کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1096524 1487487 2006 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Discriminating relative workload level by data envelopment analysis
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی صنعتی و تولید
پیش نمایش صفحه اول مقاله
Discriminating relative workload level by data envelopment analysis
چکیده انگلیسی

The study investigates a method of the extended data envelopment analysis (DEA) model to discriminate relative workload level within a group of employees, in which subjective subscales are introduced. The model chooses the most favorable set of weights under the constraint for each employee. Hence, the workload scores calculated by the extended DEA model are more considerate and friendly to employees than the method in which weights are determined by individual judgment. The proposed approach eliminates the need to specify a priori weights for each assessing factor, and it can discriminate relative workload among employees and help managers making decisions with regard to suitable human resource practices to strengthen employee capability and achieve higher performance.Relevance to industryAssessing workload is an important issue in the management and health of employees. A long-term heavy workload can affect an employee's physical or mental health, performance, or productivity. A heavy workload is a component of job stress and has a negative impact on turnover. This loss of employees and their output leads to higher costs for an organization. After understanding the relative overall workload level within a group of employees, the manager can reassign tasks to level the workload and make informed decisions about human resource practices, such as in-service education or job rotation to strengthen employee capability and achieve higher performance.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Industrial Ergonomics - Volume 36, Issue 9, September 2006, Pages 773–778
نویسندگان
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