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The aim of this study is to present a model for service supply chain performance evaluation (SSCPE) based on fuzzy cognitive mapping (FCM).

Despite the unique nature of services, which distinguishes them from goods, the performance evaluation of service supply chains (SSCs) has still not received adequate attention from researchers or practitioners. With the help of in-depth interviews conducted with insurance industry experts in Iran, the performance measures of SSCs are defined, and the relevance between the performance measures, which are based upon the knowledge of experts in this field, are presented as a fuzzy cognitive map.

By blocking the aggregate map of experts, a model for SSCPE is developed that discusses performance measures and metrics of strategic, tactical and operational SSC processes, such as service-providing management, service-enabling management, market management, cash-flow management, customer-relationship management, supplier-relationship management, knowledge- and information-flow management and risk management. Indexes of FCM models indicate that the supply chain service quality and strategy blocks have the most importance compared with others.

The paper develops an original SSCPE model that can be used as a basis for SSC improvement and develops an excellence model for SSC.

The developing academic field of machine ethics seeks to make artificial agents safer as they become more pervasive throughout society. In contrast to computer ethics, machine ethics is concerned with the behavior of machines toward human users and other machines. This study aims to use an action-based ethical theory founded on the combinational aspects of deontological and teleological theories of ethics in the construction of an artificial moral agent (AMA).

The decision results derived by the AMA are acquired via fuzzy logic interpretation of the relative values of the steady-state simulations of the corresponding rule-based fuzzy cognitive map (RBFCM).

Through the use of RBFCMs, the following paper illustrates the possibility of incorporating ethical components into machines, where latent semantic analysis (LSA) and RBFCMs can be used to model dynamic and complex situations, and to provide abilities in acquiring causal knowledge.

This approach is especially appropriate for data-poor and uncertain situations common in ethics. Nonetheless, to ensure that a machine with an ethical component can function autonomously in the world, research in artificial intelligence will need to further investigate the representation and determination of ethical principles, the incorporation of these ethical principles into a system’s decision procedure, ethical decision-making with incomplete and uncertain knowledge, the explanation for decisions made using ethical principles and the evaluation of systems that act based upon ethical principles.

To date, the conducted research has contributed to a theoretical foundation for machine ethics through exploration of the rationale and the feasibility of adding an ethical dimension to machines. Further, the constructed AMA illustrates the possibility of utilizing an action-based ethical theory that provides guidance in ethical decision-making according to the precepts of its respective duties. The use of LSA illustrates their powerful capabilities in understanding text and their potential application as information retrieval systems in AMAs. The use of cognitive maps provides an approach and a decision procedure for resolving conflicts between different duties.

This paper suggests that cognitive maps could be used in AMAs as tools for meta-analysis, where comparisons regarding multiple ethical principles and duties can be examined and considered. With cognitive mapping, complex and abstract variables that cannot easily be measured but are important to decision-making can be modeled. This approach is especially appropriate for data-poor and uncertain situations common in ethics.

The purpose of this paper is to apply a fuzzy LinPreRa cognitive map to evaluate the interaction and importance of factors affecting the development of strategic alliance partnerships between the outlying island duty-free shops and existing collaboration firms in duty-free shops. Meanwhile, the key factors should be considered in establishing strategic alliance partnerships while analyzing and comparing the perspectives of owners for outlying island duty-free shop and partner vendors of collaborating firms along with differences of influencing key factors on partnership quality.

This study incorporates a fuzzy linguistic preference relation analytical network process (fuzzy LinPreRa ANP) in the fuzzy cognitive map (FCM) method to formulate a fuzzy LinPreRa cognitive map to evaluate the interactions and importance of key factors and the conditions of interactive impacts during the establishment of strategic alliance partnerships. The authors use the outlying island duty-free shops in Taiwan as the empirical subject to illustrate how the fuzzy LinPreRa cognitive map is applied. In-depth, interviews and questionnaire surveys are conducted to collect and evaluate respondents concerning key factors affecting strategic alliance partnerships establishment.

The following three findings based on the results of empirical analysis: first, the administrative behavioral patterns of managers for strategic alliance partnerships encompass shared values and goal coherence, while the associative statements are located on the first layer of fuzzy LinPreRa cognitive map core associations, which illustrates that businesses attach great importance to conceptual ideas. Second, integrity and reputations of both parties are the governing mechanism of strategic alliance partnerships, influencing mutual reputation. Third, the relationship of strategic alliance partnerships refers to the profit opportunities of both parties and their ability to respond to the market, including future development, regional indicators, marketing capabilities, brand multiplicity and customer retention. However, it can be inferred that such associative factors are located in the outer layer or belong to noncore associations, which means that both parties’ abilities to respond to market reactions are weakened.

This study provides valuable relationship managerial strategies to maintain long-term partnerships for outlying island duty-free shops and their alliance collaborating firms including strengthened relationships of both parties’ managers to achieve common values and consistent objectives; improved beneficial value of both parties in strategic alliance partnerships; continued close communications to enhance the quality of strategic alliance partnerships; and establishment of personnel training mechanisms and strict formulation of management rules for strategic alliance partnerships.

The main valuable contributions are included the fuzzy LinPreRa cognitive map by combining two different decision methods including FCM and fuzzy LinPreRa ANP is proposed to help decision makers to improve the evaluation quality and calculation efficiency for critical elements’ interaction and importance; the fuzzy LinPreRa cognitive map can clarify considering significant factors when maintaining strategic alliance partnerships and further provide valuable relationship managerial strategies to maintain long-term relationships for duty-free shop owners and their alliance collaborating firms.

Noting the scarcity of complexity techniques applied to modelling social systems, this paper attempts to formulate a conceptual model of decision‐making behaviour within the information systems evaluation (ISE) task, against the backdrop of complexity theory.

Complexity theory places an emphasis on addressing how dynamic non‐linear systems can be represented and modelled utilising computational tools and techniques to draw out inherent system dynamics. In doing so, the use of fuzzy cognitive mapping (FCM) and morphological analysis (MA) (hence a fuzzy‐morphological approach), is applied to empirical case study data, to elucidate the inherent behavioural and systems issues involved in ISE decision making within a British manufacturing organisation.

The paper presents results of applying a combined FCM and MA approach to modelling complexity within management decision making in the ISE task: both in terms of a cognitive map of the key decision criteria; a matrix of constraint criteria; and a synthesised model that provides an indication of the linkages between technology management factors and organisational imperatives and goals. These findings show the usefulness of viewing the topic in complexity science terms (emergent behaviour, non‐linearity and chaotic response).

This research is limited in applying the given technique to a single case study organisation in the UK manufacturing sector, where the sample size is limited. Since this is the first time that such a combined MA‐FCM technique has been used in this field known to the authors, future research needs to validate and explore the implications of this approach in a wider context (multiple organisations and viewpoints).

The paper highlights the need for those involved in analysing managerial decision making to include aspects of complexity theory in their evaluations – namely uncovering inherent inter‐relationships that may exist between stakeholders, processes and systems. In doing so, expanding the manager's understanding of how to achieve congruence between driving forces and factors, which may exhibit non‐linear, chaotic or feedback behaviour.

The given research brings together both artificial intelligence and operational research techniques, applied in the socio‐technical milieu of information systems evaluation, within the context of complexity theory, in order to describe the rich detail within the ISE decision‐making task.

The concept of smart city has recently become more topical in academic and policy discussions. This idea is considered a complex, non-consensual subject since its definition has not yet been agreed upon by most authors in the relevant fields. The need to identify and measure smart city indicators has also given rise to many different evaluation procedures. However, the available frameworks have yet to overcome challenges in structuring and measuring all the evaluation parameters of the cities in question. Thus, methods still need to be developed and applied that can structure criteria used to assess smart city success.

This study sought to show cognitive mapping's tangible usefulness as an expedient tool for strategic analysis, using smart cities as a complex object of study. To this end, various cognitive maps were constructed and compared using the Strategic Options Development and Analysis (SODA) approach.

Cognitive mapping's advantages and limitations in the strategic visualization research context are analyzed and discussed.

The authors know of no prior work reporting comparative analysis of this methodological approach in the same research context.

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.

Developments in the world of distributed computing have made possible the successful integration of diverse information systems working in different environments. Electronic government (eGovernment) provides governmental stakeholders with a wealth of information stored at the various entities in the organisation. Decision makers are often overloaded with the amount of information that they receive. Notwithstanding the logistics of information flows from government bodies to citizens, the flow of information between various entities with national and local government organisations has become a critical issue. As a result, this paper seeks to analyse the logistics of information decision‐making flows, within an eGovernment implementation, by modelling and extrapolating those key decision factors via a cognitive mapping approach.

The paper adopts a multi‐method approach in terms of combining an empirical qualitative case study with a quantitative analytical simulation technique for analyzing decision‐making behaviour relating to policy considerations within the eGovernment realm in a Gulf municipality, through the use of a Fuzzy Cognitive Mapping (FCM) approach.

By using the FCM approach, the paper was able to highlight the unique interplay between eGovernment stakeholders in the case context, whereby inherent relationships were shown to exist between decision‐making eGovernment stakeholders and the consumers of eGovernment information. Thus, project management information, relationships and deployment; evaluation of information systems, relationships and policy, change management policy and processes, system validation, processes and deployment; and alignment with strategic eGovernment drivers, deployment with policy are identified.

This realisation of the demand and supply of the underlying logistics information management needs, within an eGovernment context, provides an understanding of the principal factors which drive and define those technological and organisational challenges experienced by the eGovernment municipality. By exploring these factors through a combination of qualitative discourse and quantitative simulation, it is subsequently shown that an abundance of information exists within a seemingly placid organisational system, the basis for which resides in the constant flow of information between and among stakeholders, processes, and systems.

The paper uses a combination of a qualitative case research with quantitative analysis/simulation technique in order to identify inter‐relationships in the decision‐making criteria of a Gulf‐based municipality in order to shed light on the key components of their policy control.

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 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 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.