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Item type:Publication, A new approach for ranking efficient DMUs with data envelopment analysis(Emerald, 2020-07-02)Purpose: Classical models of data envelopment analysis (DEA) calculate the efficiency of decision-making units do not differentiate between efficient units. The purpose of this paper is to present a new method for ranking efficient units and compare it with the other methods presented in this field. Design/methodology/approach: In this paper, a new method is presented for ranking efficient units. To validate the proposed method, a real case, which was studied by Li et al. (2016) is examined and the rankings of the efficient units are compared with four other methods including the Andersen and Petersen’s super-efficiency, game theory and the concept of Shapley value and the technique for order of preference by similarity to ideal solution methods. Findings: The results show that there is a high correlation between the rankings of efficient units obtained by the new proposed method and the other methods such as Andersen and Petersen’s super-efficiency, game theory and Shapley value methods. Originality/value: The problem of ranking efficient units with the DEA method is an important issue for researchers. Extensive studies have been proposed to provide methods for ranking efficient units. This paper proposes a simple and fast method for ranking efficient units that achieves better results. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Evaluating efficiency in construction projects with the TOPSIS model and NDEA method considering environmental effects and undesirable data(Springer Science+Business Media, 2021-05-30)Today, project stakeholders seek to reduce the total costs and durations of projects while increasing their quality levels. Also, the governments have paid more attention to the environmental effects of projects. This study tackles the time–cost–quality-environmental effects trade-off project scheduling problem. Various activity execution modes are evaluated using the network data envelopment analysis (NDEA) method to select the best modes in order to mitigate the environmental impacts, along with reducing the duration and cost of project implementation and enhancing the overall quality of the project. The method of ideal and anti-ideal virtual units is applied to rank the efficient execution modes. In addition, the TOPSIS method is utilized to rank the different execution modes of each activity. Finally, the results of two methods are compared. The findings show that the selection of an efficient execution mode for each activity leads to a trade-off between the four project objectives including time, cost, quality, environmental impacts. The shortest project duration and the lowest total project cost were obtained using the NDEA-Nuo method, the highest quality level was gained by the NDEA-INP method, and the minimum environmental impacts of the entire project were attained by the TOPSIS method. Also, the lowest amount of resource consumption was obtained using the TOPSIS method, so that the daily consumption amount of each resource was less than the other two methods. As a result, the project management team can apply either the NDEA or TOPSIS method based on the organizational policy. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Analysis of the Organizational Knowledge Management System of Nurse Education Centers with Hybrid Fuzzy DEMATEL-Network DEA Method(IOS Press BV, 2023-12-27)On-the-job training is important for the growth of organizational human capital. The present paper evaluates the efficiency of on-the-job training using the DEA model and knowledge management system to illustrate the interactions of organizational knowledge management concepts for measuring the efficiency of on-the-job training courses for employees within the organizational knowledge management systems. In this research, the DEA method was used to evaluate the efficiency of knowledge management system and analyze the interdependencies of the system. Also, the EU Knowledge and Innovation Management Measurement and the Kirkpatrick models were employed to identify the indicators. This study was conducted on 27 education centers in Iran. The results of evaluating the effectiveness of the knowledge management system show that the factor of “educational resources and facilities” is the most affecting variable and the most affected variable is “educational effectiveness”. Then, based on the DEA method, the weights of the sub-factors of the model were determined, and the efficiency of each step and as a result the efficiency of the whole system was obtained. Inefficient units were discarded and finally the efficient units were ranked. This study can help the organizations to identify the factors affecting the effectiveness of knowledge management programs.