Factors Determining the Behavioral Intention of Using Food Delivery Apps during COVID-19 Pandemics
Abstract
:1. Introduction
1.1. Food Delivery Apps (FDAs)
1.2. Effects of COVID-19 on Online Delivery Business
2. Materials and Methods
UTAUT Model
3. Results
3.1. Participants Demographics
3.2. Model Results
4. Discussions
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Estimates | CR | AVE | ||
---|---|---|---|---|
Performance Expectancy | PE3 | 0.723 | ||
PE2 | 0.898 | |||
PE1 | 0.821 | 0.7281 | 0.72199 | |
Effort Expectancy | EE3 | 0.721 | ||
EE2 | 0.821 | |||
EE1 | 0.823 | 0.8727 | 0.7281 | |
Social Influence | SI3 | 0.898 | ||
SI2 | 0.723 | |||
SI1 | 0.834 | 0.8781 | 0.6332 | |
Timeliness | TM3 | 0.882 | ||
TM2 | 0.872 | |||
TM1 | 0.723 | 0.7894 | 0.7792 | |
Task-Technology Fit | TT1 | 0.836 | ||
TT2 | 0.792 | 0.8393 | 0.6892 | |
TT3 | 0.872 | |||
Behavioral Intention to Use | BIU1 | 0.632 | ||
BIU2 | 0.723 | |||
BIU3 | 0.628 | 0.6728 | 0.5289 | |
Perceived Trust | PT1 | 0.881 | ||
PT2 | 0.755 | 0.6922 | 0.5287 | |
PT3 | 0.729 | |||
Perceived Safety | PS1 | 0.792 | ||
PS2 | 0.729 | 0.8745 | 0.7278 |
N | Percentage | ||
---|---|---|---|
Gender | Male | 192 | 48 |
Female | 210 | 52 | |
Age | Below 21 | 121 | 30 |
21–30 | 217 | 54 | |
31–40 | 36 | 9 | |
Above 40 | 28 | 7 | |
Education level | High School | 24 | 6 |
Bachelor’s Degree | 265 | 66 | |
Master’s Degree | 81 | 20 | |
PhD | 32 | 8 | |
Frequency of use | 0–3 times per week | 76 | 55 |
Above 3 times per week | 121 | 45 | |
Total | 402 | 100 |
Relationship | Beta (β) | S.E | CR | p-Value | ||
---|---|---|---|---|---|---|
BIU | ← | EE | 0.311 | 0.013 | 10.957 | *** |
BIU | ← | SI | 0.207 | 0.012 | 7.744 | *** |
BIU | ← | TT | 0.491 | 0.016 | 14.694 | *** |
BIU | ← | PE | 0.106 | 0.011 | 4.289 | *** |
BIU | ← | PS | 0.305 | 0.014 | 9.744 | *** |
BIU | ← | TM | 0.563 | 0.015 | 16.338 | *** |
BIU | ← | PT | 0.444 | 0.013 | 14.324 | *** |
Hypothesis | Relationship | Beta (β) | p-Value | Accepted/Rejected | ||
---|---|---|---|---|---|---|
Hypothesis 2 (H2) | BIU | ← | EE | 0.311 | *** | Accepted |
Hypothesis 3 (H3) | BIU | ← | SI | 0.207 | *** | Accepted |
Hypothesis 5 (H5) | BIU | ← | TTF | 0.491 | *** | Accepted |
Hypothesis 1 (H1) | BIU | ← | PE | 0.106 | *** | Accepted |
Hypothesis 7 (H7) | BIU | ← | PS | 0.305 | *** | Accepted |
Hypothesis 4 (H4) | BIU | ← | TM | 0.563 | *** | Accepted |
Hypothesis 6 (H6) | BIU | ← | PT | 0.444 | *** | Accepted |
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Muangmee, C.; Kot, S.; Meekaewkunchorn, N.; Kassakorn, N.; Khalid, B. Factors Determining the Behavioral Intention of Using Food Delivery Apps during COVID-19 Pandemics. J. Theor. Appl. Electron. Commer. Res. 2021, 16, 1297-1310. https://doi.org/10.3390/jtaer16050073
Muangmee C, Kot S, Meekaewkunchorn N, Kassakorn N, Khalid B. Factors Determining the Behavioral Intention of Using Food Delivery Apps during COVID-19 Pandemics. Journal of Theoretical and Applied Electronic Commerce Research. 2021; 16(5):1297-1310. https://doi.org/10.3390/jtaer16050073
Chicago/Turabian StyleMuangmee, Chaiyawit, Sebastian Kot, Nusanee Meekaewkunchorn, Nuttapon Kassakorn, and Bilal Khalid. 2021. "Factors Determining the Behavioral Intention of Using Food Delivery Apps during COVID-19 Pandemics" Journal of Theoretical and Applied Electronic Commerce Research 16, no. 5: 1297-1310. https://doi.org/10.3390/jtaer16050073