Search Results (1,421)

Higher education institutions operate complex digital environments that combine administrative services, research infrastructures, learning platforms, identity systems, and heterogeneous departmental IT. In the European Union, the NIS2 Directive increases the need for structured cybersecurity governance, while ISO/IEC 27001:2022 provides a mature information security management system standard that can support implementation. This paper proposes a design science artefact for aligning NIS2 obligations with ISO/IEC 27001:2022 clauses and Annex A controls in the context of higher education institutions. The framework organizes cybersecurity governance, asset and service scoping, risk management, incident handling, business continuity, supplier and cloud dependencies, access control, awareness, monitoring, and continual improvement into a staged maturity model. The artefact is instantiated for a Romanian public university context and assessed through internal traceability analysis, including mappings between NIS2 Articles 20, 21, and 23, Romanian NIS2 transposition requirements, and ISO/IEC 27001:2022 control areas. The institutional illustration identifies candidate assessment domains and evidence requirements but does not assign maturity levels because the internal records required by the scoring protocol were unavailable; it therefore does not constitute an audit, verified institutional measurement, or empirical validation. The contribution is therefore a structured and reusable compliance design artefact, together with a transparent mapping method that can support future expert validation, institutional pilots, and audit-oriented refinement. Full article

The pervasive rise in digital platforms has fundamentally recalibrated the relationship between urban communities and their cultural landscapes, reconfiguring not only the sensory experience of these environments but also their interpretive frames and the everyday contestations that surround them. Using coffee spaces in Beijing as an empirical lens, this study integrates 630 validated POI locations, 287,632 online reviews from Dianping, GIS spatial analysis, LDA topic modelling, semiotic coding, and a fine-tuned RoBERTa (Robustly Optimized BERT Pretraining Approach) text classifier to examine the convergence between platform-mediated public perceptions and urban spatial differentiation. Our spatial interrogation identifies a statistically significant centre–periphery divide within this platform-curated corpus—a pattern that describes the geography of platform-mediated visibility rather than the total physical distribution of coffee outlets in Beijing, characterised by pronounced high-density agglomerations nesting within historic urban cores, central business districts, nascent knowledge hubs, and gentrifying lifestyle enclaves. Three landscape prototypes are derived from the data—business corridors, cultural experimental fields, and social-media spectacles. Each type exhibits discernibly different patterns of spatial density, adjacent land-use configurations, perceived experiential qualities, and underlying symbolic discourses. While positive sentiments dominate platform discourse, localised anxieties emerge regarding visual homogenization, intense queuing, premium pricing, and loss of place authenticity. The 630 venues analysed here represent a platform-visibility stratum—establishments sufficiently reviewed to feature on digital intermediaries—and the spatial patterns we map describe the geography of this visibility rather than the total physical distribution of coffee outlets. Full article

Green digital technologies are increasingly used to improve environmental visibility, resource efficiency, and sustainability-oriented decision-making. However, their association with sustainable business performance may depend on whether firms convert digital resources into organizational capabilities and implemented circular practices. Drawing on the Natural Resource-Based View, Dynamic Capabilities Theory, and Institutional Theory, this study examines a moderated serial mediation model in which eco-innovation and circular economy adoption sequentially mediate the relationship between green digital technologies and sustainable business performance, while institutional support moderates the relationship between eco-innovation and circular economy adoption. Survey data were collected from managers and professionals in Saudi industrial and manufacturing firms. Of the 450 questionnaires distributed, 420 were returned, and 386 usable responses remained after data-quality screening and were analyzed using partial least squares structural equation modeling in SmartPLS 4. The results show that green digital technologies are positively associated with eco-innovation (β = 0.662, p < 0.001) and circular economy adoption (β = 0.263, p < 0.001). Eco-innovation is positively associated with circular economy adoption (β = 0.487, p < 0.001), which, in turn, is strongly associated with sustainable business performance (β = 0.726, p < 0.001). The serial indirect association through eco-innovation and circular economy adoption is significant (β = 0.234, p < 0.001). Institutional support also strengthens the eco-innovation–circular economy adoption relationship, although the interaction is comparatively modest (β = 0.118, p = 0.002). The study contributes by distinguishing eco-innovation as a resource-conversion capability from circular economy adoption as an implemented organizational practice and by identifying institutional support as a boundary condition within Saudi industrial firms. Full article

Purpose: This study investigates the structural pathways driving the startup potential of Generation Z students in Romania’s post-transition economy. It examines the sequential relationship between Entrepreneurial Mindset (EM), Entrepreneurial Intentions (EIs), and Entrepreneurial Behavior (EB), focusing on the mediating role of intentions in bridging the gap between cognition and action. Design/methodology/approach: Using a quantitative explanatory design, data were collected through a two-stage hybrid framework from a sample of 215 Romanian business students associated with the Hackathon Innovation Labs (HILs), selected via a non-probability purposive sampling method. Hypotheses were tested using Structural Equation Modeling (SEM) with maximum likelihood estimation, supported by Confirmatory Factor Analysis (CFA) to ensure statistical rigor. Findings: Results confirm that EM is a robust predictor of EI, which significantly drives EB, explaining 45.2% of its variance. The findings highlight that intentions fully mediate the relationship, suggesting that a growth-oriented mindset turns into firm intentions to overcome institutional and cultural barriers. Originality: This research applies a rigorous SEM framework to a cohort of digital natives in an underrepresented Eastern European emerging market. It integrates mindset as a foundational cognitive precursor and provides empirical evidence of the sequential path to entrepreneurial behavior. Research limitations/implications: The study is limited by its sample size and geographic focus on Romanian business students. Future longitudinal research should explore external contingency factors, such as access to capital and ecosystem support, to validate model generalizability. Practical and social implications: Higher education should shift toward experiential programs like HILs, embedding credit-bearing hackathons and micro-credentials to foster an entrepreneurial mindset. Socially, sustaining this momentum with structured mentorship bridges the intention–action gap, transforming Gen Z’s digital potential into tangible economic value for the post-transition ecosystem. Full article

Small- and medium-sized enterprises (SMEs) increasingly use artificial intelligence (AI)-based customer tools and social media marketing to compete in digital markets. However, prior research has not fully explained how customer-facing digital interaction and strategic customer sensing are converted into internal organisational capabilities or how alternative combinations of capabilities lead to business sustainability. In this study, we develop and test a sequential mixed-method framework for Thai SMEs. In Phase I, we applied the Interval Type-2 Fuzzy Delphi Method (IT2FDM) with 21 experts to validate 43 observed variables. In Phase II, we analysed 659 Thai SME responses using Partial Least Squares Structural Equation Modelling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA). The PLS-SEM measurement assessment showed that service innovation and internal learning formed a consolidated service innovation–internal learning capability (SILC) construct, with 42 indicators retained in the final measurement model. The structural model supported all hypothesised paths: AI chatbot usage, social media marketing, and customer value anticipation were positively associated with SILC; SILC was positively associated with external learning, business performance, and business sustainability; external learning was positively associated with business performance; and business performance was positively associated with business sustainability. The fsQCA results showed that no single present or absent/low condition was necessary for business sustainability and identified three sufficient pathways, with SILC and business performance present across all primary configurations. One pathway further showed that strong SILC, external learning, and business performance could support business sustainability even when AI chatbot usage, social media marketing, and customer value anticipation were weak or absent. The findings advance SME digital transformation and sustainability research by demonstrating capability conversion, integrated innovation–learning transformation, and multiple compensatory pathways to business sustainability. Full article

The central challenge of the energy transition lies in whether an economy possesses the institutional capacity to systematically regulate its own energy inputs and carbon emissions. Drawing upon social metabolism theory, this study constructs an indicator of carbon–energy metabolic control capacity (CMCC). Building on business ecosystem theory, it conceptualizes the intelligent economic ecosystem (IEE) and incorporates industrial chain intellectual property empowerment (IP) into a causal framework of institutional provision → ecosystem development → enhancement of metabolic control capacity. Using panel data from 30 provincial-level administrative regions in China covering the period 2010–2022, this study employs a spatial Durbin difference-in-differences (SDID) model and a double machine learning (DML) framework for empirical analysis. The results indicate that industrial chain intellectual property empowerment significantly enhances carbon–energy metabolic control capacity and generates positive spatial spillover effects on neighboring regions through the public diffusion of patent information. Furthermore, intelligent economic ecological development serves as a significant partial mediator between intellectual property empowerment and carbon–energy metabolic control capacity, with the indirect effect accounting for more than one-third of the total effect. This mediating mechanism remains robust after replacing machine learning algorithms, altering sample-splitting ratios, controlling for concurrent innovation policies, and excluding the impact of the COVID-19 pandemic. Path-specific mediation analysis further reveals that computing power acquisition and value transformation together with digital substrate robustness constitute the dominant transmission channels, whereas innovation metabolic flux contributes a relatively smaller mediating effect due to the long gestation period required for translating fundamental research into practical applications. Heterogeneity analysis further demonstrates that the transmission mechanism exhibits full mediation in the dimension of metabolic structure, indicating that the contribution of industrial chain intellectual property empowerment to the clean substitution of energy structures depends almost entirely on the mediating role of the intelligent economic ecosystem. These findings provide clear actionable guidelines for three specific policy-making domains to advance low-carbon transitions. First, intellectual property authorities should transition from quantity-driven patent creation to establishing cross-regional patent navigation and industrial chain IP pooling. Second, digital economy and industry regulators need to prioritize computing power value conversion (CCV) over raw infrastructure expansion to mitigate energy rebound effects. Third, energy and environmental agencies ought to integrate real-time algorithmic dispatching with green finance incentives. Ultimately, this study demonstrates that achieving deep low-carbon transformation requires leveraging institutional public goods to catalyze digital ecosystems, which in turn enable precise, dynamic carbon–energy metabolic control. Full article

As artificial intelligence (AI) technologies advance, traditional craftsmen face new challenges: innovating using digital tools while preserving cultural authenticity and heritage knowledge. The “hybrid artisan,” who strategically integrates AI-based design tools with traditional craft, emerges as a response to this tension. This article addresses research questions regarding how integrating generative AI technologies into design processes influences: (1) artisans’ productivity and product quality; (2) cultural authenticity and heritage preservation; (3) sustainable business models in creative entrepreneurship. The research methodology employs a convergent design with mixed methods, combining: (a) a systematic literature review (SLR) guided by the preferred reporting items for systematic reviews and meta-analyses (PRISMA 2020, n = 33 articles, 2022–2025); and (b) a qualitative survey (n = 13 artisans, Romania; semi-structured questionnaire, 34 items). The literature review identifies three dominant human–AI collaboration models: task-level cooperation, process-level coordination, and system-level co-creation. Diffusion models fine-tuned with low-rank adaptation (LoRA) and generative adversarial networks (GANs) achieve cultural authenticity scores of 73–95% while reducing design time by 30–70%. Empirical data reveal paradoxes: artisans value authentic creativity and sustainability (4 of 13 respondents (31%) rate sustainability as “extremely important”) but adopt AI cautiously (6 of 13 respondents (46%) report that they were not familiar with AI tools). Those using AI report 15–40% productivity gains without a proportional increase in sales, suggesting that market recognition of AI-assisted crafts remains uneven and that sustainability benefits are not yet clearly linked to AI use in practice. The successful “hybrid artisan” model relies on collaborative rather than autonomous AI positioning, explicit cultural safeguards in system design, and transparent communication with consumers about AI involvement. This research provides a conceptual heuristic, points to new research directions, and outlines policy implications for understanding when and how AI-assisted craft practices may support cultural integrity while also accepting that such benefits are context-dependent and not universally validated. Full article

Digitalisation is increasingly viewed as an instrument for narrowing the VAT gap in the European Union, yet the relative relevance of voluntary business digitalisation and mandatory administrative reporting remains unclear. This study distinguishes cloud accounting from mandatory transaction reporting and analyses an unbalanced EU-27 panel for 2013–2024, with estimations limited to 2013–2023. Sequential pooled OLS, two-way fixed-effects models and robustness checks are applied to European Commission, Eurostat and World Bank data. The initially negative association between cloud accounting and the VAT gap disappears after controlling for income and government effectiveness. Mandatory digital reporting is associated with a VAT gap of about 3–4 percentage points lower, although the small number of adopters and pre-adoption trends preclude causal claims. Theoretically, first, the findings distinguish firm-level digital capability from information directly accessible to tax administrations; second, they show that technology adoption and institutional capacity must be analysed separately. Practically, first, the results support interoperable systems providing timely, structured and verifiable transaction data; second, they indicate that cloud accounting should complement, rather than replace, mandatory reporting infrastructure. Full article

AI is currently shaping how people are being entrepreneurial by allowing the establishment of AI-native ventures. The creation of these new types of businesses builds off an infrastructure of data, computing power, and research that typically accompany advanced economies. In contrast, most developing economies are still experiencing institutional and structural barriers that inhibit the formation of new ventures and their subsequent growth. Despite the existence of research that explores some of the ways in which successful ecosystems from developed economies could be applied to developing ecosystems, there is little guidance on how to systematically adapt these successful practices in resource-constrained environments. This research uses a comparative, document-based study design to assess how to benchmark and configure AI-native entrepreneurship ecosystems across heterogeneous institutional environments. Using Switzerland and Jordan as two contrasting analytical cases, we define twelve dimensions of an ecosystem and then create comparative ecosystem profiles using a standardized coding and scoring framework. We combine dimension-level data on talent development, applied research, infrastructure, financing, governance and market access with baseline socio-economic indicators. Our results demonstrate a high level of structural asymmetry between the two ecosystems. Switzerland has a balanced and highly coordinated configuration, whereas there is a strong university anchor and demand for talent in Jordan, but there are also significant weaknesses in terms of infrastructure, financing, and industry linkages. Building from these results, we present the parameter re-weighting and the context-sensitive design model to encourage the emergence of AI-native entrepreneurship in Jordan through coordinated architecture, collaborative experimentation resources and internationalization at an early stage. This article advances both the fields of entrepreneurial ecosystems and digital entrepreneurship by framing AI-native entrepreneurship as a new form of knowledge-intensive venture creation and providing a context-sensitive approach for adapting entrepreneurial ecosystems. The results provide a document-informed basis for policymakers, academic institutions and other ecosystem actors seeking to develop AI-based innovation in resource-constrained economies. Full article

Legal certainty is a central condition of commercial exchange, yet its relationship with contractual digitalization remains insufficiently specified in business-to-business settings. This study examined how the degree of contractual digitalization was associated with legal certainty in intercompany commercial relations in Ecuador. A contract-level dataset of 160 commercial contracts was analyzed using descriptive statistics, Spearman correlation, MANOVA, robust OLS regression, binary logistic regression, principal component analysis, k-means clustering, and bootstrap resampling. A digitalization gradient was observed across the sample. Digitalization levels were associated with evidentiary support, legal risk, legal certainty, formal-dispute prevalence, and contingency-resolution times. The most pronounced monotonic association linked digitalization with legal certainty (Spearman’s ρ = 0.8379, p < 0.001). In the adjusted OLS model, digitalization level was associated with a 14.90-point difference in legal certainty per unit increase, while the adjusted logistic model showed lower odds of formal dispute at higher digitalization levels. Unsupervised analyses identified two broad contract profiles corresponding to lower- and higher-certainty digital environments, and bootstrap results indicated stability of the principal estimates. These findings should be interpreted as correlational evidence derived from a contract-level, non-probabilistic sample of Ecuadorian commercial contracts, and not as causal or nationally representative conclusions. Full article

The rapid paradigm shift from traditional keyword-matching algorithms to AI-driven answer engines has fundamentally disrupted Search Engine Optimization (SEO). As Large Language Models (LLMs) power modern Search Generative Experiences (SGEs), organizations must transition from legacy web analytics to sophisticated Business Intelligence (BI) frameworks to capture visibility. Despite the immense strategic implications of this shift, academic literature remains fragmented across computer science, information systems, and digital marketing management. To bridge this gap, this paper adopts an integrative literature review methodology, synthesizing 70 high-value studies selected from an initial corpus of 11,382 papers filtered to 2962 on-topic studies. Rather than utilizing restrictive systematic protocols (e.g., PRISMA) that isolate empirical data within narrow boundaries, the integrative approach enables a holistic synthesis of emerging, multi-disciplinary concepts necessary to decode a rapidly evolving phenomenon. Through this methodological lens, this study introduces the Signal–Structure–Surface–Score (4S) lifecycle framework, illustrating how AI-BI systems capture conversational search intents (Signal), architect machine-readable, entity-based data (Structure), optimize content for LLM retrieval and Generative Engine Optimization (Surface), and define novel attribution metrics for zero-click environments (Score). Furthermore, the paper maps the critical technical and strategic landscape, systematically evaluating prevailing trends (e.g., zero-click searches, AI-generated content velocity), core organizational challenges (e.g., search data attribution loss, algorithmic opacity), and emerging strategic opportunities (e.g., real-time intent mapping, competitor LLM audit trails). Ultimately, this paper bridges the gap between AI search mechanics and strategic BI measurement, providing a robust future research agenda designed to guide scholars and practitioners in navigating data-driven visibility in the age of generative search. Full article

Sustainable business models (SBMs) describe how organizations create, deliver, and capture value while simultaneously generating economic, environmental, and social benefits for a broad set of stakeholders. Although the field has expanded rapidly since the late 2000s, the literature remains conceptually dispersed: definitions proliferate, design tools and archetypes coexist without integration, and findings on the link between sustainability practices and firm performance remain inconsistent. To address this fragmentation, this study conducts a PRISMA 2020-guided systematic literature review of foundational and recent contributions published between 2008 and 2025. Of 300 records identified through database searching, 30 studies met the eligibility criteria and were synthesized qualitatively; these are interpreted together with complementary theoretical and methodological literature. Rather than reporting bibliometric indicators, the review synthesizes the field across three dimensions: the evolution of the SBM concept, its dominant design logics and archetypes, and its contemporary thematic landscape. The findings trace a progression from foundational triple-bottom-line conceptualization, through archetype- and tool-based design approaches such as the Triple-Layered Business Model Canvas and pattern taxonomies, toward digitally enabled, circular, and resilience-oriented models. These patterns are interpreted through complementary theoretical lenses—the resource-based and natural-resource-based views, dynamic capabilities, information-processing theory, and stakeholder theory. The review consolidates these insights into an integrative conceptual framework that links theoretical foundations, value-design dimensions, enabling capabilities, and triple-bottom-line outcomes. It further discusses implications for managers and outlines a research agenda emphasizing digital and circular enablers, longitudinal designs, and the under-examined context of emerging markets, with an applied emphasis on Central Asia and Kazakhstan. Full article

The post-pandemic acceleration of digital tools has reshaped how small and medium-sized enterprises (SMEs) in Latin America compete, yet the resulting maturity gains remain poorly understood in individual emerging-market economies. Ecuador exemplifies this gap: SMEs account for over ninety per cent of the formal business register but appear in few econometric studies, most based on convenience samples. This study asks how strongly digital adoption is associated with the digital maturity of Ecuadorian SMEs and which tools best predict e-commerce engagement. The analysis draws on the National Digital Skills Survey (ENHD, Encuesta Nacional de Habilidades Digitales), administered by Ecuador’s Ministry of Telecommunications (MINTEL), covering 847 SMEs in 2021. A ten-indicator Digital Adoption Index (DAI) is related to the ENHD maturity score through least squares regression with robust standard errors, and a binary logit model with multicollinearity diagnostics identifies the tools that predict e-commerce adoption. The DAI explains over half of the variance in digital maturity, robust to firm-size and sector controls. Website presence exerts the largest marginal effect on e-commerce adoption, followed by cloud services. Top adopters score twice as high as non-adopters, consistent with cumulative advantage. Policy implications include subsidised digital-foundations bundles for laggard micro-enterprises. Full article

Corporate resilience has become a critical capability for firms to cope with increasing environmental uncertainties and external shocks. Against the backdrop of the rapid development of the digital economy, this study examines whether digital transformation enhances corporate resilience and further investigates whether environmental, social, and governance (ESG) performance serves as a complementary transmission mechanism in this relationship. Drawing on resource orchestration theory, this study uses panel data of Chinese A-share listed companies from 2016 to 2024 and estimates a series of firm fixed-effects models. The results indicate that digital transformation significantly enhances corporate resilience, and the findings remain robust after a series of robustness checks and endogeneity tests are conducted. Further analysis reveals that ESG performance partially mediates the relationship between digital transformation and corporate resilience, suggesting that responsible business practices complement the resilience-enhancing effect of digital transformation. The results of the heterogeneity analysis further indicate that the positive effect of digital transformation is significantly stronger for high-tech firms. In addition, firms exhibit substantial variation in the consistency between digital transformation communication and actual digital investment. Further analysis suggests that greater alignment between digital transformation communication and substantive implementation is associated with stronger resilience outcomes, providing supplementary evidence on the implementation process of digital transformation. This study contributes to the literature on digital transformation and corporate resilience by revealing the resource orchestration process through which digital transformation creates organizational value and identifying ESG performance as a complementary transmission mechanism. The findings also have practical implications for firms seeking to strengthen their resilience and achieve sustainable development in an increasingly uncertain environment. Full article