Evaluation of employment quality of college graduates based on interval MULTIMOORA with combination weights

Abstract

PurposeThe purpose of this paper is to develop a novel interval Multi-Objective Optimization by a Ratio Analysis plus the Full Multiplicative Form(MULTIMOORA) with combination weights to evaluate the employment quality of college graduates, where the criteria are expressed by interval numbers and the weights of criteria are completely unknown.Design/methodology/approachFirstly, considering the subjective uncertainty of the weights of the criteria, the interval best worst method (I-BWM) was present to determine the subjective weights of the criteria. Secondly, by the improved interval number distance measure, an improved interval deviation maximization method (I-MDM) was introduced to detemine the objective weights. In the following, based on the I-BWM and the improved I-MDM, a combination weighting method that takes into account the subjective and objective weights is proposed. Finally, a multi-criteria decision-making method based on the interval MULTIMOORA with combination weights is present to evaluate the employment quality of college graduates, and then a comparative analysis with some of the existing distance measures of interval numberswas conducted to illustrate the flexibility.FindingsAccording to the data of the Report on Employment Quality of Chinese College Graduats released by Mycos Research Institute in 2016–2020 and 2021–2022, the proposed method was used to evaluate the employment quality of college graduates during the period before and after the COVID-19 epidemic. The results verify that the method is more reasonable because the subjective and objective weights of the criteria can be fully considered. Finally, the feasibility and practicability of the proposed method are further verified by varying parameters.Originality/valuePresent an evaluation method on the employment quality of college graduates based on the Interval MULTIMOORA with combination weights considering the subjective and objective weights. And the proposed method is proved that it can provide a more reasonable evaluation results. At the same time, it is verified that the feasibility and the practicability of the proposed method are affected by varying parameters in the paper.

Evaluation of high quality and full employment based on CRITIC-entropy-TOPSIS multi-criteria framework

“…The comprehensive scores and rankings of HQaFE under different weight determination methods are shown in Table 5 and Table 6, respectively. Note that M1, M2 and M3 in Tables 5 and 6 are present the evaluation methods proposed by Xie et al (2023), Wang et al (2023) and this paper, respectively.…”

“…In this section, the entropy weight (Xie et al ., 2023) and CRITIC method (Wang et al ., 2023) are taken to compare with the proposed CRITIC-entropy model in this paper. The comprehensive scores and rankings of HQaFE under different weight determination methods are shown in Table 5 and Table 6, respectively.…”

“…From the evaluation scores shown in Table 5, the comparison between most of the evaluation scores shows that the evaluation scores obtained by the entropy-TOPSIS model (Xie et al ., 2023) are relatively the highest, the evaluation scores obtained by the CRITIC-entropy-TOPSIS model are the middle and the evaluation scores obtained by the CRITIC-TOPSIS model (Wang et al ., 2023) are relatively the lowest. The evaluation results show that the proposed CRITIC-entropy-TOPSIS framework combines the advantages of two weight determination methods.…”