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About

About

Assistant Professor in the Department of Science and Technology of the Open University. Coordinator of the Master in Information and Business Systems. PhD in Information Systems and Technologies, University of Minho. Master in Informatics from the Faculty of Sciences of the University of Lisbon. Degree in Computer Engineering from COCITE.

Consultant in Information, Systems and Technological Systems and Architectures. I have a particular interest in Informatics applied to organizations.

Interest
Topics
Details

Details

  • Name

    Henrique São Mamede
  • Role

    Senior Researcher
  • Since

    01st May 2014
013
Publications

2025

The relationship between digital transformation and digital literacy - an explanatory model: Systematic literature review

Authors
Arnaud, J; São Mamede, H; Branco, FA;

Publication
F1000Research

Abstract
Digital transformation has been one of the main trends in organizations in recent years, and digital literacy is a critical factor in the success of this transformation. Digital transformation involves the use of digital technologies to improve an organization’s processes, products, and services. For this transformation to be successful, it is necessary for employees to have knowledge of and skills in digital technologies. Digital literacy allows employees to understand technologies and their applications, know how to use them efficiently and safely, evaluate and select the most appropriate digital tools for each task, and be prepared to deal with problems and challenges that arise in the digital environment. This study investigates the relationship between digital transformation and digital literacy through a Systematic Literature Review conducted in accordance with Kitchenham’s guidelines. A total of 54 articles, published from 2018, were analyzed from databases such as Scopus, Science Direct, IEEE and Springer. The results reveal that digital literacy significantly influences the success of digital transformation, particularly in areas such as employee adaptability, innovation capacity, and digital tool integration. Key mediating and moderating factors identified include organizational learning culture, leadership support, ongoing training programs, and technological infrastructure. Based on these findings, an explanatory model was developed that maps the interaction between these variables and their impact on digital transformation outcomes. The study offers practical implications for organizations seeking to enhance their digital maturity: investing in employee digital literacy development, aligning leadership strategies with digital initiatives, and fostering a supportive culture for digital adoption are crucial steps. Thus, this study is relevant because it seeks to understand how digital literacy can impact Digital Transformation in organizations and, through the construction of an explanatory model, allows the identification of variables that influence this relationship by developing strategies to improve the digital literacy of employees in organizations. © 2025 Elsevier B.V., All rights reserved.

2025

A new proposed model to assess the digital organizational readiness to maximize the results of the digital transformation in SMEs

Authors
Silva, RP; Mamede, HS; Santos, V;

Publication
JOURNAL OF INNOVATION & KNOWLEDGE

Abstract
Scientific research in digital transformation is expanding in scope, quantity, and relevance, bringing forth diverse perspectives on which factors and specific dimensions-such as organizational structure, culture, and technological readiness-affect the success of digital transformation initiatives. Numerous studies have proposed mechanisms to assess an organization's maturity through digital transformation across various models. Some of these models focus on external influences, others on internal factors, or both. Although these assessments provide valuable insights into a company's transformation state, they often lack consistency, and recent research highlights key gaps. Specifically, many models primarily reflect the views of senior management on the general progress of digital transformation rather than on measurable outcomes. Moreover, these models tend to target large enterprises, overlooking small and medium enterprises (SMEs), which are crucial to economic growth yet face unique challenges, such as limited resources and expertise. Our study addresses these gaps by concentrating on SMEs and introducing a novel approach to assessing digital transformation readiness-a metric that reflects how prepared an organization is to optimize transformation outcomes. Following design science research methodology, we develop a model that centers on the perspectives of general employees, offering companies an in-depth view of their readiness across 20 dimensions. Each dimension is evaluated through behaviors indicative of the highest level of digital transformation readiness, helping companies identify areas to maximize potential benefits. Our model focuses not on technological quality but on the degree to which behaviors essential for leveraging technology and innovative business models are integrated within the organization.

2025

From data to action: How AI and learning analytics are shaping the future of distance education

Authors
Dias, JT; Santos, A; Mamede, HS;

Publication
AI and Learning Analytics in Distance Learning

Abstract
This chapter examines how Artificial Intelligence (AI) and Learning Analytics (LA) are transformingdistanceeducation, accelerated by the COVID-19 shift toe-learning. By using data from Learning Management Systems (LMS), these technologies can personalize learning, improve student retention, and automate tasks. AI, particularly machine learning, enables dynamic adaptation to student needs, while LA provides valuable insights for informed instructional decisions. However, ethical concerns, including data privacy and algorithmic bias, must be addressed to ensure equitable access and fair learning outcomes. The future of distance learning lies in responsible integration of AI and LA, creating immersive and inclusive educational experiences. © 2025 by IGI Global Scientific Publishing. All rights reserved.

2025

AI and learning analytics in distance learning

Authors
Mamede, S; Santos, A;

Publication
AI and Learning Analytics in Distance Learning

Abstract
The ever-changing landscape of distance learning AI and learning analytics transforms engagement and efficiency in education. AI systems analyze behavior and performance data to provide real-time feedback for improved outcomes. Learning analytics further help educators to identify at-risk students while fostering better teaching strategies. By integrating AI with learning analytics, distance education becomes more inclusive, ensuring learners receive the support necessary to thrive in an increasingly digital and knowledge-driven world. AI and Learning Analytics in Distance Learning explores the development of distance learning. It examines the challenges of using these systems and integrating them with distance learning. The book covers topics such as AI, distance learning technology, and management systems, and is an excellent resource for academicians, educators, researchers, computer engineers, and data scientists. © 2025 by IGI Global Scientific Publishing. All rights reserved.

2025

Preface

Authors
Mamede, S; Santos, A;

Publication
AI and Learning Analytics in Distance Learning

Abstract
[No abstract available]

Supervised
thesis

2023

A parallel functional programming framework for in-browser operation of enumerations of business entities

Author
Carlos Miguel Barreira Ferreira

Institution
UAB

2023

A Decision Framework for the Implementation of Technologies in Talent Management within Organisations

Author
Helena Maria Rodrigues Ferreira

Institution
UAB

2023

Estratégias e Modelos para Estimular o Engagement de Estudantes no Ensino Superior

Author
Viktoriya Limonova

Institution
UAB

2023

Business Process Automation in SME

Author
Silvia Catarina de Oliveira Moreira

Institution
UAB

2022

SMEs recruitment processes supported by Artificial Intelligence

Author
Hugo Trovão Mota

Institution
UAB