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Most decision-making problems in construction are complex and difficult to solve, as they involve multiple criteria and multiple decision makers in addition to subjective uncertainties, imprecisions and vagueness surrounding the decision-making process. In many instances, the decision-making process is based on linguistic terms rather than numerical values. Hence, structured fuzzy consensus-reaching processes and fuzzy aggregation methods are instrumental in multi-criteria group decision-making (MCGDM) problems for capturing the point of view of a group of experts. This chapter outlines different fuzzy consensus-reaching processes and fuzzy aggregation methods. It presents the background of the basic theory and formulation of these processes and methods, as well as numerical examples that illustrate their theory and formulation. Application areas of fuzzy consensus reaching and fuzzy aggregation in the construction domain are identified, and an overview of previously developed frameworks for fuzzy consensus reaching and fuzzy aggregation is provided. Finally, areas for future work are presented that highlight emerging trends and the imminent needs of fuzzy consensus reaching and fuzzy aggregation in the construction domain.

Panel data provide the possibilities of estimating individual treatment effects for multiple individuals. Two issues are considered: (1) differences in the estimated individual treatment effects are due to heterogeneity or a chance mechanism? (2) what is the best way to estimate the average treatment effects? Testing and aggregation methods are suggested. Monte Carlo simulations are also conducted to shed light on these two issues. An empirical analysis on the involvement of underground organization in China’s Peer-to-Peer (P2P) activities through the “anti-gang” campaign is also provided.

The purpose of this paper is to construct an optimal resource reallocation model of the limited resource by a moderator for reaching the greatest consensus, and show how to reallocate the limited resources by using optimization methodology once the consensus opinion is reached. Moreover, this paper also devotes to theoretically exploring when or what is the condition that the group decision-making (GDM) system is stable; and when new opinions enter into the GDM, how the level of consensus changes.

By minimizing the differences between the individuals’ opinions and the collective consensus opinion, this paper constructs a consensus optimization model and shows that the objective weights of the individuals are actually the optimal solution to this model.

If all individual deviations of the decision makers (DMs) from the consensus balance each other out, the information entropy theorem shows this GDM is most stable, and economically each individual DM gets the same optimal unit of compensation. Once the consensus opinion is determined and each individual opinion of the DMs is under an acceptable consensus level, the consensus is still acceptable even if additional DMs are added, and the moderator’s cost is still no more than a fixed upper limitation.

The optimization model based on acceptable consensus is constructed in this paper, and its economic significance, including the theoretical and practical significance, is emphatically analyzed: it is shown that the weight information of the optimization model carries important economic significance. Besides, some properties of the proposed model are discussed by analyzing its particular solutions: the stability of the consensus system is explored by introducing information entropy theory and variance distribution; in addition, the effect of adding new DMs on the stability of the acceptable consensus system is discussed by analyzing the convergence of consensus level: it is also built up the condition that once the consensus opinion is determined, the consensus degree will not decrease even when additional DMs are added to the GDM.

The main purpose of this paper is to develop a methodology to analyze the competitiveness based on the diamond model and constructing a composite index; the secondary aim is to apply this methodology to the national index of Turkey’s defense industry.

Instead of providing the results based only on diamond, a composite index study was carried out. The collected variables were distributed using subject-groups under determinants via an expert opinion survey. The variables were analyzed with alternative methods of imputation, normalization and aggregation. Factor analysis (FA) was performed with the aggregated values of each subject to find the years’ clusters.

Turkey’s diamond model indicated an improvement in defense industry between 1998-2010. And, FA revealed the clusters as 1998-2000, 2001-2007, 2008-2010. It was found that Turkey had an advantage in demand conditions but needs to give higher importance to factor conditions. In addition, the key provisions were catered to the issues related to government and the defense industry.

Turkey’s competitiveness structure between 1998-2010 were researched.

This study provides a qualitative approach of the composite index to the quantitative side of the diamond model.

The purpose of this paper is to enhance accessibility of graphical information in particular for blind and visually handicapped people.

Prototype development based on an intense analysis of the state of the art and potential technologies with later on heuristic analysis of different approaches to enrich graphical information for better accessibility.

A novel approach to enhance accessibility named “Intention Tree” for enhancing accessibility. It allows integrating descriptive and navigation information into standard Scalable Vector Graphics and also mechanisms to analyse and aggregate data.

The approach promises interesting new tools for better accessing and navigating graphical information with potential not only for blind and visually handicapped people.

Design prototype for further development.

Potential for better social inclusion and participation.

This paper presents a novel and new approach for enhanced accessibility and usability and a new technique for authoring graphical information.

The behavioral decision-making of digital-self is one of the important research contents of the network of crowd intelligence. The factors and mechanisms that affect decision-making have attracted the attention of many researchers. Among the factors that influence decision-making, the mind of digital-self plays an important role. Exploring the influence mechanism of digital-selfs’ mind on decision-making is helpful to understand the behaviors of the crowd intelligence network and improve the transaction efficiency in the network of CrowdIntell.

In this paper, the authors use behavioral pattern perception layer, multi-aspect perception layer and memory network enhancement layer to adaptively explore the mind of a digital-self and generate the mental representation of a digital-self from three aspects including external behavior, multi-aspect factors of the mind and memory units. The authors use the mental representations to assist behavioral decision-making.

The evaluation in real-world open data sets shows that the proposed method can model the mind and verify the influence of the mind on the behavioral decisions, and its performance is better than the universal baseline methods for modeling user interest.

In general, the authors use the behaviors of the digital-self to mine and explore its mind, which is used to assist the digital-self to make decisions and promote the transaction in the network of CrowdIntell. This work is one of the early attempts, which uses neural networks to model the mental representation of digital-self.

This paper aims to examine the applicability of real options methodology with respect to developing internal transfer pricing mechanisms. A pervasive theme in existing models is their inability to handle the dynamic and volatile nature of today’s business environment, as well as their lack of objective managerial flexibility. The authors address these and other issues and develop a transfer pricing mechanism based on Black–Scholes and the binomial options pricing methodology, which is better suited in today’s dynamic business environment.

The authors use a conceptual approach in developing theoretical justifications and show, practically, how a transfer price can be developed using two different real options pricing models.

The authors find that real options transfer price mechanism (real options framework [ROF]) can effectively deal with many of the issues that permeate a modern organization with complex multi-dimensional operations. The authors argue that uncertainty and behavioral issues commonly associated with setting transfer prices are better handled using a transfer pricing mechanism that preserves flexibility at the business unit level, the managerial level and the firm level. The approach allows for different managerial styles in both centralized and decentralized sub-units within the same organization. The authors argue that an open multi-dimensional framework using real options is suitable under conditions of uncertainty and managerial opportunism.

ROF-based transfer pricing may be significant in that firms can use it as a tool to manage an organization by setting the prices centrally and at the same time allowing managers to select the transfer price that best suits their specific situation and operating conditions. This may result in a more efficient and more profitable organization.

The contribution of the paper is the melding of the ROF from the finance literature with the accounting problem of setting a transfer price for items lacking a competitive market price. The authors also contribute to existing research by explicitly developing a framework that values managerial flexibility, takes into account uncertainty and considers the behavioral aspects of the transfer pricing process. The authors establish the conditions under which a generic real options model is a feasible alternative in determining a transfer price.

This is mainly because the restrictive condition of intuitionistic hesitant fuzzy number (IHFN) is relaxed by the membership functions of Pythagorean probabilistic hesitant fuzzy number (PyPHFN), so the range of domain value of PyPHFN is greatly expanded. The paper aims to develop a novel decision-making technique based on aggregation operators under PyPHFNs. For this, the authors propose Algebraic operational laws using algebraic norm for PyPHFNs. Furthermore, a list of aggregation operators, namely Pythagorean probabilistic hesitant fuzzy weighted average (PyPHFWA) operator, Pythagorean probabilistic hesitant fuzzy weighted geometric (PyPHFWG) operator, Pythagorean probabilistic hesitant fuzzy ordered weighted average (PyPHFOWA) operator, Pythagorean probabilistic hesitant fuzzy ordered weighted geometric (PyPHFOWG) operator, Pythagorean probabilistic hesitant fuzzy hybrid weighted average (PyPHFHWA) operator and Pythagorean probabilistic hesitant fuzzy hybrid weighted geometric (PyPHFHWG) operator, are proposed based on the defined algebraic operational laws. Also, interesting properties of these aggregation operators are discussed in detail.

PyPHFN is not only a generalization of the traditional IHFN, but also a more effective tool to deal with uncertain multi-attribute decision-making problems.

In addition, the authors design the algorithm to handle the uncertainty in emergency decision-making issues. At last, a numerical case study of coronavirus disease 2019 (COVID-19) as an emergency decision-making is introduced to show the implementation and validity of the established technique. Besides, the comparison of the existing and the proposed technique is established to show the effectiveness and validity of the established technique.

Paper is original and not submitted elsewhere.

The purpose of this paper is to develop a new decision making method based on distance measures that uses the probabilistic weighted averaging (PWA) operator. The paper introduces the PWA distance (PWAD) operator. It is a new aggregation operator that uses probabilities, weighted averages (WAs) and distance measures. Some of its main properties and particular cases are studied such as the arithmetic weighted Hamming distance and the arithmetic probabilistic Hamming distance. An application in a group decision making problem concerning the selection of investment strategies is also presented.

The paper follows the aggregation operator literature by designing new aggregation operators based on the use of distance measures. Also an application in investment selection is developed.

The PWAD operator is presented. It permits to use distance measures with probabilities and WAs in the same formulation. Moreover, the paper also finds the PWA norm aggregation and implements them in a group decision making problem.

The PWAD operator can be applied in a wide range of problems including statistics, economics and engineering. The paper focuses on a multi‐person decision making application concerning the selection of the optimal investment strategies.

New aggregation operators by using distance measures are presented. Their main advantage is that they unify the WA with the probability. Thus, the paper considers distance measures that include subjective and objective information in the same formulation.

The aim of this study as to find out an approach for emergency program selection.

The authors have generated six aggregation operators (AOs), namely picture fuzzy Yager weighted average (PFYWA), picture fuzzy Yager ordered weighted average, picture fuzzy Yager hybrid weighted average, picture fuzzy Yager weighted geometric (PFYWG), picture fuzzy Yager ordered weighted geometric and picture fuzzy Yager hybrid weighted geometric aggregations operators.

First of all, the authors defined the score and accuracy function for picture fuzzy set (FS), and some fundamental operational laws for picture FS using the Yager aggregation operation. After that, using the developed operational laws, developed some AOs, namely PFYWA, picture fuzzy Yager ordered weighted average, picture fuzzy Yager hybrid weighted average, PFYWG, picture fuzzy Yager ordered weighted geometric and picture fuzzy Yager hybrid weighted geometric aggregations operators, have been proposed along with their desirable properties. A decision-making (DM) approach based on these operators has also been presented. An illustrative example has been given for demonstrating the approach. Finally, discussed the comparison of the proposed method with the other existing methods and write the conclusion of the article.

To find the best alternative for emergency program selection.