In the nonparametric data envelopment analysis literature,scale elasticity is evaluated in two alternative ways:using either the technical efficiency model or the cost efficiency model.This evaluation becomes problema...In the nonparametric data envelopment analysis literature,scale elasticity is evaluated in two alternative ways:using either the technical efficiency model or the cost efficiency model.This evaluation becomes problematic in several situations,for example(a)when input proportions change in the long run,(b)when inputs are heterogeneous,and(c)when firms face ex-ante price uncertainty in making their production decisions.To address these situations,a scale elasticity evaluation was performed using a value-based cost efficiency model.However,this alternative value-based scale elasticity evaluation is sensitive to the uncertainty and variability underlying input and output data.Therefore,in this study,we introduce a stochastic cost-efficiency model based on chance-constrained programming to develop a value-based measure of the scale elasticity of firms facing data uncertainty.An illustrative empirical application to the Indian banking industry comprising 71 banks for eight years(1998–2005)was made to compare inferences about their efficiency and scale properties.The key findings are as follows:First,both the deterministic model and our proposed stochastic model yield distinctly different results concerning the efficiency and scale elasticity scores at various tolerance levels of chance constraints.However,both models yield the same results at a tolerance level of 0.5,implying that the deterministic model is a special case of the stochastic model in that it reveals the same efficiency and returns to scale characterizations of banks.Second,the stochastic model generates higher efficiency scores for inefficient banks than its deterministic counterpart.Third,public banks exhibit higher efficiency than private and foreign banks.Finally,public and old private banks mostly exhibit either decreasing or constant returns to scale,whereas foreign and new private banks experience either increasing or decreasing returns to scale.Although the application of our proposed stochastic model is illustrative,it can be potentially applied to all firms in the information and distribution-intensive industry with high fixed costs,which have ample potential for reaping scale and scope benefits.展开更多
Scale management remains the core position in entire development process of the economics and is a major issue of academic research and government concern. Focusing on related problems of agricultural scale management...Scale management remains the core position in entire development process of the economics and is a major issue of academic research and government concern. Focusing on related problems of agricultural scale management,this paper explored 4 aspects of past literature.( i) It defined the agricultural scale management based on economies of scale theory and changes in returns to scale.( ii) From the perspective of the returns to scale of grain production,there are changes in returns to scale of China's grain production,but the measured changes are not significant.( iii) Existing analysis on factors influencing agricultural scale management mainly includes factors influencing farmers' willingness of scale management and restrictive factors of implementation of scale management.( iv) In studies of the relationship between land management scale and production efficiency,many scholars made qualitative and quantitative analysis on land scale efficiency on the basis of economic indicators they defined,but they reached different conclusions. Finally,it summarized literature and pointed out several issues needing special attention in this field.展开更多
This paper gives a dynamic concept and a new non-parametric method for evaluating returns to scale(RTS) of economic units with multiple inputs and outputs.It is frequently noticed that when we increase the input of ...This paper gives a dynamic concept and a new non-parametric method for evaluating returns to scale(RTS) of economic units with multiple inputs and outputs.It is frequently noticed that when we increase the input of a decision making unit(DMU) with a certain status of RTS,different status of RTS is observed.For example,when we increase the input of a DMU with constant RTS under the traditional method,a decreasing RTS is often observed instead of the expected constant RTS.We thus define the RTS of each DMU in both input expansion and contraction regions respectively.The research starts from transferring the production possibility set into the intersection form,by giving the explicit linear inequality representation of production frontiers.The RTS structural characteristics of DMUs' on the production frontier are described.Status of RTS of those DMUs on the production frontier include increasing RTS,constant RTS,decreasing RTS,saturated RTS and evidence of congestion.Necessary and suficient conditions for RTS evaluation are provided.The definition and evaluation method given here provide more detailed economic characteristics of DMU for policy makers.展开更多
Data Envelopment Analysis(DEA) and Ratio Analysis(RA) are two widely used methods for measuring units' productivity and any other criteria that could be assessed based on the available input and output variables....Data Envelopment Analysis(DEA) and Ratio Analysis(RA) are two widely used methods for measuring units' productivity and any other criteria that could be assessed based on the available input and output variables.A number of researchers have studied DEA and RA and noted the positive and negative differences between them.Aggregated ratio analysis(ARA) model,which provide an important linkage between DEA and RA theory,is equivalent to the CCR DEA model,and this equivalence property offers a great deal of opportunities for DEA to be interpreted and applied in different ways.This paper extends the results of ARA model and proposes an extended aggregated ratio analysis(EARA) model,similar as the development from CCR model to BCC model in DEA context.The proposed model can offer an insight into the characteristic of returns to scale,playing the corresponding role as BCC model does.The numerical example is revisited in the paper and the results are compared.展开更多
This studyfirst proposes a definition for directional congestion in certain input and output directions within the framework of data envelopment analysis.Second,two methods from different viewpoints are proposed to es...This studyfirst proposes a definition for directional congestion in certain input and output directions within the framework of data envelopment analysis.Second,two methods from different viewpoints are proposed to estimate the directional congestion.Third,we address the relationship between directional congestion and classic(strong or weak)congestion.Finally,we present a case study investigating the analysis performed by the research institutes of the Chinese Academy of Sciences to demonstrate the applicability and usefulness of the methods developed in this study.展开更多
This paper provides data envelopment analysis methods based on partially ordered set theory.These methods reveal the special relationships between two decision making units from the perspective of mathematical theory ...This paper provides data envelopment analysis methods based on partially ordered set theory.These methods reveal the special relationships between two decision making units from the perspective of mathematical theory and offer the classification,projection and improvement methods of decision making units.It is proved that an efficient decision making unit must be a maximal element of the related poset,and the maximal element may not be efficient.For this,we introduce the concepts of minimum envelope and efficiency envelope which further reveal the special relationship among efficient and inefficient decision making units.Compared with the previous methods,this method not only reveals theoretically the complex relationship among decision making units and the causes of the ineffectiveness,but also gives a new importance and competitiveness measurement method to each decision making unit.Finally,related algorithm and examples are given for the application of these methods to complex decision making problems.展开更多
文摘In the nonparametric data envelopment analysis literature,scale elasticity is evaluated in two alternative ways:using either the technical efficiency model or the cost efficiency model.This evaluation becomes problematic in several situations,for example(a)when input proportions change in the long run,(b)when inputs are heterogeneous,and(c)when firms face ex-ante price uncertainty in making their production decisions.To address these situations,a scale elasticity evaluation was performed using a value-based cost efficiency model.However,this alternative value-based scale elasticity evaluation is sensitive to the uncertainty and variability underlying input and output data.Therefore,in this study,we introduce a stochastic cost-efficiency model based on chance-constrained programming to develop a value-based measure of the scale elasticity of firms facing data uncertainty.An illustrative empirical application to the Indian banking industry comprising 71 banks for eight years(1998–2005)was made to compare inferences about their efficiency and scale properties.The key findings are as follows:First,both the deterministic model and our proposed stochastic model yield distinctly different results concerning the efficiency and scale elasticity scores at various tolerance levels of chance constraints.However,both models yield the same results at a tolerance level of 0.5,implying that the deterministic model is a special case of the stochastic model in that it reveals the same efficiency and returns to scale characterizations of banks.Second,the stochastic model generates higher efficiency scores for inefficient banks than its deterministic counterpart.Third,public banks exhibit higher efficiency than private and foreign banks.Finally,public and old private banks mostly exhibit either decreasing or constant returns to scale,whereas foreign and new private banks experience either increasing or decreasing returns to scale.Although the application of our proposed stochastic model is illustrative,it can be potentially applied to all firms in the information and distribution-intensive industry with high fixed costs,which have ample potential for reaping scale and scope benefits.
基金Supported by Consulting Project of Chinese Academy of Engineering in 2015(2015-XY-22)
文摘Scale management remains the core position in entire development process of the economics and is a major issue of academic research and government concern. Focusing on related problems of agricultural scale management,this paper explored 4 aspects of past literature.( i) It defined the agricultural scale management based on economies of scale theory and changes in returns to scale.( ii) From the perspective of the returns to scale of grain production,there are changes in returns to scale of China's grain production,but the measured changes are not significant.( iii) Existing analysis on factors influencing agricultural scale management mainly includes factors influencing farmers' willingness of scale management and restrictive factors of implementation of scale management.( iv) In studies of the relationship between land management scale and production efficiency,many scholars made qualitative and quantitative analysis on land scale efficiency on the basis of economic indicators they defined,but they reached different conclusions. Finally,it summarized literature and pointed out several issues needing special attention in this field.
基金supported by the National Natural Science Foundation of China (No. 70531040 and 70871114)the 985 Research Grant of Renmin University of Chinasupported by the Hong Kong CERG Research Fund PolyU 5515/10H and PolyU 5485/09H
文摘This paper gives a dynamic concept and a new non-parametric method for evaluating returns to scale(RTS) of economic units with multiple inputs and outputs.It is frequently noticed that when we increase the input of a decision making unit(DMU) with a certain status of RTS,different status of RTS is observed.For example,when we increase the input of a DMU with constant RTS under the traditional method,a decreasing RTS is often observed instead of the expected constant RTS.We thus define the RTS of each DMU in both input expansion and contraction regions respectively.The research starts from transferring the production possibility set into the intersection form,by giving the explicit linear inequality representation of production frontiers.The RTS structural characteristics of DMUs' on the production frontier are described.Status of RTS of those DMUs on the production frontier include increasing RTS,constant RTS,decreasing RTS,saturated RTS and evidence of congestion.Necessary and suficient conditions for RTS evaluation are provided.The definition and evaluation method given here provide more detailed economic characteristics of DMU for policy makers.
基金support by National Natural Science Foundation of P.R.C. (70901069)Ministry of Education Foundation of Humanities and Social Sciences of P.R.C. (10YJC630208)+1 种基金Key Foundation of Natural Science for Colleges and Universities in Anhui, China (KJ2011A001) Social Science Foundation of Anhui, China (AHSK07-08D25, AHSKF09-10D116, AHSK09-10D14)
文摘Data Envelopment Analysis(DEA) and Ratio Analysis(RA) are two widely used methods for measuring units' productivity and any other criteria that could be assessed based on the available input and output variables.A number of researchers have studied DEA and RA and noted the positive and negative differences between them.Aggregated ratio analysis(ARA) model,which provide an important linkage between DEA and RA theory,is equivalent to the CCR DEA model,and this equivalence property offers a great deal of opportunities for DEA to be interpreted and applied in different ways.This paper extends the results of ARA model and proposes an extended aggregated ratio analysis(EARA) model,similar as the development from CCR model to BCC model in DEA context.The proposed model can offer an insight into the characteristic of returns to scale,playing the corresponding role as BCC model does.The numerical example is revisited in the paper and the results are compared.
基金We would like to acknowledge the support of the National Natural Science Foundation of China(NSFC,Nos.71201158,71671181)The other supports of data and related materials from the Institutes of Science and Development,Chinese Academy of Sciences are also acknowledged.
文摘This studyfirst proposes a definition for directional congestion in certain input and output directions within the framework of data envelopment analysis.Second,two methods from different viewpoints are proposed to estimate the directional congestion.Third,we address the relationship between directional congestion and classic(strong or weak)congestion.Finally,we present a case study investigating the analysis performed by the research institutes of the Chinese Academy of Sciences to demonstrate the applicability and usefulness of the methods developed in this study.
基金supported by the National Natural Science Foundation of China under Grant No.71961026the National Natural Science Foundation of Inner Mongolia under Grant No.2019MS07001.
文摘This paper provides data envelopment analysis methods based on partially ordered set theory.These methods reveal the special relationships between two decision making units from the perspective of mathematical theory and offer the classification,projection and improvement methods of decision making units.It is proved that an efficient decision making unit must be a maximal element of the related poset,and the maximal element may not be efficient.For this,we introduce the concepts of minimum envelope and efficiency envelope which further reveal the special relationship among efficient and inefficient decision making units.Compared with the previous methods,this method not only reveals theoretically the complex relationship among decision making units and the causes of the ineffectiveness,but also gives a new importance and competitiveness measurement method to each decision making unit.Finally,related algorithm and examples are given for the application of these methods to complex decision making problems.