DEA models for two decision makers with conflicts: the principal-agent problem

2019 ◽  
Vol 53 (3) ◽  
pp. 749-765
Author(s):  
Yuandong Gu ◽  
Linlin Zhao ◽  
Yong Zha ◽  
Liang Liang
Keyword(s):  
Data Envelopment Analysis ◽  
Electric Power ◽  
Incentive Contracts ◽  
Decision Makers ◽  
The Other ◽  
Principal Agent ◽  
Data Envelopment ◽  
Principal Agent Problem ◽  
Dea Models ◽  
The Impact

This paper studies the impact of two decision makers’ interaction with conflicts on the efficiencies of the system. We start with a general principal-agent framework where the principal and the agent make decisions independently and the principal has a contradictive objective to that of the agent. We develop data envelopment analysis (DEA) models in the principal’s and the agent’s perspectives respectively. Non-cooperation between the principal and the agent is discussed to illustrate how one decision maker affects the other and the corresponding efficiency and incentive contract of the system. In addition, cooperation of the two parties is also analyzed to better derive how the performance of the system is influenced by the parties and their interactions as well. Then, this study illustrates the proposed models and effective incentive contracts by applying them to the efficiency evaluations of 22 China listed electric power companies.

scholarly journals A Range Adjusted Measure of Super-Efficiency in Integer-Valued Data Envelopment Analysis with Undesirable Outputs

2021 ◽  
Vol 9 (4) ◽  
pp. 378-398
Author(s):  
Chunhua Chen ◽  
Haohua Liu ◽  
Lijun Tang ◽  
Jianwei Ren
Keyword(s):  
Data Envelopment Analysis ◽  
Transportation Systems ◽  
Decision Makers ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Super Efficiency ◽  
Dea Model ◽  
Dea Models ◽  
Analysis Models ◽  
Transport Accidents

Abstract DEA (data envelopment analysis) models can be divided into two groups: Radial DEA and non-radial DEA, and the latter has higher discriminatory power than the former. The range adjusted measure (RAM) is an effective and widely used non-radial DEA approach. However, to the best of our knowledge, there is no literature on the integer-valued super-efficiency RAM-DEA model, especially when undesirable outputs are included. We first propose an integer-valued RAM-DEA model with undesirable outputs and then extend this model to an integer-valued super-efficiency RAM-DEA model with undesirable outputs. Compared with other DEA models, the two novel models have many advantages: 1) They are non-oriented and non-radial DEA models, which enable decision makers to simultaneously and non-proportionally improve inputs and outputs; 2) They can handle integer-valued variables and undesirable outputs, so the results obtained are more reliable; 3) The results can be easily obtained as it is based on linear programming; 4) The integer-valued super-efficiency RAM-DEA model with undesirable outputs can be used to accurately rank efficient DMUs. The proposed models are applied to evaluate the efficiency of China’s regional transportation systems (RTSs) considering the number of transport accidents (an undesirable output). The results help decision makers improve the performance of inefficient RTSs and analyze the strengths of efficient RTSs.

RELAXING THE IMPACT OF EXTREME UNITS IN DATA ENVELOPMENT ANALYSIS

2012 ◽  
Vol 11 (05) ◽  
pp. 893-907 ◽  
Author(s):  
YIANNIS G. SMIRLIS ◽  
DIMITRIS K. DESPOTIS
Keyword(s):  
Data Envelopment Analysis ◽  
Original Data ◽  
Efficiency Score ◽  
Data Envelopment ◽  
Programming Technique ◽  
Data Set ◽  
Usual Practice ◽  
Dea Models ◽  
Production Possibility Set ◽  
The Impact

Data envelopment analysis (DEA) is a nonparametric linear programming technique for measuring the relative efficiency of decision making units (DMUs) on the basis of multiple inputs and outputs. DEA assessments, however, are proved to be sensitive to extreme units that deviate substantially in their input/output patterns. In this paper we introduce an approach for handling extreme observations in DEA, i.e., observations that exhibit irregularly high values in some outputs and/or low values in some inputs. Unlike the usual practice of removing such observations, we retain them in the production possibility set reducing their impact on the other units. Our modeling approach is based on the concept of diminishing returns, assuming that the contribution of an output (input) to the efficiency score diminishes as the output increases beyond a pre-specified level, i.e., the level beyond which a value is characterized as extreme. According to our approach the original data set is transformed to an augmented data set, where standard DEA models can then be applied, remaining thus in the grounds of the standard DEA methodology. We illustrate our approach with a numerical example.

scholarly journals Data Envelopment Analysis with Uncertain Inputs and Outputs

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Meilin Wen ◽  
Linhan Guo ◽  
Rui Kang ◽  
Yi Yang
Keyword(s):  
Data Envelopment Analysis ◽  
Deterministic Model ◽  
The Other ◽  
Data Envelopment ◽  
Decision Tool ◽  
Uncertain Measure ◽  
Dea Model ◽  
Dea Models ◽  
The One ◽  
Inputs And Outputs

Data envelopment analysis (DEA), as a useful management and decision tool, has been widely used since it was first invented by Charnes et al. in 1978. On the one hand, the DEA models need accurate inputs and outputs data. On the other hand, in many situations, inputs and outputs are volatile and complex so that they are difficult to measure in an accurate way. The conflict leads to the researches of uncertain DEA models. This paper will consider DEA in uncertain environment, thus producing a new model based on uncertain measure. Due to the complexity of the new uncertain DEA model, an equivalent deterministic model is presented. Finally, a numerical example is presented to illustrate the effectiveness of the uncertain DEA model.

scholarly journals APPLICATION OF STEPWISE DATA ENVELOPMENT ANALYSIS AND GREY INCIDENCE ANALYSIS TO EVALUATE THE EFFECTIVENESS OF EXPORT PROMOTION PROGRAMS

2013 ◽  
Vol 14 (3) ◽  
pp. 638-650 ◽  
Author(s):  
Seyed Hossein Razavi Hajiagha ◽  
Edmundas Kazimieras Zavadskas ◽  
Shide Sadat Hashemi
Keyword(s):  
Resource Allocation ◽  
Data Envelopment Analysis ◽  
International Markets ◽  
Export Promotion ◽  
Decision Makers ◽  
The Other ◽  
Data Envelopment ◽  
Different Types ◽  
Grey Incidence Analysis ◽  
Incidence Analysis

Export promotion programs are incentives to increase the participation of companies in international markets. On the other hand, governments try to help exporting companies with developing their goal markets. Therefore, for this purpose, many different programs have been created. To show the effectiveness of these programs, the paper refers to stepwise DEA and grey incidence analysis. Finally, the article determines a unified ranking of the applied programs that can be used by decision makers for resource allocation considering different types of programs based on their effectiveness.

scholarly journals Assess the Impact of the COVID-19 Pandemic and Propose Solutions for Sustainable Development for Textile Enterprises: An Integrated Data Envelopment Analysis-Binary Logistic Model Approach

2021 ◽  
Vol 14 (10) ◽  
pp. 465
Author(s):  
Han-Khanh Nguyen ◽  
Mai-Nam Vu
Keyword(s):  
Data Envelopment Analysis ◽  
Textile Industry ◽  
Logistic Model ◽  
Business Performance ◽  
Data Envelopment ◽  
Factors Affecting ◽  
Dea Models ◽  
Binary Logistic Model ◽  
The Impact ◽  
Model Approach

The COVID-19 pandemic impacted many socio-economic areas of countries around the world. It has made the production and business situations of enterprises face substantial difficulties. In this study, the authors used data envelopment analysis (DEA) models to assess the impact of the COVID-19 pandemic on Vietnam’s textile and garment enterprises. The authors have used the binary logistic model to determine the factors affecting employees’ decision to change jobs in the textile industry. The research results showed that the COVID-19 pandemic greatly affected the business performance of the textile and garment enterprises in Vietnam. Moreover, the results helped identify the factors affecting employee turnover and proposed solutions to help businesses stabilize their personnel situation and develop sustainable businesses in the post-COVID-19 era.

scholarly journals A Study on the Impact of R&D Intensity on Business Performance: Evidence from South Korea

2021 ◽  
Vol 7 (2) ◽  
pp. 135
Author(s):  
Hun Park ◽  
Jun-Hwan Park ◽  
Sujin Lee ◽  
Hyuk Hahn
Keyword(s):  
South Korea ◽  
Research And Development ◽  
Business Performance ◽  
Decision Makers ◽  
The Other ◽  
Research Groups ◽  
Innovative Firms ◽  
The Impact ◽  
Knowledge Services

The role of R&D (research and development) intensity on the effect of knowledge services on the business performance of firms has been discussed by using PLS-SEM and PLS-MGA methods. Research groups were divided into two groups, innovative and non-innovative. Respondents were classified into innovative firms if their R&D intensity was over 3% and vice versa. PLS-SEM and PLS-MGA results were compared for two groups and valuable insights were extracted. For innovative firms, knowledge services seemed to be verified and processed by the decision makers and utilized to achieve their business performance. On the other hand, a large number of non-innovative firms seemed to have a stronger tendency to utilize knowledge services directly for their business without sufficient verification by the decision makers.

Measuring Performance of a Three-Stage Network Structure Using Data Envelopment Analysis and Nash Bargaining Game: A Supply Chain Application

2018 ◽  
Vol 17 (05) ◽  
pp. 1429-1467 ◽  
Author(s):  
Mohammad Amirkhan ◽  
Hosein Didehkhani ◽  
Kaveh Khalili-Damghani ◽  
Ashkan Hafezalkotob
Keyword(s):  
Supply Chain ◽  
Data Envelopment Analysis ◽  
Nash Bargaining ◽  
Data Envelopment ◽  
Second Stage ◽  
Proposed Model ◽  
Nash Bargaining Game ◽  
Dea Models ◽  
Overall Efficiency

The issue of efficiency analysis of network and multi-stage systems, as one of the most interesting fields in data envelopment analysis (DEA), has attracted much attention in recent years. A pure serial three-stage (PSTS) process is a specific kind of network in which all the outputs of the first stage are used as the only inputs in the second stage and in addition, all the outputs of the second stage are applied as the only inputs in the third stage. In this paper, a new three-stage DEA model is developed using the concept of three-player Nash bargaining game for PSTS processes. In this model, all of the stages cooperate together to improve the overall efficiency of main decision-making unit (DMU). In contrast to the centralized DEA models, the proposed model of this study provides a unique and fair decomposition of the overall efficiency among all three stages and eliminates probable confusion of centralized models for decomposing the overall efficiency score. Some theoretical aspects of proposed model, including convexity and compactness of feasible region, are discussed. Since the proposed bargaining model is a nonlinear mathematical programming, a heuristic linearization approach is also provided. A numerical example and a real-life case study in supply chain are provided to check the efficacy and applicability of the proposed model. The results of proposed model on both numerical example and real case study are compared with those of existing centralized DEA models in the literature. The comparison reveals the efficacy and suitability of proposed model while the pitfalls of centralized DEA model are also resolved. A comprehensive sensitivity analysis is also conducted on the breakdown point associated with each stage.

Benchmarking the efficiencies of Indonesia’s municipal water utilities using Stackelberg data envelopment analysis

2015 ◽  
Vol 22 (4) ◽  
pp. 588-609 ◽  
Author(s):  
Andreas Wibowo ◽  
Hans Wilhelm Alfen
Keyword(s):  
Data Envelopment Analysis ◽  
The Body ◽  
Water Utilities ◽  
Data Envelopment ◽  
Two Stage ◽  
Restrictive Assumption ◽  
Content Type ◽  
Second Stage ◽  
Municipal Water ◽  
The Impact

Purpose – The purpose of this paper is to present a yardstick efficiency comparison of 269 Indonesian municipal water utilities (MWUs) and measures the impact of exogenous environmental variables on efficiency scores. Design/methodology/approach – Two-stage Stackelberg leader-follower data envelopment analysis (DEA) and artificial neural networks (ANN) were employed. Findings – Given that serviceability was treated as the leader and profitability as the follower, the first and second stage DEA scores were 55 and 32 percent (0 percent = totally inefficient, 100 percent = perfectly efficient), respectively. This indicates sizeable opportunities for improvement, with 39 percent of the total sample facing serious problems in both first- and second-stage efficiencies. When profitability instead leads serviceability, this results in more decreased efficiency. The size of the population served was the most important exogenous environmental variable affecting DEA efficiency scores in both the first and second stages. Research limitations/implications – The present study was limited by the overly restrictive assumption that all MWUs operate at a constant-return-to-scale. Practical implications – These research findings will enable better management of the MWUs in question, allowing their current level of performance to be objectively compared with that of their peers, both in terms of scale and area of operation. These findings will also help the government prioritize assistance measures for MWUs that are suffering from acute performance gaps, and to devise a strategic national plan to revitalize Indonesia’s water sector. Originality/value – This paper enriches the body of knowledge by filling in knowledge gaps relating to benchmarking in Indonesia’s water industry, as well as in the application of ensemble two-stage DEA and ANN, which are still rare in the literature.

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