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This study aims to analyze the role of information systems in supporting digital business success, particularly among Small and Medium Enterprises (SMEs), using a Narrative Literature Review (NLR) approach. The review examined various national and international scientific articles obtained from Scopus, ScienceDirect, SpringerLink, and Google Scholar databases published between 2021 and 2025. The findings reveal that information systems play a strategic role in improving operational efficiency, decision-making quality, innovation capability, customer engagement, and organizational competitive advantage in the digital transformation era. Technologies such as Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), cloud computing, Artificial Intelligence (AI), and digital platforms have proven to enhance SME performance and business sustainability. In addition to technological factors, the successful implementation of information systems is influenced by organizational readiness, digital capabilities of human resources, organizational culture, transformational leadership, as well as government support and digital infrastructure. The study also identifies several challenges in SME digitalization, including limited digital literacy, technological readiness, and financial resources. This research contributes theoretically by integrating the perspectives of Resource-Based View (RBV), Dynamic Capability Theory, and Digital Transformation Theory in explaining information systems as strategic organizational resources.

Financial information systems in higher education institutions manage highly sensitive assets, including tuition payments, scholarships, payroll, vendor transactions, budgeting, and institutional financial reporting. Although ISO/IEC 27001:2022 provides a risk-based foundation for establishing an Information Security Management System, its implementation in universities is frequently constrained by fragmented governance, limited resources, complex asset environments, inconsistent managerial commitment, cultural resistance, and limited real-time monitoring capability. This study aims to develop an integrated security evaluation model for campus financial information systems by combining ISO/IEC 27001:2022, Zero Trust Architecture, AI-driven threat detection, security maturity assessment, and human-factor analysis. The study adopts a mixed-method sequential explanatory design integrated with Design Science Research. Quantitative stages include asset identification, risk scoring, ISO 27001 control gap analysis, maturity assessment, Zero Trust readiness assessment, and AI-driven detection readiness assessment. Qualitative stages include document analysis, semi-structured interviews, observation, expert judgment, and thematic analysis to examine organizational, cultural, and behavioral factors influencing security control effectiveness. The proposed outcome is the HEFIS-ISMS Model, an integrated framework consisting of seven layers: ISO 27001 control compliance, risk-based asset protection, security maturity, human and organizational factors, Zero Trust readiness, AI-driven detection readiness, and improvement roadmap. The model is expected to address the static and compliance-oriented limitations of conventional ISO 27001 assessments by introducing adaptive access control, continuous monitoring, anomaly detection readiness, and phased implementation guidance. The study contributes theoretically to cybersecurity governance in higher education and practically to risk-prioritized security improvement for resource-constrained universities.

This study aims to analyze the effect of Knowledge Sharing and Knowledge Leakage on Supply Chain performance, with Monitoring Opportunity as a mediating variable at the Library Office of Mesuji Regency. The research problem arises from the limited structure of knowledge-sharing practices, weak documentation of organizational knowledge, and the potential risk of knowledge leakage that may disrupt the effectiveness of library service supply chains. This study employs a quantitative approach using a survey method. Data were collected through questionnaires distributed to 115 employees of the Library Office of Mesuji Regency and analyzed using Structural Equation Modeling based on Partial Least Squares with SmartPLS. The results show that Knowledge Sharing has a positive and significant effect on Supply Chain performance and Monitoring Opportunity. Knowledge Leakage does not have a significant direct effect on Supply Chain performance, but it has a negative and significant effect on Monitoring Opportunity. Furthermore, Monitoring Opportunity significantly mediates the relationship between Knowledge Sharing and Supply Chain performance, but does not mediate the relationship between Knowledge Leakage and Supply Chain performance. These findings indicate that knowledge sharing becomes more valuable when supported by monitoring capability, while knowledge leakage should be controlled through documentation, access control, and knowledge protection mechanisms. This study contributes to knowledge management and supply chain literature in public library service organizations.

The rapid proliferation of learning analytics, business intelligence (BI), artificial intelligence (AI), and generative AI (GenAI) has significantly expanded universities’ ability to collect, integrate, analyze, and operationalize institutional data. However, despite advances in predictive analytics, dashboards, and AI-driven systems, the translation of analytical outputs into consistent and accountable institutional decision-making remains uneven. This systematic literature review synthesizes contemporary research on analytics-enabled decision-making in higher education with the aim of moving beyond dashboard-centric perspectives toward a socio-technical and computing-oriented understanding of how data are transformed into institutional actions and outcomes. Guided by the PRISMA framework, the review synthesizes evidence across four interconnected dimensions: data ecosystems and learning analytics foundations; analytics capability, BI adoption, and digital readiness; AI and advanced analytics for decision support; and human-in-the-loop (HITL) decision routines and institutional outcomes. The findings show that predictive performance and analytical sophistication alone do not guarantee decision value. Instead, effective analytics-enabled decision-making depends on interoperable data ecosystems, organizational analytics capability, governance mechanisms, explainability, and sustained human oversight. Based on these findings, this review contributes a computing-oriented decision-intelligence framework that conceptualizes analytics-enabled decision-making as an end-to-end socio-technical pipeline linking heterogeneous data acquisition, integration, feature construction, analytical modeling, explainability, human validation, governance, and feedback-based refinement. By integrating learning analytics, BI, AI, GenAI, and HITL mechanisms within a unified framework, the review clarifies how universities can move beyond dashboard-based reporting toward accountable, adaptive, and institutionally actionable decision-support infrastructures.

This study aims to investigate the determinants of job performance by integrating the variables of capability, social interaction, and Organizational Citizenship Behavior (OCB) as a moderating variable. The phenomenon of employee turnover and discrepancies in staff discretionary behavior within the hospital setting serves as the primary rationale for this study. Using a quantitative approach, data were collected from 240 respondents at Magelang City Islamic Hospital through purposive sampling. Data analysis was conducted using Structural Equation Modeling (SEM) based on AMOS software to test the causal relationships among variables in the structural model. The research findings provide empirical confirmation that individual capabilities and the quality of social inter-actions have a positive and significant influence on stimulating the formation of OCB. Furthermore, statistical test results demonstrate that capabilities, social interactions, and OCB simultaneously make a significant contribution to improving employee work performance. The presence of OCB is identified as a crucial factor capable of strengthening organizational performance outcomes. The practical implications of this study emphasize the need for hospital management to formulate human resource development strategies focused on strengthening technical skills and social cohesion to mit-igate the impact of turnover and accelerate the sustainable performance of healthcare services.

This study explores the role of Business Intelligence (BI) in improving operational effectiveness and company performance amid rapid digital transformation, big data, Artificial Intelligence (AI), and data analytics development. Using a Narrative Literature Review (NLR) approach, this study analyzed 48 national and international scientific articles related to BI, firm performance, digital transformation, and big data analytics. The findings reveal that BI positively influences decision-making quality, operational efficiency, organizational agility, innovation capability, marketing effectiveness, customer relationship management, and competitive advantage. Furthermore, integrating BI with Big Data Analytics, predictive analytics, machine learning, and AI enhances organizational responsiveness to dynamic business environments. The study also identifies key success factors for BI implementation, including organizational readiness, management support, technological infrastructure, information quality, and system integration. These findings indicate that BI has evolved from a technological tool into a strategic organizational capability that supports sustainable business performance and digital transformation. This study contributes to the Business Intelligence literature by providing a comprehensive understanding of BI’s strategic role across various industries and organizational contexts.

This research investigates the effectiveness of container cargo information management systems at Indonesian ports, examining the critical roles of competency training, shore-based personnel capabilities, and technology adoption in determining system performance and operational outcomes. Container terminals increasingly rely on sophisticated information systems including Terminal Operating Systems (TOS), Port Community Systems (PCS), and Electronic Data Interchange (EDI) for coordinating complex cargo operations, yet system effectiveness depends not solely on technology sophistication but critically on personnel competency, training adequacy, and human-technology integration. Through qualitative analysis involving terminal operators, port information system managers, shore-based operational personnel, training coordinators, and technology providers, this study examines how the interplay between human capabilities and technological capabilities determines information system effectiveness. Results demonstrate that comprehensive competency training programs can improve system utilization effectiveness by 45-65%, reduce operational errors by 50-70%, and enhance productivity by 25-40% through better human-technology integration. Key challenges include inadequate training investment, high personnel turnover, technology complexity exceeding user capabilities, and organizational resistance to systematic training programs. Findings reveal that container terminal information system effectiveness depends fundamentally on sociotechnical system optimization addressing both technological infrastructure and human capability development through sustained competency building programs. This research contributes to port operations literature by providing evidence-based frameworks for human factors integration in port technology implementation.

This systematic review maps how innovation, technology adoption, and Islamic entrepreneurial behaviors are intertwined and contribute to the SDGs. Searches in Scopus followed PRISMA 2020: of the 166 initial records, 46 were eliminated prior to screening; 120 filtered by title–abstract; 45 read in full; and 25 articles were analyzed in depth. Four RQs lead the synthesis: the form of innovation/adoption (RQ1), impact on behavior and performance (RQ2), and their relationship to the SDGs (RQ3). The findings show five complementary faces of innovation: (1) process-organization (knowledge management, open innovation; innovation capability), (2) sharia business/finance models (sharia venture capital, agricultural value chain finance), (3) financial and platform digitalization (fintech, Islamic crowdfunding), (4) technological innovation in business models (e.g., urban farming–aquaponics) that are value-framed, and (5) halal product/marketing innovation (halal assurance and halal trust). Behind that, the drivers are layered: individual values and psychology, Islamic HRM cultural orientation and organizational learning, Islamic finance architecture and regulation, and access to digital literacy and trust in the platform. The impact is multidimensional performance, access to ethical capital, halal market behavior, and social and religious environmental outcomes with strong contributions to SDG 8 and SDG 9, and footprints on SDGs 1–2, 3, 10, 11, 12, 13, 16, 17. This SLR offers an integrated financial innovation value framework and proposes SDGs micro-indicators; limitations mainly in the variation of measurements and the dominance of cross-section designs.

The strategic role of SMEs in the Indonesian economy and the phenomena of declining performance as a result of the Covid-19 pandemic motivated author to research this sector. Various internal problems make it difficult for SMEs to improve their performance and competitiveness in a competitive business environment. Using the dynamic capability perspective, this study examines the influence of human resource configuration through employee training and organizational culture which is able to encourage innovation that improves SME performance. This study uses purposive sampling technique and data collection is done through questionnaires and interviews with 122 SMEs in East Java. Data analysis is carried out using PLS SEM. The research results show that employee training does not have a direct effect on SME performance, however employee training is able to encourage innovation which has an impact on improving SME performance On the other hand, organizational culture has a significant direct and indirect effect on SME performance trough innovation. Results of this study can be used as a consideration by SME owners in making business decisions in order to improve their performance. From the theoretical side, the results of this study confirm the dynamic capability theory by Teece and Pisano regarding the key role of innovation and Becker's opinion from a human resource management perspective which states that employee training must be designed systematically according to the long-term needs of the organization in order to have an impact on improving organizational performance.

Rapid technological change in the digital era has reshaped the nature of organizational innovation, requiring firms not only to innovate but also to align their innovation activities with technological developments and market dynamics, a capability referred to as Techno-Resonance Innovation Capability (TRIC). Although Knowledge Management (KM) has been widely recognized as a driver of innovation, studies that explicitly link KM to the development of techno-resonant innovation remain limited. This study aims to address this gap by systematically reviewing the literature to examine how KM contributes to innovation capability and how this relationship evolves toward TRIC through absorptive capacity. Using the systematic literature review methodology proposed by Tranfield et al., this study follows three stages planning, conducting, and reporting the review to identify, evaluate, and synthesize relevant studies on KM, absorptive capacity, innovation capability, and techno-resonance. The findings indicate that innovation capability emerges from interconnected KM processes, including knowledge acquisition, sharing, storage, and application, which form the organizational infrastructure for innovation. Absorptive capacity is identified as a key bridging mechanism that enables organizations to transform managed knowledge into innovative outcomes by enhancing their ability to acquire, assimilate, transform, and exploit technological knowledge. This study concludes that integrating KM and TRIC through absorptive capacity extends conventional innovation capability models and provides a stronger theoretical explanation of innovation in technology-driven and digitally dynamic environments.

This research investigates the development of IT-based Automatic Identification System (AIS) data surveillance models supporting maritime safety through integration of advanced information technology, maritime engineering principles, and human factors optimization. AIS technology generates vast real-time vessel movement data creating unprecedented opportunities for safety enhancement through systematic surveillance, collision risk detection, traffic pattern analysis, and incident prevention, yet effectiveness depends critically on intelligent data processing algorithms, reliable IT infrastructure, and competent personnel capable of interpreting surveillance outputs and taking appropriate actions. Through qualitative analysis involving maritime safety authorities, vessel traffic service (VTS) operators, port authorities, marine engineers, IT specialists, data scientists, and maritime training institutions, this study examines how IT-based surveillance models incorporating pattern recognition, anomaly detection, predictive analytics, and crew-centered interfaces can transform maritime safety management from reactive incident response toward proactive risk prevention. Results demonstrate that intelligent AIS surveillance can identify 75-90% of high-risk situations 15-45 minutes before critical events, reduce collision risks by 60-80%, improve traffic management efficiency by 35-55%, and enhance crew situational awareness by 45-65% when integrated with appropriate training programs developing personnel competencies in data interpretation, system operation, and coordinated response. Key implementation challenges include data quality and completeness issues, computational infrastructure requirements, algorithm development complexity, personnel competency gaps requiring substantial training investments, organizational coordination barriers, and privacy/security concerns. Findings reveal that successful AIS surveillance implementation requires holistic sociotechnical approaches integrating IT systems engineering, maritime domain expertise, and human capability development through coordinated design, deployment, and training strategies. This research contributes to maritime safety literature by providing integrated frameworks for IT-based surveillance systems incorporating technical capabilities, operational requirements, and human factors supporting evidence-based safety management.

The rapidly changing and increasingly uncertain business environment presents significant challenges for micro, small, and medium enterprises (MSMEs), requiring them to adapt quickly and strategically to survive and remain competitive. This conceptual article examines the role of business models as an effective adaptation strategy for MSMEs in responding to dynamic market conditions, technological change, and shifting consumer preferences. Through a comprehensive review of various business model frameworks and dynamic capability theories, this study emphasizes that business models play a crucial role in shaping organizational flexibility and strategic responsiveness. The findings highlight that adaptable value propositions enable MSMEs to continuously align their offerings with evolving customer needs, while agile resource management allows firms to efficiently reconfigure internal and external resources. Furthermore, continuous business model innovation and renewal are identified as essential mechanisms for sustaining long-term resilience and competitiveness. The article argues that a business model should not be viewed merely as an operational or administrative tool, but rather as a core strategic mechanism that integrates strategic vision, organizational capabilities, and market orientation. By actively leveraging flexible and innovative business models, MSMEs can enhance their adaptive capacity, mitigate environmental uncertainty, and achieve sustainable competitive advantage in rapidly changing business environments.

Information technology (IT) governance plays a strategic role in supporting the achievement of organizational goals, especially in higher education institutions. Adiwangsa University Jambi, as a private university, is required to manage IT effectively, efficiently, and in line with the institution's vision. This study aims to analyze the level of IT governance capabilities at Adiwangsa Jambi University using the COBIT 2019 framework with a focus on the EDM (Evaluate, Direct, Monitor) domain. The research method used is a descriptive quantitative method through data collection using questionnaires, interviews, and documentation studies. The results show that the level of IT governance capability in the EDM domain is at level 2 (Managed Process), indicating that the IT governance process is running but still needs improvement in several aspects, especially in monitoring and controlling IT performance. This study is expected to provide recommendations for Adiwangsa University Jambi in improving IT governance in a sustainable manner.

This qualitative literature review synthesizes interdisciplinary research on how employees’ technological sensing capabilities shape generative artificial intelligence (GenAI) capabilities and innovative work behavior. Drawing on dynamic capabilities theory, microfoundations of sensing, and human–AI interaction literature, the review integrates findings from management, information systems, and innovation studies. The synthesis reveals that technological sensing—employees’ ability to identify, interpret, and anticipate emerging technologies—does not directly translate into innovation, but operates through the development of distinct GenAI capabilities. In particular, GenAI evaluation capability consistently emerges as a stronger driver of innovative work behavior than GenAI usage capability alone, as it enables critical judgment, contextualization, and creative recombination of AI-generated outputs. The review further highlights contextual moderators such as leadership support, task complexity, and organizational climate. Overall, the study advances theory by positioning individual sensing as a microfoundation of AI-enabled innovation and offers implications for organizations seeking to leverage GenAI beyond efficiency gains.

The integration of Artificial Intelligence (AI) into Human Resource Management (HRM) is accelerating and reshaping how organizations attract, develop, manage, and retain talent. Despite abundant case examples and growing practitioner interest, academic findings remain fragmented regarding the antecedents (drivers), impediments (barriers), and organizational effects (outcomes) of AI-based HR transformation. This paper presents a PRISMA-guided systematic literature review of 112 peer-reviewed articles (2015–2025) to synthesize empirical and conceptual evidence on AI in HRM. Results identify three primary drivers: technological capability, strategic alignment, and a data-driven culture; three critical barriers: ethical concerns (bias, privacy, and transparency), skill and capability gaps, and resistance to change; and three outcome clusters: operational efficiency, enhanced employee experience, and elevated strategic HR contribution. We propose a socio-technical conceptual framework that models drivers moderated by barriers to outcomes, and we advance a research agenda focused on ethical governance, human–AI collaboration, capability measurement, and longitudinal evaluation. The review contributes to theory by integrating socio-technical and dynamic capability  perspectives and provides actionable guidance for HR leaders on responsible AI adoption.

This research is a Systematic Literature Review (SLR) that aims to identify, analyze, and synthesize scientific literature related to effective facilitation strategies in the context of organizational capability development and employee learning improvement. The main focus of this research is to map various forms of facilitation interventions, assess their impact on organizational capabilities such as innovation, adaptability, and efficiency, and explore the role of facilitation in strengthening organizational and individual learning mechanisms. By using an SLR approach that follows the guidelines of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), this study ensures transparency and replication of the study process. The results of the synthesis show that facilitation strategies contribute significantly to improving organizational capabilities through the creation of a collaborative learning environment, strengthening communication, and improving employees' adaptive skills. In addition, facilitation has been proven to support the integration of new knowledge into organizational practices, thereby strengthening competitiveness and sustainability. These findings are expected to provide evidence-based guidance for practitioners in designing effective facilitation interventions, as well as a theoretical basis for future researchers to develop studies on the relationship between facilitation, learning, and organizational capabilities.

Digital transformation has become a major driver in enhancing the competitiveness of Micro, Small, and Medium Enterprises (MSMEs) in the era of global competition. However, scientific evidence regarding the pathway of digital transformation and its impact on market performance remains separately distributed and has not been systematically synthesized. This study conducts a Systematic Literature Review (SLR) based on PRISMA 2020 on international publications within the 2013–2024 range. The results of the analysis indicate that the digital transformation pathway encompasses digital capability, digital orientation, digital integration, digital strategy alignment, and the utilization of operational technology. Each pathway contributes differently to market outcomes such as sales growth, customer retention, market expansion, and competitive advantage. The study also found the presence of moderating and mediating roles through innovation capability, dynamic capability, organizational culture, and competition intensity. This research produces an integrated conceptual model and recommendations for a further research agenda to deepen strategic management theory in the context of MSMEs.

The purpose of this research is to determine the influence of knowledge sharing and innovative work behavior on organizational innovation capability. This research design uses a quantitative approach with a survey method. This approach is used to measure the influence of knowledge sharing variables and innovative work behavior on innovation capability. This research was conducted at the PDAM Kolaka Regency office, Southeast Sulawesi Province. The population of this study was 30 employees of PDAM Kolaka Regency, Southeast Sulawesi Province. In this research, primary data sources are used in the form of survey results by distributing questionnaires to obtain information and responses related to knowledge variables, innovative work behavior and employee innovation capabilities. To test the hypothesis, this research uses PLS-SEM with the help of the Smart-PLS version 3.0 application.  The research results show that there is no influence between knowledge sharing and innovative work behavior on organizational innovation capability .  

Goals – Goals from studies This is For explore approach strategic in development System Information Management (SIM) as integral part in support digital transformation of modern organizations. Study This emphasize importance integration technology information , effective data management as well as improvement digital competence resources Power man in operation system. Design/ methodology / approach – Conceptual article This use method review library with analyze various work relevant academic and technical manuals , in particular related implementation of SIM in the sector public and private . Study This referring to the works Jatnika et al. (2022–2024), including utilization Microsoft Office applications as skills supporting basis​ organizational digital literacy . Findings – Findings studies This show that SIM development is not just effort technical , but rather need strategic in support digital transformation . Key strategies covers design modular systems , data mining integration , training programs based users , and evaluation system in a way periodic . Components This allows organization build responsive and adaptive SIM ecosystem . Implications practical – Organizations that want to do digital transformation is necessary invest in development digital capabilities of sources Power the human as well as ensure effectiveness use developed SIM system in a way strategic can become driving force main in increase efficiency , accuracy , and capability taking decision across work units . Originality / value – Study This offers a conceptual model structured about development of SIM in context digital transformation , based on literature applications and needs organizations in the real world . This article give outlook practical for taker policy , IT managers , and HR developers .  

Digital transformation has changed the way modern organizations measure their success, but traditional performance measurement models have not fully adapted to the needs of the digital age. This study conducted a systematic literature review of 25 high-quality publications from the Scopus, Web of Science, and Emerald Insight databases to identify models and indicators of organizational performance measurement in the digital era. Using the PRISMA 2020 framework and strict inclusion-exclusion protocols, this study analyzes research from the period 2021-2025 with a focus on the integration of the digital dimension in the performance measurement framework. Key findings identify 13 categories of key indicators that consistently appear in the literature, including financial performance, operational efficiency, innovation performance, digital transformation readiness, customer experience, and employee digital capability. The analysis of influence mechanisms found three ways in which digital transformation affects performance: direct effects, mediating effects through dynamic capability and organizational agility, and moderation effects from contextual and organizational cultural factors. The research proposes a three-level integrative framework (strategic, operational, and individual-cultural) that can be differentially adapted according to the size of the organization and the industry sector. The theoretical contribution of this research enriches the academic literature with a systematic synthesis of digital performance measurement, while practical contribution provides evidence-based guidance for organizations in designing a comprehensive performance measurement system that is responsive to the evolving dynamics of digital transformation.