Integrated Data Envelopment Analysis Model Research Articles

A methodology for evaluating salespeople performance considering efficiency and effect: A case study of a liquor company in China.

The performance evaluation is one of the most important organizational management strategies used to guide the sales behavior of sales staff. However, it should be work process-oriented or sales result-oriented has become a dilemma for the management when evaluating employees' performance. Therefore, comprehensively evaluating the work process and sales results has become a challenge when it comes to salespeople performance appraisal. To solve this dilemma, this research builds a salesperson performance evaluation model which considering both of work efficiency and effectiveness, based on the decision tree model. Specifically, we use the Data Envelopment Analysis (DEA) model to quantify the work efficiency of salespeople and measure the work effectiveness by amount of sales. Moreover, this research proposes an advanced integrated DEA model by integrating the self-evaluation DEA models, peer-evaluation DEA models, and Gini impurity, which is identified to be more stable compared with the current DEA model. Finally, a case study of a Chinese liquor company is introduced to illustrate the applicability and feasibility of the salesperson performance evaluation model. The proposed model is applied to evaluate the performance of the salespeople, and a set of comprehensive and objective sales performance evaluation results are obtained. The estimated results can provide feasible sales management suggestions for the company in diagnosing work problems of salespeople.

Efficiency Analysis of Fixed Broadband Service Management Industry: Measurement of the Integrated DEA Model

The goal of this study was to examine the level of efficiency of fixed broadband service providers as a measure of the research model's input as influenced by internal and external factors. Non-parametric approaches, Data Envelopment Analysis (DEA) models, and Path Analysis were used in this study to assess the efficiency of Fixed Broadband Service Providers. The reason for the study is that the ability to generate income to obtain maximum profit in order to be in a strategic position for business competitiveness is a key component to consider for the Fixed Broadband Service Provider industry in order to ensure business continuity. The research findings indicate that the input variable has an impact on the output variable. For the 2015 – 2020 period, the input size in the form of Total Assets has an impact on the Cost Flow Investing Act, total subscribers, and fiber optic backbone network, all of which affect the efficiency of Fixed Broadband Service Providers as many as 5 (five) Big Providers (The Big Five). External factors such as Customer Price Index (CPI) and Interest Rates, on the other hand, have a favorable impact on Operator Efficiency.

Theory of binary-valued data envelopment analysis: an application in assessing the sustainability of suppliers

PurposeThe objective of this study is to present a binary-valued data envelopment analysis (DEA) theory. The authors’ proposed approach, for the first time, combines binary-valued and integer-valued theories concurrently in the DEA context. To do so, new production possibility sets (PPSs) with some distinguished features are developed.Design/methodology/approachThe authors address integer inputs and outputs in the proposed approach by introducing a new PPS.FindingsTo take into account the binary data, the authors develop axiomatic DEA principles. The binary production principles guarantee any combination of convexity and feasibility. Furthermore, the authors develop a new DEA model to consider integer and real data. A case study is presented to show the usefulness of the developed models. Using the proposed models, the authors obtained benchmarks to solve the sustainable supplier selection problems.Originality/value(1) For the first time, binary-valued and integer-valued theories are presented in an integrated DEA model. (2) To deal with the pure binary data, a new PPS is proposed. (3) To consider real, integer and binary data, a new PPS is introduced. (4) New technologies are developed to propose feasible solutions. (5) The proposed models can project inefficient decision-making units (DMUs) on efficiency frontier given binary, integer and real data. (6) A case study is given for the performance evaluation of sustainable suppliers.

Selecting Six Sigma project: a comparative study of DEA and LDA techniques

PurposeNowadays, most of the organizations have focused through the world on Six Sigma to reduce the costs, improve the productivity and enhance concerned individuals’ satisfaction, especially customers’ satisfaction. Annually, these organizations define and execute thousands of Six Sigma projects which involve a great deal of investments. But are all of these projects successful and do the organizations benefit from the above advantages? The purpose of this study is to proposing a methodology to to answer this question that: How can we reduce the risk of failure in Six Sigma projects? The first step to reduce the risk of failure in Six Sigma projects is selecting optimal ones which have the most profits and the least expected risks.Design/methodology/approachFirst, the effective criteria are recognized and defined in selecting Six Sigma projects. Then, a new data envelopment analysis (DEA) model is proposed for project selection process. A real example is resolved by the presented model. Finally, the authors use linear discriminate analysis (LDA) to examine the validity of obtained results from the proposed model.FindingsThe results show that the proposed model is a suitable tool for selecting Six Sigma Projects. The findings demonstrate that the selected projects by suggested integrated DEA model are those confirmed by LDA.Originality/valueThe paper, using a real case study, provides a mathematical model to enhance decision quality in Six Sigma project selection. Applying the specific DEA model is remarkable itself, which joined to a pioneering procedure to use LDA to validity evaluation of the results.

An Integrated DEA Model Allowing Decomposition of Eco-Efficiency: A Case Study of China

Abstract A common feature of previous studies about the application of data envelopment analysis (DEA) to determine environmental and economic efficiencies is that the two were analyzed in separate models or frameworks. The purpose of this paper is to analyze the economic efficiency and environmental efficiency with a single model. This paper proposes an integrated DEA model, based on a modification of the directional distance function, which allows us to decompose the eco-efficiency (EE) into the economic efficiency (ECE) and environmental efficiency (ENE). The ECE characterizes the ability of gaining economic benefits while the ENE characterizes the ability to control pollutant emissions in production activities. Identification of ECE and ENE can help decision makers of different regions detect what kind of factor (economic inefficiency or environmental inefficiency) is the main source of eco-inefficiency. This can help decision makers more targeted to improve EE. To illustrate the feasibility of our approach, a case study of 30 regions in China is presented. The empirical results show that almost all regions have very high economic efficiencies. The environmental inefficiency is the main source of eco-inefficiency. The differences of environmental efficiencies lead to the differences of eco-efficiencies in the east, central and west areas, while the economic efficiencies do not have significant differences among these areas. The economic efficiencies showed an opposite “V” shape and the environmental efficiencies showed a decreasing trend during the period 2010–2014.

The role of non-Archimedean epsilon in finding the most efficient unit: With an application of professional tennis players

The determination of a single efficient decision making unit (DMU) as the most efficient unit has been attracted by decision makers in some situations. Some integrated mixed integer linear programming (MILP) and mixed integer nonlinear programming (MINLP) data envelopment analysis (DEA) models have been proposed to find a single efficient unit by the optimal common set of weights. In conventional DEA models, the non-Archimedean infinitesimal epsilon, which forestalls weights from being zero, is useless if one utilizes the well-known two-phase method. Nevertheless, this approach is inapplicable to integrated DEA models. Unfortunately, in some proposed integrated DEA models, the epsilon is neither considered nor determined. More importantly, based on this lack some approaches have been developed which will raise this drawback.In this paper, first of all some drawbacks of these models are discussed. Indeed, it is shown that, if the non-Archimedean epsilon is ignored, then these models can neither find the most efficient unit nor rank the extreme efficient units. Next, we formulate some new models to capture these drawbacks and hence attain assurance regions. Finally, a real data set of 53 professional tennis players is applied to illustrate the applicability of the suggested models.

An epsilon-free approach for finding the most efficient unit in DEA

Data envelopment analysis (DEA), considering the best condition for each decision making unit (DMU), assesses the relative efficiency and partitions DMUs into two sets: efficient and inefficient. Practically, in traditional DEA models more than one efficient DMU are recognized and these models cannot rank efficient DMUs. Some studies have been carried out aiming at ranking efficient DMUs, although in some cases only discrimination of the most efficient unit is desirable. Furthermore, several investigations have been done for finding the most CCR-efficient DMU. The basic idea of the majority of them is to introduce an integrated model which achieves an optimal common set of weights (CSW). These weights help us identify the most efficient unit in an identical condition.Recently, Toloo (2012) [13] proposed a new mixed integer programming (MIP) model to find the most BCC-efficient unit. Based on this study, we propose a new basic integrated linear programming (LP) model to identify candidate DMUs for being the most efficient unit; next a new MIP integrated DEA model is introduced for determining the most efficient DMU. Moreover, these models exclude the non-Archimedean epsilon and consequently the optimal solution of these models can be obtained, straightforwardly. We claim that the most efficient unit, which could be obtained from all other integrated models, has to be one of the achieved candidates from the basic integrated LP model. Two numerical examples are illustrated to show the variant use of these models in different important cases.

Integrated data envelopment analysis: Global vs. local optimum

Chiou et al. (2010) (A joint measurement of efficiency and effectiveness for non-storable commodities: integrated data envelopment analysis approaches. European Journal of Operational Research 201, 477–489) propose an integrated data envelopment analysis model in measuring decision making units (DMUs) that have a two-stage internal network structure with multiple inputs, outputs, and consumptions. They claim that any optimal solutions determined by their DEA model are a global optimum, not a local optimum. We show that such a conclusion is a false statement due to their misuse of Hessian matrix in examining the concavity of the objective function, and their DEA model is actually a non-convex optimization problem. As a result, their DEA model is unusable in practice due to a lack of efficient algorithm for this particular non-convex DEA model. We further show that Chiou et al.’s (2010) model is a special case of a well-known two-stage network DEA model, and it can be transformed into a parametric linear program for which an approximate global optimal solution can be obtained by solving a sequence of linear programs in combination with a simple search algorithm.

A note on “A new method for ranking discovered rules from data mining by DEA”, and a full ranking approach

In a recent paper by Toloo et al. [Toloo, M., Sohrabi, B., & Nalchigar, S. (2009). A new method for ranking discovered rules from data mining by DEA. Expert Systems with Applications, 36, 8503–8508], they proposed a new integrated data envelopment analysis model to find most efficient association rule in data mining. Then, utilizing this model, an algorithm is developed for ranking association rules by considering multiple criteria. In this paper, we show that their model only selects one efficient association rule by chance and is totally depended on the solution method or software is used for solving the problem. In addition, it is shown that their proposed algorithm can only rank efficient rules randomly and will fail to rank inefficient DMUs. We also refer to some other drawbacks in that paper and propose another approach to set up a full ranking of the association rules. A numerical example illustrates some contents of the paper.

Proposing new models for finding the most efficient DMUs in DEA

This paper improves the integrated Data Envelopment Analysis (DEA) model introduced by Amin (2009) [1]. for finding the most efficient Decision Making Units In addition this research introduces an integrated DEA model called “MinMin” and using comparisons between earlier models and the proposed model determines the most efficient Decision Making Unit (DMU). The properties are included in an improved mathematical calculation and this is applied to a real data set consisting of the 19 facility layout alternatives to demonstrate the usefulness and intelligibility of the study.

Information technology project evaluation: An integrated data envelopment analysis and balanced scorecard approach

Information technology (IT) is a tool crucial for enterprises to achieve a competitive advantage and organizational innovation. A critical aspect of IT management is the decision whereby the best set of IT projects is selected from many competing proposals. The optimal selection process is a significant strategic resource allocation decision that can engage an organization in substantial long-term commitments. However, making such decisions is difficult because there are lots of quantitative and qualitative factors to be considered in evaluation process. This paper has two main contributions. Firstly, it combines two well-established managerial methodologies, balanced scorecard (BSC) and data envelopment analysis (DEA), and proposes a new approach for IT project selection. This approach uses BSC as a comprehensive framework for defining IT projects evaluation criteria and uses DEA as a nonparametric technique for ranking IT projects. Secondly, this paper introduces a new integrated DEA model which identifies most efficient IT project by considering cardinal and ordinal data. Applicability of proposed approach is illustrated by using real world data of Iran Ministry of Science, Research and Technology.

INTEGRATED DATA ENVELOPMENT ANALYSIS MODELS FOR MEASURING TRANSPORT EFFICIENCY AND EFFECTIVENESS

Abstract: This paper proposes integrated data envelopment analysis (DEA) models to jointly evaluate the transport efficiency and effectiveness by measuring the efficiency scores under three aspects of technical efficiency, service effectiveness, and technical effectiveness simultaneously. The underlying reason for requiring joint evaluation is that when the transport services are produced and a portion of which are not consumed, the technical effectiveness would be less than the technical efficiency. A case study on 15 bus companies in Taipei is conducted. Results show that the number of efficient companies determined by the proposed models is fewer than that determined by conventional two-stage DEA models. It indicates a superior benchmarking power of the proposed models. Key Words : integrated DEA model, service effectiveness, technical efficiency, technical effectiveness 1. INTRODUCTION Data envelopment analysis (DEA) has been widely used to evaluate the technical efficiency or technical effectiveness of decision making units (DMUs). Numerous applications of DEA can be found in various transport fields, such as airline (e.g. Schefczyk, 1993; Charnes