Abstract
There is a clear gap in the literature on comparing entrepreneurship in urban and rural areas and analysing distinct differences between them, impacting their survival and growth. This study aims to find the motivations and classifications of success for urban and rural entrepreneurs. A case study approach was adopted, with six cases on urban and rural Scottish enterprises. These contrasting motivations and conceptions of success have been linked to the way companies strategise. Our findings contribute to the literature by adding an understanding of the motivations of entrepreneurs in rural and urban businesses, respectively. Further, the study was conducted in Scotland, which adds a subsequent understanding of the motivations of entrepreneurs within the country specifically, which can be used in future research within the country.

Abstract
The teaching of entrepreneurship has been progressively included in the curricula of several university courses to stimulate the development of empowering attitudes and an entrepreneurial mentality. However, a new form of entrepreneurship has emerged with a focus on sustainability and the creation of new projects that aim to reduce social asymmetries and contribute to a fairer and more balanced society. The role of universities is also to foster the emergence of these projects through the implementation of practices aimed at fostering social entrepreneurship among students. This study aims to understand the determinant dimensions that characterise the students' social entrepreneurial intention. For this purpose, a sample of 177 students attending a social entrepreneurship course in a higher education institution was employed. The findings indicate that individual, organisation, and context constructs are determinants of students' entrepreneurial intention. However, not all organisational factors contribute equally. Mentoring and social networks are relevant elements for the entrepreneurial intention of individuals, while curriculum and critical pedagogy are not recognised as determinants.

Abstract
Metrics are key elements that can give us valuable information about the effectiveness of agile software development processes, particularly considering the Scrum environment. This study aims to learn about the metrics adopted to assess agile development processes and explore the impact of how the role performed by each member in Scrum contributed to increasing/reducing the perception of the importance of these metrics. The impact of years of experience in Scrum on this perception was also explored. To this end, a quantitative study was conducted with 191 Scrum professionals in companies based in Portugal. The results show that the Scrum role is not a determining factor, while individuals with more years of experience have a higher perception of the importance of metrics related to team performance. The same conclusion is observed for the business value metric of the product backlog and the percentage of test automation in the testing phase. The findings allow for extending the knowledge about Scrum project management processes and their teams, in addition to offering important insights into the implementation of metrics for software engineering companies that adopt Scrum.

Abstract
Software development companies have progressively been experiencing the need to migrate their traditional development processes to agile environments. Several frameworks have emerged that support this paradigm, and Scrum is one of the most widely adopted on a global scale. However, Scrum was originally designed to work in small, local team environments. The challenge lies in designing its adoption in large-scale environments with geographically distributed teams. This chapter seeks to explore this challenge by identifying communication and coordination issues that may arise when adopting distributed Scrum. Three case studies are considered to allow comparison of different approaches considering structural and contextual factors associated with each organization.

Abstract
The complex and interconnected infrastructure of smart cities offers several opportunities for attackers to exploit vulnerabilities and carry out cyberattacks that can have serious consequences for the functioning of cities' critical infrastructures. This study aims to address this phenomenon and characterize the dimensions of security risks in smart cities and present mitigation proposals to address these risks. The study adopts a qualitative methodology through the identification of 62 European research projects in the field of cybersecurity in smart cities, which are underway during the period from 2022 to 2027. Compared to previous studies, this work provides a comprehensive view of security risks from the perspective of multiple universities, research centers, and companies participating in European projects. The findings of this study offer relevant scientific contributions by identifying 7 dimensions and 31 sub-dimensions of cybersecurity risks in smart cities and proposing 24 mitigation strategies to face these security challenges. Furthermore, this study explores emerging cybersecurity issues to which smart cities are exposed by the increasing proliferation of new technologies and standards.

Abstract
Background: The estimation of the real number of COVID-19 infected people is one of the concerns of the governments around the world. In this sense, this study seeks to assess the incidence and fatality of COVID-19 in Europe considering the expected number of the infected cases. Methods: A quantitative exploratory study was performed on the top 10 countries most affected by COVID-19 by 9th June in Europe. Furthermore, this study presents three propagation estimation models of the COVID-19 that help us to understand the real incidence of the pandemic in each country. Each model is briefly explained and applied. Results: The findings revealed a great heterogeneity of COVID-19 cases and deaths among the countries. The indicator of the number of deaths reveals the greatest disparity between other countries with the United Kingdom, recording about 6 or 7 times more deaths than Russia or Germany. Infection fatality rate (IFR) tends to be a more reliable indicator when analyzing data because it is less dependent on the number of tests performed. Conclusion: Several estimation models can be used to determine the incidence of COVID-19. However, their results in European countries are still quite asymmetrical although they are more reliable than just looking at the perspective of the number of cases or deaths recorded. The infection fatality rate (IFR) emerges as a more accurate indicator by estimating the expected number of registered cases, which includes asymptomatic cases and patients with mild symptoms that are not known and reported by health authorities. © 2020 The authors.