DEA-based hypothesis tests for comparing two groups of decision making units

In this paper, we develop five statistical tests to compare the efficiencies of different groups of DMUs. We consider a data generating process (DGP) that models the deviation of the output from the best practice frontier as the sum of two components, a one-sided inefficiency term and a two-sided random noise term. We use simulation to evaluate the performance of the five tests against the Banker tests (Banker, 1993) that were designed for DGPs containing a single one-sided error term. It is found that while the Banker tests are very effective when efficiency dominates noise, the tests developed in this paper perform better than the Banker tests when noise levels are significant.     

A comparative approach to the economic modelling of a large-scale wave power scheme

Conversion of marine energy sources, including ocean waves and tidal currents, into electricity is a rapidly developing industry. Although many technologies have been proposed and some have generated electricity at full scale, it is difficult to predict which technology will be economic at large scales of installation. Several studies have been conducted which estimate the cost of electricity on the basis of schematic designs. However, each study represents a best estimate of the future cost based on current design details and direct comparison between the results of these studies is not straightforward. A methodology for directly comparing different wave energy concepts and potential locations would be beneficial to aid investment decisions. In this study we describe how the established data envelopment analysis technique could be employed for this purpose. The developed model is employed to rank the efficacy with which several types of conceptual and prototype wave energy conversion technologies generate electricity from the wave energy resource available at UK and US sites.     

Performance evaluation of purchasing and supply management using value chain DEA approach

Purchasing and Supply Management (PSM) today is increasingly becoming more important to senior management due to its potential to strategically influence both operational performance as well as financial performance outcomes. However the cross-functional nature of many PSM activities has led to inadequate data collection and performance measurement resulting in weak performance evaluation methodologies and mixed results. We address this gap in the current study, firstly by using an external assessment survey methodology that complements the internal perceptional measures of PSM performance, to collect data for a sample of over 120 firms across the globe with more than 3 billion US dollar turnover, representing seven industry sectors. Next, we develop a comprehensive performance measurement framework using the classical and two-stage Value Chain Data Envelopment Analysis models, which make use of multiple PSM measures at various stages and provide a single efficiency measure that estimates the all-round performance of a PSM function and its contribution to the long term corporate performance in each of these seven industry sectors. The relevance of this measurement methodology is demonstrated through an in-depth analysis of the distribution of efficiencies within and across industry sectors and through the estimation of target PSM performance levels.     

Relating the perspectives of the balanced scorecard for R&D by means of DEA

The objective of this article is to propose a framework for analysis of the relationships between the four perspectives of the balanced scorecard (BSC) of Kaplan and Norton. To this end, several different models of efficiency have been developed, utilising data envelopment analysis (DEA). Each of the variables has been extracted from a model of the BSC for research and development (R&D) activities. A study has been carried out with 90 companies to illustrate a case of this analysis.     

Developing a measure of risk adjusted revenue (RAR) in credit cards market: Implications for customer relationship management

Current models of customer lifetime value (CLV) consider the discounted value of profits that a customer generates over an expected lifetime of relationship with the firm. This practice can be misleading in the financial services markets because it ignores the risk posed by the customer (such as delinquency and default). Specifically, in the credit card market, the correlation between revenue and risk is positive. Therefore, firms need to adjust a customer’s profits for the associated risk before developing a measure of customer lifetime value. We propose a new measure, risk adjusted revenue (RAR), that can incorporate multiple sources of risk and demonstrate the usefulness of the proposed measure in correctly assessing the value of a customer in the credit card market. The model can be extended to compute risk adjusted lifetime value (RALTV). We use the RAR metric to understand the effectiveness of different modes of acquisition, and of retention strategies such as affinity cards and reward cards. We find that both reward- and affinity-cardholders generate higher RAR than non-reward and non-affinity cardholders respectively. The ordering of different modes of acquisition with respect to RAR (in decreasing order) is as follows: Internet, direct mail, telesales, and direct selling.     

A dynamic benchmarking system for assessing the recovery of inpatients: Evidence from the neurorehabilitation process

The shortage of medical resources (mainly beds) is a critical and increasingly prevalent problem affecting hospitals. Of the factors that contribute to these shortages, the ambiguity and insufficiency of the criteria used to identify whether an inpatient should be discharged are among the most detrimental. To address this issue, this study applies data envelopment analysis (DEA) on existing inpatient data from the Neurorehabilitation Center at Toronto’s Bridgepoint Hospital to create a dynamic benchmarking system to evaluate the health stage of an inpatient ready to be discharged. Unlike the more traditional parametric techniques, DEA provides non-subjective benchmarking that does not require any prior specification of the production function making it a more desirable choice for this application. The dynamic model categorizes the inpatient’s discharge status as rejected, under observation, or approved. This new approach not only allows managers to gain insight into the potential causes of medical resource shortages, but also allows clinicians to treat inpatients more effectively based on their discharge categories. For validation, the results of the dynamic model were compared with actual inpatient discharge assessments provided by the Bridgepoint Hospital.     

New approach for the assignment of new European agricultural subsidies using scores from data envelopment analysis: Application to olive-growing farms in Andalusia (Spain)

More than 60% of olive-growing farms in Andalusia (Spain) would have negative returns without European agricultural subsidies. Agenda 2000 criteria imply that agricultural subsidies currently play the role of enhancing the production quality and the environmental and social values of agriculture. Although the necessity of the modulation of subsidies is stated, the EU regulations do not state which objective criteria should be used or how they should be measured, despite the fact that regulations demand objectivity in this measurement.