Necmi K. Avkiran

Investigating technical and scale efficiencies of Australian universities through data envelopment analysis

Performance indicators in the public sector have often been criticised for being inadequate and not conducive to analysing efficiency. The main objective of this study is to use data envelopment analysis (DEA) to examine the relative efficiency of Australian universities. Three performance models are developed, namely, overall performance, performance on delivery of educational services, and performance on fee-paying enrolments. The findings based on 1995 data show that the university sector was performing well on technical and scale efficiency but there was room for improving performance on fee-paying enrolments. There were also small slacks in input utilisation. More universities were operating at decreasing returns to scale, indicating a potential to downsize. DEA helps in identifying the reference sets for inefficient institutions and objectively determines productivity improvements. As such, it can be a valuable benchmarking tool for educational administrators and assist in more efficient allocation of scarce resources. In the absence of market mechanisms to price educational outputs, which renders traditional production or cost functions inappropriate, universities are particularly obliged to seek alternative efficiency analysis methods such as DEA.

The evidence on efficiency gains: The role of mergers and the benefits to the public

Operating efficiencies, employee productivity, profit performance and average relative efficiency (using Data Envelopment Analysis) were measured for Australian trading banks from 1986 to 1995. Changes in a bank’s market share of deposits is explored as a means of determining the extent to which efficiency gains are passed on to the public. In general, efficiencies rose in the post-deregulation period. Evidence from the merger cases studied supports the reports of others that acquiring banks are more efficient than target banks. However, the acquiring bank does not always maintain its pre-merger efficiency. Decision-makers ought to be more cautious in promoting mergers as a means to enjoying efficiency gains. There is mixed evidence on the extent to which the benefits of efficiency gains are passed on to the public.

Developing an Instrument to Measure Customer Service Quality in Branch Banking

A 17‐item scale emerges following the study to develop an instrument for measuring customer service quality at trading bank branches, with a focus on retail banking. The conceptual framework addresses the psychometric shortcomings of the existing work in service quality research. A robust research design takes the study through multiple stages of development where the construct is pretested and piloted; in the main survey stage, data collection methods are triangulated, returning 791 completed questionnaires. Analysis of instrument reliability, dimensionality and validity present gratifying results; for example, scale alpha is recorded at 0.9249. The instrument can be applied as part of branch performance measurement, as well as help diagnose problems in delivery of service, and segment the bank′s customer base for healthier decision making in marketing.

An application reference for data envelopment analysis in branch banking: helping the novice researcher

Demonstrates the application of data envelopment analysis (DEA) in examining the efficiency of bank branches relative to other branches. Shows that accounting variables can be complemented by non‐accounting variables controllable by management. The process of generating and interpreting relative efficiency scores and potential improvements is discussed in a language that will be particularly appreciated by managers, consultants and novice researchers. The theory needed to use DEA and the key model design considerations are addressed. The discussion includes such issues as appropriate sample size, strengths and weaknesses of DEA, analysis options, and an application checklist. DEA can be applied to benchmarking best practice branches. Management can use DEA to test the established knowledge of branches and initiate investigations when contradictions arise.

Rising productivity of Australian trading banks under deregulation 1986–1995

Productivity of four major trading banks and six regional banks is investigated using Malmquist productivity indices in the deregulated period 1986–1995. The principal findings indicate an overall rise in total productivity driven more by technological progress than technical efficiency. Performance of major trading banks on technical efficiency is similar to that of regional banks but higher on technological progress. Distinguishing between improvement in technical efficiency and technological change is significant for policy formulation. Technological innovation can be construed as a sign of dynamic efficiency where banks take advantage of new cost-effective technologies and pursue product and market development.

Quality customer service demands human contact

Investigates the interrelationships between the factors comprising the bank customer service quality construct through path analysis. Credibility is modelled as an outcome of the causal variables staff conduct, access to teller services and communication. Staff conduct emerges as the key variable explaining the direct and indirect linkages between the causal variables and the outcome variable. Those advocating high‐technology solutions as substitutes for branch staff may be ignoring the essence of high customer service quality which involves staff‐customer contact. It is necessary to provide adequate staff numbers to serve customers and train staff to be responsive and professional in their conduct. Structural equations and OLS regression were used to decompose zero‐order bivariate correlations into direct, indirect and spurious effects in the path model. Internal reliability coefficients for the four factors and instrument reliability are also calculated with gratifying results.

Scientific collaboration in finance does not lead to better quality research

The study reports an empirical comparison of quality of collaborative research with the quality of individual research. Quality of a paper is measured by the citation rate over the four years following the year of publication. Papers published in fourteen Finance journals between 1987–1991 are sampled. There is no significant difference between the quality of collaborative and individual research. Decision-makers should hesitate in interpreting collaborative research as a definitive sign of ability to produce better research.

Sensitivity analysis of network DEA: NSBM versus NRAM

Abstract Users of data envelopment analysis (DEA) often presume efficiency estimates to be robust. While traditional DEA has been exposed to various sensitivity studies, network DEA has so far escaped similar scrutiny. Thus, there is a need to investigate the sensitivity of efficiency estimates, further compounded by the recent attention network DEA has been receiving in literature. We compare network slacks-based measure (NSBM) with network range-adjusted measure (NRAM), where the latter is developed for the first time. Following various data perturbations overall findings indicate positive and significant rank correlations when new results are compared against baseline results – suggesting resilience. Key findings show that, (a) as in traditional DEA, greater sample size brings greater discrimination, (b) removing a relevant input improves discrimination, (c) introducing an extraneous input leads to a moderate loss of discrimination, (d) simultaneously adjusting data in opposite directions for inefficient versus efficient branches shows a mostly stable estimates, (e) swapping divisional weights produces a substantial drop in discrimination, (f) stacking perturbations has the greatest impact on efficiency estimates with substantial loss of discrimination, and (g) layering suggests that the core inefficient cohort is resilient against omission of benchmark branches. Further insight gained by comparing NSBM with NRAM includes: (h) identical benchmark groups across both formulations, (i) a narrower range of efficiency estimates and a more stable mean across different sample sizes under NRAM, (j) distribution of NRAM efficiency estimates is negatively skewed whereas NSBM estimates are mostly positively skewed, and (k) there is no evidence of inefficient unit size bias among NRAM estimates, whereas larger inefficient units appear more inefficient under NSBM.

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.

Models of retail performance for bank branches: predicting the level of key business drivers

Details the process whereby multivariate interdisciplinary measures of potential to perform are integrated with performance measures to develop models of retail performance for bank branches. The predictive models use the key business drivers of a major trading bank as dependent variables. Independent variables explaining business drivers are the theorized potential variables that measure the capacity to generate retail business. The models allow a comparison between the predicted and actual levels of key business diverts, thus measuring unrealized performance. Findings can assist decision making during restructuring, branch closures or downsizing. The variables presented should be regarded as examples rather than universally accepted measures of branch performance.