Model and Data-Driven System Portfolio Selection Based on Value and Risk

Wei, Hechuan; Xia, Boyuan; Yang, Zhiwei; Zhou, Zhexuan

doi:10.3390/app9081657

Cited by 4 publications

(4 citation statements)

References 29 publications

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“…Big-sized portfolios still represent fewer cases and may configure an opportunity to be explored by future papers, since it may represent the reality of many modern companies with big data-sets. In the case of big-sized portfolios, all papers use traditional MCDM approaches, except for Wei et al [104], that used correlation analysis as an objective method. In some articles, researchers have used software, solvers, or programming languages to implement MCDM methods in R&D PPS.…”

Section: 3%mentioning

confidence: 99%

“…Wei et al [104] Model and Data-Driven System Portfolio Selection 2019 Samanlioglu et al [94] An intelligent approach for the evaluation of innovation projects 2020 Aghdaie et al [116] Decision making on exigent issues in organizations: a case study on R&D projects 2020 Yalcin et al [80] Research and Development Project Selection via IF-DEMATEL and IF-TOPSIS…”

Section: Montajabiha Et Al [9]mentioning

confidence: 99%

“…Several articles do not explain why they have chosen some methods to PPS among all possible options. When this is the case, they mainly use usage frequency, which is the case of standalone AHP applications [74,75,104]. A framework that helps researchers to select the method to use is a lacuna not only in R&D PPS.…”

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confidence: 99%

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MCDM-Based R&D Project Selection: A Systematic Literature Review

et al. 2021

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From small spin-offs deploying innovative software to big pharmaceutical complexes making vaccines, Research and Development (R&D) Project Portfolio Selection (PPS) is an essential strategic process for various companies. It was never easy to select a set of projects among many feasible possibilities, even for yesterday’s paces. However, the world is rapidly changing, and so is R&D PPS. The portfolio objectives excel profit in the same manner that model constraints go beyond budget limitations. In parallel, project selection approaches and solving algorithms followed the increase of computational power. Despite all those changes, the importance of Multi-Criteria Decision Making (MCDM) methods and the decision criteria used for R&D PPS, there is still room for a systematic literature review (SLR) for the topic. Thus, this paper offers an SLR of the existing literature from the half-century, 1970, and onward MCDM-based R&D PPS performed in Scopus and Web of Science Core Collection. We provide a comprehensive picture of this field, show how it is changing, and highlight standard practices and research opportunities in the area. We perform a broad classification of the MCDM methods, categorized by the nature of alternatives, types of integration approach, the MCDM method itself, and types of uncertainty, by the 66 studies in the SLR database. The portfolios’ classification obeys the application domain and the number of projects. We have also explored all the 263 criteria found in the literature by grouping them according to experts from five Brazilian R&D organizations that together manage portfolios valued around US$ 5 billion a year, accounting for 38% of all Brazilian annual expenditure in R&D projects. We also include a bibliometric analysis of the considered papers and research opportunities highlighted or not explored by researchers. Given the increasing number of decision-making approaches and new technologies available, we hope to provide guidance on the topic and promote knowledge production and growth concerning the usage of MCDM methods and decision criteria in R&D PPS.

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Section: 3%mentioning

confidence: 99%

Section: Montajabiha Et Al [9]mentioning

confidence: 99%

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MCDM-Based R&D Project Selection: A Systematic Literature Review

et al. 2021

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“…London et al [23] investigated the Markowitz PS problem and implemented several estimators to determine the expected return of a portfolio. Kumar and Doja [24] and then Wei et al [25] showed that the feasibility of replacing expert subjectiveness with knowledge based on the given information.…”

Section: Introductionmentioning

confidence: 99%

Solution of Extended Multi-Objective Portfolio Selection Problem in Uncertain Environment Using Weighted Tchebycheff Method

Kumar

2022

Computers

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In this paper, a mathematical model for an extended multi-objective portfolio selection (EMOPS) problem is explored with liquidity considered as another objective function besides the risk and return. The model is mathematically formulated in an uncertain environment. The concerned uncertainty is dealt with by employing the fuzzy numbers in the risk matrix and return. While the fuzzy EMOPS model is converted into the corresponding deterministic case based on the α—level sets of the fuzzy numbers, a weighted Tchebycheff method is implemented by defining relative weights and ideal targets. The merit of the suggested method is the applicability in many real-world situations. At the end, some numerical illustration is exhibited for the utility of the suggested EMOPS problem. Finally, it is concluded that the suggested method is simple to learn and to implement in real-life situations for the decision maker.

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