A spatiotemporal Data Envelopment Analysis (S-T DEA) approach:the need to assess evolving units

One of the major challenges in measuring efficiency in terms of resources and outcomes is the assessment of the evolution of units over time. Although Data Envelopment Analysis (DEA) has been applied for time series datasets, DEA models, by construction, form the reference set for inefficient units (lambda values) based on their distance from the efficient frontier, that is, in a spatial manner. However, when dealing with temporal datasets, the proximity in time between units should also be taken into account, since it reflects the structural resemblance among time periods of a unit that evolves. In this paper, we propose a two-stage spatiotemporal DEA approach, which captures both the spatial and temporal dimension through a multi-objective programming model. In the first stage, DEA is solved iteratively extracting for each unit only previous DMUs as peers in its reference set. In the second stage, the lambda values derived from the first stage are fed to a Multiobjective Mixed Integer Linear Programming model, which filters peers in the reference set based on weights assigned to the spatial and temporal dimension. The approach is demonstrated on a real-world example drawn from software development

An empirical investigation of the influence of collaboration in Finance on article impact

We investigate the impact of collaborative research in academic Finance literature to find out whether and to what extent collaboration leads to higher impact articles (6,667 articles across 2001-2007 extracted from the Web of Science). Using the top 5 % as ranked by the 4-year citation counts following publication, we also follow related secondary research questions such as the relationships between article impact and author impact; collaboration and average author impact of an article; and, the nature of geographic collaboration. Key findings indicate: collaboration does lead to articles of higher impact but there is no significant marginal value for collaboration beyond three authors; high impact articles are not monopolized by high impact authors; collaboration and the average author impact of high-impact articles are positively associated, where collaborative articles have a higher mean author impact in comparison to single-author articles; and collaboration among the authors of high impact articles is mostly cross-institutional

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

The importance of service quality in British Muslim’s choice of an Islamic or non-Islamic bank account

Using an extended SERVQUAL model, this study identifies and compares the importance of service quality to Muslim consumers with an Islamic or non-Islamic bank account in a non-Muslim country, Britain. Eight group discussions and survey with 300 Muslims were conducted. Five dimensions of service quality were identified, i.e. Responsiveness, Credibility, Islamic Tangibles, Accessibility and Reputation. These differ in structure and content from the original SERVQUAL developed in the west and the subsequent CARTER model constructed in a Muslim country. In addition, significant differences were found in the importance rating of items by respondents holding an account with an Islamic bank compared to those with a non-Islamic bank account. This study is one of the first to identify and compare the importance of service quality between Islamic and non-Islamic bank account holders in a western non-Muslim country. The results advance our understanding of the impact of culture on SERVQUAL. The study provides insight into Muslims’ bank choice and helps bank managers of both Islamic and non-Islamic banks to focus their attention on the service quality dimensions that matter most to Muslim customers

Long term productivity and collaboration in information science

This is an accepted manuscript of an article published by Springer in Scientometrics on 02/07/2016, available online: https://doi.org/10.1007/s11192-016-2061-8 The accepted version of the publication may differ from the final published version.Funding bodies have tended to encourage collaborative research because it is generally more highly cited than sole author research. But higher mean citation for collaborative articles does not imply collaborative researchers are in general more research productive. This article assesses the extent to which research productivity varies with the number of collaborative partners for long term researchers within three Web of Science subject areas: Information Science & Library Science, Communication and Medical Informatics. When using the whole number counting system, researchers who worked in groups of 2 or 3 were generally the most productive, in terms of producing the most papers and citations. However, when using fractional counting, researchers who worked in groups of 1 or 2 were generally the most productive. The findings need to be interpreted cautiously, however, because authors that produce few academic articles within a field may publish in other fields or leave academia and contribute to society in other ways

Efficiency of European public higher education institutions: a two-stage multicountry approach

The purpose of this study is to examine efficiency and its determinants in a set of higher education institutions (HEIs) from several European countries by means of non-parametric frontier techniques. Our analysis is based on a sample of 259 public HEIs from 7 European countries across the time period of 2001–2005. We conduct a two-stage DEA analysis (Simar and Wilson in J Economet 136:31–64, 2007), first evaluating DEA scores and then regressing them on potential covariates with the use of a bootstrapped truncated regression. Results indicate a considerable variability of efficiency scores within and between countries. Unit size (economies of scale), number and composition of faculties, sources of funding and gender staff composition are found to be among the crucial determinants of these units’ performance. Specifically, we found evidence that a higher share of funds from external sources and a higher number of women among academic staff improve the efficiency of the institution

Multi-criteria ranking of corporate distress prediction models: empirical evaluation and methodological contributions

YesAlthough many modelling and prediction frameworks for corporate bankruptcy and distress have been proposed, the relative performance evaluation of prediction models is criticised due to the assessment exercise using a single measure of one criterion at a time, which leads to reporting conflicting results. Mousavi et al. (Int Rev Financ Anal 42:64–75, 2015) proposed an orientation-free super-efficiency DEA-based framework to overcome this methodological issue. However, within a super-efficiency DEA framework, the reference benchmark changes from one prediction model evaluation to another, which in some contexts might be viewed as “unfair” benchmarking. In this paper, we overcome this issue by proposing a slacks-based context-dependent DEA (SBM-CDEA) framework to evaluate competing distress prediction models. In addition, we propose a hybrid crossbenchmarking- cross-efficiency framework as an alternative methodology for ranking DMUs that are heterogeneous. Furthermore, using data on UK firms listed on London Stock Exchange, we perform a comprehensive comparative analysis of the most popular corporate distress prediction models; namely, statistical models, under both mono criterion and multiple criteria frameworks considering several performance measures. Also, we propose new statistical models using macroeconomic indicators as drivers of distress

Can foreign banks compete in China?

© 2015 AFAANZ Foreign banks in China have faced strict regulatory requirements that were not imposed on domestic banks and as such they have performed poorly in profitability rankings. Recent changes in the Chinese regulatory requirements prompt us to consider whether foreign banks are now on an equal footing with the Chinese domestic banks. Using Cobb–Douglas stochastic frontier analysis with total income as the dependent variable, we find no significant performance difference between foreign and domestic banks. However, robustness testing using the individual components of total income as dependent variables reveals that foreign banks need to improve efficiency of their income generation