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The objective of this study is to propose a model for the implementation of a technological platform for participants to develop solutions to problems related to the Fourth Industrial Revolution (4IR) megatrends, and taking advantage of artificial intelligence (AI) to develop their complex thinking through co-creation work.

The development of the model is based on a combination of participatory action research and user-centered design (UCD) methodologies, seeking to ensure that the platform is user-oriented and based on the experiences of the authors. The model itself is structured around the active and transformational learning (ATL) framework.

This study highlights the importance of addressing 4IR megatrends in education to prepare students for a technology-driven world. The proposed model, based on ATL and supported by AI, integrates essential competencies for tackling challenges and generating innovative solutions. The integration of AI into the platform fosters personalized learning, collaboration and reflection and enhances creativity by offering new insights and tools, whereas UCD ensures alignment with user needs and expectations.

This research presents an innovative educational model that combines ATL with AI to foster complex thinking and co-creation of solutions to problems related to 4IR megatrends. Integrating ATL ensures engagement with real-world problems and critical thinking while AI provides personalized content, tutoring, data analysis and creative support. The collaborative platform encourages diverse perspectives and collective intelligence, benefiting other researchers to better conceive learner-centered platforms promoting 21st-century skills and co-creation.

The paper aims to present an integrated foresight framework and method to support decision-makers who are confronted with today’s complex and rapidly changing world. The method aims at reducing the degree of uncertainty by addressing the inertia or duration of unfolding trends and by placing individual trends in a broader context.

The paper presents a three-layered framework and method for assessing megatrends based on their inertia or duration. It suggests that if long-term trends and key future uncertainties are studied in conjunction at a meta-level and placed in a broader multi-layered framework of trends, it can result in new insights.

The application of the proposed foresight method helps to systematically place a wide range of unrelated trends and key uncertainties in the context of a broader framework of trends, thereby improving the ability to understand the inertia, direction and mutual interaction of these trends.

The elaboration of identified trends and key uncertainties is partly case-specific and subject to interpretation. It is aimed at illustrating the potential use of the framework.

The paper presents a new approach that may, by itself or in combination with existing foresight methods, offer new means for anticipating future developments.

The use of the proposed framework has potential to provide better insight in the complexity of today’s rapid-changing world and the major transitions taking place. It aims to result in sharper foresight by reducing epistemic uncertainty for decision-makers.

The paper demonstrates how megatrends, Kondratieff waves and century-long trends can be placed in an integrated framework and analysed in conjunction.

The purpose of this study is to analyze the robot trends of the next generation.

This paper is divided into two sections: the key modern technology on which Europe's robotics industry has built its foundation is described. Then, the next key megatrends were analyzed.

Artificial intelligence (AI) and robotics are technologies of major importance for the development of humanity. This time is mature for the evolution of industrial and service robots. The perception of robot use has changed from threading to aiding. The cost of mass production of technological devices is decreasing, while a rich set of enabling technologies is under development. Soft mechanisms, 5G and AI have enabled us to address a wide range of new problems. Ethics should guide human behavior in addressing this newly available powerful technology in the right direction.

The paper describes the impact of new technology, such as AI and soft robotics. The world of work must react quickly to these epochal changes to enjoy their full benefits.

This paper aims to review the experience so far of the Spanish labour market during the Covid-19 crisis in the light of the existing institutions, its performance during past recessions and the policy measures adopted during the pandemic. Emphasis is placed on the role of worldwide trends in labour markets because of automation and artificial intelligence, in shaping a potential recovery of this (hopefully) transitory shock through a big reallocation process of employment and economic activity. It also highlights some innovations to employment and social policies needed to smooth the reallocation process and lessen the rise in inequality associated to technological trends.

Theory and empirics.

The Spanish labour market will subject to a great reallocation shock as a result of Covid-19 and secular technological changes. Reforms need to be undertaken.

An overview and some new results.

The tourist industry has to adopt a big data-driven foresight approach to enhance decision-making in a post-COVID international landscape still marked by significant uncertainty and in which some megatrends have the potential to reshape society in the next decades. This paper, considering the opportunity offered by the application of the quantitative analysis on internet new data sources, proposes a prediction method using Google Trends data based on an estimated transfer function model.

The paper uses the time-series methods to model and predict Google Trends data. A transfer function model is used to transform the prediction of Google Trends data into predictions of tourist arrivals. It predicts the United States tourism demand in Italy.

The results highlight the potential expressed by the use of big data-driven foresight approach. Applying a transfer function model on internet search data, timely forecasts of tourism flows are obtained. The two scenarios emerged can be used in tourism stakeholders’ decision-making process. In a future perspective, the methodological path could be applied to other tourism origin markets, to other internet search engine or other socioeconomic and environmental contexts.

The study raises awareness of foresight literacy in the tourism sector. Secondly, it complements the research on tourism demand forecasting by evaluating the performance of quantitative forecasting techniques on new data sources. Thirdly, it is the first paper that makes the United States arrival predictions in Italy. Finally, the findings provide immediate valuable information to tourism stakeholders that could be used to make decisions.

In a world where innovation became a “buzzword” and everyone within companies is required to foster innovation, the engagement of people toward innovation is fundamental to prompt individual motivation and actions to make innovation happen. However, despite the relevance of the relationship between engagement and innovation, the literature on the topic appears still fragmented. The purpose of this study is to provide an overview of the topic through a systematic literature review.

A final sample of 108 papers has been selected and analyzed through co-citation and text mining analyses. The former enabled the analysis of the structure of the theoretical foundation of the filed, while the latter facilitated a systematic and unbiased content-driven review of the literature.

The results of the analysis indicated two main areas of interest describing the relationship between engagement and innovation. On the one hand, there is the focus on “engagement as an attitude,” intended as the capacity of individuals to generate and realize innovation. On the other hand, there is a stream of literature focused on “engagement as involvement,” which refers to co-innovation paradigms, involving both internal and external stakeholders.

From an academic perspective, this paper highlights the relevance of the “human-side” of innovation, proposing avenues for future research that dig into the relationship between people's engagement and innovation dynamics. Moreover, it shows how the recent developments in the innovation management literature are coherent with this emerging relevance of the human perspective in innovation.

From a practitioner’s perspective, this paper helps managers by highlighting the two different approaches that they can have in terms of engagement. The study aims to help them in identifying the kind of engagement they are looking for in their employees and other innovation stakeholder having the support to find relevant studies in that direction.

The study unveils how the evolution of both areas over the years is strictly related to the megatrends of innovation fields, which are the main areas of knowledge not covered yet. Therefore, a research agenda is proposed.

Corporate governance principles are living a positive momentum in light of the megatrends reshaping the world. An effective company based on sound governance principles can prevent issues and corporate scandals as the company ensures greater transparency and accountability. Accordingly, this paper aims to investigate the relationship between shareholder-oriented corporate governance mechanisms, value and performances in the real estate sector.

This paper investigates the relationship between corporate governance mechanisms, performance and value in a sample of 111 USA real estate firms. After collecting data from 2014 to 2018, this paper tests the research hypothesis using the linear fixed-effect model.

The results demonstrate a positive impact of shareholder-oriented corporate governance mechanisms on performance and value. In particular, firms with no chief executive officer (CEO) duality and staggered board mechanisms and recognizing excess variable compensation to the firms' executive have a significantly higher Tobin's Q, return on assets (ROA) and price-to-book performance.

The implications are twofold: on the one hand, this motivates shareholders to establish new corporate control mechanisms to maximize value, attract more capital and improve operating performance. On the other hand, this allows investors to direct the investors' resources toward real estate firms with effective corporate governance mechanisms that may return higher performance and value.

Focusing on the real estate industry, where governance is expected to have a lower impact due to solid regulation, especially in real estate investment trusts (REITs), the research allows the formulation of industry-specific inferences that may be generalized for the general market.