Mahnaz Maghbouli

Bio: Mahnaz Maghbouli is an academic researcher from Islamic Azad University. The author has contributed to research in topics: Data envelopment analysis & Ranking. The author has an hindex of 2, co-authored 8 publications receiving 91 citations.

Increasing the discrimination power of data envelopment analysis

Abstract: In data envelopment analysis (DEA), to discriminate between efficient units, several ranking methods have been proposed by different authors from various points of views. However, despite of the fact that each technique has some advantages and disadvantages, all of them will face the relatively high computational complexity level. Moreover, different ranking procedures yield to different results. Although there are many ranking approaches in DEA literature, there is a need to provide a complete ranking on efficient units with a lower complexity. The current paper proposes a complete ranking method for fully ranking of all DMUs. Furthermore, this approach makes use of a common set of weights for all DMUs. In the proposed ranking approach, the infeasibility and instability problems of the existing methods have been removed. Moreover, the computational effort of the approach is relatively low in comparison to the existing methods. Sample and real cases will be presented for more illustration.

The relation between emotional intelligence (EQ) and mathematics performance: a DEA-based approach

Abstract: Emotional intelligence (EQ) is considered as an alternative issue in both fields of psychology and education. Studies that have been conducted in this area illustrate the role of emotional intelligence (EQ) and its components in different aspects of one's life such as academic achievement, occupation, and social relationships. Turning to a view to academic performance measurement, mathematics is considered as a science which can promote the learners' ability in order to respond to the ups and downs of every individual’s life. Most of the previous papers have investigated the relationship between EQ and mathematical Performance. The main feature of those studies were focusing on statistical analysis. To deal with this issue, this study proposes an alternative procedure not only is interested in employing non parametric models, such as Data Envelopment Analysis (DEA), but also provides the statistical analysis to assess the questioned relation. The proposed procedure can serve as an evaluation tool for educational policy and students ‘promotion. To do so, eighty-one individuals have been selected among Islamic Azad University (Yadegar -e- Imam Khomeini (RAH) branch) engineering students with simple random during the first midterm of academic year 2019-2020. Distributing a standard EQ questionnaire of Bradberry (2005) reveals EQ and its four components’ scores. The average of three completed math scores have presented mathematical performance quantity. The results of Data Envelopment Analysis (DEA) point out no specific pattern between EQ and mathematical performance. The study also reveals that statistical analysis show a similar trend as efficiency analysis method did.

Multi-dimensional Nondiscretionary Factors in Data Envelopment Analysis: A Slack-Based Measure

Abstract: Various extension using data envelopment analysis (DEA) are available in the literature for performance measurement in public sector. The existence of multiple non- discretionary factors in DEA based public sector models leads to overestimation of the efficiency. This paper proposes a two-step procedure to handle non-discretionary factors in DEA models. In the first step, the multiple non-discretionary factors are transformed into a single artificial factor and then, using a slack-based model the performance assessment is done. To highlight the comparison, an analysis using simulated data is performed. The results show that the proposed two-stage approach is relatively better than existing approaches when we apply the slack based measure of efficiency.

Identifying the best university educational departments using data envelopment analysis

Abstract: Selecting the best performer departments can be a difficult task when there are many applicants for comparison. Data envelopment analysis (DEA) representative a non parametric tool can be used as a fair technique to support the decision making process .Considering the fact that competition and dependency always exist between two real DMUs, a DMU must only be compared with real DMUs lying at different efficiency levels. This paper applied a context-dependent DEA to determine the best candidate relative to the others, evaluate the degree of excellence of best candidates' performance and then clusters them.

Two-stage DEA models with undesirable input-intermediate-outputs $

Abstract: Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). Many studies have examined DEA efficiencies of two-stage systems, where all the outputs from the first stage are the only inputs to the second stage. Although single-stage DEA models with undesirable input-outputs have been extensively studied, there still lacks of more systematical investigation on two-stage DEA with undesirable variables. For instance, depending on its operating model, even whether an intermediate variable is desirable or undesirable can be questionable for a particular two-stage system. Furthermore, most of the existing studies on two-stage systems focus on the case where only the final outputs are undesirable. In this work, we try to systematically examine two-stage DEA models with undesirable input-intermediate-outputs. Particularly, we utilize the free-disposal axioms to construct the production possibility sets (PPS) and the corresponding DEA models with undesirable variables. The proposed models are then used to illustrate some theoretical perspectives by using the data of China׳s listed banks.

Total-factor energy efficiency evaluation of Chinese industry by using two-stage DEA model with shared inputs

Abstract: Chinese industry has developed greatly since China implemented its “reform and opening-up” policy in 1978. With the rapid development of industry, the problems of growing energy consumption and environmental pollution are drawing increasing attention from government managers and scholars. This paper divides industrial systems into two stages, an energy utilization stage and a pollution treatment stage, for accurately evaluating the total-factor energy efficiency as well as the overall efficiency. We build a new two-stage data envelopment analysis model with shared inputs to open the “black box” of efficiency measurement in traditional energy efficiency methods. Applying the model to data for Chinese regions, we can display the advantages and disadvantages of these two stages of industry. The results show that (1) the performance of Chinese industry improved during the years 2006–2010; (2) the energy utilization stage performance was better than that of the pollution treatment stage, but the gaps reduced year by year; and (3) energy efficiency increased during this period. Based on these results, some policy recommendations are given.

Slacks-based inefficiency approach for general networks with bad outputs: An application to the banking sector

Abstract: In this paper the efficiency assessment of general networks of processes that produce both desirable and undesirable outputs is addressed. This problem arises in many contexts (e.g. transportation, energy generation, etc.). A general networks slacks-based inefficiency (GNSBI) measure can be computed using a simple linear program that takes into account the weak disposability of the bad outputs. The slacks-based inefficiency (SBI) of each process is also calculated. Target values for all inputs, outputs (both desirable and undesirable) and even intermediate products are also provided. The proposed approach is rather general and can accommodate many different network topologies and returns to scale assumptions. Two applications to the banking sector are presented: one to assess banks efficiencies and another to assess bank branches.