Search Results (147)

In the digitally saturated hospitality environment, research on digital transformation remains dominated by macro-level adoption trends and user-generated content, while the potential of micro-level web-behavioural data remains largely untapped. Recent systematic reviews highlight a fragmented body of literature and note that hospitality studies seldom address first-party behavioural data or big-data analytics capabilities. To address this gap, we collected clickstream, navigation and booking-funnel data from five luxury hotels in the Mediterranean and employed big-data analytics integrated with simulation modelling—specifically fuzzy cognitive mapping (FCM)—to model causal relationships among digital touchpoints, managerial actions and customer outcomes. FCM is a robust simulation tool that captures stakeholder knowledge and causal influences across complex systems. Using a case-study methodology, we show that first-party behavioural data enable real-time insights, support knowledge-based decision-making and drive digital service innovation. Across a 12-month panel, visitor volume was strongly associated with search traffic and social traffic, with the total-visitors model explaining 99.8% of variance. Our findings extend digital-transformation models by embedding micro-level behavioural data flows and simulation modelling. Practically, this study offers a replicable framework that helps managers integrate web-analytics into decision-making and customer-centric innovation. Overall, embedding micro-level web-behavioural analytics within an FCM framework yields a decision-ready, replicable pipeline that translates behavioural evidence into high-leverage managerial interventions. Full article

The Mediterranean Sea, a biodiversity hotspot with over 8500 marine species, faces escalating threats from climate change, pollution, overfishing, and habitat degradation. This study introduces a novel Decision Support System (DSS) integrating a modified PESTEL framework (BESTEL: Biological, Economic, Social, Technological, Environmental, Legal) with Fuzzy Cognitive Mapping (FCM) to assess and mitigate risks to marine species. Leveraging expert knowledge from 34 specialists, we identified 30 key factors influencing extinction risk, analyzed through Principal Component Analysis (PCA) to reduce dimensionality. The resulting FCM model simulated four policy scenarios, evaluating the impacts of climate change and dam proliferation on biodiversity. Findings reveal that mitigating both drivers significantly reduces extinction risk (−0.14), while unchecked climate change offsets gain from dam removal. The DSS highlights the dominance of climate stressors, with pollution and temperature shifts (−0.45, −0.42) as critical variables. Biological traits like reproductive frequency and longevity respond strongly to environmental improvements. This integrative approach bridges qualitative expertise and quantitative modeling, offering actionable insights for conservation planning. The study underscores the need for holistic strategies combining climate mitigation and habitat restoration to safeguard Mediterranean marine ecosystems. The FCM-based DSS provides a scalable tool for policymakers to prioritize interventions and assess trade-offs in complex socio-ecological systems. Full article

The present study explores the enablers for the integration of Industry 5.0 principles within the automotive industry, emphasizing the transition towards human-centric, sustainable, and resilient manufacturing. This research utilized a three-round Delphi method involving a panel of experts to identify, evaluate, and prioritize key enablers associated with the adoption of Industry 5.0. In order to enhance the analytical depth, consensus trajectory mapping was employed to track opinion convergence across rounds. Fuzzy ranking was applied to provide a more nuanced evaluation of item prioritization. The results indicate a substantial degree of consensus on subjects such as collaborative robotics, cognitive automation, and circular manufacturing. The present study offers theoretical and practical implications, providing a roadmap for researchers and automotive stakeholders seeking to operationalize Industry 5.0 values. Full article

The rise of streaming services and online story-sharing has led to a vast amount of cinema and television content being viewed and reviewed daily by a worldwide audience. It is a unique challenge to grasp the nuanced insights of these reviews, particularly as context, emotion, and specific components like acting, direction, and storyline intertwine extensively. The aim of this study is to address said complexity with a new hybrid Multi Criteria Decision-Making MCDM model that combines the Deck of Cards Method (DoCM) with the Circular Pythagorean Fuzzy Set (CPFS) framework, retaining the symmetry of information. The study is conducted on a simulated dataset to demonstrate the framework and outline the plan for approaching real-world press reviews. We postulate a more informed mechanism of assessing and choosing the most appropriate deep learning assembler, such as the transformer version, the hybrid Convolutional Neural Network CNN-RNN, and the attention-based framework of aspect-based sentiment mapping in film and television reviews. The model leverages both the cognitive ease of the DoCM and the expressive ability of the Pythagorean fuzzy set (PFS) in a circular relationship setting possessing symmetry, and can be applied to various decision-making situations other than the interpretation of media sentiments. This enables decision-makers to intuitively and flexibly compare alternatives based on many sentiment-relevant aspects, including classification accuracy, interpretability, computational efficiency, and generalization. The experiments are based on a hypothetical representation of media review datasets and test whether the model can combine human insight with algorithmic precision. Ultimately, this study presents a sound, structurally clear, and expandable framework of decision support to academicians and industry professionals involved in converging deep learning and opinion mining in entertainment analytics. Full article

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

The growing number of older adults with cancer confront practical and organizational limitations that hinder their ability to obtain care that is adapted to their health status, needs, expectations, and life choices. The integration into practice of evidence-based and institutional recommendations for a geriatric approach and person-centered high-quality care remains incomplete. This study uses an action research design to explore stakeholders’ perspectives of the challenges involved in translating the established care priorities into a compassionate geriatric approach in oncology and identify promising pathways to improvement. Fifty-three stakeholders participated in focus groups to create cognitive maps representing perceived relationships between concepts related to compassionate care of older adults with cancer. Combining maps results in a single model constructed in Mental Modeler software to weigh relationships and calculate concept centrality (importance in the model). The model represents stakeholders’ collective perspective of the determinants of compassionate care that need to be addressed at different decision-making levels. The results reveal pathways to improvement at systemic, organizational, practice, and societal levels. These include connecting policies on ageing and national cancer programs, addressing fragmented care through interdisciplinary teamwork, promoting person-centered care, cultivating relational proximity, and combatting ageism. Translating evidence-based practices and priority orientations into compassionate care rests on collective capacities across multiple providers to address the whole person and their unique trajectory. 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

In today’s hyperconnected world, disaster announcements—regardless of actual impact—can significantly shape consumer behaviour and brand perception in the hospitality sector. This study investigates how customers respond online to disaster-related signals, focusing on digital marketing activities by luxury hotels in Santorini, Greece. Drawing on a case study of the Santorini Earthquake in February 2025—during which the Greek government declared a state of emergency—we use big data analytics, including web traffic metrics, social media interaction and fuzzy cognitive mapping, to analyse behavioural shifts across platforms. The findings indicate that disaster signals trigger increased engagement, altered sentiment and changes in advertising efficiency. This study provides actionable recommendations for tourism destinations and hospitality brands on how to adapt digital strategies during crisis periods. 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

Watersheds are threatened by numerous issues, such as climate change, population growth, urban expansion, and industrial development. These issues are complex and interconnected, and effectively addressing them requires integrating the values, knowledge, and expertise of various governing bodies, local organizations, and community members, all of whom have their own viewpoints and priorities. The current study employs a participatory approach and systems lens to engage different stakeholders in the complexity of watershed issues and management approaches. Using participatory modeling and semi-quantitative scenario analysis techniques, the study identifies relationships among watershed values, challenges, and strategies as well as the dynamics of these relationships. A fuzzy cognitive map was developed, which consists of 53 nodes (i.e., 13 values, 12 challenges, and 28 strategies) and 113 connections. Biodiversity, mental health, and sense of place emerged as key values, as they exhibited high centrality values when analyzing the system, and challenges like invasive species and urban sprawl were found to exert considerable impacts on these values. Strategies such as establishing and expanding greenspace, community stewardship, and governance-based interventions were identified as critical for addressing watershed challenges and enhancing watershed values. The study identified a series of governance-based strategies that focus on resource allocation, participatory governance, and institutional collaboration to address watershed management challenges as well as a set of engagement-based strategies that focus on environmental communication and public awareness. The study demonstrates the potential that participatory modeling and semi-quantitative analysis techniques can have for integrating both tangible, measurable values and intangible, difficult-to-measure values into planning and policymaking. The research reinforces the idea that local governments play a critical role in fostering inclusive and collaborative watershed management strategies. 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

The promotion of carbon reduction in the private car sector is crucial for advancing sustainable transportation development and addressing global climate change. This study utilizes vehicle trajectory big data from Guangdong Province, China, and employs machine learning, an LDA topic model, a gradient descent-based fuzzy cognitive map model, and grey correlation analysis to investigate the influencing factors and emission reduction pathways of carbon emissions from private cars. The findings indicate that (1) population density exhibits the strongest correlation with private car carbon emissions, with a coefficient of 0.85, rendering it a key factor influencing emissions, (2) the development of public transportation emerges as the primary pathway for carbon reduction in the private car sector under a single-factor scenario, and (3) coordinating public transport with road network density and fuel prices with traffic congestion are both viable pathways as well for reducing carbon emissions in the private car sector. This study attempts to integrate multiple factors and private car carbon emissions within a unified research framework, exploring and elucidating carbon reduction pathways for private cars with the objective of providing valuable insights into the green and low-carbon transition of the transportation sector. Full article

In the current operational landscape, organizations face a growing and diverse array of cybersecurity challenges, necessitating the development and implementation of innovative and effective security solutions. This paper presents a novel methodology for dynamic risk assessment and mitigation suggestions aimed at assessing and reducing cyber risks. The proposed approach gathers information from publicly available cybersecurity-related open sources and integrates it with environment-specific data to generate a comprehensive understanding of potential risks. It creates multiple distinct risk scenarios based on the identification of vulnerabilities, network topology, and the attacker’s perspective. The methodology employs Bayesian networks to proactively and dynamically estimate the probability of threats and Fuzzy Cognitive Maps to dynamically update vulnerability severity values for each risk scenario. These elements are combined with impact estimations to provide dynamic risk assessments. Furthermore, the methodology offers mitigation suggestions for each identified vulnerability across all risk scenarios, enabling organizations to effectively address the assessed cybersecurity risks. To validate the effectiveness of the proposed methodology, a case study is presented, demonstrating its practical application and efficacy. 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