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It is always of great importance for managers in organizations to evaluate their staff members and create incentive systems, using instruments such as Data Envelopment Analysis (DEA) and DEA-R (DEA models based on ratio analysis). The purpose of this paper is to propose a two-stage network incentives system for commercial banks.

Centralized Resource Allocation (CRA) models make it possible to project all decision-making units (DMUs) onto the efficient frontier by solving a single linear programming model. In this paper, we use our proposed DEA-R-based CRA models to evaluate commercial banks in a two-stage case when the only ratios available are the assets-to-costs and income-to-assets vectors.

Thirteen commercial banks modeled as two-stage networks were evaluated by the models proposed in two different cases of ratio data. Results suggest that the proposed methodology yields more accurate efficiency scores, thus allowing better discrimination among DMUs. Furthermore, evaluating the DMUs when they are structured as two-stage (or even three-stage) networks makes it possible to examine the incentives system in more detail. Therefore, the use of incentive systems by managers would allow a better focus on the priority activities of commercial banks and a faster movement toward the frontier of best practices.

The super-efficiency scores of a number of commercial banks are evaluated based on the CRA model, as a cornerstone criterion for the two-stage evaluation in DEA-R, thus allowing the rank of each commercial bank in terms of the incentives system rather on the performance of the productive process.

This study extends the educational institutions' performance and efficiency literature by examining Brazil's Federal Institute of Education, Science and Technology (FIEST), which consists of educational units throughout the country that span several levels of education.

The authors build and analyze a covariance matrix consisting of both a group of efficiency measures and a group of performance indicators used by Brazil's Ministry of Education (BME). The values in the covariance matrix are maximized through application of the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS), in which the weights of each variable are optimized in order to capture the direction of the relationship between the two sets of efficiency measures.

Although the authors find that the collective efficiency of the educational units analyzed did not change during the period of study, the analysis reveals that government indicators of performance do not exhibit a strong relationship to the ideal solution efficiency measures used in this study.

This study extends the educational institution efficiency literature by examining Brazil's FIEST, which consists of 40 educational units throughout the country that spans several levels of education, from upper high school vocational courses to higher degrees.

The purpose of this paper is to investigate the issue of efficiency in the Brazilian motor carrier industry, which has undergone significant transformations since the economy deregulation in the mid-1990s. The main research objective is to determine whether or not different types of cargoes and geographic regions serviced significantly impact trucking managerial efficiency levels.

Research objectives are accomplished by applying a two-stage data envelopment analysis model with bootstrapped estimates. Based on an unbalanced panel model, secondary data from the annual study published by Transporte Moderno (years 2002-2010) were collected and analyzed.

Results support anecdotal evidence regarding a heterogeneous impact of cargo mix and route mix on efficiency levels.

A major limitation of this work concerns the fact of working with secondary data instead of primary data, especially with respect to the set of inputs and outputs used in the analysis, which may not cover all aspects relevant to building an efficiency frontier. Despite this limitation, the study has made an important contribution in its use of panel data to demonstrate the impacts of different types of cargoes and geographic regions serviced on managerial efficiency levels in the trucking industry.

Managerial impacts in terms of mergers and acquisitions are addressed.

The contribution of this study is twofold. On the theoretical side, a valuable scale for the measurement of managerial efficiency was built and validated, representing an index toward the most productive cargo/route mix. On the other hand, the managerial implication of this possibility of measuring the efficiency levels is that motor carriers can use it as a basis for establishing future action plans.

Brazil, DEA, Longitudinal study, Efficiency drivers, Trucking industry, Unbalanced panel

 Research paper

El estudio investiga el tema de la eficiencia en la industria del transporte Brasileña, la cual ha experimentado cambios significativos desde la desregulación de la economía a mediados de los años noventa. El objetivo principal de la investigación es determinar si los diferentes tipos de cargas y regiones geográficas que han recibido los servicios impactan significativamente o no los niveles de eficiencia administrativa de las empresas de camiones.

Los objetivos de la investigación se lograron usando un modelo DEA de dos etapas con estimaciones bootstrap. Basado en un modelo de panel no balanceado, se obtuvieron y analizaron datos secundarios del estudio anual publicados por Transporte Moderno (años 2002-2010).

Los resultados apoyan la evidencia anécdota en lo relacionado con el impacto heterogéneo de mezcla de cargas y una combinación de rutas en los niveles de eficiencia.

La limitación más grande de este trabajo es el hecho de trabajar con datos secundarios en vez de usar datos primarios, especialmente en relación con el set de inputs y outputs usados en este análisis, que podrían no cubrir todos los aspectos relevantes en la construcción de una frontera eficiente. A pesar de esta limitación, este estudio hace una importante contribución al usar datos de panel para demostrar los impactos de los diferentes tipos de cargas y regiones geográficas atendidas, en los niveles de eficiencia de la administración de la industria de transporte de camiones.

Se discuten los impactos de administración en términos fusiones y adquisiciones.

La contribución de este estudio es doble. Por el lado teórico, una escala relevante para medir la eficiencia de la administración fue construida y validada, que representa un índice hacia la combinación carga/ruta más efectiva. Por otro lado, las implicaciones administrativas de la posibilidad de medir niveles de eficiencia es que las empresas de transportes pueden usarloa como base para establecer planes futuros de acción.

Estudio longitudinal, Industria camionera, Brasil, DEA, Promotores de eficiencia, Panel no balanceado

 Trabajo de investigación

A pesquisa investiga o tema da eficiência na indústria brasileira de transporte rodoviário, a qual tem experimentado mudanças significativas desde a desregulamentação da economia em meados dos anos noventa. O objetivo principal da pesquisa é determinar se os diferentes tipos de cargas e de regiões geográficas atendidas impactam significativamente ou não nos níveis de eficiência na gestão de cargas rodoviárias.

Os objetivos da pesquisa foram atingidos usando um modelo DEA de dois estágios com estimativas bootstrap. Baseados em um modelo de painel, foram recolhidos e analisados dados secundários publicados no estudo anual da publicação Transporte Moderno (anos 2002-2010).

Os resultados apoiam a evidência baseada no senso comum relacionada ao impacto heterogêneo do mix de cargas e do mix de rotas nos níveis de eficiência.

A maior limitação de esta pesquisa concerne ao fato de trabalhar com dados secundários em vez de dados primários, especialmente em relação com a série de inputs e outputs utilizados na análise, que não puderam cobrir todos os aspectos relevantes para definição da fronteira de eficiência. Apesar dessa limitação, esta pesquisa traz uma importante contribuição ao utilizar dados de painel para demonstrar os impactos dos diferentes tipos de cargas e de regiões geográficas atendidas sobre os níveis de eficiência na gestão do transporte de cargas rodoviárias.

Os impactos da gestão em termos de fusão e aquisição são abordados.

A contribuição deste estudo é dupla. Pelo lado teórico, foi construída e validada uma escala relevante para medir a eficiência de gestão de cargas rodoviárias, que indica um índice para a combinação mais efetiva da combinação entre cargas e rotas. Por outro lado, quanto às implicações gerenciais, a possibilidade de medir os níveis de eficiência criam a possibilidade das empresas de transportes utilizá-los como base para futuros planos de ação.

Estudo longitudinal, Setor de transporte rodoviário, Brasil, DEA, Condutores de eficiência, Dados em painel

 Trabalhos de pesquisa

Logisticians must make strategic level decisions in order to manage uncertainty, customer service and cost. This research explores the relationships between three strategic level decisions and selected product, operational and demand variables. The three strategic decisions are: make to order vs make to stock; push vs pull inventory deployment; and inventory centralization vs decentralization. The data used to study the relationships were collected in an international environment and analyzed with correlation analysis and logistic regression. Results suggest that the three strategic decisions are each explained by specific product, operational and demand variables.

The purpose of this paper is to assess the efficiency of agricultural production in South Africa from 1970 to 2014, using an integrated two-stage fuzzy approach.

Fuzzy technique for order preference by similarity to ideal solution is used to assess the relative efficiency of agriculture in South Africa over the course of the years in the first stage. In the second stage, fuzzy regressions based on different rule-based systems are used to predict the impact of socio-economic and demographic variables on agricultural efficiency. They are compared with the bootstrapped truncated regressions with conditional α levels proposed in Wanke et al. (2016a).

The results show that the fuzzy efficiency estimates ranged from 0.40 to 0.68 implying inefficiency in South African agriculture. The results further reveal that research and development, land quality, health expenditure–population growth ratio have a significant, positive impact on efficiency levels, besides the GINI index. In terms of accuracy, fuzzy regressions outperformed the bootstrapped truncated regressions with conditional α levels proposed in Wanke et al. (2015).

Policies to increase social expenditure especially in terms of health and hence productivity should be prioritized. Also policies aimed at conserving the environment and hence the quality of land is needed.

The paper is original and has not been previously published elsewhere.

The purpose of this paper is to assess the efficiency determinants of mergers and acquisitions (M&A) in the context of Latin American airlines based on business-related variables commonly found in the literature. The idea is to identify preferable potential airline matches in light of fleet mix, ownership structure and geographical proximity.

In order to achieve the objective, all possible combinations of M&A pairs are considered in the analysis, which is developed in a two-stage approach. First, the M&A Data Envelopment Analysis model efficiency and returns-to-scale estimates are computed. Then, robust regression and multinomial logistic regression are respectively used to discriminate these estimates in terms of such business-related variables.

The results reveal that these different contextual variables significantly impact virtual efficiency and returns-to-scale levels. Private ownership, passenger focus and a better match between aircraft size and demand for flights appear to be key drivers for merged airline efficiency.

The study makes theoretical contributions, though limited to analyzing Latin American airlines only. The use of bootstrapped robust/multinominal logistic regression, compared to the methods adopted by previous literature studies, generates more accurate and robust results related to the efficiency drivers due to its special feature and ability to allow the discrimination of increasing, decreasing, and constant returns to scale in light of a given set of contextual variables.

This study examines the pure effect of the merging activity on efficiency gains. Not only private ownership but also a hybrid public–private ownership has a positive influence on virtual efficiency, suggesting an important governmental role in promoting M&A in the airline industry.

The authors present an original take on the issue of airline mergers by exploring what are the major drivers possibly involved in efficiency gains of potentially merged (virtual) airlines. The authors identify preferable potential airline matches where efficiency gains would be positive in light of business-related variables such as fleet mix, ownership structure and geographical proximity. The analysis also includes an assessment of the impact of contextual variables such as cargo type, ownership structure and geographical proximity in relation to the strategic fit of mergers considering the resulting efficiency and returns-to-scale scores of virtually merged airlines. To the authors’ knowledge, no previous research has addressed these issues in Latin American airlines. Further research directions for this industry are also discussed.

This paper aims to measure and unveil the relationship between customer satisfaction and efficiency levels in the most relevant Brazilian airports.

The authors utilize a two-stage network DEA (data envelopment analysis) and AHP (analytic hierarchy process) model as the cornerstones of the study. The first stage of the network productive structure focuses on examining the infrastructure efficiency of the selected airports, while the second stage assesses their business efficiency.

Although the results indicate that infrastructure and business efficiency levels are heterogeneous and widely dispersed across airports, controlling the regression results with different contextual variables suggests that the impact of efficiency levels on customer satisfaction is mediated by a set of socio-economic and demographic (endogenous) and regulatory (exogenous) variables. Furthermore, encouraging investment in airports is necessary to achieve higher infrastructural efficiency and scale efficiency, thereby improving customer satisfaction.

There is a scarcity of studies examining the relationships among customer satisfaction, privatization and airport efficiency, particularly in developing countries like Brazil.

This paper aims to present a citation-based bibliometric review of Islamic banking efficiency literature from 2000 until August 2020 for analyzing the content of the literature and mapping future research directions.

Using bibliometric citation analysis, this study reviews and examines a total of 278 documents from Web of Science (WoS) indexed sources coupled with content analysis.

The results identified that the growth of Islamic banking efficiency literature has begun to rise since 2008 with an annual growth rate of 12.5% while identifying the most influential aspects of Islamic banking efficiency literature in terms of topics, papers, authors and keywords. The outcomes of science mapping (i.e. co-citation network, bibliometric coupling and co-authorship network) reveal that there are three underlying research streams in Islamic banking efficiency literature: growth of Islamic banking efficiency literature, stability and genuineness of Islamic banking operations and the methods in Islamic banking efficiency literature.

To the best of the knowledge, this is the first bibliometric review paper on Islamic banking efficiency literature. It successfully unveils the scientific mapping of published WoS documents with a future research agenda also proposed based on the review outcomes. These findings can be used in efficiency-related initiatives by managers or regulators for managing Islamic bank operations worldwide.

The purpose of this paper is to analyze the bank efficiency in three developing countries, namely Angola, Brazil and Mozambique, aiming to infer differences given that they belong to the same cultural tradition. The underlying idea is to control for the cultural background, thus allowing the discussion on how different socio-economic and historical variables maybe impacting different levels of banking efficiency and returns to scale results within the ambit of these three countries.

Due to the presence of latent inefficiency, the authors have to modify the technique to accommodate simulation by importance sampling; therefore, in effect, the authors use a local maximum simulated likelihood approach.

The results reveal that Brazil has the highest level of output-oriented efficiency, followed by Angola and then Mozambique. The same ranking is observed in returns to scale, except that vis-à-vis technical change, Brazil and Angola rank first. Finally, inefficiency derived from technical change is highest in Mozambique, followed by Angola and then Brazil. Therefore, these results reveal that the countries with the highest degree of development are higher in efficiency.

Previous studies have identified factors such as legal tradition, accounting conventions, regulatory structures, property rights, culture and religion as possible explanations for cross-border variations in financial development and economic growth. This is the first time banking efficiency is assessed in light of a common cultural background by selecting a group of countries that share the same language and colonial past. Since results are controlled for the same background, it is possible to affirm that the findings are purely related to scale size and economic/political background issues of each country.

The aim of this paper is to provide an approach to analyze the performance of TV programs and to identify what can be done to improve them.

The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the Ng-model, Grey relational analysis (GRA), and principal component analysis (PCA) were applied to evaluate the programs, using audience, share, and duration as the performance criteria.

By comparing TOPSIS to the Ng-model, PCA, and GRA, we verified that SVD and bootstrap SVD TOPSIS provide a good balance between equal-weights TOPSIS and the other models. This is because SVD and bootstrap SVD TOPSIS break down the data to a higher degree, but are less impacted by outliers compared to the long tail models.

To determine which TV programs should be replaced or modified is a complex decision that has not been addressed in the literature. The advantage of using a multi-criteria decision-making (MCDM) approach is that analysts can choose as many criteria as they want to rank TV programs, rather than relying on a single criterion (e.g., audience, share, target rating point).

This work represents the first time that robust MCDM methodology is applied to an audience data set to analyze the performance of TV programs and to identify what can be done to improve them. This study shows the application of a detailed methodology that is useful for the improvement of TV programs and other entertainment industry content.