Figure 1:
Research Framework
Table 1:
Participants’ demographics (N = 261)
| Participants’ Profile | Percentage % |
|---|---|
| Gender | |
| Male | 68 |
| Female | 32 |
| Age | |
| Less than 30 years | 16.5 |
| Between 30 - 39 | 39.8 |
| Between 40 - 49 | 33.7 |
| More than 50 years | 10.0 |
| Marital Status | |
| Single | 57.9 |
| Married | 42.1 |
| Education | |
| High school graduate | 15.6 |
| Bachelor’s degree | 48.9 |
| Associate’s degree | 35.5 |
| Other | 0 |
Table 2:
Descriptive statistics
| Factor/Variable | Mean | Std. Dev. |
|---|---|---|
| Customer beliefs | 3.8 | 0.577 |
| – Review authenticity | 3.7 | 0.637 |
| – Trust in content sources | 3.4 | 0.521 |
| – The tone of online reviews | 4.3 | 0.574 |
| Customer trust | 4.4 | 0.402 |
| Brand reputation | 4.4 | 0.551 |
| Purchase intention | 4.2 | 0.540 |
Table 3:
Research model statistics
| Factor/Variable | Loading | CR | CA | AVE | Std. Deviation |
|---|---|---|---|---|---|
| Customer beliefs | 0.948 | 0.871 | 0.726 | 0.289 | 0.577 |
| Customer trust | 0.823 | 0.913 | 0.850 | 0.201 | 0.402 |
| Brand reputation | 0.956 | 0.949 | 0.747 | 0.276 | 0.551 |
| Purchase intention | 0.811 | 0.85 | 0.778 | 0.270 | 0.540 |
Table 4:
The correlation between fake online reviews and study variables.
Table 5:
Structural path results
| Hypothesis | R2 | β | t-values | P Value | VIF | Result |
|---|---|---|---|---|---|---|
| H1 Fake online reviews - Customer belief | 0.416 | 0.191 | 3.011 | 0.000 | 1.025 | Accepted |
| H2 Customer belief - Customer trust | 0.236 | 0.205 | 3.006 | 0.002 | 1.000 | Accepted |
| H3 Customer trust - Brand reputation | 0.312 | 0.283 | 4.544 | 0.000 | 1.088 | Accepted |
| H4 Customer trust - Purchase intention | 0.463 | 0.681 | 4.876 | 0.000 | 1.000 | Accepted |
Figure 2:
Research Model Result
| Indicators | (Adapted from Berry, 2024; Harrison-Walker & Jiang, 2023) |
|---|---|
| 1 - Belief in reviews | |
| A. Authenticity | |
| – Overlap | |
| Fake reviews are time-stamped and too close to each other, even though posted by different reviewers. Reviews that sound or look similar are fake. Fake reviews may contain repeated words from other reviews in the review set. | |
| – Non-compliance | |
| Fake reviews may contain spelling errors. Fake reviews may contain improper grammar. Fake reviews contain phrases copied directly from the product description page. | |
| – Details | |
| Fake reviews are not very specific in detail. Fake reviews do not seem to be written by customers who know much about the real product. Fake reviews are not balanced or two-sided showing both pros and cons of the product in a single review. | |
| – Platforms | |
| Before buying a service or visiting a restaurant, do you check online reviews on their websites or platforms? Upon reviewing the online restaurant reviews, I distrusted the website responsible for hosting the reviews. Some restaurant owners/managers ask customers to leave a review on their platforms. | |
| B. Content sources | |
| – Reviewer validity | |
| Fake reviews may be posted by reviewers with nonsensical usernames like x827bdjn19. A reviewer with no photo or missing details may post a fake review. Fake reviewers use excessive phrases (such as ‘This is the last × you will ever have to buy!’) Fake reviews do not have photos or videos about real experiences. | |
| C. Tone of reviews | |
| Fake reviews are extremely positive. Fake reviews are extremely negative. Fake reviews show a significant positive bias compared to negative reviews. | |
| 2 - Fake reviews and customer trust | |
| Online fake reviews are true (from real people with real experiences)? Online restaurant reviews use misleading tactics to convince consumers to dine in. Knowing some reviews are fake would influence your trust in other reviews. My trust is unaffected by online reviews, even if they are fake when it comes to a specific brand. After getting deceived in a restaurant by trusting online fake reviews, it makes you disappointed. | |
| 3 - Brand Reputation | |
| Did your perception of online restaurant reviews affect your interest in purchasing the brand? After reading the online reviews, did you find the brand less appealing? Do you think some business owners may ask customers or hired employees to leave fake reviews against their competitors? | |
| 4 - Purchase Intention | |
| Do you believe that your decision to make a purchase can be influenced by how much you trust online reviews? Fake negative reviews significantly impact whether customers decide to make a purchase. I will choose the restaurant due to the customer reviews. Reading online reviews caused my interest in purchasing the brand to decline. | |