Modelling generalized firms' restructuring using inverse DEA

The key consideration for firms’ restructuring is improving their operational efficiencies. Market conditions often offer opportunities or generate threats that can be handled by restructuring scenarios through consolidation, to create synergy, or through split, to create reverse synergy. A generalized restructuring refers to a move in a business market where a homogeneous set of firms, a set of pre-restructuring decision making units (DMUs), proceed with a restructuring to produce a new set of post-restructuring entities in the same market to realize efficiency targets. This paper aims to develop a novel inverse Data Envelopment Analysis based methodology, called GInvDEA (Generalized Inverse DEA), for modeling the generalized restructuring. Moreover, the paper suggests a linear programming model that allows determining the lowest performance levels, measured by efficiency that can be achieved through a given generalized restructuring. An application in banking operations illustrates the theory developed in the paper

Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds

Development and application of the data envelopment analysis (DEA) method, have been the subject of numerous reviews. In this paper, we consider the papers that apply DEA methods specifically to financial services, or which use financial services data to experiment with a newly introduced DEA model. We examine 620 papers published in journals indexed in the Web of Science database, from 1985 to April 2016. We analyse the sample applying citations network analysis. This paper investigates the DEA method and its applications in financial services. We analyse the diffusion of DEA in three sub-samples: (1) banking groups, (2) money market funds, and (3) insurance groups by identifying the main paths, that is, the main flows of the ideas underlying each area of research. This allows us to highlight the main approaches, models and efficiency types used in each research areas. No unique methodological preference emerges within these areas. Innovations in the DEA methodologies (network models, slacks based models, directional distance models and Nash bargaining game) clearly dominate recent research. For each subsample, we describe the geographical distribution of these studies, and provide some basic statistics related to the most active journals and scholars

Bridging radial and non-radial measures of efficiency in DEA

Data envelopment analysis (DEA) has been utilized worldwide for measuring efficiencies of banks, telecommunications, electric utilities and so forth. Yet, the existing models have some well-known shortcomings that limit their usefulness. In DEA we have two fundamental approaches to measuring efficiency with very different characteristics; radial and non-radial. We demonstrate a method for linking these two approaches in a unified framework called Connected-SBM (slacks-based measure). It includes two scalar parameters, and by changing the parameter values we can relocate the analysis anywhere between the radial and the non-radial models. An appropriate choice of these parameters can overcome the key shortcomings inherent in the two approaches, namely, proportionality and mixed patterns of slacks