The global digital economy presents a formidable challenge to traditional institutions, demanding a paradigm shift that balances cultural preservation with economic innovation. This study investigates the construction of an ethical and sustainable Digital Entrepreneurial Ecosystem (DEE) for Indonesian Islamic boarding schools (pesantren), institutions central to the nation’s social and religious fabric. Grounded in a philosophical synthesis of Indonesia’s People’s Economy (Ekonomi Kerakyatan) principles and Islamic ethics, this research addresses the critical nexus of traditional values and modern digital transactional demands. Employing a qualitative multi-case study of five influential pesantren in East Java, the research identifies the core components and strategic pathways for this digital transition. The findings reveal that a successful ecosystem architecture rests on three pillars: Ethical-Spiritual Governance, leveraging the moral authority of leadership (Kyai) and community trust; Socio-Digital Collaboration, which translates immense social capital into structured digital networks; and Inclusive Capacity Building, which creates accessible pathways for digital literacy and entrepreneurship. This study critiques the conventional technology-centric ecosystem models, proposing a novel, values-driven framework that positions pesantren as architects of a more equitable and culturally resonant digital future. It contributes a philosophically robust model for digital entrepreneurship that prioritizes holistic community welfare (falah) over profit-centric metrics, offering a significant contribution to the discourse on ethical technology adoption in religious communities.

This paper examines the application of Artificial Intelligence (AI) for conducting skill gap analysis in seafood processing and export units, with particular relevance to emerging seafood hubs where traditional workforce assessment methods remain prevalent. The seafood industry faces persistent challenges in maintaining product quality, regulatory compliance, operational efficiency, and sustainability, many of which stem from deficiencies in workforce skills. Conventional approaches are often slow, subjective, and incapable of delivering real-time insights. In contrast, AI enables data-driven, scalable, and predictive assessment of workforce competencies. The study proposes a multi-phase AI-driven framework that integrates machine learning, natural language processing, IoT-based monitoring, and predictive analytics to identify, measure, and address skill gaps across processing, logistics, compliance, and sustainability functions. Data sources include employee profiles, performance records, training histories, and industry benchmarks. AI tools such as computer vision for quality inspection, digital twins for process optimization, blockchain for traceability, and AR/VR platforms for training are analyzed for their role in enhancing workforce capability. Findings from a case study of a mid-sized seafood processing unit reveal significant deficiencies in advanced quality testing and export documentation knowledge. AI-based adaptive training improved compliance rates by 25%, reduced processing errors by 15%, and shortened export cycle time by 10%, demonstrating measurable operational gains. However, implementation challenges persist, including limited data availability, workforce resistance, digital literacy gaps, and high initial investment costs. The paper recommends the development of unified data platforms, change-management initiatives, scalable cloud-based AI solutions, and policy support through subsidies and skill-development programs. Overall, the study concludes that AI-enabled skill gap analysis can significantly enhance productivity, sustainability, and global competitiveness in seafood processing and export industries, providing a strategic pathway for modernization in an increasingly technology-driven global market.

MSMEs in the food and beverage (F&B) sector play a strategic role in labor absorption and regional development in Bandar Lampung. However, many business owners still face challenges such as limited innovation and low adoption of digital technology, which hinder their growth and performance in a dynamic market. This study aims to examine the influence of Information and Communication Technology (ICT) adoption and open innovation on the business resilience of F&B MSMEs. Using a quantitative approach, the population of this study consisted of 1,183 F&B MSME owners in Bandar Lampung who utilize ICT. A sample of 112 respondents was determined using the Slovin method with a purposive sampling technique. Data were collected through structured questionnaires with Likert scales and analyzed using multiple linear regression techniques via SPSS 25 software. The results indicate that ICT adoption (β =0,685; p =0,000) and open innovation (β =0,251$; p =0,000$) have a positive and significant effect on business resilience both partially and simultaneously. The model achieved a coefficient of determination (R2) of 0.694, meaning the independent variables explain 69.4% of the variance in business resilience.The implications of this research emphasize that strengthening internal digital literacy and external knowledge collaboration, particularly customer involvement, is crucial for increasing competitiveness and ensuring the business sustainability of MSMEs amidst local economic pressures.

Background: The Maltese banking sector is rapidly adopting multi-channel services, combining digital platforms with traditional branches to meet diverse customer needs. However, limited research on customer channel preferences creates a gap that may lead to misaligned strategies, reduced service quality, and exclusion of less digitally literate users. Aims: This study aims to identify and analyse the key factors influencing customers’ selection of contact channels in Maltese core domestic banks, with a focus on cognitive, demographic, and affective variables. Study Design: A quantitative, deductive research design based on a post-positivist approach was adopted. Place and Duration of Study: The study was conducted in Malta among customers of core domestic banks between late 2025 and early 2026. Methodology: Data were collected through an online self-administered questionnaire distributed via social media. A total of 260 valid responses were obtained from individuals aged 18 years and above with an active bank account. The questionnaire consisted of 18 items that measured channel accessibility, query nature, technological proficiency, user experience, age, and gender. Data were analysed using SPSS (version 29). As normality assumptions were violated, non-parametric tests, including Spearman correlation and Chi-Square tests, were employed to examine relationships between variables. Results: Findings indicate that all six independent variables significantly influence contact channel selection (p < 0.05). Online banking was the most preferred channel (mean = 4.44), followed by call centres (mean = 3.49), chatbots (mean = 2.77), and branches (mean = 2.53). Technological proficiency showed a strong positive correlation with online banking usage (ρ = 0.390, p < 0.001). Age was negatively correlated with digital channel usage (ρ = -0.255, p < 0.001), indicating higher adoption among younger users. Gender was significant only for call centres (p < 0.001), with males more likely to use them. Channel accessibility and user experience also demonstrated significant positive relationships with channel choice. Social Implication: The findings highlight the risk of digital exclusion among less technologically proficient and older banking customers, emphasising the need for inclusive strategies that ensure equitable access to financial services. Additionally, promoting digital literacy and maintaining hybrid service models can enhance financial inclusion and improve overall customer well-being within the Maltese banking sector. Conclusion: The study confirms that customer channel selection is shaped by a combination of accessibility, user characteristics, and prior experiences. Banks should adopt hybrid service strategies, enhance digital platforms, and promote digital literacy to improve customer engagement and service efficiency.

Grounded in Coleman’s view of social capital as trust, norms, and reciprocal relationships that support purposeful action, and Bourdieu’s framework in which habitus, various forms of capital, and the field interact to shape educational practices, this study examines how these dynamics influence the learning experiences of children from three vulnerable families in a rural community. Using a qualitative case study approach, data were collected through semi-structured interviews, field notes, and documentation, and then analyzed thematically to explore how family relationships, daily routines, and digital access shape children’s learning processes. The findings show that each family carries a distinct configuration of social and digital capital that produces different habitus and leads to varied educational practices. The first family demonstrates strong social capital, warm relationships, and functional use of digital technology, enabling the child to overcome limitations in the learning environment. The second family reflects weak social capital, an unstable habitus, and digital engagement dominated by entertainment, resulting in inconsistent study habits and low learning motivation. The third family exhibits a supportive habitus, positive peer networks, and purposeful digital engagement, allowing the child to develop independent learning strategies despite a limited parental educational background. Overall, the study reveals that children’s educational outcomes in vulnerable families are shaped not merely by economic constraints but by the interplay between relational quality, internal dispositions, social networks, and digital competence within the field of schooling. These findings underscore the importance of strengthening family communication, fostering meaningful digital literacy, and building supportive social networks to sustain children’s learning in resource-limited environments.

The world financial market is experiencing a technological revolution like never before that is fuelled by Unified Payments Interface (UPI), blockchain and artificial intelligence (AI). It is particularly significant in India: UPI has already conducted more than 131 billion transactions (200 trillion rupees) in FY 202425 alone and AI-based fraud detection and blockchain-based smart contracts are transforming the very core of the banking processes. The present paper provides empirical studies of adoption trends, user satisfaction, and structural issues of fintech technologies with a survey consisting of 50 participants via an intersect survey of urban and semi-urban India. Descriptive analysis, chi-square, and Likert-scale composite scoring reveal that 76 percent of the respondents pay with digital systems frequently, 68 percent of them feel that technology has made them more financially safe, and 62 percent enjoy cybersecurity threats and 58 percent digital literacy gaps as the ongoing challenges. Statistically analysed results showed significant correlations between the age, the degree of digital familiarity, and trust in fintech platforms (p < 0.05). The paper highlights some of the most important gaps in the research, specifically those associated with the role of the government in regulation and adoption of fintech by SMEs, and suggests a realistic policy framework that can be used to contribute to the inclusive adoption of fintech in developing economies.

Background: Strengthening community health workers’ (CHWs) digital competencies is critical to ensuring that digital health transformation translates into improved community-level services. Aims: This systematic review aimed to synthesize evidence on the effectiveness of training, empowerment, or capacity-building interventions in enhancing CHWs’ competencies in using digital technologies and artificial intelligence (AI). Methods: Following PRISMA guidelines, articles published between 2016 and 2026 were identified from four databases. Quantitative studies and community-based implementation reports assessing improvements in digital knowledge and/or skills were included. Results: Of 885 records screened, 30 met eligibility criteria. Interventions encompassed mobile health applications, web-based information systems, digital data management tools, and AI-assisted screening platforms. Most studies reported significant gains in knowledge scores, digital data entry and reporting skills, electronic form management, digital surveillance, and AI-assisted interpretation. Improvements in data completeness, timeliness, and perceived reporting accuracy were also documented. However, sustainability challenges emerged, including limited internet infrastructure, unequal access to devices, heterogeneous baseline digital literacy, reliance on external mentoring, short-term evaluations, and incomplete integration with routine health information systems. Conclusion: Overall, structured digital training interventions consistently enhance CHWs’ competencies and support the strengthening of primary health care. Sustainable impact, however, requires institutional embedding, standardized tiered training, infrastructure investment, and governance mechanisms to prevent digital initiatives from remaining fragmented pilot projects.

This study investigated the impact of interactive learning and self-regulated learning on the development of digital literacy among primary school students in Guizhou. The research employed a mixed-method approach, conducting surveys with 260 teachers and students. The research utilized a mixed-methods approach, gathering survey data from 260 primary school educators, while assessing kids’ interactive learning, self-regulated learning, and digital literacy development based on teachers’ professional perceptions. The results showed that both learning methods significantly enhanced students’ digital literacy (p < 0.01). Interactive learning (mean 3.802) not only directly promoted the development of digital literacy (β = 0.811), but also had an indirect promoting effect by improving the students’ autonomous learning ability. The interactive learning and digital literacy development paths (β = 0.42) supports the presence of a meaningful indirect effect through self-regulated learning, consistent with partial mediation. The study demonstrated that by designing collaborative learning activities, students’ abilities in information screening and digital creation could be effectively enhanced, and it also helped students from different backgrounds bridge the digital divide. These findings provide a feasible model for digital literacy education in the western region and have positive implications for promoting educational equity.

This paper explores the predictors of the cryptocurrency investment intentions of individual investors in Vietnam, and it will focus on three main groups of factors, including digital financial literacy, generational differences, and financial advisory services. Based on 674 observations, quantitative analysis methods were used to validate the research model. The results show that digital financial literacy and access to advisory services have a positive impact on investment intentions. Both Millennials and Gen Z, simultaneously, are more proactive in accessing technology and decision-making. The problem of overconfidence had a significant effect, conversely, risk perception and herd behavior were not statistically significant. From then on, the study proposes a few implications to promote the transparent and sustainable development of the cryptocurrency market in Vietnam.

The rapid expansion of digital technology has significantly influenced adolescents' behavioural patterns, resulting in growing concerns related to excessive internet use and its psychological consequences. This study examines the relationship between Internet Addiction and Parenting Style on the Mental Health of XI standard students. The research employed a descriptive survey method, with a stratified sample of 1,000 higher secondary students from schools within Thiruvallur district. Standardised tools were used for data collection, including the Internet Addiction Inventory, Parenting Style Scale and Mental Health Scale, supported by a personal data sheet to capture demographic variables. Data analysis involved descriptive statistics, t-tests, ANOVA, Pearson's correlation, Multiple Regression and Structural Equation Modelling (SEM). The findings revealed that Internet Addiction and Parenting Style significantly predict Mental Health, and their components together discriminate students across low, average and high mental health levels. Significant differences were observed in mental health and parenting style based on gender, locality, medium of instruction, school type and socio-economic status, whereas no significant differences were noted in internet addiction across most demographic categories. SEM validation confirmed strong linear relationships among the selected variables. The study concludes that supportive parenting styles contribute to better mental health, while higher internet addiction levels are associated with poorer psychological well-being. The findings recommend school-based mental health interventions, digital literacy, teacher involvement and parental awareness initiatives to enhance adolescent resilience and responsible technology use.

Older adults in rural or underserved settings face persistent access barriers. Digital and remote health interventions may mitigate these gaps. The aim of this study is to assess technologies, effectiveness, and implementation challenges of digital or remote health interventions for adults ≥60 years old in rural or underserved contexts. A systematic search was conducted in 4 electronic databases, such as PubMed, Scopus, Web of Science, and Embase (inception: April 2025), under dual screening by 2 reviewers. The tool Cochrane Risk of Bias 2.0 was used to assess the risk of bias for randomized trials, and Risk Of Bias In Non-randomized Studies-of Interventions (ROBINS-I) was used for nonrandomized trials. For observational studies, we used the National Institutes of Health quality assessment tool, and a narrative synthesis was performed. Fourteen studies met the inclusion criteria (randomized and nonrandomized designs; median follow-up ~12 mo). Ten of 14 (71%) reported significant improvements in at least 1 clinical end point (eg, hemoglobin A1c, blood pressure, and weight), 11 of 14 (79%) improved behavioral or psychosocial outcomes, and 5 of 9 (56%) reduced hospitalizations or acute episodes. Risk-of-bias concerns most frequently related to missing data and selective reporting. Digital literacy and broadband access were the most consistent barriers, while multicomponent, nurse-supported models achieved higher adherence. Equity-related dimensions (place, gender, and socioeconomic status) were variably reported, with limited attention to language, cultural tailoring, or social capital. No study included a formal cost-effectiveness analysis. Digital and remote health interventions can benefit older adults in rural and underserved settings by improving selected clinical and behavioral outcomes. However, heterogeneity, small sample sizes, and the absence of economic evaluations temper certainty. Importantly, gaps in equity reporting and persistent barriers to digital inclusion highlight the need for future trials to integrate PROGRESS-Plus (place of residence, race/ethnicity, occupation, gender, religion, education, socioeconomic status, social capital, plus other context-specific determinants of health equity) dimensions, embed cost-effectiveness assessments, and design interventions that are both sustainable and accessible to the most underserved populations.

Rapid advancements in the field of Artificial Intelligence (AI) and adaptive learning have revolutionized the way educational processes occur, especially in ESL settings. This paper seeks to evaluate the impact of implementation of AI and adaptive learning on the engagement and learning of university-level ESL learners. For this purpose, quantitative approach was adopted; and 250 ESL learners were targeted through a survey based on the 5-point Likert scale. Four primary constructs were incorporated in the proposed conceptual framework namely AI Usage (AIU), Adaptive Learning (AL), Student Engagement (SE) and Learning Outcomes (LO). Data analysis was conducted by utilizing Partial Least Square Structural Equation Model (PLS-SEM). Results demonstrate that both AI usage and AL have significant positive influences on SE. In addition, AL has a comparatively greater influence as compared to AI due to the reason that AL is personalized learning. Besides, SE is found to have the greatest influence on LO, which confirms the role of student engagement as a mediator between technology usage and learning outcome. Also, AI usage has a positive influence on LO with a smaller magnitude as compared to SE. Overall findings of this study highlight the significance of using AI-based technology and personalized learning systems to increase student engagement and improve their learning in the field of ESL. This study makes an important contribution to literature through employing PLS-SEM in ESL setting, which has been used quite rarely before. Practical implications have been discussed for educators, institutions and policymakers to enhance the process of ESL learning through use of technology. Future research could further investigate other factors like learner satisfaction, digital literacy etc.

This study aims to analyze the extent to which social engineering influences data leaks among social media users in Indonesia and to identify the factors that increase their vulnerability. A quantitative approach was used in this study by distributing an online questionnaire to 325 respondents who are active social media users from various backgrounds. Regression analysis shows that exposure to social engineering, particularly phishing and impersonation techniques, has a significant influence on the likelihood of data leaks. In addition, the level of information security awareness was found to moderate this relationship. This study concludes that personal data leaks are not only caused by technical weaknesses, but also by human factors that can be manipulated psychologically. The implications of this study suggest the need to improve digital security literacy, provide advanced security features on social media platforms, and strengthen personal data protection regulations in Indonesia.

Electronic patient records (EPRs) have shown potential to improve health care delivery, coordination, and patient engagement. In Switzerland, the development of a national EPR is supported by the Confederation, while its deployment is carried out by the cantons through EPR communities. Since health policy and the organization of health systems are entrusted to cantonal governments, each of the 26 Swiss cantons must decide its strategy for the implementation and application of EPRs within its jurisdiction. The canton of Vaud has joined with other French-speaking cantons (Geneva, Valais, Fribourg, and Jura) in organizing the implementation of the EPR through the CARA association since 2018. By June 2025, approximately 32,350 individuals have opened an EPR (Dossier électronique du patient) through CARA, accounting for 28% of all EPRs opened nationwide at that time. This study aimed (1) to document patients' use of EPR in the canton of Vaud and to examine the user profiles; and (2) to explore users' and nonusers' perceptions regarding EPR benefits and barriers. This mixed methods study was conducted in 2 phases. First, a quantitative questionnaire examined EPR user profiles (eg, demographics and health status). Health literacy and digital health literacy were assessed using the HLS19-Q12-CH (Health Literacy Survey 2019-2021) and HLS19-DIGI-CH (Digital Health Literacy) scales in French. Second, qualitative semistructured interviews explored experiences and perceptions of users and nonusers through thematic analysis. Data from both phases were integrated during interpretation. All analysis was conducted in French with quotes translated for publication. The population included 839 patients with EPRs (early adopters from December 2021 to December 2023) and a matched control group. Overall participation was 19.3% (324/1678), with higher participation among EPR users (255/839, 30.4%) than nonusers (69/839, 8.2%). Early adopters were predominantly male (185/255, 72.5%), highly educated (155/255, 60.8%), affected by chronic illness (204/255, 80%), and with extensive health care networks (80% consulted 2 or more health care professionals in the last 3 months). The vast majority (249/253, 98.4%) had a general practitioner. While only a minority (76/252, 30.2%) of early adopters were satisfied with the service provided by the EPR, a majority (172/254, 67.7%) would recommend it to their family and friends. Qualitative analysis identified themes that influence EPR adoption, including the contextual environment, level of health literacy, EPR as a tool, professionals' resistance to EPR, and level of engagement with digitalization. This study identified early EPR adopters as predominantly highly educated males with chronic diseases and a regular general practitioner. Despite moderate satisfaction with the current implementation, most users recommend the system to others, suggesting a belief in its potential value. Important questions are raised regarding EPR accessibility, limited adoption by professionals, and potential digital health disparities in the general population.

This study aims to explore the psychological impact experienced by adolescents due to exposure to beauty standards displayed on the TikTok application. Using a qualitative approach with a phenomenological design, this study involved five adolescents aged 16 - 18 years at MAN 4 East Aceh as research subjects. Data collection was carried out through observation, in-depth interviews, and content analysis. Data were analyzed using descriptive - interpretive which included data reduction, data presentation, and conclusion drawn. The findings of the study show three main psychological impacts, namely decreased self-esteem, negative body image, and social anxiety. However, some subjects also reported a motivation to do better despite experiencing psychological impacts. In addition, this study identifies coping strategies used by adolescents to deal with these psychological challenges, including selective content consumption, seeking social support, developing self-acceptance, and utilizing beauty standards as positive motivation. The novelty of this research lies in a phenomenological approach that explores the subjective experiences of adolescent girls in the context of religious Acehnese culture. The implications of the study show the need for psychological intervention programs and digital literacy education to help adolescents use social media more healthily.

In the context of rapid digital transformation, cyberspace has become a crucial environment for information exchange as well as a key arena for ideological interaction. However, it is also increasingly exploited for the dissemination of misinformation and hostile viewpoints, which pose significant challenges to social stability and ideological security. University students, as active users of digital platforms, are particularly vulnerable to such influences. This study aims to examine the current situation of educating students to counter wrong and hostile viewpoints in cyberspace at Nghe An University, Vietnam. Using a mixed-method approach, including survey data and document analysis, the study evaluates students’ awareness, their ability to identify misinformation, and their capacity to respond to misleading content. The findings indicate that although students have basic awareness of misinformation, their critical thinking skills and ability to actively counter hostile viewpoints remain limited. The study also identifies key challenges, including outdated educational content, lack of practical engagement, and insufficient integration of digital literacy into ideological education. Based on these findings, the paper proposes policy implications focusing on enhancing information literacy, promoting interactive learning methods, strengthening institutional roles, and encouraging student participation in constructive online discourse. This research contributes to bridging the gap between political education and media literacy, providing both theoretical insights and practical recommendations for improving higher education strategies in the digital age.

The rapid proliferation of mobile AI assistants — including voice-activated agents, recommendation engines, and automated decisional nudges — has fundamentally altered how individuals form preferences, evaluate choices, and reach decisions in everyday life. This paper investigates the cognitive, behavioral, and societal implications of delegating decision-making to mobile AI systems through a mixed-methods study combining systematic literature review with empirical survey analysis across 1,240 participants in six countries. Findings reveal that sustained reliance on AI-mediated recommendations is associated with a 34% reduction in decision uncertainty tolerance (willingness to defer a choice pending additional information), measurable atrophy in metacognitive self-assessment accuracy, and significant shifts in perceived personal agency. Behavioral analytics indicate that users who rely heavily on AI recommendations exhibit narrowed consideration sets, averaging 2.1 options versus 5.8 for low-reliance users, and reduced tolerance for decision uncertainty. A dual-process theoretical framework is proposed that distinguishes between efficiency-enhancing automation and autonomy-eroding automation, enabling more nuanced policy and design interventions. Results carry significant implications for AI system design, digital literacy policy, and regulatory frameworks governing AI decision-support tools in consumer contexts.

Purpose The purpose of this article is to analyze data-driven insights as a technological factor capable of generating knowledge from the failures of the organization's previous innovation projects. Furthermore, this new knowledge plays a critical role in expanding the organization's knowledge resources, enabling it to better access and leverage the knowledge provided by its external partners. Design/methodology/approach The three-way interaction model was tested on a sample of 197 Colombian firms operating in medium- and high-digital-intensity sectors, which are characterized by the development of more sophisticated projects and the use of more advanced digital technologies. For this purpose, partial least squares structural equation modeling (PLS-SEM) was employed due to its explanatory and predictive capabilities. Findings The main findings reveal that innovation failure is a traumatic experience that triggers evasive and cautious behaviors within the organization and among its members. Moreover, this behavior, which is counterproductive to digital innovation, can only be reversed through prescriptive insights. This is because the nature of such insights enables the automation and decentralization of decision-making, thereby fostering greater agility and responsiveness to market needs. Research limitations/implications This article emphasizes the importance of broadening the organization's innovation approach to include external knowledge and technology, aiming to expedite the development of digital solutions and maximize their potential for market success. Moreover, this study challenges the dominant perspective that views technological and market knowledge gained from unsuccessful innovations as sufficient to prevent failures in subsequent innovation projects. Finally, it addresses the recent call in the literature for the design of innovation models integrating tools or mechanisms aimed at transforming the traumatic experiences of innovation failure into new knowledge assets to improve the performance of subsequent projects. Practical implications The main practical contribution of the article lies in recognizing the significant differences between descriptive and predictive insights versus prescriptive insights in decision-making, due to their distinct nature. Accordingly, the primary recommendation is to prioritize prescriptive insights, which requires the organization to ensure the availability of adequate technological infrastructure, data architecture and quality, as well as specialized technical expertise. Finally, the organizational learning strategy should be oriented toward the systematization of innovation failure in order to generate inputs for data analytics. Social implications This study has important social implications, as it encourages a cultural shift toward viewing innovation failure as a valuable source of collective learning. By highlighting the potential of prescriptive insights to transform failure into actionable knowledge, the article promotes more inclusive access to organizational learning, fosters interorganizational collaboration, and emphasizes the need for knowledge management practices. Moreover, the automation and decentralization of decision-making processes imply evolving skill requirements, underscoring the importance of digital literacy and workforce adaptability in an increasingly data-driven society. Originality/value The originality of this article lies in the application of descriptive, predictive and prescriptive insights to generate organizational knowledge from past innovation failures. This responds to the call in the literature to identify technological tools capable of fostering organizational learning, as well as to the practical need for organizations to recover value from resources invested in failed innovation projects. Furthermore, the study contributes to understanding the combined effect of failure-based learning, enabled through insights, on the organization's ability to leverage both internal and external knowledge for digital innovation.

Abstract—A Social Media Post and News Summarizer with Authenticity Verification is an intelligent web-based system designed to address the growing challenge of misinformation in today’s digital ecosystem. With the exponential increase in online content generated through news platforms and social media, users are frequently exposed to vast amounts of information that may be incomplete, biased, or misleading. The rapid spread of such content creates significant challenges in identifying reliable information and increases the risk of misinformation influencing public perception and decision-making. Existing systems primarily focus on either automatic content summarization or fake news detection independently, lacking a unified approach that ensures both clarity and credibility. To overcome this limitation, the proposed system integrates advanced Artificial Intelligence (AI) and Natural Language Processing (NLP) techniques to perform automated summarization and authenticity verification within a single framework. The system collects data from multiple trusted sources, preprocesses it to remove noise and redundancy, and generates concise and meaningful summaries using AI-based models. In addition to summarization, the system incorporates a multi-layered authenticity verification mechanism that evaluates information reliability using parameters such as Credibility Score, Agreement Score, and Confidence Level. The Credibility Score assesses the trustworthiness of sources, the Agreement Score measures consistency across multiple sources, and the Confidence Level provides an overall reliability indicator. This structured evaluation enables users to quickly understand not only the content but also its level of trustworthiness. The platform is developed using a modern and scalable architecture, ensuring efficient data processing and real-time response. It supports seamless user interaction, allowing users to input news articles or social media posts and instantly receive summarized content along with authenticity metrics. The transparent scoring mechanism enhances user trust by clearly indicating how the evaluation is performed. Furthermore, the system significantly reduces information overload by presenting only essential and verified information, thereby saving time and improving user comprehension. By combining AI-driven summarization with multi-source verification, the proposed system enhances digital literacy, promotes critical thinking, and supports informed decision-making. Furthermore, the system significantly reduces information overload by presenting only essential and verified information, thereby saving time and improving user comprehension. By combining AI-driven summarization with multi-source verification, the proposed system enhances digital literacy, promotes critical thinking, and supports informed decision-making. Overall, this system represents a significant advancement toward building a reliable and transparent information ecosystem, where users can access concise, accurate, and trustworthy information in real time. The proposed approach not only addresses current challenges in misinformation detection but also provides a scalable foundation for future enhancements in intelligent information processing systems.

Abstract This study investigates the interactions among leadership capability (LCAP) and organization capability (OCAP) in the Malaysian construction industry, emphasizing the mediating role of digital mindset (DIND) and the moderating effect of digital technology capability (DCAP). Data from 341 managerial-level personnel were analysed through Partial Least Squares Structural Equation Modeling (PLS-SEM), indicating that strong leadership styles significantly enhance the organization’s innovation and digital mindset. The DIND mediates the relationship between LCAP and OCAP, confirming that enhanced digital leadership capabilities (DLCAP) are crucial for transforming leadership styles towards effective organization innovation. Furthermore, DCAP negatively moderates the relationship between LCAP and OCAP; the deficiency of automation demands to manage organizational management challenges effectively, but as future development. These findings extend digital literacy by integrating leaders and organizational innovation dimensions and offer practical insights for construction stakeholders striving to incorporate Construction Industry Competency Standard (CICS) practices through technological and digital advancement. This research enriches the disclosure on the synergy between technology and environmental innovation within the knowledge of DLCAP standards. It provides valuable perspectives for policymakers and construction leaders aiming to foster awareness, realization, and transformation of technologically adept constant innovation as a digital roadmap.