We propose a dynamic DEA model involving network structure in each period within the framework of a slacks-based measure approach. We have previously published the network SBM (NSBM) and the dynamic SBM (DSBM) models separately. Hence, this article is a composite of these two models. Vertically, we deal with multiple divisions connected by links of network structure within each period and, hori...

Along with the reform in electric power market and the establishment of bidding for access mechanism, the competition among the power generation enterprises is more intense. As a kind of renewable clean energy, wind power has the disadvantages of no pollution, low cost, but the wind power also has the inherent shortcoming of intermittence, random and instability. To evaluate the core competitiv...

data envelopment analysis (dea) is a technique that uses all collected observations to measure performance. this method presents no data about how to operate on dmu. the present research attempted to study a unit with all its subunits, if the unit is efficient, it means that all its subunits are efficient too and if it is an inefficient, it shows clearly that which one of the subunits makes ine...

Supply chain performance evaluation problems are complex problems with multiple criteria and multi-layered internal linking activities. Data Envelopment Analysis (DEA) has been used to evaluate the relative performance of organizational units called Decision Making Units (DMUs). However, the conventional DEA models cannot take into account the complex nature of supply chains with internal linki...

We developed an alternative approach for measuring information and communication technology (ICT), applying Data Envelopment Analysis (DEA) using data from the International Telecommunications Union as a sample of 183 economies. We compared the ICT-Opportunity Index (ICT-OI) with our DEAOpportunity Index (DEA-OI) and found a high correlation between the two. Our findings suggest that both indic...

Conventional data envelopment analysis (DEA) assists decision makers in distinguishing between efficient and inefficient decision making units (DMUs) in a homogeneous group. However, DEA does not provide more information about efficient units. Super-efficiency DEA models can be used in ranking the performance of efficient DMUs. This research proposes a methodology to determine an Euclidean dist...

Due to various seasonal and monthly changes in electricity consumption and difficulties in modeling it with the conventional methods, a novel algorithm is proposed in this paper. This study presents an approach that uses Artificial Neural Network (ANN), Principal Component Analysis (PCA), Data Envelopment Analysis (DEA) and ANOVA methods to estimate and predict electricity demand for seasonal a...

The variable returns to scale data envelopment analysis (DEA) model is developed with a maintained hypothesis of convexity in input-output space. This hypothesis is not consistent with standard microeconomic production theory that posits an S-shape for the production frontier, i.e. for production technologies that obey the Regular Ultra Passum Law. Consequently, measures of technical efficiency...

In the existing DEA models, we have a centralized decision maker (DM) who supervises all the operating units. In this paper, we solve a problem in which the centralized DM encounters limited or constant resources for total inputs or total outputs. We establish a DEA target model that solves and deals with such a situation. In our model, we consider the decrease of total input consumption and th...