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Managing complex construction projects is a challenging task because it involves multiple factors and decision-making processes. A systematic evaluation of these complex factors is imperative for achieving project success. As most of these factors are qualitative or intangible in nature, decision makers often rely on subjective judgements when comparing and evaluating them. The hybrid techniques that integrate fuzzy set theory and the analytic hierarchy process (AHP) are able to deal with such problems. This chapter discusses various hybrid techniques of the fuzzy AHP and presents an application of these techniques to the evaluation of transportation project complexity, which is essential for prioritising resource allocation and assessing project performance. Project complexity can be quantified and visualised effectively with the application of the fuzzy AHP. This chapter enhances the understanding of construction project complexity and fuzzy hybrid computing in construction engineering and management. Future research should address the calibration of fuzzy membership functions in pairwise comparisons for each individual decision maker and develop computational tools for solving optimisation problems in the constrained fuzzy AHP. In the area of construction project complexity, future research should investigate how scarce resources are allocated to better manage complex projects and how appropriate resource allocation improves their performance.

The purpose of this paper is to improve the complicated pairwise comparison problem and the consistency of analytic hierarchy process (AHP), the consistent fuzzy preference relation (CFPR) method is applied to select the best fashion design scheme in this study.

The first stage is to review the traditional AHP for fashion design scheme evaluation. The second stage is based on the procedure of CFPR to select the best fashion design scheme. The procedure includes: establishment of the fuzzy preference relation matrix of pairwise comparisons, calculation of criteria weight, and calculation of the evaluation value for ratings of fashion design schemes with respect to criteria. The final stage is to compare the procedures and results between AHP and CFPR for the evaluations of fashion design schemes.

For fashion design scheme selection, there are 76 data for fashion design scheme evaluation in AHP, but only 31 in CFPR. Comparing both AHP and CFPR methods, the rankings of the criteria weight are identical and the priority scores of the fashion design scheme are similar. The CFPR is more efficient than AHP, obviously, to solve the inconsistency of hierarchical decision-making problem.

This paper proposes the CFPR method for the selection of the best fashion design scheme. According to the finding of this study, the CFPR is proposed as a practicable option for solving complicated pairwise comparison problems in fashion design decision.

This paper aims to provide insight into how knowledge resources in R & D organizations can be effectively and separately measured for knowledge sharing and transfer. Knowledge is recognized as a durable strategic resource to obtain sustainable competitive advantage.

The paper proposes a theoretical framework integrating an analytic network process (ANP) with a balanced scorecard (BSC) to measure the performance of knowledge resources under value perspective. Four indicators and three knowledge value (KV) components including labor value, technology value and utilization value are discussed. The model construction, problem structuring and calculation procedure for measuring the performance of knowledge resources based on ANP and BSC are demonstrated.

Despite a number of models to assess the performance of knowledge resources being proposed, they highlighted a need for separately measuring under value perspective. With the aim of filling this gap, the main finding of the paper is to clarify relevant issues, providing a better framework for assessment of the performance of knowledge resources.

To handle the dynamic nature of knowledge, the research should take into account more advanced methods to measure the performance of knowledge resources. Both qualitative and quantitative methods should be utilized in future research.

The consequences of measuring the performance of knowledge resources under value perspective may help managers to organize and arrange the separate knowledge resources, improving the knowledge resources exchange between different institutions in R & D organizations.

The main contribution of this paper lies in the development of a comprehensive model, which incorporates diversified issues for conducting the performance of knowledge resources under value perspective.

Although the multi-criteria technique analytic hierarchy process (AHP) has successfully been applied in many areas, either selecting or ranking alternatives or to derive priority vector (weights) for a set of criteria, there is a significant drawback in using this technique if the pairwise comparison matrix (PCM) has inconsistent comparisons, in other words, a consistency ratio (CR) above the value of 0.1, the final solution cannot be validated. Many studies have been developed to treat the inconsistency problem, but few of them tried to satisfy different quality measures, which are minimum inconsistency (fMI), the total number of adjusted pairwise comparisons (fNC), original rank preservation (fKT), minimum average weights adjustment (fWA) and finally, minimum L1 matrix norm between the original PCM and the adjusted PCM (fLM).

The approach is defined in four steps: first, the decision-maker should choose which quality measures she/he wishes to use, ranging from one to all quality measures. In the second step, the authors encode the PCM to be used in a many-objective optimization algorithm (MOOA), and each pairwise comparison can be adjusted individually. The authors generate consistent solutions from the obtained Pareto optimal front that carry the desired quality measures in the third step. Lastly, the decision-maker selects the most suitable solution for her/his problem. Remarkably, as the decision-maker can choose one (mono-objective), two (multi-objective), three or more (many-objectives) quality measures, not all MOOAs can handle or perform well in mono- or multi-objective problems. The unified non-sorting algorithm III (U-NSGA III) is the most appropriate MOOA for this type of scenario because it was specially designed to handle mono-, multi- and many-objective problems.

The use of two quality measures should not guarantee that the adjusted PCM is similar to the original PCM; hence, the decision-maker should consider using more quality measures if the objective is to preserve the original PCM characteristics.

For the first time, a many-objective approach reduces the CR to consistent levels with the ability to consider one or more quality measures and allows the decision-maker to adjust each pairwise comparison individually.

To provide customer‐oriented group decision methodology for designers or developers in using quality function deployment which is based on voice of customer.

Technical importance rating in house of quality (HoQ) should be evaluated considering both the roof and relationship matrix. Since the roof is generally irreducible, all of relationships between customer attribute (CA) and engineering characteristic (EC) are evaluated. A customer‐oriented evaluating method is proposed and empirical test is issued.

The phenomenon of inconsistency which is frequently found in HoQ is easily protected by proposed approach which focuses on the view of customer.

The proposed evaluating method is appropriate for the time when the number of ECs or CAs are greater than nine. If the number of alternatives is less than nine, analytic hierarchical process is usually used. However, 1‐9 scaling pairwise comparison is not suitable for customers such as non‐experts, housewives, or even children.

Especially, the proposed evaluating method could be widely used for organizations depending on customers.

In various fields, this paper supports the customer‐centered environment.

World-class total productive maintenance (TPM) status depends on critical success factors (CSF) to be properly implemented. The relevant literature has identified several CSF; however, researchers have not investigated the degree of importance of each phase of the process. The purpose of this paper is to prioritize the CSFs that influence TPM implementation during each phase of the process in order to aid decision making in companies.

The main CSF are identified from a literature review. This paper focusses on the judgments of managers who are experts in TPM implementation in companies which have received TPM awards for excellence. The judgments are processed using the analytic hierarchy process (AHP) method. Three aggregation methods (geometric mean, Copeland and fuzzy) are employed for comparative analysis.

Although the literature highlights some important CSF, the relevance of these factors is not the same in each phase of TPM implementation. Analysis shows that ranking using the Copeland method is most coherent.

This research was carried out in some Brazilian companies.

If managers are aware of the CSF to be prioritized in each phase, this facilitates decision making, resulting in a more effective implementation of TPM.

If TPM implementation is effective, this stimulates the personnel involved and avoids the possibility of the program being abandoned.

The originality of this paper consists in the proposed model to prioritize CSF during each phase of the implementation of TPM.

This study aims to provide a good insight into the use of analytic network process (ANP), a multi‐criteria decision‐making methodology in selecting and benchmarking enterprise resource planning (ERP) systems.

In this study, ANP model is proposed with an actual case example in selecting the best ERP system as a framework to guide managers.

This model provides firms with a simple, flexible and easy to use approach to evaluate ERP systems efficiently. Findings demonstrate that the ANP model, with minor modifications, can be useful to all firms in their ERP system selection decisions.

ANP is a highly complex methodology and requires more numerical calculations in assessing composite priorities than the traditional analytic hierarchy process and hence it increases the effort.

This is probably the first time that an attempt has been made to apply the ANP model in ERP system selection decisions. ANP has the ability to be used as a decision‐making analysis tool since it incorporates feedback and interdependent relationships among decision criteria and alternatives. In addition, evaluation and selection of ERP system software can be very useful for both academic research and practice.

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 purpose of this research is to explore the critical success factors of mobile animation games, by exploring the game itself, information systems, game motivation and promotional activities, as well as conducting research and analysis on mobile animation game players.

This research used the Analysis Hierarchy Process (AHP) method and the consistent fuzzy preference relationship for data analysis. In this study, collect 1,286 valid questionnaires through online questionnaire surveys. And comparing the two games “Legend Showdown” and “Tower of Gods and Demons”, players believe that the more successful mobile animation game is “Legend Showdown”.

Through experimental design, and the consistent fuzzy preference relationship for data analysis. The results found that the critical factors considered by the player in relation to the mobile animation game were firstly the information system, followed by promotional activities, game motivation and finally the game itself.

Because this research does not involve the concept of fuzzy theory at all, it is easy to produce subjective, uncertain and ambiguity issues when comparing pairwise. We recommended that follow-up researchers can use fuzzy semantic preference relations to solve this problem.

This study proposed a new approach that takes the critical factors for the mobile animation game. According to the research results, the critical success factor of mobile animation games is the information system, as it could provide a reference direction for game manufacturers when designing or formulating marketing strategies in the future.