Polytechnic Institute of Cávado and Ave

This article aims to systematically analyse the main trends in formulating digital strategies aimed at environmental sustainability. In particular, it will examine the use of these strategies to foster the development of sustainable initiatives and the need for integrating technological innovation with environmentally responsible practices. Carrying out a systematic review of the literature, the study exposed a variety of approaches that encompass innovations in products and services, energy efficiency through smart technologies and the development of digital platforms that support the circular economy. The success of these initiatives depends significantly on collaboration between different sectors and the strategic use of data.

Virtual reality (VR) has gained significant attention in various fields including healthcare and industrial applications. Within healthcare, an interesting application of VR can be found in the field of physiotherapy. The conventional methodology for rehabilitating upper limb lesions is often perceived as tedious and uncomfortable. The manual nature of the process, performed by physicians, leaves patients in an environment lacking motivation and engagement. This presents an opportunity for implementing VR as a tool to enhance the rehabilitation process and improve the quality, efficiency, and evolution of recovery. However, physiotherapy often lacks relevant data to track the recovery process effectively, further compounding concerns about its efficacy. To address this, we propose the development of a posture control system using the Oculus Quest 2, a VR device. Our primary objective was to validate the performance aspects of this device and assess its potential as a rehabilitation tool, providing valuable support to healthcare professionals. Through a series of tests, we evaluated the effectiveness of our VR solution by integrating it into specific therapeutic exercises. This approach enhances patient involvement by offering real-time feedback on exercise execution and providing clear instructions for posture correction. The results demonstrate a notable impact on exercise performance, highlighting the feasibility of developing physiotherapeutically adapted solutions utilizing VR technology. By leveraging the Oculus Quest 2 system and the proposed framework, our research contributes to the advancement of VR-based rehabilitation practices. The findings offer valuable insights into the potential benefits of integrating immersive technologies into the field of physiotherapy, empowering healthcare professionals in their treatment approaches.

Establishing strong bonds between consumers and brands is a key objective for organizations, as it leads to positive outcomes such as favorable Word of Mouth (WOM), commitment, loyalty, and a willingness to pay premium prices (Orth et al., 2010; Kim et al., 2005). Grisaffe and Nguyen (2011) noted that organizations can benefit by fostering effective and lasting attachment to a brand. Given its exploratory potential and wide range of practical applications, this article focuses on studying the impact of brand attachment on consumer behavior in the luxury car market, specifically concerning Porsche customers’ opinions, perceptions, and attitudes. Thus, the central research question emerges: “How does brand attachment influence the customer’s connection with a luxury car brand?” In this context, the main objectives of this chapter are to analyze the predisposition of luxury car brand customers, with a focus on Porsche, toward satisfaction, commitment, trust, and loyalty, and its relationship with Brand Attachment; to understand the specifics of the customer’s decision-making process when choosing luxury car brands, given the available alternatives; to examine the profile and behavior of consumers in specific marketing contexts (in this case, customers of luxury car brands); and to identify the practical implications of Brand Attachment in the luxury segment of the automotive market.

An in-depth understanding of the business dynamics of a given sector enables key stakeholders to define appropriate strategies for its development, promotion and consolidation. This study aims to analyse the Portuguese tourism and hospitality sector, characterising the companies and their business dynamics between 2011 and 2022. It uses a Related-Samples Friedman‘s Two-Way Analysis of Variance by Ranks to identify any statistically significant differences between the subsegments of Hotels and Restaurants, Recreational and Cultural Activities, and Transports and Logistics using specific competitiveness indicators. The results show significant differences between the subsegments in some indicators. The sector is resilient and plays a key role in recovering from highly impactful challenges. Micro and small companies employ thousands of people and make hotels and restaurants a key subsegment of activity for the sector. This study contributes to a comprehensive understanding of the dynamics of the tourism sector, providing valuable information to industry players and researchers.

As a person ages, there is a tendency for the progressive degeneration of the body, which usually manifests as a loss of motor, cognitive and sensory abilities. This introduces new challenges to the independent accomplishment of previously routine tasks. Through the analysis of this issue, the authors identify that the adherence to complex medication regimes might pose a particularly difficult challenge for elderly patients, whose limitations can introduce the risk of ineffective treatments and health hazards by the wrongful taking of medicine. The solution proposed is the development of an automatic pill dispenser, designed to counteract the adverse effects of aging and enable the elderly to retain a degree of autonomy in their daily care, or support family and professional caretakers. This chapter will follow the projects’ development through the identification and analysis of the challenges faced by elderly individuals; a comparative study of the options currently available to support them in the identified issue; the proposal of a solution; and concluding with the construction of a preliminary prototype.

In face of the current economic and financial environment, predicting corporate bankruptcy is arguably a phenomenon of increasing interest to investors, creditors, borrowing firms, and governments alike. Within the strand of literature focused on bankruptcy forecasting we can find diverse types of research employing a wide variety of techniques, but only a few researchers have used survival analysis for the examination of this issue. We propose a model for the prediction of corporate bankruptcy based on survival analysis, a technique which stands on its own merits. In this research, the hazard rate is the probability of ‘‘bankruptcy’’ as of time t, conditional upon having survived until time t. Many hazard models are applied in a context where the running of time naturally affects the hazard rate. The model employed in this paper uses the time of survival or the hazard risk as dependent variable, considering the unsuccessful companies as censured observations.

(1) Background: Continuous health promotion systems are increasingly important, enabling decentralized patient care, providing comfort, and reducing congestion in healthcare facilities. These systems allow for treatment beyond clinical settings and support preventive monitoring. Wearable systems have become essential tools for health monitoring, but they focus mainly on physiological data, overlooking motor data evaluation. The World Health Organization reports that 1.71 billion people globally suffer from musculoskeletal conditions, marked by pain and limited mobility. (2) Methods: To gain a deeper understanding of wearables for the motor rehabilitation, monitoring, and prediction of the progression and/or degradation of symptoms directly associated with upper-limb pathologies, this study was conducted. Thus, all articles indexed in the Web of Science database containing the terms “wearable”, “upper limb”, and (“rehabilitation” or “monitor” or “predict”) between 2019 and 2023 were flagged for analysis. (3) Results: Out of 391 papers identified, 148 were included and analyzed, exploring pathologies, technologies, and their interrelationships. Technologies were categorized by typology and primary purpose. (4) Conclusions: The study identified essential sensory units and actuators in wearable systems for upper-limb physiotherapy and analyzed them based on treatment methods and targeted pathologies.

Given the recent developments in sustainability reporting frameworks, this paper aims to systematically review the research on sustainability matters concerning its implementation in the educational area within the accounting-related courses or higher education institutions overall from a more comprehensive scope of analysis. For this purpose, a systematic literature review combined with a bibliometric analysis was applied, using the Scopus database to collect the papers published in this century (since 2000 onwards). The final sample is comprised of 56 papers, covering different clusters of analysis. The findings indicate an increase in sustainability publications, which aligns with the growing relevance of such issues worldwide. In recent years, studies with practical applications and a more diverse set of methodologies have increased instead of the initial focus on theoretical essays and analyses. Nevertheless, there are still some gaps that can serve as avenues for future research, regarding, for instance, the papers’ geographical scope, thematic area and methodologies proposed. This study expands to further topics not found in the literature such as what the classical social science theories have been proposed for evaluation, and the main results/conclusions the studies have reached. Finally, it suggests avenues for future research from the identified gaps and then contributes to the literature.

This study systematically reviews the literature on integrating sustainability within the luxury market, focusing on cultural adaptations from 2007 to 2024. We aim to analyze how luxury brands implement sustainable practices across different cultural contexts and assess global consumer perceptions. Findings indicate that while some brands effectively align their sustainability strategies with local cultural values, significant challenges still must be addressed due to diverse consumer expectations. These challenges impact the effectiveness of sustainability initiatives and consumer purchasing decisions. The study suggests that luxury brands should develop culturally sensitive marketing strategies that promote sustainability while resonating with local norms to enhance consumer engagement and global sustainability efforts. Future research should empirically test these strategies and explore innovative approaches to deepen sustainability in the luxury sector.

This study delves into higher education students' active participation in an Erasmus+ blended intensive program (BIP) that focuses on teaching game creation. Three universities facilitated the BIP, which had 22 international students. The program, designed around project-based learning and on-site/online collaboration, empowered students to better prepare them for careers the game industry. Two student focus groups were analyzed using thematic analysis to understand the students' perceptions of the educational approach. The investigation findings emphasize that aligning game creation teaching with conditions and technologies in the game industry is challenging in practice despite its apparent simplicity on paper. It also underscores the crucial role of soft skills and transversal competencies in game creation education. These skills, often overlooked, play a vital role in the success of game creation projects. With this study, we wish to contribute to the discourse on game education by offering insights into the enablers and barriers to teaching game creation within higher education. It provides ten useful considerations for game scholars and educators to deliberate in their profession.

Introduction A promising approach to optimizing recovery in youth football has been the use of machine learning (ML) models to predict recovery states and prevent mental fatigue. This research investigates the application of ML models in classifying male young football players aged under (U)15, U17, and U19 according to their recovery state. Weekly training load data were systematically monitored across three age groups throughout the initial month of the 2019–2020 competitive season, covering 18 training sessions and 120 observation instances. Outfield players were tracked using portable 18-Hz global positioning system (GPS) devices, while heart rate (HR) was measured using 1 Hz telemetry HR bands. The rating of perceived exertion (RPE 6–20) and total quality recovery (TQR 6–20) scores were employed to evaluate perceived exertion, internal training load, and recovery state, respectively. Data preprocessing involved handling missing values, normalization, and feature selection using correlation coefficients and a random forest (RF) classifier. Five ML algorithms [K-nearest neighbors (KNN), extreme gradient boosting (XGBoost), support vector machine (SVM), RF, and decision tree (DT)] were assessed for classification performance. The K-fold method was employed to cross-validate the ML outputs. Results A high accuracy for this ML classification model (73–100%) was verified. The feature selection highlighted critical variables, and we implemented the ML algorithms considering a panel of 9 variables (U15, U19, body mass, accelerations, decelerations, training weeks, sprint distance, and RPE). These features were included according to their percentage of importance (3–18%). The results were cross-validated with good accuracy across 5-fold (79%). Conclusion The five ML models, in combination with weekly data, demonstrated the efficacy of wearable device-collected features as an efficient combination in predicting football players’ recovery states.

This paper presents a face recognition system that is part of a global solution for online soccer piracy detection. The overall solution uses several building blocks to detect illegal sharing of live soccer broadcasts. This paper presents one of the building blocks, a face recognition system, that recognizes the faces of players that participate in the soccer match that the overall solution is trying to identify. The face recognition system detects faces in the broadcast image frames and tries to match them to a database faces of players from the clubs that participate in the game. The proposed face recognition system uses Retinaface and OpenCV to detect faces, applies Deep Learning networks Facenet128 and FaceNet512 to extract features from the detected faces, computes the cosine distance between features to evaluate the dissimilarity between faces, and compares the distance to a predefined threshold. This approach aims to maximize Precision and True Positive Rate while ensuring a False Positive Rate equal to zero, even at the cost of a lower Recall and Accuracy, and also provides results in as close to real-time as possible. The experiments show that the proposed face recognition system is able to achieve a True Positive Rate of 38.4% while ensuring a False Positive Rate of 0, which is an important aspect for the overall solution. The system is able to analyze an average of 20 frames per second. The results show the potential of this approach to identify and combat illegal broadcasts of sporting events, offering a robust approach to address the escalating issue of unauthorized audiovisual content sharing.

This study aims to analyze the explanatory factors of the accounting choices for investments of entities with securities traded on regulated markets from the European Union (EU) under International Accounting Standards (IAS) 27 — Separate Financial Statements (SFS). According to IAS27, investments in their scope can be accounted for by using the cost, equity method, or fair value, which represents alternative accounting methods commonly known in the literature as accounting choices. To identify the factors that may explain the accounting choices for investments under IAS27, a logistic regression model is used. The research covers listed entities from 19 out of the 21 EU countries where IAS27 is required or permitted. The findings highlight that the entities’ size and investment weight likely explain the adoption of the cost method, conversely to the size of the board of directors, which negatively explains its use. Accounting choices for investments under SFS are not yet explored in the literature. Moreover, this research also proposes further explanatory factors in the scope of the literature on accounting choices. This paper can potentially benefit a diverse set of stakeholders, namely the accounting standard-setters, as they can draw attention to the comparability issues from the use of accounting choices, which may mitigate the financial information usefulness for decision making. Furthermore, auditors, supervisors, as well as investors and other users, can have a more comprehensive perspective of the reasons behind the method chosen by entities for accounting for their financial investments.

Using a quasi-experimental method and content analysis as a technique, this study tests ChatGPT, in its version 4, by assessing its textual characteristics and overall understanding regarding the recognition criteria of provisions under International Accounting Standards (IAS) 37, as issued by the International Accounting Standards Board (IASB). For this purpose, it uses a set of questions (input) from the IASB's illustrative examples to compare the answers (output) from IASB and ChatGPT in two distinct strategies: with and without prompting. The findings indicate that ChatGPT’s answers are wordier, have higher magnitude levels, and are more predominantly inserted in Business and Finance. The no-prompting strategy is globally more negative and subjective, while the prompting one improves the answers’ focus and readability, also presenting more diverse tones in its textual characteristics, similar to what was found in the IASB's answers. However, some answers were not globally accurate in both strategies. These findings provide insights into how ChatGPT, as one of the most disseminated artificial intelligence tools, can be used by accounting professionals and educators, being aware of the potential risks and benefits from both strategies underlying this experiment. Then, by considering those aspects, practitioners, including accountants and managers, but also investors can use it to understand the matters and issues under assessment in a given situation, as well as the sources to consider when preparing financial statements or making a decision. Academics can also use it to open up discussions and promote students’ critical thinking skills in a classroom environment.