Fuzzy preference programming formulation in data envelopment analysis for university department evaluation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dyanne Brendalyn Mirasol-Cavero ◽  
Lanndon Ocampo
Keyword(s):  
Data Envelopment Analysis ◽  
Real Life ◽  
The Philippines ◽  
Data Envelopment ◽  
Data Accessibility ◽  
Content Type ◽  
Proposed Model ◽  
University Department ◽  
Fuzzy Dea ◽  
Fuzzy Preference

Purpose University department efficiency evaluation is a performance assessment on how departments use their resources to attain their goals. The most widely used tool in measuring the efficiency of academic departments in data envelopment analysis (DEA) deals with crisp data, which may be, often, imprecise, vague, missing or predicted. Current literature offers various approaches to addressing these uncertainties by introducing fuzzy set theory within the basic DEA framework. However, current fuzzy DEA approaches fail to handle missing data, particularly in output values, which are prevalent in real-life evaluation. Thus, this study aims to augment these limitations by offering a fuzzy DEA variation. Design/methodology/approach This paper proposes a more flexible approach by introducing the fuzzy preference programming – DEA (FPP-DEA), where the outputs are expressed as fuzzy numbers and the inputs are conveyed in their actual crisp values. A case study in one of the top higher education institutions in the Philippines was conducted to elucidate the proposed FPP-DEA with fuzzy outputs. Findings Due to its high discriminating power, the proposed model is more constricted in reporting the efficiency scores such that there are lesser reported efficient departments. Although the proposed model can still calculate efficiency no matter how much missing and unavailable, and uncertain data, more comprehensive data accessibility would return an accurate and precise efficiency score. Originality/value This study offers a fuzzy DEA formulation via FPP, which can handle missing, unavailable and imprecise data for output values.

Data Envelopment Analysis with Fuzzy Parameters

2013 ◽  
pp. 94-108 ◽  
Author(s):  
Adel Hatami-Marbini ◽  
Saber Saati ◽  
Madjid Tavana
Keyword(s):  
Data Envelopment Analysis ◽  
Real Life ◽  
Evaluation Process ◽  
Data Envelopment ◽  
Value Judgments ◽  
Life Problems ◽  
Fuzzy Goal ◽  
Ranking Order ◽  
Fuzzy Dea ◽  
Fuzzy Parameters

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. In the conventional DEA, all the data assume the form of specific numerical values. However, the observed values of the input and output data in real-life problems are sometimes imprecise or vague. Previous methods have not considered the preferences of the decision makers (DMs) in the evaluation process. This paper proposes an interactive evaluation process for measuring the relative efficiencies of a set of DMUs in fuzzy DEA with consideration of the DMs’ preferences. The authors construct a linear programming (LP) model with fuzzy parameters and calculate the fuzzy efficiency of the DMUs for different a levels. Then, the DM identifies his or her most preferred fuzzy goal for each DMU under consideration. A modified Yager index is used to develop a ranking order of the DMUs. This study allows the DMs to use their preferences or value judgments when evaluating the performance of the DMUs.

Assessing the efficiency of environmental regulations of large-scale enterprises based on extended fuzzy data envelopment analysis

2018 ◽  
Vol 118 (2) ◽  
pp. 463-479 ◽  
Author(s):  
Shuhong Wang ◽  
Hui Yu ◽  
Malin Song
Keyword(s):  
Data Envelopment Analysis ◽  
Fuzzy Numbers ◽  
Environmental Regulations ◽  
Environmental Efficiency ◽  
Data Envelopment ◽  
Triangular Fuzzy Numbers ◽  
Content Type ◽  
Trapezoidal Fuzzy Numbers ◽  
Fuzzy Data Envelopment Analysis ◽  
Proposed Model

Purpose As the functions of environmental regulations cannot be quantified while assessing their environmental efficiency, there has been no comprehensive evaluation of environmental efficiency. The purpose of this paper is to evaluate environmental regulations based on triangular and trapezoidal fuzzy numbers. Design/methodology/approach This paper uses L-R fuzzy numbers to transform the evaluation language into triangular fuzzy numbers, and adopts an α-level flexible slacks-based measurement model to evaluate the performance of these regulations. Trapezoidal fuzzy numbers are combined with a data envelopment analysis model, and an α-slack-based measurement (SBM) model is used to evaluate the environmental efficiency. The α-SBM model is confirmed to be stable and sustainable. Findings Relevant index data from 16,375 enterprises were collected to test the proposed model, and models corresponding to triangular fuzzy numbers and trapezoidal fuzzy numbers were used to evaluate their environmental efficiency. Comparative results showed that the proposed model is feasible and stable. Originality/value The main contributions of this study are twofold. First, this paper provides a valuable evaluation method for environmental regulation. Second, our research improves the practical performance of trapezoidal fuzzy data envelopment analysis and enhances its feasibility and stability.

Efficiency of banks in Southeast Asia: Indonesia, Malaysia, Philippines and Thailand

2017 ◽  
Vol 44 (12) ◽  
pp. 2302-2312 ◽  
Author(s):  
Shazida Jan Mohd Khan ◽  
Shamzaeffa Samsudin ◽  
Rabiul Islam
Keyword(s):  
Data Envelopment Analysis ◽  
Southeast Asia ◽  
Design Methodology ◽  
The Philippines ◽  
Data Envelopment ◽  
Bank Efficiency ◽  
Financial Reforms ◽  
Content Type ◽  
Cross Country

Purpose The purpose of this paper is to use the concept of meta-frontiers data envelopment analysis (DEA) to compare the technical efficiencies of banks in selected Southeast Asia countries in the periods of 1998-2012. Design/methodology/approach The authors evaluate bank efficiency in Indonesia, Malaysia, Thailand and the Philippines by means of DEA, and the authors employ a meta-frontiers approach to calculate efficiency scores in a cross-country setting. Findings The analysis shows that even there are some similarities in the process of financial reforms undertaken in the selected countries, the observed efficiency levels of banks vary substantially across the market. Originality/value It is crucial to take into consideration of different technologies in explaining the efficiency differences.

Forecasting sustainability of supply chains in the circular economy context: a dynamic network data envelopment analysis and artificial neural network approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hadi Shabanpour ◽  
Saeed Yousefi ◽  
Reza Farzipoor Saen
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Data Envelopment Analysis ◽  
Supply Chains ◽  
Circular Economy ◽  
Real Life ◽  
Network Data ◽  
Data Envelopment ◽  
Content Type ◽  
First Time

PurposeThe objective of this research is to put forward a novel closed-loop circular economy (CE) approach to forecast the sustainability of supply chains (SCs). We provide a practical and real-world CE framework to improve and fill the current knowledge gap in evaluating sustainability of SCs. Besides, we aim to propose a real-life managerial forecasting approach to alert the decision-makers on the future unsustainability of SCs.Design/methodology/approachIt is needed to develop an integrated mathematical model to deal with the complexity of sustainability and CE criteria. To address this necessity, for the first time, network data envelopment analysis (NDEA) is incorporated into the dynamic data envelopment analysis (DEA) and artificial neural network (ANN). In general, methodologically, the paper uses a novel hybrid decision-making approach based on a combination of dynamic and network DEA and ANN models to evaluate sustainability of supply chains using environmental, social, and economic criteria based on real life data and experiences of knowledge-based companies so that the study has a good adaptation with the scope of the journal.FindingsA practical CE evaluation framework is proposed by incorporating recyclable undesirable outputs into the models and developing a new hybrid “dynamic NDEA” and “ANN” model. Using ANN, the sustainability trend of supply chains for future periods is forecasted, and the benchmarks are proposed. We deal with the undesirable recycling outputs, inputs, desirable outputs and carry-overs simultaneously.Originality/valueWe propose a novel hybrid dynamic NDEA and ANN approach for forecasting the sustainability of SCs. To do so, for the first time, we incorporate a practical CE concept into the NDEA. Applying the hybrid framework provides us a new ranking approach based on the sustainability trend of SCs, so that we can forecast unsustainable supply chains and recommend preventive solutions (benchmarks) to avoid future losses. A practicable case study is given to demonstrate the real-life applications of the proposed method.

Data envelopment analysis with interactive variables

2015 ◽  
Vol 53 (10) ◽  
pp. 2390-2406 ◽  
Author(s):  
Aibing Ji ◽  
Hui Liu ◽  
Hong-jie Qiu ◽  
Haobo Lin
Keyword(s):  
Data Envelopment Analysis ◽  
Special Form ◽  
Design Methodology ◽  
Data Envelopment ◽  
Content Type ◽  
Dea Model ◽  
Proposed Model ◽  
Choquet Integrals ◽  
Practical Implications ◽  
Decision Making Units

Purpose – The purpose of this paper is to build a novel data envelopment analysis (DEA) model to evaluate the efficiencies of decision making units (DMUs). Design/methodology/approach – Using the Choquet integrals as aggregating tool, the authors give a novel DEA model to evaluate the efficiencies of DMUs. Findings – It extends DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form. At last, the authors use the numerical examples to illustrate the performance of the proposed model. Practical implications – The proposed DEA model can be used to evaluate the efficiency of the DMUs with multiple interactive inputs and outputs. Originality/value – This paper introduce a new DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form.

Developing a novel data envelopment analysis model to determine prospective benchmarks of green supply chain in the presence of dual-role factor

2015 ◽  
Vol 22 (4) ◽  
pp. 711-730 ◽  
Author(s):  
Amir Shabani ◽  
Reza Farzipoor Saen
Keyword(s):  
Supply Chain ◽  
Data Envelopment Analysis ◽  
Critical Path ◽  
Dual Role ◽  
Green Supply Chain ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Content Type ◽  
Proposed Model ◽  
Inputs And Outputs

Purpose – The purpose of this paper is to develop a model based on data envelopment analysis (DEA) and program evaluation and review technique/critical path method (PERT/CPM) for determining prospective benchmarks. Design/methodology/approach – The idea of determining prospective benchmark is needed for developing a model for future planning where inputs and outputs of systems are influenced by external factors such as economic conditions, demographic changes, and other socio-economic factors. In this paper, the PERT/CPM method estimates prospective inputs and outputs. On the other hand, in particular systems some measures play the role of both input and output. Such factors in DEA literature are called dual-role factors. This paper integrates PERT/CPM technique and the DEA. Findings – The results of the proposed model depict that a present benchmark may not be a benchmark in future. A numerical example validates the proposed model. Originality/value – This paper, for the first time, applies the PERT/CPM technique to incorporate the ideas for identifying prospective benchmarks. Moreover, the proposed model is an alternative solution for classifying inputs and outputs in DEA. Also, the proposed model is utilized in benchmarking green supply chain management.

Detection of cost leaders using non-central principal component analysis and data envelopment analysis

2019 ◽  
Vol 26 (2) ◽  
pp. 548-566 ◽  
Author(s):  
Subhadip Sarkar
Keyword(s):  
Data Envelopment Analysis ◽  
Primary School ◽  
Primary Schools ◽  
Data Envelopment ◽  
Content Type ◽  
Cost Leadership ◽  
True Cost ◽  
Proposed Model ◽  
Decision Making Unit ◽  
The Cost

Purpose The purpose of this paper is to express the strategic positioning of a firm among its rivals based on an overall analysis. The proposed model uses data envelopment analysis (DEA) to determine the indexes due to cost leadership and differentiation. The model can be useful to identify the true cost leaders and those who are stuck in the middle. This work suggests the way how the strategic position can be explored from the consumption of resources (unlike the prevalent models like Banker et al., 2014). Design/methodology/approach Depending on the previous surveys, two inputs (spending per student and percentage of non-poor income group) and two outputs (average scores attained by students in science group and in language group in six private schools, located within the outskirt of Durgapur) were analyzed. Findings The classification made on the basis of the result of the proposed model reveals that out of the six schools (A, B, C, D, E and F), A, E and F occupy a strong position in this context, whereas B can be an example of stuck in the middle scenario. It not only has to reduce cost by 30 percent but also improve the differentiation index by 140 percent. C and D are lagging behind as they do not have enough differentiating qualities. Research limitations/implications Only six schools were taken for the analysis. Second, the input and output vectors had to be non-negative. In case of a negative input (output) set, separate treatment must be applied to them before the application of non-central PCA. Any decision-making unit producing an output of 0 will prohibit the use of the non-central PCA. Practical implications The extant study provides the indices to measure cost leadership and differentiation strategies for the classification as per the generic strategies. A firm which is lagging behind can adjust its consumption to remain successful. Social implications According to Hillman and Jenkner (2002), the developing countries lack the willingness of a primary school to impart education to children. The current study is used to explore whether any private primary school has the same goal or not. They also pointed out the possible future consequences while stating that the cost of educating children from the poorer section might be outweighed by the cost of not educating them and adults lacking basic skills had greater difficulty in finding well-paying jobs to escape poverty. So it is important to understand the role of a private primary school to offer seats to underprivileged students for educating them. The intention of six private primary schools toward educating the population of the small area within Durgapur is analyzed in this study, The study revealed that few schools spend more to serve the students belonging to upper classes to remain successful, whereas few schools as a differentiator make conscious attempts for providing services to poorer sections in an economical manner like a cost leader. Originality/value The extant research aims to formulate the determining methods of identifying strategic groups (proposed by Hunt, 1983) to make a parity between business definition view and strategic type concepts. The model can assess the rivals within an industry to explore the true cost leaders and those who are stuck in the middle using DEA. There are not enough kinds of literature which could effectively measure them.

Application of fuzzy DEA and machine learning algorithms in efficiency estimation of paddy producers of rural Eastern India

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anirban Nandy ◽  
Piyush Kumar Singh
Keyword(s):  
Machine Learning ◽  
Data Envelopment Analysis ◽  
Agricultural Production ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Data Envelopment ◽  
Content Type ◽  
Dea Efficiency ◽  
Efficiency Estimation ◽  
Fuzzy Dea

PurposeData envelopment analysis (DEA) has wide applications in the agricultural sector to evaluate the efficiency with crisp input and output data. However, in agricultural production, impreciseness and uncertainty in data are common. As a result, the data obtained from farmers vary. This impreciseness in crisp data can be represented in fuzzy sets. This paper aims to employ a combination of fuzzy data envelopment analysis (FDEA) approach to yield crisp DEA efficiency values by converting the fuzzy DEA model into a linear programming problem and machine learning algorithms for better evaluation and prediction of the variables affecting the farm efficiency.Design/methodology/approachDEA applications are focused on the use of a common two-step approach to find crucial factors that affect efficiency. It is important to identify impactful variables for minimizing production adversities. In this study, first, FDEA was applied for efficiency estimation and ranking of the paddy growers. Second, the support vector machine (SVM) and random forest (RF) were used for identifying the key leading factors in efficiency prediction.FindingsThe proposed research was conducted with 450 paddy growers. In comparison to the general DEA approach, the FDEA model evaluates fuzzy DEA efficiency giving the user the flexibility to measure the performance at different possibility levels.Originality/valueThe use of machine learning applications introduces advanced strategies and important factors influencing agricultural production, which may help future research in farms' performance.

Supplier selection and evaluation in e-commerce enterprises: a data envelopment analysis approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saurabh Pratap ◽  
Yash Daultani ◽  
Ashish Dwivedi ◽  
Fuli Zhou
Keyword(s):  
Data Envelopment Analysis ◽  
Supplier Selection ◽  
Management Practices ◽  
Real Life ◽  
Supplier Management ◽  
Supplier Evaluation ◽  
Business Practices ◽  
Data Envelopment ◽  
Content Type ◽  
Customer Service Level

PurposeE-commerce refers to the facilitation and delivery of goods and services to the customers employing an electronic arrangement. For an e-commerce firm, the customer service level provided by its suppliers can make or break the firm. The purpose of this research is to help e-commerce enterprises in addressing the vast challenge of complex supplier selection and evaluation process that must be performed vigilantly.Design/methodology/approachThe present study utilizes a three-pronged approach that integrates supplier management practices with the operational business practices of an e-commerce enterprise. In the first step, key performance factors for e-commerce capable suppliers are identified through an expert opinion and existing supplier management literature. Further, Data Envelopment Analysis (DEA) is employed to obtain the efficiency score for each supplier that enables their ranking on various performance parameters. Lastly, the suppliers are classified into different categories based on their performance and efficiency.FindingsUnder the proposed classification scheme, top five suppliers, i.e. supplier 1, 7, 9, 11 and 17 are categorized as HE (High Performance and Efficient). It is suggested that e-commerce enterprises must build long-term relationship with the identified top performing suppliers. The study also provides real insights into supplier's performance on a number of objective criteria. Further, the present study enhances the overall performance and productivity of an e-commerce firm by achieving input cost minimization and output quality maximization, simultaneously.Research limitations/implicationsThe results are valid for e-commerce enterprises in general. However, the present DEA model can be further evolved when applied in case of any particular e-commerce enterprise depending upon the internal capabilities of that firm. The nuances related to a firm's own supply capability development can be further explored by practitioners and researchers.Practical implicationsThe proposed approach is expected to motivate decision-makers to consider using more sophisticated approached like DEA in supplier evaluation processes. Also, as a benchmarking technique, the proposed supplier classification approach is expected to be highly useful for practitioners in real-life settings.Originality/valueThe novel contribution of this study includes the supplier evaluation, ranking and classification for e-commerce enterprises based on the real-life data. The insights would help the practitioners to formulate novel strategies for appropriately investing in supplier relationships.

Data Envelopment Analysis with Fuzzy Parameters

2011 ◽  
Vol 2 (3) ◽  
pp. 39-53 ◽  
Author(s):  
Adel Hatami-Marbini ◽  
Saber Saati ◽  
Madjid Tavana
Keyword(s):  
Data Envelopment Analysis ◽  
Real Life ◽  
Evaluation Process ◽  
Data Envelopment ◽  
Value Judgments ◽  
Life Problems ◽  
Fuzzy Goal ◽  
Ranking Order ◽  
Fuzzy Dea ◽  
Fuzzy Parameters

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. In the conventional DEA, all the data assume the form of specific numerical values. However, the observed values of the input and output data in real-life problems are sometimes imprecise or vague. Previous methods have not considered the preferences of the decision makers (DMs) in the evaluation process. This paper proposes an interactive evaluation process for measuring the relative efficiencies of a set of DMUs in fuzzy DEA with consideration of the DMs’ preferences. The authors construct a linear programming (LP) model with fuzzy parameters and calculate the fuzzy efficiency of the DMUs for different a levels. Then, the DM identifies his or her most preferred fuzzy goal for each DMU under consideration. A modified Yager index is used to develop a ranking order of the DMUs. This study allows the DMs to use their preferences or value judgments when evaluating the performance of the DMUs.

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