Ranking DMUs by Calculating the Interval Efficiency with a Common Set of Weights in DEA

Rezaie, Vahideh; Ahmad, Tahir; Awang, Siti Rahmah; Khanmohammadi, M.; Maan, Normah

doi:10.1155/2014/346763

Cited by 9 publications

(8 citation statements)

References 22 publications

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“…Choosing the individual desirable weights for each input and output of each DMU estimates the highest efficiency for each DMU and the DMUs cannot be evaluated at the same point of view. Therefore, the interval efficiency model is generated based on a common set of weights by considering positive and anti-ideal DMU [6].…”

Section: Related Workmentioning

confidence: 99%

“…This paper uses the new ranking method proposed by Rezaie et al [6] that considers an integration of both "optimistic" and "pessimistic" efficiencies in the form of an interval. The method determines the lower-and upperbounds of the interval efficiency with a common set of weights.…”

Section: Related Workmentioning

confidence: 99%

“…In this paper the performance of the intelligence parameters are evaluated and ranked for epileptics by considering the demographics and illness background based on Awang's database by an interval efficiency method with a common set of weights in Data Envelopment Analysis (DEA) [6]. As the employment is one of the most challenging issues facing people with epilepsy (PWE) that based on the previous studies have high unemployment rates and cannot keep their jobs, the results from this study are important and may improve the employment opportunities of PWE.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multiple intelligence prioritization for people with epilepsy

Rezaie

Ahmad

Awang

et al. 2015

Mal. J. Fund. Appl. Sci.

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This study uses the data envelopment analysis (DEA) interval efficiency to determine the priorities of eight perceived intelligence parameters skills by considering the people with epilepsy (PWE)'s demographic background. The results of this study help the PWE to identify their strengths and weaknesses where to improve the chances of employability in the job market and to improve their inherent skills for suitable employment. The ranking of PWE's intelligence parameters would describe the status quo of epilepsy sufferers with respect to their intelligence level. Gardner had introduced related activities, products, and suitable careers to each of eight intelligence parameters. Therefore, training the various recommended activities for an epileptic sufferer is paramount in order to be successful in the workplace.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multiple intelligence prioritization for people with epilepsy

Rezaie

Ahmad

Awang

et al. 2015

Mal. J. Fund. Appl. Sci.

View full text Add to dashboard Cite

show abstract

“…Majority of the documentations, as found in [5], [6], [7], [8], and [9] are opinions or comments directed at the determinants of absence, and interventions attempting to address those determinants, but few possess any scientific strategy. This paucity of strategic evidence is largely responsible for the concern raised in [10] relating to the existence of much ambiguity in meanings and uses of absence management mechanism-based thinking in the literature.…”

Section: Introductionmentioning

confidence: 99%

Software Development Models for Computer Based Workplace Attendance Management System

Obidinnu

Ekechukwu

Ejiofor

2015

BJMCS

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This paper establishes that: a formally instituted and consistently applied attendance management system significantly reduces absence levels. It further establishes that: the effectiveness of an attendance management system depends largely on the monitoring, recording, measuring, and reporting of attendance statistics. The paper then affirms that: computer based technologies will be suitable for implementing such systems, since they possess the capacity for effectively performing the listed tasks, as well as producing information for making prompt, informed, and consistent decisions across organisational units. However, the paper discovers that generalizable standards for building these systems are lacking in the literature, due to the obscuring of the internal logic of the existing systems, which are also strategically organisation-centric. The paper therefore, emphasises the need to shift from organisation-centric to process-centric (inter-organisational) approaches. Consequently, it introduces a set of systematic drivers (algorithms, flowcharts, structure chart, and mathematical models), for building new systems, rather than discussing the features of a black-box oriented system that may not have complied adequately with the software engineering best practices. This paper is thus, providing opportunities for broader scientific evaluations, development of sound evidence-based guidelines, and rational framework for ongoing modification and refinement in the future. It will therefore, lead to the implementation of

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“…Ramon et al [12,13] extended their research on the cross-efficiency evaluation into the common weights DEA method based on the idea of reducing differences between profiles of weights. Some other techniques have also been introduced into the DEA method for determining common weights, such as goral programming [14], regression analysis [15], robust optimization [16] and so on [17][18][19][20]. Applications of the common weights DEA models can be found in economy evaluation [21], technology selection [22], resource allocation [23], and so on.…”

Section: Introductionmentioning

confidence: 99%

Determining Common Weights in Data Envelopment Analysis with Shannon’s Entropy

2014

Entropy

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Data Envelopment Analysis (DEA) is a non-parametric method for evaluating the efficiency of Decision Making Units (DMUs) with multiple inputs and outputs. In the traditional DEA models, the DMU is allowed to use its most favorable multiplier weights to maximize its efficiency. There is usually more than one efficient DMU which cannot be further discriminated. Evaluating DMUs with different multiplier weights would also be somewhat irrational in practice. The common weights DEA model is an effective method for solving these problems. In this paper, we propose a methodology combining the common weights DEA with Shannon's entropy. In our methodology, we propose a modified weight restricted DEA model for calculating non-zero optimal weights. Then these non-zero optimal weights would be aggregated to be the common weights using Shannon's entropy. Compared with the traditional models, our proposed method is more powerful in discriminating DMUs, especially when the inputs and outputs are numerous. Our proposed method also keeps in accordance with the basic DEA method considering the evaluation of the most efficient and inefficient DMUs. Numerical examples are provided to examine the validity and effectiveness of our proposed methodology.

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Ranking DMUs by Calculating the Interval Efficiency with a Common Set of Weights in DEA

Cited by 9 publications

References 22 publications

Multiple intelligence prioritization for people with epilepsy

Multiple intelligence prioritization for people with epilepsy

Software Development Models for Computer Based Workplace Attendance Management System

Determining Common Weights in Data Envelopment Analysis with Shannon’s Entropy

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