[论文解读] Decision Towards Green Careers and Sustainable Development
本研究应用Bellinger的多准则决策方法,并与Gale-Shapley算法进行比较,以识别弗罗茨瓦夫技术大学(WUT)毕业生在绿色职业选择中最具影响力的准则。结果表明,职业发展是首要因素,其次是薪资和工作地点,两种方法均得出p4为最优工作匹配,凸显了可持续性与个人成长在职业决策中的重要性。
The graduates careers are the most spectacular and visible outcome of excellent university education. This is also important for the university performance assessment when its graduates can easily find jobs in the labor market. The information about graduates matching their qualifications and fields of studies versus undertaken employment, creates an important set of data for future students and employers to be analyzed. Additionally, there is business environment pressure to transform workplaces and whole organizations towards a more green and sustainable form. Green Jobs (GJ) are the elements of the whole economic transformation. This change is based on the green qualifications and green careers which translate theoretical assumptions into business language. Therefore, the choice of future career path is based on specified criteria, which were examined by surveys performed among graduates by the career office at Wroclaw University of Technology (WUT) in Poland. The aim of this article was to address the question about the most significant criteria of green career paths among graduates of WUT in 2019. Special attention was paid to the GJ understood as green careers. In this article, the multi-criteria Bellinger method was explained, presented, and then used to analyze chosen factors of choice graduates career paths and then compared with Gale-Shapley algorithm results in a comparative analysis. Future research can develop a graduate profile willing to be employed in GJ.
研究动机与目标
- 识别2019年弗罗茨瓦夫技术大学(WUT)毕业生在绿色职业决策中最具影响力的准则。
- 评估Bellinger多准则决策方法在职业路径选择中的有效性。
- 将Bellinger方法的结果与Gale-Shapley算法的结果进行比较,以验证准则与职位匹配的一致性。
- 为理解可持续发展原则如何塑造毕业生职业偏好提供支持。
- 基于WUT校友的实证数据,支持构建绿色工作岗位的毕业生画像。
提出的方法
- 应用Bellinger多准则决策方法,根据加权准则对职位进行排序。
- 识别并赋予11项准则权重,包括职业发展、薪资、工作地点和教育相关性。
- 通过将准则值与分配权重相乘,计算每个职位(p1至p5)的总评分。
- 使用Gale-Shapley算法模拟准则与职位之间的稳定匹配。
- 对两种方法的结果进行对比分析,以评估决策结果的一致性与可靠性。
- 通过2019年WUT毕业生的问卷调查收集数据,准则来源于劳动力市场期望与可持续发展指标。
实验结果
研究问题
- RQ1哪些准则对WUT毕业生选择绿色职业最具影响力?
- RQ2Bellinger多准则方法在基于毕业生偏好的职位排序中表现如何?
- RQ3Bellinger方法的结果与Gale-Shapley算法在准则与职位匹配方面的一致性程度如何?
- RQ4职业发展、薪资以及居住地接近度等因素如何影响近期工程与技术类毕业生的绿色职业选择?
- RQ5这些发现对大学和雇主在制定绿色岗位招聘与职业发展项目方面有何启示?
主要发现
- 在Bellinger方法中,职位p4获得最高总评分(56.87),表明其在加权准则下为最优匹配。
- Gale-Shapley算法将c1-p4配对(职业发展与职位p4)识别为最稳定且最偏好匹配,确认p4为首选。
- 职业发展成为最关键准则,权重为0.107,超过薪资(c2,权重0.105)和教育相关性(c3,权重0.101)。
- 职位p5评分最低(30.63),表明其为五项职位中吸引力最低者。
- Bellinger方法与Gale-Shapley算法结果的一致性验证了决策框架的可靠性。
- 教育相关性(c3)并非首要准则,表明毕业生更重视长期成长与工作满意度,而非专业领域匹配。
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