Understanding the Effects of eWOM Antecedents on Online Purchase Intention in China
Abstract
:1. Introduction
2. Theoretical Background
2.1. Online Purchase Intention
2.2. Social Identity Theory
3. Conceptual Model and Hypothesis Development
3.1. Fashion Involvement
3.2. Sense of Belonging
3.3. Trust
3.4. Tie Strength
3.5. Informational Influence
3.6. Moderating Role of Social Media Usage
4. Methodology
4.1. Sample and Data Collection
4.2. Instrument Development
4.3. Result
4.4. Convergent and Discriminant Validity
5. Results of Proposed Hypothesis
6. Discussion
7. Theoretical Implication
8. Managerial Implications
9. Limitations and Avenues for Future Developments
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Measure | Category | Frequency | % |
---|---|---|---|
Gender | Male | 263 | 55.13 |
Female | 214 | 44.86 | |
AGE | 18–25 | 209 | 43.81 |
26–30 | 115 | 24.10 | |
31–40 | 89 | 18.65 | |
Over 40 | 64 | 13.41 | |
Education Level | Intermediate/High School | 47 | 9.85 |
Bachelors | 193 | 40.46 | |
Masters | 110 | 23.06 | |
Doctoral/PhD | 69 | 14.46 | |
Others | 58 | 12.15 | |
Frequency of using WeChat | Many times a day | 287 | 60.16 |
Several times a day | 157 | 32.91 | |
Once a day | 33 | 6.91 | |
Online Shopping Experience through WeChat. | >1 Years | 97 | 20.33 |
1–2 Years | 196 | 41.09 | |
3–4 Years | 117 | 24.52 | |
<4 Years | 67 | 14.04 | |
eWOM posting experience on social Media sites (WeChat) | Never | 15 | 3.14 |
Few (1–2 times) | 47 | 9.85 | |
Frequently (2–3 times) | 148 | 31.02 | |
Often (more than 3 times) | 267 | 55.97 |
Key Variables | Items | Means | SD | Item Loading | CR | AVE | Cronbach’s | KMO |
---|---|---|---|---|---|---|---|---|
Fashion involvement | 6 | 4.101 | 1.32 | 0.82–0.93 | 0.921 | 0.626 | 0.729 | 0.79 |
Sense of belonging | 3 | 3.220 | 1.37 | 0.79–0.91 | 0.890 | 0.620 | 0.878 | 0.81 |
Trust | 3 | 3.542 | 1.21 | 0.86–0.94 | 0.791 | 0.612 | 0.988 | 0.79 |
Tie strength | 4 | 3.213 | 1.12 | 0.77–0.89 | 0.881 | 0.717 | 0.705 | 0.69 |
Informational influence | 3 | 4.011 | 1.42 | 0.82–0.93 | 0.858 | 0.693 | 0.912 | 0.82 |
eWOM intention | 3 | 3.212 | 1.71 | 0.86–0.95 | 0.896 | 0.710 | 0.878 | 0.66 |
Purchase intention | 4 | 4.544 | 1.45 | 0.82–0.94 | 0.813 | 0.703 | 0.808 | 0.84 |
Social media | 4 | 3.331 | 1.31 | 0.81–0.95 | 0.898 | 0.706 | 0.856 | 0.71 |
Key Variables | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
---|---|---|---|---|---|---|---|---|
(1) Fashion involvement (FI) | _ | |||||||
(2) Sense of belonging (SB) | 0.245 | _ | ||||||
(3) Trust (TT) | 0.212 | 0.331 | _ | |||||
(4) Tie strength (TS) | 0.185 | 0.112 | 0.211 | _ | ||||
(5) Informational influence (II) | 0.322 | 0.476 | 0.432 | 0.414 | _ | |||
(6) Electronic word-of-mouth (eWOM) | 0.412 | 0.329 | 0.587 | 0.345 | 0.424 | _ | ||
(7) Purchase intention (PI) | 0.409 | 0.552 | 0.434 | 0.55 | 0.342 | 0.434 | _ | |
(8) Social media (SM) | 0.511 | 0.576 | 0.441 | 0.597 | 0.551 | 0.478 | 0.448 | _ |
H | Relationship | Estimates | SE | CR |
---|---|---|---|---|
H1a | Fashion involvement → eWOM | 0.73 | 0.159 | 2.311 *** |
H2a | Sense of Belonging → eWOM | 0.43 | 0.209 | 2.442 *** |
H3a | Trust → eWOM | 0.37 | 0.185 | 2.167 ** |
H4a | Tie Strength → eWOM | 0.03 | 0.193 | 1.878 *** |
H5a | Informational Influence → eWOM | 0.63 | 0.175 | 2.434 ** |
Moderating Effect | ||||
H6 | eWOM * social Media → purchase intention | 1.32 | 0.341 | 3.765 *** |
Dependent Variable | Effect of IV on M (a) | Effect of M on DV (b) | Total Effect of IV on DV (c) | Direct Effect of IV on DV(c’) | Bootstrap Result for Indirect Effect (ab) | Result | |||||
---|---|---|---|---|---|---|---|---|---|---|---|
β | t | Β | t | β | t | β | t | LL 95% CI | UL 95% CI | ||
FI-eWOM-PI | 0.42 ** | 12.87 | 0.68 ** | 12.07 | 0.46 * | 19.34 | 0.27 ** | 9.29 | 0.192 | 0.294 | Supported |
SB-eWOM-PI | 0.28 ** | 8.36 | 0.39 ** | 10.78 | 0.52 ** | 12.56 | 0.39 * | 11.83 | 0.186 | 0.263 | Supported |
TR-eWOM-PI | 0.17 ** | 11.65 | 0.11 ** | 8.32 | 0.54 ** | 27.65 | 0.42 ** | 5.65 | 0.193 | 0.432 | Supported |
II-eWOM-PI | 0.18 ** | 11.64 | 0.12 ** | 8.56 | 0.55 ** | 18.12 | 0.40 ** | 10.12 | 0.194 | 0.455 | Supported |
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Bilal, M.; Jianqiu, Z.; Dukhaykh, S.; Fan, M.; Trunk, A. Understanding the Effects of eWOM Antecedents on Online Purchase Intention in China. Information 2021, 12, 192. https://doi.org/10.3390/info12050192
Bilal M, Jianqiu Z, Dukhaykh S, Fan M, Trunk A. Understanding the Effects of eWOM Antecedents on Online Purchase Intention in China. Information. 2021; 12(5):192. https://doi.org/10.3390/info12050192
Chicago/Turabian StyleBilal, Muhammad, Zeng Jianqiu, Suad Dukhaykh, Mingyue Fan, and Aleš Trunk. 2021. "Understanding the Effects of eWOM Antecedents on Online Purchase Intention in China" Information 12, no. 5: 192. https://doi.org/10.3390/info12050192
APA StyleBilal, M., Jianqiu, Z., Dukhaykh, S., Fan, M., & Trunk, A. (2021). Understanding the Effects of eWOM Antecedents on Online Purchase Intention in China. Information, 12(5), 192. https://doi.org/10.3390/info12050192