Abstract
The article aims to appraise the role of Corporate Social Responsibility (CSR) and innovation strategies as leverages of a company's financial performance. The theoretical and empirical statement of this link aims to reinforce the importance of these strategical options in both the managerial and the public policy domain. Shedding light on the economic return of these practices will help managers make better strategic decisions. Policy makers will also grasp the required evidence to encompass CSR in policy packages. To address the research question, data were collected from the Thomson Reuters Eikon Datastream covering the 1000 largest companies listed on the stock exchange worldwide. Thereafter, hierarchical linear regressions were performed to produce the econometric results. Two time frames (2015-2019) were compared to address time-space trends. Enrolling in CSR activities entails additional costs which can undermine the company's financial performance if not properly supported by public policies. Combining CSR and innovation appears to be the best strategy for companies seeking improvements in their financial performance while being socially responsible. The contribution of this study is threefold: first, the analysis covers the largest thousand firms in operation worldwide; secondly, the econometric results demonstrate that combining CSR with innovation positively impacts financial performance; and lastly, the time comparison evidences a positive but slow evolution in CSR adoption. The article provides an applied perspective, of use both for managers and policy makers, as to how they should approach and disseminate involvement in these types of activities.

Abstract
The European Defence Industry is undergoing profound changes. Industrial activity is now operating on a quintuple helix innovation model with the deep involvement of universities and governments in innovation. In addition, military innovations are being transferred to civil society, with increasing attention paid to the environment. In the first stage, we report on the state-of-the-art of existing research using PRISMA protocol. The PRISMA technique is widely accepted by the academic community for its ability to discover concepts, ideas, and debates about the defence industry. In the second stage, we present a case study involving the Portuguese Defence Industry, for which multiple data collection sources were used to ensure triangulation and corroboration. The results show that, in the light of the quintuple helix innovation model, it was possible to bring applications from theoretical discussion to real life. Moreover, within the scope of the triple helix, it was possible to develop, produce and test military products, allowing to improve the military capacity of ground forces. In the future, ecological concerns will likely increase, so we suggest a greater focus on this area of research.

Abstract
The search for a pleasant home has concerned people ever since. Paradoxically, people are facing strong difficulties in finding a decent place to settle their lives in cities. As such, the housing market regained momentum in connection with the development of Smart Cities, where life quality of residents is strongly emphasized. Well-being in the metropolis is affected by a wide variety of factors with housing supply being among the most important, hence stirred by financing costs, construction costs, vacancy rate, sales delay, inflation rate, housing stock, price of agricultural land, and regulation. The present article reviews empirical studies on housing supply for a better understanding of the dynamics in this market, shedding some light on the expectable outcomes of policy actions in the promotion of sustainable housing towards the smart city transition. Our review shows that the long-run price elasticity of housing supply is larger than the short-run, as well as the existence of substantial differences in the price elasticity across countries and regions. As such, overall, the hypothesis of a perfectly elastic supply is rejected. In addition, our review highlights that housing supply is negatively related to financial costs, inflation, sales delay, and the existence of regulatory or physical constraints. Also, the elasticity is lower when there are regulatory constraints. Newfangled strategic interaction models, though overlooked in the literature, reinforce that housing does not fit the perfect competition frame. The review proves that we are in face of a non-competitive market in which policy intervention is required to maximize social welfare; policy packages to grant people access to the housing market may be required. However, policy interventions should be carefully designed and clear, to mitigate their potentially negative impact on the housing supply as adverse results may be harmful to the transition towards a smart city.

Abstract

Abstract
Scholars and practitioners continue to recognize the crucial role of entrepreneurial ecosystems (EEs) in creating a conducive environment for productive entrepreneurship. Although EEs are fundamentally interaction systems of hierarchically independent yet mutually dependent actors, few studies have investigated how interactions among ecosystem actors drive the entrepreneurial process. Seeking to address this gap, this paper explores how ecosystem actor interactions influence new ventures in the financial technology (fintech) EE of Singapore. Guided by an EE framework and the use of an exploratory-abductive approach, empirical data from semi-structured interviews is collected and analyzed. The findings reveal four categories representing both the relational perspective, which features interaction and intermediation dynamics, and the cultural perspective, which encompasses ecosystem development and regulatory dynamics. These categories help explain how and why opportunity identification and resource exploitation are accelerated or inhibited for entrepreneurs in fintech EEs. The present study provides valuable contributions to scholars and practitioners interested in EEs and contributes to the academic understanding of the emerging fintech phenomenon.

Abstract
Climate change and global warming interconnected with the new contexts created by the COVID-19 pandemic and the Russia-Ukraine conflict have brought serious challenges to national and international organizations, especially in terms of food security and agricultural planning. These circumstances are of particular concern due to the impacts on food chains and the resulting disruptions in supply and price changes. The digital agricultural transition in Era 4.0 can play a decisive role in dealing with these new agendas, where drones and sensors, big data, the internet of things and machine learning all have their inputs. In this context, the main objective of this study is to highlight insights from the literature on the relationships between machine learning and food security and their contributions to agricultural planning in the context of Agriculture 4.0. For this, a systematic review was carried out based on information from text and bibliographic data. The proposed objectives and methodologies represent an innovative approach, namely, the consideration of bibliometric evaluation as a support for a focused literature review related to the topics addressed here. The results of this research show the importance of the digital transition in agriculture to support better policy and planning design and address imbalances in food chains and agricultural markets. New technologies in Era 4.0 and their application through Climate-Smart Agriculture approaches are crucial for sustainable businesses (economically, socially and environmentally) and the food supply. Furthermore, for the interrelationships between machine learning and food security, the literature highlights the relevance of platforms and methods, such as, for example, Google Earth Engine and Random Forest. These and other approaches have been considered to predict crop yield (wheat, barley, rice, maize and soybean), abiotic stress, field biomass and crop mapping with high accuracy (R2 approximate to 0.99 and RMSE approximate to 1%).