Board busyness and firm productivity

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ameneh Bazrafshan ◽  
Reza Hesarzadeh
Keyword(s):  
Data Envelopment Analysis ◽  
Design Methodology ◽  
Negative Association ◽  
Data Envelopment ◽  
Firm Productivity ◽  
Regulatory Oversight ◽  
Content Type ◽  
Multiple Directorships ◽  
Regulatory Frameworks

PurposePrior studies provide mixed evidence on the association of board busyness and firm productivity. Thus, this paper empirically analyzes how board busyness affects firm productivity.Design/methodology/approachTo measure board busyness, this paper computes the percentage of directors on a board who sit on three or more boards. Furthermore, to calculate firm productivity, the paper employs data envelopment analysis.FindingsFindings demonstrate that the association of board busyness and firm productivity (association) is generally negative and statistically significant but economically insignificant. In this respect, the findings reveal that the association is negative (positive) and both statistically and economically significant for firms having higher monitoring (advising) needs. Moreover, the findings demonstrate that regulatory oversight (1) weakens the general negative association; (2) changes the direction of association from negative to positive, for firms having higher monitoring needs; and (3) does not influence the association, for firms having higher advising needs.Originality/valueTaken together, the findings indicate that the association of board busyness and firm productivity is conditional to monitoring/advising needs and regulatory oversight. As such, the findings enrich the current debates on the association. Furthermore, the findings offer novel perspectives to enrich the regulatory frameworks of countries which are constraining multiple directorships.

Efficiency of banks in Southeast Asia: Indonesia, Malaysia, Philippines and Thailand

2017 ◽  
Vol 44 (12) ◽  
pp. 2302-2312 ◽  
Author(s):  
Shazida Jan Mohd Khan ◽  
Shamzaeffa Samsudin ◽  
Rabiul Islam
Keyword(s):  
Data Envelopment Analysis ◽  
Southeast Asia ◽  
Design Methodology ◽  
The Philippines ◽  
Data Envelopment ◽  
Bank Efficiency ◽  
Financial Reforms ◽  
Content Type ◽  
Cross Country

Purpose The purpose of this paper is to use the concept of meta-frontiers data envelopment analysis (DEA) to compare the technical efficiencies of banks in selected Southeast Asia countries in the periods of 1998-2012. Design/methodology/approach The authors evaluate bank efficiency in Indonesia, Malaysia, Thailand and the Philippines by means of DEA, and the authors employ a meta-frontiers approach to calculate efficiency scores in a cross-country setting. Findings The analysis shows that even there are some similarities in the process of financial reforms undertaken in the selected countries, the observed efficiency levels of banks vary substantially across the market. Originality/value It is crucial to take into consideration of different technologies in explaining the efficiency differences.

Measuring operational efficiency of isolation hospitals during COVID-19 pandemic using data envelopment analysis: a case of Egypt

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahmoud Abdelrahman Kamel ◽  
Mohamed El-Sayed Mousa
Keyword(s):  
Data Envelopment Analysis ◽  
Design Methodology ◽  
Operational Efficiency ◽  
Data Envelopment ◽  
Allocation Of Resources ◽  
Tobit Regression ◽  
Health Crisis ◽  
Content Type ◽  
Dea Analysis ◽  
Using Data

PurposeThis study used Data Envelopment Analysis (DEA) to measure and evaluate the operational efficiency of 26 isolation hospitals in Egypt during the COVID-19 pandemic, as well as identifying the most important inputs affecting their efficiency.Design/methodology/approachTo measure the operational efficiency of isolation hospitals, this paper combined three interrelated methodologies including DEA, sensitivity analysis and Tobit regression, as well as three inputs (number of physicians, number of nurses and number of beds) and three outputs (number of infections, number of recoveries and number of deaths). Available data were analyzed through R v.4.0.1 software to achieve the study purpose.FindingsBased on DEA analysis, out of 26 isolation hospitals, only 4 were found efficient according to CCR model and 12 out of 26 hospitals achieved efficiency under the BCC model, Tobit regression results confirmed that the number of nurses and the number of beds are common factors impacted the operational efficiency of isolation hospitals, while the number of physicians had no significant effect on efficiency.Research limitations/implicationsThe limits of this study related to measuring the operational efficiency of isolation hospitals in Egypt considering the available data for the period from February to August 2020. DEA analysis can also be an important benchmarking tool for measuring the operational efficiency of isolation hospitals, for identifying their ability to utilize and allocate their resources in an optimal manner (Demand vs Capacity Dilemma), which in turn, encountering this pandemic and protect citizens' health.Originality/valueDespite the intensity of studies that dealt with measuring hospital efficiency, this study to the best of our knowledge is one of the first attempts to measure the efficiency of hospitals in Egypt in times of health' crisis, especially, during the COVID-19 pandemic, to identify the best allocation of resources to achieve the highest level of efficiency during this pandemic.

scholarly journals Benchmarking freight transportation corridors and routes with data envelopment analysis (DEA)

2018 ◽  
Vol 25 (2) ◽  
pp. 713-742 ◽  
Author(s):  
Isotilia Costa Melo ◽  
Paulo Nocera Alves Junior ◽  
Ana Elisa Perico ◽  
Maria Gabriela Serrano Guzman ◽  
Daisy Aparecida do Nascimento Rebelatto
Keyword(s):  
Data Envelopment Analysis ◽  
Design Methodology ◽  
Composite Index ◽  
Freight Transportation ◽  
Principal Component ◽  
Data Envelopment ◽  
Long Distance ◽  
Content Type ◽  
Inland Waterway ◽  
Infrastructure Investments

Purpose The purpose of this paper is to collectively measure and compare the efficiency of Brazilian and American soybean transport corridors, from farmers to export ports, using the data envelopment analysis (DEA). Design/methodology/approach This paper aims to determine routes from main producing micro-regions to main export ports, specifically using slack-based measure and variables that represent the three pillars of sustainability (economic, social, and environmental). The choice of variables was guided by literature review and analyzed through the principal component analysis. After the application of the model, the quantitative tiebreaking method of the composite index is applied. Findings The findings are coherent with a global report that compares soybean transportation in both countries (Brazil and USA). Efficient routes and corridors tend to present short distance truck trips and long distance train or barge trips. The efficiency of the inland waterway trips depends on how many barges are used in the same expedition. Routes with more than three modes tend to be inefficient which suggest that there is a limit for multimodality. Originality/value Corridor benchmarking is a rare topic in the literature and previous works normally focus on some specific and limited corridor performance characteristics, such as cost. The main contribution of this research is that it expands the discussion regarding corridor benchmarking and it focuses on efficiency as a whole. The paper also proposes a method that can be applied in different logistics contexts, like expanding the study to different countries. More specifically, this method could be used in infrastructure investments programs.

Data envelopment analysis with interactive variables

2015 ◽  
Vol 53 (10) ◽  
pp. 2390-2406 ◽  
Author(s):  
Aibing Ji ◽  
Hui Liu ◽  
Hong-jie Qiu ◽  
Haobo Lin
Keyword(s):  
Data Envelopment Analysis ◽  
Special Form ◽  
Design Methodology ◽  
Data Envelopment ◽  
Content Type ◽  
Dea Model ◽  
Proposed Model ◽  
Choquet Integrals ◽  
Practical Implications ◽  
Decision Making Units

Purpose – The purpose of this paper is to build a novel data envelopment analysis (DEA) model to evaluate the efficiencies of decision making units (DMUs). Design/methodology/approach – Using the Choquet integrals as aggregating tool, the authors give a novel DEA model to evaluate the efficiencies of DMUs. Findings – It extends DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form. At last, the authors use the numerical examples to illustrate the performance of the proposed model. Practical implications – The proposed DEA model can be used to evaluate the efficiency of the DMUs with multiple interactive inputs and outputs. Originality/value – This paper introduce a new DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form.

The relationship between supervision quality, CEO’s ability and authority with firm performance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahdi Salehi ◽  
Ameneh Bazrafshan ◽  
Mahdieh Hosseinkamal
Keyword(s):  
Data Envelopment Analysis ◽  
Firm Performance ◽  
Design Methodology ◽  
Business Strategies ◽  
Data Envelopment ◽  
Improve Performance ◽  
Return On Assets ◽  
Content Type ◽  
Listed Firms ◽  
The Relationship

Purpose This paper aims to investigate the relationship between a CEO's ability and authority with firm performance. The authors used a sample of 127 Iranian listed firms for over seven years, from 2011 to 2017. Design/methodology/approach The authors used data envelopment analysis (DEA) to evaluate managers' abilities, and the authors used business strategies to gauge authorities. Also, the methods of Fama–French and Herfindal–Hirschman were used for 889 firm-year observations. Findings The results show that managers' ability based on return on assets can affect firm performance, and skilled managers can improve performance. Originality/value In Iran, managers' abilities and other variables can impact it has been studied. Still, no study has been conducted on managers' strength and their level of authority with the presence of supervision on them.

Simultaneous evaluation of efficiency, input effectiveness, and output effectiveness

2017 ◽  
Vol 24 (7) ◽  
pp. 1854-1870 ◽  
Author(s):  
Amir Shabani ◽  
Gholam Reza Faramarzi ◽  
Reza Farzipoor Saen ◽  
Mohsen Khodakarami
Keyword(s):  
Data Envelopment Analysis ◽  
Design Methodology ◽  
Integrated Model ◽  
Data Envelopment ◽  
Mathematical Approach ◽  
Content Type ◽  
Discriminating Power ◽  
Simultaneous Evaluation ◽  
Efficiency And Effectiveness ◽  
Non Parametric

Purpose The purpose of this paper is to develop a data envelopment analysis (DEA) technique that simultaneously measures efficiency and effectiveness to provide a comprehensive appraisal of the productivity. Additionally, an algorithm is recommended to determine targets that are used for measuring effectiveness. Design/methodology/approach In this paper, for measuring productivity, a new methodology based on non-parametric mathematical DEA technique was presented. The proposed procedure is able to compute the efficiency input effectiveness, and output effectiveness, simultaneously. Findings By comparing with previous models, the authors’ proposed integrated model generates more detailed results and has more discriminating power. Originality/value To the best of the authors knowledge, there is not any study in which a non-parametric mathematical approach measures productivity through simultaneous combining of the effectiveness, including input effectiveness, and output effectiveness, and the efficiency.

scholarly journals Outliers in data envelopment analysis

2016 ◽  
Vol 9 (2) ◽  
pp. 168-183 ◽  
Author(s):  
Taylor Boyd ◽  
Grace Docken ◽  
John Ruggiero
Keyword(s):  
Data Envelopment Analysis ◽  
Design Methodology ◽  
Data Envelopment ◽  
Production Frontier ◽  
Real World Data ◽  
Content Type ◽  
Maximum Likelihood Approach ◽  
Efficiency Measures ◽  
Likelihood Approach ◽  
Stochastic Data

Purpose The purpose of this paper is to improve the estimation of the production frontier in cases where outliers exist. We focus on the case when outliers appear above the true frontier due to measurement error. Design/methodology/approach The authors use stochastic data envelopment analysis (SDEA) to allow observed points above the frontier. They supplement SDEA with assumptions on the efficiency and show that the true frontier in the presence of outliers can be derived. Findings This paper finds that the authors’ maximum likelihood approach outperforms super-efficiency measures. Using simulations, this paper shows that SDEA is a useful model for outlier detection. Originality/value The model developed in this paper is original; the authors add distributional assumptions to derive the optimal quantile with SDEA to remove outliers. The authors believe that the value of the paper will lead to many citations because real-world data are often subject to outliers.

scholarly journals Comparing the productivity of major shipyards in China, South Korea, and Japan – an application of a metafrontier framework

2020 ◽  
Vol 5 (2) ◽  
pp. 193-210
Author(s):  
Shih-Liang Chao ◽  
Yi-Hung Yeh
Keyword(s):  
Data Envelopment Analysis ◽  
South Korea ◽  
Design Methodology ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Shipbuilding Industry ◽  
Content Type ◽  
Substantial Progress

Purpose This study aims to measure the productivity of 21 major shipyards in China, South Korea and Japan. Design/methodology/approach Data envelopment analysis was applied to measure the productivity of shipyards. The contemporaneous and intertemporal productivity scores of each shipyard were measured. Additionally, the technical gaps among shipyards in China, South Korea and Japan were measured and compared. Findings The results indicate that Japan led the global shipbuilding industry in 2014 and South Korea dominated in 2015. Additionally, from 2014 to 2015, shipyards in South Korea and Japan maintained their levels of productivity. Comparatively, major shipyards in China made substantial progress from 2014 to 2015, revealing their strong ambition to improve productivity. Originality/value This study first used a metafrontier framework to measure the technical gap of shipyards among major shipbuilding countries. The model and approach objectively analyze the productivity of major shipyards and considers their nationalities. Additionally, this study is the first to measure changes in the productivity of shipyards. By decomposing the metafrontier Malmquist productivity index, major shipyards were categorized into eight sets. The results of this study can provide a clear direction for shipyards to improve their productivity.

scholarly journals ASSESSMENT OF TFP IN EUROPEAN AND AMERICAN HIGHER EDUCATION INSTITUTIONS – APPLICATION OF MALMQUIST INDICES

2016 ◽  
Vol 24 (2) ◽  
pp. 467-488 ◽  
Author(s):  
Joanna WOLSZCZAK-DERLACZ
Keyword(s):  
Higher Education ◽  
Data Envelopment Analysis ◽  
Productivity Growth ◽  
Negative Association ◽  
Distance Measures ◽  
Data Envelopment ◽  
Total Revenue ◽  
American Higher Education ◽  
Malmquist Indices ◽  
The U.S

In this study we apply Malmquist methodology, based on the estimation of distance measures through Data Envelopment Analysis (DEA), to a sample of 500 universities (in 10 European countries and the U.S.) over the period 2000 to 2010 in order to assess and compare their productivity. On average, a rise in TFP is registered for the whole European sample (strongest for Dutch and Italian HEIs), while the productivity of American HEIs suffered a slight decline. Additionally, we show that productivity growth is negatively associated with size of the institution and revenues from government, and positively with regional development in the case of the European sample, while American HEI productivity growth is characterised by a negative association with GDP and a positive one with the share of government resources out of total revenue.

Fuzzy preference programming formulation in data envelopment analysis for university department evaluation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dyanne Brendalyn Mirasol-Cavero ◽  
Lanndon Ocampo
Keyword(s):  
Data Envelopment Analysis ◽  
Real Life ◽  
The Philippines ◽  
Data Envelopment ◽  
Data Accessibility ◽  
Content Type ◽  
Proposed Model ◽  
University Department ◽  
Fuzzy Dea ◽  
Fuzzy Preference

Purpose University department efficiency evaluation is a performance assessment on how departments use their resources to attain their goals. The most widely used tool in measuring the efficiency of academic departments in data envelopment analysis (DEA) deals with crisp data, which may be, often, imprecise, vague, missing or predicted. Current literature offers various approaches to addressing these uncertainties by introducing fuzzy set theory within the basic DEA framework. However, current fuzzy DEA approaches fail to handle missing data, particularly in output values, which are prevalent in real-life evaluation. Thus, this study aims to augment these limitations by offering a fuzzy DEA variation. Design/methodology/approach This paper proposes a more flexible approach by introducing the fuzzy preference programming – DEA (FPP-DEA), where the outputs are expressed as fuzzy numbers and the inputs are conveyed in their actual crisp values. A case study in one of the top higher education institutions in the Philippines was conducted to elucidate the proposed FPP-DEA with fuzzy outputs. Findings Due to its high discriminating power, the proposed model is more constricted in reporting the efficiency scores such that there are lesser reported efficient departments. Although the proposed model can still calculate efficiency no matter how much missing and unavailable, and uncertain data, more comprehensive data accessibility would return an accurate and precise efficiency score. Originality/value This study offers a fuzzy DEA formulation via FPP, which can handle missing, unavailable and imprecise data for output values.

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