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The purpose of this paper is to explore the relationship between effective strategies to improve the quality and quality management of allocated resources for the successful implementation of the strategies. For this purpose, three quality management resources (human, organizational and technological) and eight different strategies related to quality are considered.

The paper employs the fuzzy analytic network process (FANP) to prioritize and model the interactions between eight strategies, the three types of resources (human, organizational and technological) needed for effective strategy implementation and the ability to enhance quality. Then, Goal Programming (GP) is formulated by the output of the FANP to identify the extent to which each single strategy is inhibited by a lack of (or overloaded by) resources.

The first three priorities of strategies identified by the FANP include continuous management of quality system, continuous use of human knowledge and continuous approach toward target, and the order of resources is as follows: human resources, organizational resources and technological resources. The results obtained showed the largest share of human resources and its crucial role in improving the quality of the products. The contribution of organizational resources amounts to half of the contribution of human resources.

The main contribution of this paper is to employ the FANP to prioritize, whereas in prior studies in this area, priorities were conducted as definitive, and uncertainty in the opinion of experts was not considered. In this paper, the FANP–GP combined method is used.

In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to review and compile the current AI methods used for cost-risk assessment in the construction management domain in order to capture complexity and risk interdependencies under high uncertainty.

This paper makes a content analysis, based on a comprehensive literature review of articles published in high-quality journals from the years 2008 to 2018. Fuzzy hybrid methods, such as fuzzy-analytical network processing, fuzzy-artificial neural network and fuzzy-simulation, have been widely used and dominated in the literature due to their ability to measure the complexity and uncertainty of the system.

The findings of this review article suggest that due to the limitation of subjective risk data and complex computation, the applications of these AI methods are limited in order to address cost overrun issues under high uncertainty. It is suggested that a hybrid approach of fuzzy logic and extended form of Bayesian belief network (BBN) can be applied in cost-risk assessment to better capture complexity-risk interdependencies under uncertainty.

This study only focuses on the subjective risk assessment methods applied in construction management to overcome cost overrun problem. Therefore, future research can be extended to interpret the input data required to deal with uncertainties, rather than relying solely on subjective judgments in risk assessment analysis.

These results may assist in the management of cost overrun while addressing complexity and uncertainty to avoid chaos in a project. In addition, project managers, experts and practitioners should address the interrelationship between key complexity and risk factors in order to plan risk impact on project cost. The proposed hybrid method of fuzzy logic and BBN can better support the management implications in recent construction risk management practice.

This study addresses the applications of AI-based methods in complex construction projects. A proposed hybrid approach could better address the complexity-risk interdependencies which increase cost uncertainty in project.

The purpose of this paper is to overcome the drawbacks of analytic hierarchy process in solving complex decision-making problems, especially for the evaluation of enterprise technology innovation ability (ETIA). Because interval type-2 fuzzy sets (IT2 FSs) can handle uncertainty linguistic variables in a more flexible and precise way than type-1 fuzzy sets with their second fuzzy membership functions, a fuzzy ANP method with IT2 FSs is proposed to evaluate the ETIA.

The criteria of evaluation on ETIA are identified and an evaluation model for ETIA is constructed on the basis of the application analysis of ETIA and theoretical design of ANP. In addition, two different ranking methods of IT2 FSs are applied in processing the relationships between influence factors of ETIA.

By using the proposed interval type-2 fuzzy ANP (IT2 FANP) method, the efficiencies of the whole evaluation of ETIA can be measured and the important factors in the ETIA can also be determined. Compared with the type-1 FANP through the ranking results, the proposed IT2 FANP is more reasonable and robust for the evaluation of ETIA.

The proposed IT2 FANP method is applied on the evaluation of ETIA. With respect to the application, the proposed method can be used to evaluate many more complex problems that contain feedback and circular relationships.

The proposed IT2 FANP approach can solve the complexities and uncertainties at the same time. Considering the subjective initiative of decision-makers and the feedback between influence factors, the proposed method is more efficient than the existing type-1 approaches in the literature.

The purpose of this paper is to identify the barriers of knowledge management (KM) implementation in Alborz Province industrial Parks Corporation and prioritize them using fuzzy analytical network process (FANP).

Through an in-depth review of the literature on KM and researcher findings from observations and interviews with experts, the main barriers of KM implementation, namely, organizational culture, organizational structure, human resource, technology and miscellaneous factors along with their related factors in the surveyed organization were identified. Then, based on the information gathered, an expert questionnaire was developed. Finally, the priority of each main barrier and their sub-factors were determined using FANP.

The results show that human resource and organizational culture factors with the weights of 0.66 and 0.22, respectively, have the highest ranking and therefore are the most important barriers. The technology factor with the weight of 0.00002 is the least important barrier in implementing KM in the surveyed corporation.

One of the limitations of this study is the generalizability of the findings, which may be limited by the single case study method used.

There are fewer studies about KM barriers specifically with a focus on prioritizing them in organizations, especially in the context of Iran as a developing country. This study develops a comprehensive and solid mathematical technique to prioritize the identified barriers of KM implementation in the context of Iran.

The purpose of this paper is to propose an instrument to evaluate the collaboration quality of sustainable supply chains by considering collaboration behaviour and sustainability factors.

The proposed model integrates Quality Function Deployment (QFD), Fuzzy Analytical Network Process (FANP) and Data Envelopment Analysis (DEA) to assess the efficiency score of each stakeholder involved. A case of a sugar company in Indonesia was analysed as the illustration of the application of the model.

The integrated QFD-FANP-DEA method enables to incorporate collaboration behaviour and sustainability factors in a single assessment model. The results of the case study showed the benchmarking results associated with the performance variance of stakeholders and the number of samples.

Future research could consider other DEA approaches, extend the research by simulating a different number of scenarios and evaluating the improvement/deterioration, and expand the scope of collaboration.

Each stakeholder will be able to obtain the collaboration assessment results, and the improvements suggested by the model.

Smallholders and farmers will be able to increase their benefits by using the existing resources.

This paper provides a methodological contribution by introducing new collaboration quality assessment methods that can accommodate any variance in multi-stakeholders, involve qualitative and quantitative measurements, and benefit all stakeholders.

The purpose of this paper is to determine the criteria weights of outsourcing and their key role in ranking outsourcing suppliers.

A new hybrid multi-criteria decision-making approach merges three tools, namely, decision making trial and evaluation (DEMATLE), fuzzy analytic network process (FANP) and ordinal/cardinal data envelopment analysis (DEA) model. Afterwards, experts’ opinions were gathered from a Pipe and Fittings company. Finally, their opinions were incorporated in three-stage approach for outsourcing suppliers’ selection.

The findings of this study show that among the selective criteria for outsourcing, business development, focus on basic activities and order delays are the three most important criteria. Also, the proposed approach ranks suppliers to facilitate decision making for selection.

The number of suppliers, selection criteria and the number of members of the respondents’ team have been identified as some of the limitations of the present study.

The study has significant and practical implications for the managers and for the organizations which have to choose top suppliers, particularly in the case of dealing with numerous and qualitative/quantitative criteria.

This paper proposed a new three-stage approach that incorporates outputs of previous as inputs of next stage to increasing results accuracy. Also, it showed that by incorporating results of FANP method into DEA model, key role of experts’ opinions as a qualitative and quantitative criteria can be caused by increasing flexibility of decision process.

The purpose of this paper is to develop a fuzzy analytic network process (FANP) model to select the maintenance policy of an acid manufacturing company.

Four maintenance strategies of Corrective Maintenance (CM), Time-Based Maintenance (TBM), Condition-Based Maintenance (CBM) and Shutdown Maintenance (SM) are investigated to be considered for seven equipment of the case study. These equipment are almost new and include boiler, molten sulfur ponds, cooling towers, absorption tower, converter, sulfur fuel furnace and heat exchanger. Chang’s extended analysis has been employed to deal with fuzzy data and analyze the fuzzy decision matrices. The proposed approach is applied to a sulfuric acid production plant and the suitable maintenance policy is found for all seven equipment of the company.

Based on the obtained results, the CBM policy is appropriate for high-risk (cooling tower) and high added value equipment (absorption tower). In addition, TBM is selected for boiler and converters while SM is selected for molten sulfur ponds. Finally, high-cost, low-risk and low added value equipment (sulfur fuel furnace and heat exchanger) are more appropriate with CM policy.

This research presents a novel idea to consider cost, risk and added value in the context of maintenance policy selection. From the methodological and theoretical features, this research offers new insights in this area since, to the best of the authors’ knowledge, no comparable study has been conducted before.

The purpose of this paper is to determine as to develop a fuzzy multi-criteria decision-making (MCDM) algorithm with self-check capability that can solve any manufacturing company's printed circuit boards (PCB) design computer aided design (CAD) tool selection problem and to implement it.

An algorithm that consists of two sub-algorithms that use same inputs and alternative pool is developed, thus self-check capability is introduced. The first sub-algorithm designed as an integration of fuzzy AHP and TOPSIS, where the second sub-algorithm composes of fuzzy analytic network process and TOPSIS. Fuzzy set theory and linguistic variables were utilized to handle uncertainty and usage of verbal expressions, respectively. MATLAB programming language was used for the implementation. The used MCDM methods’ and fuzzy set theory's explanations are given along with the literature review prior to real life application of the developed algorithm.

A MCDM algorithm with self-check capability is introduced. Moreover, a practical decision aid tool is generated for the usage of the manufacturing companies that are related with PCB design.

A practical computerized MCDM aid tool is generated. Using the tool let the manufacturers, i.e. high-tech device manufacturers, evaluate available PCB CAD design tools with respect to tangible and intangible criteria, and obtain a reliable result.

Self-check capability is incorporated into the decision process. Along with this capability, although the decision-making process takes place in a fuzzy environment, result of the algorithm becomes more reliable than the ones deprived of this characteristic. Furthermore, a practical computerized MCDM aid tool is generated.

This paper aims to provide a quantitative basis to analytically determine the ranking of the brand personality of Adidas, Asics, Nike, Puma and Saucony brands among Iranian customers via a conventional multi-criteria decision-making (MCDM) method.

Data for determining the importance of evaluation criteria and ranking of brands are gathered by means of distributing questionnaires among a group of Iranian customers of sport shoes, as well as some industrial experts. The fuzzy analytic network process (FANP) was used to rank the brands with regard to dependencies between criteria and alternatives.

The results indicate that FANP is a capable method which provides invaluable insights for strategic marketing decisions in the sport product industry. Results show Adidas has the best performance in the sports shoe market compared to the other four brands. In this study, it was found that expertise sophistication was the most important criterion among Aaker’s five main criteria.

The value of this paper is applying FANP decision-making method for ranking sport shoe brands. This method has not been commonly used in the area of marketing, hence it is added to the pool of techniques used in ranking brands. In addition, evaluation and ranking of brands can be very useful for both academic research and practice. Researchers can benchmark the competences of each brand through evaluating them, and industrialists can extract the competitive advantages of the selected brands.

This chapter of the book aims to achieve sustainability and productivity in light of the interaction between managers and engineers in a lean and agile supply chain management system in today’s organizations. The main innovation of this chapter is the use of the balanced scorecard (BSC) model and fuzzy analysis network process (FANP) to create a suitable platform for the realization of this interaction between managers and engineers and to identify exactly which expert system is ideal for the main purpose. Indeed, this chapter introduces its readers to the application of strategic management tools such as the BSC accompanied by FANP in the elements of supply chain management where data analysis of lean and agile networks in supply chain management can create a competitive advantage in the organization.