Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
How to Evaluate College Students’ Green Innovation Ability—A Method Combining BWM and Modified Fuzzy TOPSIS
Currently, enterprises are paying more and more attention to green innovation in order to reduce the negative impact on the environment and achieve sustainable development. Different from evaluating the green innovation ability of enterprises, how to evaluate a person’s green innovation ability from the perspective of open innovation is a new direction. This study aims at proposing a novel framework to evaluate college students’ green innovation ability. First, a set of criteria to evaluate college students’ green innovation ability is determined by experts using the panel consensus approach. Second, the best worst method (BWM) is used to calculate the weights of criteria. Lastly, modified fuzzy technique for order of preference by similarity to ideal solution technique (TOPSIS) technique is adopted to rank college students’ green innovation ability. Moreover, a case study is presented to verify the validity of the proposed method. The results provide implications for academic, industry, and policymakers. Specifically, through the evaluation of college students’ green innovation ability, universities can find the inadequacies in culturing students’ green innovation ability and strengthen education in the aspects corresponding to the criteria with high global weights. Companies can select the talented internship students with green innovation ability as employees and should realize that it is good for them to cultivate college students with universities. Policymakers of the education department can trace the quality of education in college senior students’ green innovation ability every year. In addition, they should pay more attention to establish policies regarding those criteria with high global weights.
How to Evaluate College Students’ Green Innovation Ability—A Method Combining BWM and Modified Fuzzy TOPSIS
Currently, enterprises are paying more and more attention to green innovation in order to reduce the negative impact on the environment and achieve sustainable development. Different from evaluating the green innovation ability of enterprises, how to evaluate a person’s green innovation ability from the perspective of open innovation is a new direction. This study aims at proposing a novel framework to evaluate college students’ green innovation ability. First, a set of criteria to evaluate college students’ green innovation ability is determined by experts using the panel consensus approach. Second, the best worst method (BWM) is used to calculate the weights of criteria. Lastly, modified fuzzy technique for order of preference by similarity to ideal solution technique (TOPSIS) technique is adopted to rank college students’ green innovation ability. Moreover, a case study is presented to verify the validity of the proposed method. The results provide implications for academic, industry, and policymakers. Specifically, through the evaluation of college students’ green innovation ability, universities can find the inadequacies in culturing students’ green innovation ability and strengthen education in the aspects corresponding to the criteria with high global weights. Companies can select the talented internship students with green innovation ability as employees and should realize that it is good for them to cultivate college students with universities. Policymakers of the education department can trace the quality of education in college senior students’ green innovation ability every year. In addition, they should pay more attention to establish policies regarding those criteria with high global weights.
How to Evaluate College Students’ Green Innovation Ability—A Method Combining BWM and Modified Fuzzy TOPSIS
Tingting Li (Autor:in) / Dan Zhao (Autor:in) / Guiyun Liu (Autor:in) / Yuhong Wang (Autor:in)
2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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