Fernanda Strozzi

Learning Factories (LFs) have become increasingly important in engineering education, offering environments where students can engage in experiential learning and connect theoretical knowledge with industrial practice. In 2016, LIUC University established the i-FAB LF, a foosball assembly line where students experience real factory scenarios, as part of educational formats designed to develop skills in lean manufacturing and Industry 4.0. In this context, a variety of activities devoted to industrial engineering students has been developed. Among these, a learning activity centered on the integration of Artificial Intelligence (AI) into quality management stands out as a representative example, fostering the development of the skills required by the new workforce in the context of Industry 5.0 (I5.0). This activity offers a hands-on, team-based learning experience, with its pedagogical foundation rooted in the A3 problem-solving framework, which guides students in systemat ically identifying quality issues, collecting relevant data, and analyzing root causes in the production process. Following this structured analysis, students apply their insights to develop an AI tool leveraging convolutional neural networks to automati cally detect and classify assembly defects. In this way, the A3 process provides both the diagnostic foundation and the data driven roadmap for AI implementation, connecting structured problem solving with innovative technological countermeasures. Taken together, these elements foster skills in creative and innovative thinking, collaboration, data analytics and problem solving – considered as key competencies in the I5.0 paradigm. The contribution of this study is to present the LF-based educational activity and to report students’ perceptions collected through a structured questionnaire on three dimensions: learn ing experience and pedagogical design, collaboration and motivation, and quality of the learning environment.

Background: This study explores sourcing risk in supply chains by identifying key risk categories, trends, and management strategies. It responds to increased vulnerabilities exposed by recent global disruptions such as the COVID-19 pandemic and geopolitical conflicts. Methods: The research applies a Systematic Literature Network Analyses (SLNA) combined with textual analysis to examine 687 peer-reviewed publications over the past three decades using the PRISMA protocol. Citation network analysis, keyword co-occurrence mapping, and main path analysis were conducted to map intellectual developments. Additionally, textual analysis using the Semantic Brand Score (SBS) approach revealed thematic relevance, novelty, and impact. Results: A shift exists from foundational supplier optimization models to resilience-building/strengthening, ethical sourcing, and technology-enabled strategies. Responsible sourcing and modern slavery were found to be the most innovative and underexplored areas. Research on sector-specific challenges, particularly for small and medium-sized enterprises, remains limited. Conclusions: Sourcing risk has become a systemic challenge requiring resilience, ethics, and data-driven coordination across supply networks.

As industries worldwide face mounting environmental regulations and resource constraints, the integration of Circular Economy (CE) principles has gained prominence, with Industrial Symbiosis (IS) emerging as a key operational mechanism. IS facilitates the mutual exchange of materials, energy, water, and by-products among firms, thereby enhancing resource efficiency and minimizing waste. This study investigates the intersection of IS and Social Network Analysis (SNA), a methodological approach increasingly used to map and analyze the complex inter-organizational networks underpinning symbiotic exchanges. Employing a Systematic Literature Network Analysis (SLNA) framework, this research reviews and synthesizes 86 core publications to uncover prevailing themes, methodological trends, and network structures. The results highlight the growing sophistication of SNA applications within IS studies, revealing key metrics such as centrality, density, and tie formation that elucidate the dynamics of resource sharing. Furthermore, the analysis identifies dominant network configurations—such as core-periphery and decentralized clusters—that characterize successful IS systems. The study proposes a conceptual framework delineating the cyclical development phases of IS networks, emphasizing the critical roles of trust, information sharing, and stakeholder engagement.

Purpose – This study aims to explore the interaction between social media and firms’ absorptive capacity (ACAP), which involves acquiring, assimilating, transforming and exploiting external knowledge. While existing research often examines these topics separately, this paper bridges the gap by analyzing their interconnectedness to provide a holistic understanding. Design/methodology/approach – A data-driven approach combining bibliographic coupling and authors’ keyword network analysis was used to mitigate the subjectivity of traditional literature reviews. A total of 50 peer-reviewed journal and conference articles from Scopus were analyzed using VOSviewer to identify thematic research streams (RSs). Findings – The analysis identifies five RSs: the impact of social media and ACAP on innovation performance; their effect on performance in a multi-level landscape across different analytical units (individual, team, organization); the role of social media in specific contexts, including internal and external collaborations; online communities; and the new product development process. A key finding is the internal inconsistency in the literature regarding the relationship between ACAP and social media constructs. To address this, two alternative research frameworks are proposed, offering theoretical foundations for future studies. Originality/value – To the best of the authors’ knowledge, this paper is the first to comprehensively address the interaction between social media and ACAP by resolving theoretical inconsistencies, clarifying variable roles and proposing frameworks to guide future research. It also offers actionable insights for R&D and innovation managers to strategically leverage social media for acquiring and exploiting external knowledge, thereby enhancing competitive advantage.

GoogLeNet is a pre-trained Convolutional Neural Network (CNN) that allows transfer learning and has achieved high recognition rates in image classification tasks. A Recurrence Plot (RP) is an imaging method that depicts the recurrence of the state space system using coloured points and lines in 2D images. This work contributes to facilitating time series feature extraction by proposing a method that applies the GoogLeNet to time series images obtained with RP. The developed method is tested using simulated time series and selected time series from the M3 competition dataset. The results shows that the transfer learning approach allowed the extraction of business time series features by means of a GoogLeNet fine-tuned using 100 simulated time series. The combination of GoogLeNet and RPs outperforms the alternative and easier combination of GoogLeNet and plots of the time series and support the convenience of the RP transformation step. This application of deep learning techniques to business time series imaging offers opportunity for further developments.

This work aims to figure out a landscape of the scientific and technological production on the Smart City concept. Smart cities have attracted the attention of both academia and industry. However, the state of the art is still unclear and most of the focus has been on literature reviews without looking at technological aspects. To achieve this objective, a scientometric dynamic methodology has been applied on paper and patent data. This methodology combines traditional systematic reviews with the analysis of networks and keywords. These dynamic analyses allow depicting the evolution of Smart City, the research and technological directions, the critical areas, the emerging topics and it reveals the position of the technological evolution with respect to the scientific one. These techniques reveal that while research papers are concerned with social aspect, the technology is mainly focused on specific technical solutions without completely looking at the citizen role. Moreover, patents are not fully embodying sustainability concepts yet.

Purpose: over the last few decades, more emphasis has been placed on those innovations that can reconcile economic, social and environmental goals in order to achieve a "win-win-win" situation. This paper aims to systematise the scientific literature on Sustainable Innovation as a broad field in order to identify the most relevant scholars and their significant contributions as well as existing lines of research. Finally, future research directions are suggested. Design/methodology/approach: a novel methodology, the Systematic Literature Network Analysis, has been applied. By using a dynamic approach to the traditional Systematic Literature Review, the present review investigates the creation, transfer, and development of knowledge throughout the epistemic community of Sustainable Innovation. Findings: starting from a sample of 1,108 articles, the critical assessment of the results detected five main themes: (1) "the role of Regulation, Market and Technology"; (2) "Eco-Innovation determinants and firm specific factors and the debate between corporate environmental performance and corporate financial performance"; (3) "Green innovation and internal and external drivers"; (4) "The strategic determinants of green (non-green) innovation"; (5) "The interplay between policy, regulations and the green innovation". Practical implications: from a practitioner's perspective, this study provides an objective view on the current internal, external drivers and strategic determinants of sustainability-oriented innovations and relevant studies that can guide managers in their decision-making processes and enhance sustainable innovation performance. Originality/value: this study is a first attempt to unveil the evolution of knowledge in the field of sustainable innovation by utilizing bibliometric tools.

Organisational Learning (OL) is essential for the survival of an organisation and has led to a significant amount of conceptual and empirical studies. However, no attempt has yet been made to track the overall evolution of OL literature along with the inter-related concepts of learning organisation and organisational learning orientation. Therefore, the present study attempts to fill this gap and track the interdisciplinary flow of knowledge by applying a structural methodology called Systematic Literature Network Analysis (SLNA). The results reveal four main areas of investigation within the field: i) the fundamentals of OL; ii) OL in relation to managerial and economic variables; iii) management of learning organisation; iv) learning orientation in relation to managerial and economic variables. Furthermore, this review contributes by arranging the findings into a theoretical framework which is termed organisational learning chain. Based on the co-analysis of main themes and key concepts detected, the framework integrates and highlights the factors that influence learning performance in and by organisations. Finally, several further research avenues are discussed, and the benefits of the applied review methodology are highlighted.

Background: The crowding of emergency departments (EDs) is one of the major poor-quality factors for patients. Because of this, measuring ED performance in Healthcare Systems is a difficult but an important task needed to enhance quality and efficiency. Purpose: (i) Development of a tool to observe and evaluate performance measurement, analysing two critical variables (quality and efficiency), verifying the change in performance due to the implementation of a new organizational model; (ii) the implementation of the tool in two EDs with comparable annual volumes of activity in the Italian context. Methods: A literature review on ED performance was conducted in order to identify acknowledged performance measurements used in this context that can be used in the development of a tool for the evaluation of EDs' performance. The goal is to have a matrix that is easily understood and that shows a simple relationship between quality and efficiency. This was possible by setting up a method that translates the ED annual performance data (in this case the data related to year 2018) into a graph with benchmarking purposes, also including an actual situation (AS-IS) view as compared to a TO-BE situation (i.e., before and after an organizational change occurred). Results: Two real EDs were compared and their results depicted; they can be easily related with each other to benchmark healthcare organisations. More precisely, a comparison can be used for two main tasks: identifying different strategic areas and observing the positioning of a health organization at any given moment in time, seeing where it stands among its competitors in a matrix; knowing how to best allocate available resources and where to divert investment. Results show that the tool depicts the situation of EDs, with a clear indication of how performance increases or decreases in the case of AS-IS and TO-BE evaluation, and also offers a quick understanding of the benchmarked EDs' situations. Practice Implications: The results can be shown on a graph that summarises the performance change for the AS-IS versus TO-BE conditions. This can be a useful tool for the ED and for the hospital decision makers, as it allows for an observation of performance by analysing two critical variables: the quality and the efficiency of the service provided. The former represents customer satisfaction, which in this work is the combination of two factors (i.e., appropriateness of assigning the triage code and patient satisfaction), and the latter represents the ED's efficiency in providing emergency care. The tool also helps the organizational changes to be easily evaluated.

Purpose: Lean and agile are essential supply chain management (SCM) strategies that enhance companies' performance. Previous studies have reported the capabilities of different SCM strategies to enhance performance; however, the emergence of Industry 4.0 technologies has bred focus on the possibility of attaining more levels of operational performance. Despite being demonstrated helpful at enabling supply chain (SC) strategies, the literature linking Industry 4.0 with SCM strategies is still in its infancy. Thus, this work investigates the degree to which “Industry 4.0 technologies” enable the implementation of lean and agile practices and subsequently assesses the potential performance implications of integrating Industry 4.0 technologies with the SC operations. Design/methodology/approach: The work employs an exploratory case study approach using empirical data from selected organisations drawn from an Estonian manufacturing cluster and digital solution providing companies. The data collected via interviews were used to assign numerical scores and subsequently aggregated across the five cases for the research variables of interest. The work is crowned with a model grounded on the cross-case analysis to depict which technologies impact each of the lean and agile practices. Findings: The analysis enabled comprehension of the potential impact and level of importance of the main Industry 4.0 technologies on lean and agile practices and ultimately the potential implication on performance. The findings revealed that the technologies have a high impact on the practices. Although the impacts are of varying degrees, the analysis provides means to identify the technologies with the most significant impact on lean and agile SCM and the sets of practices with the greatest likelihood of being enabled by various digital technologies. Practical implications: The work presents various lean and agile practices that practitioners can deploy to operations, alongside the technologies that could support the implementation of the practices towards achieving the various performance measures. Also, it provides some guides for the digital solution providing companies towards understanding the SCM practices that can be improved upon by various digital technologies. This enables them to have more saleable proposals for intending companies who might be sceptical about transiting into the digital operation phase. Originality/value: This is the first attempt to empirically address the connection between Industry 4.0 technologies and the integrated lean and agile strategies despite literature backing of the complementary nature of the two SCM strategies.