Search Results (34)

The accelerating integration of electric vehicles (EVs) into contemporary transportation infrastructure has underscored significant limitations in traditional charging paradigms, particularly in accommodating heterogeneous user requirements within dynamic operational environments. This study presents a differentiated optimization framework for EV charging strategies through the systematic classification of user types. A multidimensional decision-making environment is established for three representative user categories—residential, commercial, and industrial—by synthesizing time-variant electricity pricing models with dynamic carbon emission pricing mechanisms. A bi-level optimization architecture is subsequently formulated, leveraging deep reinforcement learning (DRL) to capture user-specific demand characteristics through customized reward functions and adaptive constraint structures. Validation is conducted within a high-fidelity simulation environment featuring 90 autonomous EV charging agents operating in a metropolitan parking facility. Empirical results indicate that the proposed typology-driven approach yields a 32.6% average cost reduction across user groups relative to baseline charging protocols, with statistically significant improvements in expenditure optimization (p < 0.01). Further interpretability analysis employing gradient-weighted class activation mapping (Grad-CAM) demonstrates that the model’s attention mechanisms are well aligned with theoretically anticipated demand prioritization patterns across the distinct user types, thereby confirming the decision-theoretic soundness of the framework. Full article

The article aims to identify consumer types based on their attitudes and behaviors toward phygital tools and solutions. The analysis was based on the authors’ empirical research. The research was conducted on a sample of 2160 Polish consumers. The study employed an online survey technique. To determine the types of consumers, a 20-item scale was used, allowing the respondents to express their attitudes toward solutions and tools that improve shopping in the phygital space. The extraction of types was carried out in two steps. The first was cluster analysis, conducted using the hierarchical Ward method with the square of the Euclidean distance, and the second was non-hierarchical cluster analysis using the k-means method. As a result of the analyses, three relatively homogeneous types of consumers were distinguished: phygital integrators, digital frequenters, and physical reality anchors. The behaviours of consumers from each type were examined in the context of their impact on sustainable consumption and the sustainable development of the planet. The proposed typology contributes to developing consumer behavior theory in sustainable consumption environments. It provides practical implications for designing customer experiences that are more inclusive, resource-efficient, and aligned with responsible consumption patterns. Understanding how different consumer groups engage with phygital tools allows businesses and policymakers to tailor strategies that support equitable access to digital services and foster more sustainable, adaptive consumption journeys in an increasingly digitized marketplace. Full article

This study investigates the effectiveness of active structural control in mitigating seismic damage of inelastic structures. A fuzzy control algorithm is integrated into a custom-developed finite element routine to examine the relationship between maximum control force requirements and the resulting structural damage state. Consequently, a series of nonlinear dynamic simulations was conducted on 3D inelastic numerical models representing five building typologies—three residential, one office, and one school using seismic inputs from two historical earthquakes. Structural damage was quantified using the Park–Ang damage index. Key findings show that active control can reduce structural damage of inelastic structures, but its effectiveness depends on seismic input and the complexity structural layout. Lower forces are adequate for low-rise or simple buildings, while taller or complex structures require substantially higher forces, which may be challenging to apply in real applications. Moreover, the results emphasize how local seismic conditions and variations in building dynamic characteristics impact the demands in control forces. Full article

This study integrates customer loyalty program data with a synthetic population to analyze grocery shopping behaviours in Montreal. Using clustering algorithms, we classify 295,631 loyalty program members into seven distinct consumer segments based on behavioural and sociodemographic attributes. The findings reveal significant heterogeneity in consumer behaviour, emphasizing the impact of urban geography on shopping decisions. This segmentation also provides valuable insights for retailers optimizing store locations and marketing strategies and for policymakers aiming to enhance urban accessibility. Additionally, our approach strengthens agent-based model (ABM) simulations by incorporating demographic and behavioural diversity, leading to more realistic consumer representations. While integrating loyalty data with synthetic populations mitigates privacy concerns, challenges remain regarding data sparsity and demographic inconsistencies. Future research should explore multi-source data integration and advanced clustering methods. Overall, this study contributes to geographically explicit modelling, demonstrating the effectiveness of combining behavioural and synthetic demographic data in urban retail analysis. Full article

This study presents an integrated approach for adapting building energy systems using Machine Learning (ML), the Internet of Things (IoT), and Building Information Modeling (BIM) in a hotel retrofit in Italy. In a concise multi-stage process, long-term climatic data and on-site technical documentation were analyzed to create a detailed BIM model. This model enabled energy simulations using the Carrier–Pizzetti method and supported the design of a hybrid HVAC system—integrating VRF and hydronic circuits—further enhanced by a custom ML algorithm for adaptive, predictive energy management through BIM and IoT data fusion. The study also incorporated photovoltaic panels and solar collectors, reducing reliance on non-renewable energy sources. Results demonstrate the effectiveness of smart energy management, showcasing significant potential for scalability in similar building typologies. Future improvements include integrating a temporal evolution model, refining feature selection using advanced optimization techniques, and expanding validation across multiple case studies. This research highlights the transformative role of ML, IoT, and BIM in achieving sustainable, smart, and efficient building energy systems, offering a replicable framework for sustainable renovations in the hospitality sector. Full article

Scholars have long sought to understand the meanings and implications of holidays for societies, groups, and individuals. Normative observances for holidays shift over time, which scholars have explained primarily with macro-level forces such as galvanizing events/trends and priorities of social institutions, but this approach tends to undersell individual and familial agency to customize holidays to their own circumstances, including to reject or resist normative symbols, meanings, and practices, either in part or wholly. Micro-level processes, then, offer insight into what happens when cultural projections about how to observe a holiday collide with an individual’s decision about whether and how to participate, especially with respect to negotiation processes. While the extant literature is robust regarding rituals commonly attached to holidays, there has been much less focus specifically on how agency shapes nonconformity to (or adoption of) normative scripts, including novel expressions. More research would also be helpful for understanding the dynamics of how families and other small groups negotiate shared observances. Finally, micro-level processes may serve—under certain conditions—to promote macro-level change in holiday patterns. To stimulate further research on processes involving agency and perceived constraints to holiday observation, I suggest a preliminary typology of U.S. holiday customization for individuals. Full article

This research explores the development of a modular prefabricated concrete housing prototype, focusing on sustainability and flexibility. Supported by industry collaboration, it examines three key hypotheses: (1) a rigid geometric modular layout optimizing standardized panels while allowing spatial customization and adaptability, (2) a mixed construction system combining panels with pillars and beams for greater design flexibility, and (3) prefabricated concrete panels with integrated thermal insulation to enhance comfort. An analytical framework was developed based on modularity, flexibility, and sustainability, informed by an extensive literature review and applied to contemporary collective housing case studies. Insights from this analysis guided the development of a housing prototype that integrates modularity, adaptable construction, and sustainable principles. The proposed design follows the principles of design for assembly and disassembly (DFA/DFD), increasingly relevant in modern construction. The findings suggest that combining concrete solutions with thermal insulation, structured around a regular geometric grid, enables diverse housing typologies while ensuring cost efficiency through prefabrication. This approach challenges the monotony of conventional housing, offering visually engaging and functionally adaptable alternatives. It promotes architecture that balances efficiency, sustainability, and aesthetic value while addressing modern housing needs. Full article

This study examines the intrinsic motivation of preservice primary teachers in a science education course designed with player-type personalization in gamification strategies. Using a mixed-methods approach, a one-group post-test-only design was combined with qualitative analysis. Game elements were personalized based on the HEXAD user typologies, aligning with Self-Determination Theory to support autonomy, competence, and relatedness. Quantitative data from the Intrinsic Motivation Inventory revealed high median scores across these psychological needs, suggesting that customization fostered deeper engagement. Key elements included cooperative challenges, branching narratives, and flexible participation pathways. Qualitative findings reinforced these results, highlighting students’ increased sense of agency, social connection, and investment in learning. The structured integration of narrative played a crucial role in contextualizing academic tasks, transforming the learning process into an immersive experience. Overall, the findings indicate that well-designed, personalized gamification strategies effectively bolster preservice teachers’ intrinsic motivation in this science education course. By demonstrating how player-type personalization optimizes motivation in gamified teacher education, this study contributes to the growing body of research on tailored gamification. Full article

Aquaculture is a globally widespread practice and the world’s fastest-growing food sector and requires technological advances to both increase productivity and minimize environmental impacts. Monitoring the sector is one of the priorities of state governments, international organizations, such as the Food and Agriculture Organization of the United States (FAO), and the European Commission. Data collection in aquaculture, particularly information on the location, number, and size of production facilities, is challenging due to the time required, the extent of the area to be monitored, the frequent changes in farming infrastructures and licenses, and the lack of automated tools. Such information is usually obtained through direct communications (e.g., phone calls and e-mails) with aquaculture producers and is rarely confirmed with on-site measurements. This study describes an innovative and automated method to obtain data on the number and placement of structures for marine and freshwater finfish farming through a YOLOv4 model trained on high-resolution images. High-resolution images were extracted from Google Maps to test their use with the YOLO model for the identification and geolocation of both land (raceways used in salmonids farming) and sea-based (floating sea cages used in seabream, seabass, and meagre farming) aquaculture systems in Italy. An overall accuracy of approximately 85% of correct object recognition of the target class was achieved. Model accuracy was tested with a dataset that includes images from Tuscany (Italy), where all these farm typologies are represented. The results demonstrate that the approach proposed can identify, characterize, and geolocate sea- and land-based aquaculture structures without performing any post-processing procedure, by directly applying customized deep learning and artificial intelligence algorithms. Full article

The primary aim of this study is to conduct a comprehensive review of the existing literature to identify the most relevant environmental variables and other factors influencing the life cycle assessment of the wine industry. This research seeks to determine whether the type of wine significantly impacts the carbon footprint and to highlight the importance of production strategies over wine typology or grape variety in reducing greenhouse gas emissions. This review encompasses an extensive analysis of previous studies on the environmental impact of wine production. This method involves synthesizing findings from life cycle inventory assessments to identify key variables contributing to greenhouse gas emissions. This analysis also considers regional variations and the effectiveness of different production strategies in mitigating environmental impacts. This review indicates that wine typology (red or white) and grape variety are less significant in determining the carbon footprint than the production strategies employed. It identifies specific variables that contribute substantially to greenhouse gas emissions in wine production. The analysis highlights the need for standardized assessment methods to ensure accurate determination of influential factors in reducing emissions. This study concludes that achieving environmental sustainability in the wine industry requires a balanced approach that integrates environmental, economic, and social aspects. It emphasizes the necessity of developing standardized and universal strategies for assessing wine sustainability. The application of artificial intelligence is proposed as a crucial tool for improving data gathering, trend analysis, and formulating customized sustainability strategies for different wine regions. Addressing the challenges of sustainability in the wine industry is imperative for environmental preservation and the wellbeing of future generations. Full article

A global trend regarding the “platformization” of the internet has been, for years, emerging roughly across all traditional industries. It is reflected in the proliferation of digital platforms (DPs) based on the creation of new activities or the online expansion of offers traditionally available only physically (e.g., boutiques, supermarkets). Thus, digital platforms are a new springboard of development opportunities for all businesses, and Africa, with demographic (more than 1.2 billion customers), economic (middle-class boom), and technological (internet and smartphone penetration) dynamism, represents a huge potential market for the DP industry. This exploratory research is based on a qualitative approach applied to the case of Senegalese DPs. From its finding, we have a mapping of DPs and a classifying typology of the types of actors involved, according to their specialization and their paradigmatic orientation. New insights into how DP organizations and the firms within them operate and create value are proposed as well as a new conceptual framework for the articulation of DPs, specifically those particularly adapted to the African context. This work opens avenues for future research linked to the scale of the new challenges related to marketing and managerial issues and the new business models that have recently been developed by innovative local actors (TukkiJamm, ShopMeWay, etc.). Full article

In the fast-paced digital economy, stakeholders across regions, industries and organisational typologies are recognising the growing significance of adopting customer-centric digital strategies. Inexorably, this necessitates the comprehension of consumer behaviours across a diverse customer spectrum, including individuals with disabilities (PwD). In this context, the present expert-driven conceptual research examines tourism digital sustainability and inclusion and elucidates the role of tourism e-commerce platforms in promoting a barrier-free digital environment for PwD and creating a more inclusive and sustainable online marketing landscape. The findings highlight the need for ongoing evaluation and improvement of the user experience to achieve satisfaction, loyalty and stakeholder engagement, as well as the factors in need of consideration towards a barrier-free and sustainable e-commerce environment. Further research could explore the assessment of the framework presented here in a practical context towards implementation to uncover its strengths and limitations. Full article

The evolution of base/bottom of the pyramid (BoP) literature from BoP 1.0 to 3.0 prompted the need for fresh theoretical perspectives to address complex and persistent social issues. This article investigates BoP through the lens of business model innovation, using a literature review along with bibliometric, network, and content analyses, to map the intellectual and conceptual structure and understand the key variables relating to BoP business models. The research encompasses 161 articles extracted from the Web of Science and Scopus databases. Documents were screened manually and with the assistance of VOS Viewer 1.6.18, Biblioshiny 4.0, IBM SPSS 20, UCINET6, and NVivo12, using abductive and deductive coding techniques. The findings reveal a prevailing focus on the exploratory phase among the articles, with a predominant utilization of qualitative research methods, particularly centered on case studies. Interviews and public data sources constitute the primary sources for supporting empirical evidence. Notably, the majority of these cases pertain to emerging economies situated across Asia, Africa, and Latin America, with India emerging as the most frequently cited country in the literature. Sectors, such as energy, healthcare, agrifood, finance, and telecommunications are studied, emphasizing themes of innovation, entrepreneurship, and corporate social responsibility (CSR). Emerging themes include social entrepreneurship, frugal innovation, and inclusive business models. The research panorama encompasses a categorization of BoP enterprises based on their origin (top-down or bottom-up), their typology (commercial, assistance, or collaboration), and their interactions with BoP communities (either as customers or entrepreneurs). From an innovation standpoint, certain concepts emerged, notably frugal innovation and bricolage, accompanied by the incorporation of ecosystem theory and sustainability perspectives. The research also outlines a BoP business model framework, providing insights into key components favored by entrepreneurs in this realm. Full article

Social media are an important approach for florists to reach consumers, and many florists have set incentives to encourage users to engage with their social media pages. However, various subjects can serve as rewards, but what is more effective for encouraging users to engage with the florists’ social media pages remains unknown. This study is intended to address this deficiency. The objectives of this study are as follows: (1) to explore the typology of the incentives used by succulent retailers to promote user engagement; (2) to compare the difference across various types of incentives in regard to the effect on promoting user engagement with succulent retailers’ social media pages. Data were gained from the succulent retailers’ empirical practices on their Facebook brand pages. As a result, 2602 Facebook posts were downloaded and analyzed via content analysis to explore the typology of the incentives applied by succulent retailers. The number of clicks on likes, comments, shares, and emojis by users was recorded as the index of user engagement with the post. The effect of various incentives on user engagement with the succulent retailers’ FB pages was analyzed via the statistical approach of MANOVA. The study results showed that the incentives applied by succulent retailers can be classified into three categories: economic incentives; social incentives; mixed incentives, which contain both economic and social values. The economic incentives included discounts, gifts, sweepstakes, and bidding, while social incentives included gratitude to customers, leaving a question mark, and inviting users to respond. The statistical results revealed that economic incentives are more likely to encourage users’ emotional engagement, while social incentives in the form of inviting users to react are more significant for encouraging users’ behavioral engagement in terms of leaving comments on posts. Full article

Heavy metals have become widespread urban pollutants, exposing vulnerable age groups such as children to potential risk. Specialists need feasible approaches that can routinely assist them in customizing options for sustainable and safer urban playgrounds. The aim of this research was to explore the practical relevance of the X-ray Fluorescence (XRF) method from the perspective of landscaping specialists, and the practical significance of screening for those heavy metals that currently present elevated levels across urban environments Europe-wide. Soil samples from six public children’s playgrounds of different typologies from Cluj-Napoca, Romania, were analyzed. The results indicated that this method was sensitive to identifying thresholds stipulated in legislation for the screened elements (V, Cr, Mn, Ni, Cu, Zn, As, and Pb). Coupled with the calculation of pollution indexes, this method can serve as a quick orientation in landscaping options for urban playgrounds. The pollution load index (PLI) for the screened metals showed that three sites displayed baseline pollution with incipient deterioration in soil quality (PLI = 1.01–1.51). The highest contribution to the PLI among the screened elements, depending on the site, was due to Zn, Pb, As, and Mn. The average levels of the detected heavy metals were within admissible limits according to national legislation. Implementable protocols addressed to different categories of specialists could help to transition towards safer playgrounds and more research on accurate cost-effective procedures to overcome the limitations of existing approaches is currently needed. Full article