Data envelopment analysis (DEA) is a representative method to estimate efficient frontiers and derive efficiency. However, in a situation with weight restrictions on individual input–output pairs, its suitability has been questioned. Therefore, the main purpose of this paper is to develop a mathematical method, which we call the input-oriented ratio-based comparative efficiency model, DEA-R-I, ...

In the data envelopment analysis (DEA) literature, linear fractional non-cooperative network DEA models for two-stage network structures are often transformed into parametric linear models. The transformed parametric linear models are then solved by computing a series of linear models when the parameter is varied. For example, Wu, Zhu, Ji, Chu and Liang (2016) provide a linear fractional non-co...

Airport efficiency is an area of increasing interest to academics, policy makers and practitioners. This has resulted in a body of literature applying various econometric techniques to compare efficiency between different samples of airports. This paper uses the multi-criteria decision making method Analytic Hierarchy Process (AHP) to incorporate the weightings of input and output variables int...

Airport efficiency is an area of increasing interest to academics, policy makers and practitioners. This has resulted in a body of literature applying various econometric techniques to compare efficiency between different samples of airports. This paper uses the multi-criteria decision making method Analytic Hierarchy Process (AHP) to incorporate the weightings of input and output variables int...

Abstract Data Envelopment Analysis (DEA) is a method for measuring efficiencies of Decision Making Units (DMUs). While it has been widely used in many industrial and economic applications, for large DMUs with many inputs and outputs, DEA would require huge computer resources in terms of memory and CPU time. Several studies have attempted to overcome this problem for large datasets. However, the...

The paper deals with models and methods for evaluation of efficiency of production units. The standard modeling approach for evaluation of efficiency is data envelopment analysis (DEA) based on the definition of efficiency as the ratio of outputs produced by the unit and inputs spent in the production process. Standard data envelopment analysis models divide the units into inefficient and effic...

Standard Data Envelopment Analysis (DEA) is characterized by uniform proportional input reduction or output augmentation in calculating improvement projections. This paper develops a new Euclidean Distance Minimization model in the context of DEA in order to derive a more appropriate efficiency-improving projection model by means of a weighted projection function. The model is extended to the s...

It has been shown in prior work in management science, statistics and machine learning that using an ensemble of models often results in better performance than using a single ‘best’ model. This paper proposes a novel Data Envelopment Analysis (DEA) based approach to combine models. We prove that for the 2-class classification problems, DEA models identify the same convex hull as the popular RO...

The proposal of the Belt and Road Initiative (BRI) has had a profound impact on development construction industry. Based panel data from 2014 to 2020 in 18 China's provinces along Road, we combined envelopment analysis (DEA) with Malmquist productivity index (MPI) model analyze static production efficiency industry these changes 2020. results show that China’s is relatively high, nearly half ar...