Regional Sustainability ›› 2024, Vol. 5 ›› Issue (3): 100160.doi: 10.1016/j.regsus.2024.100160cstr: 32279.14.j.regsus.2024.100160
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Maula Fadhilata RAHMATIKA*(), Agus SUMAN, Wildan SYAFITRI, Sri MULJANINGSIH
Received:
2023-10-20
Revised:
2024-07-10
Accepted:
2024-08-21
Published:
2024-09-30
Online:
2024-09-25
Contact:
Maula Fadhilata RAHMATIKA
E-mail:maulafadhilata@yahoo.com
Maula Fadhilata RAHMATIKA, Agus SUMAN, Wildan SYAFITRI, Sri MULJANINGSIH. Understanding factors affecting non-participants’ interest in community-supported agriculture[J]. Regional Sustainability, 2024, 5(3): 100160.
Table 1
Description of variables used in the well-established unified theory of acceptance and use of technology (UTAUT2) model."
Variable | Definition | Reference |
---|---|---|
Behavioral intention (BI) | BI refers to an individual’s willingness to perform a specific action. In the context of technology adoption, it represents the level of desire to use a particular technology or innovation. This variable serves as a strong predictor of whether an individual will actually engage in the desired behavior. | Davis ( |
Effort expectancy (EE) | EE refers to the perceived ease of use of a technology or innovation. This variable reflects how much effort someone believes is required to use the technology effectively. Higher EE indicates that the technology is perceived as easier to use, which can positively impact adoption and continued use, as individuals are more likely to participate if they find the technology easy to use. | Davis et al. ( |
Facilitating conditions (FC) | FC refers to the resources and support that help individuals use technology or innovations, including infrastructure, technical support, and other necessary resources. The higher the FC, the better the support and resources available. | Venkatesh et al. ( |
Habit (H) | H refers to the repeated and automatic use of technology. The higher the H, the more ingrained and automatic the usage. | Venkatesh et al. ( |
Hedonic motivation (HM) | HM refers to the enjoyment people get from using technology or innovations. This variable reflects how much satisfaction the technology provides in terms of pleasure and enjoyment. A higher level of HM means greater enjoyment from using the technology. | Venkatesh et al. ( |
Performance expectancy (PE) | PE refers to the expectation that a technology or innovation will enhance task performance or achieve desired outcomes. This variable reflects how useful a technology is perceived to be, with higher PE indicating greater perceived benefits. | Venkatesh et al. ( |
Price value (PV) | PV refers to how much individuals believe a technology or innovation is worth, based on the benefits they receive and the price they pay. A higher PV means people think the benefits are worth the cost. | Venkatesh et al. ( |
Social influence (SI) | SI refers to the degree to which an individual believes other people, such as friends, family, or society more generally, expect them to use a technology or innovation. | Venkatesh et al. ( |
Table 2
Respondent profile."
Variable | Description | Frequency | Percentage (%) |
---|---|---|---|
Gender | Male | 363 | 30.25 |
Female | 837 | 69.75 | |
Age (years old) | 20-30 | 1147 | 95.58 |
31-40 | 41 | 3.42 | |
41-50 | 12 | 1.00 | |
Education | Middle school | 5 | 0.42 |
High school | 398 | 33.17 | |
Undergraduate | 763 | 63.58 | |
Postgraduate | 34 | 2.83 | |
Income (USD/month) | <73.6 | 831 | 69.25 |
73.6-368.0 | 286 | 23.83 | |
>368.0 | 83 | 6.92 | |
Place of origin | Urban areas | 966 | 80.50 |
Rural areas | 234 | 19.50 |
Table 3
Results of outer loadings."
Latent variable | Indicator | Outer loading | Latent variable | Indicator | Outer loading |
---|---|---|---|---|---|
BI | BI4 | 0.874 | HM | HM2 | 0.815 |
BI5 | 0.907 | HM3 | 0.840 | ||
BI6 | 0.886 | HM4 | 0.766 | ||
EE | EE1 | 0.765 | HM5 | 0.811 | |
EE2 | 0.743 | PE | PE1 | 0.779 | |
EE3 | 0.740 | PE2 | 0.821 | ||
EE4 | 0.746 | PE3 | 0.757 | ||
EE5 | 0.780 | PE4 | 0.787 | ||
FC | FC1 | 0.745 | PE5 | 0.805 | |
FC2 | 0.798 | PE6 | 0.816 | ||
FC3 | 0.799 | PV | PV1 | 0.900 | |
FC4 | 0.777 | PV2 | 0.873 | ||
H | H1 | 0.865 | PV3 | 0.895 | |
H2 | 0.857 | PV4 | 0.816 | ||
H3 | 0.871 | SI | SI1 | 0.916 | |
H4 | 0.862 | SI2 | 0.912 | ||
HM | HM1 | 0.804 | SI3 | 0.898 |
Table 4
Evaluation of the measurement model."
Construct | Cronbach’s alpha | Composite reliability | AVE | Construct | Cronbach’s alpha | Composite reliability | AVE |
---|---|---|---|---|---|---|---|
BI | 0.868 | 0.919 | 0.791 | HM | 0.866 | 0.903 | 0.652 |
EE | 0.813 | 0.869 | 0.570 | PE | 0.883 | 0.911 | 0.631 |
FC | 0.785 | 0.861 | 0.608 | PV | 0.894 | 0.927 | 0.760 |
H | 0.886 | 0.921 | 0.746 | SI | 0.895 | 0.934 | 0.826 |
Table 5
Fornell-Larcker criterion discriminant validity assessment."
BI | EE | FC | H | HM | PE | PV | SI | |
---|---|---|---|---|---|---|---|---|
BI | 0.889 | |||||||
EE | 0.457 | 0.755 | ||||||
FC | 0.496 | 0.550 | 0.780 | |||||
H | 0.430 | 0.590 | 0.592 | 0.864 | ||||
HM | 0.563 | 0.584 | 0.659 | 0.677 | 0.807 | |||
PE | 0.547 | 0.571 | 0.585 | 0.579 | 0.649 | 0.794 | ||
PV | 0.419 | 0.509 | 0.658 | 0.672 | 0.679 | 0.613 | 0.872 | |
SI | 0.456 | 0.458 | 0.406 | 0.278 | 0.367 | 0.275 | 0.250 | 0.909 |
Table 7
Assessment results of structural equation modeling."
Path | Path coefficient | Mean | Standard deviation | t statistic | P value |
---|---|---|---|---|---|
From EE to BI | 0.002 | 0.003 | 0.037 | 0.058 | 0.953 |
From FC to BI | 0.086 | 0.087 | 0.040 | 2.162 | 0.031 |
From H to BI | -0.001 | 0.000 | 0.039 | 0.017 | 0.987 |
From HM to BI | 0.262 | 0.262 | 0.048 | 5.502 | 0.000 |
From PE to BI | 0.292 | 0.291 | 0.040 | 7.348 | 0.000 |
From PV to BI | -0.060 | -0.059 | 0.040 | 1.484 | 0.138 |
From SI to BI | 0.259 | 0.258 | 0.028 | 9.362 | 0.000 |
Fig. 1.
Results of structural equation modeling. PE, performance expectancy; EE, effort expectancy; SI, social influence; BI, behavioral intention; FC, facilitating conditions; HM, hedonic motivation; PV, price value; H, habit; R2, coefficient of determination; Q2, cross-validated redundancy; f2, effect size; **, statistical significance at P≤0.05 level. The first number on the horizontal line represents the path coefficient of the model."
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