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Necmi K. Avkiran
Researcher at University of Queensland
Publications - 83
Citations - 4072
Necmi K. Avkiran is an academic researcher from University of Queensland. The author has contributed to research in topics: Data envelopment analysis & Benchmarking. The author has an hindex of 27, co-authored 83 publications receiving 3753 citations.
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Investigating technical and scale efficiencies of australian universities through data envelopment analysis
TL;DR: In this article, the authors used data envelopment analysis (DEA) to examine the relative efficiency of Australian universities and developed three performance models, namely, overall performance, performance on delivery of educational services, and performance on fee-paying enrolments.
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The evidence on efficiency gains: The role of mergers and the benefits to the public
TL;DR: In this article, changes in a bank's market share of deposits are explored as a means of determining the extent to which efficiency gains are passed on to the public, and evidence from the merger cases studied supports the reports of others that acquiring banks are more efficient than target banks.
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Developing an Instrument to Measure Customer Service Quality in Branch Banking
TL;DR: 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 as mentioned in this paper, which addresses the psychometric shortcomings of the existing work in service quality research.
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An application reference for data envelopment analysis in branch banking: helping the novice researcher
TL;DR: In this article, the authors demonstrate the application of data envelopment analysis (DEA) in examining the efficiency of bank branches relative to other branches and demonstrate that accounting variables can be complemented by non-accounting variables controllable by management.
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Association of DEA super-efficiency estimates with financial ratios: Investigating the case for Chinese banks
TL;DR: In this article, the authors investigate to what extent bank DEA super-efficiency estimates are associated with key financial ratios and find that a low correlation may present an opportunity to address inefficiencies that were not obvious in financial ratio analysis, thus enabling an update of inferences drawn from ratios.