Research and development project evaluation based on an integrated common set of weights in data envelopment analysis and balanced scorecard approach

2012 ◽  
Vol 6 (26) ◽  
Author(s):  
M. Nili. Ahmadabadi
Keyword(s):  
Data Envelopment Analysis ◽  
Research And Development ◽  
Balanced Scorecard ◽  
Project Evaluation ◽  
Development Project ◽  
Data Envelopment ◽  
Common Set Of Weights

A New Integrative Approach Based on Balanced Scorecard, Data Envelopment Analysis, and Management Performance to Prioritize Research and Development Projects

2015 ◽  
pp. 324-348
Author(s):  
Salaman Abbasian-Naghneh ◽  
Mahboobeh Samiei ◽  
Marziyeh Felahat ◽  
Marziyeh Mahdavi
Keyword(s):  
Data Envelopment Analysis ◽  
Research And Development ◽  
Balanced Scorecard ◽  
Integrative Approach ◽  
Development Projects ◽  
Data Envelopment ◽  
Discrimination Power ◽  
New Approach ◽  
The Balanced Scorecard ◽  
Common Basis

The objective of this chapter is to propose a new approach for evaluating Research and Development (R&D) projects at different stages of their life cycle. The approach is based on the integration of the balanced scorecard, Data Envelopment Analysis (DEA), and Multiple Objective (MO) linear programming. An interactive MO-DEA model is presented to incorporate Decision Maker's (DM) preference to effectively establish a common basis for fully ranking projects. The approach is illustrated on 50 R&D projects from the literature to highlight the effectiveness of the approach to fully rank all competing projects, hence increasing the discrimination power of DEA approach.

A Common Set of Weights for Ranking Decision-Making Units with Undesirable Outputs: A Double Frontiers Data Envelopment Analysis Approach

2018 ◽  
Vol 35 (06) ◽  
pp. 1850039 ◽  
Author(s):  
Lei Chen ◽  
Fei-Mei Wu ◽  
Feng Feng ◽  
Fujun Lai ◽  
Ying-Ming Wang
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Optimal Solution ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Discrimination Power ◽  
Efficiency Optimization ◽  
Common Set Of Weights ◽  
Desirable And Undesirable Outputs ◽  
Decision Making Units

Major drawbacks of the traditional data envelopment analysis (DEA) method include selecting optimal weights in a flexible manner, lacking adequate discrimination power for efficient decision-making units, and considering only desirable outputs. By introducing the concept of global efficiency optimization, this study proposed a double frontiers DEA approach with undesirable outputs to generate a common set of weights for evaluating all decision-making units from both the optimistic and pessimistic perspectives. For a unique optimal solution, compromise models for individual efficiency optimization were developed as a secondary goal. Finally, as an illustration, the models were applied to evaluate the energy efficiency of the Chinese regional economy. The results showed that the proposed approach could improve discrimination power and obtain a fair result in a case where both desirable and undesirable outputs exist.

scholarly journals Analisis Kinerja Perusahaan dengan Menggunakan Balanced Scorecard dan Data Envelopment Analysis

2017 ◽  
Vol 5 (1) ◽  
Author(s):  
Hanung Eryadi Prasetya ◽  
Bambang Subroto ◽  
Erwin Saraswati
Keyword(s):  
Data Envelopment Analysis ◽  
Performance Improvement ◽  
Balanced Scorecard ◽  
Research Data ◽  
Data Envelopment ◽  
Determination Method ◽  
Financial Perspective ◽  
Analysis Instrument ◽  
Performance Decline ◽  
Customer Perspective

The objective of this research is to understand cooperation performance using integration of Balanced Scorecard and Data Envelopment Analysis an to analyze the eficiency and efectivity level by utilizing Data Envelopment Analysis based on criteria in Balanced Scorecard. The sampling determination method used non probability sampling. The research data were collected from Cooperation Agency in Jombang Regency. The data analysis instrument was performance assesment using Balanced Scorecard Perpective based on financial perspective, customer, internal bisnis, learning and growth, and also eficiency calculation using DEA output oriented model. The result of this research concludes : from financial perspective is has been there was performance improvement in 2014 and 2 Cooperation were eficient; from customer perspective it has been discovered that there was performance decline in 2014 and 2 Cooperation were eficient; from internal bisnis perspective, it has been detected that there was performance improvement in the last year and 2 Cooperation were eficient; from learning and growth perspective, it that only one Cooperation was able to reach maximum eficiency. Keywords: Performance, DEA, BSC, Efficiency

scholarly journals New Approach in Fixed Resource Allocation and Target Setting Using Data Envelopment Analysis with Common Set of Weights

Complexity ◽  
2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Marzieh Ghasemi ◽  
Mohammad Reza Mozaffari ◽  
Farhad Hosseinzadeh Lotfi ◽  
Mohsen Rostamy malkhalifeh ◽  
Mohammad Hasan Behzadi
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Target Setting ◽  
New Approach ◽  
Common Set Of Weights ◽  
Programming Techniques ◽  
Using Data ◽  
Decision Making Units

One of the mathematical programming techniques is data envelopment analysis (DEA), which is used for evaluating the efficiency of a set of similar decision-making units (DMUs). Fixed resource allocation and target setting with the help of DEA is a subject that has gained much attention from researchers. A new model was proposed by determining a common set of weights (CSW). All DMUs were involved with the aim of achieving higher efficiency in every DMU after the procedure. The minimum resources and targets allocated to each DMU were commensurate to the efficiency of that DMU and the share of DMU in the input resources and the output productions. To examine the proposed method, other methods in the DEA literature were examined as well, and then, the efficiency of the method was demonstrated through a numerical example.

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