Selecting most efficient information system projects in presence of user subjective opinions: a DEA approach

Toloo, Mehdi; Nalchigar, Soroosh; Sohrabi, Babak

doi:10.1007/s10100-018-0549-4

Cited by 36 publications

(15 citation statements)

References 59 publications

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“…Supplier-related decisions often rely on personal judgment, as some criteria reflect expert opinions. Thus, using DEA for an evaluation requires making use of imprecise data (Toloo et al 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

Supplier selection: comparison of DEA models with additive and reciprocal data

Dobos

Vörösmarty

2020

Cent Eur J Oper Res

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Supplier evaluation is one of the most important fields of application for data envelopment analysis (DEA). Criteria may include negative data in both input and output factors. Data translation can solve this problem, but interpretation is not evident from the literature. Use of an additive model is one method of managing the problem of negative data. This paper addresses this issue in relation to the supplier ranking problem. It describes the development of a ranking with cross-efficiency that incorporates negative data into the additive model. The additive model we describe is compared with previously used DEA models in which data is replaced with reciprocal values when necessary. We present a supplier-evaluation-related example of this case. After the efficiency evaluation, a supplier ranking system is constructed. To do this, we use the cross-efficiencies obtained from the additive model. Aggregate efficiencies help display the suppliers in descending order of efficiency. Finally, the paper compares self-and peer-appraisal indicators for reciprocal and additive DEA models.

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Section: Literature Reviewmentioning

confidence: 99%

Supplier selection: comparison of DEA models with additive and reciprocal data

Dobos

Vörösmarty

2020

Cent Eur J Oper Res

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“…Linton et al () use CCR model to categorize PPs, so that efficient PPs are accepted automatically, whereas inefficient ones are categorized into “accept,” “consider further,” and “reject.” Swink, Talluri, and Pandejpong () and Lu and Hung () discuss a sequential DEA model to categorize PPs into tiers of efficient and inefficient PPs. However, these studies often identify more than one PP as efficient and are found to be less adequate in project decision contexts where full ranking of PPs is desired (Toloo, Nalchigar, & Sohrabi, ). To overcome this difficulty, various alternatives have been proposed.…”

Section: Introductionmentioning

confidence: 99%

“…Popular MADM methods that are used in the first model include analytic hierarchy process (Shaygan & Testik, 2019), decision-making trial and evaluation laboratory (Abdel-Basset, Atef, & Smarandache, 2019), linear programming technique for Nalchigar, and Jamporazmey (2010), Toloo et al (2018), and Wen, An, Xu, and Chen (2018). Particularly, the common feature of the studies in Sowlati et al (2005) and Toloo et al (2018) is the incorporation of DMs' subjective opinions and judgments within the DEA model to align with real-world organizational decision-making contexts. However, gathering these DMs' opinions can not only be costly and time consuming but also yield less robust ranking patterns due to judgmental errors.…”

Section: Introductionmentioning

confidence: 99%

A hybrid multi‐attribute decision‐making procedure for ranking project proposals: A historical data perspective

Oukil

Govindaluri

2019

Manage Decis Econ

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This paper develops a hybrid multiattribute decision‐making methodology for ranking project proposals (PPs) through a judicious usage of historical data of completed projects to determine attribute weights, enabling elimination of problems associated with projected data such as cost and schedule overruns of real‐world projects. The weights generated from data envelopment analysis are explicitly utilized for ranking PPs while allowing subjectivity to be ingeniously incorporated into the decision process. The new approach is implemented for ranking 25 PPs, and the rankings it yields are found indifferent to the decision maker's attitude, which ascertains the robustness of the ranking methodology.

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“…The approach for selecting efficient projects presented in (Fiala 2018) can be used for various types of projects, such as information system projects (Toloo et al 2018). It can also be used for other types of problems, such as selecting an efficient subset of supply chain members with subsequent profit allocation (Fiala 2016).…”

mentioning

confidence: 99%

“…The paper (Shao et al 2018) proposes a new DEA based approach to allocate the resources in branch network system which is not covered by the existing resource allocation works under a centralized decision-making environment. Toloo et al (2018) introduce a DEA approach to find most efficient information system projects while considering subjective opinions and intuitive senses of decision makers. This work is a continuation of the research published in (Toloo et al 2017).…”

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confidence: 99%

Editorial: Special issue on data envelopment analysis

Jablonský

Emrouznejad

Toloo

2018

Cent Eur J Oper Res

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Data Envelopment Analysis (DEA) originally developed by Charnes et al. (1978) is an optimization method of mathematical programming to generalize the Farrell (1957) single-input/single-output technical efficiency measure to the multiple-input/multipleoutput case by constructing a relative efficiency score as the ratio of a single virtual output to a single virtual input. Thus, DEA become a new tool in operational research for measuring technical efficiency. Since 1978 over 10,000 articles, books and dissertation have been published (Emrouznejad and Yang 2018) and DEA has rapidly extended to many other fields with applications to evaluate and compare educational departments (schools, colleges and universities), health care (hospitals, clinics), agricultural production, banking, armed forces, sports, market research, transportation (highway maintenance), courts, benchmarking, index number construction and many other applications. The International DEA Society organized several international DEA conferences in order to spread the use of DEA in both theoretical and application views. Past DEA conferences were held in many countries including Russia,

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Selecting most efficient information system projects in presence of user subjective opinions: a DEA approach

Cited by 36 publications

References 59 publications

Supplier selection: comparison of DEA models with additive and reciprocal data

Supplier selection: comparison of DEA models with additive and reciprocal data

A hybrid multi‐attribute decision‐making procedure for ranking project proposals: A historical data perspective

Editorial: Special issue on data envelopment analysis

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