Abstract
Objective: The present investigation aims to identify the explanatory factors for academic satisfaction, as well as the influence that the identified factors have on the degree of academic satisfaction in its global context and on the chances of the institution's recommendation to friends and family.   Method: The investigation was conducted with a sample of 290 students from the Federal Institute of Education, Science, and Technology of Piauí (FIEPI-Campus Oeiras). The instrument used for data collection was a questionnaire. The statistical techniques used were of a descriptive, exploratory, and multivariate nature for the treatment, analysis, and validation of the results.   Results and Discussion: The results indicate that Academic Satisfaction is determined by the factors (1) Teaching Environment and (2) Structural Environment and that there is a significant decrease in Academic Satisfaction when students move from the group from High School to Higher Education due to the determinants satisfaction.   Research Implications: The development of strategies for the maintenance and attraction of new students by FIEPI-Campus Oeiras and other educational institutions must be based on academic satisfaction considering their specificities, namely, concerning the different perceptions and expectations generated by students about educational services.   Originality/Value: The relevance of this investigation is based on the fact that the measurement of student satisfaction by a given educational institution becomes essential for it to understand the perception of its students about its products and services, enabling the identification of new ways of generating satisfaction and loyalty.

Abstract
The pandemic marked the beginning of a succession of events on a global scale (not the least of which is a greater concern for the environment and for quality of life/distance work) with a major impact on the economy. Innovation plays a key role in meeting the challenges of the future, but despite investment in innovation, global economic growth has fallen short of the expected performance. The aim of this study is to identify the factors with the greatest impact on the performance of innovation ecosystems based on the performance of the innovation ecosystems of 64 countries assessed by the Global Innovation Index 2022. The methodology consists of multiple hierarchical linear regressions, in which the impact factors on innovation ecosystems, measured through indicators, are the independent variables and innovation performance, in knowledge and technology and in creativity, are the dependent variables in an iterative process, using STATA/MP 18.0 data analysis software. The results indicate that human capital and research (the basis of business and innovative products aimed at filling gaps in the market are people with a good higher education, which is also linked to local university rankings) and business sophistication (highly qualified work, leveraging strategic partnerships, and with knowledge absorption capacity) are the main pillars determining innovation performance at a global level. Education (an educated workforce is of growing importance in the knowledge era), R&D investment (including support from the state in the form of tax incentives for whoever invests in R&D), innovation partnerships (for a faster, more open innovation effort), ecological sustainability (a new reinforced priority after COVID-19) and knowledge absorption (to absorb one must first detain valuable knowledge in the area) are the variables with the greatest impact on innovation performance. The work provides guidance on which areas should be prioritized in the development of policies and strategies to accelerate innovation in countries. The study is limited by the time frame and reveals, by comparison with pre-pandemic studies, that the determinants of innovation can be dynamic, varying according to the countries and, consequently, the global context of the analysis.

Abstract
The NEXUS project involves innovation and entrepreneurship. The first task of the project team, which is eclectic and includes several different profiles (research assistants, researchers, managers, engineers, designers and marketing specialists) was to do a stakeholder analysis, which involved doing some field work – six unstructured interviews – as well as some secondary data analysis (scientific articles on the Scopus database; Google searches; among others). The main concerns were to: unlock value through stakeholder engagement; move from concept to collaboration – for sustainable port development; and to connect ports worldwide which will involve international stakeholder collaboration and synergies for sustainable innovation. A Stakeholder analysis is a process consisting of identifying the individuals or groups that have a specific interest in a project, which can affect them, or be affected by them, including large groups such as customers and suppliers; employees; shareholders and investors. It is necessary to sort them according to their impact and consequences regarding the project. It is essential to manage stakeholder expectations when making decisions, especially in a project with thirty-five partners and with a global reach. The initial funding is around 92 million euros (approved by the Recovery and Resilience Plan (RRP)), to ensure the ambitious implementation of the new NEXUS platform and other related products. To minimize backlash, early as well as ongoing stakeholder involvement is a prerequisite. Strategy formulation should not occur in an “ivory tower” and involvement is key. For effective and efficient decision-making, to minimize risks, which need to be identified as well as all the connections and relationships to be created and nurtured. The research question at the outset was: How may we successfully implement a multi-partner project which involves considerable investment, and which aims to digitalize maritime ports worldwide? The theme is, currently, without precedent as the impact intended is for there to be a positive impact on all stakeholders involved – a win-win situation all around. The project will finish in 31-12-2025 and will produce 28 innovative solutions for commercialization. NEXUS is a green and digital project which is up to date as regards the latest sustainability norms and regarding overall operational efficiency in multimodal logistics. Work Package 10 is a specific exploitation, internationalization, promotion, and dissemination package.

Abstract
This cross-sectional study addresses Portuguese online shoppers' behavior toward Chinese online retailers, assessing the impact of financial, product, and time-convenience risks and demographic traits on their willingness to buy from those e-stores. The research relies on a survey of 1,432 participants who have shopped online at least once. Approximately half of the sample already buys from Chinese websites; age, financial, and time-convenience risks explain 21.5% of the variance of their purchase intention. On the other hand, participants who buy on Chinese websites present significantly lower values of all risks and the intention to buy from Chinese websites, possibly reflecting a satisfactory transaction experience. Furthermore, a generation gap is evident as younger people feel more confident in dealing intuitively with and solving online issues, giving them the confidence necessary to purchase online from Chinese e-stores - perhaps geographically and ideologically distant - but brought closer by e-expertise (online dexterity).

Abstract
Artificial intelligence (AI) has gained significant evolution in recent years that, if properly harnessed, may meet or exceed expectations in a wide range of application fields. However, because Machine Learning (ML) models have a black-box structure, end users frequently seek explanations for the predictions made by these learning models. Through tools, approaches, and algorithms, Explainable Artificial Intelligence (XAI) gives descriptions of black-box models to better understand the models' behaviour and underlying decision-making mechanisms. The AI development in companies enables them to participate in Industry 4.0. The need to inform users of transparent algorithms has given rise to the research field of XAI. This paper provides a brief overview and introduction to the subject of XAI while highlighting why this topic is generating more and more attention in many sectors, such as industry.

Abstract
Exploring a rich administrative matched employer -employee longitudinal dataset over the 2002-2020 period and a task -based approach, this study investigates to what extent the recent paradigm shift in the electricity sector has affected the structure of employment and wages in the Portuguese case. Our results show that the liberalization in the sector led to the entry of new players and firms' downsizing of the workforce, most notably in occupations involving routine cognitive tasks and non -routine manual tasks. In two decades, the employment share of occupations involving non -routine cognitive tasks (abstract or interactive) doubled, from 29.7% in 2002 to 58.1% in 2020. Regarding wage premiums, the results reveal a clear positive trend in real hourly wages for all types of occupations in the sector. However, we observe a lower wage growth acceleration for workers employed in routine (cognitive or manual) occupations, when compared with similar workers employed in non -routine occupations (cognitive or manual). Our findings are partly consistent with the skill -biased and routine -biased technological change hypotheses in the sense that we observe, respectively, a skill up -grading translated into an increase in employment share in non -routine cognitive occupations and a substantial decline in employment share in routine cognitive occupations.