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

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.

2017 ◽  
Vol 44 (12) ◽  
pp. 2302-2312 ◽  
Author(s):  
Shazida Jan Mohd Khan ◽  
Shamzaeffa Samsudin ◽  
Rabiul Islam

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahmoud Abdelrahman Kamel ◽  
Mohamed El-Sayed Mousa

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.


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

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.


2016 ◽  
Vol 23 (1) ◽  
pp. 113-126 ◽  
Author(s):  
Punita Saxena ◽  
Ratnesh R. Saxena ◽  
Deepak Sehgal

Purpose – Data envelopment analysis (DEA) is a non-parametric technique of computing efficiencies of decision-making units using similar set of inputs to give similar set of outputs. The objective is to pick out inefficient units from a data set of similar units and thus analyse their performance amongst their peer group. Stock markets can be considered to be an economy’s barometer. Thus, evaluation of efficiency effectiveness of the companies operating at stock exchange is a valuable exercise. Further, if the inefficient units can be given a benchmark for improvement, they can increase their market value. The purpose of this paper is to evaluate the efficiencies of the Oil, Gas and Power (OGP) sector of India for the companies that form a part of the CNX Energy Index and CNX 500 Index of the National Stock Exchange of India. Design/methodology/approach – A group of 24 units has been included in the study. DEA was applied for ranking the units as per their efficiency levels by computing their technical, pure technical and scale efficiencies (SE). It was observed that only nine units are efficient and the remaining 15 were inefficient. It was observed that ONGC is the most efficient unit and CESC Ltd is the least efficient unit in this group. Also in this group there are ten units that show inefficiency due to their scales of operations. Further, benchmarking for the inefficient units has also been done in terms of inputs/outputs and the targets are suggested. It was observed that some of the Public Sector Companies like NTPC are using more inputs compared to the other units from the same group for achieving the same efficiency. Findings – The present study attempted a limited objective of establishing the technical, pure technical and scale inefficiencies of the companies operating in OGP sector in India and listed on National Stock Exchange with the help of the non-parametric technique of DEA and suggesting how they can strive to improve their performance. It is observed that 37.5 per cent are technically efficient as well as scale efficient, whereas 62.5 per cent are pure technically efficient. There are 42 per cent companies representing approximately half of the output and more than half of the input that have scale inefficiencies characterized by their PTE less than SE. Out of the efficient companies, ONGC appears to be the best whereas Essar Oil has a comparatively lower rank. Out of the inefficient companies, the worst performer is CESC Ltd. However, inspite of being the worst performer, this unit does not have the worst benchmarking targets. The units like Sterlite technologies and KSK energy ventures need to improve their profit by almost 1,000 per cent. These kind of targets are very difficult to attain. Hence these units need to improve their scale of operation. The managers of these units must take up this issue seriously and take measures to improve their productivity. The study also attempted benchmarking where various inefficient units have been suggested targets they need to scale to improve their efficiency. If addressed, they can have micro as well as macro benefits. Research limitations/implications – In the present paper, the analysis is restricted only to the OGP sector of Indian economy. The study can be further extended to various other sectors of Indian economy such as agriculture, telecommunications etc. This would help in the holistic analysis of the economy. The flag bearer efficient units would set up a benchmark for the improvement to the inefficient units that would help improve the developing economy of India. Originality/value – An increase in productivity is the most crucial management objective for any industry. Assessing the performance of companies listed and traded in stock market is imperative for investors and financial managers. Researchers have widely studied the performance evaluation of listed companies. Establishing efficiency of stock markets as a whole as well as of the constituent companies has been subject of wide research, but to the understanding no study has been done on evaluating the efficiencies of the OGP sector of India. In the present study the authors have concentrated on companies, out of the universe of energy companies operating in India, which form part of the CNX Energy Index and CNX 500 Index of the National Stock Exchange of India. The reason is that they represent the Indian energy market pretty well.


2015 ◽  
Vol 53 (10) ◽  
pp. 2390-2406 ◽  
Author(s):  
Aibing Ji ◽  
Hui Liu ◽  
Hong-jie Qiu ◽  
Haobo Lin

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahdi Salehi ◽  
Ameneh Bazrafshan ◽  
Mahdieh Hosseinkamal

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.


2018 ◽  
Vol 18 (2) ◽  
pp. 148-164 ◽  
Author(s):  
Marina Cavalieri ◽  
Calogero Guccio ◽  
Ilde Rizzo

Purpose This paper aims at contributing to the research on the role played by corruption in the health procurement by use non-parametric techniques to examine whether the efficient execution of Italian public contracts for healthcare infrastructures is affected by socio-economic variables (including the level of “environmental” corruption) in the area where the work is localised and by the institutional features of the contracting authority. Design/methodology/approach A data envelopment analysis (DEA) is applied to a sample of 405 contracts during the period 2000-2005. Smoothed bootstrap techniques to calculate confidence intervals for the estimated efficiency parameters along with different non-parametric tests and kernel density estimates are used. Findings Results show that “environmental” corruption negatively influences the performance of healthcare infrastructures. Furthermore, healthcare contracting authorities appear to be less efficient than other public bodies acting as procurers. Originality/value The paper highlights the role of environmental corruption in the provision of healthcare infrastructures.


Author(s):  
Taylor Boyd ◽  
Grace Docken ◽  
John Ruggiero

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.


2020 ◽  
Vol 5 (2) ◽  
pp. 193-210
Author(s):  
Shih-Liang Chao ◽  
Yi-Hung Yeh

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ameneh Bazrafshan ◽  
Reza Hesarzadeh

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.


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