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In this paper, lower-order mathematical thinking skills within finance were studied from the viewpoint of financial employees in the Iranian Bank of Industry and Mine. To conduct this research, a questionnaire was developed after reviewing lower-order mathematical thinking skills in finance. In accordance with the revised Bloom's taxonomy, the skills considered in the questionnaire were "remembering mathematics in finance", "understanding mathematics in finance", and "applying mathematics in finance". In order to develop the questionnaire, we conducted interviews with employees and scholars, then a suitable sample familiar with mathematics and finance, consisting of 141 bank employees, was studied. Descriptive and inferential statistics were used for data analysis. Our findings show a hierarchical relationship between the first three mathematical thinking skills in finance, which confirms the revised Bloom's taxonomy. In addition, the attitudes of participants were positive concerning the importance of these skills. Participants believed that, in order to achieve proper functioning, it is essential to improve the skills of financial employees. The results were analysed with a T-test and ANOVA. This showed that the gender, position, experience, department, degree, and field of study of participants did not affect their attitudes. This research indicates that, for the successful utilisation of skills, it is essential to form an effective relationship between mathematical science and its practical application in the banking world. It is recommended to hold on-the-job training courses for financial employees in banks to empower them to use their computational skills.

The purpose of this article is to identify the factors which affect students' creative thinking in problem solving. The research which was performed was quasi-experimental. It used one experimental group and two control groups from three second-grade high school classes. They received either traditional, active or heuristic problem-solving training. In the traditional method, no teaching aids were used, and the material was taught traditionally. In the active method, 34 students were trained using teaching aids, such as coloured balls, and handicrafts, such as shirts and pants. They were trained to use the teaching aids in order to solve problems. In the heuristic method, the researcher introduced problems which the students thought about. After a few sessions, I commenced teaching the procedures--in each session, two heuristics were introduced. They learned to use these strategies to solve problems. Creativity and mathematics tests were given to the students, both before and after they received training in problem-solving. The findings show that parents' education (but not gender) and parents' job type affected students' ability to think creatively. Students' creative thinking was improved by active training, but not by the heuristic or traditional methods.

Background: Rare diseases, characterized by low prevalence and high complexity, pose significant challenges to health systems due to the uncertainty surrounding the best diagnostic methods and availability of effective treatments. Objectives: This study aimed to introduce new methods for prioritizing orphan drugs, with a pilot application to hemophilia, spinal muscular atrophy (SMA), cystic fibrosis (CF), and multiple sclerosis (MS). Methods: This quantitative research, conducted at Iran's National Institute for Health Research from 2021 to 2023, employs multi-criteria decision-making models (MCDA) to evaluate the efficacy of health care technologies for "rare and hard to cure" diseases. A preliminary model was developed based on a pilot selection of seven medications, for which comprehensive data was extracted. The clinical efficacy was assessed using quality adjusted life years (QALY) as a metric. The model design was grounded on three critical factors: The annual cost of intervention per individual, the annual number of eligible patients for intervention, and the Proportion of expenses covered by the governmental budget. Additionally, the model incorporated various constraints and a regulatory coefficient, denoted as "w," to enhance its robustness. Results: By running the model, the coverage of selected medications through model optimization, revealing the following percentages: Alemtuzumab (30%), ocrelizumab (30%), emicizumab (6%), dornase alfa (29%), tobramycin (2%), and spinraza (0.02%). Additionally, the corresponding monetary coverage in Iranian Rials is reported as follows: Alemtuzumab (27,144,000,000 IRR), ocrelizumab (109,645,200,000 IRR), emicizumab (17,360,490,000 IRR), dornase alfa (43,350,930,000 IRR), tobramycin (1,268,505,000 IRR), and spinraza (350,000,000 IRR). Conclusions: This model has tried to solve the shortcomings of the existing models regarding the prioritization of orphan drugs by combining different factors to improve access to essential treatments for rare diseases, although it can be generally asserted that no unique model can answer all policymakers' questions regarding budget allocation of rare diseases and orphan products. [ABSTRACT FROM AUTHOR]

We developed a DEA-based resource re-allocation model based on environmental DEA technology for organizations with a central decision-making environment. The proposed model considered a weak disposability axiom for undesirable outputs and combined Data Envelopment Analysis (DEA) with Multiple-Objective Programing (MOP). The objective was to find the appropriate re-allocation model in order to save energy and reduce environmental pollution, so that the next steps could be taken toward improvement. Given that reducing the inputs and outputs of inefficient units is sometimes not achievable and does not seem logical, for the reduction in the values to be logical and achievable, we divided the Decision-Making Units (DMUs) into different levels of efficient frontier using the context-dependent DEA technique. For this purpose, the model was designed to move the DMUs from the current frontier to the efficient frontier of the previous layer, which has better efficiency conditions, or keep them on their own frontier. In addition, the opinion of the central decision maker regarding the amount of reduction in the inputs and outputs was expressed using Goal Programing (GP) in a way that does not make the model infeasible. By implementing the model in 8 regions of the world, suggestions were made regarding the amounts of energy saving and CO2 pollution reduction based on the conditions determined by the central decision maker aiming improve the efficiency of inefficient units in the next step. [ABSTRACT FROM AUTHOR]

Since companies are inclined to implement lean production, researchers have proposed a number of fundamental success factors to facilitate the implementation of this production approach. This study analyzes the critical success factors (CSFs) in lean production extracted from 14 review studies. The interpretive structural modeling approach is utilized to analyze the impact of these critical success factors on one another. The aim is to enhance insights into lean production and facilitate informed decision-making. In this article, a seven-tiered model is presented. According to the conceptual model of success factors in lean production, leadership is positioned at the base of the model and serves as the origin for other factors. It should be regarded as the foremost critical success factor in lean production. When establishing lean production systems, organizations and senior managers should focus on higher levels and critical success factors that underlie the model. Subsequently, nonfuzzy and fuzzy driving and dependence power analyses were conducted that the fuzzy matrix cross-reference multiplication applied to a classification (MICMAC) analysis provides deeper insights into the analysis of driving and dependence power. The fuzzy matrix cross-reference multiplication applied to a classification analysis helped identify some key factors that are highly effective for successfully implementing lean manufacturing. [ABSTRACT FROM AUTHOR]

The data envelopment analysis method is commonly used to measure efficiency. An estimate of the relative efficiency of this model is derived by calculating the ratio between inputs and outputs. Data envelopment analysis models can also be applied to network structures due to the extension of these models. Supply Chain Management (SCM) is a novel approach that governed production management in recent years. In complex and dynamic environments, the petrochemical industry requires an investigation system similar to those used by other organizations to inform about its activity's desirability, especially in complex and dynamic environments. This research focused on the petrochemical company supply chain. Laboratory studies, experts, and visits to petrochemical sites were used to identify production processes and determine indicators. After that, they were evaluated with an envelopment model and a coefficient corresponding to the identified petrochemical supply chain structure. The aggregate and componentwise efficiency of the studied units in petrochemical were also examined from 2016 to 2019. [ABSTRACT FROM AUTHOR]

In this paper, while taking into account the cooperative relationships between units, the problem of revenue allocation is considered as a coalitional game. In order for the allocation to be equitable, by relying on the concept of DEA efficiency, a new characteristic function is presented, and then using the concept of the Shapley value, which is a wellrecognized concept in coalitional game theory, a unique solution is obtained for the revenue allocation problem. And finally, to evaluate the equitability of the performed revenue allocation, the Gini coefficient is utilized. A comparison of the Gini coefficient obtained for our method with those of some existing methods showed that our method is more equitable than the previous ones. This demonstrates how impactful the wise and accurate selection of the characteristic function is in the equitability of the results. [ABSTRACT FROM AUTHOR]

Purpose: The current paper tries to determine the type of returns to scale in a decision-making unit under the condition that integer-valued inputs or outputs are present. Methodology: This paper introduces radial models for determining the value and type of Returns to Scale (RTS) in 4 scenarios, including single integer-valued input -- single real output (scenario one), mixed inputs -- exclusively real outputs (scenario two), exclusively integer-valued inputs -- exclusively real outputs (scenario three), and exclusively integer-valued inputs -- exclusively integer-valued outputs (scenario four); in each scenario, the values of the left RTS and right RTS are determined, and the RTS type is then determined on that basis. Finally, by presenting three examples based on two scenarios, namely single integervalued input -- single real output and single integer-valued input -- single integer-valued output, the new method is compared with previous methods using GAMS software, and the conclusions are provided. Findings: The type of returns to scale differs when integer-valued inputs or outputs are present as compared with the case where the inputs and outputs are assumed to have real values. Originality/Value: This study focuses on the value and type of returns to scale for integer-valued data. For this purpose, returns to scale was modeled in 4 scenarios using input-oriented radial models, and in the fourth scenario (exclusively integervalued inputs -- exclusively integer-valued outputs), the modeling was carried out for output orientation as well. The existence of a difference between the results produced by our proposed model and those of the classical model was demonstrated through two examples, one using hypothetical data and the other real-world data. [ABSTRACT FROM AUTHOR]

The structure of production technology has been made of a few stages. Therefore, it generates an intermediate output, which is important to estimate the quantitative and qualitative returns to scale and for managers to make decisions. Estimates of scale elasticity have long been considered in two-stage technologies, many researchers have suggested methods to estimate it, but they were not investigated from the base, and the intermediate output was also ignored. There were no strong relationships between the total scale elasticity and the scale elasticity of both stages. The proposed method can estimate the scale elasticity from the base and from the production transfer function, which in turn has a stronger basic structure compared to previously proposed methods. It is much simpler and easier to be understood than previous methods. The scale elasticity of the entire network can be estimated by multiplying the scale elasticity of both stages. By expressing the parametric and nonparametric approaches of two-stage network scale elasticity, the ratio of the final output to primary input changes can be obtained according to the change of the intermediate output compared to primary input as well as the final output to intermediate input. Finally, the superiority of the proposed method is illustrated by practical examples. [ABSTRACT FROM AUTHOR]

Congestion is one of the important concepts in data envelopment analysis that occurs when excessive inputs reduce the maximally possible outputs. Identification and elimination of congestion have a significant impact on reducing inputs along with increasing outputs. Hence, various studies have been conducted to detect and evaluate congestion. However, in today's world, no organization can achieve its final output with just one process of input. In other words, today's organizations have a network structure that consists of several subsections. Ignoring the existing influences among the subsections processes may lead to inadequate or even incorrect results for evaluating the congestion. While all of the existing methods only evaluate the congestion of each subsection or the whole system independently. Therefore, in this paper, the concept of congestion is developed for a specific and so practical case of network structure called "two-stage network structure". This case of network structure consists of two series stage such that Stage 1 consume some primary inputs to produce some intermediate outputs. In the following, the intermediate outputs are used as the inputs of Stage 2 to produce the final output. Here, the concept of congestion is defined for systems with a two-stage structure. Then, to examine the congestion of each stage as well as the congestion of the whole system, a single linear programming model is proposed. The validity of the proposed model is investigated using several theorems and it is shown that the new definition is a generalization of the previous definitions of the congestion for the black-box systems. Finally, the proposed model is applied to a case study including 24 non-life insurance companies in Taiwan. [ABSTRACT FROM AUTHOR]

The formation of modifications or conception in the landscape could possibly, be a procedure relative to its natural and non-disturbance process; and it could be hastened by the occurrence of disturbance regimes. The objective of this research is to survey the changes in a landscape structure, over a period of 30 years, to attain information, as to the current conditions of land use, utilizing landscape metrics in the watershed area of the Latian Dam, so as to analyze the results and the voids present, towards obtaining a specified sustainable regional planning for the abovementioned watershed. Land use was identified and reviewed by means of four Landsat satellite images for 1987, 1998, 2007, and 2017; and in this watershed, it was classified into four classes, (a) build-up areas, (b) vegetated areas, (c) bare lands and (d) water bodies. Subsequently, by taking advantage of 7 metrics at the landscape level and 8 metrics at the class level, the landscape structure in this watershed was quantified by utilizing the Fragstats 4.2 Software. The survey results illustrated an increment in the number of patches (NP), decrementing the mean area of the patches (AREA-MN), and increasing the Interspersion & Juxtaposition Index (IJI) signifies amplified fragmentation at the landscape level in this watershed. Similarly, the NP has also incremented at the class level, and thus, the fragmentation of patches and fragmentation in the entire three classes of land use, namely, build-up areas, bare lands, and vegetated areas has occurred. The amount of patchiness for the build-up class, with due attention to the increment in the mean area of patches (AREA-MIN), which demonstrates the fact that, this class is inclined and has a tendency towards a coarse-grained structure and a metric decrement in the AREA-MIN in the vegetated areas, illustrates that this class is prone to the fine-grained structure. [ABSTRACT FROM AUTHOR]

In traditional cost-efficiency models, inputs and outputs, as well as input prices were known as constant values for each decision-making unit In our daily applications, however, market entry prices vary at different times. In other words, input prices for Decision-Making Units (DMUs) are time dependent. Traditional methods cannot calculate the cost efficiency of DMUs with time-dependent prices. This paper proposes a new method to calculate the cost efficiency of DMUs in the presence of time-dependent prices. The proposed model is a parametric programming problem model depending on time. In the presented model, the inputs and outputs are functions in terms of time, which is not present in the models introduced by other researchers. New definitions for time-dependent cost efficiency have also been introduced. The cost efficiency of DMUs is measured over a given time and the units are ranked according to the time obtained. Finally, a numerical example has been presented to illustrate the proposed method. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2006.06.012 Byline: Gholam Reza Jahanshahloo (a), Helcio Vieira Junior (b), Farhad Hosseinzadeh Lotfi (a), Darush Akbarian (a) Keywords: Data envelopment analysis (DEA); Efficiency; Ranking Abstract: This research proposes a new ranking system for extreme efficient DMUs (Decision Making Units) based upon the omission of these efficient DMUs from reference set of the inefficient DMUs. We state and prove some facts related to our model. A numerical example where the proposed method is compared with traditional ranking approaches is shown. Author Affiliation: (a) Department of Mathematics, Science and Research Branches, Islamic Azad University, P.O. Box 14155/775 and 14155/4933, Postcode: 1477893855, Tehran, Iran (b) Electronic Warfare Center, CGEGAR, Brazilian Air Force, SHIS QI 05 Area Especial 12, Postcode 71615-600, Brasilia, DF, Brazil Article History: Received 21 January 2006; Accepted 6 June 2006

The estimating returns to scale (RTS) and identifying the area in which the type of returns to the scale of a single decision maker unit (DMU) remains sustainable helps managers to have more accurate predictions about the size variations of a DMU. Contrary to theoretical studies and attitudinal surveys, the RTS-based econometric estimates of the panel data are derived from the time changes observed in inputs and outputs. Therefore the description of returns-to-scale based on the panel data is closer to those that are related to changes in demand and changes in the policy of managers during the sample period. it’s clear that the use of the panel data, in addition to estimating returns to scale closer to the view of the managers, leads to a significant increase in the number of inputs and outputs for each DMU. Since we know that the DEA models have computational complexity for the great practical issues, use particularly when there are large numbers of outputs and inputs reducing the number of models will greatly help to solve these issues. In most articles, the returns-to-scale estimates for decision-making units (DMU) are performed with at least two LP models. Furthermore have problems in some cases and may not be able to investigate all DMUs. In this paper, a method has been proposed which determines returns-to-scale and identifies boundary units by solving only one model. In fact, unlike some articles which explore the boundary DMUs, the assessment area in this paper is all the DMUs observed in PPS (Production Possible Set). Therefore, based on this approach, identifying boundary units and estimating their returns-to-scale will be possible by solving only one LP model. Further, according to the proposed dual model, a different perspective has been proposed to identify and evaluate boundary units and to estimate the returns-to-scale by solving a single LP model. Additionally and according to numerous observations, the dual model is able to estimate the returns-to-scale of the image point of the inefficient units in the BCC model in the input orientation. The correctness of all content has been shown theoretically as well as intuitively, with due substantiation. [ABSTRACT FROM AUTHOR]

In conventional DEA models, it is supposed real-valued inputs and outputs while every measure must be determined as an input or output. However, in some cases, there are flexible measures which can only take integer values in two-stage network DEA. In all previous researches has not been mentioned the classification flexible measures while some inputs, outputs, and flexible measures can only take integer values in two-stage network DEA. So in this paper, we propose integer-valued FNDEA approach is based on envelopment form of CCR that evaluates the relative efficiency of DMUs and determines the status of flexible measures in the presence of integer data in basic and general two-stage network structures. Our model can determine projection points of inputs, outputs, and flexible measures in the presence of integer data in two-stage network DEA. Numerical examples are used to illustrate the procedure. [ABSTRACT FROM AUTHOR]

The efficiency evaluation of a network opens the "black box" and focuses on the internal structures and innermost interactions of the system. In this paper, we have made efforts to consider a three-stage system, comprising of six sub- DMUs, in combination with additional inputs and undesirable outputs. The proposed models are simulations of a factory, with a production area and three warehouses for goods and two delivery points. Hence, an authentic example of production planning and inventory control in a factory for a year and within duration of 24 periods was taken under consideration as a dynamic structure. In this simulation, all costs were considered, including, production costs, setup cost, maintenance costs of the products, warehouse reservation costs, transportation costs, delay penalty costs and the profit obtained from the sale of products. We utilized the multiplicative DEA with a double-frontier approach to measure the efficiency of a general system and improve the accuracy of efficiencies. Moreover, a heuristic technique was used to convert non-linear models into linear models. The ranking results of the 24 time periods indicate that the time periods 24 and 1 respectively are the best and poorest periods in terms of efficiency. Finally, we suggest using a k-means method to cluster DMUs into several groups with similar characteristics based on double-frontier Standpoint. [ABSTRACT FROM AUTHOR]

An accurate assessment of performance of Health, Safety, and Environment (HSE) system allows managers to identify strengths and weaknesses in the HSE system. This paper mainly was aimed to assess the performance of HSE management system using Fuzzy Data Envelopment Analysis (FDEA) model in the smelting industry. The indices of performance evaluation of process HSE management systems of smelting industries were weighted and ranked by Fuzzy System. Then, based on the weights of performance indices and data collected in the case study, performance was evaluated via DEA. The FDEA model was solved using a network model with constant returns to scale. According to the results, environment was the most important index of efficiency. Number of HSE Expert (0.16) and annual HSE Budget per employee (0.17) were the most important input indices in HSE performance system. Ergonomic risk control (0.08), Fire source control (0.08), and waste water quality (0.08) were the most important output indices in HSE performance system, respectively. The different performance criteria or safety performance with varying levels of significance can be used in each step of the assessment process. Budget of HSE was ranked the most important of HSE performance input indicators. This index affects other input indicators. Risk control in the three areas of safety, health, and the environment was one of the most important indicators of performance appraisal output. To evaluate systems safety, a performance evaluation system based on multiple inputs and multi-outputs was more applicable than other systems. [ABSTRACT FROM AUTHOR]

In this study, the multi-objective programming (MOP) method was used to solve network DEA (NDEA) models with assumption that, negative data is considered for the proposed NDEA model which consists of semi-negative and semi-positive input and output. At first, two stage and then k stage production models were formulated with consideration of negative data. In the multi-objective programming, two separate objective functions including the divisional efficiencies and the overall efficiency of the organization are modeled. In comparison to conventional DEA with negative data, the advantage of the proposed NDEA models is consideration of intermediate processes and products, in order to calculate the organization's overall efficiency. However, in conventional DEA, sub-stages of the organizations are neglected. To measure the efficiencies of an organization regarding interactive internal process, two case studies were investigated by application of the NDEAMOP method with negative data. Case study 1 is focused on units with two stages having semi-negative and semi-positive indexes. In case study 2, units with three stages are evaluated. These units also have semi-negative and semi-positive indexes. The overall efficiency of each unit is calculated using the proposed models. Fuzzy approach as a solution procedure is applied. [ABSTRACT FROM AUTHOR]

Organizations and companies have realized the significance of Health, Safety and Environmental (HSE) management as an integral and vital part of modern factories and organizations. Developing HSE processes requires performance assessment, for which defining appropriate indicators is a necessity. Because of the nondeterministic nature of performance indicators, assessments are prone to influence from personal judgments by the assessors. Many HSE management system indices are uncertain. Fuzzy approaches can reduce the effects of assessor judgments as well as uncertainty. The aim of the study was to present an HSE management system performance assessment model in a fuzzy environment. A questionnaire was used to conduct the study in one of the largest steel companies in Iran. The results revealed that, in the areas of health, safety, and environment, control of disease, fire hazards, and air pollution were of paramount importance, with coefficients of 0.057, 0.062, and 0.054, respectively. Furthermore, health and environment indicators were the most common causes of poor performance. Many performance health indicators had remained unchanged which were also due to the long-term nature of health indicators. Finally, it was shown that HSE management systems could affect the majority of safety indicators the short run, whereas health and environment indicators require longer periods. [ABSTRACT FROM AUTHOR]

The highest efficiency score 1 (100% efficiency) is regarded as a common benchmark for Decision Making Units (DMUs). This brings about the existence of more than one DMU with the highest score. Such a case normally occurs in all Data Envelopment Analysis (DEA) models and also in all the Common Set of Weights (CSWs) methods and it may lead to the lack of thorough ranking of DMUs. And ideal DMU based on its specific structure is a unit that no unit would do better than. Therefore, it can be utilized as a benchmark for other units. We are going to take advantage of this feature to introduce a linear programming problem that will produce CSWs. The proposed method assures that the efficiency of all the units is less than that of the benchmark unit. As a result, it provides a comprehensive ranking of DMUs. Moreover, the proposed method is also noteworthy regarding computation. A numerical example is suggested to clarify and explain the proposed method and compare it to two other CSWs methods. Finally, 33 universities in Iran were ranked and compared using the proposed method. [ABSTRACT FROM AUTHOR]

Congestion is an economic phenomenon in the production process where excessive amounts of the input cause a reduction of the output. The motivation of this paper is to investigate and compare the methods provided for estimating congestion in the DEA literature. [ABSTRACT FROM AUTHOR]