Regional innovation ecosystems play a crucial role in advancing national innovation capacity. However, the question of how to foster sustained collaborative innovation among diverse actors within these ecosystems under digitalization remains underexplored. This study aims to investigate the dynamic mechanisms and key factors influencing synergistic innovation behavior among multiple stakeholders in digitally enabled regional innovation ecosystems. Drawing on evolutionary game theory, we develop a tripartite game model involving core enterprises, complementary parties, and the government. A simulation analysis is conducted using the Zhongguancun Science and Technology Park as a case context to examine the evolutionary trajectories of cooperation strategies. The results indicate that: (1) increasing the intensity of digital investment by innovation agents significantly enhances the stability and sustainability of the regional innovation ecosystem; (2) core enterprises can stimulate cooperative innovation by providing incentives to complementary parties in the digital context; (3) innovation actors exhibit substantial positive spillover effects, facilitating the circulation and integration of digital resources and data elements; and (4) government subsidies and penalties positively influence system stability and accelerate the convergence of evolutionary dynamics. By integrating a digital perspective into the analysis of regional innovation ecosystems, this study contributes to theoretical discussions on innovation cooperation and provides practical insights for local governments seeking to improve synergistic mechanisms within digital innovation ecosystems. The findings also offer strategic references for promoting the sustainable development of regional innovation systems under digitalization.

ABSTRACT In Nigeria’s rapidly evolving digital ecosystem, gossip and celebrity culture modulate how stories are produced, circulated, and consumed, with viral scandals moving through the networked milieu as cultural objects that traverse social media, music, and film, braiding moral scrutiny and entertainment into the same performative logic of digital spectacle. This study, hence, critically examines the 2025 Nollywood film Truth or Dare as a cultural text that dramatises a real-life celebrity scandal involving Baba Tee, Ijoba Lande, Dara, and Mary Gold, and conceptualises it as part of a growing ‘gossip genre’ in Nigerian cinema. Specifically, it analyzes how the film (re)constructs celebrity scandal through narrative framing, gendered moral judgement and the aestheticization of gossip as spectacle, further revealing Nollywood’s ambivalent participation in the digital age. Drawing on scholarship in digital culture studies alongside Yekú theorisation of ‘cultural netizenship’ – which elucidates how vernacular digital practices mediate the reciprocal relationship between technology and narratives – it posits that the film participates in the mechanisms of networked culture by re-enacting the viral scandal through livestream mimicry, confessional framing and viral speech acts. It concludes with a reflection on the ethical stakes of such adaptations, especially around consent, representation, and gendered moral scrutiny.

Music popularity prediction is a fundamental problem in music information retrieval, with important implications for digital content dissemination and creative decision-making on streaming platforms. In this study, music popularity prediction is formulated as a supervised regression problem, and six widely-used tree ensemble models (Random Forest, XGBoost, CatBoost, LightGBM, Extra Trees, and Decision Tree) are systematically evaluated using large-scale Spotify data. Among these models, Random Forest achieves the best predictive performance on this dataset (RMSE = 6.79, MAE = 5.10, and R2 = 0.6658), followed by Extra Trees (R2 = 0.6378) and Decision Tree (R2 = 0.6328). Bayesian hyperparameter optimization based on a Tree-structured Parzen Estimator with an Expected Improvement acquisition function is conducted over 50 trials with 5-fold cross-validation to ensure robust model selection. Shapley value decomposition via SHAP analysis reveals that temporal recency dominates feature importance, far surpassing traditional musical attributes, while acoustic intensity (loudness) exhibits a U-shaped contribution pattern with optimal values at moderate intensity levels. Further SHAP dependence analysis uncovers non-linear relationships, indicating substantial popularity advantages for recent releases and optimal loudness levels around −5 to 0 dB. These findings suggest that streaming popularity is primarily governed by temporal exposure dynamics and production-related characteristics rather than intrinsic musical structure, offering both theoretical insights for music information retrieval research and suggestive empirical patterns that may inform future investigations into digital music ecosystems.

Abstract This study employs a postcolonial technoscience framework to examine TikTok’s evolution from its origins in China to its global prominence. It identifies three critical phases in TikTok’s journey within a historical and technical foundation of mobile communication technologies: the establishment of ByteDance through Western app mimicry to enhance its innovations, the role of parallel platformization and platform glocalization in fostering a hybridity of TikTok, and the rising tensions due to ambivalence around TikTok amid growing techno-nationalism. By showing the complexity of TikTok’s rise as the result of a shifting global technological order in which non-Western platforms challenge conventional dominance, this article presents an alternative narrative of platform globalization, aligned with postcolonial technoscience, and contributes to a nuanced understanding of the global digital platform ecosystem and the dynamics of technology power.

Abstract This paper explores the relationship between cultural memory, heritage archives, and digital technologies through the case study of the Villa del Casale in Piazza Armerina, a UNESCO World Heritage Site since 1997. Building on theoretical frameworks developed in the last decades, it highlights how archives function not as neutral repositories but as active agents in shaping memory through processes of selection, interpretation, and narration. The project “Digital strategies for enhancing cultural heritage: the Villa del Casale of Piazza Armerina” addresses these challenges by digitizing over a century of archaeological documentation, unpublished excavation diaries, and stored artifacts. Through 3D scanning, semantic metadata enrichment, and an open-source Web platform, the initiative creates a digital ecosystem that bridges the Museum of Palazzo Trigona, the Villa, and their archival collections. Ultimately, the project demonstrates how digital technologies not only safeguard fragile heritage but also actively reshape European cultural memory, transforming archaeological sites into global memory platforms.

This study investigates the influence of digital payment ecosystems on the financial behavior of Vietnamese youth through a three-tier analytical framework comprising technological behavior, the perceived usefulness construct, and smart financial behavior. Utilizing survey data from 300 respondents aged 18–35 and estimated via Structural Equation Modeling (SEM) combined with OLS regressions, the findings reveal that technological behavior is the principal driver of digital payment usage, whereas financial literacy and demographic characteristics exhibit no statistically significant effects. The model further demonstrates that perceived usefulness exerts a substantial impact on spending-tracking practices and facilitates more disciplined financial planning. The study elucidates both the determinants of digital payment adoption among young users and the subsequent financial behaviors that arise thereafter. Moreover, the results underscore the need for tiered smart-financial-education interventions that align with distinct behavioral levels and are embedded directly within digital payment applications to enhance relevance and effectiveness for young consumers.

In recent years, increasing evidence has highlighted the potential of remote management in cardiovascular diseases, with growing recognition of its feasibility and clinical value supporting its broad future application. This study aimed to investigate the efficacy of remote management for patients with heart failure (HF) in eastern China. A single-center, prospective, nonrandomized controlled trial enrolled 433 patients with HF, comprising 52 opting for remote management and 381 receiving usual care. Propensity score matching (1:2) yielded 95 patients (37 intervention and 58 control) for analysis. The intervention comprised a multi-level digital health ecosystem (WeChat mini-program and centralized digital health management platform), structured health monitoring (weight, blood pressure, heart rate, and oxygen saturation), and education. The primary outcome includes a composite of cardiovascular mortality and HF-related rehospitalization. The composite primary outcome occurred in 11 (30%) patients receiving intervention and 24 (41%) controls over a maximum 24-month follow-up period. The intervention group demonstrated a statistically significant reduction in the percentage of days lost due to unplanned HF rehospitalization or all-cause death (p = 0.049). Numerically lower rates were observed for HF-related rehospitalization, cardiovascular mortality, and all-cause mortality, along with higher quality of life scores, although with no statistical significance. Remote management demonstrated feasibility and potential clinical benefits, particularly in reducing the cumulative burden of illness. Further, it provides a foundation for integration into primary healthcare systems to optimize resource allocation and improve long-term patient outcomes.

Based on core theories of the education industry, this paper defines the core concepts of the institutional and digital environments of the education industry. It compares and analyzes the differences in the development models of the education industries in China and Belarus in terms of institutional systems and digital ecosystem construction. Combining the practical foundations of the education industry development in both countries, it proposes targeted development suggestions from the perspectives of self-optimization and bilateral cooperation, aiming to provide theoretical reference and practical paths for the high-quality development and international cooperation of the education industries in China and Belarus.

ABSTRACT In live streaming commerce (LSC), fast-paced and fragmented information often drives consumers to conduct cross-platform searches through social networking services, increasing cognitive burden and decision difficulty. While prior studies mainly examine factors that promote purchase intention within single platforms, this study focuses on the inhibiting mechanisms that arise in cross-platform shopping contexts. Drawing on Social Support Theory, we use a mixed-method approach combining Partial Least Squares Structural Equation Modeling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA) to examine how insufficient informational and emotional support shapes consumer decisions. The results show that information overload and information conflict increase informational uncertainty, whereas situational anxiety and emotional fatigue heighten emotional ambiguity, both of which reduce purchase intention. Digital literacy alleviates information-related challenges, while utilitarian motivation buffers emotional ambiguity by encouraging goal-oriented decision-making. FsQCA further reveals multiple asymmetric configurations leading to high purchase intention. These findings extend Social Support Theory by highlighting the consequences of insufficient support in complex digital ecosystems and provide implications for improving information design and user experience in LSC.

This study aims to analyze the arrangement and implementation of online medical dispute resolution in hospitals to ensure legal certainty, as well as formulate an ideal form of the resolution model to realize justice in the future. The research method used is normative juridical with a qualitative approach through a statute approach to health regulations and electronic transactions. Legal materials were collected through literature studies at the National Library and analyzed descriptively analytically to answer the complexity of medical disputes in the digital ecosystem. The arrangement for online medical dispute resolution currently still relies on Law Number 17 of 2023 concerning Health, which requires non-litigation mediation as a first step, as well as the ITE Law as the basis for the validity of electronic documents. Implementation in hospitals is still fragmentary through medical committees or internal complaint units that are limited to simple online communication, but do not yet have special regulations for Online Dispute Resolution (ODR) outside the courts that comprehensively regulate mediator standards and data security. The condition of the absence of a standard standard creates legal uncertainty, especially regarding the strength of execution of the results of online mediation agreements. The ideal model of the future requires an integrated ODR platform that includes video mediation features, encrypted medical records, as well as the involvement of a certified neutral mediator who understands health law and professional ethics. This system prioritizes the principle of restorative justice to restore the therapeutic relationship between patients and medical personnel through a transparent, efficient, and accountable process.

The International Community Service Program themed “Integration of Social Media Algorithms in Optimizing the Use of Digital Marketing for Micro and Small Enterprises (MSEs) in Indonesia and Malaysia” is a collaborative initiative between Universitas Jambi (UNJA) and Universiti Poly-Tech Malaysia (UPTM). This program aims to enhance the digital literacy capacity of micro-entrepreneurs through a comprehensive understanding of social media algorithms and the application of creative content strategies rooted in local wisdom and culture. The implementation methods include interactive training sessions, thematic workshops, intensive mentoring, and cross-country benchmarking to strengthen knowledge transfer and the adoption of best practices. The results demonstrate a significant improvement in participants’ digital competencies, reflected in their enhanced ability to optimize social media algorithms for product marketing, the establishment of a cross-border digitalpreneur community between Indonesia and Malaysia, and the development of adaptive digital marketing training modules and standard operating procedures (SOPs). The sustainability impact of this program not only increases the competitiveness and resilience of MSEs but also strengthens international academic collaboration between the two universities. Furthermore, this initiative contributes to achieving the universities’ Key Performance Indicators (KPI) and supports the development of an inclusive and sustainable digital economic ecosystem within the ASEAN region.

The study aimed to identify the e-learning prospects for librarians’ sustainable competence and smart library service delivery in academic settings. A systematic literature review methodology was employed to address the study’s objectives. 20 peer-reviewed articles published in the world’s reputed digital databases were selected to conduct the study. The study identified six key prospects of e-learning on librarians’ sustainable competence development that included enhancement of digital pedagogy and instructional competence, advancement of technological adaptability and digital integration, promotion of lifelong learning and self-paced professional growth, strengthening of collaborative and global engagement skills, expansion of specialized information and content curation skills, and empowerment in user-centered service innovation. The study also revealed four key positive effects of e-learning on smart library services in academic settings that included service realignment and digital continuity, integration of intelligent systems and user analytics, expansion of digital learning ecosystems, the personalized and inclusive learning support. The study has provided the best practices to incorporate e-learning in academic settings for building sustainable competence development of librarians and innovative library services.

Type of the article: Research ArticleAbstractIn the context of Vietnam’s rapidly expanding digital ecosystem, understanding how psychological differences shape brand cognition among Generation Z has become increasingly important. This study aims to examine the influence of the Big Five personality traits on brand awareness across major digital touchpoints, addressing the limited empirical evidence from emerging markets. A quantitative survey was conducted in January 2025 with 898 Gen Z consumers residing in Hanoi and Ho Chi Minh City. Using Cronbach’s Alpha, Exploratory Factor Analysis, and multiple regression, the study assessed the reliability of measurement scales and the effects of personality traits on brand awareness indicators derived from Aaker’s (1991) framework. The findings show that four personality traits – openness, conscientiousness, extraversion, and neuroticism – positively and significantly predict brand awareness on digital platforms (β = 0.171–0.250; p < 0.001). Conscientiousness exhibits the strongest impact (β = 0.250), followed by neuroticism (β = 0.240), extraversion (β = 0.224), and openness (β = 0.171). Agreeableness does not demonstrate adequate construct validity and is excluded from the final model. Additional analyses using ANOVA reveal significant differences in brand awareness across regions but not across genders. These results illustrate that personality-driven tendencies, such as exploratory behavior, systematic information processing, social interaction, and risk-avoidance, play a substantial role in determining how frequently and effectively young consumers encode brand cues in digital environments. The study concludes that integrating personality insights into digital brand communication strategies can enhance relevance, memorability, and consumer-brand alignment, especially within dynamic Gen Z segments.Acknowledgment(s)The researchers express sincere gratitude to all the participants who generously participated in this study.

Security, Resilience and Interoperability Perspectives on Digital Twin Ecosystems

Reservoir computing for enhanced fidelity in hierarchical digital twin ecosystems

Abstract With the increasing scale of global data transmission, to meet the security data communication needs of the Internet of Things and 5G era, and to address traditional encryption algorithms being prone to cracking and having unsatisfactory communication efficiency, a new encryption algorithm - Advanced Encryption Standard/Secure Hash Algorithm 256-bit (AES/SHA-256) is proposed. The new algorithm optimizes the instantaneous key preprocessing process by introducing the Secure Hash Algorithm 256-bit (SHA-256), outputs the Proxy Re-Encryption (PRE) value, and generates the instantaneous key using PRE. Subsequently, the instantaneous key is introduced into the Advanced Encryption Standard (AES) to construct a more secure dynamic encryption framework. The results showed that the key preprocessing and key generation took 700 μs and 1,010 μs, respectively. The algorithm encryption and decryption processes took 1,000 μs and 800 μs, respectively. The highest number of request processes per second was 380, and the response time was 3,000 μs under a load of 50 users. The AES/SHA-256 performs better than other comparison algorithms. The application test results show that the algorithm has strong instantaneous dynamics and meets the requirements of information security transmission. The AES/SHA-256 encryption algorithm has positive significance for supporting the security of the digital economy ecosystem.

Impact assessment of digital ecosystem in healthcare services: A qualitative case study of hospital data management in Bikaner District in India

Agricultural communities increasingly depend on digital tools, yet most available platforms provide isolated services such as advisory portals or scheme listings without integrated interaction and intelligent assistance. Farmers often lack real-time expert access and community knowledge sharing. This paper presents a unified smart agricultural platform that combines farmer social networking, AI-based chatbot support, one-to-one expert consultation, and secure scalable data management. The system allows farmers to create profiles, share field experiences, interact with experts, and receive automated responses for common agricultural queries. A flexible NoSQL database backend is used to manage heterogeneous data including user profiles, chat logs, posts, and advisory records. Security controls such as authentication and role-based authorization protect sensitive farmer information. The proposed architecture improves advisory accessibility, reduces response delay, and strengthens farmer collaboration. The platform demonstrates how combining social interaction, artificial intelligence, and secure data infrastructure can significantly enhance digital agriculture ecosystems.

The rapid expansion of digital media has transformed journalistic media consumption patterns in higher education, raising concerns about information credibility and increasing vulnerability to misinformation. This study aims to analyse differences in patterns, preferences, and objectives of journalistic media use between university students and lecturers in Medan City. The research employed a qualitative descriptive approach, with data collected through in-depth interviews, observations, and documentation involving students and lecturers from several higher education institutions. The findings reveal clear differences between the two groups. Students tend to rely on social media platforms and digital news portals due to their speed, ease of access, and compatibility with digital lifestyles. At the same time, lecturers predominantly use more credible and analytical journalistic sources, such as Kompas.com, Tempo.co, and academic journals to support teaching and research activities. Variations influence these differences in digital literacy levels, information needs, and attitudes toward misinformation. Students are found to be more vulnerable to hoaxes, whereas lecturers demonstrate more critical and selective information practices. The study highlights the importance of strengthening media literacy in higher education through curriculum integration, targeted training, and collaboration with media professionals to foster a credible and educational digital information ecosystem.

The increasing demand for personalized, real-time healthcare necessitates efficient, secure patient data management. Digital Twins (DTs) enable AI-powered monitoring and decision support but also introduce challenges related to latency, computational cost, and security. This paper proposes a cost-optimized, AI-driven Medical Digital Twin (MDT) framework that manages task allocation across heterogeneous edge, fog, and cloud infrastructures. The system is formulated as a tri-objective optimization model that jointly minimizes latency and operational cost while maximizing security, subject to resource and clinical-priority constraints. To solve this problem, three complementary approaches are developed: (i) an exact Integer Linear Programming (ILP) model for optimal benchmarking, (ii) a Patient-Aware Task Intelligence Greedy (PATI-Greedy) heuristic algorithm for low-latency decision-making, and (iii) a Hybrid Q-Learning Enhanced Genetic Algorithm (HybridQeGA) for scalable, near-optimal performance in complex environments. Extensive simulations in a smart ICU scenario with 4, 8, and 12 patients demonstrate that ILP consistently achieves the best objective values but is computationally impractical for large instances. PATI-Greedy executes rapidly with polynomial complexity, achieving results within 5-[Formula: see text] of ILP for small- to medium-scale workloads. HybridQeGA offers the closest match to ILP in larger problem sizes, with less than [Formula: see text] deviation in overall objective value while maintaining scalability. Security-sensitive scenarios highlight HybridQeGA's adaptability, improving security scores by an average of [Formula: see text] compared to PATI-Greedy. These findings establish a balanced trade-off between accuracy and computational efficiency, positioning the proposed framework as a robust and deployable solution for intelligent and trustworthy digital health ecosystems.