AMOS SAMPLE DATA
This data idea is built from the article by Dinh & Lee (2022) – ““I want to be trendy like influencers” – how “fear of missing out” leads to determined product purchase intention received by social media influencers.” See full article here.
Dinh, T. C. T., & Lee, Y. (2022). “I want to be as trendy as influencers”–how “fear of missing out” leads to buying intention for products endorsed by social media influencers. Journal of Research in Interactive Marketing, 16(3), 346–364.
♥ Payment and some notes with the Sample Data Set
The sample data set is compatible with the model presented here. The data set is fixed and there is no option to customize according to customer requirements. If you have any other requests please use our Data Processing service here.
Note that this dataset is not unique, so many people may have purchased it. However, currently this dataset has no users yet.
Payment method: pay first, receive data later.
Payment terms: If you buy data, please transfer money to the account:
Account holder: NGUYEN THANH TIEN
ACB Account 4707776 (THANH DA Transaction Office)
Transfer content: Data code + space + your email (only take the part before @)
For example, your email is hathu2212@gmail.com, the transfer content is as follows: Data23061101 hathu2212
After transferring, please send an email with payment documents confirming successful transfer to email address phatichamos@gmail.com or send a direct message to zalo at 0971.202.308. We will send the data file to you within 30 minutes after receiving the transfer information. The data file includes data files pre-encoded in spss and related model files if any. In the file sent to you, we have included an article inspired by creating sample data (if any).
♥ Data Information
Data code: Data23061101
Price: 439,000 VND
♥ Data Description
- Model run CB SEM using Amos software.
- Sample size: 243
- Scale: 7-point Likert
| The scale | Observed variables | Source |
| Imitate influencers | I want to be fashionable like influencers. I want to be stylish like influencers. I crave the influencer life. | Kasser et al (2004) |
| Social comparison | Influencers are able to buy better places to live (apartments, houses) than me. Influencers are able to travel more than me. Influencers are able to buy food and drinks better than me. Influencers can afford more expensive entertainment activities than me. Influencers can travel by better means of transportation (car, bus) than others. me. Influencers can afford to buy better and more clothes than me. Influencers have better access to healthcare than me. Influencers have the ability to pay for it College costs are easier than mine. | (Solberg et al., 2002) |
| FOMO (the fear of missing out)The fear of missing out | Maybe later I will regret not buying products recommended by influencers. I will worry about missing out on products recommended by influencers. I will worry that other people have the same things. more fun than I am by using products recommended by influencers. I worry that other people are having more fun with products recommended by influencers while I am not. I would feel out of touch with trends if I didn’t own products recommended by influencers. I would regret not trying products recommended by influencers. I would feel anxious for not using products recommended by influencers. I would feel upset because I missed the opportunity to use products recommended by influencers. | (Good và Hyman, 2020a) |
| Materialism | I admire people who own expensive houses, cars and clothes. The items that I own say a lot about the success of my life. I like to have many luxuries in my life. My life would be better if I owned things I don’t have yet. I would be happier if I could afford to buy more things. | (Richins, 2004) |
| Purchase intention | Products recommended by influencers influence my purchasing decisions. I buy a product because I like the personality of the influencer. I feel happy when I buy a product recommended by the influencer. enjoy famous introduction. | (Liu and Brock, 2011) |
- Description: The model has 5 factors, measured by 27 observed variables. For details, see research model + scale;
- Model running CB SEM with Amos 28: Gives good results. All hypotheses were supported.
- Statistical information section: Here, based on the original article, the information section is detailed as follows:
| Variable | Detail | Total | % |
| Gender | Male | 155 | 63.8% |
| Female | 88 | 36.2% | |
| Age | 20 below | 3 | 1.2% |
| 20-30 | 73 | 30.0% | |
| 31-40 | 117 | 48.1% | |
| 41-50 | 48 | 19.8% | |
| 50 above | 2 | 0.8% |
♥ Analysis results
See details here. Click here
