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4806 Articles

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Economic policy uncertainty, information production, and transparency

Economic policy uncertainty, information production, and transparency

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  • Journal IconInternational Review of Financial Analysis
  • Publication Date IconJul 1, 2025
  • Author Icon Binsheng Qian + 3
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ACCURACY OF INFORMATION ON SCORPION ACCIDENTS: A STRATEGY TO COMBAT DISINFORMATION

New information and communication technologies have enabled unparalleled access, production, and dissemination of information. However, However, the veracity, completeness, and intelligibility of this information can be questionable. Misinformation concerning health-related topics can cause harm to individuals and communities. Assessing the quality of health information on the internet can be a critical approach to adress this issue. This article presents an instrument for evaluating the accuracy of information on scorpion accidents, a growing problem in Brazil, as revealed by the results of the evaluation of information on scorpion accidents available on the Ministry of Health's “Health A-Z” website. The instrument consists of 21 indicators distributed in the dimensions of prevention, symptoms, diagnosis and treatment of scorpion accidents. The results indicate that 43% of the information available on the Ministry of Health's website complies with the indicators constructed.

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  • Journal IconARACÊ
  • Publication Date IconJul 1, 2025
  • Author Icon Fabiana De Azevedo Soares + 3
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Rainfall forecast and potential flooding of agricultural land in Serang Regency, Banten, Indonesia

Serang Regency has a sub-tropical climate and is classified as lowland, generally consisting of rice fields, fields, and gardens. These three lands have the potential to flood during the rainy season, which has implications for a decrease in agricultural production. Flood forecasts are carried out on agricultural land to avoid decreased production. The data used included rainfall, harvest area, and agricultural production. Estimates of farmland flooding and agricultural production changes are overlayed with Geographic Information Systems (GIS) and production percentages. The results of rainfall analysis show that the monthly average rainfall in Serang Regency is categorized as low to high. Meanwhile, heavy rain has the potential to occur in January and February. After being coated with GIS, it is spatially predicted that six sub-districts with an altitude below 10 meters above sea level have the potential to flood. Of the six sub-districts, 2,902.80 ha of agricultural land is estimated to have the potential to be flooded. Flooding in the area has implications for decreasing the production of seasonal crops, vegetables and fruits. Food crop production decreased by 0.42 %, while seasonal vegetables and fruits decreased by 48.04 %. There are five types of food crops and 12 types of vegetables and fruits that have the potential to be developed in Serang Regency. The food crop with the most significant production is rice, while the seasonal production of vegetables and fruits is cucumbers. In the event of a flood, rice production in Serang Regency is predicted to decrease by 1.23 % and cucumber production is expected to decrease by 0.48 %. It is necessary to adopt a planting pattern with a climate approach to minimize the decline in production.

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  • Journal IconMathematical Models in Engineering
  • Publication Date IconJun 30, 2025
  • Author Icon Yayat Ruhiat + 3
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Implementation of lean manufacturing in the spinning industry to increase production efficiency

The spinning industry is an important part of the textile sector that faces efficiency challenges due to the large amount of waste in the production process. This study aims to analyze the implementation of Lean Manufacturing as a strategic approach to improving production efficiency in one of the medium-scale spinning companies in West Java. Using a qualitative descriptive method, data were obtained through direct observation, in-depth interviews with six key informants, and analysis of company documents. The results of the study indicate that the application of Lean principles such as 5S, Just-In-Time (JIT), Total Productive Maintenance (TPM), and Visual Management can reduce waiting time between processes by 55%, reduce the frequency of machine breakdowns by 62.5%, and increase the orderliness of the work area by 68%. Even so, the implementation of lean is not free from challenges such as the mismatch of production schedules with machine readiness, resistance to work culture from senior employees, and lack of in-depth understanding of lean tools. This study confirms that the success of Lean Manufacturing depends not only on the tools used, but also on the readiness of the organizational culture and supporting information systems. These findings provide practical contributions to the development of efficient and sustainable operational management strategies in the spinning industry, and offer recommendations in the form of integrated training, integration of production information systems, cross-departmental evaluation, periodic lean audits, and performance-based reward schemes.

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  • Journal IconJurnal Konseling dan Pendidikan
  • Publication Date IconJun 25, 2025
  • Author Icon Sih Parmawati + 4
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Session 7. Oral Presentation for: A novel way to achieve early commercialisation of tight-sand and shale gas fields: small-scale modularised liquefied natural gas

Presented on 27 May 2025: Session 7 Based upon published reports, tight-sand and shale gas are one of the largest sources of natural gas under development globally, with annual production increasing dramatically from 2008 to 2023. This was particularly so in China, driven by advancements in drilling and completion technology such as multi-stage hydraulic fracturing in long horizontal wells. Given Australia’s geological setting and industrial environment, which have some similarities with USA and Canada, the country has potential to become a major player in commercially viable tight sand/shale gas production. An estimated 12.93 TCF of 2C contingent gas resources have been identified in Australia, primarily located in the Beetaloo Sub-basin within the greater McArthur Basin, as well as in the Cooper Basin, Canning Basin and Bowen-Surat Basins. However, developing tight-sand and shale gas resources in Australia presents numerous challenges, including their remote location, lack of existing gas export infrastructure, and well productivity constraints due to restrictions on the use of hydraulic fracturing. Additionally, a high-cost environment further hinders the path to commercial production. In China, a small-scale modularised LNG production approach has been successfully applied to tight sand/shale gas developments in the Sichuan Basin, demonstrating how early cash flow and extended production information can provide key support for an operator’s financial position in the market, increasing the chance of development. Lessons from these case studies could be instrumental in overcoming the challenges faced by Australia’s operators for development of this resource type, potentially paving the way to successful commercialisation. To access the Oral Presentation click the link on the right. To read the full paper click here

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  • Journal IconAustralian Energy Producers Journal
  • Publication Date IconJun 19, 2025
  • Author Icon Hongfeng Wu
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Generative artificial intelligence in education: (what) are we thinking?

ABSTRACT Debates linking generative artificial intelligence (Gen-AI) to knowledge work have become increasingly popular, with discussions of technological innovation and information production efficiency central to the justification of its integration in education contexts. Questions are however raised about the intellectual capacities that these technologies appear to replace or provide, with a special emphasis placed on the activity of thinking, an element so essential to a contemplative life. Inspired by Arendt’s preoccupation with society’s state of ‘thoughtlessness’ and Freire’s critical pedagogy, this article explores how the role of thinking is impacted by the introduction of Gen-AI in education. Via these theoretical engagements, we argue that the presence of Gen-AI in education can have serious consequences for the intellectual development of individuals and that working towards a culture of learning that responsibilises thinking, also as a form of intellectual honesty, is key to preserving individuals’ thinking agency.

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  • Journal IconLearning, Media and Technology
  • Publication Date IconJun 18, 2025
  • Author Icon Cristina Costa + 1
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Friendships to Perish and Friendships to Cherish: Corporate Political Tactic and Earnings Management Method

Abstract Critical of a literature which examines corporate political connections with scant attention to their dynamic nature, we blend political theory with inter‐organizational exchange research to propose and test a framework based on which firms’ earnings management (EM) method can vary predictably with their political tactic. Using hand‐collected data on political money spent by US firms, we reveal an unknown dichotomy. Firms taking a transactional approach to politics tend to use the least costly EM method, substituting accruals‐based EM (AEM) for real EM (REM). Conversely, firms following a relational approach, concerned that possible detection may alienate career‐focused politicians, substitute REM for AEM. Consistent with the goodwill trust in the firm–politicians relationship moderating the EM trade‐off, firms revert to AEM when the trust is impaired and they no longer perceive the need to insulate politicians from reputational damage. Notwithstanding the firm's political tactic, the total EM remains unaffected, suggesting perfect substitution. As a refined and dynamic lens for examining firm–politicians exchanges, our framework reconciles the conflicting evidence of prior studies on how political connections affect reported earnings and is generalizable to other third‐party affiliations that may have important reputational stakes but no monitoring capacity over the production of financial information.

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  • Journal IconBritish Journal of Management
  • Publication Date IconJun 11, 2025
  • Author Icon Antonios Kallias + 4
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An Examination Of The Influence Of Leadership On The Execution Of Knowledge Management Strategies Inside: The Chinese Family Of Kings

The Greater China area's sectors display a wide range of approaches to knowledge management, information communication, and knowledge development. This research examines it in light of several new technologies, with Big Data at the forefront. The enabling environment has been shortened by scientists to "Big Data Context" (BDC). As China works to become an information-based economy and society, knowledge management is becoming more important. This study use quantitative methods to investigate the BDC's internal processes for knowledge generation and distribution. A quantitative method was used in this investigation. Researchers also conducted 24 semi-structured interviews with informants in addition to field notes. The second step was to conduct a thorough industry-scale survey and use structural equation modelling (SEM), a quantitative method, to assess the underlying structure of the model's dependability. The constructs as variables have a modest but comprehensive and, for the most part, favourable influence on knowledge development and sharing when applied to the BDC/KM environment. Using SEM with the constructs as variables, the researcher identify key stakeholders in information sharing and important mediators in knowledge development. Modern substantive theory predicts that a slew of innovative innovation shape China's Big Data environment. At its heart, Big Data has a profound effect on the dissemination and production of new information. Incorporating BDC into the knowledge management system is essential, according to the results.

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  • Journal IconFrontiers in Health Informatics
  • Publication Date IconJun 6, 2025
  • Author Icon Zhu Meixia + 1
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Sustainable production and consumption ease of robotic disassembly metric and information for digital product passports in flexible remanufacturing systems

Sustainable production and consumption ease of robotic disassembly metric and information for digital product passports in flexible remanufacturing systems

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  • Journal IconSustainable Production and Consumption
  • Publication Date IconJun 1, 2025
  • Author Icon Terrin Pulikottil + 3
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Potential for Machine Learning Emulators to Augment Regional Climate Simulations in Provision of Local Climate Change Information

Abstract High-resolution regional climate simulations provide detailed information on future climate change to support decision-making. Ensembles of simulations, including at kilometer-scale resolution, are becoming available from international coordinated initiatives, but these do not effectively sample the full range of uncertainties. Machine learning (ML) has already been used for statistical downscaling but has the potential to augment high-resolution simulations, via emulators, enabling rapid production of local climate information at a fraction of the cost. Here, we explore skill in ML-based emulators sampling a range of architectures and identify remaining scientific issues that need to be addressed before such emulators can be considered ready for application in climate services. This includes the ability to capture extremes, produce coherent multivariate predictions, account for memory in the climate system, and robustly downscale other (out of sample) global climate models. Climate expertise needs to be integrated into the development and evaluation of ML emulators, and here, we provide recommendations on validation methods. If skillful, ML emulation has implications for how we coordinate and perform regional climate simulations. We should focus on running at the highest resolution and greatest Earth system complexity affordable, to give the best representation of processes at the local scale, for subsequent training of ML emulators. Emphasis should be on sampling the full range of conditions, including high-end scenarios. Overall, ML has promise to augment our production of regional-to-local climate projection information over the next 5–10 years, and as a climate community, we need to come together to address the relevant scientific issues.

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  • Journal IconBulletin of the American Meteorological Society
  • Publication Date IconJun 1, 2025
  • Author Icon Elizabeth J Kendon + 9
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Dual-Reward Reinforcement Learning with Intrinsic Exploration Mechanisms for Real-Time Reservoir Management

Summary In the process of oil and gas reservoir development, the natural heterogeneity of the reservoir makes the development performance extremely sensitive to the matching of the injection-production well control scheme. Reasonable production optimization is the key to achieving balanced displacement and efficient development. Due to the complexity of oil and gas reservoirs and the large number of variables, traditional production optimization methods often face problems, such as complex and time-consuming calculations, hindering their ability to obtain global optimal solutions. Reinforcement learning (RL), with its intrinsic strengths in sequential decision-making and high-dimensional problem solving, offers a promising alternative for production optimization. Nevertheless, existing RL approaches exhibit limited exploration capabilities in complex reservoir environments, often becoming trapped in local optima. Additionally, they typically fail to incorporate well pattern information effectively, overlooking the location information and the connectivity between injection and production wells. To address these challenges, we propose a dual-reward coupled RL production optimization algorithm based on a global perspective. Specifically, the production optimization problem will be modeled as a Markov decision process. Through the intrinsic reward mechanism, the agent is encouraged to conduct deeper exploration to overcome the optimization limitations in complex environments, and the well network production information is integrated into the model in combination with the graph neural network (GNN) to enhance the modeling ability of the dynamic characteristics of the reservoir. In this way, the agent can effectively avoid relying only on local objectives for optimization and then achieve a more balanced injection and production strategy. The proposed method adaptively learns by engaging in intrinsic-extrinsic directional interactions with the uncertain reservoir environment, effectively leveraging accumulated well control experience in a manner that is similar to real-world field operating mode. Simulation results derived from two reservoir models demonstrate that, in comparison with other optimization methods, the proposed approach achieves higher net present value (NPV) and exhibits outstanding performance in oil displacement. Keywords Production Optimization, Intrinsic Reward, Extrinsic Reward, Deep Reinforcement Learning, Graph Neural Network

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  • Journal IconSPE Journal
  • Publication Date IconJun 1, 2025
  • Author Icon Guojing Xin + 7
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The Role of AI in Social Media Misinformation: Strategies and Impacts

Abstract: Artificial intelligence (AI) has significantly influenced content distribution on social media, but it has also contributed to the rapid dissemination of misinformation. AI-powered technologies, such as deep fake manipulation, automated content creation, and engagement-driven algorithms, facilitate the swift production and amplification of false information. This paper investigates how AI is leveraged to spread misinformation across major social media platforms, including Facebook, Twitter (X), YouTube, and Instagram. Through a case study approach, we examine real-world incidents where AI-generated content has misled users, particularly in political campaigns, public health crises, and viral digital trends. Social media algorithms, designed to boost engagement, often unintentionally amplify misleading content, making the detection and regulation of misinformation more challenging. This study explores the difficulties in identifying AI-generated fake news and assesses the effectiveness of current fact-checking mechanisms and moderation strategies. While AI plays a role in propagating misinformation, it can also serve as a solution through advanced natural language processing (NLP), deep fake detection technologies, and automated verification systems. The findings emphasize the necessity of ethical AI usage, enhanced content moderation techniques, and stricter regulatory frameworks to curb AI-driven misinformation. Strengthening detection technologies and raising public awareness can significantly reduce the impact of false information on social media ecosystems.

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  • Journal IconInternational Journal for Research in Applied Science and Engineering Technology
  • Publication Date IconMay 31, 2025
  • Author Icon Akash Kumar + 1
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Climate Change Information and Potato Production in Ebonyi State, Nigeria

The study examined climate change information and potato production in Ebonyi State, Nigeria. About 96 potato farmers were selected using a purposive method. Primary information on the objectives of the study was collected with questionnaire and analysed using percentages, charts, and the probit regression model. The results show that potato farmers were of a productive age, married, experienced, and relatively educated. Most of the potato growers (90.6%) were highly aware of the changing climate disturbance. Radio (97.9%), fellow farmers (98.9%), workshops/training (91.7%), and newspapers (10.4%) formed sources of climate information. The farmers’ adaptation strategies were modifying planting dates (77.1%), using drought-resistant varieties (86.5%), applying irrigation methods (54.2%), diversifying crops (97.9%), practising crop rotation (93.8%) and organic farming (98.9%). Probit regression analysis indicated that education (P < 0.01), household size (P < 0.01), farming experience (P < 0.01), access to early climate change information (P < 0.01), and extension contacts (P < 0.1) were favourable determinants. In conclusion, potato farmers faced several challenges including climate-related issues, pests and diseases, limited resources and credit access, soil quality and fertility problems, and market fluctuations. The study's originality stems from its research survey in linking climate information to potato production and advancing potato farmers' knowledge. The study recommended the implementation of educational programs that focus on climate change awareness, sustainable farming practices, and the use of climate-smart technologies and seeking early climate information and extension services in improving crop performance.

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  • Journal IconResearch on World Agricultural Economy
  • Publication Date IconMay 30, 2025
  • Author Icon Emeka Emmanuel Osuji + 17
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Implementasi Digitalisasi Laporan Produksi Harian di Industri Manufaktur Untuk Meningkatkan Efisiensi dan Akurasi Data

The development of science and technology is increasingly rapid, including in the industrial world in the production and manufacturing sectors, technology is increasingly used in improving company performance. In the Manufacturing Industry, including the Fast-Moving Consumer Goods (FMCG) sector, it continues to strive to improve operational efficiency and productivity. This digitalization has been key in this effort. Through the integration of digital technology, companies can automate their production processes, increase visibility over operational performance, and make informed decisions. Prior to digitization, daily reporting often involved manually collecting data from various sources, such as production machines, operators, and physical work daily sheets. This can lead to errors in data entry, delays in processing and difficulty interacting data from different systems. This digitalization training aims to improve operational efficiency, improve data accuracy, and increase the accessibility of production information, such as knowing the process or flow in making daily reports to visualizing production data so as to make it easier for the Operations and Management Team to monitor factory productivity.

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  • Journal IconJournal Scientific of Mandalika (JSM) e-ISSN 2745-5955 | p-ISSN 2809-0543
  • Publication Date IconMay 28, 2025
  • Author Icon Wely Teguh Setyawan + 2
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La digitalització deis gabinets de premsa i comunicació. Estudi del cas del Servei Català de Transit (SCT)

The digitalization of press and communications offices has unleashed the appearance of new information production processes at the disposal of the journalist, which modify the productive routines of these offices. Their employees acquire new habits and know-how and thus become more versatile. However, there are also some tensions that are generated. Online contents do not satisfy the needs of those who inform , who demand more data and audiovisual material adapted to their requirements. And they do this by telephone because personal contact offers them communicative advantages that the digital offering does not provide.

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  • Journal IconTripodos
  • Publication Date IconMay 26, 2025
  • Author Icon Sonia González Molina
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Large language models’ capabilities in responding to tuberculosis medical questions: testing ChatGPT, Gemini, and Copilot

This study aims to evaluate the capability of Large Language Models (LLMs) in responding to questions related to tuberculosis. Three large language models (ChatGPT, Gemini, and Copilot) were selected based on public accessibility criteria and their ability to respond to medical questions. Questions were designed across four main domains (diagnosis, treatment, prevention and control, and disease management). The responses were subsequently evaluated using DISCERN-AI and NLAT-AI assessment tools. ChatGPT achieved higher scores (4 out of 5) across all domains, while Gemini demonstrated superior performance in specific areas such as prevention and control with a score of 4.4. Copilot showed the weakest performance in disease management with a score of 3.6. In the diagnosis domain, all three models demonstrated equivalent performance (4 out of 5). According to the DISCERN-AI criteria, ChatGPT excelled in information relevance but showed deficiencies in providing sources and information production dates. All three models exhibited similar performance in balance and objectivity indicators. While all three models demonstrate acceptable capabilities in responding to medical questions related to tuberculosis, they share common limitations such as insufficient source citation and failure to acknowledge response uncertainties. Enhancement of these models could strengthen their role in providing medical information.

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  • Journal IconScientific Reports
  • Publication Date IconMay 23, 2025
  • Author Icon Meisam Dastani + 2
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Transforming Customer Experience in Digital Banking Through Machine Learning Applications

In the contemporary landscape of digital banking, the transformation of customer experience has emerged as a pivotal focus for financial institutions seeking competitive differentiation. Through the integration of machine learning applications, banks are now able to analyze vast datasets to improve service delivery, enhance customer engagement, and personalize user interactions. Leveraging algorithms capable of discerning patterns within customer behavior, banks can proactively offer services tailored to individual needs, thereby fostering an environment that prioritizes customer satisfaction and loyalty. Machine learning technologies serve multiple purposes in bolstering customer experience. Firstly, they enable predictive analytics that forecast customer needs, reduce churn rates, and inform product development. By employing natural language processing, banks can assess sentiment from customer communications, allowing for targeted interventions that address concerns before they escalate. Additionally, machine learning models facilitate real-time transaction monitoring to detect fraudulent activities, thereby building trust and security in banking products. Furthermore, through automated customer service channels, such as chatbots, banks enhance operational efficiency while providing immediate support, mitigating common issues faced by users. Consequently, the application of machine learning in digital banking is reshaping the customer experience by creating more intuitive, responsive, and secure banking environments. As banks embrace these technologies, they not only streamline internal processes but also cultivate a deepened understanding of their clientele, leading to more meaningful interactions. This essay delves into the intricate relationship between machine learning applications and customer experience enhancement in digital banking, examining case studies, best practices, and the inherent challenges faced by institutions navigating this transformative journey. By focusing on actionable insights derived from data-driven methodologies, it posits that successful digital banking strategies hinge upon the effective integration of machine learning, ultimately defining the future of customer interaction in the financial sector.

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  • Journal IconInternational Journal of Engineering and Computer Science
  • Publication Date IconMay 23, 2025
  • Author Icon Bharath Somu
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The impact of social media information on brand evangelism: a moderating effect model based on three-way interaction

PurposeThis study aims to investigate the impact of social media information (argument quality, post attractiveness, and post popularity) on brand evangelism, as well as the mediating role of value resonance and the moderating role of personal relevance and product type.Design/methodology/approachThis paper distributed no fewer than 600 questionnaires to gather data from the virtual brand communities of sneakers, which are utilitarian products, and smartphones, which are hedonic products. This paper tested the proposed hypothesis using AMOS and SPSS software.FindingsSocial media information has a significant positive effect on brand evangelism. Value resonance mediates the relationship between social media information and brand evangelism. The higher the personal relevance, the more significant the mediating effect of value resonance. The interactions between product type, personal relevance, post attractiveness, and post popularity were significant, respectively, and personal relevance had a greater effect on the relationship between social media information and value resonance in hedonic products than in utilitarian products.Research limitations/implicationsThere are many social media channels; this paper only selects the relevant information in the virtual brand community. The follow-up can choose different social media platforms, such as microblogging, micro, etc., based on different social media characteristics to do further in-depth research.Practical implicationsTo provide theoretical suggestions for promoting consumer brand evangelism by studying the influencing factors of consumer brand evangelism in social media information. This paper can guide enterprises to provide feasible suggestions to improve user stickiness by guiding consumer values when releasing information.Social implicationsWith the prevalence of the “fan economy”, the role of consumers has undergone a major shift, and the impact of consumer communication and interaction on brands has become more and more far-reaching. This paper reveals that the quality, attractiveness, and popularity of information can drive brand evangelism by resonating with consumers' values, and this finding suggests that enterprises should pay attention to the production and dissemination of information to create a good information environment.Originality/valueThis study adds to the body of literature by examining the impact of social media information on brand evangelism while accounting for the moderating effects of product type and personal relevance. It emphasises the significance of value resonance and offers marketers of various product types insightful information.

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  • Journal IconAsia Pacific Journal of Marketing and Logistics
  • Publication Date IconMay 22, 2025
  • Author Icon Yi Wang + 3
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Multidimensional urban classification of ecoparks

Approaches to the formation of multidimensional urban classification as a way of production and presentation of scientific information are outlined. Such classification is developed for ecoparks - specialized objects of landscape architecture, park forestry, landscape urban protection, - instances of regional strategy and urban planning. On this basis the modern tendencies of creation of these innovative landscape and urban planning forms are revealed, their basic subtypes are established, as well as the peculiarities of design of the latter. Theoretical and verbal models are developed for each of the subtypes. The general regularities of the formation of ecoparks of different subtypes, fixed by the stable correlations of their qualitative and quantitative characteristics, are determined.

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  • Journal IconUrban construction and architecture
  • Publication Date IconMay 22, 2025
  • Author Icon Daria D Chernyshova + 2
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Resentment and revolt: The shared anger of the Brazilian and Nordic punk movements of the 1980s

In this article, I analyse the political articulations and interactions between São Paulo punks and their Nordic counterparts, particularly in Helsinki and Oslo, during the 1980s. Preliminary findings suggest that São Paulo punk groups actively participated in the global punk movement in the context of Brazil's military dictatorship and the shifting geopolitical landscape of the Cold War. During this period, Nordic and Brazilian punks regularly exchanged information and musical productions, sharing a common political passion. I interpret punk’s political and aesthetic articulations through the distribution of the sensible, fostering new ways of being together. I also draw on theories of resentment and revolt to illustrate how punk engages with politics and social formations in specific ways. Through an analysis of exchanges between Finnish and Brazilian punks, my article highlights multiple aesthetic and political dialogues between punk cultures in Norway, Finland and Brazil, shedding light on how punk’s political and aesthetic forces emerge as products of diverse cultural and affective interactions.

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  • Journal IconPunk & Post-Punk
  • Publication Date IconMay 22, 2025
  • Author Icon João Augusto Neves Pires
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