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The purpose of this paper is to advance a new grey risky multi-attribute decision-making (RMADM) method from the perspective of regret aversion, which is based on the general grey numbers (GGNs) taking the form of kernel and degree of greyness.

First, the normalised grey decision-making matrix is obtained on the basis of kernel and greyness degree of GGNs. Then the regret theory is integrated into the decision-making process by constructing the grey perceived utility function based on GGNs. Finally, the method of evaluation based on distance from average solution (EDAS) is applied to handle with the ranking problem because of its efficiency, stability as well as simplicity.

GGNs have more powerful capacity in expressing uncertainty than interval grey numbers, so the method can solve a larger number of RMADM problems in uncertain and imprecise environments. Meanwhile, the method fully considers the psychological behaviour of the decision makers, which is more applicable to the real world. It is the supplement and perfection of the existing RMADM methods.

The RMADM problem, the grey regret-rejoice function and the EDAS method are all introduced for the first time with GGNs in the form of kernel and degree of greyness. At the same time, the EDAS method is also the first time to be used in combination with the grey RMADM method based on the regret theory.

This paper aims to deal with the problems of failure dependence and common cause failure (CCF) that arise in reliability analysis of complex systems.

Firstly, a dynamic fault tree (DFT) is used to capture the dynamic failure behaviours and converted into an equivalent generalized stochastic petri net (GSPN) for quantitative analysis. Secondly, an efficient decomposition and aggregation (EDA) theory is combined with GSPN to deal with the CCF problem, which exists in redundant systems. Finally, Birnbaum importance measure (BIM) is calculated based on the EDA approach and GSPN model, and it is used to take decisions for system improvement and fault diagnosis.

In this paper, a new reliability evaluation method for dynamic systems subject to CCF is presented based on the DFT analysis and the GSPN model. The GSPN model is easy to capture dynamic failure behaviours of complex systems, and the movement of tokens in the GSPN model represent the changes in the state of the systems. The proposed method takes advantage of the GSPN model and incorporates the EDA method into the GSPN, which simplifies the reliability analysis process. Meanwhile, simulation results under different conditions show that CCF has made a considerable impact on reliability analysis for complex systems, which indicates that the CCF should not be ignored in reliability analysis.

The proposed method combines the EDA theory with the GSPN model to improve the efficiency of the reliability analysis.

Due to the high rate of failure of most crowdfunding projects, knowing the most essential factor to obtain funding success on the crowdfunding platform is of great importance for fund seekers on the crowdfunding platform. The purpose of this study is to explore crowdfunding success factors to know the most essential success factor for stakeholders of the crowdfunding platform to make the best decision when seeking funds on the crowdfunding platform. This study identified and ranked crowdfunding success factors for stakeholders of crowdfunding platforms. Sixteen factors were identified and categorized under five broad headings. These were; project ideas, target capital, track records, geographical proximity and equity.

To rank the identified crowdfunding success factors and subfactors, this study used the Multi-Objective Optimization Based on Ratio Analysis (MULTIMOORA) integrated with the Evaluation based on Distance from Average Solutions (EDAS).

Target capital ranked first among the five categories—while duration involved in raising funds ranked first among the sixteen subfactors. An approach for analyzing how each success factor enhances a crowdfunding campaign was developed in this study. This study provides valuable insight to fund seekers on the crowdfunding platform on how funding success can be achieved by knowing which factor to consider essential when seeking funds on the crowdfunding platform.

This is the first study to explore crowdfunding success factors using the MULTIMOORA-EDAS method. The use of this method will help fund seekers on the crowdfunding platform to know which crowdfunding success factor is essential, thereby aiding fund seekers to make the best decision when seeking funds on the crowdfunding platform. Also, this study is particularly helpful for business owners, platform operators and policymakers when deciding how to allocate resources, plan campaigns and implement regulations.

The purpose of this paper is to develop a multi-criterion group decision-making (MCGDM) method by combining the regret theory and the Choquet integral under 2-tuple linguistic environment and apply the proposed method to deal with the supplier selection problem.

When making a decision, the decision-maker is more willing to choose the alternative(s) which is preferred by the experts so as to avoid the regret. At the same time, the correlative relationships among the criterion set can be sufficiently described by the fuzzy measures, later the evaluations of a group of criteria can be aggregated by means of the Choquet integral. Hence, the authors cope with the MCGDM problems by combining the regret theory and the Choquet integral, where the fuzzy measures of criteria are partly known or completely unknown and the evaluations are expressed by 2-tuples. The vertical and the horizontal regret-rejoice functions are defined at first. Then, a model aiming to determine the missing fuzzy measures is constructed. Based on which, an MCGDM method is proposed. The proposed method is applied to tackle a practical decision-making problem to verify its feasibility and the effectiveness.

The vertical and the horizontal regret-rejoice functions are defined. The relationships of the fuzzy measures are expressed by the sets. A model is built for determining the fuzzy measures. Based on which, an MCGDM method is proposed. The results show that the proposed method can solve the MCGDM problems within the context of 2-tuple, where the decision-maker avoids the regret and the criteria are correlative.

The paper proposes an MCGDM method by combining the regret theory and the Choquet integral, which is suitable for dealing with a variety of decision-making problems.

This study constructs a three-stage evaluation model for interdisciplinary organizations to solve their ranking problems effectively.

A three-stage interdisciplinary organization evaluation model abounds the key problems of “who will evaluate the projects?” and “how to evaluate the projects?”. In the first stage, the authors build a consensus maximization model to identify the selected experts based on the interval grey number because of the uncertainty in assessment. In the second stage, considering the reliability of the experts, the authors calculate the reliability of the experts based on historical data. Meanwhile, considering the gradual changes of the experts, the dynamic weighting method is obtained based on the clustering method. In the third stage, considering decision-makers regret psychological behavior, the authors construct a cross-organizational performance evaluation model based on consensus expectations.

First, for selecting the experts responsible for assessing interdisciplinary organizations, the consensus-reaching method can effectively avoid cognitive bias. Second, during the assessment, the authors obtained more reasonable results by considering the psychological changes of experts based on regret theory. Third, based on the results, the cross-organization of colleges focused on the achievements of talent training, cross effects, and system construction.

Our study could help organizations establish a suitable assessment mechanism and promote interdisciplinary development.

First, considering the importance of selecting the experts, the authors use the consensus-reaching process for expert selection. This method could guarantee most experts' preferences. Then, the authors propose a two-stage dynamic weighting method, including a pre-determined and adjusted process. The dynamic method can better perform the preferences of experts. Third, the authors studied the assessment in interdiscipline. In addition, based on the framework and considering the features of the interdiscipline, the authors use the grey number to perform the uncertain preferences of the experts using regret theory.

The paper seeks to address the European Union's emerging role in the management of international security challenges and its implications for collaboration in armaments procurement. While the former is about integrating member governments at policy level, the latter concerns organising states' defence industries into a cohesive and competitive supply base.

Theoretical frameworks include historic‐comparative analysis and the bureaucratic politics model. Independent variable comprises state actors and interest groups, while the dependent variable comprises the outcomes in terms of defence policy and armaments collaboration decisions. European armaments integration is considered, contrasting liberal inter‐governmentalism and neo‐functionalism theory. Case study data are derived from official EU document sources.

In general, national governments tend to protect important industrial actors irrespective of ownership. Bringing market and defence issues closer challenges the traditional separation between “low” and “high” politics. The collaboration in armaments acquisition is ad hoc and somewhat piecemeal in nature. Structures have evolved in an attempt to integrate the armaments process with spill‐over effect at policy level fostering armaments integration, helped by a more favourably structured and organised defence industry symptomatic of neo‐functionalism. Co‐ordination of European defence policy and armaments procurement through EDA should, in theory, lead to longer‐term co‐ordination, co‐operation and integration between the member states. The latter may see it in their interests to integrate as they come to recognize that EU institutions lack the capabilities to make policies realistic.

European armaments procurement and integration is not well researched; nor are the theoretical issues well understood. An explanation (model) of European armaments procurement integration is developed, along with an identification of key facilitators.

Advanced manufacturing machines (AMMs) are searched as a momentous asset across the manufacturing societies for quenching and addressing the production units under economical circumstances, i.e. production of high-quality of goods under feasible cost. AMMs are significant in holding the managers against their rivals and competitors with high profit margins. The authors developed the decision support mechanism/portfolio (DSM-P) consist of knowledge-based cluster approach with a dynamic model. The purpose of research work is to measure overall economic worth of AMMs under objective and grey-imperfect (mixed) data by exploring the proposed DSM-P.

The authors developed the DSM-P that consist of knowledge-based cluster, three multi-criteria decision-making (MCDM) techniques-1-2-3 with complementary grey relational analysis-4(GRA), approach with a dynamic model (complied by technical plus cost and agility measures of AMMs). The proposed DSM-P enables the manager to map the overall economic worth of candidate AMMs under objective and grey-mixed data.

The presented DSM-P assist the managers for handling the selection problem of AMMs, i.e. CNCs, robots, automatic-guided vehicle, etc under mixed (objective cum grey) data. To enable the readers for intensely understand the work, the utility of proposed approach is displayed by illustrating a polar robot evaluation and selection problem. It is ascertained that the robot candidate-11 alternative is fulfilling the entire technical cum cost and agility measures.

The DSM-P provides more precise and reliable outcomes due to a usage of the dominance theory. Under the dominance theory, the ranks are obtained by MCDM techniques-1-2-3 are compared with ranks gathered by the GRA-4 under objective cum grey data, formed the novelties in presented research work. From a future perspective, the grey-based models in DSM-P can be built/extended/constructed more extensive and can be simulated by the same approach.

The purpose of this study is to construct a gray relational model based on information diffusion to avoid rank reversal when the available decision information is insufficient, or the decision objects vary.

Considering that the sample dependence of the ideal sequence selection in gray relational decision-making is based on case sampling, which causes the phenomenon of rank reversal, this study designs an ideal point diffusion method based on the development trend and distribution skewness of the sample information. In this method, a gray relational model for sample classification is constructed using a virtual-ideal sequence. Subsequently, an optimization model is established to obtain the criteria weights and classification radius values that minimize the deviation between the comprehensive relational degree of the classification object and the critical value.

The rank-reversal problem in gray relational models could drive decision-makers away from using this method. The results of this study demonstrate that the proposed gray relational model based on information diffusion and virtual-ideal sequencing can effectively avoid rank reversal. The method is applied to classify 31 brownfield redevelopment projects based on available interval gray information. The case analysis verifies the rationality and feasibility of the model.

This study proposes a robust method for ideal point choice when the decision information is limited or dynamic. This method can reduce the influence of ideal sequence changes in gray relational models on decision-making results considerably better than other approaches.

This paper aims to classify journal papers in the context of hybrid quality function deployment QFD and multi-criteria decision-making (MCDM) methods published during 2004–2021.

A conceptual classification scheme is presented to analyze the hybrid QFD-MCDM methods. Then some recommendations are given to introduce directions for future research.

The results show that among all related areas, the manufacturing application has the most frequency of published papers regarding hybrid QFD-MCDM methods. Moreover, using uncertainty to establish a hybrid QFD-MCDM the relevant papers have been considered during the time interval 2004–2021.

There are various shortcomings in conventional QFD which limit its efficiency and potential applications. Since 2004, when MCDM methods were frequently adopted in the quality management context, increasing attention has been drawn from both practical and academic perspectives. Recently, the integration of MCDM techniques into the QFD model has played an important role in designing new products and services, supplier selection, green manufacturing systems and sustainability topics. Hence, this survey reviewed hybrid QFD-MCDM methods during 2004–2021.

China is a critical factor for constructing an all-round well-off society. Infrastructure construction, especially high-grade highways, in the western area is an essential component of the strategy for large-scale development of west China. It is crucial to evaluate investment projects for high-grade highways and select the best one. Testing investment projects and selecting the best one can be recognized as a multicriteria decision-making (MCDM) problem. In this process, decision-makers (DMs) usually face with uncertain information because of complicated decision environment or their limited knowledge.

A new Evaluation based on the Distance from Average Solution (EDAS) for PFS based on the DEMATEL is proposed: The authors offer a new score function and prove some properties for the score function. They put forward a novel Decision-making Trial and Evaluation Laboratory (DEMATEL) method for PFS to analyze the relations of criteria and get criteria weights. Considering the bounded rationality of DM, the authors propose a new EDAS method for PFS based on prospect theory. They apply their proposed approach to a western city's actual case in selecting a suitable project for building a high-grade highway.

By comparison, the authors can observe that our method has some traits: (1) considering bounded rationality of DM; (2) fewer computation; (3) having the ability to obtain the relation of criteria and finding the critical factor in the decision system.

In this paper, the authors propose a new EDAS method for PFS based on the DEMATEL technique. They transform PFS into crisp numbers by their proposed new score function for PFN to make the decision process more convenient. Then, the authors use the DEMATEL method to obtain the relationship between criteria and criteria weights. Furthermore, they propose a new EDAS method for PFS based on DEMATEL to reduce the computational complexity. Finally, they apply our method to a real case and compare our method with two traditional methods.