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1 – 10 of 182Qingxian An, Zhaokun Cheng, Shasha Shi and Fenfen Li
Environmental performance becomes a key issue for the sustainable development. Recently, incremental information technology is adopted to collect environmental data and improve…
Abstract
Purpose
Environmental performance becomes a key issue for the sustainable development. Recently, incremental information technology is adopted to collect environmental data and improve environmental performance. Previous environmental efficiency measures mainly focus on individual decision-making units (DMUs). Benefited from the information technology, this paper develops a new environmental efficiency measure to explore the implicit alliances among DMUs and applies it to Xiangjiang River.
Design/methodology/approach
This study formulates a new data envelopment analysis (DEA) environmental cross-efficiency measure that considers DMUs' alliances. Each DMUs' alliance is formulated by the DMUs who are supervised by the same manager. In cross-efficiency evaluation context, this paper adopts DMUs' alliances rather than individual DMUs to derive the environmental cross-efficiency measure considering undesirable outputs. Furthermore, the Tobit regression is conducted to analyze the influence of exogenous factors about the environmental cross-efficiency.
Findings
The findings show that (1) Chenzhou performs the best while Xiangtan performed the worst along Xiangjiang River. (2) The environmental efficiency of cities in Xiangjiang River is generally low. Increasing public budgetary expenditure can improve environmental efficiency of cities. (3) The larger the alliance size, the higher environmental efficiency. (4) The income level is negatively correlated with environmental efficiency, indicating that the economy is at the expense of the environment in Xiangjiang River.
Originality/value
This paper contributes to developing a new environmental DEA cross-efficiency measure considering DMUs' alliance, and combining DEA cross-efficiency and Tobit regression in environmental performance measurement of Xiangjiang River. This paper examines the exogenous factors that have influences on environmental efficiency of Xiangjiang River and derive policy implications to improve the sustainable operation.
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This paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking decision-making…
Abstract
Purpose
This paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking decision-making units (DMUs) based on cross-efficiency technique and subjective preference(s) of the decision maker.
Design/methodology/approach
Self-evaluation in data envelopment analysis (DEA) lacks in discrimination power among DMUs. To fix this, a cross-efficiency technique has been introduced that ranks DMUs based on peer-evaluation. Different cross-efficiency formulations such as aggressive and benevolent and neutral are available in the literature. The existing ranking approaches fail to incorporate subjective preference of “one” or “some” or “all” or “most” of the cross-efficiency evaluation formulations. Therefore, the integrated framework in this paper, based on DEA and multicriteria decision-making (MCDM), aims to present a ranking approach to incorporate different cross-efficiency formulations as well as subjective preference(s) of decision maker.
Findings
The proposed approach has an advantage that each of the aggressive, benevolent and neutral cross-efficiency formulations contribute to select the best alternative among the DMUs in a MCDM problem. Ordered weighted averaging (OWA) aggregation is applied to aggregate final cross-efficiencies and to achieve complete ranking of the DMUs. This new approach is further illustrated and compared with existing MCDM approaches like simple additive weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prove its validity in real situations.
Research limitations/implications
The choice of cross-efficiency formulation(s) as per subjective preference of the decision maker and different orness levels lead to different aggregated scores and thus ranking of the DMUs accordingly. The proposed ranking approach is highly useful in real applications like R and D projects, flexible manufacturing systems, electricity distribution sector, banking industry, labor assignment and the economic environmental performances for ranking and benchmarking.
Practical implications
To prove the practical applicability and robustness of the proposed integrated DEA-MCDM approach, it is applied to top twelve Indian banks in terms of three inputs and two outputs for the period 2018–2019. The findings of the study (1) ensure the impact of non-performing assets (NPAs) on the ranking of the selected banks and (2) are enormously valuable for the bank experts and policy makers to consider the impact of peer-evaluation and subjective preference(s) in formulating appropriate policies to improve performance and ranks of underperformed banks in competitive scenario.
Originality/value
To the best of the authors’ knowledge, this is the first study that has integrated both DEA and MCDM via OWA aggregation to present a ranking approach that can incorporate different cross-efficiency formulations and subjective preference(s) of the decision maker for ranking DMUs.
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Li-Huan Liao, Lei Chen and Yu Chang
Safety efficiency is the key to balance safety and production in construction industry; but the existing safety efficiency evaluation methods have the limitations of…
Abstract
Purpose
Safety efficiency is the key to balance safety and production in construction industry; but the existing safety efficiency evaluation methods have the limitations of overestimating efficiency and ignoring undesirable outputs; therefore, according to the characteristics of safety production in construction industry, this paper innovatively develops a new cross-efficiency data envelopment analysis method to analyze safety efficiency, which can solve the limitations of traditional methods; and then the safety efficiency and its influencing factors of China's construction industry are analyzed, and some useful conclusions are obtained to improve its safety efficiency.
Design/methodology/approach
A new cross-efficiency data envelopment analysis method with undesirable outputs is proposed; and the two-stage efficiency analysis framework is designed.
Findings
First, the construction industries in different areas have different reasons for affecting their safety efficiency; second, the evaluation results of global safety priority tend to be more acceptable; third, frequent safety accidents and low resource utilization lead to a slow downward trend of the safety efficiency of China's construction industry in the long run; fourth, construction engineering supervision, construction industrial scale, and construction industrial structure have the significant impact on safety efficiency.
Originality/value
Theoretically, a new cross-efficiency data envelopment analysis method with undesirable outputs is proposed for evaluating safety efficiency; practically, the safety efficiency and its influencing factors of China's construction industry are analyzed.
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Abdollah Noorizadeh, Mahdi Mahdiloo and Reza Farzipoor Saen
The purpose of this paper is to propose a data envelopment analysis (DEA) method for customers' evaluation.
Abstract
Purpose
The purpose of this paper is to propose a data envelopment analysis (DEA) method for customers' evaluation.
Design/methodology/approach
This paper introduces a variable return to scale (VRS) cross‐efficiency (one of the DEA models) to evaluate customers. This new model can consider ratio values and give a complete ranking of customers.
Findings
It is found that the proposed model can evaluate customers in a multi criteria context; does not demand weights from the decision maker; and can consider both the ratio and absolute numbers. An aggressive form of the VRS model is formulated to evaluate the peer‐appraisal value of customers instead of self‐appraisal.
Originality/value
To the best of the authors' knowledge, there is no reference that uses cross‐efficiency model with the ratio values for customers' evaluation.
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Jianhua Zhu, Luxin Wan, Huijuan Zhao, Longzhen Yu and Siyu Xiao
The purpose of this paper is to provide scientific guidance for the integration of industrialization and information (TIOII). In recent years, TIOII has promoted the development…
Abstract
Purpose
The purpose of this paper is to provide scientific guidance for the integration of industrialization and information (TIOII). In recent years, TIOII has promoted the development of intelligent manufacturing in China. However, many enterprises blindly invest in TIOII, which affects their normal production and operation.
Design/methodology/approach
This study establishes an efficiency evaluation model for TIOII. In this paper, entropy analytic hierarchy process (AHP) constraint cone and cross-efficiency are added based on traditional data envelopment analysis (DEA) model, and entropy AHP–cross-efficiency DEA model is proposed. Then, statistical analysis is carried out on the integration efficiency of enterprises in Guangzhou using cross-sectional data, and the traditional DEA model and entropy AHP–cross-efficiency DEA model are used to analyze the integration efficiency of enterprises.
Findings
The data show that the efficiency of enterprise integration is at a medium level in Guangzhou. The efficiency of enterprise integration has no significant relationship with enterprise size and production type but has a low negative correlation with the development level of enterprise integration. In addition, the improved DEA model can better reflect the real integration efficiency of enterprises and obtain complete ranking results.
Originality/value
By adding the entropy AHP constraint cone and cross-efficiency, the traditional DEA model is improved. The improved DEA model can better reflect the real efficiency of TIOII and obtain complete ranking results.
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The purpose of this paper is to propose a methodological framework that combines several data envelopment analysis (DEA) models to deal with the problem of evaluating and ranking…
Abstract
Purpose
The purpose of this paper is to propose a methodological framework that combines several data envelopment analysis (DEA) models to deal with the problem of evaluating and ranking advanced manufacturing technologies (AMTs) without introducing any subjectivity in the analysis.
Design/methodology/approach
The methodology follows a two-phase procedure. First, the relative efficiency of every technology is calculated by implementing different DEA cross-efficiency models generating the same number of high-order indicators as efficiency vectors. Second, high-order indicators are used as outputs in a SBM-DEA super-efficiency model to obtain a comprehensive DEA-like composite indicator.
Findings
The framework is implemented to evaluate a sample of flexible manufacturing systems. Comparing it to other methods, results show that the methodology provides reliable information for AMTs selection and effective support to management decision-making.
Originality/value
This paper contributes to the body of knowledge about the utilization of DEA to select AMTs. The framework has several advantages: a discriminating power higher than the basic DEA models; no subjective judgment relative to weights necessary to aggregate single indicators and choice of aggregation function; no need to perform any transformation normalizing original data; independence from the unit of measurement of the DEA-like composite indicator; and great flexibility and adaptability allowing the introduction of further variables in the analysis.
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Wenjun Jiang, Shuli Liu and Susan Li
Green economy and economic development with high quality have set higher requirements for the development of the urban logistics industry. It can grasp the recent development…
Abstract
Purpose
Green economy and economic development with high quality have set higher requirements for the development of the urban logistics industry. It can grasp the recent development level of the urban logistics industry by measuring its environmental efficiency to guide its future development direction. The purpose of this study is to improve the environmental efficiency and development level of the urban logistics industry by using a reasonable evaluation method.
Design/methodology/approach
This paper uses information entropy to directly aggregate index weights from different models to acquire comprehensive index weights (CIWs) for calculating peer-evaluation efficiency. Then, we weight self and peer-efficiencies to obtain final efficiency. The environmental efficiencies of the urban logistics industry in Anhui Province in 2019 are obtained according to the above method.
Findings
Several findings are summarized below. The logistics industry in Anhui is in urgent need of improving environmental efficiency. The environmental efficiency of the logistics industry in North Anhui is the highest one, showing that the logistics industry in North Anhui has achieved a relative balance between economic development and environmental protection. Their final cross-efficiency values based on the CIWs are smaller than those based on the comprehensive efficiency. And the environmental efficiency of almost all urban logistics industries is lower than its economic efficiency. The findings show that the proposed method is feasible and more reasonable. More economic implications and suggestions are proposed.
Originality/value
This paper proposes an extended cross-efficiency evaluation method based on information entropy to measure the environmental efficiency of the urban logistics industry, effectively avoiding the overestimation of efficiency results.
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Marcello Braglia and Alberto Petroni
In an era of global sourcing, the firm’s success often hinges on the most appropriate selection of its suppliers. Supplier selection is sometimes very complicated, owing to a…
Abstract
In an era of global sourcing, the firm’s success often hinges on the most appropriate selection of its suppliers. Supplier selection is sometimes very complicated, owing to a variety of uncontrollable and unpredictable factors which affect the decision. Describes a multiple attribute utility theory based on the use of data envelopment analysis (DEA), aimed at helping purchasing managers to formulate viable sourcing strategies in the changing market place. An application of the methodology using actual data retrieved from a firm operating in the bottling industry is illustrated. DEA has proved to be capable of handling multiple conflicting attributes inherent in supplier selection while simultaneously trading‐off key supplier selection criteria.
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The traditional data envelopment analysis (DEA) model as a non-parametric technique can measure the relative efficiencies of a decision-making units (DMUs) set with exact values…
Abstract
Purpose
The traditional data envelopment analysis (DEA) model as a non-parametric technique can measure the relative efficiencies of a decision-making units (DMUs) set with exact values of inputs and outputs, but it cannot handle the imprecise data. The purpose of this paper is to establish a super efficiency interval data envelopment analysis (IDEA) model, an IDEA model based on cross-evaluation and a cross evaluation-based measure of super efficiency IDEA model. And the authors apply the proposed approach to data on the 29 public secondary schools in Greece, and further demonstrate the feasibility of the proposed approach.
Design/methodology/approach
In this paper, based on the IDEA model, the authors propose an improved version of establishing a super efficiency IDEA model, an IDEA model based on cross-evaluation, and then present a cross evaluation-based measure of super efficiency IDEA model by combining the super efficiency method with cross-evaluation. The proposed model cannot only discriminate the performance of efficient DMUs from inefficient ones, but also can distinguish between the efficient DMUs. By using the proposed approach, the overall performance of all DMUs with interval data can be fully ranked.
Findings
A numerical example is presented to illustrate the application of the proposed methodology. The result shows that the proposed approach is an effective and practical method to measure the efficiency of the DMUs with imprecise data.
Practical implications
The proposed model can avoid the fact that the original DEA model can only distinguish the performance of efficient DMUs from inefficient ones, but cannot discriminate between the efficient DMUs.
Originality/value
This paper introduces the effective method to obtain the complete rank of all DMUs with interval data.
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Rodrigo Restrepo and Juan G. Villegas
The purpose of this paper is to present a case study in which data envelopment analysis (DEA) is used to evaluate and classify the suppliers of a Colombian motorcycle assembly…
Abstract
Purpose
The purpose of this paper is to present a case study in which data envelopment analysis (DEA) is used to evaluate and classify the suppliers of a Colombian motorcycle assembly company. This tool allows the integration of several attributes into single performance measures (cross-efficiency and diversity efficiency) and subsequent classification based on the values obtained for these two metrics.
Design/methodology/approach
The classification uses a methodology based on two main tools. The first is an input-oriented cross-efficiency DEA model with ordinal variables to evaluate the suppliers’ performance, and the second is a classification of these into categories that identifies those with good performance for features that make them outstanding.
Findings
The assembly company segments its suppliers according to supply frequency. The results show that suppliers working under a just-in-time system achieve superior performance with respect to other suppliers.
Practical implications
The application of this methodology in a real-world case illustrates how DEA can be a useful tool to support the evaluation and classification of suppliers (a process of increasing complexity given the current trend to include multiple strategic measures together with classical operational measures). Moreover, the methodology illustrated in the study can be adapted to other similar settings.
Originality/value
The main contributions of this paper are twofold. First, to the best of our knowledge, this is the first study to illustrate the use of DEA in a real case related to supplier evaluation. Second, the presence of ordinal variables (e.g. quality or environmental ratings) gives rise to DEA variants seldom used in this context.
Propósito
Este artículo presenta un caso de estudio en el que se utiliza análisis envolvente de datos (DEA) para evaluar y clasificar los proveedores de una ensambladora colombiana de motocicletas. Dicha herramienta permite integrar múltiples atributos en dos medidas de desempeño (eficiencia cruzada y de diversidad) y la posterior clasificación de éstos con base en los valores obtenidos para ambas medidas.
Diseño/metodología/enfoque
La clasificación usa una metodología basada en dos herramientas. La primera es un modelo DEA de eficiencia cruzada orientado a las entradas con variables ordinales que se usa para evaluar el desempeño de los proveedores. La segunda es una clasificación de los proveedores en categorías para identificar aquellos con buen desempeño en algunas características que los hacen sobresalientes.
Resultados
La compañía segmenta sus proveedores de acuerdo con la frecuencia de abastecimiento. Los resultados muestran que los proveedores que operan bajo justo a tiempo (Just-in-time, JIT) tienen un desempeño superior con respecto a los demás proveedores.
Implicaciones prácticas
La aplicación de esta metodología en un caso real ilustra como DEA es una herramienta útil para apoyar la evaluación y clasificación de proveedores (un proceso de complejidad creciente gracias a la tendencia actual de incluir medidas estratégicas junto a las medidas operacionales comúnmente utilizadas). Además, la metodología utilizada puede adaptarse fácilmente a otras situaciones similares.
Originalidad/valor
Las contribuciones de este artículo son dos. Primero, hasta donde sabemos, este es el primer estudio que ilustra el uso de DEA en un caso real de evaluación de proveedores. Segundo, la presencia de variables ordinales (por ejemplo, evaluaciones de calidad y medioambiente) resultan en modelos DEA que son poco utilizados en este contexto.
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