The aggregate black-box approach of conventional Data Envelopment Analysis (DEA) limits its usefulness in situations where the observation is the result of independent decision making in sub-units (sub-DMUs), sequentially linked through processes or semi-finished products. The situation is...

Conventional data envelopment analysis (DEA) for measuring the relative efficiency of a set of decision-making units (DMUs) requires the observations to have precise values. When observations are imprecise and represented by interval values, the efficiencies are also expected to reflect interval...

Purpose – This paper aims to propose an integration of the analytic hierarchy process (AHP) and data envelopment analysis (DEA) methods in a multiattribute grey relational analysis (GRA) methodology in which the attribute weights are completely unknown and the attribute values take the form of...

A data processing procedure, DEA (Data Envelopment Analysis) is described as as an analytical tool in audit engagement. DEA receives data inputs from from financial statements of a plurality of clients, constructs efficiency frontiers and evaluates relative income efficiencies. DEA can be used...

Effective supply chain management relies on information integration and implementation of best practice techniques across the chain. Supply chains are examples of complex multi-stage systems with temporal and causal interrelations, operating multi-input and multi-output production and services...

The recent years have been extremely difficult for banks. Competition has increased and, in addition, last year the global financial market crisis hit the industry, from which many banks did not recover yet. As a consequence, financial institutions are looking for ways to cut costs and to...

The measurement of corporate performance is central to strategic management research. A common objective of this research is to identify top performers in an industry and their sources of competitive advantage. Despite this focus on best firms and practices, most researchers utilize statistical...

The standard indicators used to compare cross-country innovation are in the Global Competitiveness Report (GCR). But there are problems with aggregation and response bias with these largely self-reported measures (Hollanders and van Cruysen, 2008). We propose a theory-based metric using Data...

Some models are presented in this paper which extend the concept of measuring superefficiency to the useful case of variable returns-to-scales (VRS), thus enabling the ranking of efficient as well as inefficient units. Two models, namely the Universal Radial Model and the Universal Additive...