 4.2 | | Master’s degree | 32 | 2.5 |
Total | 1306 | 100.0 | | Doctoral degree | 4 | 0.3 |
| | | | Total | 1306 | 100.0 |
Ethnicity | | | | | | |
Malay | 82 | 6.3 | | Household Income | | |
Chinese | 974 | 74.6 | | Below RM2500 | 994 | 76.1 |
Indian | 71 | 5.4 | | RM2501-RM5000 | 213 | 16.3 |
Others | 179 | 13.7 | | RM5001-RM7500 | 55 | 4.2 |
Total | 1306 | 100.0 | | RM7501-RM10,000 | 23 | 1.8 |
| | | | RM10,001-RM12500 | 9 | 0.7 |
Living Areas | | | | More than RM12500 | 12 | 0.9 |
Urban | 1147 | 87.8 | | Total | 1306 | 100.0 |
Rural | 159 | 12.2 | | | | |
Total | 1306 | 100.0 | | ES | | |
| | | | No ES | 1153 | 88.3 |
| | | | Have ES | 153 | 11.7 |
| | | | Total | 1306 | 100.0 |
4.2. Reliabilities and Validities
The reliabilities for the study’s latent constructs can be achieved and appraised by Cronbach’s alpha (CA), DG rho, and composite reliability (CR) (Hair et al., 2019). The CA values for each construct are above the threshold of 0.70, and the minimum value of CA value is 0.789 (Chin, 2010). The results are reported in Table 2. Furthermore, all DG rho values are above the threshold of 0.70, where the minimum value of DG rho is 0.796 (Hair et al., 2019). Moreover, CR values are beyond the threshold of 0.70, where the minimum value of CR value is 0.856 (Chin, 2010). These results signify that the latent constructs have achieved adequate reliabilities and performed well for the subsequent analysis. The AVE for all items for each construct must be above 0.50 score to confirm convergent validity (Hair et al., 2019). The items display that the constructs have acceptable convergent validity (see Table 2.). All the VIF values for each construct are below the threshold of 3.3., displaying no issue of multicollinearity (Chin, 2010). The item loading and cross-loading are reported for the construct discriminant validity in Tables 3 and 4, respectively.
Table 2
Variables | No. Items | Mean | SD | CA | DG rho | CR | AVE | VIF |
ENC | 5 | 5.178 | 0.815 | 0.789 | 0.796 | 0.856 | 0.546 | 1.404 |
ENK | 5 | 4.886 | 0.987 | 0.854 | 0.856 | 0.895 | 0.630 | 1.404 |
ATT | 5 | 5.200 | 0.985 | 0.883 | 0.884 | 0.914 | 0.682 | 1.916 |
SBN | 5 | 4.444 | 1.210 | 0.925 | 0.928 | 0.943 | 0.769 | 2.108 |
PBC | 5 | 4.658 | 1.137 | 0.893 | 0.895 | 0.921 | 0.700 | 2.706 |
AOI | 5 | 5.084 | 0.950 | 0.805 | 0.815 | 0.865 | 0.564 | 2.059 |
PMB | 5 | 4.991 | 0.987 | 0.817 | 0.818 | 0.873 | 0.579 | 1.958 |
WTP | 4 | 4.980 | 1.147 | 0.919 | 0.919 | 0.943 | 0.805 | 1.000 |
PES | 1 | 0.117 | 0.322 | 1.000 | 1.000 | 1.000 | 1.000 | |
Note: ENC.: Environmental Concern; ENK.: Environmental Knowledge, ATT: Attitude towards ESs; SBN.: Subjective Norms; PBC.: Perceived Behavioural Control; AOI.: ES’s Attributes of Interest; PMB: Perceived Monetary Benefit; WTP.: Willingness to Purchase ES; PES: Purchased ES; SD: Standard Deviation; CA: Cronbach’s Alpha; DG rho - Dillon-Goldstein’s rho; CR - Composite Reliability; AVE - Average Variance Extracted; VIF - Variance Inflation Factors |
Source
Author’s data analysis
Table 3
| ENC | ENK | ATT | SBN | PBC | AOI | PMB | WTP | PES |
Fornell-Larcker Criterion | | | | | |
ENC | 0.739 | | | | | | | | |
ENK | 0.536 | 0.794 | | | | | | | |
ATT | 0.479 | 0.460 | 0.826 | | | | | | |
SBN | 0.255 | 0.438 | 0.514 | 0.877 | | | | | |
PBC | 0.318 | 0.435 | 0.587 | 0.714 | 0.837 | | | | |
AOI | 0.402 | 0.340 | 0.590 | 0.489 | 0.618 | 0.751 | | | |
PMB | 0.348 | 0.366 | 0.589 | 0.486 | 0.579 | 0.620 | 0.761 | | |
WTP | 0.371 | 0.365 | 0.626 | 0.551 | 0.639 | 0.616 | 0.661 | 0.897 | |
PES | -0.017 | 0.053 | 0.059 | 0.133 | 0.172 | 0.064 | 0.094 | 0.070 | 1.000 |
Heterotrait-Monotrait Ratio (HTMT) | | | | | |
ENC | - | | | | | | | | |
ENK | 0.667 | - | | | | | | | |
ATT | 0.573 | 0.526 | - | | | | | | |
SBN | 0.305 | 0.493 | 0.565 | - | | | | | |
PBC | 0.384 | 0.496 | 0.656 | 0.781 | - | | | | |
AOI | 0.509 | 0.407 | 0.698 | 0.547 | 0.713 | - | | | |
PMB | 0.435 | 0.439 | 0.693 | 0.559 | 0.679 | 0.764 | - | | |
WTP | 0.439 | 0.411 | 0.694 | 0.594 | 0.704 | 0.712 | 0.763 | - | |
PES | 0.058 | 0.057 | 0.071 | 0.139 | 0.182 | 0.098 | 0.106 | 0.073 | - |
Note: ENC.: Environmental Concern; ENK.: Environmental Knowledge, ATT: Attitude towards ESs; SBN.: Subjective Norms; PBC.: Perceived Behavioural Control; AOI.: ES’s Attributes of Interest; PMB: Perceived Monetary Benefit; WTP.: Willingness to Purchase ES; PES: Purchased ES |
Source
Author’s data analysis
All the study constructs have suitable discriminant validities (see Table 3). Furthermore, the Fornell-Larcker criterion (1981) and HTMT ratio were employed to evaluate the discriminant validity of study constructs. The Fornell-Larcker criterion was estimated with the square root of the respective construct’s AVE, and the square root of AVE for the construct must be higher than the correlation among other constructs (Hair et al., 2019). HTMT ratio needs to be less than 0.90 to establish discriminant validity for each construct (Henseler et al., 2015). Tables 3 and 4 show that the study has discriminant validity for each construct.
Table 4
Loadings and Cross-Loading
Code | ENC | ENK | ATT | SBN | PBC | AOI | PMB | WTP | PES |
ENC1 | 0.755 | 0.412 | 0.356 | 0.195 | 0.220 | 0.265 | 0.261 | 0.270 | 0.014 |
ENC2 | 0.790 | 0.454 | 0.357 | 0.224 | 0.253 | 0.277 | 0.285 | 0.291 | -0.027 |
ENC3 | 0.795 | 0.321 | 0.390 | 0.121 | 0.199 | 0.317 | 0.257 | 0.272 | -0.082 |
ENC4 | 0.723 | 0.284 | 0.355 | 0.136 | 0.203 | 0.342 | 0.235 | 0.272 | -0.010 |
ENC5 | 0.614 | 0.542 | 0.305 | 0.287 | 0.315 | 0.285 | 0.249 | 0.269 | 0.059 |
ENK1 | 0.427 | 0.788 | 0.319 | 0.351 | 0.343 | 0.234 | 0.283 | 0.264 | 0.033 |
ENK2 | 0.463 | 0.775 | 0.347 | 0.312 | 0.300 | 0.255 | 0.290 | 0.281 | 0.050 |
ENK3 | 0.464 | 0.813 | 0.394 | 0.305 | 0.324 | 0.248 | 0.295 | 0.311 | 0.002 |
ENK4 | 0.397 | 0.803 | 0.382 | 0.377 | 0.397 | 0.317 | 0.319 | 0.294 | 0.073 |
ENK5 | 0.381 | 0.790 | 0.375 | 0.392 | 0.359 | 0.289 | 0.264 | 0.292 | 0.052 |
ATT1 | 0.423 | 0.411 | 0.835 | 0.372 | 0.466 | 0.504 | 0.477 | 0.497 | 0.010 |
ATT2 | 0.450 | 0.397 | 0.843 | 0.427 | 0.506 | 0.485 | 0.471 | 0.538 | 0.087 |
ATT3 | 0.415 | 0.348 | 0.813 | 0.288 | 0.370 | 0.474 | 0.469 | 0.446 | -0.022 |
ATT4 | 0.361 | 0.341 | 0.859 | 0.482 | 0.523 | 0.501 | 0.524 | 0.559 | 0.069 |
ATT5 | 0.326 | 0.398 | 0.776 | 0.541 | 0.546 | 0.469 | 0.489 | 0.536 | 0.090 |
SBN1 | 0.218 | 0.377 | 0.448 | 0.850 | 0.592 | 0.393 | 0.415 | 0.445 | 0.139 |
SBN2 | 0.224 | 0.386 | 0.465 | 0.888 | 0.601 | 0.423 | 0.426 | 0.471 | 0.093 |
SBN3 | 0.213 | 0.394 | 0.438 | 0.901 | 0.620 | 0.439 | 0.417 | 0.456 | 0.113 |
SBN4 | 0.200 | 0.388 | 0.416 | 0.885 | 0.632 | 0.411 | 0.419 | 0.483 | 0.144 |
SBN5 | 0.255 | 0.374 | 0.480 | 0.860 | 0.673 | 0.468 | 0.448 | 0.547 | 0.097 |
PBC1 | 0.255 | 0.378 | 0.509 | 0.652 | 0.817 | 0.487 | 0.464 | 0.537 | 0.160 |
PBC2 | 0.306 | 0.376 | 0.534 | 0.585 | 0.838 | 0.550 | 0.485 | 0.584 | 0.115 |
PBC3 | 0.247 | 0.374 | 0.497 | 0.637 | 0.864 | 0.514 | 0.491 | 0.529 | 0.151 |
PBC4 | 0.249 | 0.341 | 0.459 | 0.582 | 0.841 | 0.517 | 0.491 | 0.521 | 0.159 |
PBC5 | 0.267 | 0.347 | 0.448 | 0.527 | 0.823 | 0.512 | 0.492 | 0.498 | 0.136 |
AOI1 | 0.321 | 0.285 | 0.477 | 0.456 | 0.553 | 0.764 | 0.460 | 0.509 | 0.048 |
AOI2 | 0.313 | 0.262 | 0.494 | 0.472 | 0.553 | 0.799 | 0.522 | 0.522 | 0.072 |
AOI3 | 0.297 | 0.276 | 0.419 | 0.350 | 0.438 | 0.783 | 0.459 | 0.438 | 0.049 |
AOI4 | 0.266 | 0.238 | 0.417 | 0.361 | 0.464 | 0.778 | 0.475 | 0.454 | 0.104 |
AOI5 | 0.320 | 0.208 | 0.398 | 0.139 | 0.260 | 0.618 | 0.402 | 0.372 | -0.056 |
PMB1 | 0.346 | 0.261 | 0.533 | 0.270 | 0.395 | 0.524 | 0.680 | 0.498 | -0.004 |
PMB2 | 0.209 | 0.297 | 0.393 | 0.444 | 0.468 | 0.479 | 0.724 | 0.472 | 0.087 |
PMB3 | 0.258 | 0.292 | 0.463 | 0.404 | 0.491 | 0.449 | 0.823 | 0.518 | 0.106 |
PMB4 | 0.250 | 0.275 | 0.408 | 0.361 | 0.407 | 0.444 | 0.793 | 0.489 | 0.086 |
PMB5 | 0.258 | 0.266 | 0.438 | 0.370 | 0.440 | 0.462 | 0.777 | 0.532 | 0.080 |
WTP1 | 0.318 | 0.294 | 0.573 | 0.499 | 0.562 | 0.550 | 0.612 | 0.895 | 0.047 |
WTP2 | 0.327 | 0.327 | 0.569 | 0.506 | 0.584 | 0.535 | 0.598 | 0.915 | 0.063 |
WTP3 | 0.339 | 0.347 | 0.552 | 0.515 | 0.603 | 0.563 | 0.593 | 0.914 | 0.086 |
WTP4 | 0.349 | 0.341 | 0.553 | 0.456 | 0.545 | 0.565 | 0.569 | 0.864 | 0.053 |
PES | -0.017 | 0.053 | 0.059 | 0.133 | 0.172 | 0.064 | 0.094 | 0.070 | 1.000 |
Note: ENC.: Environmental Concern; ENK.: Environmental Knowledge, ATT: Attitude towards ESs; SBN.: Subjective Norms; PBC.: Perceived Behavioural Control; AOI.: ES’s Attributes of Interest; PMB: Perceived Monetary Benefit; WTP.: Willingness to Purchase ES; PES: Purchased ES. (2) The Italic values in the matrix above are the item loadings, and others are cross-loadings |
Source
Author’s data analysis
4.3. Path Analysis
After realising the acceptable reliabilities and validities from the structural evaluation of the model, the next measurement assessment was performed to investigate the study hypothesis. The adjusted r2 value for two exogenous constructs (i.e., ENC and ENK) on the attitude towards ES explains the per cent 28.7 of change in the attitude towards ES. The predictive relevance (Q2) value for the part of the model is 0.193, indicating a medium predictive relevance (Chin, 2010). The adjusted r2 value for the five exogenous constructs (i.e., ATT, SBN, PBC, AOI, and PMB) on WTP elucidates the per cent 58.6 of change in WTP of ES. The predictive relevance (Q2) value for the part of the model is 0.469, indicating a high predictive relevance (Chin, 2010). The adjusted r2 value for the one exogenous construct (i.e., WTP) on PES explicates the per cent 0.4 of change in the purchase of ES. The predictive relevance (Q2) value for the part of the model is 0.003, indicating no predictive relevance (Chin, 2010).
Table 5. Path Coefficients
Hypo
|
|
Beta
|
CI - Min
|
CI - Max
|
t
|
p
|
r2
|
f2
|
Q2
|
Decision
|
Factors affecting Attitude towards ESs
|
|
|
|
|
H1
|
ENC è ATT
|
0.326
|
0.278
|
0.374
|
11.123
|
0.000
|
0.287
|
0.106
|
0.193
|
Accept
|
H2
|
ENK è ATT
|
0.285
|
0.235
|
0.335
|
9.442
|
0.000
|
0.081
|
|
Accept
|
Factors affecting Willingness to Purchase ES
|
|
|
|
H3
|
ATT è WTP
|
0.206
|
0.155
|
0.256
|
6.701
|
0.000
|
|
0.054
|
|
Accept
|
H4
|
SBN è WTP
|
0.096
|
0.044
|
0.147
|
3.066
|
0.001
|
|
0.011
|
|
Accept
|
H5
|
PBC è WTP
|
0.188
|
0.121
|
0.256
|
4.606
|
0.000
|
0.586
|
0.032
|
0.469
|
Accept
|
H6
|
AOI è WTP
|
0.152
|
0.104
|
0.201
|
5.187
|
0.000
|
|
0.027
|
|
Accept
|
H7
|
PMB è WTP
|
0.290
|
0.235
|
0.346
|
8.620
|
0.000
|
|
0.104
|
|
Accept
|
Factor affecting the Purchase of ES
|
|
|
|
|
|
H8
|
WTP è PES
|
0.070
|
0.030
|
0.109
|
2.925
|
0.002
|
0.004
|
0.005
|
0.003
|
Accept
|
Note: ENC.: Environmental Concern; ENK.: Environmental Knowledge, ATT: Attitude towards ESs; SBN.: Subjective Norms; PBC.: Perceived Behavioural Control; AOI.: ES’s Attributes of Interest; PMB: Perceived Monetary Benefit; WTP.: Willingness to Purchase ES; PES: Purchased ES
Source: Author’s data analysis
Table 5 shows the model standardised path values, t-values, and significance level. The path coefficient between ECN and ATT (β = 0.326, t = 11.123, p = 0.000) indicates a significant and positive effect of environmental concern on the attitude towards ESs. This result forms significant statistical support for H1. The path value for ENK and ATT (β = 0.285, t = 9.442, p = 0.000) shows the influence of environmental knowledge for the attitude towards ES that is positive and significant; hence, it offers significant statistical support for H2. The path between ATT and WTP (β = 0.206, t = 6.701, p = 0.000) shows the influence of attitude towards ESs in influencing the willingness to purchase ESs that is positive and significant; hence, it supports H3. The path coefficient for SBN and WTP (β = 0.096, t = 3.066, p = 0.001) shows a positive and significant effect; it supports H4. The path between PBC and WTP (β = 0.188, t = 4.606, p = 0.000) shows the influence of PBC in influencing WTP ESs that is positive and significant; it supports H5. The path coefficient for ATI and WTP (β = 0.152, t = 5.187, p = 0.000) shows a positive and significant effect; it supports H6. The path between PMB and WTP (β = 0.290, t = 8.620, p = 0.000) shows the influence of perceived monetary benefits in influencing the willingness to purchase ESs that is positive and significant; it supports H7. The path coefficient for WTP and PES (β = 0.070, t = 2.925, p = 0.002) shows a positive and significant effect; it supports H8. Table 5 shows the path coefficients.
4.4. Mediation Analysis
The mediation effect of the attitude towards ES was tested with H1M for the relationship between ENC and WTP. The result reveals that the attitude towards ES mediates the relationship between ENC and WTP (β = 0.067, CI min = 0.048, CI max = 0.086, p = 0.000), and it supports H1M. and H2M for the relationship between ENK and WTP that is mediated by ATT. The result shows that the attitude towards ESs mediates the relationship between ENK and WTP (β = 0.059, CI min = 0.041, CI max = 0.076, p = 0.000), and it supports H2M. In H3M, the relationship between ATT and PES is mediated by WTP. The result shows that WTP mediates the relationship between ATT and PES (β = 0.014, CI min = 0.006, CI max = 0.023, p = 0.004), and it supports H3M. For H4M, the relationship between SBN and PES is mediated by WTP. The result reveals that WTP mediates the relationship between SBN and PES (β = 0.007, CI min = 0.001, CI max = 0.012, p = 0.020), and it supports H4M. For H5M, the relationship between PBC and PES is mediated by WTP. The result reveals that WTP mediates the relationship between PBC and PES (β = 0.013, CI min = 0.004, CI max = 0.022, p = 0.010), and it supports H5M. For H6M, the relationship between AI and PES is mediated by WTP. The result reveals that WTP mediates the relationship between AI and PES (β = 0.011, CI min = 0.004, CI max = 0.017, p = 0.005), and it supports H6M. For H7M, the relationship between MV and PES is mediated by WTP. The result reveals that WTP mediates the relationship between MV and PES (β = 0.020, CI min = 0.008, CI max = 0.032, p = 0.003). The mediation results are presented in Table 7.
Table 7. Mediating Effects
Hypo
|
Associations
|
Beta
|
CI - Min
|
CI - Max
|
t
|
p
|
Decision
|
H1M
|
ENC è ATT è WTP
|
0.067
|
0.048
|
0.086
|
5.871
|
0.000
|
Accept
|
H2M
|
ENK è ATT è WTP
|
0.059
|
0.041
|
0.076
|
5.603
|
0.000
|
Accept
|
H3M
|
ATT è WTP è PES
|
0.014
|
0.006
|
0.023
|
2.701
|
0.004
|
Accept
|
H4M
|
SBN è WTP è PES
|
0.007
|
0.001
|
0.012
|
2.057
|
0.020
|
Accept
|
H5M
|
PBC è WTP è PES
|
0.013
|
0.004
|
0.022
|
2.326
|
0.010
|
Accept
|
H6M
|
AOI è WTP è PES
|
0.011
|
0.004
|
0.017
|
2.557
|
0.005
|
Accept
|
H7M
|
PMB è WTP è PES
|
0.020
|
0.008
|
0.032
|
2.783
|
0.003
|
Accept
|
Note: ENC.: Environmental Concern; ENK.: Environmental Knowledge, ATT: Attitude towards ESs; SBN.: Subjective Norms; PBC.: Perceived Behavioural Control; AOI.: ES’s Attributes of Interest; PMB: Perceived Monetary Benefit; WTP.: Willingness to Purchase ES; PES: Purchased ES
Source: Author’s data analysis
4.5. Multiple Group Analysis
Multiple group analyses were executed to match the results for different groups based on gender, living area, and education. One non-parametric test was employed to evaluate the differences in the vital association between the model based on the gender, areas of living, and education. Table 8 shows the path values for two groups with the differences within groups and the p-values as recommended by Henseler et al. (2009). PMGA represents the p-values that are achieved using the multiple group analysis of PLS-SEM as the measure for the significance of the difference between the groups (Henseler et al., 2009).
Table 8. Multi-group Analysis
|
Male
|
Female
|
Difference
|
|
|
Beta
|
p-value
|
Beta
|
p-value
|
Beta
|
p-value
|
Decision
|
ENC è ATT
|
0.244
|
0.000
|
0.173
|
0.000
|
0.071
|
0.129
|
No Difference
|
ENK è ATT
|
0.130
|
0.007
|
0.171
|
0.000
|
-0.041
|
0.268
|
No Difference
|
ATT è WTP
|
0.304
|
0.000
|
0.353
|
0.000
|
-0.049
|
0.229
|
No Difference
|
SBN è WTP
|
0.255
|
0.000
|
0.297
|
0.000
|
-0.042
|
0.259
|
No Difference
|
PBC è WTP
|
0.204
|
0.000
|
0.171
|
0.001
|
0.033
|
0.338
|
No Difference
|
AOI è WTP
|
0.256
|
0.000
|
0.318
|
0.000
|
-0.062
|
0.188
|
No Difference
|
PMB è WTP
|
0.097
|
0.018
|
0.099
|
0.013
|
-0.002
|
0.491
|
No Difference
|
WTP è PES
|
0.090
|
0.007
|
0.046
|
0.068
|
0.044
|
0.181
|
No Difference
|
|
Urban
|
Rural
|
Difference
|
|
|
Beta
|
p-value
|
Beta
|
p-value
|
Beta
|
p-value
|
Decision
|
ENC è ATT
|
0.320
|
0.000
|
0.387
|
0.000
|
-0.068
|
0.209
|
No Difference
|
ENK è ATT
|
0.282
|
0.000
|
0.296
|
0.000
|
-0.014
|
0.438
|
No Difference
|
ATT è WTP
|
0.228
|
0.000
|
0.006
|
0.461
|
0.221
|
0.002
|
Sig. Difference
|
SBN è WTP
|
0.083
|
0.005
|
0.233
|
0.007
|
-0.150
|
0.069
|
No Difference
|
PBC è WTP
|
0.186
|
0.000
|
0.190
|
0.038
|
-0.004
|
0.497
|
No Difference
|
AOI è WTP
|
0.149
|
0.000
|
0.201
|
0.005
|
-0.052
|
0.258
|
No Difference
|
PMB è WTP
|
0.281
|
0.000
|
0.345
|
0.000
|
-0.064
|
0.209
|
No Difference
|
WTP è PES
|
0.057
|
0.019
|
0.130
|
0.025
|
-0.074
|
0.155
|
No Difference
|
|
Secondary School Certificate
|
Bachelor Degree or Equivalent
|
Difference
|
|
|
Beta
|
p-value
|
Beta
|
p-value
|
Beta
|
p-value
|
Decision
|
ENC è ATT
|
0.220
|
0.003
|
0.385
|
0.000
|
-0.165
|
0.031
|
Sig. Difference
|
ENK è ATT
|
0.452
|
0.000
|
0.237
|
0.000
|
0.216
|
0.011
|
Sig. Difference
|
ATT è WTP
|
0.233
|
0.003
|
0.217
|
0.000
|
0.016
|
0.429
|
No Difference
|
SBN è WTP
|
0.014
|
0.437
|
0.109
|
0.003
|
-0.095
|
0.159
|
No Difference
|
PBC è WTP
|
0.136
|
0.096
|
0.139
|
0.003
|
-0.004
|
0.478
|
No Difference
|
AOI è WTP
|
0.219
|
0.002
|
0.182
|
0.000
|
0.037
|
0.325
|
No Difference
|
PMB è WTP
|
0.311
|
0.000
|
0.290
|
0.000
|
0.020
|
0.411
|
No Difference
|
WTP è PES
|
0.056
|
0.178
|
0.033
|
0.172
|
0.023
|
0.381
|
No Difference
|
Note: ENC.: Environmental Concern; ENK.: Environmental Knowledge, ATT: Attitude towards ESs; SBN.: Subjective Norms; PBC.: Perceived Behavioural Control; AOI.: ES’s Attributes of Interest; PMB: Perceived Monetary Benefit; WTP.: Willingness to Purchase ES; PES: Purchased ES
Source: Author’s data analysis
4.5.1. Effects of Gender on the Groups
The results of the two groups are based on the gender of the sample. The gender has no significant difference in the relationship of the model. The variance of gender does not influence the relationship between study models. The results are depicted in Table 8.
4.5.2. Effects of Living Area on the Groups
The results of the two groups are based on the living area of the sample. The living area shows a significant difference in the relationship between ATT and WTP for ES. The urban respondents have more ATT in influencing WTP for ES. However, the variance of the living area (i.e., urban and rural respondents) does not influence the variance between the study’s other paths. Study results are provided in Table 8.
4.5.3. Effects of Education on the Groups
The results of the two groups are based on the education of the sample. Education has a significant difference in the relationship between ECN and ATT, ENK, and ATT for ES. The variance of education does not influence the variance between the study’s other paths. Analysis results are shown in Table 8.
4.6. Importance Performance Matrix
Table 9 shows the outcomes of IPMA. ECN is the most vital cause in the performance of PES (0.326; 73.083), followed by ATT (0.206; 70.001), AOI (0.152, 67.674), and PMB (0.290; 66.742).
Table 9
Performance and Total Effects
Target Construct | Purchase of ES |
Variables | Total Effect | Performance |
Environmental Concern | 0.326 | 73.083 |
Environmental Knowledge | 0.285 | 64.886 |
Attitude towards ESs | 0.206 | 70.001 |
Subjective Norms | 0.096 | 57.468 |
Perceived Behavioural Control | 0.188 | 61.028 |
ES’s Attributes of Interest | 0.152 | 67.674 |
Perceived Monetary Benefit | 0.290 | 66.742 |
Willingness to Purchase ES | 0.070 | 66.333 |
Source: Author’s data analysis |
4.7. Predictive Assessment
The sample predictive power of the model was estimated with the PLSPredict with ten folds and one repetition. This assessment establishes the performance of the PLS model with new predictive observations. The distribution of error is presented in Fig. 3. Most of the endogenous constructs’ indicators outperform the naïve benchmark (Shmueli et al., 2019). The Q2predict value is above 0. Then, the prediction error is analysed in detail to evaluate the relevant prediction statistic. The error distribution plots show that the error distribution for all items of WTP (Fig. 3) is not highly non-symmetric (Shmueli et al., 2019). Therefore, this study assessed the predictive power based on the RMSE value. The error distribution for PES is highly non-symmetric, and this study used the mean absolute error (MAE) values to assess the predictive power based on PES.
Table 10. Predictive Model Assessment
|
Q²Predict
|
RMSE (PLS-SEM)
|
RMSE (LM)
|
Difference
|
Predictive Power
|
WTP1
|
0.446
|
0.947
|
0.935
|
0.013
|
|
WTP2
|
0.449
|
0.970
|
0.968
|
0.002
|
Medium Predictive Power
|
WTP3
|
0.466
|
0.941
|
0.947
|
-0.006
|
|
WTP4
|
0.421
|
0.949
|
0.953
|
-0.003
|
|
|
Q²Predict
|
MAE (PLS-SEM)
|
MAE (LM)
|
|
|
PES
|
0.009
|
0.206
|
0.206
|
0.000
|
No Predictive Power
|
Note: ENC.: Environmental Concern; ENK.: Environmental Knowledge, ATT: Attitude towards ESs; SBN.: Subjective Norms; PBC.: Perceived Behavioural Control; AOI.: ES’s Attributes of Interest; PMB: Perceived Monetary Benefit; WTP.: Willingness to Purchase ES; PES: Purchased ES; MAE: Mean Absolute Error; RMSE: Root Mean Squared Error; PLS-SEM: Partial Least Squares – Structural Equation Modelling; LM: Linear Regression Model
Source: Author’s data analysis
This study compared the root mean squared error (RMSE) values from the PLS-SEM analysis with the naïve LM benchmark, and it reveals that the PLS-SEM analysis produces equal prediction errors for two cases out of four cases. The results show that the study model has medium predictive power for WTP. The naïve LM benchmark score performs better in two cases as the LM does not consider the mediation effect tested in the PLS-SEM model analysis (Shmueli et al., 2019) (see Table 10). However, there is no predictive power for PES as the error is equal for the PLS-SEM and naive LM benchmark.