Programa del congreso

• The circular economy (CE) model has emerged as a new paradigm to reduce the environmental impact of human activity. While sustainability research argues that implementing CE models requires innovation ecosystems, the innovation ecosystem literature offers a limited understanding of how agents interact to develop CE innovations.

• This paper explores the configuration of collaboration patterns in Innovation Ecosystems for Circular Economy (IECEs).

• Our empirical setting is the Horizon Europe programme. We used 275 projects—involving a network of 2,364 organisations and 30 countries—that contributed to the transition to circular models. The study hinges on a multilevel network analysis that looks at the country and organisational levels and considers the different types of agents in the IECE.

• Hence, we are able to obtain insights into the networks’ macro and microstructure, deepening our understanding of the collaboration dynamics between economic agents in the IECE. Additionally, and challenging conventional wisdom, this study offers policy and managerial implications by unveiling how economic resources are distributed and interconnection patterns are configured.

Our objective is to examine whether the formulation of eco-innovative objectives impacts on the open innovation strategy. Specifically, we analyse the influence on the breadth and depth of knowledge sources.

This paper is framed in the literature on open eco-innovation. Open innovation has been considered as an idiosyncratic driver of eco-innovation. However, we follow the strategic management process to analyze how the orientation of innovative activity towards environmental goals can determine a firm's open innovation strategy.

We examine the influence of eco-innovation objectives on the breadth and depth of knowledge sources and compare the results with firms that formulate non-eco-innovation objectives. Additionally, we analyze the open innovation strategy adopted by firms that start to formulate eco-innovation objectives. Using data from the Community Innovation Survey of Spanish firms (PITEC), we construct panel data from 2008 to 2016.

The results show that the formulation of eco-innovation objectives positively influences the open innovation strategy of the firm, both in terms of breadth and depth of knowledge sources. This is in contrast to the implementation of non-eco-innovation objectives, which presents a negative relationship. Moreover, our analysis confirms that the open innovation strategy is reinforced in those companies that start to formulate eco-innovation objectives.

The evolution of the entrepreneurial university has given rise to institutions that are more committed to the environment and oriented towards a more broadly defined mission. This research, considering the role to play by the universities in the ecosystem, adapts the ambidexterity concept to the university from a multi-dexterity approach, and defines the University-Ecosystem Ambidexterity as the capability of the university to align with its internal objectives while at the same time adapting to the ecosystem dynamics, exchanging value efficiently.

By means of the participation in a European project, a database of international academics recognized for their ambidextrous behavior is created and analyzed through thematic analysis. The results highlight the need to act on individual behavior, promoting academics' ambidexterity to foster effective and fruitful relations with the ecosystem. From a contextual perspective, the university can achieve this through three areas of action: organizational, motivational and individual. The characteristics of each conditioning factor are defined. In addition to advancing knowledge in the field of ambidexterity and the entrepreneurial university from an ecosystemic approach, this research provides value at the applied level, defining areas of action for university management.

Open innovation has revolutionized the way organizations approach innovation by breaking down barriers and utilizing the exchange of knowledge to enhance their innovation processes. This shift in the innovation paradigm has moved away from a more protective approach towards fostering cooperative connections. However, the management of the vast quantity of information and data produced in an open innovation ecosystem often necessitates the utilization of information and communication technology. Artificial intelligence can significantly aid in capitalizing on the various opportunities that arise from open innovation in this particular setting. This work utilizes bibliometric analysis to unravel the knowledge structure of research on the utilization of artificial intelligence tools in open innovation ecosystems. The recent surge in academic output suggests a potentially significant interest in this subject, which can be examined from various levels, including operational, managerial, and social. This analysis uncovers the presence of significant research opportunities.

The ways firms innovate and digitalize have attracted enormous attention through the so-called open innovation paradigm and the industry 4.0 revolution, respectively. Surprisingly, the open innovation and industry 4.0 relationship has been mainly overlooked. How open innovation strategies may foster industry 4.0 adoption remains neglected. This study postulates that innovation is increasingly only possible in manufacturing by relying on the interconnectedness that provides industry 4.0 and the embeddedness enabled by open innovation. According to this view, we explore whether innovativeness and openness accelerate the adoption of 12 industry 4.0 technologies, ranging from augmented/virtual reality to 3D manufacturing, including machine learning, internet of things (IoT), cloud computing, big data, natural language processing, radio frequency identification (RFID), industrial robots, and automated storage and retrieval systems. Using a sample of 733 manufacturing firms competing in Spain, the regression results indicate that more innovative and open firms are ahead in the race for the digital transformation of manufacturing, but they do so according to a moderated relationship. In particular, openness amplifies the positive effect of innovativeness on industry 4.0 adoption after other variables are controlled for. Managerial and policy implications call for a coevolutionary approach to open innovation and industry 4.0 in the future.