جستجوی مقالات مرتبط با کلیدواژه "انتخاب کارکنان" در نشریات گروه "مدیریت"

Since the improvement of human resource efficiency can play an effective role in the efficiency of organizations, it has always been one of the main research topics.The tendency to leave the organization is one of the factors affecting the efficiency of human capital, which can be predicted using in-data models, conditions governing the organization and the factors affecting it. For this purpose, intelligent algorithms based on neural network and multi-objective genetic algorithm have been used in this research to predict the tendency to leave an organization. In this regard, a standard dataset was created based on a questionnaire of employees satisfaction and the desire to leave the job in the Karoon Oil and Gas Production Company. Then, using an artificial neural network as a classifier and a multi-objective genetic algorithm, the important factors or features were selected. In the next step, an expert system was proposed to select effective features. In order to test and evaluate the neural network algorithm developed with the standard data set, the necessary training was provided. The results showed that by using the proposed model, not only the willingness of employees to leave the organization can be predicted with more than 88% accuracy, but also, the key factors of leaving the organization can be determined.

Maintain and enhance the quality of human resources and achieve maximum value from IT industry employees is the most important concern of managers. Most of researches in this area focus on companies’ endeavour to recruiting qualified experts in the IT industry in the next decade. The selection of qualified personnel for organizations which focus on human resouces as a strength، will be a major issue. Therefore، in this study، companies active in the field of information technology as one of the technology companies، have been examined for optimal absorption of manpower. In the present study، multi-criteria decision-making is used. IT active companies are studied in the current research. In order to design the proper employment model of this companies and due to a variety of quantitative and qualitative parameters، TOPSIS multi attribute decision making (MADM) model is used for prioritization of employment alternatives. Moreover Meta synthesis method is employed to extract the effective indices in the scientific literature. Among authentic researches، finally 7 indices are selected for TOPSIS weighted measure. According to the model، 33 alternatives are investigated at a sample active company. The model is used for three types of professions: IT project manager، information systems analyst and computer programmer. Our model is compared with the traditional methods of personnel selection. The results، shows the consistency between the model and traditional methods. At the end، cause of some contradictions is discussed.