ESTiG - Artigos em Revistas Indexados à WoS/Scopus
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- 2024 U.S. presidential elections: An event study for U.S. and non-U.S. fossil fuel and renewable listed firmsPublication . Martins, António Miguel; Albuquerque, Bruno; Sardinha, Luís; Moutinho, NunoThis study examines the short-term market effect of Donald Trump' victory in the 2024 US presidential election on largest US and non-US listed worldwide fuel fossil and renewable firms. Employing an event study methodology, we observe a negative and statistically significant stock price reaction for worldwide renewable listed firms. An analysis by economic zones reveals the existence of negative abnormal returns for renewable energy firms in the US, Europe, India and in the rest of the world. In the case of China, abnormal returns are not statistically significant. With respect to worldwide fossil fuel listed firms, abnormal returns are generally not statistically significant. However, regarding US firms, we observe positive and statistically significant abnormal returns. These abnormal returns are explained by the change of US energy policy (pro-oil and gas policy) and the expected cut in subsidies and lower profitability of investments in green energies. Finally, our study provide insight into which firm-specific characteristics emerge as value drives around US presidential elections. The results show that despite the change in environmental policy in the US, favourable to fossil energy, the stock markets reward firms with high environmental ratings. Overall, our results indicate that 2024 US presidential election, for implying a change in US energy policy, has relevant policy implications for energy listed firms.
- An AI-driven Ukrainian history web platformPublication . Kolomiets, Valentyna; Oliveira, Pedro Filipe; Matos, PauloThe AI-driven Ukrainian History web platform offers an innovative way for users to engage with the nation’s rich history. By integrating artificial intelligence, natural language processing (NLP), and geospatial analysis, it presents historical events, significant locations, and notable figures in an interactive and visually engaging format. The platform systematically gathers historical data using tools like Scrapy for web scraping and Tesseract OCR for digitizing scanned documents. While noisy or degraded documents may affect accuracy, the availability of high-quality sources ensures reliable data extraction. Fine-tuned NLP models, including transformers like BERT and RoBERTa, process the data to identify and categorize key entities such as dates, locations, and names of historical figures. Contextual summarization ensures the extracted information is both accurate and easy to understand. Geospatial data is managed with PostGIS, an extension of PostgreSQL, and visualized using Leaflet.js. An interactive map interface enables users to explore events by location and time period, with filters for categories like political milestones or cultural events. The backend, built on PostgreSQL, ensures scalability and performance, while development in Visual Studio Code streamlined integration across components. This platform not only preserves Ukraine’s cultural heritage but also demonstrates the potential of modern technology to transform historical education, offering an intuitive way to connect with the past and explore its influence on Ukraine’s landscape and culture.
- AI-enhanced neuromarketing and social media communication: evidence from PLS-SEM analysis in an academic contextPublication . Bucea-Manea-Tonis, Rocsana; Martins, Oliva M.D.; Orzan, Mihai Cristian; Goldbach, Dumitru; Popa, MirceaArtificial intelligence (AI) is reshaping neuromarketing by enabling the real-time analysis of neurometric, biometric, and psychometric data to optimize consumer engagement. This study investigates how AI-enhanced neuromarketing influences social media marketing strategies, using a structural equation modeling (PLS-SEM) approach to assess relationships between neuromarketing knowledge, application, activities, and social media communication. Data were collected through a survey of 416 Romanian university students and professors with practical exposure to neuromarketing tools in educational environments. The results confirm that neuromarketing knowledge significantly improves practical application (β = 0.726, p < 0.001), which in turn enhances both marketing activities (β = 0.555, p < 0.001) and social media communication effectiveness (β = 0.633, p < 0.001). AI was found to amplify these effects through predictive analytics, real-time consumer data processing, and automated content optimization. Ethical considerations—such as privacy risks and algorithmic bias— are acknowledged, and the academic sample limits generalizability to commercial contexts. Future research should explore cross-industry applications, diverse cultural settings, and longitudinal impacts to strengthen external validity.
- (Des)ordem informacional: Uma discussão sobre o plano institucional de comunicação de crisePublication . Moraes, Thiago Assunção de; Cordeiro, Juliana de Oliveira; Reis, Uesllei SousaO acesso rápido e fácil às informações por meio da internet provoca desafios quanto ao seu controle e gerenciamento. A percepção de liberdade pode favorecer a criação e a disseminação de notícias falsas, um problema presenciado por pessoas e instituições. Desse modo, como podemos extinguir notícias falsas e comportamentos oportunistas no fornecimento de informação? Esse caso busca contribuir para o desenvolvimento das habilidades de análise, diagnóstico e busca por soluções; despertar o aluno para possíveis ameaças; exercitar a criatividade na tomada de decisões e na concepção de estratégias, orientando-o, assim, à responsabilidade pela informação e à consulta de fontes oficiais. Os fatos apresentados no enredo do caso para ensino foram inspirados em acontecimentos reais no Instituto Federal do Piauí (IFPI). Apesar da história ser fictícia, acontecimentos nesse sentido eventualmente ocorrem na instituição. As informações são oriundas do IFPI, extraídas através da Diretoria de Comunicação e do site da instituição. A página oficial do IFPI no Instagram também constitui fonte de dados. O caso pode ser utilizado em disciplinas de graduação e pós-graduação lato sensu, nos cursos de Tecnologia da Informação, Comunicação Social, Administração e Gestão Pública, que discutam temas como: imagem institucional, gestão, crise, divulgação (e suas ferramentas), comunicação estratégica.
- Digital transformation and the new combinations in tourism: a systematic literature reviewPublication . Gutierriz, Ives; Ferreira, João J.; Fernandes, Paula OdeteThis study aims to analyse the research involving the evolution and development of digital transformation and the new combinations in tourism development. To this end, a systematic literature review was conducted in the Scopus and Web of Science databases, which gathered 167 studies published between 1997 and 2023, representing the final sample analysed in this review. The results allow the identification of three main findings: i) there are four thematic groups - Digital Marketing, Digital Economy, Education and Hospitality and Free Digital; ii) there is a growing interest in the research of this topic and the use of available technologies for the development of tourism companies and their businesses and the respective wider economy; and, iii) digital transformation tends to be a positive factor when applied to the tourism sector. This research further proposes a framework that provides a detailed description of these studies with key issues and contributions from the available literature.
- Ethical challenges using technology in sport competitionsPublication . Bucea-Manea-Țonis, Rocsana; Păun, Dan G.; Coelho, Ana Sofia; Urdes, Laura; Mihoreanu, Larisa; Martins, Oliva M.D.Purpose: Technologies such as artificial intelligence or tools such as AR and VR can potentially improve performance in sports. However, not all athletes, coaches, or sports clubs can access these resources. In addition, ethical issues related to data protection need to be considered. This research aims to evaluate the main challenges and potential drawbacks of using innovative technologies in sports, which may have an influence on their measures and the utility of innovative technologies. Design/methodology/approach: Considering Ethics in Sports, Ethical Measures, and Tech Benefits, to evaluate the main challenges and potential drawbacks of tech introduction in sports, which may influence their measures and the utility of innovative technologies, quantitative descriptive research was developed, and statistical analysis was carried out. Findings: This research found that ethical technologies in sports influence ethical measures, but technologies` utility influences ethical measures. It is necessary to broaden knowledge of the complex and dynamic relationships associated with the use of technology, to understand better the advantages and possible disadvantages associated with it, to promote the involvement of the different stakeholders, and to promote long-term engagement–the main consequences of introducing technology into sports influence both the measures and the usefulness of innovative technologies. Research limitations/implications: This study has many limitations, namely that it includes self-reported data and has a cross-sectional design, which may cause a conscious or unconscious bias. Practical implications: Ethical aspects of the use of technology, such as justice and equity, need to be considered. Social implications: It is well known that some technologies and tools, such as artificial intelligence, augmented reality (AR), or virtual reality (VR), can improve performance in sports. However, not all athletes, coaches, or sports clubs have access to these types of resources, which raises an ethical question regarding parity or fairness in competitions.
- Goliath and the cognitive load theoryPublication . Freitas, Tiago Carvalho; Costa Neto, Alvaro; Pereira, Maria João; Henriques, Pedro RangelA successful teaching effort is usually dependant on several factors. From the right environment, to a precisely worded exercise statement, it rests on the teacher's shoulders the concoction of the most effective learning assets to their students. A significant part of this process lies on practise: students commonly solidify their knowledge by solving exercises. Creating new programming exercises, specially in high-demand environments such as large classrooms, is a repetitive and error-prone process, specially when stacked with other typical affairs that educators are required to attend to. Goliath, one of the two main contributions of this article, is a template-based, Artificial Intelligence (AI) supported exercise generator, that aims to facilitate the creation of exercise repositories. By using a Domain-Specific Language (DSL) to define exercise templates, combined with the automatic generation of different exercise types, educators can use Goliath's features to improve their exercise repositories, both in size and variety. This systematic approach allows for greater control and automatisation than using a Large Language Model (LLM) directly, as the exercises’ main components can be pre-defined and pre-configured via their templates. Goliath, which is available online for free access, has been tested and its usability assessed. Combined with these functionalities, the content of the exercises themselves, the manner in which they are presented, and how they are rated for difficulty should also be considered in high regard when designing programming exercises. The Cognitive Load Theory (CLT) provides a conceptual foundation to understand problem-solving mechanisms that are commonly found in several aspects and situations of daily life, such as solving programming exercises. This foundation has been explored and systematically structured to construct the second main contribution of this article: guides to create exercise templates in Goliath founded on the Cognitive Load Theory, aiming to improve both teaching and learning computer programming.
- Impact of hyper-parameter tuning on CNN accuracy in agricultural image classificationPublication . Mendes, João; Lima, José; Costa, Lino; Hendrix, Eligius M.T.; Pereira, Ana I.This study explores the impact of hyper-parameter optimization on the performance of convolutional neural networks (CNNs) for olive cultivar classification using transfer learning. Pre-trained ImageNet models such as VGG16, InceptionV3, and ResNet50 were adapted to a proprietary dataset, with VGG16 selected for detailed evaluation. Key hyper-parameters, including layer count, neurons per layer, dropout rate, learning rate, and batch size, were tuned using random search. The best configuration achieved a validation accuracy of 87.5%, significantly outperforming the control model. Sensitivity analyses with Morris and Sobol methods identified the number of layers as the most influential factor, followed by dropout and learning rates through interaction effects. These findings demonstrate the importance of tailoring CNN architecture and regularization settings to the problem domain. These results underscore the importance of tuning architectural depth and regularization mechanisms for performance optimization. As a practical guideline, models with fewer layers and intermediate dropout levels demonstrated higher robustness and generalization, offering an effective strategy for adapting CNNs to agricultural classification tasks.
- Insights from a five-year academic analytics observatory: challenges and achievementsPublication . Franco, Tiago; Alves, Paulo; Rufino, José; Pacheco, Maria F.; Ribeiro, Nuno A.This paper presents a five-year case study of the development and operation of the Academic Success Observatory, an institutional platform designed to support data-driven academic management in higher education. The system combines automated data extraction modules, interactive dashboards, and a machine learning-based dropout prediction model. Drawing from three institutional databases, updated weekly, the platform enables continuous monitoring of academic indicators, report generation, and targeted support actions. The article discusses key technical and institutional challenges faced, as well as the benefits of integrating the platform into the academic decisionmaking process. The results highlight the system’s potential to enhance decision-making, enable faster interventions, and foster a data-informed institutional culture.
- Learning a foreign language: traditional listening vs interactive immersive virtual realityPublication . Peixoto, Bruno; Gonçalves, Guilherme; Bessa, Maximino; Bessa, Luciana C. Pereira; Melo, MiguelImmersive Virtual Reality (iVR) is a promising educational tool for learning a second/foreign language. However, interactive iVR studies remain in their infancy, with more research required to validate what and how it can be implemented. This study focuses on the English listening dimension and evaluates the impact of a realistic interactive iVR compared to traditional listening exercises. The results were favourable and indicated that interactive iVR positively impacts the users’ knowledge retention compared to a traditional listening approach. Likewise, the users revealed a preference for using iVR for learning when compared to traditional listening exercises, as well as higher user satisfaction with the iVR experiment.
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