A multi-objective grey hierarchical group consensus model and its application

Gu, Sheng-qiang; Liu, Yong; Diao, Wei-xue

doi:10.1108/gs-09-2022-0095

Cited by 3 publications

(2 citation statements)

References 42 publications

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“…Karimi and Yahyazade (2022) investigated the risk of software development projects from four dimensions, including the risk of cost deviation, time deviation, quality deviation and scope deviation, which used rough set theory (RST) and used GST used to cluster the Applying claim reduction criteria attributes and data. Gu et al (2023) constructed a novel multi-objective grey hierarchical group consensus approach to deal with the group consensus problems consisting of hierarchical relationships and non-cooperative behaviors among decision makers (DMs).…”

Section: Applying Claim Reduction Criteriamentioning

confidence: 99%

Applying claim reduction criteria in selecting efficient contractors with the two-step grey data envelopment analysis approach

Asnaashari,

Sheikh Aboumasoudi,

Mozaffari

et al. 2023

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PurposeThe application of correct contractor selection strategies leads to the selection of a qualified contractor and, as a result, the on-time delivery of the project with the desired quality and within the predetermined budgetary constraints. For this reason, evaluating and qualifying contractors before reviewing the proposed prices has been considered an important issue. One factor that disrupts the project completion process and the failure to achieve pre-planned goals effectively is the occurrence of contractors' disputes and claims in projects. To this end, the present study explores claim-reduction strategies for selecting effective contractors in an uncertain environment to reduce possible problems.Design/methodology/approachThe two-step grey data envelopment analysis (GDEA) approach was used to measure efficiency as a powerful tool in selecting efficient contractors during tenders. This approach can extend the applications of multi-criteria decision-making (MCDM) models. In other words, given some uncertainties, the unavailability of some data, and the problems with the DEA model, the two-step GDEA model was used to rank the contractors. The data confirmed the satisfactory outcomes from the selected model.FindingsThe preliminary assessment of contractors is a pre-tendering process and a step in categorizing contractors, excluding contractors lacking required qualifications, and selecting efficient contractors. At first, it will help the employer to exclude inexperienced and unqualified contractors, save resources and time, reduce threats, replace opportunities with threats, and reduce material and non-material costs during the completion of the project until the projects are put into operation. Consequently, this approach reduces claims to a minimum level and increases the organization's effective material and non-material profit.Originality/valueOil and gas plans and projects have a significant, sensitive, and decisive role in the economic, social, political, cultural, infrastructural, and all-round development of Iran; This is while most of the financial resources needed to implement the development and programs across the country come from oil revenues. Studies have indicated that despite the importance of these plans and projects, many of them are not completed successfully, and this causes irreparable losses to the country's economy and development in various fields.HighlightThe findings of this study can be used by organizations to select more effective contractors to assign projects and plans to them.The preliminary assessment of contractors is a pre-tendering process and a step in categorizing contractors, excluding contractors who lack required qualifications, and finally selecting efficient contractors.At first, it will help the employer to exclude inexperienced and unqualified contractors, save resources and time, reduce threats, replace opportunities with threats, and reduce material and non-material costs during the completion of the project until the projects are put into operation.This approach also gives credit to the employer during the execution period and contributes to assessing unqualified contractors and reducing the temptation to hand over the project to an unqualified contractor but with a lower bid price.Consequently, this approach reduces claims to a minimum level and increases the effective material and non-material profit of the organization.Moreover, it provides an extra-organizational evaluation for contractors, motivating them to upgrade their capabilities and optimally allocate material and non-material resources, especially human resources.

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Section: Applying Claim Reduction Criteriamentioning

confidence: 99%

Applying claim reduction criteria in selecting efficient contractors with the two-step grey data envelopment analysis approach

Asnaashari,

Sheikh Aboumasoudi,

Mozaffari

et al. 2023

View full text Add to dashboard Cite

show abstract

“…At present, the theoretical research of grey goal decision model mainly focuses on the optimization of modeling method and the expansion of modeling object. In terms of optimization of modeling methods, Gu et al (2023) proposed a new multi-objective grey hierarchical group consensus method to deal with the group consensus problem composed of hierarchical relationships and non-cooperative behaviors among decision makers. Ma et al (2022) proposed a generalized grey target decision method with mixed attributes.…”

Section: Introductionmentioning

confidence: 99%

Dynamic multi-attribute grey target group decision model based on quantum-like Bayesian networks

Zhang,

Wang,

Gong

2023

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PurposeGrey target decision-making serves as a pivotal analytical tool for addressing dynamic multi-attribute group decision-making amidst uncertain information. However, the setting of bull's eye is frequently subjective, and each stage is considered independent of the others. Interference effects between each stage can easily influence one another. To address these challenges effectively, this paper employs quantum probability theory to construct quantum-like Bayesian networks, addressing interference effects in dynamic multi-attribute group decision-making.Design/methodology/approachFirstly, the bull's eye matrix of the scheme stage is derived based on the principle of group negotiation and maximum satisfaction deviation. Secondly, a nonlinear programming model for stage weight is constructed by using an improved Orness measure constraint to determine the stage weight. Finally, the quantum-like Bayesian network is constructed to explore the interference effect between stages. In this process, the decision of each stage is regarded as a wave function which occurs synchronously, with mutual interference impacting the aggregate result. Finally, the effectiveness and rationality of the model are verified through a public health emergency.FindingsThe research shows that there are interference effects between each stage. Both the dynamic grey target group decision model and the dynamic multi-attribute group decision model based on quantum-like Bayesian network proposed in this paper are scientific and effective. They enhance the flexibility and stability of actual decision-making and provide significant practical value.Originality/valueTo address issues like stage interference effects, subjective bull's eye settings and the absence of participative behavior in decision-making groups, this paper develops a grey target decision model grounded in group negotiation and maximum satisfaction deviation. Furthermore, by integrating the quantum-like Bayesian network model, this paper offers a novel perspective for addressing information fusion and subjective cognitive biases during decision-making.

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The grey decision model and its application based on generalized greyness of interval grey number

Li,

2024

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PurposeIn order to solve the decision-making problem that the attributive weight and attributive value are both interval grey numbers, this paper tries to construct a multi-attribute grey decision-making model based on generalized greyness of interval grey number.Design/methodology/approachFirstly, according to the nature of the generalized gresness of interval grey number, the generalized weighted greyness distance between interval grey numbers is given, and the transformation relationship between greyness distance and real number distance is analyzed. Then according to the objective function that the square sum of generalized weighted greyness distances from the decision scheme to the best scheme and the worst scheme is the minimum, a multi-attribute grey decision-making model is constructed, and the simplified form of the model is given. Finally, the grey decision-making model proposed in this paper is applied to the evaluation of technological innovation capability of 6 provinces in China to verify the effectiveness of the model.FindingsThe results show that the grey decision-making model proposed in this paper has a strict mathematical foundation, clear physical meaning, simple calculation and easy programming. The application example shows that the grey decision model in this paper is feasible and effective. The research results not only enrich the grey system theory, but also provide a new way for the decision-making problem that the attributive weights and attributive values are interval grey numbers.Practical implicationsThe decision-making model proposed in this paper does not need to seek the optimal solution of the attributive weight and the attributive value, and can save the decision-making labor and capital investment. The model in this paper is also suitable for the decision-making problem that deals with the coexistence of interval grey numbers and real numbers.Originality/valueThe paper succeeds in realizing the multi-attribute grey decision-making model based on generalized gresness and its simplified forms, which provide a new method for grey decision analysis.

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A multi-objective grey hierarchical group consensus model and its application

Cited by 3 publications

References 42 publications

Applying claim reduction criteria in selecting efficient contractors with the two-step grey data envelopment analysis approach

Applying claim reduction criteria in selecting efficient contractors with the two-step grey data envelopment analysis approach

Dynamic multi-attribute grey target group decision model based on quantum-like Bayesian networks

The grey decision model and its application based on generalized greyness of interval grey number

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