The increasing integration of digital technologies (DT)—such as artificial intelligence, big data, and extended reality—is transforming the domain of academic entrepreneurship. Despite the growing interest in digital academic entrepreneurship, extant literature rarely distinguishes the unique institutional challenges faced by student entrepreneurs, whose ventures are typically less resource-intensive, more agile, and deeply embedded in digitally mediated learning environments. Moreover, while studies acknowledge the transformative potential of DT, few have examined their dual interaction with formal and informal university mechanisms, especially from a comparative perspective across institutional ecosystems. Finally, existing frameworks often overlook how students appropriate digital tools and platforms to navigate institutional constraints, thus underestimating student agency in shaping entrepreneurial outcomes in the digital age. This study addresses that gap by investigating how formal and informal university-based mechanisms influence the entrepreneurial motivations and capabilities of student founders in digitally evolving environments.
Grounded in the conceptual frameworks of Rippa and Secundo (2019) and Guerrero and Urbano (2012), the study adopts a qualitative, comparative case-study approach. Six student-led digital startups were analysed across two entrepreneurial universities—University of Naples Federico II (Italy) and Universitat Autònoma de Barcelona (Spain)—using in-depth interviews and documentary analysis. Findings reveal that while formal structures such as entrepreneurship education and technology transfer systems are widely available, they often lack practical alignment with the needs of digital ventures. Informal factors—like cultural perceptions of entrepreneurship, experiential learning practices, and exposure to role models—also play a crucial role, yet their effectiveness varies across institutional contexts.
The study advances two key propositions: first, that universities providing access to advanced digital skills and specialised technical resources are more likely to foster the successful development of digital startups; and second, that institutions facilitating access to online educational resources and entrepreneurial networks significantly enhance the success potential of student-led ventures. These findings demonstrate how DT reshape the interplay between institutional structures and entrepreneurial behaviour, offering theoretical contributions to digital academic entrepreneurship and practical insights for higher education institutions aiming to cultivate inclusive and future-ready innovation ecosystems.

The intersection of sustainability, inclusion, and entrepreneurship is increasingly recognised as a strategic priority for contemporary businesses and societies. Among underserved groups, people with disabilities (PwDs) present both a significant entrepreneurial potential and unique barriers to business creation and operation. While self-employment offers a promising pathway towards economic inclusion for PwDs, research into the specific mechanisms enabling this form of disadvantage entrepreneurship remains fragmented and under-theorised (Klangboonkrong and Baines, 2022; Bhardwaj et al., 2023). This paper critically reviews the business and management literature to examine how emerging digital technologies can act as affordances facilitating entrepreneurial activity among PwDs.
Drawing upon affordance theory (Gibson, 1979; Leonardi, 2011), this study employs a qualitative, problematising literature review methodology (Alvesson and Sandberg, 2011, 2020), sourcing peer-reviewed articles across entrepreneurship, business, management, and disability studies. A theoretical framework is developed by synthesising the findings, identifying four key technological affordances: communication and interaction, business creation and operation, learning and capability development, and community and identity formation.
The analysis demonstrates that digital technologies are not neutral enablers but dynamic socio-material actors whose affordances depend on user capability and institutional context. It reveals how digital solutions can meaningfully reduce systemic barriers, enhance market access, and foster entrepreneurial identity among PwDs. This study contributes to extending the understanding of inclusive entrepreneurship within a digital economy, proposing that inclusive technology strategies must be embedded in policy and education, digital platform design, and business support services.
The paper advocates for future empirical research to validate and refine the proposed framework across diverse PwD populations and socio-economic contexts. It emphasises the need to account for intersectional factors and to evaluate the long-term sustainability of technology-enabled ventures. Ultimately, enabling entrepreneurs with disabilities through technology is not merely an ethical imperative but a strategic investment in unlocking innovation, diversity, and sustainable growth.

The advent of the Fourth Industrial Revolution has marked a profound shift in the global economy, driven by the integration of artificial intelligence (AI), the Internet of Things, and quantum computing. AI stands out as a transformative force, profoundly reshaping industries, labour markets, and economic interactions. Also, AI’s widespread implementation generates both opportunities and disruptions, with forecasts of the displacement of millions of jobs and the creation of new roles. However, these transformations vary significantly across regions and demographics, with countries like Italy facing unique challenges, including a substantial digital skills gap among the working population. Despite the growing interest in AI’s technological and economic implications, limited research has investigated how specifically entrepreneurs adopt and utilise AI technologies in their daily business practices. While existing literature has focused predominantly on sector-specific applications—most notably in healthcare—entrepreneurship as a dynamic and multifaceted phenomenon remains underexplored in this context. Indeed, our study investigates how entrepreneurs adopt AI into their professional routines, the digital competencies they display during this process, and the learning ecosystems that support their acquisition of AI-related knowledge. To reach our research aim, we adopt a qualitative approach, conducting semi-structured interviews with a sample of entrepreneurs operating in Southern Italy. Through thematic analysis, we aim to highlight the existing patterns of AI adoption and the support mechanisms within the entrepreneurial ecosystems. The findings contribute to a deeper understanding of the AI adoption for entrepreneurs and their main digital competencies gap, offering theoretical insights and practical implications for policymakers, educators, and innovation stakeholders.

The pursuit of sustainable and accelerated growth in small- and medium-sized enterprises (SMEs) can be effectively promoted through the application of Growth Hacking (GH) strategies. Improving the performance of GH practices within SMEs has therefore emerged as a critical objective for both practitioners and researchers. Drawing on the theoretical foundations of the Technology-Organization-Environment (TOE) framework, this article proposes an integrated analytical model to explore the determinants of GH performance in SMEs. Based on a sample of SMEs actively engaged in GH initiatives, the research will employ fuzzy-set qualitative comparative analysis (fsQCA) to examine the configurational relationships between technological, organizational, and environmental factors that influence GH outcomes. It is expected that: (1) no single condition will be sufficient on its own to achieve high GH performance; (2) multiple and equally effective combinations of internal and external factors will lead to successful outcomes, supporting the principle of equifinality; and (3) key technological capabilities, such as digital transformation and data analytics, along with organizational adaptability and responsiveness to environmental dynamism, will emerge as critical elements in successful configurations. Furthermore, relying solely on technology adoption or external market conditions may prove insufficient to maximize GH performance without appropriate organizational adaptation. These findings enrich the current understanding of the complex mechanisms influencing GH performance and offer practical insights for SMEs wishing to design more effective and resource-efficient growth strategies.
Overall, this research is expected to make a threefold contribution. First, it enriches the theoretical foundations of GH research by applying and extending the TOE framework in a configurational context. Second, it advances methodological practice by employing fsQCA to uncover complex causal relationships often missed by traditional methods. Third, it provides actionable insights for practitioners and policymakers by identifying strategic pathways to optimize GH practices according to different organizational contexts and resource profiles.

This paper explores how AI startups articulate their value propositions—a critical element in defining and communicating value to customers. AI startups, in fact, struggle to align their technological capabilities with real market needs. Drawing on an exploratory multiple-case study of ten Italian AI startups, this research tries to investigate emerging patterns and main challenges AI startups face in articulating the value proposition. Preliminary findings reveal a fragmented landscape: while some startups adopt detailed use cases and visuals to support their claims, others rely on minimal communication and invite direct contact. Value propositions often emphasize efficiency and cost savings but lack quantification and substantiation. The study highlights the tension between technological sophistication and market clarity, especially in cross-industry applications. By focusing on how AI startups construct their value propositions, this research contributes to both AI entrepreneurship literature and broader discussions on value proposition strategy in emerging, high-tech markets.

Startups’ success is strongly influenced by the capabilities, traits, and dynamics of their founding teams. While the role of co-founders in shaping venture outcomes is well established in entrepreneurship literature, little is known about how they are selected in contexts where founding teams are externally assembled, such as within venture studios. Venture studios represent a distinct form of new venture creation (NVC), where organizations (rather than individuals) initiate and structure the entrepreneurial process. Central to this model is the strategic recruitment of external co-founders who are expected to lead ventures they did not originate. The goal of this paper is to investigate how co-founder selection processes are designed and implemented within venture studios, with a focus on the underlying decision criteria and timing strategies adopted in practice.
This research adopts a qualitative, exploratory design based on multi-case illustrative studies of three European venture studios: Rocket Internet, Hexa, and Mamazen. Findings reveal that the co-founder search in venture studios is a deliberate strategic activity. Rather than being recruited solely for executional tasks, co-founders are selected for their entrepreneurial mindset, risk appetite, and capacity to take full ownership of the venture. Venture Studios do not hire CEOs but rather recruit founder-like individuals to lead ventures alongside them, offering shared equity and full operational responsibility from day one. This inversion of traditional entrepreneurial logic positions venture builders as orchestrators of resources and talent, aligning with Gartner’s (1985) view of entrepreneurship as an organizing activity and the Resource-Based View’s emphasis on leveraging human capital.

Enterprise architecture (EA) is a fundamental framework for aligning technology, processes, and information systems with organizational strategy. In the context of knowledge assets and artificial intelligence (AI), EA provides the necessary structure for effective knowledge management and AI integration. However, traditional EA models face limitations in handling dynamic knowledge flows and AI-driven insights. This summary explores EA’s role in managing knowledge, the impact of AI on knowledge assets, and necessary modifications to improve AI integration.
EA plays a crucial role in structuring and governing knowledge within organizations. Frameworks like TOGAF and Zachman facilitate the creation of repositories, workflows, and governance structures to optimize knowledge storage, retrieval, and dissemination. In AI-driven organizations, EA ensures that AI initiatives align with knowledge management strategies, preventing disruptions while enhancing decision-making capabilities.
Knowledge serves as both an input and output in AI systems. High-quality, structured data is essential for training AI models, while AI-generated insights contribute to organizational knowledge. However, poorly curated or siloed knowledge assets can lead to biased models and unreliable results. Enterprise architects must ensure the integrity, accessibility, and interoperability of knowledge assets.
Conventional EA models struggle with:
• A lack of flexible standards for data pipelines, making it difficult to integrate AI-driven DataOps and MLOps.
• Siloed architectures that limit knowledge-sharing and AI effectiveness.
• Static frameworks that do not support real-time knowledge processing.
To enhance AI integration, organizations should:
• Adopt modular, dynamic EA metamodels supporting microservices and AI scalability.
• Implement knowledge-centric frameworks incorporating semantic models and ontologies.
• Integrate DataOps and MLOps pipelines to facilitate continuous AI model refinement.
• Foster a knowledge-sharing culture through training and transparent governance.
By evolving EA frameworks and fostering a collaborative organizational culture, businesses can optimize knowledge management and AI utilization for sustained performance.

Financial digitalisation represents a systemic transformation that affects the entire business lifecycle, emphasising trust, transparency, sustainability, and innovation. Digital tools and platforms, such as crowdfunding and online peer-to-peer lending, increase access to credit and mitigate entry barriers, particularly for startups and small and medium sized enterprises. New technologies, including blockchain and big data, reduce information asymmetries, improve risk assessment, and strengthen stakeholder trust. The transparency of these platforms, associated with the use of reputational signals (for instance credit ratings and reviews), plays a pivotal role in attracting investors and optimizing capital allocation. The democratisation of access to finance supports innovative business models that are not just profit-driven but also oriented towards social and environmental value.
In this context, our research aims to systematically conceptualise digital finance tools, their specific benefits and challenges. The integration of advanced digital technologies into financial services allows greater access to lending resources and innovative funding models. Moreover, several issues and trends emerge, such as, the regulatory uncertainty, the data quality for privacy and cybersecurity, increasing use of AI to customise financial services and risk assessment. Specifically, our study presents a detailed analysis of the state of the art on the connections between digital finance and entrepreneurship, focusing on credit rating in the digital context. In addition, it also provides propositions through which firms can gain competitive advantage and highlights the democratization of credit and financial inclusion, made possible by reducing geographical and socio-economic barriers. Several implications emerge from a managerial point of view and from a theoretical perspective.

In an increasingly digitalised society, Artificial Intelligence (AI) is gaining prominence as a key driver of business innovation and competitiveness. While much research has focused on AI adoption in large enterprises, fewer studies have explored its integration within small and medium-sized enterprises (SMEs), especially in regions with specific socio-economic contexts. This study investigates the awareness, perceptions, and adoption of AI technologies among SMEs in Sicily, a region in southern Italy, characterised by unique economic and organisational dynamics. Adopting a mixed-methods approach, the research combines qualitative insights from in-depth interviews with entrepreneurs from both digital and non-digital sectors, and a large-scale quantitative survey targeting over 2.000 Sicilian SMEs. The methodological framework is structured in sequential phases, where the qualitative component plays a foundational role in informing and shaping the subsequent quantitative investigation. The qualitative findings reveal significant disparities in AI awareness and implementation between sectors, highlighting both enablers and barriers such as digital maturity, organizational culture, training needs, and resistance to change. These insights informed the development of a structured questionnaire to capture broader trends in AI readiness, perceived benefits, and challenges. The study contributes to the literature on digital transformation in SMEs by applying the Technology–Organization–Environment (TOE) framework to a specific regional context, offering both theoretical insights and practical recommendations for policymakers, training institutions, and business leaders seeking to foster inclusive AI adoption.

The increasing integration of Artificial Intelligence (AI) in the advertising industry is opening up both promising opportunities and new challenges for brands leveraging social media to promote their offerings. The rise of Generative AI (gen-AI) is reshaping how advertising content is developed. Yet, while the benefits of creative automation are evident, little is known about how disclosing AI involvement influences consumer perceptions and attitudes toward advertisements. This research investigates the effects of openly stating the use of AI in social media advertising on how consumers perceive and respond to content. Results of two experimental studies show that transparency regarding AI use significantly boosts perceived advertising credibility and enhances comprehension of the advertising message. These findings indicate that consumers value transparency in AI-generated content. The study offers practical implications for marketing professionals and underlines the importance of further research into the ethical and regulatory dimensions of AI use in advertising.

This study examines the intersection of digital transformation (DT) and business model innovation (BMI) within traditional “Made in Italy” sectors, such as Food & Wine, Fashion & Clothing, Home & Furnishings, and Automation. While these industries are renowned for their cultural heritage, they face the challenge of integrating digital technologies to remain competitive without losing their identity. The research explores how Italian firms in these sectors are navigating the balance between embracing digital innovation, particularly within the framework of Industry 5.0, and preserving traditional values. Industry 5.0, with its emphasis on human-centered innovation and sustainable practices, provides a lens through which to understand the evolving relationship between digital technologies and traditional craftsmanship. Through a qualitative multiple case study approach, this study aims to uncover how digital technologies, aligned with Industry 5.0 principles, are reshaping business models.

The aim of this work is to investigate how the academic literature has addressed the relationship between industrial districts and female entrepreneurship. This relationship is particularly relevant since industrial districts are widely recognized as dynamic environments that foster innovation and business growth, especially for small and medium-sized enterprises (SMEs). The review seeks to identify the main areas of analysis that have emerged in recent years and to explore future research directions related to the role of territorial ecosystems in supporting women-led SMEs.
This study adopts a structured literature review (SLR) methodology to systematically analyze the scientific contributions published between 2008 and 2025. The review was conducted using the SCOPUS database. Each contribution was manually classified according to three dimensions: research focus, methodology used, and geographical area of the authors. This analytical framework allowed for the identification of recurring patterns and theoretical gaps.
The findings reveal that most studies focus on the structural and cultural barriers that female entrepreneurs face, even within cooperative environments such as industrial districts. These include limited access to credit, gender stereotypes, family responsibilities and weak support networks. A smaller body of literature highlights the strategic role of women’s human capital, including leadership, training, and innovation capacity, in enhancing the competitiveness of district-based SMEs. Only a few studies explicitly explore how industrial districts can act as enabling ecosystems for female entrepreneurship. From a methodological standpoint, the literature is dominated by quantitative research, while qualitative studies remain limited but offer valuable insights into personal experiences and informal networks. In terms of geographical distribution, most contributions come from Asia and Southern Europe, reflecting both emerging interest in inclusive entrepreneurship and the historical importance of district models in countries such as Italy and Spain.
This study contributes to the literature by providing a comprehensive and up-to-date mapping of the intersection between industrial districts and female entrepreneurship. It highlights the need for more inclusive district governance and calls for future research using qualitative and mixed-method approaches to better understand the lived experiences of women entrepreneurs and the real impact of local production systems.

Digital transformation is reshaping how public administrations operate, with artificial intelligence and emerging technologies playing a growing role in the management and delivery of public services. The National Recovery and Resilience Plan (NRRP) offers a strategic opportunity to modernize the Italian Public Administration (PA) and to foster more equitable and inclusive access to digital resources. However, administrative digitalization alone does not automatically ensure the overcoming of gender disparities. Without deliberate inclusion strategies, technological innovations risk reinforcing existing inequalities. This study analyzes the extent to which the NRRP, specifically through Mission 1, Component 1 (M1C1), has integrated gender equity objectives into PA digitalization initiatives.
Adopting a qualitative content analysis (QCA) approach, this research examines a sample of ten Public Calls for Proposals issued by the Presidency of the Council of Ministers – Department for Digital Transformation (PCM-DTD) portal and manually coded based on two analytical dimensions: (1) compliance with NRRP horizontal principles, and (2) adherence to EU legal obligations on gender equality. Special attention was paid to the use of gender-aware language, objectives, and evaluation mechanisms.
The analysis reveals that all ten calls formally acknowledge gender equality in line with the NRRP’s horizontal principles. However, such references are typically generic and are not translated into concrete requirements or measurable criteria. The reviewed calls lack any form of operationalization, such as gender-disaggregated indicators or structured evaluation mechanisms. Furthermore, binding EU legal provisions on gender equality are merely mentioned, without detailed elaboration or integration into project evaluation frameworks. This superficial treatment limits the enforceability of equity commitments and reflects a broader institutional gap between legal mandates and their practical implementation in the digitalization of the public sector.
This study offers a novel contribution to the literature on public sector innovation by introducing a gender-sensitive perspective into the analysis of digital transformation policies. It critically reflects on the risks of procedural formalism and emphasizes the need to embed gender equality principles more deeply into digital public investments. The findings provide actionable insights for policymakers aiming to leverage technological innovation as a true vector for social inclusion and equity.
The study is limited by its qualitative nature and the small sample size focused solely on Italian cases. Moreover, the analysis is restricted to document-based data without empirical validation through project outcomes or stakeholder feedback. Future research should integrate quantitative measures and fieldwork to assess the real-world impact of digital transformation initiatives on gender inclusion and explore comparative studies across different EU contexts.

Throughout history, women have played an active role in entrepreneurship, although their participation has often been invisibilized or restricted by social and legal norms. Today, digitalization and new technologies present significant opportunities to expand women’s participation in entrepreneurial activities. However, they can also intensify existing challenges or generate new ones. In this context, it becomes necessary to analyze in depth how digitalization impacts on the specific opportunities and challenges faced by women entrepreneurs. The objective of this paper is to analyze the intersection in research between female entrepreneurship and digitalization. To do so, a comprehensive review of 171 scientific articles published in Web of Science (WoS) between 2010 and 2025 was conducted. The results report the main references in the literature on the nexus between female entrepreneurship and digitization: countries (China, USA, India and the UK), authors (McAdam, Maura from Dublin City University and Kelly, Grainne from Queens University Belfast), papers (Pergelova et al., 2019; McAdam et al., 2020; Ughetto et al., 2020), journals (International Journal of Gender and Entrepreneurship and Small Business Economics). The co-word analysis allowed us to identify seven main thematic fronts: (1) social networks, (2) financing, (3) Covid-19, (4) competitive advantage and internationalization, (5) entrepreneurship ecosystems, (6) education, and (7) miscellaneous topics. Each of these fronts was characterized in terms of the opportunities and challenges posed by digital transformation for female entrepreneurship . The results are of interest to researchers concerned with women’s entrepreneurship, policy makers charged with fostering gender-responsive entrepreneurship, and women entrepreneurs as they seek to seize the opportunities and circumvent the challenges posed by digital technologies.

This study presents a Structured Literature Review (SLR) aimed to explore a relationship between Artificial Intelligence (AI) and Gender equality, with a particular focus on the historical developments of this topic and the identification of future research prospectives.
AI is widely regarded as a transformative force with the capacity to reshape numerous dimensions of global society. While its long-term effects on economic system remain subject to debate, the labor market is already emerging as a critical area of impact. Moreover, AI holds the potential to enhance efficiency and productivity, but it simultaneously raises concerns about job displacement, access to opportunities and, exacerbation of existing social inequality.
In this context, our objective is to examine how academic literature has responded to the emergence of AI, particularly analyzing the extent to which gender-related themes are integrated into discussions of AI development and application.
To achieve this, the review is supported by a bibliometric analysis, conducted using the Biblioshny package in R-Studio, were performed on a sample of 290 academic documents (Articles and Book Chapters) available on Scopus and published from 2015 to 2025. The dataset was selected through a rigorous and validated screening process to ensure relevance and academic quality. The analysis is structured around four main dimensions: the annual evolution of publications, the identification and frequency of emerging keywords and trending topics, and the geographical distribution of scholarly contributions.
The originality of this research lies in its methodological approach and use of bibliometric analysis, to explore a broad spectrum of academic publications over a significant period, serving as a potential base for further insights and future studies.

This paper seeks to advance understanding of the persistent gap between the growing societal and organizational attention to Diversity, Equity, and Inclusion (DE&I) and the limited reduction of non-inclusive behaviors and practices in real-world contexts. While inclusivity is inherently linked to the cultural and value systems of organizations, it is equally evident that socially undesirable or inappropriate behaviors fall within the realm of individual decision-making. These behaviors are frequently influenced by cognitive biases and prejudices, which tend to perpetuate or normalize inappropriate conduct rather than stigmatizing or sanctioning it. Despite increasing sensitivity to DE&I issues in both societal and organizational domains, training remains the most widely adopted intervention. However, such initiatives often yield only limited short-term awareness and rarely generate enduring structural change.
Accordingly, this paper first explores the intersection between DE&I and various forms of knowledge management, with particular attention to interdisciplinary frameworks that integrate diverse epistemological perspectives. Within this framework, the paper highlights the growing relevance of technology not only in terms of content accessibility and knowledge dissemination related to DE&I, but also as a transformative tool in shaping learning processes. Specifically, the focus is on emerging Web3 technologies—most notably immersive solutions such as virtual reality (VR) and Artificial Intelligence (AI)—which hold disruptive potential for reshaping traditional training paradigms. These technologies offer new opportunities for insight into individual decision-making mechanisms and behavioral patterns.
The development of advanced immersive applications presents the potential to transcend the limitations of passive cognitive learning by fostering active engagement in dynamic, simulated environments. This facilitates the unconscious acquisition of new skills and behavioral responses. The paper analyzes various implementation strategies and their outcomes, with particular emphasis on integrative approaches that combine VR, neuroscience, and artificial intelligence (AI). These multidimensional solutions appear especially effective in enhancing individual self-awareness and facilitating unconscious behavioral recalibration.
The study concludes by proposing an initial conceptual framework that categorizes the range of emerging approaches according to their respective objectives and impacts. It further identifies key strengths and limitations, offering guidance for the more effective design and deployment of DE&I training interventions.

This study explores how university-industry-government (U-I-G) cooperation fosters sustainable innovation in the context of Estonia’s post-industrial Ida-Viru region—a historically oil shale–dependent area undergoing a complex sustainability transition. Drawing on the multi-actor collaboration frameworks, which integrates both innovation and sustainability perspectives, this we study how collaborative efforts across institutional boundaries can enhance socio-technical change in peripheral European regions. Using a qualitative methodology 46 stakeholders from educational institutions, companies, municipalities, and umbrella organisations were interviewed to understand the dynamics of regional innovation system. The findings highlight the dual role universities and other educational institutions play—as knowledge producers and civic institutions—bridging technological advancement with societal values. The study reveals how knowledge spillovers, academic-industry exchanges, and boundary-spanning organizations enable sustainable innovation practices, even despite of significant structural challenges such as brain drain, low trust, weak entrepreneurship, and demographic decline. The analysis identifies enabling mechanisms, such as state support via the Just Transition measure, localized collaboration platforms like clusters, industrial parks, joint events and increased trust among actors—as pivotal to overcoming barriers. Companies in the region are adopting sustainable practices, ranging from incremental efficiency improvements to radical innovations such as resource valorization and bio-based production models. The findings also underscore the tensions between short-term economic goals and long-term sustainability. The research advances theoretical understanding of the multi-actor collaboration frameworks, including Triple Helix Twins model and its practical relevance in navigating the complex interdependencies between technological and social innovation. It concludes that reconfiguring regional innovation systems around sustainability goals requires not only institutional collaboration, but also the cultivation of shared values and systemic reflexivity.

The Human Resources field, on a national and global scale, faces increasing challenges related to Skill Mismatch, a phenomenon in which candidates’ profiles do not align with labour market demand. The contributing factor analysed in this paper is the lack of inclusivity in job advertisements, as non-inclusive language and biases in the selection criteria may discourage applications from underrepresented communities. Ensuring compliance with Diversity & Inclusion (D&I) principles in job postings is essential to fostering fair hiring practices and promoting employment equity.
While AI-based technologies are finding increasing applications in the recruitment process, thus becoming part of the research topics in HR management, most existing tools primarily focus on gender discrimination, underestimating other critical aspects of D&I. This study explores how an integrated approach, based on a broader range of aspects of D&I European principles, may enrich AI-based tools to identify, but also solve, biases in job advertisements, enhancing inclusivity and employment equity for both candidates and recruiters. By expanding the scope of these tools, organizations can better align their hiring practices with the evolving expectations of a diverse and inclusive workforce.
The approach to the problem has been broken down into two main phases. First, guidelines were developed based on European non-discrimination regulations, providing a structured framework for evaluating job advertisements. Then, a Generative AI-based software was designed to screen job postings for inclusivity and compliance. The study underscores the potential advantages of AI-driven automation in screening job advertisements, reducing human biases, resource commitment, and processing time while ensuring adherence to D&I principles.

In recent years, the growing emphasis on social sustainability and ethical corporate behavior has brought Diversity, Equity, and Inclusion (DE&I) to the forefront of both academic debate and corporate strategy. Movements such as Me Too and Black Lives Matter, alongside the impact of the COVID-19 pandemic, have accelerated awareness around social inequalities, urging firms to enhance transparency and commitment to inclusive practices. Despite this trend, empirical studies investigating the determinants of DE&I disclosure remain scarce.
This study aims to fill this gap by analyzing the quality of DE&I disclosure among S&P 500 firms. A manual content analysis is conducted using the Global Reporting Initiative (GRI) standards, leading to the construction of a DE&I Disclosure Quality Index (DE&ID). Each disclosure item is scored on a 0–3 scale, allowing a maximum index value of 51. The analysis incorporates “Requirements,” “Recommendations,” and “Guidelines” outlined in the GRI framework.
The second objective is to investigate the influence of firm-specific economic and financial characteristics—firm size, firm profitability, firm leverage, and firm age—on DE&I disclosure levels. Four hypotheses, grounded in stakeholder theory, are tested using OLS regression.
Results demonstrate that larger, more leveraged, and younger firms exhibit higher DE&I disclosure, driven by greater stakeholder pressure and the strategic benefits of enhanced transparency. This study contributes to the ESG literature by offering new insights into the drivers of DE&I communication, with implications for both academia and policy, and supports the integration of DE&I into corporate accountability frameworks.

This cross-sectional study investigates the energy use behaviors, carbon emissions, and energy-related knowledge, attitudes, and practices (KAP) of undergraduate students from six private medical universities across northern, central, and southern Taiwan. Data were collected via structured questionnaires from May to June 2023, encompassing 184 students with diverse academic years, departments, and gender distributions (69% female). The study quantified daily activity durations involving energy consumption-such as air conditioning, heating, transportation, and use of electrical appliances-and estimated individual annual carbon emissions by integrating activity duration, energy consumption rates, and emission factors. Results indicate that air conditioning and heating account for the longest daily energy use (244 to 750 minutes), reflecting Taiwan’s subtropical climate and high cooling demand. Transportation activities, including car, motorcycle, and public transit use, also contribute substantially, with Taipei Medical University students exhibiting the highest public transportation usage (mean 98 minutes). Departmental variations were noted, with pharmacy students using air conditioning most extensively and medical laboratory science students using public transit more frequently.
The KAP survey revealed moderate to high knowledge levels but comparatively lower positive attitudes and practices toward energy conservation, aligning with international findings. These results highlight the importance of targeted educational interventions to promote sustainable energy behaviors among medical students, who are future healthcare professionals with potential influence on institutional sustainability. This study fills a research gap by linking individual-level energy behaviors with carbon emission estimates in Taiwan’s higher education context, providing a foundation for policy and behavioral strategies aimed at reducing the carbon footprint of medical education institutions.