Raffaella Manzini

Innovation strategy is one of the most critical decisions firms face. Beyond the traditional make-or-buy dichotomy, hybrid and plural sourcing approaches, such as strategic alliances, highlight a third strategic option: collaboration. This study examines the combined effects of “making” (independently or jointly with partners) and “buying” innovation on firm performance. We develop an agent-based model and simulator in which heterogeneous firms are embedded in a directed random graph, enabling the analysis of interaction-driven innovation dynamics. Results indicate that the most advantageous strategy for economic performance varies with sectoral innovation intensity, underscoring the contextual nature of innovation choices. The agent-based approach reveals complex emergent behaviors and provides insights into how strategic decisions propagate through the system. These findings emphasize the importance for managers and policy-makers of adopting a holistic view of the innovation process and considering the interplay between internal development, external sourcing, and collaborative activities.

In this dynamic and full-opportunity world, firms must face challenges in markets and technologies. One of the main assets that firms can use to address these challenges is innovation, and an important element is to define the most appropriate innovation strategy. Inside innovation strategy, fundamental decisions are about selection, acquisition, and timing. Selected the innovations to develop; and how to acquire the innovation with respect to timing, firms are heterogeneous and two main approaches can be identified: to be technological leaders and technological followers. In this paper, the two approaches have been investigated to study the impact on the firm’s performance. To conduct this investigation, the Patent Agent-Based Innovation Model and Simulator (PABIM) has been enhanced. The PABIM is characterized by heterogeneous firms that are organized as a directed random graph. The use of an agent-based model allows for the exploration of emergent dynamics and their subsequent effects on performance. The results indicate that when a firm can adopt all the acquisition strategies (make, buy, collaborate), the optimal strategy concerning timing for firm performance is the leaders’ approach, independently of the sector innovation intensity. The study recommends that managers and policymakers adopt a comprehensive approach to innovation management, integrating pertinent technical knowledge related to product or process development with the necessary resources for effective implementation.

In this world so dynamic and full of opportunities, firms need to face challenges in markets and technologies. One of the main assets that firms can use to address these challenges is innovation and one important aspect of innovation management is choosing between insourcing (make) or outsourcing (buy) innovation. Not only the historical and dichotomous make-or-buy perspective should be taken into account by firms, but also hybrid and plural sourcing views as well as the creation of strategic alliances. Thus, in the dilemma, there is a third opportunity for firms, i.e. collaboration. In this work, the joint impact that "making" (alone or opening to collaborations with other companies) or "buying" innovation may have on companies' performance has been investigated. For this study, an agent-based model and simulator characterized by heterogeneous firms that are organized as a directed random graph has been developed. Results show that the most convenient strategy for economic performance is the buying innovation strategy. The adoption of an agent-based model allows an understanding of emerging dynamics and their effect on performance. For managers and policy-makers, it suggests the need to see the innovation process with a comprehensive view, including the understanding not only of the technical knowledge of the product or process produced but also the resources that need to be used or acquired to make it.

Debate is a transversal, active, cooperative, and problem-based learning methodology and its use is positively and effectively documented also within the field of engineering education to boost transversal skills. The significant and acknowledged contribution to educational innovation that debate can offer in the current university context and in engineering education in terms of content learning and skill development, however, tends to overshadow its broader potential for Faculty Development. Assuming that Faculty Development can encompass at least broad dimensions such as professional, curricular, and institutional development, this article explores with a case study and qualitative methodology how debate can be fruitfully adopted for supporting Faculty Development in engineering faculties. The experiences conducted at the Faculty of Engineering of the Cattaneo University – LIUC – a systematic adoption of debate in didactics and a national university tournament on Sustainable Development Goals entitled Debating Agenda 2030, among others – show how debate can enrich Faculty Development by providing opportunities for professional and curricular development while fostering learning and collaboration among students, institutions, and communities.

The Engineering Skills Special Interest Group (SIG) ran a workshop on the current challenges in teaching engineering skills. This workshop employed the “world café” participatory method where attendees visited three tables for a structured discussion with a member of the SIG. Each table posed a different question: On the What? table we discussed which skills are most relevant for future practitioners. The Who? table focussed on the differences in the way that various professional skills are conceptualised by main stakeholders. Finally, at the How? table we discussed the facilitators and barriers in designing and delivering skills education. The outcome of the workshop presented here is a mapping of skills in terms of present and future importance to attendees and their countries, and a classification of stakeholders in terms of macro, meso, micro level when considering their influence over skill conceptualisation and realisation.

To stay abreast of the dynamic market and technological environment, firms should improve their innovation and economic performance continuously. To cope with such requirements, companies often adopt an Open Innovation (OI) strategy. Among several possible OI strategies, co-patenting is a tool to develop innovation with more actors. Thus, companies leverage time by time their innovation network in which each actor represents a node and the knowledge between the companies the link existing between the nodes. The work aims to investigate if and how different innovation networks, foster the innovation and economic performance of firms. An agent-based model and simulator have been developed to investigate the emergence of hubs and the impact on firm performance. The economic and innovation performances are evaluated respectively using turnover and the Innovation Patent Index (IPI). Results show that the presence of hubs in the network helps firms to increase their performance.

The role and education of engineers are widely discussed in recent years, because of the increasing relevance of technology and technological knowledge for the future sustainable economic development. Engineering programs should be able to provide students with the desirable level of vertical specialisation, and also with multi- and inter-disciplinarity, non-traditional, horizontal competences and soft skills. To this aim, a "situated" or "embedded teaching" approach could be helpful. An example is reported in which such an approach has been applied to a bachelor and a master program in management engineering at LIUC Università Cattaneo. Three transversal paths have been introduced on sustainability, critical thinking and fieldwork, in which a set of theoretical and practical activities are totally embedded not only into a real context, but also into the set of laws, language and symbols typical of the traditional specialization engineering disciplines.

Several actors – including governments, academics, and NGOs – are calling for an urgent shift to circular economy. Nevertheless, few research attention centers on tools or frameworks to support organizations engaged in the creation of circular value. This research leverages design thinking in the field of business model innovation, with the aim to uncover its implications for circular value co-creation. Based upon a multiple case study design, this research shows that higher levels of cybernetics coupled with a more circular mindset can contribute to the creation of circular value, but only the highest levels of cybernetics in combination with a highest circular mindset result in self-sustaining circular value in systems in which multiple stakeholders are engaged. The theoretical and managerial implications emphasize the contribution of design thinking in the process of implementing circular business models and the concept of circular self-sustaining value as central to their success.

Teaching innovation management to engineers is becoming increasingly relevant. However, it can be difficult to involve engineers in a discipline in which technical competences do not represent the core whereas professional and soft skills play a critical role. For this reason, adopting the proper teaching approach is key to capture the students' attention and interest. In our study, we propose a laboratory for teaching innovation based upon two elements that are very closed to the engineering mindset: patents and machine learning algorithms. The laboratory proposes the application of machine learning approaches to patents data, for studying the innovation activity of companies. Three machine learning algorithms, Least Squares, Deep Neural Networks and Decision Trees are exploited. Their application is proposed to capture the relationships between relevant patents output variables (such as, for example, the number of forward citations, as proxy of the company's innovation capability) and the related input features (such as, for example, the number and type of patent technological classes). By practically using this approach, students can be introduced to some relevant topics in innovation management, such as investments, protection, market identification, cumulation of knowledge.

Capabilities and, in particular, Innovation Capability (IC), are fundamental strategic assets for companies in providing and sustaining their competitive advantage. IC is the firms' ability to mobilize and create new knowledge applying appropriate process technologies and it has been investigated by means of its main determinants, usually divided into internal and external factors. In this paper, starting from the patent data, the patent's forward citations are used as proxy of IC and the main patents' features are considered as proxy of the determinants. In details, the main purpose of the paper is to understand the patent's features that are relevant to predict IC. Three different algorithms of machine learning, i.e., Least Squares (RLS), Deep Neural Networks (DNN), and Decision Trees (DT), are employed for this investigation. Results show that the most important patent's features useful to predict IC refer to the specific technological areas, the backward citations, the technological domains and the family size. These findings are confirmed by all the three algorithms used.