How Do Fresh Live Broadcast Impact Consumers’ Purchase Intention? Based on the SOR Theory
Abstract
:1. Introduction
- How do live broadcast features such as visibility, interactivity, and authenticity impact consumers’ perceived value and trust toward the fresh live broadcast?
- Do perceived utility, hedonic value, and perceived trust influence consumers’ purchase intensions in fresh live broadcast scenarios?
- What are the most important factors in forming consumers’ perceived value and trust and driving purchase intentions of fresh products?
2. Theoretical Background and Hypothesis Development
2.1. SOR Theory
2.2. Live Streaming Features as Stimuli (S)
2.3. Perceived Value and Perceived Trust as an Organism (O)
2.4. Consumer Purchase Intension as Response (R)
2.5. Impact of Live Streaming Characteristics on Perceived Value and Perceived Trust
2.6. Impact of Perceived Value and Perceived Trust on Consumers’ Purchase Intension
3. Methodology
3.1. Sampling and Data Collection
3.2. Measurements
4. Data Analysis Results
4.1. Descriptive Statistics
4.2. Measurement Model Analysis
4.3. Structural Model
4.4. Mediating Effects
5. Discussion and Conclusions
6. Research Implications
7. Limitations and Further Research
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Characteristics | Categories | Frequency | Percentage (%) |
---|---|---|---|
Gender | male | 102 | 33.22 |
female | 205 | 66.78 | |
Age (years) | Less than 20 | 15 | 4. 89 |
20–30 | 178 | 57.98 | |
31–40 | 96 | 31.27 | |
41–50 | 10 | 3.28 | |
More than 50 | 8 | 2.64 | |
Education level | Secondary school or below | 11 | 3.58 |
Junior college | 35 | 11.40 | |
Bachelor’s | 215 | 70.03 | |
Master’s | 39 | 12.70 | |
Ph.D. | 7 | 2.30 | |
Incomes (RMB) | Less than 2000 | 40 | 13.03 |
2001–5000 | 71 | 23.13 | |
5001–8000 | 87 | 28.34 | |
8001–11,000 | 60 | 19.54 | |
Above 11,000 | 49 | 15.96 | |
Frequency of viewing live streaming content (per day) (hours) | Less than 1 | 60 | 19.54 |
1–3 | 187 | 61.51 | |
3–5 | 48 | 15.64 | |
5–7 | 8 | 2.61 | |
More than 7 | 4 | 1.30 |
Latent Variable Name | Code | Factor Load | Cronbach’s Alpha | Composite Reliability | AVE |
---|---|---|---|---|---|
Visibility (V) | V1 | 0.847 | 0.834 | 0.838 | 0.634 |
V2 | 0.734 | ||||
V3 | 0.804 | ||||
Interactivity (I) | I1 | 0.751 | 0.766 | 0.769 | 0.525 |
I2 | 0.709 | ||||
I3 | 0.714 | ||||
Authenticity (A) | A1 | 0.735 | 0.796 | 0.796 | 0.566 |
A2 | 0.767 | ||||
A3 | 0.754 | ||||
Perceived Utility value (PUV) | PUV1 | 0.838 | 0.876 | 0.875 | 0.701 |
PUV2 | 0.842 | ||||
PUV3 | 0.831 | ||||
Perceived Hedonic value (PHV) | PHV1 | 0.760 | 0.846 | 0.849 | 0.652 |
PHV2 | 0.819 | ||||
PHV3 | 0.842 | ||||
Perceived Trust (PT) | PT1 | 0.760 | 0.817 | 0.810 | 0.587 |
PT2 | 0.749 | ||||
PT3 | 0.788 | ||||
Purchase Intention (PI) | PI1 | 0.752 | 0.810 | 0.810 | 0.588 |
PI2 | 0.756 | ||||
PI3 | 0.791 |
Estimate | Standardized Estimate | S.E. | C.R. | p | Test Result | |||
---|---|---|---|---|---|---|---|---|
PUV | <--- | V | 0.423 | 0.356 | 0.1 | 4.244 | *** | H1a supported |
PHV | <--- | V | 0.302 | 0.298 | 0.103 | 2.935 | ** | H1b supported |
PT | <--- | V | 0.316 | 0.314 | 0.081 | 3.917 | *** | H1c supported |
PUV | <--- | I | 0.304 | 0.231 | 0.117 | 2.59 | * | H2a supported |
PHV | <--- | I | 0.437 | 0.390 | 0.126 | 3.459 | *** | H2b supported |
PT | <--- | I | 0.471 | 0.423 | 0.101 | 4.677 | *** | H2c supported |
PUV | <--- | A | 0.441 | 0.332 | 0.148 | 2.976 | ** | H3a supported |
PHV | <--- | A | 0.063 | 0.056 | 0.152 | 0.416 | 0.677 | H3b not supported |
PT | <--- | A | 0.313 | 0.279 | 0.12 | 2.612 | ** | H3c supported |
PI | <--- | PUV | 0.244 | 0.322 | 0.061 | 3.975 | *** | H4a supported |
PI | <--- | PHV | 0.219 | 0.246 | 0.056 | 3.906 | *** | H4b supported |
PI | <--- | PT | 0.382 | 0.427 | 0.082 | 4.686 | *** | H5 supported |
Total Effects | Indirect Effects | |||||
---|---|---|---|---|---|---|
β | T Value | β | Bootstrap 95% CI | Zero Included? | ||
V→PI | 0.601 | 14.630 ** | V→PUV→PI | 0.154 | 0.030–0.339 | No |
V→PHV→PI | 0.103 | 0.052–0.183 | No | |||
V→PT→PI | 0.126 | 0.049–0.231 | No | |||
I→PI | 0.589 | 12.914 ** | I→PUV→PI | 0.173 | 0.059–0.342 | No |
I→PHV→PI | 0.115 | 0.060–0.191 | No | |||
I→PT→PI | 0.142 | 0.040–0.268 | No | |||
A→PI | 0.618 | 14.154 ** | A→PUV→PI | 0.169 | 0.042–0.346 | No |
A→PHV→PI | 0.110 | 0.059–0.191 | No | |||
A→PT→PI | 0.134 | 0.038–0.263 | No |
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Song, Z.; Liu, C.; Shi, R. How Do Fresh Live Broadcast Impact Consumers’ Purchase Intention? Based on the SOR Theory. Sustainability 2022, 14, 14382. https://doi.org/10.3390/su142114382
Song Z, Liu C, Shi R. How Do Fresh Live Broadcast Impact Consumers’ Purchase Intention? Based on the SOR Theory. Sustainability. 2022; 14(21):14382. https://doi.org/10.3390/su142114382
Chicago/Turabian StyleSong, Zhijie, Chang Liu, and Rui Shi. 2022. "How Do Fresh Live Broadcast Impact Consumers’ Purchase Intention? Based on the SOR Theory" Sustainability 14, no. 21: 14382. https://doi.org/10.3390/su142114382