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With numerous and ambiguous sets of information and often conflicting requirements, construction management is a complex process involving much uncertainty. Decision makers may be challenged with satisfying multiple criteria using vague information. Fuzzy multi-criteria decision-making (FMCDM) provides an innovative approach for addressing complex problems featuring diverse decision makers’ interests, conflicting objectives and numerous but uncertain bits of information. FMCDM has therefore been widely applied in construction management. With the increase in information complexity, extensions of fuzzy set (FS) theory have been generated and adopted to improve its capacity to address this complexity. Examples include hesitant FSs (HFSs), intuitionistic FSs (IFSs) and type-2 FSs (T2FSs). This chapter introduces commonly used FMCDM methods, examines their applications in construction management and discusses trends in future research and application. The chapter first introduces the MCDM process as well as FS theory and its three main extensions, namely, HFSs, IFSs and T2FSs. The chapter then explores the linkage between FS theory and its extensions and MCDM approaches. In total, 17 FMCDM methods are reviewed and two FMCDM methods (i.e. T2FS-TOPSIS and T2FS-PROMETHEE) are further improved based on the literature. These 19 FMCDM methods with their corresponding applications in construction management are discussed in a systematic manner. This review and development of FS theory and its extensions should help both researchers and practitioners better understand and handle information uncertainty in complex decision problems.

This paper aims at multi-attribute and multi-program group decision making when the attribute weights are completely unknown and the attribute value information is in the form of the interval number.

This is an artificial intelligence algorithm for designing information gathering in group decision making. The authors propose the nonlinear programming model to gather information based on plant growth simulation algorithm (PGSA). The authors collect each program on each attribute group decision preference ordering interval and then use them to find the preference vector and the preference matrix. The entropy method is used to determine the weight of each attribute by the constructed preference matrix. According to the possibility degree matrix of each attribute, the combined effect vector is established by the priority weight vector method, which sorts and selects the best decision making program.

To the authors' knowledge, the application of PGSA in the field of management decisions to collect program on each attribute group decision making preference interval number is the first trial in literature. It has retained more valuable decision making information from all experts without distortion.

In practice, a real number may not be an accurate representation, but only gives a range of values to describe the attributes. This study provides a useful measurement of interval number information for managers to evaluate military science, venture capital, and environmental assessment, etc.

The methodology considers the complete information to ensure no information distortion even with large and complex systems. The authors adopt computer artificial intelligence algorithms to obtain the objective evaluation, which is meaningful for both research studies and practical use.

Decision making is the task of selecting the most appropriate alternative among a finite set of possible alternatives with respect to some attributes. The attributes may be subjective or objective (or combination of both), depending upon the situation; requirements may also be conflicting. In practice, most of the real-world decision-making problems are based on subjective evaluation criteria which are basically ill-defined and vague. Since subjective human judgment bears ambiguity and vagueness in the decision making; application of grey numbers set theory may be proved fruitful in this context. The paper aims to discuss these issues.

Owing to the advantages of grey numbers set theory in tackling subjectivity in decision making; the crisp-TODIM needs to be extended by integrating with grey numbers set theory in order to facilitate decision making consisting of subjective data. Hence, the unified objective of this paper is to propose a grey-based TODIM approach in the context of decision making.

Application potential of grey-TODIM has been demonstrated through a case empirical robot selection problem. Result obtained thereof, has also been compared to that of existing grey-based decision support systems available in literature.

Application potential of grey-based decision support systems (grey-TOPSIS, grey analysis, grey-MOORA) have been highlighted in available literature resource. However, the shortcoming of these approaches is that they do not consider decision-makers’ risk attitude while decision making. TODIM method is derived from the philosophy of Cumulative Prospect Theory (CPT) which considers risk averting attitude of the decision maker in case of gain and risk seeking attitude in case of loss, while comparing dominance between two alternatives with respect to a particular criterion. Hence, this paper contributes a mathematical foundation of TODIM coupled with grey numbers set theory for logical decision making.

Green technology adoption (GTA) in small and micro enterprises (SMEs) is a complex multi-attribute group decision-making issue. Conflicts of opinions can hamper the achievement of group coherence. The purpose of this paper is to solve the conflict decision-making problem in SMEs.

This paper reconstructs the GTA evaluation index system for SMEs and proposes an intragroup coordination relationship model to mitigate group decision-making conflicts based on the cloud model and social networks (GCS). The numerical characteristics of these GTA indicators are determined using fuzzy theory and cloud model.

It was found that establishing a trust relationship network and a conflict coordination relationship could improve the consistency of group decision-making. The degree of coordination has subtle differences with the trust relationship. Particularly, the coordination relationship has obvious influences on the decision-making results among small groups in SMEs.

The conflict coordination model can significantly improve the consistency of group decision-making in SMEs. At the same time, it discusses the differences between the level of conflict coordination and the trust propagation in the process of group decision-making.

The circular economy concept emerged as the resolution to the destructive linear economy practices. Nevertheless, the transition to a circular built environment is hindered due to the ambiguities of the economic value of the concept. Conversely, numerous decision-making tools are applied in the construction industry in assessing economic alternatives, even if there is a gap in utilising these tools in appraising circular economic practices. Hence, this study investigates the potential benefits of applying proven decision-making practices, particularly criteria scoring matrices, in developing circular built environments.

A qualitative approach was followed to achieve the aim of the study. A conceptual design of a criteria scoring matrix was developed with a comprehensive literature survey. Semi-structured interviews of a three-round Delphi expert survey were employed to assess the matrix qualitatively and develop the matrix further. Data were analysed using the content analysis method.

The lack of a value assessment tool in economically assessing the circular economy principles is a key barrier to transcending to a circular built environment. In addressing this issue, this study develops a criteria scoring matrix for circularity value assessment during the design stage of a construction project.

This research contributes to the theory by developing a criteria scoring matrix to measure the economic contribution of circular economy principles. Further, this research contributes to the practice by allowing construction alternatives to be selected, balancing the potential economic return options of a project with the project's contribution to a circular economy.

The purpose of this paper is to investigate the critical decision factors of public–private partnership (PPP) concession which is complex due to a number of uncertain and random variables. To identify critical factors contributing to determination of concession period, this study reviews the published literature. It also identifies countries contributing most in PPP research. As a whole, it provides a mutually beneficial scenario by formulating a decision-making matrix.

This paper reviews the literature published during the period 2005-2015. A two-staged methodology is followed on retrieved scholarly papers: first, countries contributing to PPP are identified along with authors and affiliated institutions. Second, using frequency analysis of shortlisted critical factors, yearly appearance and stakeholders affected, a decision matrix is formulated.

The most contributing country toward PPP research is China, followed by the USA both in terms of country- and author-based contribution. In total, 63 factors are identified that affect PPP concession out of which, 8 per cent are highly critical and 21 per cent are marginally critical for decision-making.

Critical factors of PPP concession period will be identified with the help of decision-making matrix. This will help in adequate resource allocation for handling critical factors ensuring project success. Researchers may also understand the research trends in the past decade to usher ways for future improvements.

This paper reports findings of an original and innovative study, which identifies critical success factors of PPP concession period and synthesizes them into a decision-making matrix. Many of the previous studies have identified and ranked the critical factors but such a synthesis has not been reported.

The purpose of the paper is to propose a novel approach, based on grey clustering decision, to fill in an omission of quantitative monitoring parameter selection methods.

The basic monitoring parameter selection criteria and the corresponding calculation methods are presented. Then, the grey clustering decision model for monitoring parameter optimization selection is constructed, and an integrated weight determination method based on analytic hierarchy process (AHP) and information entropy is provided.

Basic principle for monitoring parameter selection is proposed and quantitative description is carried out for selection principle in engineering application. Grey clustering decision‐making model for monitoring parameter optimization selection is established. Comprehensive weight ascertainment method based on AHP and information entropy is provided to make the index weight more scientific.

At system design stage, it is of significance to carry out selection and optimization of monitoring parameters. After the optimization of monitoring parameters is confirmed, measurability analysis and design in parallel are carried out for convenience of timely information feedback and system design revision. Therefore, the system integration efficiency is improved and the cost of research and manufacturing is reduced.

Monitoring parameter optimization selection process based on grey clustering decision‐making model is described and the analysis result shows that the proposed method has certain degree of effectiveness, rationality and universality.

This paper proposes a new multi-criteria decision-making method, called the vital-immaterial-mediocre method (VIMM), to determine the weight of multiple conflicting and subjective criteria in a decision-making problem.

The novel method utilizes pairwise comparisons, vector-based procedures and a scoring approach to determine weights of criteria. The VIMM compares alternatives by the three crucial components, namely the vital, immaterial and mediocre criteria. The vital criterion has the largest effect on the final results, followed by the mediocre criterion and then the immaterial criterion, which is the least impactful on the prioritization of alternatives. VIMM is developed in two forms where the first scenario is designed to solve one-goal decision-making problems, while the second scenario embraces multiple goals.

To validate the method’s performance and applicability, VIMM is applied to a problem of sustainable supplier selection. Comparisons between VIMM, analytic hierarchy process (AHP) and best-worst method (BWM) reveal that VIMM significantly requires fewer comparisons. Moreover, VIMM works well with both fractional and integer numbers in its comparison procedures.

As an implication for research, we have added the development of the VIMM under fuzzy and grey environments as the direction for optimization of the method.

As managerial implications, VIMM not only provides less complex process for the evaluation of the criteria in the managerial decision-making process, but it also generates consistent results, which make VIMM a reliable tool to apply to a large number of potential decision-making problems.

As a novel subjective weighting method, there exist five major values that VIMM brings over AHP and BWM methods: VIMM requires fewer comparisons compared with AHP and BWM; it is not sensitive to the number of criteria; as a goal-oriented method, it exclusively takes the decision-making goals into account; it keeps the validity and reliability of the Decision-Makers’ (DMs’) opinions and works well with integer and fractional numbers.

The chapter presents an analysis of the decision-making process of leaders on issues of nuclear armament and nuclear disarmament, through four case studies. The first, pertaining armament, is South Africa, with a focus on Pieter Willem Botha, former prime minister and president of South Africa. The second deals with former Libyan President Muammar Gaddafi’s nuclear armament decision. The third case study investigates the decision of former president of South Africa, F. W. De Klerk, on nuclear disarmament. The fourth and final case study uncovers Colonel Muammar Gaddafi’s nuclear disarmament decision.

Using the Applied Decision Analysis (ADA) method historical decisions have been analyzed in this chapter for the purpose of identifying each leader’s ‘decision code’. Specifically, were these decisions based on rational calculations or were they influenced more by cognitive decision processes?

By revealing a ‘decision code’ using a reverse engineering of the decision processes, I conclude that the three leaders placed high importance on security and geopolitics. By analyzing different dimensions and processes that impacted their decision processes, it is evident that while armament decision utilizes the poliheuristic decision rule, disarmament decisions abide by rational calculations.

An essential corporate decision-making tool, the Boston Consulting Group's growth-share matrix, is due for an upgrade. The purpose of this paper is to upgrade this growth matrix for use by corporate managers in the current platform age. Designed in the conglomerate age of the 1960s and 1970s to help corporate managers make disciplined and systematic portfolio investment decisions, the matrix is ill-adapted to the platform age in which we now live. The most valuable companies in the world are now platform companies, and many companies are transitioning to a more platform-based corporate portfolio. In this paper, the author explains how corporate managers can build and execute a sustainable platform portfolio.

The author started with a thorough study of the contextual assumptions and theoretical background of the original Boston Consulting Group growth-share matrix (which the author has been teaching for the past decade). He contrasted these with the assumptions and theoretical background developed in the platform strategy literature. To test and refine the framework, the author presented and discussed its applicability at companies such as GSK and with local consultants. He then used five consecutive cohorts of master students [280 students (70 groups)] to test this framework on a total of 20 companies (both “born platform” and “product to platform” companies).

The platform ecosystem age requires a corporate decision-making matrix that discriminates between businesses on the basis of platform market growth and platform commercialization capability, rather than product market growth and market share. As in the original matrix, these businesses correspond to three different investment horizons (Figure 1): the continuous renewal of blockbuster business, the integration of emerging killer businesses and the experimentation with joint innovation businesses. This paper helps corporate managers build and execute a sustainable platform portfolio by means of a sequence of six decision-making steps and a clear organizational template for successful execution.

The portfolio matrix, decision-making sequence and organizational execution advice presented in this paper are fit for both “born platform” companies such as Google (Alphabet) and “product to platform” hybrids such as Lego. The paper illustrates this with practical examples for both types of companies.