The centrality of data quality within data management, and more broadly in business decision-making processes, constitutes an essential prerequisite for the reliability of analyses and, consequently, for the effectiveness of business strategies. The growing complexity and heterogeneity of data flows make data quality management an increasingly critical challenge, aimed at preserving the accuracy and consistency of extracted information. In this context, efficiency and timeliness become fundamental requirements. However, data quality processes are often resource-intensive and require specialized expertise. In this perspective, the adoption of generative artificial intelligence models, particularly Large Language Models (LLMs), opens new opportunities to support data management and quality control activities. This study proposes a conceptual framework for modelling the use of an LLM Agent to assist Data Quality and Application Maintenance teams. The framework is designed to facilitate the analysis of anomalies and malfunctions detected within systems responsible for data quality controls. Furthermore, the agent can suggest a set of technical solutions, specifying the potential impacts on the existing infrastructure and scheduled processes. This approach provides a solid foundation for future applications, promoting more efficient anomaly management and a strategic use of existing technical knowledge.

Recent developments of Generative Artificial Intelligence (GenAI) are profoundly impacting the creative contexts, offering innovative tools that redefine how artistic content is conceived, developed, and delivered. Across visual arts, design, music, and storytelling, GenAI is being embraced for its capacity to accelerate ideation, facilitate rapid prototyping, and democratize creative processes, so allowing both professionals and novices to produce high-quality outcomes. Its algorithmic creativity could augment human imagination and opens new frontiers for experimentation and collaborative creation.
However, while the GenAI tools are being celebrated, its adoption is not without reservations. Creatives express apprehension over issues such as loss of creative autonomy, potential homogenization of artistic outputs, and ethical concerns related to authorship and copyright infringement. The question of trust is pivotal: without transparency in AI processes and assurance over the originality of AI-generated content, users remain skeptical about relying on GenAI systems for meaningful creative work. Furthermore, aesthetic satisfaction plays a critical role, as artists seek not just functional outputs but final works that align with their personal and cultural values.
The study investigates the conceptual foundations underlying GenAI adoption in creative contexts. Existing theoretical frameworks such as the Technology Acceptance Model (TAM) provide useful foundations for examining user attitudes towards new technologies. However, these models originally developed in contexts of general-purpose technologies do not fully capture the emotional, aesthetic, and autonomy-related dimensions that characterize creative practices. As such, this paper critically explores their applicability to GenAI adoption in creative fields and identifies the need for further contextualization. Based on a systematic literature review of peer-reviewed articles sourced from Scopus and from existing AI governance frameworks (e.g. OECD and NIST), the paper identifies a set of constructs—including perceived usefulness, ease of use, trust, creative autonomy, aesthetic satisfaction, and behavioral intention—that can inform the future development of a tailored survey instrument. The relevance of the core constructs to education and artistic production is discussed. The contribution of the study is twofold: it offers an academically rigorous synthesis of current knowledge on GenAI adoption within creative domains and proposes a refined conceptual framework that can inform future empirical studies. By aligning established theoretical models with the distinctive needs of creative practice, the study provides a critical foundation for educators, researchers, and policymakers committed to supporting a responsible, ethical, and inspiring integration of AI technologies in the arts.

The transition from linear to circular manufacturing systems (CMS) is essential for manufacturing firms aiming to enhance sustainability and mitigate resource depletion. Despite clear environmental and economic benefits, the adoption of circular economy (CE) principles within the manufacturing sector remains limited, largely due to significant technological, operational, and organisational barriers. This study addresses these issues by exploring the specific challenges that manufacturing companies face during their transition to CMS and proposes digital technologies to effectively overcome these barriers. Utilising an exploratory, qualitative, single-case study approach, we investigated a European white goods manufacturer implementing a refurbishment centre aimed at establishing circular practices within their laundry appliance segment. Through thematic analysis, we identified three primary challenges: uncertainty regarding the condition of returned appliances due to limited consumer data sharing, insufficient durability and longevity data from laboratory tests of new models, and operational inefficiencies due to inexperience with dismantling and refurbishing processes. To address these challenges, we propose advanced digital solutions leveraging Internet of Things (IoT), Artificial Intelligence (AI), and Augmented Reality (AR) technologies. Specifically, IoT and AI-based systems are recommended for comprehensive product tracking, real-time condition monitoring, predictive maintenance, and informed decision-making, significantly improving data availability and accuracy for refurbishment operations. Additionally, we suggest AR-enhanced workstations to assist workers in dismantling processes, enhancing operational efficiency, reducing error rates, and facilitating knowledge management across diverse product models. Our findings extend the current body of knowledge on CE barriers, particularly in relation to IoT capabilities and consumer data-sharing practices and highlight practical implications for manufacturers seeking effective digital interventions. This research underscores the critical role of technology integration and organisational readiness in achieving successful CMS transitions.

The rapid advancement of digital technologies has opened new possibilities for cultural heritage institutions (CHIs), enabling digitization and AI-supported initiatives that improve preservation, accessibility, and public engagement. However, CHIs often face significant challenges in evaluating and selecting appropriate projects due to fragmented resources, institutional complexity, and existing decision-support frameworks prioritize financial and technical feasibility while neglecting cultural and social dimensions. This study addresses a critical gap by presenting a micro-level decision-support framework specifically designed to guide CHIs in the evaluation of digitization and AI-supported projects. The framework was constructed through a three-stage mixed-method research design that combined a systematic literature review (SLR), focus group discussions, and the Delphi technique. It draws on the expertise of professionals from the European cultural and creative industries, including representatives from CH institutions and ethnic minority groups. Their diverse perspectives ensured that the framework reflects both technical and cultural priorities. The process resulted in a validated set of 43 criteria, grouped into six categories: finance and investment, employment and personnel, market, accessibility, social impact, and cultural heritage object. The framework offers CHIs a comprehensive but context-sensitive tool to guide structured, evidence-based decision-making. It captures both tangible and intangible project dimensions and supports strategic planning that aligns with institutional missions and stakeholder expectations. The study contributes theoretically by operationalizing cultural value and institutional priorities in micro-level evaluation, addressing the limitations of market-oriented models. It also offers practical value by enabling CHIs to navigate trade-offs between innovation, feasibility, and cultural integrity. While grounded in project-level application, the framework also serves as a foundation for the application of multi-criteria decision-making (MCDM) methods and future research on institutional-level decision making. The findings improve CHI’s ability to make informed, inclusive, and forward-looking investment decisions in a rapidly changing digital world.

In this article, we will explore innovation management in such an important sector as tourism, focusing specifically on the hotel industry. Within the hotel industry, innovation has been a major focus for some years now, moving away from the popular phrase that traditionally circulates by word of mouth, “This has always been done this way.” Proof of this is that highly important organizations in the sector such as ITH (Hotel Technology Institute in Spanish) are holding highly interesting events such as the one held in 2020: “Balance between technology and investment, common sense and people, key in ITH Hotel Virtual Innovation Lab”. Because the current situation in the sector is changing, both for the hotelier and the customer, it is essential to be able to compare what has been studied so far with the current reality. In the past, guests would go to a hotel and find things they didn’t have at home: a larger TV, a better mattress, a jacuzzi… this meant that innovation took a backseat to customer attraction. Nowadays, it’s difficult to surprise guests with such basic items that they normally have at home that are just as good or better, so innovation has taken center stage and gained significant importance. We could say without fear of being wrong that today the hotel sector is one of the most interested in innovation in all its aspects (technological, marketing and processes) without a doubt. That’s why we consider it important to conduct a study and see if the reality of the sector is surpassing the academic studies conducted on it. To contrast this reality, it is important to obtain information directly from the most relevant players in the sector and conduct as many interviews as possible.

Building on a previously developed Digital Maturity Model (DMM) tailored for cultural tourism, this paper explores the application of the model in rural tourism contexts. While digital transformation (DT) is widely recognized as a strategic imperative, rural areas often face unique barriers—including limited infrastructure, digital skill gaps, and organizational inertia—that hinder their digital evolution. This study aims to assess the digital maturity of rural tourism operators in selected pilot areas in the Basilicata region, offering insights to guide targeted DT strategies.
The research adopts an empirical approach by applying the seven-dimensional DMM—comprising Strategy, Organization, Culture, Employee, Tourists, Technology, and Operations—to a sample of rural tourism and cultural operators. Data were collected through surveys and interviews conducted within pilot areas engaged in the Tech4You PNRR initiative.
The assessment reveals heterogeneous levels of digital maturity across rural operators. While strengths emerged in cultural orientation and visitor engagement, significant gaps were observed in areas such as strategic planning, technological infrastructure, and operational data use. These findings suggest a need for differentiated support policies and context-sensitive digital transformation roadmaps.
This paper extends the applicability of the DMM to rural tourism ecosystems, demonstrating its relevance beyond urban or institutionalized cultural tourism settings. It contributes empirical evidence to the literature on digital transformation in marginal areas, helping bridge the gap between maturity models and real-world application.
The study provides a diagnostic tool for local authorities, innovation agencies, and tourism stakeholders to map digital readiness, prioritize interventions, and co-design tailored DT strategies in rural contexts. It also opens pathways for replicability in other regions with similar territorial challenges.

This study explores the role of models and tools in supporting innovation processes and digital transformation within cultural tourism ecosystems. It emphasizes the need for a shift for cultural tourism organizations towards digital innovation and innovation processes and highlights the importance of collaborative networks that actively engage stakeholders in the co-creation of smart tourism solutions. The research identifies participatory methodologies, particularly participatory events, as strategic levers to foster innovation and digital awareness in the sector.
A qualitative research design was adopted, combining desk-based analysis of existing literature with a multiple case study methodology. A series of thematic focus groups held in the Basilicata region provided empirical insights into how participatory formats can support digital transformation and innovation in cultural tourism.
The findings reveal key challenges and opportunities for fostering digital transformation and innovation in cultural tourism. The study outlines emerging models, tools, and participatory formats that enhance stakeholder engagement and co-design processes, while also identifying structural barriers and enablers critical to success.
The paper contributes to the literature by systematizing participatory practices as catalysts for digital transformation and innovation in cultural tourism. It offers practical guidelines and raises new questions for future research on innovation dynamics in rural tourism ecosystems.

This study investigates the dynamics of digital transformation in rural cultural tourism. It explores how rural territories can engage with digital innovation through context-specific strategies that enhance cultural heritage, territorial identity, and stakeholder collaboration.
The research adopts a qualitative methodology based on a SWOT analysis, drawing from semi structured interviews, participatory workshops, field observations, and desk research. This approach allows for a critical assessment of internal and external factors influencing digital transformation processes in rural tourism areas.
The analysis highlights a series of structural challenges, including limited digital infrastructure and skills gaps, but also identifies unique opportunities tied to community cohesion, authentic local narratives, and the potential for slow, sustainable tourism models. The findings emphasize the importance of bottom-up approaches and multi-actor engagement in shaping digital strategies that are both place-sensitive and innovation-oriented.
The paper contributes both to literature and to managerial and policy practices by offering a grounded perspective on rural digital transformation, moving beyond generalized frameworks to focus on localized innovation pathways. It positions cultural heritage not as a constraint but as a resource for co-creating digital solutions tailored to rural tourism contexts.

In a fast-changing and hyper-connected business environment, startups are increasingly challenged to innovate, scale efficiently, and remain competitive despite limited internal resources. This paper investigates how digitalisation and open innovation (OI) jointly impact the performance of innovative startups, with a particular focus on how digital technologies enable open innovation processes. To address this, the study adopts a systematic literature review (SLR) methodology, analysing 42 peer-reviewed articles retrieved from the Scopus database. The selected studies span various industries and geographic regions, although the majority are concentrated in developed economies and ICT-intensive sectors. The review identifies a growing interest in the role of technologies such as Artificial Intelligence (AI), Big Data Analytics (BDA), Internet of Things (IoT), Blockchain, and Cloud Computing as key enablers of both inbound (e.g., external knowledge sourcing) and outbound (e.g., licensing, platform participation) open innovation activities. Findings show that while digitalisation and OI are often studied in isolation, few models offer an integrated, startup-specific perspective. Moreover, most existing frameworks focus on financial performance, neglecting sustainable performance metrics such as environmental and social value creation. The analysis highlights several theoretical gaps, including a lack of longitudinal and cross-sectoral studies, and limited exploration of digital open innovation dynamics in early-stage firms. From a theoretical standpoint, the study maps the most frequently adopted frameworks—Resource-Based View (RBV), Dynamic Capabilities Theory (DCT), Knowledge-Based View (KBV), and Open Innovation theory—and proposes a conceptual model linking digital technology adoption, open innovation practices, and dual performance outcomes (financial and sustainable). This model provides a foundation for future empirical testing and theoretical refinement. On the managerial side, the paper offers practical insights for startup founders, innovation managers, and ecosystem developers, suggesting how digital tools can be strategically combined with open innovation practices to enhance agility, reduce costs, and drive long-term value creation. Overall, this study contributes to the literature by clarifying conceptual relationships, identifying key constructs, and outlining directions for future research at the intersection of digital transformation and collaborative innovation in startups.

The concept of Innovation Ecosystem has taken on a central role in corporate innovation strategies and industrial policies, representing a key element for competitiveness and economic growth. Innovation Ecosystems differ from traditional ecosystems due to their emphasis on cross-sector cooperation and the integration of heterogeneous skills, facilitating the alignment of supply and demand for innovation and fostering knowledge dissemination. In this context, startups emerge as key players thanks to their agility, experimentation capabilities, and focus on technological discontinuity.
However, startups face numerous challenges, including a high risk of failure, technological and market uncertainty, and difficulties in accessing financial resources and strategic networks. To overcome these obstacles, they often engage in collaborations with established companies within an Innovation Ecosystem, in line with the Open Innovation paradigm. Despite the growing attention to these ecosystems, the startup perspective remains underexplored in academic literature.
This study aims to analyze the main factors influencing the success or failure of startups in Innovation Ecosystems, with a particular focus on the role of collaborations with large companies, sustainability, and digitalization. To achieve this goal, the research framework is structured into three main phases: (1) a systematic literature review to identify key variables and build a solid theoretical foundation; (2) the design of a questionnaire and a structured interview protocol based on the literature review findings; (3) an empirical analysis conducted through interviews with innovative startups operating in Innovation Ecosystems. The methodological approach combines quantitative and qualitative tools, enabling an in-depth understanding of collaboration dynamics.
The proposed analysis will contribute to expanding knowledge on interactions between startups and established companies, highlighting the necessary conditions for effective collaboration and the strategic role of digitalization and sustainability. The findings will provide valuable insights for both theory and practice, supporting businesses and policymakers in designing more effective and inclusive innovation ecosystems.

In this paper, we rely on multiple correspondence analysis (MCA) to explore a complex ecosystem of Italian innovative enterprises. In this respect, we analyze more than 11.000 innovative SMEs and start-ups. We find that the Italian innovation ecosystem is mainly structured along two dimensions. The first and most significant dimension emphasizes the opposition between structured institutional elements that are typical of SMEs and leaner, more flexible arrangements closer to the start-ups. The second axis is that of social inclusiveness and innovation as opposed to sociocultural sedimentation, which is more representative of well-established SMEs in the industrial/artisanal sector. An additional analysis of concentration ellipses revealed that start-ups are prone to rely on higher female representation and are closer to the service sector category. If we treat the latter as a proxy category for incubators, which were all designated as services, then the unfortunate conclusion is that Italian innovative enterprises tend to lose their social innovativeness aspects, which include but are not limited to social inclusivity, once past the start-up phase. The ramifications of these dynamics are yet to be sufficiently understood in relation to the broader ability of enterprises to innovate.

This paper investigates the factors that shape the resilience of entrepreneurial ecosystems (EEs) in the context of long-term structural and technological change. Drawing on a longitudinal dataset from the Global Entrepreneurship Monitor (GEM) for Switzerland (2003–2023), we examine how ecosystem diversity, coherence, and digitalization influence adaptive capacity in the face of external shocks. Building on recent literature, we conceptualize ecosystem resilience as the ability to sustain early-stage entrepreneurial activity over time, and explore whether digitalization contributes to resilience outcomes. We construct composite indexes for diversity, coherence, and digitalization, and estimate a series of linear regression models including interaction effects. Our results confirm that diversity has a significant positive impact on resilience, and that digitalization contributes independently and strongly to resilience as well. However, we find no significant interaction between diversity and coherence, suggesting that alignment and diversity do not always produce synergistic effects. Notably, we identify a negative and statistically significant interaction between coherence and digitalization, indicating that in ecosystems with high institutional alignment, the use of digital tools may be associated with reduced flexibility and adaptability. These findings contribute to the emerging body of research on entrepreneurial ecosystem resilience by introducing digital infrastructure as a dynamic moderating variable. The study also provides one of the few longitudinal assessments of ecosystem resilience in a European context, offering new insights into the interplay between diversity, institutional alignment, and technological capacity.
We discuss the implications for theory, highlighting the conditional nature of resilience mechanisms and the need to account for ecosystem maturity and saturation effects. For policymakers, the results suggest that coherence-building and digitalization strategies should not be treated as universally beneficial, especially in already well-structured ecosystems. Instead, interventions should aim to balance structure with openness, and stability with experimentation, in order to enhance long-term ecosystem resilience.

Start-ups represent one of the main sources of innovation and, consequently, national competitiveness. However, due to their limited size, they face several challenges, such as the scarcity of technical and financial resources, which significantly constrain their innovation capacity. To overcome these challenges, start-ups should engage in the adoption of open innovation (OI) processes, which enable them to collaborate with external organizations and exchange resources and knowledge. The effectiveness of such processes is amplified when start-ups are embedded in solid innovation ecosystems. Among the various actors that compose these ecosystems, innovation intermediaries — such as business incubators (BIs) — play a key role. BIs, through targeted networking services, enable incubated start-ups to more easily develop OI collaborations, either with one another or with external organizations. This study aims to explore the role of BIs as OI intermediaries — a topic that has received limited attention in the literature — by identifying the main operational strategies implemented to foster the openness of their incubated start-ups. To achieve this objective, a case study was conducted on the incubator of the University of Calabria (UniCal), “TechNest”. The findings reveal a strong commitment by TechNest to supporting the development of both internal and external innovation networks. However, some limitations were observed in terms of openness among start-ups operating within the academic context. This research provides valuable implications. On a theoretical level, it contributes to the limited body of literature on the topic. On a practical level, it highlights the importance for incubator managers to integrate an OI perspective into their incubation programs, while also emphasizing the need for managers of incubated start-ups to open their innovation processes to external collaborations. At the same time, policymakers should work to improve innovation policies, providing greater support to incubators and, more generally, to local and national innovation ecosystems.

Entrepreneurial ecosystems are increasingly seen as complex, dynamic environments requiring effective coordination by ecosystem orchestrators. While prior research has focused on structural and institutional elements, little is known about the cognitive processes guiding orchestrators’ decisions. This study addresses this gap by examining how mental models influence ecosystem performance. The study analyzes three key attributes of mental models: complexity, centrality, and accuracy. Data were collected through a simulation environment where eleven teams played the role of orchestrators across ten rounds of strategic decision-making. Using a fuzzy-set Qualitative Comparative Analysis (fsQCA), the study identifies two causal configurations sufficient for high performance: one based on high centrality and the other on high complexity, both combined with low accuracy. The findings suggest that orchestrators can adopt different cognitive strategies to achieve strong outcomes, challenging the assumed importance of accuracy. The study contributes to the literature on entrepreneurial ecosystems and managerial cognition, offering practical insights for those aiming to enhance ecosystem performance through cognitive and strategic design.

The emergence of Digital Innovation Ecosystems (DIEs) is reshaping how innovation is generated, diffused, and scaled across sectors, especially within highly regulated domains such as pharmaceutical logistics. These ecosystems bring together startups, corporations, research institutions, and intermediaries to co-create digital solutions. However, such collaborations are inherently asymmetric—startups and corporates differ vastly in resources, legitimacy, and influence—posing challenges related to power imbalances, cultural misalignments, and governance.
This paper investigates how asymmetric collaborations are orchestrated within DIEs, drawing on a single in-depth case study: Logi-farma, a digital platform project aiming to optimize pharmaceutical distribution through AI, automation, blockchain, and data analytics. The case involves a large ICT corporation, an innovative SME, a logistics specialist, and a university research center. Guided by a conceptual framework derived from a prior systematic literature review on asymmetric collaborations, this study explores how stakeholders with diverging capabilities and motivations coordinate innovation efforts and mitigate power asymmetries.
Using semi-structured interviews, document analysis, and comparative assessments of digital innovation models, we investigate the governance mechanisms, collaboration dynamics, and innovation outcomes within the project. Findings are structured through a 6W-based framework—exploring who the actors are, how they collaborate and integrate technology, why they engage, and where/when the processes unfold. The analysis reveals that while startups benefit from legitimacy and scale, corporates leverage agility and niche expertise. However, unresolved asymmetries around data ownership, IP, and decision-making risk undermining trust and long-term viability.
This paper contributes to both theory and practice. Theoretically, it advances open innovation and ecosystem literature by integrating asymmetry as a structural component and proposing a novel conceptual lens for analyzing goal-oriented, multi-actor innovation networks. Practically, it offers guidance for ecosystem orchestrators, policymakers, and innovation managers on how to design inclusive governance structures that support fair value co-creation. The case study illustrates how digital health innovation can be scaled through collaborative orchestration, provided that power differentials are addressed and trust is actively managed. Ultimately, this work underscores the potential of orchestrated asymmetric collaborations to drive digital transformation and sustainability in complex, high-stakes sectors.

The healthcare sector is characterized by intense emotional, cognitive, and physical demands that expose professionals to chronic stress, with significant consequences for their well-being and performance. Despite growing scholarly attention to stress in healthcare, little is known about the specific coping strategies that professionals employ and the organizational factors that facilitate or hinder these approaches. This study addresses this gap by examining how healthcare workers navigate daily stressors and how organizational structures can support or undermine their coping mechanisms.
Based on a qualitative research design, the study involved 41 semi-structured interviews with healthcare professionals—including doctors, nurses, psychologists, and other staff—operating in various settings. The findings reveal that organizational support plays a crucial mediating role between job demands and perceived job control. In particular, participants who reported supportive leadership, accessible resources, and open communication channels were better equipped to handle high workloads and emotional fatigue, even in contexts with limited formal autonomy.
The concept of perceived control emerges as a central theme, expanding traditional models of occupational stress. The study demonstrates that the subjective perception of being able to influence one’s work environment—fostered by empathetic leadership and inclusive organizational culture—can significantly enhance resilience and reduce burnout risk. Moreover, the diversity of professional experiences in the sample underscores the importance of tailored organizational strategies that reflect the unique stressors and coping needs of different roles within the healthcare system.
By integrating insights from organizational behavior, human resource management, and health psychology, this research contributes to the development of more resilient and supportive healthcare organizations. The findings offer practical recommendations for policy-makers and managers seeking to promote employee well-being, improve job satisfaction, and sustain innovation in complex healthcare environments, particularly in the face of ongoing global health challenges.

Workplace safety is increasingly recognized not only as a matter of regulatory compliance but as a collective, knowledge-based infrastructure that must be cultivated early and systemically. In response to this challenge, the “Let’s Play 81!” project introduces a school-based, game-driven educational pathway aimed at promoting occupational safety awareness among students aged 8 to 13. Developed in alignment with Italy’s updated safety legislation (Legislative Decree 81/2008, reform 2024), the project reframes prevention as a civic competence rooted in shared knowledge, care, and responsibility.
The initiative was piloted in four public schools in central Italy, involving 198 students, 20 teachers, and 4 certified safety trainers. It employs analog games—developed and validated by occupational health experts—as tools to activate learning through play. Three distinct games simulate safety challenges in fictional yet relatable settings. These tools enable students to interact with roles, rules, and consequences, encouraging reflection, dialogue, and collective problem-solving.
The study adopts a mixed-methods approach. Quantitatively, it measures knowledge acquisition using a pre/post quiz (81Questionnaire), revealing a significant improvement in the intervention group (+4.43 points on average, p < 0.001). Qualitative data from teacher and trainer feedback underscore increased engagement, emotional involvement, and transversal learning outcomes (e.g., collaboration, attention, civic sense). From a knowledge management perspective, the project demonstrates how structured play can serve as a conduit for transmitting tacit and explicit knowledge in early education contexts. It also fosters interinstitutional collaboration among schools, Universities, and training bodies, suggesting a model for distributed governance in prevention. “Let’s Play 81!” offers a replicable framework to embed safety culture through experiential, inclusive, and cognitively rich learning. It contributes to the broader discourse on how public value can be co-generated through educational innovation and how knowledge-intensive processes—like risk awareness and prevention—can be activated far beyond the boundaries of formal workplaces.

Digital transformation, board characteristics, and environmental performance are increasingly significant in the realm of corporate sustainability. Numerous scholars assert that digital transformation can serve as a powerful catalyst for sustainable corporate development, delivering substantial benefits to both businesses and society. Digital transformation refers to the process through which companies evolve from traditional industrial stages to the Industry 5.0 paradigm, which integrates technological innovation with human-centric approaches.
According to the stakeholder theory, firms operate within an interconnected system encompassing economic, social, environmental and political dimensions, and enhancing corporate profitability has become an essential requirement for stakeholders. In this context, digital transformation can substantially boost corporate productivity and contribute to achieving sustainable development goals, thereby acting as a primary factor through which stakeholders can compel firms to initiate transformation processes.
Furthermore, companies are increasingly subjected to pressures from stakeholders who are placing greater emphasis on environmental issues, compelling them to adopt proactive environmental governance strategies. However, despite the extensive development of literature on digital transformation and environmental performance, studies analyzing the potential moderating role of board characteristics remain limited. This paper aims to bridge this gap by exploring the relationship between digital transformation and environmental performance, considering the specificities of board characteristics.
The existing empirical literature often employs textual analysis to quantify the extent and quality of digital transformation. Similarly, in this study, the construction of the digital transformation indicator is achieved through keywords selected based on prior literature, including: big data, informatization, intelligence, robotics, Internet of Things, blockchain, automation, digitization, and cloud computing.
Based on this method to measure the digital transformation efforts, we investigated the potential moderating effect of board gender diversity on the relationship between digitalization and corporate environmental performance, using data from Italian publicly listed companies for the year 2023.
The results of the empirical analysis indicate that 1) digital transformation has a positive and significant impact on corporate environmental performance, and 2) that impact of digital transformation on environmental performance is reinforced by a higher presence of female directors on corporate boards.
These findings provide potentially valuable insights to a diverse audience. Firstly, to companies engaged in digitalization processes. Secondly, to developing countries still in the Industry 3.0 or Industry 4.0 phase. Thirdly, to governments of developed countries, to promote national technological growth, monitor companies, and establish appropriate regulatory frameworks for the digital era.

In the current economic and business context, Artificial Intelligence (AI) becomes a debated topic among academic and practitioners. Although the specific literature has outlined the relationship between top management and digitalization, sustainability topics remain less scrutinized, particularly concerning AI. With these premises, this study intends to investigate whether sustainable corporate governance (SCG) affects disclosure about AI.
To test the research hypothesis, we adopted a mixed approach (i.e., content analysis, structural equation modelling, ordinary least squares and lasso regression) working on a sample of 104 Italian listed companies.
Firms with higher levels of SCG scores display a greater impact on AI disclosure, suggesting that sustainable boards are demonstrating greater integration of AI in their disclosures as well as in their decision-making processes.
Although the literature is becoming increasingly interested in sustainable corporate governance issues, research is still lacking. To the best of the authors’ knowledge, no study has previously investigated possible relationships between sustainable governance and the digitization process, especially with regard to the implications of AI.
Our findings provide insightful contributions to SCG- and AI-related literature, enriching the UET framework. In doing this, this study provides important implications for managers – especially at a strategic level – and policymakers.
The research is not free from limitations. First of all, AI disclosure is assumed to be representative of effective AI implementation, leaving room for doubt as a level of AI disclosure does not guarantee the same level of actual integration. Furthermore, it falls into a single-year analysis (2023) and Country (Italy). Therefore, future studies, survey-based, could increase the accuracy of the AI index and expand the analysis over time as well as to other countries.

The present research aims to explore how digital transformation, when integrated within Public-Private Partnerships (PPPs) and social enterprise models, can foster inclusive, innovative, and sustainable approaches to cultural heritage governance. Anchored in the case study of JustMO’, a cultural cooperative operating in Sepino (Molise, Italy), the study investigates how multi-stakeholder collaboration can activate new value creation processes in the cultural sector.
Adopting the SoPHIA evaluation model as a holistic analytical framework, the study examines the cultural, social, educational, and economic impacts of digitally supported heritage initiatives not only to enhance visitor experience and educational outreach but also to reinforce place identity and community ownership.
The analysis emphasizes the strategic role of Special Public-Private Partnerships (PSPPs) in enabling cross-sector collaboration, with social enterprises positioned as key orchestrators of digital ecosystems. These hybrid actors bridge institutional boundaries, channel public and private resources, and promote co-creation through participatory design and open digital infrastructures.
From a theoretical perspective, the paper contributes to current debates on PPPs by proposing an expanded view of social enterprises as drivers of digitally enabled cultural innovation. Ultimately, the study provides insights for cultural managers, policymakers, and scholars seeking to align heritage valorization with sustainability objectives and place-based development strategies.