The best way to conference proceedings by Francis Academic Press

Web of Proceedings - Francis Academic Press
Web of Proceedings - Francis Academic Press

Comprehensive Evaluation of Working Environment Based on Grey Clustering

Download as PDF

DOI: 10.25236/edssr.2020.032


Aoyang Li

Corresponding Author

Aoyang Li


Employment and job hunting are an eternal topic. Each person has to take on certain responsibilities as being a member of society. Throughout the continuous development of society from the past decade, it is way more difficult now than before for current undergraduates to find a suitable job. In reality, many college graduates feel that the employment situation is severe, and finding a job is not easy. A large part of the reason for this psychology is that the high-end talents in various positions are now saturated, and people are anxious about finding a suitable job. Therefore, if you encounter some difficulties in the process of job hunting, you must put yourself in the right frame of mind and treat them objectively. We take the selection order of four companies as an example. Firstly, we analyze the influence of job search factors. In order to better help contemporary college students find a suitable job, we use the entropy method to analyze the degree of influence of five factors, including academic qualifications, attitude, professional evaluation, practical experience, and expression ability, on the job search for candidates. We hope candidates be able to focus on the aspects that the company values and work hard on the corresponding aspects to help them find their favorite jobs. Then, we build a comprehensive evaluation model of the working environment. We utilize the grey cluster evaluation method to study the impact of five aspects, including benefits, working conditions, labor intensity, promotion opportunities, and further study opportunities on applicants’ selection of companies. And a selection order of the four companies is given in the end.


Recruitment, Employment, Entropy weight method, Grey clustering assessment, Recommendations