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The purpose of this study is to explore the potential and growth of big data across several industries between 2016 and 2020. This study aims to analyze the behavior of interest in big data within the community and to identify areas with the greatest potential for future big data adoption.

This research uses Google Trends to characterize the community’s interest in big data. Community interest is measured on a scale of 0–100 from weekly observations over the past five years. A total of 16 industries were considered to explore the relative interest in big data for each industry.

The findings revealed that big data has been of high interest to the community over the past five years, particularly in the manufacturing, computers and electronics industries. However, over the 2020s the interest in the theme decreased by more than 15%, especially in the areas where big data typically had the greatest potential interest. In contrast, areas with less potential interest in big data such as real estate, sport and travel have registered an average growth of less than 10%.

To the best of the author’s knowledge, this study is original in complementing the traditional survey approaches launched among the business communities to discover the potential of big data in specific industries. The knowledge of big data growth potential is relevant for players in the field to identify saturation and emerging opportunities for big data adoption.

The implementation of European data protection is a challenge for businesses and has imposed legal, technical and organizational changes for companies. This study aims to explore the benefits and challenges that companies operating in the information technology (IT) sector have experienced in applying the European data protection. Additionally, this study aims to explore whether the benefits and challenges faced by these companies were different considering their dimension and the state of implementation of the regulation.

This study adopts a quantitative methodology, based on a survey conducted with Portuguese IT companies. The survey is composed of 30 questions divided into three sections, namely, control data; assessment; and benefits and challenges. The survey was created on Google Drive and distributed among Portuguese IT companies between March and April of 2019. The data were analyzed using the Stata software using descriptive and inferential analysis techniques using the ANOVA one-way test.

A total of 286 responses were received. The main benefits identified by the application of European data protection include increased confidence and legal clarification. On the other hand, the main challenges include the execution of audits to systems and processes and the application of the right to erasure. The findings allow us to conclude that the state of implementation of the general data protection regulation (GDPR), and the type of company are discriminating factors in the perception of benefits and challenges.

This study has essentially practical implications. Based on the synthesis of the benefits and challenges posed by the adoption of European data protection, it is possible to assess the relative importance and impact of the benefits and challenges faced by companies in the IT sector. However, this study does not explore the type of challenges that are placed at each stage of the adoption of European data protection and does not take into account the specificities of the activities carried out by each of these companies.

The implementation of the GDPR is still in an initial phase. This study is pioneering in synthesizing the main benefits and challenges of its adoption considering the companies operating in the IT sector. Furthermore, this study explores the impact of the size of the company and the status of implementation of the GDPR on the perception of the established benefits and challenges.

The COVID-19 pandemic has significantly impacted the European Union (EU) through heavy pressure on health services, business activity and people's life. To mitigate these effects, government agencies, civil society and the private sector are working together in proposing innovative initiatives. In this sense, this study aims to characterize and explore the relevance of these projects to mitigate the effects of COVID-19.

The Observatory of Public Sector Innovation provided by the Organization for Economic Co-operation and Development was considered to enable the identification and exploration of innovative projects to combat COVID-19. A methodology based on mixed methods is adopted to initially identify quantitatively the distribution of these projects, followed by a qualitative approach based on thematic analysis that allows exploring their relevance.

A total of 206 initiatives in the EU have been identified. The distribution of these projects is quite asymmetric, with Portugal and Austria totaling 33.52% of these projects. Most of these projects focus on the areas of public health, infection detection and control, virtual education, local commerce, digital services literacy, volunteering and solidarity and hackathons.

This work is relevant to identifying and understanding the various areas in which COVID-19 initiatives have been developed. This information is of great relevance for the actors involved in this process to be able to replicate these initiatives in their national, regional and local contexts.

Knowledge about competitive environments is a determinant factor for the success of a firm, as it may allow it to anticipate threats and opportunities in its market. This study aims to explore variables that enable or prevent an employee’s intrinsic motivation to share knowledge. It studies the collection and sharing of information that may be a signal of future competitive moves in competitive intelligence (CI) processes.

Canonical correlation was used by utilizing survey data from a company. The study was based on the self-determination theory relating intrinsic motivation to behavior.

The study confirms the importance of different aspects motivating knowledge sharing behavior, such as information system’s support, top management support and information feed-back.

The study is limited to one company, respecting the limitations of a case study, but external validation was impossible to test. Findings showed a strong correlation of some variables with intrinsic motivation and are coherent with other studies in the knowledge sharing field.

Firms introducing knowledge sharing processes should pay attention to the importance of information system support. The relationship with people involved is also important, as in supporting their collaborations and giving feed-back to contributions. Sustaining intrinsic motivation seems a fundamental aspect to the process’ success.

The study indicates the relation of different variables of motivation with motivation. It explores knowledge sharing in a CI process, an important process in firms nowadays. It shows important aspects that ensure continuity of knowledge sharing as informational feed-back and top management support. Canonical correlation was also used, a technique not frequently explored and useful to study correlation among groups of variables.

Responsible innovation assessment tools (RIATs) are key instruments that can help organizations, associations and individuals measure responsible innovation. Accordingly, this study aims to review the current status of research on responsible innovation and, in particular, of studies that either present the relevance of RIATs or provide empirical evidence of their adoption.

A systematic literature review is conducted to identify and review how RIATs are being addressed in academic research and the applications that are proposed. A systematic process is implemented using the Web of Science and Scopus bibliographic databases, aiming not only to summarize existing studies, but also to include a perspective on gaps and future research.

A total of 119 publications were identified and included in the review process. The study identifies that RIATs have attracted growing interest from the scientific community, with a greater predominance of studies involving qualitative and mixed methods. A well-balanced mix of conceptual and exploratory studies is also registered, with a greater predominance of analysis of RIATs application domains in the past years, with greater incidence in the finance, water, energy, construction, manufacturing and health sectors.

This study is pioneering in identifying 16 dimensions and 60 sub-dimensions for measuring responsible innovation. It also suggests the need to include multidimensional perspectives and individuals with interdisciplinary competencies in this process.

The current student selection process for short-term mobility actions under the Erasmus + program (i.e. intensive programs and blended intensive programs) is based exclusively on the students' order of enrolment and their grades. This study offers an alternative approach using the analytic hierarchy process based on a four-layer model that collects information about the specificities of each project and the profile of the students and also promotes greater inclusion and homogenization of the project teams.

A decision support system was built by decomposing it into three stages: the predesign stage, in which the problem is characterized, and the user requirements are identified; the design stage, in which the models, the database and the interfaces are formulated; and the field stage, in which six test scenarios were built to validate the proposed solution.

The results show that this model can be applied with various selection criteria among students and consider both their hard and soft skills. It can also be applied to help build teams in which the students' knowledge is aligned with the technical skills required by the projects.

The proposed approach is innovative in that it responds to the emerging challenge of short-term European mobility programs that aim to involve students with multidisciplinary competencies. The solution considers both hard and soft skills in the selection of students, which allows changing the student selection paradigm and obtaining potentially more homogeneous multicultural teams with greater learning potential.

This study aims to identify and explore the factors affecting social entrepreneurial intentions considering an educational institution in Portugal. It also intends to determine the relevance of moderating factors in the antecedents and entrepreneurial intention of these students.

A panel of 177 undergraduate students enrolled in a social entrepreneurship course between the academic years 2018 and 2021 is considered. The data is explored quantitatively considering descriptive analysis techniques, correlational analysis and hypothesis testing.

The findings reveal that entrepreneurial intention depends on multiple individual, organizational and contextual dimensions. Students' entrepreneurial intention remains unchanged regardless of the student’s profile. However, students' professional experience is a more relevant factor for the identification of organizational dimensions related to curriculum and critical pedagogy, while previous involvement in volunteer activities contributes to a higher prevalence of individual factors.

To the best of the authors’ knowledge, this study is original in exploring the role of entrepreneurial intention and its antecedents considering a heterogeneous students' profile. It offers theoretical and practical contributions by extending the literature on social entrepreneurial intention that can be used by higher education institutions to offer specific training more focused on the student's profile.

This study aims to demonstrate the values and effects of innovation becomes a challenge when selecting clear and correlating measures. While there is extensive research in the area of innovation measurement, there is a lack of consistent quantifiable measures that organizations can use. The International Association of Innovation Professionals (IAOIP) has partnered with Spigit to crowdsource innovation measures via the Innovation Measurement Standard (IMS) challenge with IAOIP members and the global public to determine the various ways innovation is measured across industries.

This study used a mixed-methods approach and a sequential exploratory design to analyze the data collected during the IMS challenge. In the first phase, the qualitative methodology was used to analyze innovation measures submitted during the IMS challenge and participants’ interactions and comments. In the second phase, the innovation measures were analyzed quantitatively to identify the most prominent measures.

A total of 73 innovation measures were collected during the challenge. In total, 18 top measures were ranked based on the participants’ votes, and the top five measures were selected as the winning measures of the challenge. These five measures included intelligent failure rate, financial results of innovation, the results brought to the company, the number of innovative ideas selected for action and innovation portfolio balancing.

This study is the first to select the innovation metrics while considering their relevance to the community of innovators that included academics, CEOs, consultants, innovation managers, etc. Another original factor of this work is the crowdsourcing approach used to identify innovation measures. This approach allowed us to explore multiple perspectives on the significance of each submitted measure.

The purpose of this study is to explore the human resource management practices and the associated dimensions of quality of employment in university spin-offs. Through this, it becomes possible to explore and recognize the practices and difficulties placed on the employees of university spin-offs.

The United Nations Economic Commission for Europe (UNECE) framework to assess the quality of work in the European Union is adopted. It is used a qualitative approach through the development of four case studies at university spin-offs located in Portugal. These case studies relate to four sectors of activity, such as information technology, urban mobility, health and electronics.

The findings reveal that most of the challenges of quality of work in a spin-off university are common to those in an SME or micro company. Among these factors, the authors highlight the lack of job security, reduced or no social protection and very low income and nonwage pecuniary benefits. Other factors specific to university spin-offs also emerge, such as the numerous opportunities for skills development and training, the potentialities to become an entrepreneur and the high number of working hours that are necessary to face the vibrant market dynamics.

The study aims to contribute, in a theoretical and empirically grounded basis, to the knowledge about the quality of employment in a spin-off university. This work becomes relevant for policymakers to understand in depth the specific challenges faced by employees of a spin-off university.

This study aims to present a practical approach to recognizing leadership styles by adopting a serious game in the context of an entrepreneurship course in higher education.

The action-research methodology is adopted to explore how the various leadership styles are perceived and assimilated by students. Furthermore, students are organized into eight groups to explore this phenomenon through a thematic analysis.

The findings reveal that transformational and transactional leadership can coexist and be applied in organizational management. The results also indicate that students with relevant professional experience have a greater ability to identify the benefits and challenges associated with each leadership style as they recognize these styles throughout their professional careers.

This paper mainly offers practical implications by presenting an alternative and complementary approach to exploring leadership styles. Through this approach, students can recognize the various leadership styles in the game personas and realize their impact on the dynamics of an organization.