A consensus process based on regret theory with probabilistic linguistic term sets and its application in venture capital

Research on the evaluation method of whole process engineering consulting service modes based on uncertain multiple-attribute group decision-making

With the continuous development of the economy and society, the engineering construction industry has experienced rapid growth, and higher requirements have been put forward for engineering consulting services. Currently, most engineering consulting service enterprises in China only provide relevant consulting services for engineering construction at a certain stage, lacking overall planning and overall control over the entire lifecycle of engineering construction. In order to improve the scientific level of fixed assets investment decision-making and construction management, it is of great value to explore professional engineering consulting services covering the whole process of project construction in the project decision-making stage and implementation stage to achieve the optimization of project quality and economic benefits. The whole process engineering consulting service modes (ECSM) evaluation is a multiple-attribute group decision-making (MAGDM). Recently, the TODIM technique and MACONT technique was created to put forward MAGDM. The interval neutrosophic sets (INSs) are created as a tool for managing fuzzy information during the whole process ECSM evaluation. In this work, the interval neutrosophic number TODIM-MACONT (INN-TODIM-MACONT) technique is created to put forward the MAGDM under INSs. Finally, a numerical analysis for whole process ECSM evaluation is given to validate the proposed technique. The main contributions are outlined: (1) the TODIM and MACONT technique was enhanced under INSs; (2) Information Entropy is created to conduct the weight information under INSs. (3) the INN-TODIM-MACONT technique is created to implement the MAGDM under INSs; (4) a numerical example for whole process ECSM evaluation and some comparative analysis is created to verify the INN-TODIM-MACONT technique.

LogTODIM-PROMETHEE technique for development evaluation of school-enterprise cooperation from the perspective of collaborative education based on the probabilistic linguistic group decision-making

The integration of industry and education can be literally explained as the role of education in providing intellectual support and production services for the development of industries in a country or region, evolving from an auxiliary role in industrial development to a supporting role in industrial development. The government, enterprises, universities, and intermediaries are all the main bodies of industry education integration, and school enterprise cooperation is the core. The two basic functions of universities, namely "applied scientific research" and "social services", must be highlighted. How to strengthen the cultivation of applied talents and improve the quality of talent cultivation in universities is a problem that universities must face in their transformation. Strengthening school enterprise cooperation and promoting the integration of industry and education is an effective way to solve this problem. The development evaluation of school-enterprise cooperation from the perspective of collaborative education is a multiple-attribute group decision-making (MAGDM) problem. Recently, the Logarithmic TODIM (LogTODIM) and PROMETHEE technique was employed to put forward the MAGDM issues. The probabilistic linguistic term sets (PLTSs) are employed as a technique for characterizing uncertain information during the development evaluation of school-enterprise cooperation from the perspective of collaborative education. In this paper, the probabilistic linguistic LogTODIM-PROMETHEE (PL-LogTODIM-PROMETHEE) technique is constructed to put forward the MAGDM under PLTSs. The MEREC technique is employed to obtain the weight values under PLTSs. Finally, a numerical example for development evaluation of school-enterprise cooperation from the perspective of collaborative education is put forward to validate the LogTODIM-PROMETHEE technique.

Enhanced LogTODIM-TOPSIS framework for interval-valued intuitionistic fuzzy MAGDM and applications to intangible assets operational management performance evaluation of commercial sporting events

The effective operation of intangible assets in commercial sports events can bring long-term, sustainable, and large-scale economic benefits to sports events. However, currently, in the operation of commercial sports events, the lack of experience in hosting events often hinders the development of intangible assets that should have created higher profits, and cannot achieve the expected value. The intangible assets operational management performance (IAOMP) evaluation of commercial sporting events is the multiple-attribute group decision-making (MAGDM). The Logarithmic TODIM (LogTODIM) and TOPSIS technique was brought forward the MAGDM. The interval-valued intuitionistic fuzzy sets (IVIFSs) are brought forward as the useful technique for coping with uncertain and fuzzy information during the IAOMP evaluation of commercial sporting events. In this study, the interval-valued intuitionistic fuzzy number Logarithmic TODIM-TOPSIS (IVIFN-LogTODIM-TOPSIS) technique is brought forward the MAGDM under IVIFSs circumstances. Finally, the numerical example for IAOMP evaluation of commercial sporting events is brought forward to verify the IVIFN-LogTODIM-TOPSIS technique. The main contribution of this study is brought forward: (1) the LogTODIM-TOPSIS was extended to IVIFSs in light with MEREC model; (2) the MEREC model is brought forward to derive weight in light with score information values under IVIFSs circumstances. (3) the IVIFN-LogTODIM-TOPSIS is brought forward for MAGDM under IVIFSs circumstances; (4) the numerical example for IAOMP evaluation of commercial sporting events and several different comparative analysis is brought forward to verify the IVIFN-LogTODIM-TOPSIS model.

Optimized multiple-attribute group decision-making through employing probabilistic hesitant fuzzy TODIM and EDAS technique and application to teaching quality evaluation of international Chinese course in higher vocational colleges

With the construction and development of the "the Belt and Road", the international community has an increasing demand for high-quality technical and skilled talents who both understand Chinese and have an international perspective. Exploring a Chinese curriculum system suitable for the development of international students is conducive to promoting the international development of vocational education, improving the quality of international student training, providing talent support for Chinese and foreign enterprises, and promoting the "going out" of Chinese enterprises and international production capacity cooperation. The training of international students in higher vocational colleges starts late, has little experience, lacks theoretical innovation, and lacks the development characteristics of vocational education. The teaching quality evaluation of international Chinese course in higher vocational colleges is multiple-attributes group decision-making (MAGDM). Recently, the TODIM and EDAS technique has been employed to manage MAGDM. The probabilistic hesitant fuzzy sets (PHFSs) are employed as a useful tool for depicting uncertain information during the teaching quality evaluation of international Chinese course in higher vocational colleges. In this paper, the probabilistic hesitant fuzzy TODIM-EDAS (PHF-TODIM-EDAS) technique is built to manage the MAGDM under PHFSs. Finally, the numerical example for teaching quality evaluation of international Chinese course in higher vocational colleges is employed to show the PHF-TODIM-EDAS technique. The main contribution of this paper is outlined: (1) the TODIM technique based on EDAS technique has been extended to PHFSs based on CRITIC technique; (2) the CRITIC technique is employed to derive weight numbers under PHFSs. (3) the PHF-TODIM-EDAS technique is founded to manage the MAGDM under PHFSs; (4) a numerical case study for teaching quality evaluation of international Chinese course in higher vocational colleges and some comparative analysis is supplied to validate the proposed PHF-TODIM-EDAS technique.

Stochastic multiple attribute decision making with Pythagorean hesitant fuzzy set based on regret theory

The objective of this paper is to present an extended approach to address the stochastic multi-attribute decision-making problem. The novelty of this study is to consider the regret behavior of decision makers under a Pythagorean hesitant fuzzy environment. First, the group satisfaction degree of decision-making matrices is used to consider the different preferences of decision-makers. Second, the nonlinear programming model under different statues is provided to compute the weights of attributes. Then, based on the regret theory, a regret value matrix and a rejoice value matrix are constructed. Furthermore, the feasibility and superiority of the developed approach is proven by an illustrative example of selecting an air fighter. Eventually, a comparative analysis with other methods shows the advantages of the proposed methods.

A data-driven group emergency decision-making method based on interval-valued intuitionistic hesitant fuzzy sets and its application in COVID-19 pandemic

The outbreak of Corona Virus Disease 2019 (COVID-19) makes people more concerned about the validity and timeliness of emergency decision making. When an emergency occurs, it is difficult for decision makers (DMs) to give accurate assessment information in the early stage due to the urgency of time, the incompleteness of information, and the limitations of DMs’ cognition and knowledge. Hence, we use interval-valued intuitionistic hesitant fuzzy sets rather than exact numbers to better characterize the fuzziness and uncertainty of emergencies. In addition, the Internet has become a major platform for the public to express their opinions or concerns, so we can collect the user-generated content on social media to help DMs determine appropriate emergency decision-making criteria which are the premise and basis of scientific decisions. However, there is likely to be some correlation between the obtained criteria. To this end, we first extend the Bonferroni mean (BM) operator to the interval-valued intuitionistic hesitant fuzzy environment, and propose three interval-valued intuitionistic hesitant fuzzy BM operators to capture the interrelation of fuzzy input variables, including an interval-valued intuitionistic hesitant fuzzy BM operator, a simplified interval-valued intuitionistic hesitant fuzzy BM operator, and a simplified interval-valued intuitionistic hesitant fuzzy weighted BM (SIVIHFWBM) operator. Then, a new group emergency decision-making method based on the SIVIHFWBM operator and social media data is proposed, and the specific steps of ranking all emergency plans are put forward. Moreover, our method is applied to evaluate emergency plans for the prevention and control of COVID-19. Finally, the effectiveness and feasibility of the method are verified by the sensitivity analysis, validity test, and comparative analysis.

A Multiattribute Group Decision-Making Method With Probabilistic Linguistic Information Based on an Adaptive Consensus Reaching Model and Evidential Reasoning

This article proposes a new multiattribute group decision-making (MAGDM) method with probabilistic linguistic information that considers the following three aspects: an allocation of ignorance information, a realization of group consensus, and an aggregation of assessments. To allocate ignorance information, an optimization model based on minimizing the distances among experts is developed. To measure the consensus degree, a consensus index that considers the information granules of linguistic terms (LTs) is defined. On this basis, a suitable optimization model is established to realize the group consensus adaptively by optimizing the allocation of information granules of LTs with the particle swarm optimization (PSO) algorithm. With an objective to reduce the information loss during aggregation phases, the process of generating comprehensive assessments of alternatives with the evidential reasoning (ER) algorithm is presented. Therefore, a new method is developed based on the adaptive consensus reaching (ACR) model and the ER algorithm. Finally, the applicability of the proposed method is demonstrated by solving a selection problem of a financial technology company. Comparative analyses are conducted to show the advantages of the proposed method.

Intelligent decision methodology for business English teaching quality evaluation based on GHM and PG operators with 2-tuple linguistic neutrosophic numbers

Business English teaching quality evaluation Business English is a new type of composite specialty, which is a discipline innovation made by China’s higher education to adapt to the new market demand and international standards since the reform and opening up. Over the past 20 years, it has cultivated a number of compound talents for the cause of China’s reform and opening up. However, the backwardness of business English theoretical research has greatly restricted the development of business English. At present, Business English has been officially approved as a new major for undergraduate enrollment by the Ministry of Education of the People’s Republic of China. Its subject nature, specialty structure, training objectives, and specialty compound characteristics need to be qualitatively studied theoretically. The business English teaching quality evaluation is viewed as the multiple attribute decision making (MADM) issue. In this paper, we connect the geometric Heronian mean (GHM) operator and power geometric (PG) with 2-tuple linguistic neutrosophic numbers (2TLNNs) to propose the generalized 2-tuple linguistic neutrosophic power geometric HM (G2TLNPGHM) operator. Then, the G2TLNGHM operator is applied to deal with the MADM problems under 2TLNNs. Finally, an example for business English teaching quality evaluation is used to show the proposed methods. Some comparative analysis and parameter influence analysis are fully given. The results show that the built algorithms method is useful for business English teaching quality evaluation.

A Hybrid Intuitionistic Fuzzy Group Decision Framework and Its Application in Urban Rail Transit System Selection

The selection of an urban rail transit system from the perspective of green and low carbon can not only promote the construction of an urban rail transit system but also have a positive impact on urban green development. Considering the uncertainty caused by different conflict criteria and the fuzziness of decision-making experts’ cognition in the selection process of a rail transit system, this paper proposes a hybrid intuitionistic fuzzy MCGDM framework to determine the priority of a rail transit system. To begin with, the weights of experts are determined based on the improved similarity method. Secondly, the subjective weight and objective weight of the criterion are calculated, respectively, according to the DEMATEL and CRITIC methods, and the comprehensive weight is calculated by the linear integration method. Thirdly, considering the regret degree and risk preference of experts, the COPRAS method based on regret theory is propounded to determine the prioritization of urban rail transit system ranking. Finally, urban rail transit system selection of City N is selected for the case study to illustrate the feasibility and effectiveness of the developed method. The results show that a metro system (P1) is the most suitable urban rail transit system for the construction of city N, followed by a municipal railway system (P7). Sensitivity analysis is conducted to illustrate the stability and robustness of the designed decision framework. Comparative analysis is also utilized to validate the efficacy, feasibility and practicability of the propounded methodology.

Evaluation on service quality in institutional pensions based on a novel hierarchical DEMATEL method for PLTSs

In recent years, to address the continued aging of China’s population, the Chinese government has focused on the issue of pensions through a series of pension policies. The traditional system of institutional pensions is facing serious challenges, with a variety of novel pension modes placing them under enormous pressure. Furthermore, the development of institutional pensions has been restricted by many factors, such as long construction cycles and high fees, meaning that this traditional system no longer meets the pension needs of the elderly. Improving the service quality of institutional pensions is inevitable for future progress. Thus, identifying the key factors that influence the service quality of institutional pensions, and understanding the relationships between these factors, is hugely significant. Furthermore, traditional decision-making trial and evaluation laboratory (DEMATEL) method can not solve this problem because the number of factors is too large. To address these issues, we establish an evaluation system for Chinese pension institutions, and propose a hierarchical DEMATEL model based on probabilistic linguistic term sets (PLTSs), which can help decision makers to find the key factors influencing service quality in institutional pensions and deal with the evaluation problem with a large number of criteria. The proposed hierarchical DEMATEL model based on PLTSs fully reflects experts’ preferences and evaluation information, and is able to identify the directions in which China’s pension institutions should improve their quality of service. In addition, we use the best-worst method (BWM) to calculate the importance values of each subsystem, which makes the cause-effect relationship between subsystems more reasonable than the traditional DEMATEL method. Finally, we apply our method to evaluate nursing homes in Zhenjiang, Jiangsu province and propose some managerial implications.

A regret theory-based GEDM method with heterogeneous probabilistic hesitant information and its application to emergency plans selection of COVID-19

Emergency events are happening with increasing frequency, inflicting serious damage on the economic development and human life. A reliable and effective emergency decision making method is great for reducing various potential losses. Hence, group emergency decision making (GEDM) has drawn great attention in past few years because of its advantages dealing with the emergencies. Due to the timeliness and complexity of GEDM, vagueness and regret aversion are common among decision makers (DMs), and decision information usually needs to be expressed by various mathematical forms. To this end, this paper proposes a novel GEDM method based on heterogeneous probabilistic hesitant information sets (PHISs) and regret theory (RT). Firstly, the PHISs with real numbers, interval numbers and linguistic terms are developed to depict the situation that decision group sways precariously between several projects and best retain the original assessment. In addition, the score functions, the divergence functions and some operations of the three types of PHISs are defined. Secondly, the normalization model of PHISs is presented to remove the influence of different dimensions on information aggregation. Thirdly, group satisfaction degree (GSD) based on the score functions and the divergence functions is combined with RT for completely portraying the regret perception of decision group. Then, we introduce Dempster-Shafer (DS) theory to determine the probabilities of future possible states for emergency events. Finally, an example of coronavirus disease 2019 (COVID-19) situation is given as an application for the proposed GEDM method, whose superiority, stability and validity are demonstrated by employing the comparative analysis and sensitivity analysis.

The research for PLTS normalization method based on minimum entropy change and its application in MAGDM problem

In the problem of multiple attributes group decision making (MAGDM), the probabilistic linguistic term sets (PLTSs) is an useful tool which can be more flexible and accurate to express the evaluation information of decision makers (DMs). However, due to the lack of time or knowledge, DMs tend to provide the evaluation information by incomplete PLTSs (InPLTSs) which contain missing information. The process to estimate the missing information of InPLTSs is essential, which is called the normalization of InPLTSs. By analyzing the previous methods, the existing defect is that the original uncertainty information of InPLTS can be hardly retained after normalizing. Moreover, the literature that considers the normalization method from perspective of entropy change is absent. Thus, to overcome the shortcoming and fill the research blank, we propose two optimization models based on minimum entropy change of InPLTSs, which can remain the original uncertainty information of InPLTSs to the greatest extent. Inspired by entropy measure of PLTSs, the novel concepts related to entropy measure of InPLTS are developed. In addition, based on the novel normalization method, a decision model is constructed to solve the MAGDM problem. To verify the feasibility and superiority of the proposed method and model, a case about the selection of five-star scenic spots is given and we conduct to have comparative analysis with other methods.