REMIT - Research on Economics, Management and Information Technologies (UIDB/05105/2020)

REMIT - Research on Economics, Management and Information Technologies (UIDB/05105/2020)

Keywords

Innovation and creativity,Strategy and business models,Decision support systems,Territorial development,

URL

http://www.fct.pt/apoios/projectos/consulta/vglobal_projecto.phtml.en?idProjecto=157631&idElemConcurso=14275

Identifier

UIDB/05105/2020

Funding Stream

6817 - DCRRNI ID

Funder

Organizational Unit

Fundação para a Ciência e Tecnologia

A Fundação para a Ciência e Tecnologia (FCT) é uma entidade portuguesa responsável pela promoção e financiamento da investigação científica e tecnológica em Portugal. A FCT apoia projetos de investigação em diversas áreas, desde as ciências naturais e exatas até às ciências sociais e humanidades. Além disso, a FCT desempenha um papel importante na gestão de bolsas de estudo e no desenvolvimento de políticas para o avanço da ciência e tecnologia no país.

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Now showing 1 - 10 of 15

Restricted Access
Anticipating tutoring demands based on students’ difficulties in Online Learning
2024-06-01 - Pereira, Aluisio José; Gomes, Alex Sandro; Primo, Tiago Thompsen; Queiros, Leandro Marques; Moreira, Fernando
Anticipating the tutoring needs in online learning is essential to provide adequate support to students. Feedback and even silence are valuable clues to reveal the level of engagement. Approaches based on Artificial Intelligence (AI) can process this information and alleviate the workload of human tutors. In this study, Natural Language Processing (NLP) techniques were used to assess the performance of classifying students’ difficulties in an Educational Social Network. Difficulties were classified into categories such as “personal”, “technical”, and “others”. The model's performance allows you to anticipate and direct tutoring.
Restricted Access
A study on sensors in Higher Education
2024-06-01 - Sengupta, Sarthak; Bose, Anindya; Moreira, Fernando; Escudero, David Fonseca; García-Peñalvo, Francisco José; Collazos , Cesar
The Coronavirus crisis affected the higher education system drastically. A rapid surge in the usage of sensors and wearable technologies was observed. So, a need to pursue further research on the implementation of sensors in higher education institutions has been witnessed. This research study revolves around exploring the relevant research studies on sensors and higher education. The study found that a notable number of global research studies have been pursued on sensors but very few were relevant to the context of higher education institutions. It was also observed that the number of relevant research studies on the topics increased during and after the COVID-19 pandemic. It was also observed that most of the relevant research studies were published by developed countries like the USA, China, and England but negligible studies were performed by other countries. So, this study can pave the foundation to formulate novel approaches in the strategic implementation of sensors in higher education institutions across the world.
Restricted Access
NLP on text messages using sentimentality investigation
2025-06-15 - Singh, Khushwant; Yadav, Mohit; Moreira, Fernando
E-commerce is becoming more and more popular in this digital era since it allows customers to order things online and have them delivered right to their doorsteps. Reviews now have more significance as consumers use them to make informed decisions about what to buy. By classifying and learning from reviews, machine learning might help with the laborious work of sifting through hundreds of them. Sentiment analysis is a fundamental function of natural language processing (NLP) that focuses on comprehending attitudes and emotions. This research employs supervised learning techniques to analyze the feelings of product evaluations on Amazon. Thousands of reviews in various categories may be found in the dataset that was used. Recurrent neural networks (RNNs), among other NLP models, are tested for the purpose of classifying reviews into positive, negative, and neutral sentiments. The models are evaluated by applying recall, accuracy, and precision. Investigations are being conducted on the implications of sentiment analysis findings for companies and consumers using the Amazon platform. This study provides information on sentiment analysis on the dataset from Amazon and its useful applications. E-commerce is growing in popularity, and machine learning-based sentiment analysis might help evaluate massive volumes of data and effectively identify emotions. For the purpose of classifying emotions, a variety of machine learning techniques have been used, such as K-means clustering, decision trees (DTs), convolutional neural networks (CNNs), support vector machines (SVMs), and Bayesian networks (BNs). This study compares previous research and offers a real-time sentiment analysis system to monitor common feelings and provide recommendations that users would find acceptable. A key component of natural language processing (NLP) is sentiment analysis, which classifies sentiment polarity. This study offers a generic method for classifying sentiment in online product reviews from Amazon.com and aims to address problems in sentiment analysis. Investigations into categorization at the sentence and review levels are conducted, with encouraging outcomes. There is also mention of future work on sentiment analysis.
Restricted Access
Core Organizational Societal Impact (COSI): An evolving model
2025-06-14 - Carvalho, João M. S.
Measuring the social impact of organizations is complex and challenging, and it cannot be generalized to all cases. This conceptual study aims to theoretically substantiate a flexible measure of societal impact and provide recommendations to improve the accuracy and validity of such measures. The Core Organizational Societal Impact (COSI) measure is based on stakeholder, corporate social responsibility, and societal sustainability theories, assessing any organization’s societal impact, comprising indicators of general application and discretionary ones. This model can be used as a proxy and acid test to measure organizational societal footprint, i.e., how organizations impact the stakeholders based on their economic, social, legal, ethical, ecological, psychological, and discretionary responsibilities. It constitutes an adjustable index that allows for assessing the organization’s evolution and comparisons with other organizations in the activity sector. This approach sensitizes managers and entrepreneurs in any activity sector to choose a marketing strategy with a positive societal impact.
Restricted Access
Proposal of a conceptual model for a virtual environment that mediates Lesson Planning Activities
2025-07-15 - Silva, Carlos José Pereira da; Gomes, Alex Sandro; Queiros, Leandro Marques; Pereira, Aluisio José; Escudero, David Fonseca; Moreira, Fernando
This study proposes a conceptual model for a virtual environment that mediates lesson planning activities in high school education. In today’s online society, we frequently encounter innovative digital products and services that leverage advances in Information and Communication Technology (ICT). The main objective is to explore teachers’ needs and the possibilities offered by current technologies to enhance pedagogical practices. Using a projective approach based on activity theory, we identified the main challenges faced by teachers in the initial stages of lesson preparation, including short, medium, and long-term planning. Based on the identified requirements, a virtual environment was developed that represents the minimum structure necessary to mediate this activity. The results indicate that the virtual environment can promote greater participation and collaboration among teachers, facilitating the shared construction of knowledge. We conclude that the proposed virtual environment has great potential to mediate lesson planning, improving the quality of pedagogical practices and didactic activities.
Open Access
Generation Z and Travel Motivations: The Impact of Age, Gender, and Residence
2025-05-13 - Marques, Jorge; Gomes, Sofia; Ferreira, Mónica; Rebuá, Marina
This study investigates the relationship between demographic factors and travel motivations among Generation Z leisure tourists through the lens of the Travel Career Pattern (TCP) theory. More specifically, the research focuses on how gender, age, and area of residence influence the travel motivations of Generation Z. Using a quantitative approach, data were collected from 303 respondents aged 18 to 28 through an online survey. The questionnaire assessed 14 motivational factors and analyzed them in relation to the participants’ demographic characteristics using linear regression models. Results indicate that gender and age significantly influence travel motivations, with women showing higher interest in personal development and social relationships, while men prioritize nature and adventure. Furthermore, rural residents exhibit greater motivation for autonomy, self-development and self-realization, while urban residents lean towards novelty and social interactions. The findings offer valuable insights for tourism marketers, emphasizing the importance of creating segmented marketing campaigns based on demographic factors. It also contributed to overcoming the lack of studies that specifically cover this interrelation between the motivational factors of Generation Z and the demographic factors of age, gender and area of residence. Nevertheless, this study also has limitations, such as the use of a non-representative sample and the focus on quantitative methods, suggesting that future research should adopt qualitative approaches and examine additional demographic variables to gain deeper insights into youth travel motivations.
Open Access
A hierarchical multi-class classification system for face and text datasets
2025-06-20 - Saini, Ashish; Gill, Nasib Singh; Gulia, Preeti; Singh, Khushwant; Moreira, Fernando
In an era of rapidly growing multimedia data, the need for robust and efficient classification systems has become critical, specifically the identification of class names and poses or styles. This study provides an understanding of the organization of data, and feature selection (i.e., edge) using the k-means segmentation technique is explained. Furthermore, for the optimization of features, the linear regression technique is used. The optimized features can be directly used with classifiers, but to reduce the noise, outliers are identified and removed from the training data. The classifiers are involved in training and recognizing the face or text class label. After the prediction of class labels, the distance matrix-based technique is used to identify the style or pose name. Finally, the experiments are conducted with the help of the ORL dataset (40 classes and 10 poses in each class) and character dataset (36 characters and 10 font styles in each character). The experimental results indicated that the proposed methodology accurately classifies hierarchically organized data and demonstrates superiority over KNN and Bayesian-based classification when compared to support vector machine (SVM). The system provides classification outcomes with up to 100% accuracy for outlier-removed data, and up to 98% for basic features. Unlike traditional flat classification approaches, our system leverages hierarchical structures to enhance classification accuracy, scalability, and interpretability.
Open Access
Digital transformation, skills and education: A systematic literature review
2023-10-23 - Rêgo, B.; Lourenço, D.; Moreira, Fernando; Santos-Pereira, Carla
Digital transformation (DT) is raising new challenges. This article seeks to understand how DT has changed business strategies, requiring a new profile of professionals, analyzing the most sought-after skills and identifying opportunities for future professionals. Also, it studies whether universities have incorporated in their training the new skills required by the labor market impacted by DT. To these ends, a systematic literature review dealing with digital transformation, competence, and education was conducted. The existing literature was categorized into seven main areas of investigation: digital literacy; skills identification; use of digital technologies in teaching; learning models; workforce qualification or re-skilling; digital technologies in the labor market; and undergraduate course analysis. This structuring then lays the groundwork for capturing gaps in the literature and proposing future research.
Open Access
The role of leadership and strategic alliances in innovation and digital transformation for sustainable entrepreneurial ecosystems: A comprehensive analysis of the existing literature
2025-07-05 - Lobo, Carla Azevedo; Marinho, Arlindo; Santos-Pereira, Carla; Azevedo, Mónica; Moreira, Fernando
In the context of accelerating digital transformation and growing sustainability imperatives, entrepreneurial ecosystems increasingly rely on open innovation and strategic collaboration to foster resilient, knowledge-driven growth. This study aims to examine how leadership behaviors and strategic alliances interact as enablers of sustainable innovation across macro (systemic), meso (organizational), and micro (individual) levels. To achieve this, this study employs a literature review, supported by bibliometric analysis, as its core methodological approach. Drawing on 86 influential publications from 1992 to 2024, two major thematic streams emerge: leadership dynamics in entrepreneurial settings and the formation and governance of strategic alliances as vehicles for innovation. The findings underscore the pivotal role of transformational and ethical leadership in cultivating trust-based inter-organizational relationships, facilitating digital knowledge sharing, and catalyzing sustainable value creation. Simultaneously, strategic alliances enhance organizational agility and innovation capacity through co-creation mechanisms, digital platforms, and crowdsourcing, especially in small and medium-sized enterprises (SMEs). This paper highlights a mutually reinforcing relationship: effective leadership strategies empower alliances, while alliance participation enhances leadership capabilities through experiential learning in diverse, digitalized environments. By bridging leadership theory, open innovation practices, and digital transformation, this study offers critical insights for entrepreneurs, managers, and policymakers seeking to drive inclusive and sustainable innovation within interconnected global markets. Therefore, this study provides practical guidance for business leaders aiming to strengthen alliance performance through adaptive leadership and for policymakers seeking to foster innovation ecosystems through supportive regulatory and institutional frameworks.
Restricted Access
Building a usability and accessibility evaluation method for small software development companies
2025-06-15 - Casas Domínguez, Carlos Andrés; Collazos, Cesar A.; Agredo-Delgado, Vanessa; Moreira, Fernando
A good usability and accessibility evaluation in a development process has a direct impact on the success of the developed application, specifically due to the large number of users, which can often be of different types, with different skills and needs and interacting on different devices, in this sense, such development demands new needs and challenges that software development companies must consider. This is why these evaluation processes should be of great relevance within companies because the quality of a product depends on including and guaranteeing usability and accessibility within the developments, and the way to do this is through the evaluation of the products. However, it is not always easy to implement existing evaluation methods or strategies, due to the time, resources, personnel, etc. required and very necessary for these evaluations. Considering the importance of including these two characteristics in the software development process, this paper presents the general steps for the construction of the method and the execution of an evaluation on this first version. With the realization of this method, it is expected to contribute to improve the usability and accessibility evaluation processes in terms of time, resources, costs and experience. The project will carry out a research process, which initially seeks to identify and characterize existing evaluation methods, with these elements to build the evaluation method, which will subsequently validate its usefulness, efficiency and ease of use, through its implementation of two case studies in the Corporacion Universitaria Comfacauca—Unicomfacauca Colombia, one with students in their last semesters and another with students in their first semesters; as a result of this, it is obtained that the method is moderately easy to use, complete and viable although there are problems and needs that must be solved throughout the improvement and development of the method.