Project portfolio designing using data envelopment analysis and De Novo optimisation

Fiala, Petr

doi:10.1007/s10100-018-0571-6

Cited by 21 publications

(9 citation statements)

References 16 publications

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“…Karasakal and Aker (2017) prioritise a set of projects by designing a hierarchal structure to identify the most important evaluation criteria, relying on the analytic hierarchy process (AHP). Fiala (2018) assumes budget restrictions when developing an evaluation approach which relies on data envelopment analysis. Bonetti et al (2012) use ordered weighted mean to aggregate individual estimates in project management and exploit the synergies between experts and non-experts in an MCDM framework.…”

Section: Applications Of Mcdm Methods In Project Evaluationmentioning

confidence: 99%

The ambiguous proposal evaluation problem

Asadabadi

Zwikael

2020

Decision Support Systems

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Section: Applications Of Mcdm Methods In Project Evaluationmentioning

confidence: 99%

The ambiguous proposal evaluation problem

Asadabadi

Zwikael

2020

Decision Support Systems

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“…Toloo et al [19] proposes a DEA approach to find the most efficient IS project in the presence of subjective opinions and intuitive sense of decision-makers such as artificial DMUs with assigned priority scores on an equal footing. Fiala [20] proposes a new project portfolio selection method based on a combination of the DEA model and the de novo optimisation approach, assuming a total available budget.…”

Section: Literature Reviewmentioning

confidence: 99%

Data Envelopment Analysis Approach to Energy-Saving Projects Selection in an Energy Service Company

2021

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Project selection is a common problem for many companies. Specifically, it consists in identifying which projects should be selected with regard to their economic efficiency, i.e., the projects that maximise the profit they bring in while minimising the cost of the resources consumed. In this paper, we have focused our interest on energy service companies because of the importance of a convenient selection of their projects. In these types of companies, the attractiveness of a project depends on both the profit estimations obtained in simulations of the energy systems to be improved, as well as the probability that the project will be awarded (e.g., in local government bids, where typically several energy service companies compete to win the bid). We propose a new project selection method, especially tailored to energy service companies and based on centralised data envelopment analysis models with limited availability of the resources. This contrasts with all existing project selection methods and allows the proposed approach to make more efficient use of the limited resources. We have applied the model to a real-world case by selecting projects in a Spanish energy service company, showing the benefits of applying this approach, and comparing the results obtained with other data envelopment analysis project selection approaches.

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“…Pramanik et al (2019) used fuzzy Shannon entropy and fuzzy TOPSIS methods to rank and determine the weight of criteria in the selection information systems projects. Fiala (2018) presented a method for project portfolio designing based on a systemic combination of DEA model and De Novo optimization approach and provided an optimal project portfolio with a minimal budget. Lim et al (2014) introduced an approach based on DEA cross-efficiency evaluation in portfolio selection.…”

Section: Introductionmentioning

confidence: 99%

A model to reduce the risk of project selection utilizing data envelopment analysis

Sadeghiyan

Lotfı

Daneshian

et al. 2021

JM2

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Purpose Project selection management is a matter of challenge for project-oriented organizations, particularly, if the decision-makers are confronted with limited resources. One of the main concerns is selecting an optimal subset that can successfully satisfy the requirements of the organization providing enough resources to the best subset of the project. The projects for which there are not enough resources or those requiring whole resources of the organization will collapse soon after failed to success. Therefore, the issue is in the risk of choosing a set of projects so that can make a balance in investment versus on collective benefit. Design/methodology/approach A model is presented for project selection and has been tested on the 37 available projects. This model could increase the efficiency of the whole subset of the project significantly in comparison to the other model and it was because of choosing a diverse subset of projects. Findings Provides a general framework for project selection and a diverse and balanced subset of projects to increase the efficiency of the selected subset. Also, reduces the impact of uncertainty risk on the project selection process. Research limitations/implications For the purposes of project selection, any project whose results are uncertain is a risky project because, if the project fails, it will reduce combined project value. For example, a pharmaceutical company’s R&D project is affected by the uncertain results of a specific compound. If the company invests in different compounds, a failure with one will be offset by a good result on another. Therefore, with selecting a diverse set of projects, this paper will have a different set of risks. Originality/value This paper discusses the risk of selecting or being responsible for selecting a project under uncertainty. Most of the projects in the field of project selection generally consider the risks facing the projects or existing models that do not take into account the risk.

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Project portfolio designing using data envelopment analysis and De Novo optimisation

Cited by 21 publications

References 16 publications

The ambiguous proposal evaluation problem

The ambiguous proposal evaluation problem

Data Envelopment Analysis Approach to Energy-Saving Projects Selection in an Energy Service Company

A model to reduce the risk of project selection utilizing data envelopment analysis

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