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The purpose of the chapter is to study the possibility of applying modern intellectual methods and technologies of decision-making for managing complex poorly structured systems.

The methodology of the chapter includes fuzzy cognitive approach, analysis of causal connections, dynamic modeling with application of the impulse processes tools, sustainability analysis of the studied system, and scenarios analysis.

The authors offer fuzzy cognitive approach to modeling the risk management system of commercial Bank POS-loaning processes. The simulated system is represented as a fuzzy-oriented weighted multigraph with a pulse action transmitted through it. The modeling process is implemented in the form of successive execution of the following stages: determining the goal, formation of fuzzy cognitive map, dynamic modeling with application of impulse processes tools, and scenarios analysis of development situation and selection the best.

The developed model of management system is a basis for analyzing the tendencies of various situations development that appear during work of banks in the express loaning segment. It allows forecasting and modeling the strategies of behavior as a reaction to external influences and to determine trajectories of management that allow reducing the internal risks of commercial Bank POS-loaning processes. Fuzzy cognitive approach is an effective tool for decision support during risk management in activities of a commercial bank and could be used for modeling and analysis of functioning and other poorly structured socioeconomic systems.

This chapter discusses the application of fuzzy cognitive map (FCM) modelling to construction management (CM) challenges and problems. It focuses on the critical issue of managing the complexity and uncertainty inherent in CM by providing a new intelligent layer that enhances classical approaches to construction modelling and management. It investigates how the myriad types of internal and external factors affecting the feasibility and performance of construction projects can be modelled using a fuzzy hybrid method that explores the complex relationships among many contributing factors and assesses and evaluates their impacts on past and future projects. This chapter proposes a hybrid modelling approach in the traditional context of cost, schedule and risk management and describes how augmenting and enhancing existing state-of-the-art tools and processes in CM can assist construction managers. This chapter provides a background on the theory of FCMs, presents foundational and current research, and explains how to apply this approach in the CM domain. This chapter also provides a detailed description of how to develop, modify and employ interactive models to specific CM challenges and problems. It includes a customisable, interactive base model and demonstrates how the model has been applied to specific CM events and issues. Examples are presented that highlight the interplay between project-specific goals and characteristics and the way these impact the interrelated and often opposing triad of cost, schedule and risk. The presented examples and practical applications make this state-of-the-art approach useful to both academic and industry practitioners.

This paper aims to propose a new genetically evolved fuzzy cognitive mapping approach as a decision-making framework for analyzing the relationships between the drivers and strategies for green computing adoption.

A focus group discussion among stakeholders in the Philippines is used to establish the relationships between the drivers and strategies of green computing adoption.

The proposed approach significantly reduces the time complexity for developing the fuzzy cognitive maps and provides a basis for comprehensively clustering drivers and strategies that share similar characteristics.

This paper’s results provide insights into how the drivers and strategies of green computing adoption facilitate the intention of adopting stakeholders. Moreover, it provides a framework for analyzing structural relationships that exist between factors in a compliant manner.

To the best of the author’s knowledge, the paper is the first to analyze the drivers and strategies of green computing under a complex systems’ perspective. Moreover, this is the first study to offer lenses in a Philippine scenario.

The evaluation of readiness provides insight into the readiness of its individual components for successful accomplishment of tasks. This study aims to evaluate readiness in leagility of supply chains based on the design and analysis of fuzzy cognitive maps (FCM) and interpretive structural modeling (ISM).

On the basis of the purpose of this study, data are gathered via the Delphi method. Moreover, FCM and ISM are also used to evaluate readiness.

Findings initially demonstrate a categorization of factors influencing leagility into static and dynamic variables according to the degree of their influence derived from the resultant behavior of FCM and ISM. It is also found that evaluating readiness in leagility of supply chains with ISM and FCM was done with respect to the type and role of the study variables, which were determined within the minimum and maximum ranges of 20 to 100 per cent, respectively.

The evaluation of the readiness using the FCM and ISM is proved to be more efficient than other classical methods. Experimental results of the study contribute to improve readiness of leagility of supply chain as well as develop functional areas of business.

The purpose of the paper is to bring attention to documentary credits and the efforts to reduce debt obligations in credit history is recognized as an important source of uncommitted bank earnings. Credit risk has a significant impact on the stability of the banking system. This paper identifies the types of credit risk in the banking supply chain.

The authors model the types of credit risk using the intuitive fuzzy failure modes and effects analysis (IFMEA) and intuitive fuzzy cognitive mapping. The population of the study that is needed for the interviews and expert panels comprises senior managers and experts of a leading bank in Iran. The respondents are experienced in credit and banking risk and were selected through judgment sampling and snowballing.

The findings suggest that reducing the risks of the foreign letters of credit contracts can mitigate the risk in the agricultural sector, the specific risks of rent-to-own contracts, the risk of the long-term facilities and the specific risk of the domestic letter of credit contracts.

This research investigates Iran Tejart Bank’s credit risk, formulates a model of the types of credit risk present and analyzes them using the intuitive fuzzy failure modes and effects analysis and intuitive fuzzy cognitive map. Through this credit risk model, one can then facilitate risk management for better financial stability. Also, the model can be used to evaluate the risk indicators.

The purpose of this paper is to explore a very new approach of creating scenarios with fuzzy cognitive maps (FCM); specifically to create scenarios for wind energy deployment.

In this paper a small exercise is conducted to illustrate the usefulness of FCM‐based scenarios.

Scenario‐based planning is often used in technology management and scenarios are generated to cater for uncertainty and facilitate development of responsive and robust strategic plans. Scenario analysis helps to identify different alternatives of the future state of technologies, needs, policies and environment. Scenario planning helps to overcome thinking limitations by presenting multiple futures. FCMs are based on causal cognitive maps and combine the benefits of both qualitative and quantitative analysis. Domain knowledge of multiple experts can be integrated into an FCM to present collective knowledge base.

This is a conceptual paper exploring use of fuzzy cognitive maps to create scenarios for wind energy deployment. The paper provides scenarios and a way to integrate them into technology roadmaps.

This study aims to explore the influencing factors of online tourism service quality to clarify the relationship between such factors and the degree of influence so that targeted and effective measures to improve service quality can be suggested.

A questionnaire is used to obtain original data, establish the fuzzy cognitive map (FCM) structure chart model and modify the model.

The results reveal that comprehensive service types, comprehensive information provided, true and accurate, upgrade and update, payment security, data and information security, customer rights and interests protection, service friendliness and evaluation processing are the key influencing factors in online tourism service quality. In addition, the FCM can also predict the improvement of service quality.

To establish an FCM model, this study establishes the evaluation framework of influencing factors of online tourism service quality and identifies the cause and effect of 26 indicators. The mechanism of influencing factors of online tourism service quality is explored through the iteration of the model.

Because container terminals (CTs) are broker organizations, their interest has complex, various internal and external factors, the purpose of this study is to scrutiny and structure the factors affecting the interests of the CT.

In terms of purpose, this study is a developmental study that, are identified the factors related to the interests of the CT through studying the library and interviewing experts and then the degree of influence of each factor on each other by using the interview with experts of CT in Bushehr province are determined. Then, the fuzzy DEMATEL method is used to calculate the feedback loop of the indicators, and then the matrix obtained Fcmapper software and the fuzzy cognitive map (FCM) is drawn.

According to the FCM analysis, three important factors are centrality identified in terms of attracting capital, quality of service and efficiency. In addition, there are three factors, attracting capital, operator performance and law have high outdegree.

This research has identified 34 effective indicators of CT interests and evaluated their relationship with FCM. In the available researches, all these indicators measurement has not been evaluated together. Furthermore, fuzzy DEMATEL has been used to evaluate self-loops. Another contribution of this research is the introduction of a strategic route as a roadmap for CT managers in Bushehr province to decide on the interests of a CT.

This study explores how entrepreneurs modify their financial path(s) and go beyond job security to attain greater financial freedom. The present work examines the cash-flow quadrant (CFQ) attributes and demonstrates the importance of the push-pull factors for an individual's quadrant transition in achieving financial freedom.

A hypothetical model and an abductive approach were used through regression models in a population sample of 260 Bahraini entrepreneurs. Fuzzy participatory cognitive mapping was also used to develop a conceptual model of financial path transition's decision making among entrepreneurs and study the impact of certain push-pull factors on the entrepreneurs' decisions.

The triangulated study identifies six categories of variables: financial freedom, workplace condition, independence, salary level, family life-building and retirement savings as key pull-push factors that significantly impact financial path transition's decision. Fuzzy cognitive mapping (FCM) extends our knowledge of the dynamics of CFQ transitions from a push-pull factor perspective. The results indicate no significant differences between the variables listed in the regression model and the fuzzy cognitive map model. Four categories of pull-push factors appeared as the entrepreneurs' top rankings when ordered by complexity, centrality scores and impact weight. These categories were workplace conditions, financial freedom, independence and salary level. The findings widen the scope of knowledge of each quadrant and rationalize how and why such factors impact quadrant decisions among Bahraini entrepreneurs.

Many studies discuss the CFQ model and consider its quadrants a specific method for identifying a unique financial path to generate income. A shifting quadrant occurs when individuals want to change their financial path and move beyond job security to achieve more financial freedom. Although this transition is well-established in the literature, the factors accounting for the individual's transition across quadrants have not received enough attention. This study fills this gap and calls for more in-depth investigations of this area to better understand the dynamics of CFQ transitions from a push-pull factor perspective.

This article proposes a novel hybrid simulation model for understanding the complex tobacco use behavior.

The model is developed by embedding the concept of the multistage learning-based fuzzy cognitive map (FCM) into the agent-based model (ABM) in order to benefit from advantageous of each methodology. The ABM is used to represent individual level behaviors while the FCM is used as a decision support mechanism for individuals. In this study, socio-demographic characteristics of individuals, tobacco control policies, and social network effect are taken into account to reflect the current tobacco use system of Turkey. The effects of plain package and COVID-19 on tobacco use behaviors of individuals are also searched under different scenarios.

The findings indicate that the proposed model provides promising results for representing the mental models of agents. Besides, the scenario analyses help to observe the possible reactions of people to new conditions according to characteristics.

The proposed method combined ABM and FCM with a multi-stage learning phases for modeling a complex and dynamic social problem as close as real life. It is expected to contribute for both ABM and tobacco use literature.