Muslim Clothing Online Purchases in Indonesia during COVID-19 Crisis
Abstract
:1. Introduction
2. Literature Review
2.1. Theory of Planned Behavior
2.2. Buying Intention
2.3. Attitude
2.4. Subjective Norm
2.5. Behavioral Control
2.6. Religious Belief
2.7. Conceptual Model
2.8. Thinking Framework and Hypotheses
3. Research Methodology
3.1. Types of Research
3.2. Demographic Characteristics of Respondents
3.3. Data Analysis Method
4. Results
4.1. Validity and Reliability Test
4.1.1. Validity Test
4.1.2. Reliability Test
4.1.3. Goodness of Fit (GOF)
4.2. Hypotheses Tests
5. Discussion
5.1. Attitude towards the Online Buying Intention of Muslim Clothing in Indonesia during the COVID-19 Crisis
5.2. Subjective Norm towards the Online Buying Intention of Muslim Clothing in Indonesia during COVID-19 Crisis
5.3. Perceived Behavioral Control the Online Buying Intention of Muslim Clothing in Indonesia during COVID-19 Crisis
5.4. Attitude Influences the Online Buying Intention of Muslim Clothing in Indonesia with Religious Belief as Moderating Variable
5.5. Subjective Norm Influences the Online Buying Intention of Muslim Clothing in Indonesia during the COVID-19 Crisis with Religious Belief as Moderating Variable
5.6. Perceived Behavioral Control Influences Online Buying Intention of Muslim Clothing in Indonesia during COVID-19 Crisis with Religious Belief as Moderating Variable
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Demographic Attributes | Choice | Number of Answers | Percentage |
---|---|---|---|
Gender | Man | 190 | 24.9% |
Woman | 572 | 75.1% | |
Total Respondents | 762 | 100% | |
Your Age | 12—15 years | 12 | 1.6% |
16—18 years | 84 | 11% | |
19—21 years | 145 | 19% | |
>21 years old | 521 | 68.4% | |
Total Respondents | 762 | 100% | |
Marital status | Not married yet | 407 | 53.4% |
Marry | 355 | 46.6% | |
Total Respondents | 762 | 100% | |
Your Occupation | Student/Student | 320 | 42% |
Government employees | 115 | 15% | |
Private employees | 118 | 15% | |
TNI/POLRI | 25 | 3.3% | |
Businessman | 28 | 3.7% | |
Other | 156 | 20% | |
Total Respondents | 762 | 100% | |
Your monthly income | <IDR 2,000,000 | 420 | 55.1% |
Between IDR 2,000,000 to IDR 5,000,000 | 203 | 26.6% | |
Between IDR 5,000,000 to IDR 10,000,000 | 97 | 12.7% | |
Between IDR 10,000,000 to IDR 50,000,000 | 16 | 2.1% | |
>Between IDR 50,000,000 | 26 | 3.5% | |
Total Respondents | 762 | 100% | |
Your Domicile | Sumatra | 359 | 47.1% |
Java-Bali | 135 | 17.7% | |
Borneo | 72 | 9.5% | |
Sulawesi | 53 | 7% | |
NTB-NTT | 48 | 6.3% | |
Maluku | 46 | 6.1% | |
Papua | 49 | 6.4% | |
Total Respondents | 762 | 100% |
Variable Latent | Variable Manifest | Critical | Estimate | Conclusion |
---|---|---|---|---|
Factor Loading | Factor Loading | |||
ATT | ATT1 | 0.5–0.7 | 0.67 | Valid |
ATT2 | 0.77 | Valid | ||
ATT3 | 0.71 | Valid | ||
ATT4 | 0.69 | Valid | ||
ATT5 | 0.69 | Valid | ||
ATT6 | 0.66 | Valid | ||
ATT7 | 0.71 | Valid | ||
ATT8 | 0.69 | Valid | ||
ATT9 | 0.61 | Valid | ||
NS | NS1 | 0.5–0.7 | 0.70 | Valid |
NS2 | 0.80 | Valid | ||
NS3 | 0.83 | Valid | ||
NS4 | 0.73 | Valid | ||
NS5 | 0.65 | Valid | ||
PD | PD3 | 0.5–0.7 | 0.62 | Valid |
PD4 | 0.68 | Valid | ||
PD5 | 0.79 | Valid | ||
PD6 | 0.84 | Valid | ||
PD7 | 0.81 | Valid | ||
BI | BI1 | 0.5–0.7 | 0.67 | Valid |
BI2 | 0.73 | Valid | ||
BI3 | 0.72 | Valid | ||
BI4 | 0.72 | Valid | ||
BI5 | 0.71 | Valid | ||
BI6 | 0.76 | Valid | ||
BI7 | 0.78 | Valid | ||
BI8 | 0.77 | Valid | ||
BI9 | 0.53 | Valid | ||
BI13 | 0.61 | Valid | ||
BI14 | 0.68 | Valid | ||
BI15 | 0.71 | Valid | ||
BI16 | 0.73 | Valid | ||
RLG | RLG1 | 0.5–0.7 | 0.50 | Valid |
RLG2 | 0.54 | Valid | ||
RLG3 | 0.51 | Valid | ||
RLG5 | 0.53 | Valid | ||
RLG6 | 0.56 | Valid | ||
RLG8 | 0.58 | Valid | ||
RLG9 | 0.58 | Valid | ||
RLG10 | 0.59 | Valid | ||
RLG11 | 0.58 | Valid | ||
RLG12 | 0.60 | Valid | ||
RLG13 | 0.60 | Valid | ||
RLG14 | 0.56 | Valid | ||
RLG15 | 0.57 | Valid |
Variable Latent | Variable Manifest | Estimate | Cronbach’s Alpha | Composite Reliability | Conclusion |
---|---|---|---|---|---|
Factor Loading | |||||
ATT | ATT1 | 0.67 | 0.7 | 0.94 | Reliable |
ATT2 | 0.77 | ||||
ATT3 | 0.71 | ||||
ATT4 | 0.69 | ||||
ATT5 | 0.69 | ||||
ATT6 | 0.66 | ||||
ATT7 | 0.71 | ||||
ATT8 | 0.69 | ||||
ATT9 | 0.61 | ||||
NS | NS1 | 0.70 | 0.7 | 0.94 | Reliable |
NS2 | 0.80 | ||||
NS3 | 0.83 | ||||
NS4 | 0.73 | ||||
NS5 | 0.65 | ||||
PD | PD3 | 0.62 | 0.7 | 0.94 | Reliable |
PD4 | 0.68 | ||||
PD5 | 0.79 | ||||
PD6 | 0.84 | ||||
PD7 | 0.81 | ||||
BI | BI1 | 0.67 | 0.7 | 0.98 | Reliable |
BI2 | 0.73 | ||||
BI3 | 0.72 | ||||
BI4 | 0.72 | ||||
BI5 | 0.71 | ||||
BI6 | 0.76 | ||||
BI7 | 0.78 | ||||
BI8 | 0.77 | ||||
BI9 | 0.53 | ||||
BI13 | 0.61 | ||||
BI14 | 0.68 | ||||
BI15 | 0.71 | ||||
BI16 | 0.73 | ||||
RLG | RLG1 | 0.50 | 0.7 | 0.97 | Reliable |
RLG2 | 0.54 | ||||
RLG3 | 0.51 | ||||
RLG5 | 0.53 | ||||
RLG6 | 0.56 | ||||
RLG8 | 0.58 | ||||
RLG9 | 0.58 | ||||
RLG10 | 0.59 | ||||
RLG11 | 0.58 | ||||
RLG12 | 0.60 | ||||
RLG13 | 0.60 | ||||
RLG14 | 0.56 | ||||
RLG15 | 0.57 |
No | Measurement of Goodness of Fit | Cut-off Value | Estimation Result | Conclusion |
---|---|---|---|---|
absolute fit indices | ||||
1 | Chi-square P | Small scores p ≥ 0.05 | 6031.22 0.00 | Poor Fit |
2 | RMSEA | ≤0.08 | 0.069 | Good Fit |
3 | ECVI | (7.413—8.307) | 8.26 | Good Fit |
4 | RMR | ≤0.05 | 0.05 | Good Fit |
incremental fit indices | ||||
5 | NFI | ≥0.90 | 0.97 | Good Fit |
6 | CFI | ≥0.95 | 0.98 | Good Fit |
7 | IFI | >0.90 | 0.98 | Good Fit |
8 | RFI | >0.90 | 0.97 | Good Fit |
9 | NNFI | ≥0.90 | 0.98 | Good Fit |
parsimony fit indices | ||||
10 | PNFI | ≥0.90 | 0.92 | Good Fit |
Hypotheses | Exogent Variables | Endogen Variables | tstatistic | ttabel | Criterion | Conclusion |
---|---|---|---|---|---|---|
1 | ATT | BI | 5.78 | 1.96 | Significant | Complied |
2 | NS | BI | 3.44 | 1.96 | Significant | Complied |
3 | PD | BI | 4.25 | 1.96 | Significant | Complied |
4 | ATT*RLG | BI | 2.51 | 1.96 | Significant | Strengthening |
5 | NS*RLG | BI | −1.85 | 1.96 | Not Significant | Weakening |
6 | PD*RLG | BI | −0.44 | 1.96 | Not Significant | Weakening |
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Salim, M.; Aprianto, R.; Anwar Abu Bakar, S.; Rusdi, M. Muslim Clothing Online Purchases in Indonesia during COVID-19 Crisis. Economies 2022, 10, 19. https://doi.org/10.3390/economies10010019
Salim M, Aprianto R, Anwar Abu Bakar S, Rusdi M. Muslim Clothing Online Purchases in Indonesia during COVID-19 Crisis. Economies. 2022; 10(1):19. https://doi.org/10.3390/economies10010019
Chicago/Turabian StyleSalim, Muhartini, Ronal Aprianto, Syaiful Anwar Abu Bakar, and Muhammad Rusdi. 2022. "Muslim Clothing Online Purchases in Indonesia during COVID-19 Crisis" Economies 10, no. 1: 19. https://doi.org/10.3390/economies10010019
APA StyleSalim, M., Aprianto, R., Anwar Abu Bakar, S., & Rusdi, M. (2022). Muslim Clothing Online Purchases in Indonesia during COVID-19 Crisis. Economies, 10(1), 19. https://doi.org/10.3390/economies10010019