Proposing a Network Data Envelopment Analysis (NDEA) Model for Evaluating Information Efficiency of Reporting Entities

The research objective is to develop a model for evaluating information quality of reporting entities using network data envelopment analysis (NDEA) models. The main motivation is the multidimensional feature of information quality concept with respect to the proxies and consequences of information quality along with the capabilities of DEA models in evaluating efficiency of decision-making units (DMUs: here the reporting entities) based on different inputs and outputs. In this regard, firstly the most important proxies and consequences of information quality are extracted from literature review and secondly considered as inputs and outputs of consequential two-stage NDEA model depending on their relationships with information quality concept and finally the information efficiency of reporting entities measured using simultaneously the proxies and consequences of information quality. The results revealed differences in DMUs' information efficiencies in different stages suggesting classic viewpoint deficiency of DEA models in evaluating DMUs' efficiency. Moreover, DMUs' efficiencies in first stage (proxies of information quality) are greater than their corresponding efficiencies in second stage (transforming proxies to consequences) and network efficiencies, resulted from optimization of all distinct stages, take an amount between first- and second-stage efficiencies. Among other results of the research in addition to providing a unique amount of network efficiency, is giving explanations for network and its components inefficiency, and identifying benchmarks for optimizations of inputs and outputs of each stage and overall network and setting a way to efficient frontier.