| Literature DB >> 35800337 |
Teng Su1.
Abstract
With the development of big data concept and technology, big data has an important impact on human development. This paper studies the relationship between the consumption pattern and mental health of enterprise employees under the normalization of epidemic prevention and control. Starting from the consumption structure and behavior of enterprise employees, it defines the meaning of enterprise employees' consumption and the connotation of enterprise employees' health psychology and analyzes the relationship between consumption behavior and consumption psychology and the elements of enterprise employees' health psychology. Based on the change of employees' income structure and consumption patterns, this paper speculates the relationship between employees' consumption patterns and mental health, analyzes the correlation between employees' consumption patterns and mental health through a questionnaire survey, and calculates the Correlation Clustering statistical results. It plays an important role in building a good enterprise staff consumption culture under the normalization of epidemic prevention and control and effectively realizes the significance of purifying the social consumption environment.Entities:
Mesh:
Year: 2022 PMID: 35800337 PMCID: PMC9256415 DOI: 10.1155/2022/6894141
Source DB: PubMed Journal: J Environ Public Health ISSN: 1687-9805
Figure 1Flow chart of research ideas on the correlation between employees' consumption patterns and mental health.
Proportion of capital sources of employees' consumption in 2018.
| The source of enterprise employees' consumption funds | Number/person | Proportion/% |
|
| ||
| Wages | 986 | 32.87% |
| Credit card | 523 | 17.43% |
| Flowers | 1062 | 35.40% |
| Bank loans | 426 | 14.20% |
| Other | 3 | 0.01% |
| Total | 3000 | 100% |
Proportion of capital sources of enterprise employees' consumption in 2020.
| The source of enterprise employees' consumption funds | Number/person | Proportion/% |
|
| ||
| Wages | 1868 | 62.23% |
| Credit card | 298 | 9.93% |
| Flowers | 663 | 22.10% |
| Bank loans | 148 | 4.93% |
| Other | 23 | 0.07% |
| Total | 3000 | 100% |
Consumption analysis of employees in different enterprises in 2018.
| Salary range (yuan) | Consumption pattern of enterprise employees | |||
| Huabei, credit card | Cash | WeChat, Alipay | Total number | |
|
| ||||
| 0–3000 | 312 | 98 | 590 | 1000 |
| 3000–5000 | 385 | 215 | 160 | 760 |
| 5000–8000 | 58 | 94 | 88 | 240 |
| 8000–10000 | 100 | 120 | 280 | 500 |
| 10000–15000 | 50 | 155 | 95 | 300 |
| Over 15000 | 15 | 87 | 98 | 200 |
Consumption analysis of employees in different enterprises in 2020.
| Salary range (yuan) | Consumption pattern of enterprise employees | |||
| Huabei, credit card | Cash | WeChat, Alipay | Total number | |
|
| ||||
| 0–3000 | 122 | 96 | 982 | 1200 |
| 3000–5000 | 285 | 220 | 45 | 550 |
| 5000–8000 | 45 | 58 | 127 | 230 |
| 8000–10000 | 189 | 301 | 310 | 800 |
| 10000–15000 | 4 | 21 | 95 | 120 |
| Over 15000 | 12 | 33 | 55 | 100 |
Correlation between consumption patterns and mental health after cluster analysis.
| Consumption level/month | Type I | Type II | Type III |
|
|
| ||||
| 0–500 | 55.823 ± 1.66 | 43.935 ± 1.08 | 55.842 ± 7.16 | 63.554 |
| 500–1000 | 53.832 ± 1.88 | 23.845 ± 1.31 | 55.643 ± 2.62 | 231.543 |
| 1000–2000 | 14.411 ± 2.16 | 53.653 ± 2.26 | 55.643 ± 4.51 | 164.553 |
| 3000–5000 | 22.563 ± 6.43 | 76.753 ± 4.86 | 55.635 ± 1.99 | 431.542 |
| 5000–8000 | 52.521 ± 3.11 | 23.532 ± 2.56 | 55.342 ± 1.97 | 643.231 |
| 8000–15000 | 54.376 ± 4.32 | 53.643 ± 4.16 | 55.654 ± 1.76 | 743.321 |
| 15000–20000 | 65.887 ± 3.13 | 35.326 ± 3.32 | 55.133 ± 1.54 | 234.664 |
| 20000–50000 | 54.896 ± 4.21 | 64.642 ± 5.33 | 55.568 ± 1.64 | 243.431 |
| Over 50000 | 32.843 ± 2.16 | 66.532 ± 6.16 | 55.642 ± 1.31 | 532.321 |
| Class size | 46.25% | 24.21% | 29.54% | — |