THE INTEGRATION OF ANALYTICAL HIERARCHY PROCESS AND DATA ENVELOPMENT ANALYSIS IN A MULTI-CRITERIA DECISION-MAKING PROBLEM

2006 ◽  
Vol 05 (02) ◽  
pp. 263-276 ◽  
Author(s):  
NORITA AHMAD ◽  
DANIEL BERG ◽  
GENE R. SIMONS
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Analytical Hierarchy Process ◽  
Data Envelopment ◽  
Multi Criteria Decision Making ◽  
Analysis Model ◽  
Decision Tool ◽  
Manufacturing Enterprises ◽  
Decision Making Problem ◽  
Hierarchy Process

This research focuses on developing a model that can be used to assess the performance of Small to Medium-Sized Manufacturing Enterprises (SMEs). The model will result from the integration of a decision tool called the Analytical Hierarchy Process (AHP) and a data analysis model called Data Envelopment Analysis (DEA). This research demonstrates that by eliminating flaws and taking advantage of each methodology's specific characteristics in identifying and solving problems, the new integrated AHP/DEA model appears to be a logical and sensible solution in multi-criteria decision-making problem.

scholarly journals Kombinasi Analytical Hierarchy Process (AHP) dan Data Envelopment Analysis (DEA) untuk Pemilihan Supplier Pada UD. Jepara Putra Mebel

2020 ◽  
Vol 19 (2) ◽  
Author(s):  
Wilma Latuny ◽  
Daniel Bunga Paillin ◽  
Samrotul Yaniah
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Analytical Hierarchy Process ◽  
Data Envelopment ◽  
Decision Making Unit ◽  
Hierarchy Process

<p><em>Penelitian ini membahas tentang pemilihan supplier bahan baku kayu pada UD. Jepara Putra Mebel dengan integrasi AHP dan DEA. Hasil pengolahan data dengan metode AHP diperoleh nilai bobot prioritas tertinggi adalah supplier A (0.504), supplier B(0.371), supplier C(0.125). Hasil perhitungan dengan metode AHP-DEA untuk mengevaluasi setiap Decision Making Unit (DMU) atau Supplier, diperoleh nilai tingkat efisiensi untuk Supplier A, C  memiliki tingkat nilai efisienasi 1, dan supplier B tidak efisien. Hasil AHP-DEA super efisiensi menunjukan supplier C memiliki nilai tertinggi sebesar 2. 095 hasil ini menunjukan bahwa setiap Supplier C dikatakan lebih effisien dari supplier A, sehingga pendekatan AHP-DEA merekomendasikan kepada perusahan untuk Supplier yang harus di utamakan pertama yaitu Supplier C, kemudian kedua Supplier A dan ketiga yaitu Supplier B tentunya melalui pertimbangan kriteria Harga, Kualitas, Pelayanan, Pengiriman, Ketetapan jumlah dan evaluasi tingkat efisiensi setiap DMU yang telah dilakukan. </em></p>

scholarly journals A knowledge system proposal with weighted goal programming approach for multi-criteria dea model and an application

2021 ◽  
Vol 12 (2) ◽  
pp. 422-438
Author(s):  
Tugba Polat ◽  
Safak Kiris
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Goal Programming ◽  
Evaluation Process ◽  
Knowledge System ◽  
Programming Approach ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Weighted Goal Programming

In today's competitive environment, enterprises should use their resources correctly; they should continuously improve themselves and work efficiently. It is important to evaluate the performances of the units under the same conditions in enterprises according to each other, to see the current situations and to determine appropriate improvements in necessary points. One of the commonly used approaches to performance evaluation is Data Envelopment Analysis. Many approaches have been developed for the Data Envelopment Analysis model, and Goal programming using in multi-objective decision making solutions approaches is one of them. Goal Programming gives decision-makers the opportunity to evaluate many objectives together in the decision-making process. In this study, classical Data Envelopment Analysis and weighted goal programming approach for multi-criteria data envelopment analysis model was applied in the evaluation process of the projects worked in an automotive supplier industry. A knowledge system has also been proposed in order to evaluate the effectiveness of the projects periodically and to include new projects or conditions into the evaluation.

scholarly journals Assessing Factors for Designing a Successful B2C E-Commerce Website Using Fuzzy AHP and TOPSIS-Grey Methodology

Symmetry ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 363
Author(s):  
Ran Li ◽  
Tao Sun
Keyword(s):  
Decision Making ◽  
Analytical Hierarchy Process ◽  
Fuzzy Ahp ◽  
Literature Survey ◽  
Multi Criteria Decision Making ◽  
The Core ◽  
Business To Consumer ◽  
Main Factors ◽  
Hierarchy Process

The recent hype in online purchasing has skyrocketed the importance of the electronic commerce (e-commerce) industry. One of the core segments of this industry is business-to-consumer (B2C) where businesses use their websites to sell products and services directly to consumers. Thus, it must be taken care of that B2C websites are designed in a way which can build a trustworthy and long-term relationship between businesses and consumers. Thus, this study assesses and prioritizes factors for designing a successful B2C e-commerce website. The study employs multi-criteria decision making (MCDM), and to minimize any ambiguity and greyness in the decision-making, it integrates fuzzy and grey respectively with the Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to form FAHP and TOPSIS-Grey. Initially, the study conducts a thorough literature survey to screen important factors reported in past studies. Five main factors and nineteen sub-factors were selected for further prioritization. Later, FAHP prioritized factors based on their importance. Finally, based on the FAHP results, TOPSIS-Grey ranked five alternatives (e-commerce websites). FAHP revealed “service quality” as the most successful website designing factor, while TOPSIS-Grey reported “Website-3” as the most successful website, having incorporated the factors required to design a successful website.

Assessment of Coaches Using Data Envelopment Analysis and Analytical Hierarchy Process

2014 ◽  
Vol 687-691 ◽  
pp. 1560-1563
Author(s):  
Han Cong Tang ◽  
Yan An Dong
Keyword(s):  
Data Envelopment Analysis ◽  
Analytical Hierarchy Process ◽  
Comprehensive Evaluation ◽  
Data Envelopment ◽  
Filter Model ◽  
Winning Percentage ◽  
Evaluation Of Coaching ◽  
And Gender ◽  
Using Data ◽  
Hierarchy Process

This paper presents three models as a potential decision making method for selecting the best baseball, field hockey, and women’s basketball NCAA Division I coaches. Five indicators, synthesized coaching efficiency, winning percentage, consecutive championship, achievement index and gender, are introduced to give a comprehensive evaluation of coaching ability. The preliminary served as a filter model to screen out less capable coaches and a robust ranking within top 10 is achieved. The Data Envelopment Analysis (DEA) model takes the time line horizon into consideration, and helps find less efficient coaches. By comparing the first two models, we obtain a reasonable assessment of coaches from different time period. Finally, by applying the Analytical Hierarchy Process (AHP), minor changes in judgment matrices can be made to adjust the ratio of male to female in the top 5 coaches.

scholarly journals Using Data Envelopment Analysis and Multi-Criteria Decision-Making Methods to Evaluate Teacher Performance in Higher Education

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 563 ◽  
Author(s):  
Milena Popović ◽  
Gordana Savić ◽  
Marija Kuzmanović ◽  
Milan Martić
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Data Envelopment Analysis ◽  
Conjoint Analysis ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Multi Criteria Decision Making ◽  
Weight Restrictions ◽  
Analytic Hierarchy ◽  
Discrimination Power

This paper proposes an approach that combines data envelopment analysis (DEA) with the analytic hierarchy process (AHP) and conjoint analysis, as multi-criteria decision-making methods to evaluate teachers’ performance in higher education. This process of evaluation is complex as it involves consideration of both objective and subjective efficiency assessments. The efficiency evaluation in the presence of multiple different criteria is done by DEA and results heavily depend on their selection, values, and the weights assigned to them. Objective efficiency evaluation is data-driven, while the subjective efficiency relies on values of subjective criteria usually captured throughout the survey. The conjoint analysis helps with the selection and determining the relative importance of such criteria, based on stakeholder preferences, obtained as an evaluation of experimentally designed hypothetical profiles. An efficient experimental design can be either symmetric or asymmetric depending on the structure of criteria covered by the study. Obtained importance might be a guideline for selecting adequate input and output criteria in the DEA model when assessing teachers’ subjective efficiency. Another reason to use conjoint preferences is to set a basis for weight restrictions in DEA and consequently to increase its discrimination power. Finally, the overall teacher’s efficiency is an AHP aggregation of subjective and objective teaching and research efficiency scores. Given the growing competition in the field of education, a higher level of responsibility and commitment is expected, and it is therefore helpful to identify weaknesses so that they can be addressed. Therefore, the evaluation of teachers’ efficiency at the University of Belgrade, Faculty of Organizational Sciences illustrates the usage of the proposed approach. As results, relatively efficient and inefficient teachers were identified, the reasons and aspects of their inefficiency were discovered, and rankings were made.

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