The productivity change of a decision making unit (DMU) between two time periods can be evaluated by the Malmquist productivity index. In this study, we propose a method to compute the Malmquist productivity index in several time periods (from the first to the last periods) on interval data in data envelopment analysis (DEA). Then, the obtained Malmquist productivity index is compared with Malm...

One of the most popular approaches to measuring productivity changes is based on using Malmquist productivity indexes. In this paper we propose a method for obtaining interval Malmquist productivity index (IMPI). The classical DEA models have been before used for measuring the Malmquist productivity index. The current article extends DEA models for measuring the interval Malmquist productivity ...

The circle-type or global Malmquist index, which is based on Data Envelopment Analysis (DEA) models, is an important index that is widely used for measuring the relative productivity change of decisionmaking units (DMUs) in multiple time periods. This index, similar to the standard approach of measuring the productivity change using the standard Malmquist index, breaks down into various compone...

The Malmquist Index methodology is widely used in production economics for measuring the productivity changes of a set of decision making units (DMUs) within different time periods. Moreover, it is quite usual in the management literature to compare public and private DMU performance operating under the same economic sector. However, the standard Malmquist index needs a panel database to be imp...

The Malmquist index (MI) has demonstrated its usefulness in comparing the performances of Decision Making Units (DMUs) performances. global MI (GMI) been suggested as a means to overcome three drawbacks MI: non-circularity, disparate measurements, and infeasibility. Recently, it appeared that can also be used compare groups DMUs. While this new function increased usefulness, presents same MI. I...

Data envelopment analysis (DEA) models have been used in formulating the Malmquist index to measure productivity change over time periods. In this article, we question the validity of this index in the presence of input/output slacks that appear in DEA models used. We demonstrate with an application to banking that Malmquist index loses its meaning whenever slacks are present. As a corrective m...

window analysis is a known technique to evaluate performance during the time periods based on data envelopment analysis. in application of window analysis is assumed that efficient frontier have not changed during the periods in the study. unlike the window analysis, malmquist index tries to identify difference between efficient frontiers and separated them. but the means of different frontier ...

Under the concept of metafrontier, technology gap ratio is alternatively interpreted as potential energy efficiency. Combined with Malmquist index framework and Shephard energy distance function, we then develop a metafrontier Malmquist energy productivity index to analyze the total-factor energy productivity growth with four specific components: groupfrontier efficiency change index, groupfron...

The Malmquist productivity index evaluates the productivity change of a decision making unit (DMU) between two time periods. In this current study, a method is proposed to compute the Malmquist productivity index in several time periods (from the first to the last periods) in data envelopment analysis (DEA) and then, the obtained Malmquist productivity index is compared with Malmquist produ...

This paper decomposes the Malmquist productivity index into several assembling components: technical change (further break down into technical change magnitude, input bias and output bias), technical efficiency change, scale efficiency change, and output-mix effect. A translog output distance function is chosen to represent the production technology and each component of the Malmquist index is ...