Resource allocation for performance improvement

Nasrabadi, Nasim; Dehnokhalaji, Akram; Kiani, Narsis A.; Korhonen, Pekka; Wallenius, Jyrki

doi:10.1007/s10479-011-1016-y

Cited by 23 publications

(12 citation statements)

References 10 publications

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“…Common Variable Invariance Maximization Cook and Kress (1999) x x Beasley (2003) x x Jahanshahloo et al 2004x x Lozano and Villa (2004) x x Amirteimoori and Kordrostami (2005) x x Cook and Zhu (2005) x x Fang and Zhang (2008) x x Asmild et al (2009) x x Li et al (2009) x x Amirteimoori and Tabar (2010) x x Bi et al 2011x x Lin (2011a) x x Lin (2011b) x x Nasrabadi et al (2012) x x Fang (2013) x x Li et al (2013) x x Lotfi et al (2013) x x Mostafaee (2013) x x Si et al (2013) x x Du et al (2014) x x Fang (2015) x x x x x x . This is due to the fact that some inefficient DMUs could improve their efficiency scores by utilizing these allocated resources and set targets.…”

Section: Weights Efficiencymentioning

confidence: 99%

Using common weights and efficiency invariance principles for resource allocation and target setting

Feng

Song

Dolgui

et al. 2017

International Journal of Production Research

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International audienceData envelopment analysis (DEA) has proven to be a useful technique for evaluating the relative performance of comparable and homogeneous decision-making units (DMUs). In recent years, DEA-based resource allocation and target setting approaches have gained more and more attention from both practitioners and academic researchers. In this paper, we propose a new mechanism to simultaneously adopt the principles of common weights and efficiency invariance in allocating multiple resources and setting multiple targets among DMUs. To obtain the final plan, we minimize the deviation between the possible plan based on common weights and another feasible plan emphasizing efficiency invariance. If the minimum deviation equals zero, one optimal plan will be determined. In general situations, however, the proposed approach will present two plans that have a non-zero deviation. One is generated by using a common set of weights for all DMUs in such a way that the change of efficiencies are minimized, while the other is generated by strictly keeping efficiency scores unchanged yet having similar or even identical weights on input-output measures for each DMU to the utmost extent. The efficacy and usefulness of the proposed approach are demonstrated using a numerical example from previous literature and an empirical application to an urban bus company in China

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Section: Weights Efficiencymentioning

confidence: 99%

Using common weights and efficiency invariance principles for resource allocation and target setting

Feng

Song

Dolgui

et al. 2017

International Journal of Production Research

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“…Moreover, we evaluate benefits from averaging emission intensities across multiple electricity generating units. Therefore, we propose a new methodological approach which is similar to the idea of a central planner which optimally divides resources (see Nasrabadi et al 2012) or costs and revenues (see Khodabakhshi and Aryavash 2014) among subunits. Our analysis is comparable to other studies which use production analysis techniques to analyze the economic benefits of emission trading (see Brännlund et al 1998, Färe et al 2013b, and Färe et al 2014.…”

Section: Introductionmentioning

confidence: 99%

Optimal profits under environmental regulation: the benefits from emission intensity averaging

Hampf

Rødseth

2015

Ann Oper Res

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In this paper we analyze the economic effects of implementing EPA's newly proposed regulations for carbon dioxide (CO 2 ) on existing U.S. coal-fired power plants using nonparametric methods on a sample of 144 electricity generating units. Moreover, we develop an approach for evaluating the economic gains from averaging emission intensities among the utilities' generating units, compared to implementing unit-specific performance standards. Our results show that the implementation of flexible standards leads to up to 2.7 billion dollars larger profits compared to the uniform standards.Moreover, we find that by adopting best practices, current profits can be maintained even if an intensity standard of 0.88 tons of CO 2 per MWh is implemented. However, our results also indicate a trade-off between environmental and profit gains, since aggregate CO 2 emissions are higher with emission intensity averaging than with uniform standards.JEL classification: D24, L50, Q54

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“…Nasrabadi et al [31] presented a model to investigate the resource allocation problem based on efficiency improvement. Their model uses parameters which are not necessarily unique in the case of alternative optimal solution.…”

Section: Introductionmentioning

confidence: 99%

A Data Envelopment Analysis Based Approach for Target Setting and Resource Allocation: Application in Gas Companies

Mottaghi¹,

Ebrahimnejad²,

Ezzati³

et al. 2015

HJMS

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Resource allocation is an important application of data envelopment analysis and has been investigated by many researchers and managers from both economic and managerial field. In real managerial and economical decisions, situations often occur when extra productions of goods are utilized and the decision maker (DM) would like to determine the numbers of extra products that each unit can produced. In this paper, several methods based on the data envelopment analysis for resource allocation in such situations are introduced that can help the managers to make better decisions. The primary aim of this paper is to allocate resources such that the inefficient decision making units (DMUs) to become efficient as possible. For this aim, firstly several homogeneous units under the control of a central unit are considered and then the efficiency of each unit is determined. In addition, if the production of additional products seems logical, the DM wants to know how much of additional outputs should be produced by each unit such that the total outputs reach to a predetermined level. In this case the proposed algorithms determine quantities of the consumed input and produced output levels for each DMU to obtain the desirable output level. For using the whole power of system, the multi objective programming (MOP) problem has been used. A numerical example is given to show the solution process to improve the clarity of the proposed method. Finally, the real data of a gas company extracted from extant literature are used to demonstrate the proposed method.

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Resource allocation for performance improvement

Cited by 23 publications

References 10 publications

Using common weights and efficiency invariance principles for resource allocation and target setting

Using common weights and efficiency invariance principles for resource allocation and target setting

Optimal profits under environmental regulation: the benefits from emission intensity averaging

A Data Envelopment Analysis Based Approach for Target Setting and Resource Allocation: Application in Gas Companies

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