Abstract
Smart specialisation is a major driver of contemporary regional development policy in the European Union. Politicians, policymakers, and academics enthusiastically wave smart specialisation as the remedy that will fix the problems affecting previous policy rounds. The expectations towards the ‘remedial' effect of smart specialisation bear on the assumption that the policy approach will place the emphasis on what is unique in a given region by means of a so-called entrepreneurial process of discovery, basically a wide participatory process, underpinning a learning mechanism aimed at revealing the R&D and innovation domains in which that region can hope to excel. Universities are generally seen as central organisations in smart specialisation strategies, as made explicit in policy documents and academic papers. The chapter aims at knowing more about the power of smart specialisation policies to induce change in university-industry interactions and the promotion of sustainable growth.

Abstract
Entrepreneurial Ecosystems (EEs) have attracted the attention of academics, practitioners, and policymakers, that attempt to unlock 'a winning recipe' considering the different EEs pillars in order to ignite entrepreneurship at large. Therefore, understanding the degree of influence of each pillar on Entrepreneurial Initiative (EI) is helpful in framing more effective policies towards entrepreneurship. This study aims to bring a new facet to entrepreneurship research, specifically on decomposing the transformation of EEs and the influence of EEs pillars on EI. The transformation of EEs is shown by a balanced panel approach based on the Global Entrepreneurship Monitor (GEM) dataset over 8 years (2010-2017), comprising 18 countries. The study has several implications for entrepreneurship theory and practice as well as public policy since discusses three main issues, mainly supported by empirical results. First, the results show an unbalanced influence of EEs pillars on EI. Second, results also show the ineffectiveness of institutions in encouraging the desire to act entrepreneurially. Third, entrepreneurship needs to be part of the acculturation process evidencing the importance of collective normative. Therefore, providing the instruments and structures is not enough to encourage individuals to start an entrepreneurial journey. Generally, the results reveal that contextual determinants are significant in fostering entrepreneurial propensity to start a business. But the impact of the nine pillars is not equalized, revealing a fragmented influence with funding measures, R&D transfer, and cultural and social norms discouraging entrepreneurial initiative. Overall, the study contributes to the understanding of a multidimensional perspective on EEs and points future policy directions to overcome the lack of entrepreneurship and amend flawed entrepreneurship policies.

Abstract
The main goal of this article is to appraise the existence of different patterns of the Entrepreneurial Ecosystems, to identify its relationship with Entrepreneurial Initiative, and recommend entrepreneurship policies that may influence the growth of entrepreneurial action. Without evidence on entrepreneurial ecosystems landscape and what determinants stimulate entrepreneurship in a given environment, policies could become flawed and miss the target. To address research purposes, the analysis was performed using data extracted from the Global Entrepreneurship Monitor (GEM) Database carried out between 2010 and 2016. To ensure a longitudinal perspective, it was used a balanced panel approach followed by Logistic Regression estimations. The article offers a novel and systematic approach, the Entrepreneurial Ecosystem Taxonomy, to overcome a disaggregated perspective on entrepreneurial ecosystems, between individual and context levels. Empirical findings capture four different country profiles, based on two measures: Entrepreneurial ecosystems and entrepreneurial initiative. The results allow to compare the four groups and appraise significant disparities around entrepreneurship determinants, namely, the education factor. While education is commonly recognized as a positive influence on entrepreneurship, the results suggest a contradictory effect. The existence of differentiated profiles and its determinants points outs the importance of developing specific entrepreneurship policy packages attending group specificities.

Abstract
Entrepreneurial universities are a significant element of entrepreneurial ecosystems and aspire to foster entrepreneurial initiative through their "third mission". However, while entrepreneurial ecosystems are scrutinized using a contextual approach to detect differences and similarities and how they affect entrepreneurship, little is known about how entrepreneurial universities impact entrepreneurial initiatives in general, considering multiple environments. Drawing on entrepreneurial university and entrepreneurial ecosystem theories, a conceptual framework is proposed that aims to explain the effect of the entrepreneurial university on an entrepreneurial initiative through its three "missions", using an entrepreneurial ecosystem taxonomy. Based on individual data from the Global Entrepreneurship Monitor, this entrepreneurial initiative analyzed 18 European countries in 2017. The results do not generally support the importance of entrepreneurial universities to entrepreneurial initiative. The relevance of entrepreneurial universities increases in more fragile entrepreneurial ecosystems since individuals need support over multiple dimensions. Conversely, the entrepreneurial universities that are embedded in stronger entrepreneurial ecosystems lose relevance and negatively affect the entrepreneurial initiative. Therefore, the value of entrepreneurial universities is reduced when individuals receive greater support from other dimensions. The variations across both groups suggest that the concept of entrepreneurial universities is not a contemporaneous phenomenon; however, their effect is progressively revealed by the maturity of each university's mission. This perspective substantially changes the understanding of entrepreneurial universities as a thwartwise strategy, suggesting that the universities' impact is expanded as their missions gradually evolve. Overall, the study contributes to an understanding of the implications for universities that blindly follow entrepreneurship, neglecting the exogenous environment, namely, the entrepreneurial ecosystem and individual drive.

Abstract
After the Cold War, the defense industries found themselves at a crossroads. However, it seems that they are gaining new momentum, as new technologies such as robotics and artificial intelligence are enabling the development of autonomous, highly innovative and disruptive intelligent systems. Despite this new impetus, there are still doubts about where to invest limited financial resources to boost high-tech defense industries. In order to shed some light on the topic, we decided to conduct a systematic literature review by using the PRISMA protocol and content analysis. The results indicate that autonomous intelligent systems are being developed by the defense industry and categorized into three different modes-fully autonomous operations, partially autonomous operations, and smart autonomous decision-making. In addition, it is also important to note that, at a strategic level of war, there is limited room for automation given the need for human intervention. However, at the tactical level of war, there is a high probability of growth in industrial defense, since, at this level, structured decisions and complex analytical-cognitive tasks are carried out. In the light of carrying out those decisions and tasks, robotics and artificial intelligence can make a contribution far superior to that of human beings.

Abstract
Leadership styles and human capital are important drivers of innovation processes. The way the leader interacts with the organization members can pre-empt or leverage innovation processes as leaders influence, empower and motivate other individuals in the achievement of their goals. Human capital is an important driver of innovation and competitiveness, as it will shape the uniqueness of the company as well as the process to obtain skills, capabilities, knowledge and expertise. As such, the main objectives of the paper are to analyze the impact of leadership styles on the innovation process and also to address the moderation effect of the human capital on the previous relation. Four leadership styles-autocratic, transactional, democratic, and transformational-were considered to measure their impacts on the innovation process, considering the alternative types of innovations. The 2018 Community Innovation Survey (CIS) database was used, encompassing Portuguese data, covering the 2016-2018 period, with a sample of 13702 firms. In regard to the empirical part, first, an exploratory analysis was run to better understand the connection between the leadership styles and the innovative strategies followed by an econometric estimation encompassing 28 logit models to disentangle the specific impacts of each leader on each innovation type. Evidence proves that autocratic and transactional leadership styles have a negative impact on innovation and transformational and democratic leadership impact innovation positively. Furthermore, human capital was found to moderate the relationship between leadership styles and the innovation process; i.e., under the same leadership style, the presence of additional skills leverages innovative propensity. The paper brings relevant insights for both managers and policymakers, highlighting that innovation will be accelerated if firms implement more participatory (democratic and transformational) leadership styles and also if they invest in competences to promote knowledge internalization and share. All in all, participatory leadership combined with the internal skills is proved to be an efficient combination for innovation to take place; as such, policy instruments must promote the coexistence of these two factors.