Data Envelopment Analytic Hierarchy Process Research Articles

Beyond Boundaries: The AHP-DEA Model for Holistic Cross-Banking Operational Risk Assessment

Operational risk assessment has received considerable attention in bank risk management. However, current assessment methods are primarily designed to assess the risk profile of individual banks. To enable cross-bank operational risk assessment, we propose an integrated AHP-DEA (analytic hierarchy process–data envelopment analysis) method. This method determines the importance of assessment criteria by calculating the weighted sum of rank votes after obtaining the importance values for specific rankings with DEA. This procedure replaces the pairwise comparisons in AHP and addresses the challenge of traditional AHPs in determining appropriate importance values when dealing with a large number of indicators. We applied this method to assess the operational risks of three Chinese commercial banks, and the empirical results indicate that this integrated AHP-DEA method is simple and user-friendly, making it suitable for cross-bank operational risk assessment.

Assessing resilience and sustainability of suppliers: an extension and application of data envelopment analytical hierarchy process

Assessing resilience and sustainability of suppliers: an extension and application of data envelopment analytical hierarchy process

Performance evaluation of sustainable projects: a possibilistic integrated novel analytic hierarchy process-data envelopment analysis approach using Z-Number information

Performance evaluation of sustainable projects: a possibilistic integrated novel analytic hierarchy process-data envelopment analysis approach using Z-Number information

Efficiency Measurement and Factor Analysis of China’s Solar Photovoltaic Power Generation Considering Regional Differences Based on a FAHP–DEA Model

Driven by the transformation of the energy structure, China’s photovoltaic (PV) power generation industry has made remarkable achievements in recent years. However, there are more than 30 regions (cities/provinces) in China, and the economic, policy, technological, and the environmental conditions of each region are significantly different, which leads to a huge discrepancy in PV power generation efficiency. To address the imbalance in the development of PV industry, first, this paper employed the integrated fuzzy analytic hierarchy process–data envelopment analysis (FAHP–DEA) model to evaluate the PV power generation efficiency of 30 regions in China. Second, Tobit regression model was used to examine the effects of 9 potential influencing factors. Third, a concrete analysis was conducted, and discussion based on the efficiency rankings and regression results was made. Additionally, the FAHP–DEA model proposed in this study can also be applied to the efficiency evaluation issues of other types of renewable energy.

Assessment of Logistics Platform Efficiency Using an Integrated Delphi Analytic Hierarchy Process-data Envelopment Analysis Approach: A Novel Methodological Approach Including a Case Study in Slovenia

The objective of this study is to propose a trustworthy, valid and consistent methodological approach for measuring the efficiency of a logistics platform, where an entire country constitutes a logistic platform. Traditional Data Envelopment Analysis (DEA) is found to be an appropriate tool – if its weaknesses are eliminated. DEA results are highly influenced by the choice of appropriate inputs and outputs variables, but the method itself does not provide guidance for their identification. The authors therefore propose to integrate traditional DEA by combining the Delphi technique with the Analytical Hierarchy Process (AHP) method, which will assist in identifying proper, consistent input/output variables, evaluated by their relevance. The proposed framework allows the performance evaluation of the selected platform’s element or elements. It is thus a useful decision support tool for enterprises (private, public, both) that are managing logistics platforms and trying to improve their productivity in order to sustain or improve their position on the competitive market. This methodology allows comparative efficiency analyses to be estimated for similar countries. The presented methodology on one hand enables tailor-made solutions, but on the other hand is very general, and, with minor adjustments, can be applied by a variety of firms and industries. It can be applied in private sector firms in production and service industries, to analyse the relative performance of diverse logistics and non-logistics services, and in public profit or non-profit organisations.

EVALUATION OF THE EFFICIENCIES OF PUBLIC HIGH SCHOOLS IN IZMIR/TURKEY USING DEAHP APPROACH

This study is carried out to assess the relative efficiencies of the Anatolian high schools in Izmir /Turkey and to guide inefficient educational institutions to become efficient. Firstly, efficiency measurement is performed by data envelopment analysis (DEA) model. Instead of assigning equal weights to the input and output variables, the analysis is repeated by assigning weights with the aid of the analytic hierarchy process(AHP) model. 3 input and 3 output variables are determined in the study and 47 Anatolian High Schools are analyzed. In Izmir, this study is important since it is the first study to assess the efficiencies of Anatolian high schools with data envelopment analytic hierarchy process (DEAHP) integrated model.

Third-party logistics service providers selection using AHP-DEAHP approach

Third-party logistics (3PLs) service providers have become an extremely important part of any organisation's supply chain. They are required in almost all business operations right from supplying the raw material to the manufacturing plants to delivering finished products to the end customers and hence appropriate selection of these service providers will not only make the organisation competitive but also contribute significantly to profitability. Present research focuses on first identifying criteria or enablers, which can be used to evaluate 3PLs. These enablers are further utilised by a hybrid multi-criteria decision-making technique of data envelopment analytic hierarchy process (DEAHP) to select the most appropriate 3PL service provider amongst choices available. With the help of exhaustive literature review, 14 major selection criteria were identified. Uniqueness of the research lies in the application of this hybrid technique to the selection of 3PLs for a manufacturing company.

A hybrid approach for supplier selection based on revised data envelopment analytic hierarchy process

For most managers, purchasing decisions are key decisions in the achievement of business organisation's strategic objectives. Appropriate supplier selection is necessary as it fulfils these important objectives of the organisation by maximising overall value to the purchaser, reducing uncertainty in supply, and by forming a long term, reliable relationship between buyers and suppliers. Supplier selection being affected by several conflicting factors requires an appropriate multi-criteria decision making approach. One of the recent approaches used for supplier selection is a hybrid data envelopment analytic hierarchy process (DEAHP) approach. However, this approach suffers from serious drawbacks as it uses counter intuitive priority vectors for inconsistent pair wise comparison matrices and also at times, it generate illogical weights for consistent pair wise comparison matrices as well. The objective of this paper is to present a revised DEAHP (RDEAHP) approach to overcome these drawbacks of DEAHP. The uniqueness of the research lies in the application of RDEAHP approach for supplier selection problem.

A hybrid approach for supplier selection based on revised data envelopment analytic hierarchy process

A hybrid approach for supplier selection based on revised data envelopment analytic hierarchy process

Screening of carbon dioxide utilization options using hybrid Analytic Hierarchy Process-Data Envelopment Analysis method

Carbon dioxide capture, utilization, and storage is an emerging strategy that can contribute to the reduction of greenhouse gas emissions. It enables the use of captured carbon dioxide from industrial sources as feedstock for profitable use or sequestration. This strategy simultaneously allows the use of fossil fuel power plants and the reduction of carbon emissions through storage. Options for carbon dioxide utilization include enhanced oil recovery, enhanced coal bed methane and enhanced shale gas recovery, all of which involve its use as an injection fluid for additional product recovery. A significant portion of the injected carbon dioxide is sequestered. Identification and screening of utilization options for project development is important to develop a cost-effective system. In this study, a hybrid Analytic Hierarchy Process-Data Envelopment Analysis framework is developed to select efficient carbon dioxide utilization options. The selection is based on combining available quantitative data and expert judgments on qualitative criteria to come up with efficiency scores as basis for selection. Two case studies based on realistic data are presented to illustrate the framework. Analysis using Monte Carlo simulation is used to determine the effect of uncertainties on the selected options. The case studies demonstrate the applicability of the methodology to practical problems in the planning of low-carbon systems.

Evaluation of Safety Risks in Construction Using Fuzzy Failure Mode and Effect Analysis (FFMEA)

The construction industry is one of the most dangerous environments within which to work. For this reason safety-related risk analysis is one of the most significant tasks that has to be undertaken when managing major construction projects. A combination of fuzzy Logic and Failure Mode and Effects Analysis (FMEA), Fault Tree Analysis (FTA), and Analytical Hierarchy Process-Data Envelopment Analysis (AHP-DEA) is applied to improve the process of managing safety risks. Two different types of large scale construction projects were also considered as case studies. It was found that the risk of falling from a height was the most significant risk for both types of project. Moreover, the factors intensifying the risk of injury from workers falling were found to be ignoring safety and lack of personal protective equipment as well as a lack of appropriate training for construction workers. It was also concluded that the framework is applicable to all construction sites, covers all safety aspects and its results are valid.

The integrated application of the AHP and the DEA methods in evaluating the performances of higher education institutions in the Republic of Serbia

The measurement and evaluation of performance are critical for the efficient and effective functioning of the economic system, because this allows for the analysis of the extent to which the defined objectives are achieved. Organizational performance is measured by different methods, both quantitative and qualitative. Many of the known methods for the evaluation and measurement of organizational performance take into account only financial indicators, while ignoring the non-financial ones. The integration of both indicators, through the combined application of multiple methods and the comparison of their results, should provide a more complete and objective picture of organizational performance. The Analytic Hierarchy Process (AHP) is a formal framework for solving complex decision-making problems, as well as a systemic procedure for the hierarchical presentation of the problem elements. The Data Envelopment Analysis (DEA) is a non- parametric approach based on linear programming, which allows for the calculation of the efficiency of decision-making units within a group of organizations. The work is an illustration of the method and framework of the combined use of the multi-criteria analysis methods for the measurement and evaluation of the performance of higher education institutions in the Republic of Serbia. The advantages of this approach are reflected in overcoming the shortcomings of a partial application of the AHP and the DEA methods by utilizing a new, hybrid, DEAHP (Data Envelopment Analytic Hierarchy Process) method. Performance evaluation through an integrated application of the AHP and the DEA methods provides more objective results and more reliable solutions to the observed problem, thus creating a valuable information base for high-quality strategic decision making in higher education institutions, both at the national level and at the level of individual institutions.

An application of hybrid data envelopment analytical hierarchy process approach for supplier selection

Purpose – The problem of supplier selection gets complicated when a company looks for various criteria to evaluate different suppliers. The decision criteria used for supplier selection process can be different for different organizations due to a large number of factors. Hence, it can be said that supplier selection is basically, a multiple criteria decision-making (MCDM) problem. The purpose of this paper is to propose a hybrid data envelopment analytical hierarchy process (DEAHP) approach to solve the supplier selection problem for an automobile company. Design/methodology/approach – In this study, the data envelopment analysis (DEA) approach is embedded into analytic hierarchy process (AHP) methodology. Literature review suggested that majority of researches found it appropriate using DEA and AHP methodologies for supplier selection process; hence it is felt that a hybrid DEAHP would be a useful methodology to offer a MCDM model for supplier selection problem. Findings – First, the key criteria of the supplier selection problem for the company are identified. Then a model is developed and implemented for supplier selection using DEAHP approach. This study concluded that quality, cost and service are the most crucial criteria for an automobile company operational in a developing country like India. Sensitivity analysis further helped to evaluate suppliers based on each criterion. Research limitations/implications – As this analysis and findings are based on only one case study of an Indian automobile company, and this necessitates caution in interpreting the results. The limited number of interviewed managers in a company restricts the generalizability of the results. Though the company selected for this study is typical of developing country businesses, the findings of the paper may not be readily extensible to other companies. Second, this study used retrospective settings, based on the interviewed feedback after the events had occurred. This method naturally poses limitations due to respondent recall and the accuracy of information provided. Third, the problem chosen for this study is based in a single country context and further additional research will be required to examine if the findings could be extended to other automobile companies in other developing nations. Also in some cases technique used in the study may pose some extra computational efforts. Practical implications – This study points out the importance of the supplier selection problem. It provides key criteria for supplier selection in Indian context also proposes a framework to deal with multiple criteria. proposed model deals with two crucial criteria long term relationships and flexibility which were relatively less discussed and considered in the literature in past. Originality/value – The proposed MCDM model can provide the guidelines and directions for the decision makers to effectively choose suppliers in the current competitive environment.

Supplier evaluation and selection: a hybrid model based on DEAHP and ABC

Supplier evaluation and selection are now growing to be an important but complex issue due to the fact that they involve a large number of factors and decisions. These factors have complicated operational and financial implications. Therefore, it is necessary to reconcile many competing objectives before a set of comprehensive and consistent metrics for supplier evaluation and selection can be obtained. In this study, a hybrid methodology combining the data envelopment analytic hierarchy process (DEAHP) and activity-based costing (ABC) was developed for supplier evaluation. The advantages of the proposed approach include increasing suppliers’ overall efficiency and also reducing indirect costs which are related to the quality of the supplier and to their delivery performance record. Using this hybrid model, decisions on supplier selection and order quantity can easily be made within an integrated single objective function which is based on consideration of the budget of the buyer and of the capacity of the supplier. A case study was conducted during this study, demonstrating the performance of this hybrid method, in an electronics manufacturing firm.

An improved voting analytic hierarchy process–data envelopment analysis methodology for suppliers selection

Selecting an appropriate supplier is now one of the most important decisions of the purchasing department. Liu and Hai (Liu, F.H.F. and Hai, H.L., 2005. The voting analytic hierarchy process method for selecting supplier. International Journal of Production Economics, 97, 308–317) proposed a voting analytic hierarchy process method for selecting suppliers. Despite its many advantages, Liu and Hai's model (LH-model) has some shortcomings. In this article, the authors present an extended version of the LH-model for multi-criteria supplier selection problem. An illustrative example is presented to compare the authors' model and the LH-model.

A fuzzy AHP-DEA approach for multiple criteria ABC inventory classification

In order to efficiently control the inventory items and determine the suitable ordering policies for them, multi-criteria ABC inventory classification, which is one of the most common techniques of production and inventory control, is used. In this classification, other criteria in addition to annual dollar usage are taken into account and then the items are classified in three classes with different ordering policies, based on their priority. In this paper, we propose an integrated fuzzy analytic hierarchy process-data envelopment analysis (FAHP-DEA) for multiple criteria ABC inventory classification. The proposed FAHP–DEA methodology uses the FAHP to determine the weights of criteria, linguistic terms such as Very High, High, Medium, Low and Very Low to assess each item under each criterion, the data envelopment analysis (DEA) method to determine the values of the linguistic terms, and the simple additive weighting (SAW) method to aggregate item scores under different criteria into an overall score for each item. The integrated FAHP–DEA methodology is illustrated using a real case study.

An Application of Fuzzy Data Envelopment Analytical Hierarchy Process for Reducing Defects in the Production of Liquid Medicine

This article demonstrated the application of the Fuzzy Data Envelopment Analytical Hierarchy Process (FDEAHP) to evaluate the root causes of critical defect problems occurring in the production of liquid medicine. The methodology of the research began by collecting the defect data by using Check Sheets, and ranking the significant problems by using a Pareto Diagram. Two types of major problems were found to occur, including glass fragments in the medicine and damaged lid threads. The causes of each problem were then analyzed by using Cause and Effect Diagrams. The significant causes were ranked by FDEAHP under three criteria, Severity (S), Occurrence (O) and Detection (D), followed by the framework of the FMEA Technique. Two causes with the highest Final Weight (FW) of each problem were selected to be improved, such as installing auxiliary equipment, using the Poka-Yoke system, setting the scale of the shaft and lathing the bushes of each bottle size. The results demonstrated a reduction in defects from 3.209% to 1.669% and showed that improving a few significant root causes, identified by an experienced decision maker, was sufficient to reduce the defect rate.

A note on the application of the data envelopment analytic hierarchy process for supplier selection

In a very recent paper by Sevkli et al. (Sevkli, M., Koh, S.C.L., Zaim, S., Demirbag, M. and Tatoglu, E., 2007. An application of data envelopment analytic hierarchy process for supplier selection: a case study of BEKO in Turkey. International Journal of Production Research, 45 (9), 1973–2003), the data envelopment analytic hierarchy process (DEAHP) was claimed to outperform the analytic hierarchy process (AHP) method and provide a better decision for supplier selection. This note illustrates the weaknesses of the DEAHP, demonstrating the invalidity of the above claim. The case study of BEKO in Turkey is re-examined and shows that extra verification is needed to come to a decision.

An application of data envelopment analytic hierarchy process for supplier selection: a case study of BEKO in Turkey

This paper aims to apply a hybrid method of supplier selection to a well-known Turkish company operating in the appliance industry. The data envelopment analytic hierarchy process (DEAHP) methodology developed by Ramanathan, R., (Data envelopment analysis for weight derivation and aggregation in the analytic hierarchy process. Computers and Operations Research, 2006, 33, 1289–1307) was chosen as the survey method. In this method, the data envelopment analysis (DEA) approach is embedded into analytic hierarchy process (AHP) methodology. This research concluded that the DEAHP method outperforms the AHP method for supplier selection despite the findings that the AHP model suggested supplier 1 to be the best supplier, contradicting the suggestion made by the DEAHP model and the real action taken by BEKO in selecting supplier 2. These findings imply that DEAHP criteria reflect closer to the real optimum of the decision made. Drawing on a real case our study has supported Ramanathan's (2006) work confirming the view that the DEAHP method provides a better decision than the AHP method for supplier selection. Because the DEAHP model is relatively more cumbersome to apply, its application will be more appropriate for high-value components where stringent purchasing criteria are required. In contrast, AHP would remain to be an appropriate approach for relatively lower value components (C class). The novelty of this research lies in the application of a hybrid approach to a real industry case–the DEAHP method for supplier selection, where little has been done on this subject. This study has dealt with one of the most important subjects in supply chain management providing a better decision for supplier selection using appropriate quantitative approaches.