scholarly journals Variable returns to scale DEA—Taguchi approach for ternary additives optimization in expansive soil subgrade enhancement

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Chijioke Christopher Ikeagwuani ◽  
Donald Chimobi Nwonu
Keyword(s):  
Orthogonal Array ◽  
Returns To Scale ◽  
Expansive Soil ◽  
Optimal Level ◽  
Efficiency Score ◽  
Optimum Combination ◽  
Taguchi Approach ◽  
Decision Making Unit ◽  
The Cross ◽  
Variable Returns To Scale

AbstractIn this study, variable returns to scale (VRS) data envelopment analysis was integrated into the Taguchi approach to optimize ternary additives for expansive soil enhancement. The ternary additives selected were sawdust ash (SDA), quarry dust (QD) and ordinary Portland cement (OPC). The additives were set as the input variables while multiple responses obtained from the experiments performed with the Taguchi orthogonal array were set as the output variables. Each row in the orthogonal array were defined as a decision making unit (DMU) in the optimization process and output-oriented VRS model was used to obtain the efficiency score for each DMU. Next, benevolent formulation was utilized to obtain the multipliers for the inputs and outputs which were subsequently used to determine the cross efficiency scores for each DMU. The cross-efficiency scores were used to construct the cross-efficiency matrix. Thereafter, the mean cross-efficiency score (MCES) was determined for each DMU. Parameter level that maximizes the MCES was chosen as the optimal level for that parameter. Optimum combination of additives was found at A6 B2 C3. Lastly, confirmatory experiments performed by blending the soil with the optimum combination of additives showed the effectiveness of this method in the enhancement of expansive soil properties.

scholarly journals PREDICTING THE EFFICIENCY OF COMMERCIAL BANKS IN BANGLADESH

2021 ◽  
Vol 7 (1) ◽  
pp. 17-30
Author(s):  
Md. Golam Solaiman ◽  
Md. Shahnur Azad Chowdhury ◽  
Basharat Hossain ◽  
Sultana Akter ◽  
Md. Kazi Golam Azam
Keyword(s):  
Commercial Banks ◽  
Banking Sector ◽  
Returns To Scale ◽  
Allocative Efficiency ◽  
Efficiency Score ◽  
Jel Classification ◽  
Foreign Banks ◽  
Scale Efficiency ◽  
Domestic Banks ◽  
Variable Returns To Scale

This paper examines the efficiency of the thirty-six commercial banks (27 Domestic and 9 Foreign Banks) by reviewing Literature and analyzing 6 years (2011-2016) data. The sample was selected based on the availability of data.  It is assumed that the banking sector complies with the variable returns to scale (VRS) approach which means the output of a bank is not proportionately related to its inputs. Therefore, VRS in the ‘Data Envelop Analysis (DEA)’ technique has been employed in this paper. The findings reveal that most (30 banks out of 36 banks) of the banks of Bangladesh are inefficient in terms of technical, allocative, and scale efficiency during the 2011-2016 periods. Conversely, only six banks (4 domestic banks and 2 foreign banks) were found efficient in overall scores in this scrutinization. This study did not find any single bank as efficient in all categories (allocative efficiency, technical efficiency, pure efficiency ratio) for the whole study period (2011-2016). This paper provides valuable intuition, analysis, and comments to the managers and policymakers of the bank’s efficiency score so that they comprehend their position. Finally, this paper suggests necessary steps to transform the inefficient banks into efficient banks, and to make stable the banking sector of Bangladesh. JEL Classification Codes: E51, G21, M1.  

scholarly journals Efficiency Measurement on Banking Sector in Bangladesh

2013 ◽  
Vol 61 (1) ◽  
pp. 1-5 ◽  
Author(s):  
Md. Rashedul Hoque ◽  
Md. Israt Rayhan
Keyword(s):  
Data Envelopment Analysis ◽  
Banking Sector ◽  
Measurement Techniques ◽  
Returns To Scale ◽  
Efficiency Score ◽  
Annual Reports ◽  
Data Envelopment ◽  
Operating Profit ◽  
Constant Returns To Scale ◽  
Variable Returns To Scale

Nowadays banking sector in Bangladesh plays a considerable role in the economic development and business improvement, in this aspect ranking of banks is vital. In this study, an attempt has been made to rank some of the Bangladeshi Banks. Also, the most efficient bank is identified here. Data Envelopment Analysis is used for this purpose. The data from the annual reports of different banks are used in this study for the purpose of efficiency checking. In Data Envelopment Analysis two types measurement techniques are used – constant returns to scale and variable returns to scale. Since this study attempts to maximize output, that is, the operating profit, so the output oriented Data Envelopment Analysis is used here. The most efficient bank is identified here by the highest efficiency score obtained by that specific bank. Dhaka Univ. J. Sci. 61(1): 1-5, 2013 (January) DOI: http://dx.doi.org/10.3329/dujs.v61i1.15088

scholarly journals Data Envelopment Analysis (Dea) Approach In Efficiency Transport Manufacturing Industry in Malaysia

2018 ◽  
Vol 7 (3.20) ◽  
pp. 339
Author(s):  
Mohd Fahmy-Abdullah ◽  
Basri Abdul Talib
Keyword(s):  
Data Envelopment Analysis ◽  
Manufacturing Industry ◽  
Returns To Scale ◽  
Employee Training ◽  
Efficiency Score ◽  
Data Envelopment ◽  
Average Efficiency ◽  
Score Analysis ◽  
Industry Needs ◽  
Variable Returns To Scale

The objective of this study was to measure of technical efficiency, transport manufacturing industry in Malaysia score using the data envelopment analysis (DEA) from 2005 to 2010. The efficiency score analysis used only two inputs, i.e., capital and labor and one output i.e., total of sales. The results shown that the average efficiency score of the Banker, Charnes, Cooper - Variable Returns to Scale (BCC-VRS) model is higher than the Charnes, Cooper, Rhodes - Constant Return to Scale (CCR-CRS) model. Based on the BCC-VRS model, the average efficiency score was at a moderate level and only four sub-industry that recorded an average efficiency score more than 0.50 percent during the period study. The implication of this result suggests that the transport manufacturing industry needs to increase investment, especially in human capital such as employee training, increase communication expenses such as ICT and carry out joint ventures as well as research and development activities to enhance industry efficiency. 

scholarly journals Optimal solutions of multiplier DEA models

2021 ◽  
Author(s):  
Victor V. Podinovski ◽  
Tatiana Bouzdine-Chameeva
Keyword(s):  
Returns To Scale ◽  
Scale Production ◽  
Optimal Solutions ◽  
Optimal Input ◽  
Input And Output ◽  
Decision Making Unit ◽  
Dea Models ◽  
Constraint Structure ◽  
Conventional Models ◽  
Almost All

AbstractConventional models of data envelopment analysis (DEA) are based on the constant and variable returns-to-scale production technologies. Any optimal input and output weights of the multiplier DEA models based on these technologies are interpreted as being the most favorable for the decision making unit (DMU) under the assessment when the latter is benchmarked against the set of all observed DMUs. In this paper we consider a very large class of DEA models based on arbitrary polyhedral technologies, which includes almost all known convex DEA models. We highlight the fact that the conventional interpretation of the optimal input and output weights in such models is generally incorrect, which raises a question about the meaning of multiplier models. We address this question and prove that the optimal solutions of such models show the DMU under the assessment in the best light in comparison to the entire technology, but not necessarily in comparison to the set of observed DMUs. This result allows a clear and meaningful interpretation of the optimal solutions of multiplier models, including known models with a complex constraint structure whose interpretation has been problematic and left unaddressed in the existing literature.

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