Search Results (74)

Understanding psychological change requires a quantitative framework capable of capturing the complex and dynamic relationships among personal constructs. Personal Construct Psychology emphasizes the hierarchical reorganization of bipolar constructs, yet existing qualitative methods inadequately model the reciprocal and graded influences involved in such change. This paper introduces the Presence–Balance (PB) space, a centrality measure for constructs represented within Fuzzy Cognitive Maps (FCMs). FCMs model cognitive systems as directed, weighted graphs, allowing for nuanced analysis of construct interactions. The PB space operationalizes two orthogonal dimensions: Presence, representing the overall connectivity and activation of a construct, and Implication Balance, quantifying the directional asymmetry between influences exerted and received. By formalizing Hinkle’s hierarchical theory within a rigorous mathematical framework, the PB space enables precise identification of constructs that drive or resist transformation. This dual-dimensional model provides a structured method for analyzing personal construct systems, supporting both theoretical exploration and clinically relevant interpretations in the study of psychological change. Full article

Urban green spaces play a critical role in promoting health, well-being and social inclusion. However, many such spaces remain underutilized by women due to perceived safety risks and inadequate infrastructure. The aim of this study is to understand the level of accessibility of these areas for women of different ages, considering their diverse needs related to physical activity and the sense of safety in public space. This research investigates the behavioural experiences of women in Zielona Góra, Poland, focusing on municipal parks and forests. A mixed-methods approach was applied, including on-site observations, in-depth interviews, online surveys and scenario modelling using Fuzzy Cognitive Maps (FCMs), involving 204 women aged 15–85. The results show that 48% of respondents avoid green areas due to barriers such as poor lighting, fear of wild animals or unpredictable individuals and insufficient infrastructure. Women preferred afternoon visits and valued the presence of others for increased safety. The five most frequented parks were identified based on accessibility and infrastructure quality. Scenario simulations confirmed that even single targeted interventions could improve perceived safety and increase usage. This study highlights the need for inclusive urban design that addresses the specific experiences and requirements of women in public green spaces. Full article

Influencer marketing has emerged as a crucial element in digital marketing, significantly shaping consumer behavior and online shopping preferences. This study examined the multidimensional impact of influencer marketing by analyzing engagement metrics, marketing effectiveness, and consumer decision-making processes, based on consumers in the Greek sector. Through a structured methodological framework, the research employed a questionnaire-based survey, statistical modeling, and Fuzzy Cognitive Mapping (FCM) scenarios to assess consumer interactions with influencer-driven content. Findings highlight that while influencer marketing enhances brand engagement and sales, its effectiveness varies based on content authenticity, transparency, and user trust. Additionally, consumer purchasing decisions are influenced by social media visibility, personalized marketing strategies, and digital platform usability. This study underscores the need for strategic influencer selection and information-driven marketing optimization to sustain long-term consumer engagement. These insights provide practical implications for businesses aiming to enhance digital marketing strategies and contribute to the ongoing discourse on social commerce and consumer-centric marketing models. Full article

There are conflicting findings in the literature regarding the factors that influence school success. This uncertainty complicates the effective allocation of resources. The present study aims to identify critical success factors (CSFs) for schools by incorporating the perspectives of various stakeholders and addressing this gap in the literature. Additionally, a comprehensive performance measurement model is developed to ensure the sustainability of success. A three-phase complementary methodology was employed with 330 participants, including school administrators, students, and parents, from 23 high schools in Istanbul. Fuzzy cognitive mapping (FCM) was utilized to identify critical success factors (CSFs) by calculating centrality index values. Additionally, a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis was conducted to assess the institutional context, and a balanced scorecard (BSC) was developed for performance measurement. According to the results from FCM and SWOT analysis, the factors related to teachers, students, and school physical conditions were identified as the most critical success factors. The BSC model was employed in four high schools, yielding performance scores of 81.12 and 92.52, 67.89, 77.58, respectively. With its unique methodological approach integrating three analytical techniques, this study highlights the critical role of teacher experience, student quality, and appealing physical conditions in school success. It offers school administrators a scientifically grounded, practical performance evaluation tool. This study is significant as it establishes a foundation for monitoring large-scale investment performance in schools, encompassing Environmental, Social, and Governance (ESG) dimensions, and providing a basis for sustainability initiatives within educational institutions. Full article

Assessing infrastructure sustainability requires an evaluation of technical, economic, environmental, and social dimensions, with the latter often being overlooked. Asphalt mixtures incorporating end-of-life tire textile fiber additives in Chile have emerged as a sustainable alternative to conventional fibers. However, the social sustainability of these additives remains underexplored. This study develops a model to assess the social sustainability of asphalt additives in Chile using fuzzy cognitive mapping. The methodology includes three stages: (1) qualitative exploration of the conceptual model by information triangulation, (2) construction of a fuzzy cognitive model to estimate social contributions, and (3) dynamic analysis of four additives, including those derived from end-of-life tire textile fiber. The results show that these recycled additives generate distinct social impacts, particularly in terms of consumer interest, innovation, knowledge transfer, and regulatory alignment. Additionally, technical contributions and certifications significantly influence sustainability assessments, exhibiting greater independence from other factors. The findings highlight the potential of repurposed textile fiber as a socially sustainable alternative in asphalt production. This approach supports circular economy initiatives, fosters innovation, and enhances the acceptance of sustainable infrastructure materials in Chile, contributing to a more resilient and responsible construction sector. Full article

Contemporary ports are facing a variety of challenges due to technological advancements, economic pressures, and changing policies. Key issues include the effects of globalization, rapid advancements in information and communication technologies (ICTs), and the changing nature of port services. In order to tackle these challenges and achieve operational excellence, adapt to the shifting of activities, and meet new business demands, smart ports have been proposed as a comprehensive solution. These challenges arise because port success is often measured by traditional metrics such as port size and performance. To accurately assess the intelligence of a port, there is a need for a systematic and scientifically sound smart port evaluation method. This paper provides an overview of the concept of a smart port and develops a multi-criteria assessment framework of port smartness based on neutrosophic cognitive maps (NCMs). The unique and valuable characteristic of NCMs lies in their ability to manage the uncertainty associated with the relationship between two concepts, indicating their effects on each other in neutral states. This structure enables the NCM to provide results with a greater degree of sensitivity than fuzzy cognitive maps (FCMs) and allows for a greater degree of freedom of intuition for an expert to express not only the potential impacts but also the uncertainty associated with those impacts. Our methodology can make decisions using incomplete, uncertain, and inconsistent data during the assessment process, providing a rigorous quantitative framework for the assessment of port “smartness”. The proposed solution has the potential to act as a valuable tool in a group decision support environment and can be used to accelerate an organization’s development, improve productivity, and reinforce efforts to achieve strategic and sustainability objectives. To achieve this, an appropriate framework for such a methodology is demonstrated through an illustrative example offering actionable insights for improving port operations. Full article

Fuzzy Cognitive Maps (FCMs) have emerged as powerful tools for addressing diverse engineering challenges, leveraging their cognitive nature and ability to encapsulate causal relationships. This paper provides a comprehensive review of FCM applications across 15 engineering sub-domains, categorizing 80 studies by their learning family, task type, and case-specific application. We analyze the methodological advancements and practical implementations of FCMs, showcasing their strengths in areas such as decision-making, classification, time-series, diagnosis, and optimization. Qualitative criteria are systematically applied to classify FCM-based methodologies, highlighting trends, practical implications of varying complexity, and human intervention across task types and learning families. However, this study also identifies key limitations, including scalability challenges, reliance on expert knowledge, and sensitivity to data distribution shifts in real-world settings. To address these issues, we outline key areas and directions for future research focusing on adaptive learning mechanisms, hybrid methodologies, and scalable computational frameworks to enhance FCM performance in dynamic and evolving contexts. The findings of this review offer a structured roadmap for advancing FCM methodologies and broadening their application scope in both contemporary and emerging engineering domains. Full article

In this volatile, uncertain, complex, and ambiguous (VUCA) era, resilient and sustainable construction methods, such as prefabricated construction, are essential for addressing the planet’s sustainability challenges. However, disruptions in the prefabricated construction supply chain (PCSC) frequently arise, seriously impeding the performance of prefabricated building projects. Therefore, this study aims to identify the factors influencing the prefabricated construction supply chain (RPCSC) and analyze their intrinsic interconnections. Initially, an exhaustive literature review was conducted to identify the primary factors affecting the RPCSC. Subsequently, the Delphi technique was applied to validate and refine the list of factors, resulting in the identification of 11 key concepts. Finally, the impact of these concepts on the RPCSC, along with their interactions, was assessed using the fuzzy cognitive map (FCM) approach. The results indicate that these factors can be ranked by their degree of effect on the RPCSC: information exchange/sharing, research and development, the performance of prefabricated components, decision alignment, the construction of prefabricated buildings, relationship quality among members, professional management personnel/labor quality, supply–demand consistency, cost/profit sharing, policies and regulations, and transport risk. Furthermore, this study elucidates both the individual and synergistic effects of these factors on the RPCSC by constructing a pathway map. Full article

Detecting and managing speech-language pathology symptoms in patients with post-COVID syndrome (long COVID) presents a significant challenge, as the condition is marked by persistent and varied symptoms such as cognitive deficits, communication difficulties, and voice disorders. To address these challenges, a Fuzzy Cognitive Map Decision Support System (FCM-DSS) was developed to model causal relationships and integrate expert knowledge. A systematic review approach, though not comprehensive, was utilized to identify key symptoms and their prevalence from 19 studies, focusing on brain fog, attention deficits, memory problems, dyspnea, and swallowing difficulties. The weighted prevalence of these symptoms informed the development of the FCM-DSS model, designed to link symptoms to medical specialties and recommend specialist referrals. Preliminary testing on four case studies demonstrated the tool’s potential, but further validation through pilot studies is necessary. Full article

Management of reputational risk is crucial for financial institutions to establish a solid foundation for strategic decisions, gain customer trust, and enhance resilience against environmental adversities, as they largely operate on digital platforms. Since this becomes even more significant as online transactions and digital interactions amplify the visibility and potential impact of reputational issues in the context of electronic commerce, it is essential to thoroughly investigate environmental factors to achieve a comprehensive understanding of reputational risk. However, measuring and evaluating their influence on reputational risk is challenging due to their inherent connection to human perception. This study aims to explore the factors influencing reputational risk of financial organizations to mitigate potential reputational losses by addressing uncertainties associated with concepts such as vagueness. The employed methodology integrates the Decision-Making Trial and Evaluation Laboratory and Fuzzy Cognitive Map techniques using linguistic fuzzy terms. This approach focuses on both the direct effects of factors on reputational risk and the indirect effects arising from interdependencies between factors. Linguistic fuzzy variables enable us to consider the hesitation of the experts and the vagueness of human judgment. To validate the results, factors are also weighted using the fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) method. The most influential factors identified by both methods are market value, revenue, risk culture, shareholder value, firm performance, reputation awareness, and return on equity. Additionally, factors affecting other factors include firm performance, revenue, and growth opportunities. Full article

Projects involve inter-organizational relationship cognition, which is central to collaborative engineering project value added. Interest in value added in the project lifecycle is mounting and gaining increasing attention in the research literature. However, little is known about how inter-organizational relationship cognition facilitates value added and how such cognition pushes a project toward higher end-states of value. The existing literature mainly analyzes and studies value added on functional analysis and cost control. There are predominantly static analyses of the factors that influence value added in studies. The guiding role of value added has not been adequately explored in the studies on the influencing factors of value added. Utilizing a combination of Structural Equation Modeling (SEM) and Fuzzy Cognitive Maps (FCMs), this study addresses how inter-organizational relationship cognition influences engineering project value added, identifying complex structures of interaction and cognition dynamics. Results indicate that: (1) A hybrid SEM–FCM method can be able to model dynamic interactions between inter-organizational relationship cognition and value added; (2) trust and shared vision have positive effects on in-role behavior and extra-role behavior. Shared vision has a negative effect on opportunistic behavior. In-role behavior and extra-role behavior have a positive impact on value added, while opportunistic behavior has a negative impact. Organizational behavior is an important mediating variable to explain the interaction between inter-organizational relationship cognitions and value added. This hybrid method explores the potential mechanisms of inter-organizational relationship cognition on project value added from novel perspectives on construction project management practices, proposing practical advice for further project management. Full article

Agriculture is essential to any country’s economy. Agriculture is crucial not only for feeding a country’s population but also for its impact on other businesses. The paradox of agri-food companies generating substantial profits despite seemingly high product prices is explored in this article, focusing on the role of digital marketing within the agri-food industry. Enhanced digital marketing performance leads to efficient advertising campaigns, through reduced advertising costs and increased resource efficiency. To do so, the authors collected web analytical data from five established agri-food firms with the highest market capitalization. Then, linear regression and correlation analyses were used, followed by the utilization of fuzzy cognitive mapping (FCM) modeling. The analysis revealed that increased traffic through search sources is associated with reduced advertising costs. Additionally, enhanced website engagement contributes to lower advertising expenses, emphasizing the optimization of the user experience. However, it has been discovered that allocating funds for social media advertising eventually results in higher expenses with higher website-abandoning rate. Ultimately, successful management of the balance between product costs and profitability in the agri-food sector lies on the increased use of search sources and greatly reducing the use of social media sources. Full article

In the agri-food industry, strategic digital branding and digital marketing are essential for maintaining competitiveness. This study examines the economic dynamics and impact of desktop and mobile customer analytics on digital branding strategies within the sector. Through a comprehensive literature review, this research utilizes empirical evidence to validate hypotheses regarding the influence of desktop and mobile analytics metrics on key digital branding metrics and value creation. This study explores various branding indicators by utilizing descriptive statistics, correlation analyses, regression models, and fuzzy cognitive mapping (FCM). The findings reveal significant correlations between desktop and mobile analytics and digital branding outcomes, underscoring the critical role of digital analytics and Decision Support Systems (DSSs) in shaping modern branding strategies in the agri-food industry. This study highlights the economic implications of desktop and mobile customer analytics on digital branding, providing insights to enhance market performance and foster sustainable growth in the agri-food sector. Full article

In the past few years, there have been many studies addressing the simulation of COVID-19’s spatial transmission model of infectious disease in time. However, very few studies have focused on the effect of the epidemic environment variables in which an individual lives on the individual’s behavioral logic leading to changes in the overall epidemic transmission trend at larger scales. In this study, we applied Fuzzy Cognitive Maps (FCMs) to modeling individual behavioral logistics, combined with Agent-Based Modeling (ABM) to perform “Susceptible—Exposed—Infectious—Removed” (SEIR) simulation of the independent individual behavior affecting the overall trend change. Our objective was to simulate the spatiotemporal spread of diseases using the Bengaluru Urban District, India as a case study. The results show that the simulation results are highly consistent with the observed reality, in terms of trends, with a Root Mean Square Error (RMSE) value of 0.39. Notably, our approach reveals a subtle link between individual motivation and infection-recovery dynamics, highlighting how individual behavior can significantly impact broader patterns of transmission. These insights have potential implications for epidemiologic strategies and public health interventions, providing data-driven insights into behavioral impacts on epidemic spread. By integrating behavioral modeling with epidemic simulation, our study underscores the importance of considering individual and collective behavior in designing sustainable public health policies and interventions. Full article

Transhumance and its associated heritage are extremely complex and dynamic systems, and their conservation requires the analysis of interdisciplinary factors. To this end, fuzzy cognitive maps (FCMs) and Delphi surveys were applied for the first time in the field of heritage conservation. The model was applied to the tangible and intangible transhumance heritage of Andorra to determine its current state of conservation and to evaluate strategies for its preservation. Two panels of experts worked on the development of the model. Five experts with profiles related to conservation and transhumance heritage formed the first panel, which designed the preliminary FCMs, while seven experts in Andorran cultural heritage (panel 2) adapted the preliminary FCM model to Andorran transhumance heritage using Delphi surveys. The FCM model allowed us to analyze the influence of different variables on the conservation of transhumance heritage and to assess policy decisions. Further studies will focus on the implementation of this model in other countries to establish common recommendations for the conservation of the cultural heritage of transhumance. Full article