Search Results (1,507)

The landscape of marketing is rapidly evolving as companies adapt to new societal dynamics and technological advancements. Guerrilla marketing, characterized by its unconventional, creative, and cost-effective tactics, has proven effective in capturing consumer attention. When integrated with social media platforms, these tactics gain amplified reach, immediacy, and interactive potential, fostering viral spread and deeper consumer engagement. This research seeks to answer the pivotal question: “How does guerrilla marketing on social media influence consumer behavior and brand awareness?” To address this, a comprehensive literature review was conducted to provide an in-depth analysis of relevant studies in the field. Our findings reveal that this integration significantly enhances consumer engagement, boosts brand awareness, and positively influences purchasing behavior. Moreover, it provides firms with competitive advantages in dynamic, resource-constrained markets. The results highlight the importance of leveraging creative marketing approaches alongside digital platforms to shape consumer choices and drive successful marketing outcomes in the digital age. Full article

The exponential growth of scientific literature has made it increasingly difficult for researchers to identify relevant and timely publications within vast academic digital libraries. Although academic search engines, reference management tools, and recommender systems have evolved, many still rely heavily on metadata and lack mechanisms to incorporate full-text content or time-awareness. This review systematically examines the landscape of scholarly publication recommender systems, employing the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology for a comprehensive and transparent selection of relevant studies. We highlight the limitations of current systems and explore the potential of integrating fine-grained citation knowledge—such as citation proximity, context, section, graph, and intention—extracted from full-text documents. These elements have shown promise in enhancing both the contextual relevance and recency of recommendations. Our findings highlight the importance of moving beyond accuracy-focused metrics toward user-centric evaluations that emphasise novelty, diversity, and serendipity. This paper advocates for the development of more holistic and adaptive recommender systems that better align with the evolving needs of researchers. Full article

Understanding the temporal dynamics and spatial distribution of key soil properties is essential for sustainable land management and informed decision-making. This study assessed the spatial variability and decadal changes (2013–2023) of topsoil properties in Córdoba, central Argentina, using digital soil mapping (DSM) and machine learning (ML) algorithms. Three ML methods—Quantile Regression Forest (QRF), Cubist, and Support Vector Machine (SVM)—were compared to predict soil organic matter (SOM), extractable phosphorus (P), and pH at 0–20 cm depth, based on environmental covariates related to site climate, vegetation, and topography. QRF consistently outperformed the other models in prediction accuracy and uncertainty, confirming its suitability for DSM in heterogeneous landscapes. Prediction uncertainty was higher in marginal mountainous areas than in intensively managed plains. Over ten years, SOM, P, and pH exhibited changes across land-use classes (cropland, pasture, and forest). Extractable P declined by 15–35%, with the sharpest reduction in croplands (−35.4%). SOM decreased in croplands (−6.7%) and pastures (−3.1%) but remained stable in forests. pH trends varied, with slight decreases in croplands and forests and a small increase in pastures. By integrating high-resolution mapping and temporal assessment, this study advances DSM applications and supports regional soil monitoring and sustainable land-use planning. Full article

Urban Air Mobility (UAM) has the potential to revolutionize urban transportation, largely with the deployment of Unmanned Aerial Vehicles (UAVs), commonly known as drones. After an initial stage focused on technology requirements, research is now shifting toward investigating operational requirements, which are unavoidably affected by urban characteristics. This study aims to explore the implementation of UAM services within urban environments by mapping the current scientific landscape from a city-focused perspective. Following a systematic search procedure, a bibliometric analysis was conducted on studies published between 2010 and 2024, examining over 350 articles that address UAM and urban-related topics. Trends in publication volume and scientific impact were analysed, along with influential manuscripts, collaborations, and leading countries in the field. Through a keyword co-occurrence analysis, five main research themes were identified: air traffic management, risk assessment, environmental factors (wind and noise), and vertiport location. These themes were further explored through a scoping review to assess current research and emerging directions. The findings highlight that urban characteristics are not just operational constraints but also fundamental elements that shape UAM strategies, influencing UAV path planning, safety, environmental constraints, and infrastructure design. Future research directions include the development of urban digital twins, comprehensive urban spatial databases, and multi-objective optimization frameworks to support the effective implementation of UAM into cities. Full article

Cultural organizations have traditionally been viewed as resistant to change, often bound by legacy structures, public dependency, and non-commercial missions. However, recent advances in digital technologies—ranging from AI and VR to IoT and big data—are reshaping the operational and strategic landscape of these institutions. Despite this shift, academic literature has yet to comprehensively map how technological innovation transforms cultural organizations into practice. This paper addresses this gap by introducing the concept of the Cultural Organizational System (COS)—a holistic framework that captures the multi-component structure of cultural entities, including space, tools, performance, management, and networks. Using a PRISMA-based scoping review methodology, we analyze over 90 sources to identify the types, functions, and strategic roles of technological innovations across COS components. The findings reveal a taxonomy of innovation use cases, a mapping to Oslo innovation categories, and a quadrant model of enablers and barriers unique to the cultural sector. By offering an integrated view of digital transformation in cultural settings, this study advances innovation theory and provides practical guidance for cultural leaders and policymakers seeking to balance mission-driven goals with sustainability and modernization imperatives. Full article

This paper examines the evolving trajectory of the Social Determinants of Health (SDOH), tracing their development from early observational studies to contemporary, interdisciplinary frameworks that emphasize structural inequities and relational dynamics. It explores foundational milestones such as the Whitehall studies, the Heckler Report, and the World Health Organization’s conceptual models, which positioned SDOH as key drivers of population health. The paper highlights how upstream determinants—such as governance, policy, and socioeconomic systems—influence downstream health outcomes through mechanisms of social stratification and unequal access to resources. While SDOH are increasingly applied in clinical and educational settings, significant challenges persist, including underinvestment in community systems, fragmented care models, and political rollbacks of equity-centered policies. The paper critiques deterministic and deficit-focused framings of SDOH and underscores a shift toward more relational, context-sensitive, and agency-oriented approaches, reflected in the emerging concept of “social dynamics of health.” It highlights the importance of experiential education, competency-based curricula, and digital innovations in driving systemic transformation. Emphasis is placed on reimagining SDOH pedagogy and expanding interdisciplinary, data-driven research to bridge the gap between knowledge and practice. Amid shifting political landscapes, sustaining health equity efforts requires embracing adaptive, participatory models that acknowledge power, community agency, and structural change. Full article

Achieving decarbonization targets in the aviation sector requires transformative approaches to sustainable aviation fuel (SAF) production. In this pursuit, feedstock innovation has emerged as a critical challenge. This research uses the U.S. SAF Grand Challenge as a case study, focusing on its feedstock innovation workstream, to investigate how Industry 4.0 technologies can fulfill that workstream’s objectives. An integrative literature review, drawing on academic, industry, and policy sources, is used to evaluate the Technology Readiness Levels (TRLs) of Industry 4.0 technology applications across the SAF biomass supply chain. The analysis identifies several key technologies as essential for improving yield prediction, optimizing resource allocation, and linking stochastic models to techno-economic analyses (TEAs): IoT-enabled sensor networks, probabilistic/precision forecasting, and automated quality monitoring. Results reveal an uneven maturity landscape, with some applications demonstrating near-commercial readiness, while others remain in early research or pilot stages, particularly in areas such as logistics, interoperability, and forecasting. The study contributes a structured TRL-based assessment that not only maps maturity but also highlights critical gaps and corresponding policy implications, including data governance, standardization frameworks, and cross-sector collaboration. By aligning digital innovation pathways with SAF deployment priorities, the findings offer both theoretical insights and practical guidance for advancing sustainable aviation fuel adoption and accelerating progress toward net-zero aviation. Full article

In response to the changing international landscape and the risks associated with China’s supply chain security, conducting policy simulations on semiconductor supply chain security helps clarify the industry’s policies and governance strategies for semiconductor supply chain security in China. It also enables a better understanding of the current state and focus areas of China’s semiconductor supply chain security, which is of great significance for improving the security levels of semiconductor supply chains across provinces and cities and for constructing a secure, efficient, and autonomous semiconductor supply chain system. Firstly, this paper reviews the current research on semiconductor supply chains, supply chain security, and industrial policies. Secondly, based on the industrial policies for semiconductor supply chain security, an evolutionary game model is constructed, involving government departments, chain owner enterprises, and upstream and downstream small and medium-sized enterprises (SMEs) within the supply chain. Finally, the MATLAB R2016b system simulation method is employed to conduct a policy simulation analysis of China’s semiconductor supply chain security and further analyze the industrial policies related to semiconductor supply chain security. The results show that: (1) Supply chain security depends on multi-agent collaborative governance, with government leadership, and chain owner enterprises driving innovation in SMEs, improving digitalization levels, and ensuring supply chain autonomy and control. (2) Increasing government management revenue, raising the responsibility costs for chain owner enterprises, and reducing the innovation costs for SMEs can accelerate the achievement of the ideal governance state. Lastly, policy recommendations are proposed to build an autonomous and controllable supply chain system. Full article

Computer-Aided Design (CAD) software has long served as a foundation for planning and modeling in Architecture, Engineering, and Construction (AEC). In recent years, the introduction of Augmented Reality (AR) and Virtual Reality (VR) has significantly reshaped the CAD landscape, offering novel interaction paradigms that bridge the gap between digital prototypes and real-world spatial understanding. These technologies have enabled users to engage with 3D architectural content in more immersive and intuitive ways, facilitating improved decision making and communication throughout design workflows. As digital design services grow more complex and span multiple media platforms—from desktop-based modeling to immersive AR/VR environments—evaluating usability and User Experience (UX) becomes increasingly challenging. This paper presents a longitudinal usability and UX study of a multiplatform house design pipeline (i.e., structured workflow for creating, adapting, and delivering house designs so they can be used seamlessly across multiple platforms) comprising a web-based application for initial house creation, a mobile AR tool for contextual exterior visualization, and VR applications that allow full-scale interior exploration and configuration. Together, these components form a unified yet heterogeneous service experience across different devices and modalities. We describe the iterative design and development of this system over three distinct phases (lasting two years), each followed by user studies which evaluated UX and usability and targeted different participant profiles and design maturity levels. The paper outlines our approach to cross-platform UX evaluation, including methods such as the Think-Aloud Protocol (TAP), standardized usability metrics, and structured interviews. The results from the studies provide insight into user preferences, interaction patterns, and system coherence across platforms. From both participant and evaluator perspectives, the iterative methodology contributed to improvements in system usability and a clearer mental model of the design process. The main research question we address is how iterative design and development affects the UX of the heterogeneous service. Our findings highlight important considerations for future research and practice in the design of integrated, multiplatform XR services for AEC, with potential relevance to other domains. Full article

This study explores the potential of Digital Earth Africa (DE Africa) coastlines products for assessing the Coastal Vulnerability Index (CVI) along the Casablanca coastline, Morocco. The analysis integrates remotely sensed shoreline data with elevation, slope, and geomorphological information from ASTER GDEM and geological maps within a GIS environment. Shoreline change metrics, including Shoreline Change Envelope (SCE), Net Shoreline Movement (NSM), Linear Regression Rate (LRR), and End Point Rate (EPR), were used to evaluate erosion trends from 2000 to 2023. Results show that sandy beach areas, particularly those below 12 m elevation, are highly exposed to erosion (up to 1.5 m/yr) and vulnerable to coastal hazards. Approximately 44% and 23% of the study area were classified as having very high and high vulnerability, respectively. The results indicate that remotely sensed data and GIS techniques are valuable and cost-effective tools for multi-scale geo-hazard coastal assessment studies. The study demonstrates that DE Africa products, combined with local landscape data, provide a valuable tool for coastal vulnerability assessment and monitoring in Africa. Full article

Objective: This study investigates how artificial intelligence (AI) research relates to firm value, focusing on dominant thematic trends, theoretical foundations, and global collaboration patterns. Methods: A PRISMA-guided systematic review was conducted on 219 peer-reviewed articles published between 2013 and May 2025 in the Web of Science Social Sciences Citation Index. Bibliometric techniques, including co-word, co-citation, and collaboration network analyses, were performed using the bibliometrix (version 4.2.3) in R (version 4.4.2) package to map key concepts, intellectual structures, and international research partnerships. Results: The literature is primarily grounded in strategic management theories such as the resource-based view (RBV) and dynamic capabilities. Emerging research streams emphasize digital transformation, big data analytics, and decision support systems. Frequently co-occurring terms include “firm performance,” “artificial intelligence,” “dynamic capabilities,” “information technology,” and “decision-making.” Collaboration mapping highlights the United States, United Kingdom, and China as leading hubs, with increasing contributions from emerging economies such as India, Malaysia, and Saudi Arabia. The alignment between co-word and co-citation structures reflects a shift from foundational theory to applied AI capabilities in firm-value creation. Implications: By integrating a systematic review with advanced bibliometric and science-mapping methods, this work establishes a structured foundation for theory development, empirical testing, and policy formulation in AI-driven business landscapes. Full article

The fashion industry, despite its global economic importance, is a major contributor to environmental degradation and social inequality. In response, sustainable fashion has emerged as a growing movement advocating ethical, ecological, and socially responsible practices. This study presents a comprehensive bibliometric analysis of 1134 peer-reviewed journal articles on sustainable fashion indexed in Scopus from 1986 to 2025. Results show an exponential rise in research output after 2015, with interdisciplinary contributions from social sciences, business, environmental science, and engineering. By applying performance analysis and science mapping techniques, the study identifies five major research themes: “Consumer Behavior,” “Design Ethics,” “Circular Economy,” “Innovation,” and “Digital Media.” The geographic distribution reveals strong outputs from both developed and emerging economies. This study provides an integrative overview of the intellectual landscape of sustainable fashion and serves as a roadmap for researchers, policymakers, and practitioners who are interested in the development of sustainable fashion. Full article

Gully erosion, driven by the interplay of natural processes and human activities, results in severe soil degradation and landscape alteration, yet approaches for accurately quantifying erosion triggered by extreme precipitation using multi-source high-resolution remote sensing remain limited. This study first extracted digital surface models (DSM) for the years 2014 and 2024 using Ziyuan-3 and GaoFen-7 satellite stereo imagery, respectively. Subsequently, the DSM was calibrated using high-resolution unmanned aerial vehicle photogrammetry data to enhance elevation accuracy. Based on the corrected DSMs, gully erosion depths from 2014 to 2024 were quantified. Erosion patches were identified through a deep learning framework applied to GaoFen-1 and GaoFen-2 imagery. The analysis further explored the influences of natural processes and anthropogenic activities on elevation changes within the gully erosion watershed. Topographic monitoring in the Sandu River watershed revealed a net elevation loss of 2.6 m over 2014–2024, with erosion depths up to 8 m in some sub-watersheds. Elevation changes are primarily driven by extreme precipitation-induced erosion alongside human activities, resulting in substantial spatial variability in surface lowering across the watershed. This approach provides a refined assessment of the spatial and temporal evolution of gully erosion, offering valuable insights for soil conservation and sustainable land management strategies in the Loess Plateau region. Full article

With the rapid development of urbanization and tourism in China, increasing attention has been paid to the protection and utilization of historical and cultural heritage, while tourists’ demands for travel experiences have gradually shifted towards in-depth cultural perception. This paper selects Beijing Fayuan Temple Historic and Cultural District as the research case, and adopts methods such as the LDA (Latent Dirichlet Allocation) topic model, collection and analysis of online text data, and field research to explore the current situation of pedestrian space in Fayuan Temple District and its optimization strategies from the perspective of tourists’ perception. The study found that the dimensions of tourists’ perception of the pedestrian space in Fayuan Temple District mainly include six aspects: historical buildings and relics, tour modes and transportation, natural landscapes and environment, historical figures and culture, residents’ life and activities, and tourists’ experiences and visits. By integrating online text data, questionnaire surveys, and on-site behavioral observations, the study constructed a “physical environment-cultural experience-behavioral network” three-dimensional IPA (Importance–Possession Analysis) evaluation model, and analyzed and evaluated the high-frequency perception elements in tourists’ spontaneous evaluations. Based on the current situation evaluation of the pedestrian space in Fayuan Temple District, this paper puts forward optimization strategies for the perception of pedestrian space from the aspects of block space, transportation usage, landscape ecology, digital technology, and cultural symbol translation. It aims to promote the high-quality development of historical blocks by improving and optimizing the pedestrian space, and achieve the dual goals of cultural inheritance and utilization of tourism resources. Full article

As cities confront rising populations and mounting environmental pressures, waste is rapidly transforming from a logistical liability into a strategic economic resource. In this article, we investigate the evolving nexus between waste and urban economic systems by analyzing over 2000 scientific publications sourced from Web of Science and Scopus. Using advanced semantic embedding and network analysis, we identify seven major research communities at the intersection of digital innovation, circular economy, and smart urban infrastructure. Through PageRank-based influence mapping, we highlight key contributions that shape each thematic cluster—ranging from AI-powered waste classification to blockchain-enabled traceability and IoT-driven logistics. Our results reveal a dynamic and interdisciplinary research landscape where waste valorisation is not only a sustainability imperative but also a driver of urban economic renewal. This study offers both a conceptual map and a methodological framework for understanding how cities can embed intelligence, efficiency, and circularity into waste systems as part of a broader transition to regenerative, data-informed urban economies. Full article