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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.

The purpose of this paper is to analyze the cause-and-effect relationship and the mutually influential level among information security control items, as well as to provide organizations with a method for analyzing and making systematic decisions for improvement.

This study utilized the Fuzzy DEMATEL to analyze cause-and-effect relationships and mutual influence of the 11 control items of the International Organization for Standardization (ISO) 27001 Information Security Management System (ISMS), which are discussed by seven experts in Taiwan to identify the core control items for developing the improvement strategies.

The study has found that the three core control items of the ISMS are security policy (SC1), access control (SC7) and human resource security (SC4). This study provides organizations with a direction to develop improvement strategies and effectively manage the ISMS of the organization.

The value of this study is for an organization to effectively dedicate resources to core control items, such that other control items are driven toward positive change by analyzing the cause-and-effect relation and the mutual influential level among information security control items, through a cause-and-effect matrix and a systematic diagram.

Big Data can be utilised for efficient use of resources and to provide better services to the resident in order to enhance the delivery of urban services and create sustainable build environment. However, the adoption of Big Data faces many challenges at the implementation level. Therefore, the purpose of this paper is to identify the challenges towards the efficient application of Big Data in smart cities development and analyse the inter-relationships.

The 14 Big Data challenges are identified through the literature review and validated with the expert’s feedback. After that the inter-relationships among the identified challenges are developed using an integrated approach of fuzzy Interpretive Structural Modelling (fuzzy-ISM) and fuzzy Decision-Making Trial and Evaluation Laboratory (fuzzy-DEMATEL).

Evaluation of interrelationships among the challenges suggests that diverse population in smart cities and lack of infrastructure are the significant challenges that impede the integration of Big Data in the development of smart cities.

This study will enable practitioners, policy planners involved in smart city projects in tackling the challenges in an optimised manner for the hindrance free and accelerated development of smart cities.

This research is an initial effort to develop an interpretive structural model of Big Data challenges for smart cities development which gives a clearer picture of how the identified challenges interact with each other.

The identification of network user relationship in Fancircle contributes to quantifying the violence index of user text, mining the internal correlation of network behaviors among users, which provides necessary data support for the construction of knowledge graph.

A correlation identification method based on sentiment analysis (CRDM-SA) is put forward by extracting user semantic information, as well as introducing violent sentiment membership. To be specific, the topic of the implementation of topology mapping in the community can be obtained based on self-built field of violent sentiment dictionary (VSD) by extracting user text information. Afterward, the violence index of the user text is calculated to quantify the fuzzy sentiment representation between the user and the topic. Finally, the multi-granularity violence association rules mining of user text is realized by constructing violence fuzzy concept lattice.

It is helpful to reveal the internal relationship of online violence under complex network environment. In that case, the sentiment dependence of users can be characterized from a granular perspective.

The membership degree of violent sentiment into user relationship recognition in Fancircle community is introduced, and a text sentiment association recognition method based on VSD is proposed. By calculating the value of violent sentiment in the user text, the annotation of violent sentiment in the topic dimension of the text is achieved, and the partial order relation between fuzzy concepts of violence under the effective confidence threshold is utilized to obtain the association relation.

The purpose of this paper is to identify the flexible manufacturing system performance variables and analyze the interactions among these variables. Interpretive structural modeling (ISM) has been reported for this but no study has been done regarding the interaction of its variables. Therefore, fuzzy TISM (total ISM) has been applied to deduce the relationship and interactions between the variables and driving and dependence power of these variables are examined by fuzzy MICMAC.

Fuzzy TISM and fuzzy MICMAC analysis have been applied to deduce the relationship and interactions among the variables and driving and dependence power of these variables are examined by fuzzy MICMAC.

In total, 15 variables have been identified from the extensive literature review. The result showed that automation, use of automated material handling, an effect of tool life and rework percentage have high driving power and weak dependence power in the fuzzy TISM model and fuzzy MICMAC analysis. These are also at the lowest level in the hierarchy in the fuzzy TISM model.

Fuzzy TISM model has been suggested for manufacturing industries with fuzzy MICMAC analysis. This proposed approach is a novel attempt to integrate TISM approach with the fuzzy sets. The integration of TISM with fuzzy sets provides flexibility to decision-makers to further understand the level of influences of one criterion over another, which was earlier present only in the form of binary (0, 1) numbers; 0 represents no influence and 1 represents influence.

The purpose of this study is to explore and prioritize the barriers that affect weather index-insurance (WII) adoption among customers by utilizing interpretive structural modelling (ISM) and fuzzy-MICMAC.

This paper utilized the combined approach in two phases. In first phase comprehensive literature study and expert mining method have been performed to identify and validate WII adoption barriers. In second phase, ISM has been utilized to examine the direct relationships among WII adoption barriers in order to develop a structural model. Further, fuzzy-MICMAC method has been utilized to analyse indirect relationships among barriers to explore dependence and driver power.

This study has identified 15 key barriers of WII adoption among customers and developed a structural model based on binary direct relationship using ISM. Later, the outcomes of ISM model have been utilized for analysing the dependence and driver power of each WII adoption barriers in cluster form using fuzzy-MICMAC. The customer awareness related WII adoption barrier are mainly at the top level, WII demand related barriers are in the centre and WII supply related barriers at the bottom level in ISM model.

The findings offered important insights for WII insurers to understand mutual relationships amongst WII adoption barriers and assists in developing strategy to eliminate dominant key barriers in order to enhance their customer base.

Based on best of author's knowledge this paper firstly integrates the ISM fuzzy-MICMAC method into identification and prioritization of barriers that affects WII adoption among customers.

Cloud eases information processing, but it holds numerous risks, including hacking and confidentiality problems. It puts businesses at risk in terms of data security and compliance. This paper aims to maximize the covered human resource (HR) vulnerabilities and minimize the security costs in the enterprise cloud using a fuzzy-based method and firefly optimization algorithm.

Cloud computing provides a platform to improve the quality and availability of IT resources. It changes the way people communicate and conduct their businesses. However, some security concerns continue to derail the expansion of cloud-based systems into all parts of human life. Enterprise cloud security is a vital component in ensuring the long-term stability of cloud technology by instilling trust. In this paper, a fuzzy-based method and firefly optimization algorithm are suggested for optimizing HR vulnerabilities while mitigating security expenses in organizational cloud environments. MATLAB is employed as a simulation tool to assess the efficiency of the suggested recommendation algorithm. The suggested approach is based on the firefly algorithm (FA) since it is swift and reduces randomization throughout the lookup for an optimal solution, resulting in improved performance.

The fuzzy-based method and FA unveil better performance than existing met heuristic algorithms. Using a simulation, all the results are verified. The study findings showed that this method could simulate complex and dynamic security problems in cloud services.

The findings may be utilized to assist the cloud provider or tenant of the cloud infrastructure system in taking appropriate risk mitigation steps.

Using a fuzzy-based method and FA to maximize the covered HR vulnerabilities and minimize the security costs in the enterprise cloud is the main novelty of this paper.

The purpose of this paper is to focus on studying the concept of “Smart Organization” and providing a comprehensive framework for the various factors as barriers for the smart organization, identifying and classifying the key criterion of these factors based on their direct and indirect relationships.

In this paper an extensive literature survey and experts’ opinion have been used to identify major barriers of smart organization. These barriers are then modeled using interpretative structural modeling (ISM) methodology. The model so developed has been further improved and an integrated model has been developed using fuzzy-MICMAC.

Various barriers of smart organization have been identified and a structural model has been developed for barriers using the ISM methodology. The critical barriers have been found out by fuzzy-MICMAC analysis. The driver power and dependence graph has been plotted for barriers. The barriers are classified into four categories which are, autonomous, linkage, dependent and independent according to their driver power and dependence. From the ISM model and the integrated model, and from further discussions with the experts, it has been found that the barriers “(B1) organizational structure” and “(B6) Managerial actions” are the two most important barriers, every other barrier is directly or indirectly driven by these.

The basis of developing the ISM model, i.e, the structural self-interaction matrix is based on experts’ opinion, therefore the result may get influenced if there is any biasing in judging the barriers. The future research scope for this paper will be to test the model generated in this paper. The testing of the model can be done by applying structural equation modeling technique, it has the capability of testing the hypothetical model. Further a framework of smart organizations can be created to find out the smartness of different organizations.

The paper can be used by organizations in understanding the barriers in becoming “smart” on the basis of their inter-relationships. This model can help manufacturing organization of North India in understanding the barriers which needs to be worked upon and the inter-relationship among these factors. This model-based study may be helpful in understanding and implementing the practices of smart organization by removing the possible critical barriers.

This is the first study to identify the barriers of smart organizations and to develop a model of these barriers using ISM and fuzzy-MICMAC.

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.

The simultaneous scheduling of resource‐constrained maintenance and operations is addressed in this work. The purpose of the paper is to capture the uncertainty in the development of a model that schedules both preventive maintenance and operational activities. Fuzzy logic is employed to transform the human expertise into IF‐THEN rules.

The approach has the advantage of revealing semantic uncertainty with the associated non‐specifying measures. The methodology applied tracks the error values in terms of results in linguistic variable.

The results obtained indicate the feasibility of tracking the uncertain measures in the model discussed. Thus, the study may be applicable to both production system and transportation organizations that are engaged in both maintenance and operational activities.

The research has serious implication in terms of the ability to monitor the imprecision that were introduced in the previous models. This obviously provides a more reliable framework for researchers and practitioners interested in maintenance scheduling activities.

The paper is new in that it demonstrates the application of fuzzy logic in a form that was never documented.