Challenges of Digital Services in Public Administration in the Era of Digital Transformation: A Systematic Literature Review

Green innovation in a digital transformation context: implications of green social capital and green creativity.

The integration of Artificial Intelligence (AI) in education is increasingly urgent in the era of digital transformation, yet AI literacy levels among Indonesian educators remain insufficiently mapped. This study aims to analyse AI literacy levels among primary and secondary school teachers in the context of digital teaching material development in Yogyakarta. Using a descriptive-qualitative design with an observational approach, the study involved 161 educators across educational levels observed during four AI, AR, and VR workshop sessions in Yogyakarta. Data were collected through structured observation and field notes, and analysed using reflexive thematic analysis. Results revealed significant differences in generative AI exposure: all teachers with less than five years of teaching experience (49 teachers, 100%) had been exposed to generative AI, while 72.32% of senior teachers (81 out of 112) had comparable exposure. Thematic analysis identified three main themes: (1) varying patterns of AI exposure and technology readiness, (2) barriers to AI adoption encompassing infrastructure, mindset, and competency factors, and (3) preferences for practice-based training. These findings are interpreted through the Technology Acceptance Model (TAM) and Diffusion of Innovation frameworks, contributing to theoretical understanding of intergenerational gaps in educational technology adoption in Indonesia.

This study aims to analyze the effect of human resource (HR) development strategies on the competitiveness of higher education institutions in the era of digital transformation. The increasingly dynamic educational environment, characterized by the integration of digital technologies, requires universities to have adaptive, innovative, and competent human resources. This research employs a quantitative approach with an ex post facto design, involving lecturers and educational staff as respondents. Data were collected through questionnaires that had been tested for validity and reliability. Data analysis was conducted using linear regression to determine the relationship and influence between variables. The results indicate that HR development strategies, including digital-based training, enhancement of technological competencies, and strengthening of organizational culture, have a positive and significant effect on the competitiveness of higher education institutions. Universities that systematically and sustainably develop their human resources tend to be more competitive in facing global challenges, improving the quality of educational services, and strengthening institutional reputation. In addition, digital transformation acts as a supporting variable that strengthens the relationship between HR development and organizational competitiveness. The findings highlight the importance of formulating integrated HR development strategies aligned with institutional digitalization policies to achieve sustainable competitive advantage.

Abstract— In the era of digital transformation in education, providing real-time, personalized guidance to prospective students remains a significant challenge for large universities. This paper presents PU Buddy, an AI-powered Education Career Guidance Chatbot designed specifically for Parul University, Vadodara. The system leverages the Google Gemini 2.0 Flash large language model (LLM) through the OpenRouter API to provide accurate, context-aware responses about courses, fees, hostel facilities, scholarships, admissions, and campus life. The chatbot is built usinga Flask (Python) backend and a modern HTML/CSS/JavaScript frontend, incorporating advanced features such as multimodal image analysis, voice-to-text input via the Web Speech API, session-based conversation management, and structured HTML table outputs for data-rich queries. A comprehensive knowledge base derived from the official Parul University 2025–26 Brochure is embedded as a system prompt to ensure domain-restricted, hallucination-free responses. Evaluation results indicate that PU Buddy successfully reduces student inquiry response times by an estimated 85%, handles parallel sessions with contextual continuity, and gracefully degrades to a fallback offline guide when API limits are exceeded. The system also includes a pixel-perfect university website clone with 570+ pages, serving as a standalone digital information platform. This pap. Keywords - AI Chatbot, Career Guidance, Large Language Models (LLM), Natural Language Processing (NLP), Flask, Gemini 2.0, OpenRouter API, Education Technology (EdTech), Parul University, Multimodal AI

This research is motivated by obstacles in the implementation of character education at SMP Negeri 1 Loceret, particularly in the aspect of learning media that is less innovative in the era of digital transformation. The focus of this research is to develop Normapedia interactive media integrated with the SATRIA BAIK (One Day Three Goodness) program to strengthen students' moral actions in a real way. Using the Research and Development method with the ADDIE development model, this research goes through the stages of analysis, design, development, implementation, and comprehensive evaluation. The results of the validity test show a very high level of product feasibility reaching 91.87%, covering aspects of material, character, and media design. In the effectiveness test stage on 32 students, a significant increase in moral actions was found with an average score that jumped from 65.12 in the pretest to 84.56 in the posttest. This increase of 19.44 points is supported by an N-gain value of 0.71 which is in the high category and a significance of 0.000. Qualitatively, this program succeeded in increasing discipline consistency by 87% and social empathy by 81%. The main conclusion confirms that the synergy between interactive normative content and digital daily reflection features effectively builds a measurable and sustainable moral habitus. This innovation bridges the gap between students' understanding of ethical theory and their daily behavioral practices in a junior high school environment through the systematic use of technology. This medium supports the creation of a generation of intelligent and high-integrity learners.

The rapid advancement of artificial intelligence (AI) technologies has significantly reshaped educational systems and learning environments worldwide. In particular, the integration of AI into language education has created new opportunities for improving learning efficiency, enhancing personalized instruction, and facilitating interactive communication environments. In the context of globalization and international talent development, the ability to communicate effectively in English has become an essential competence for participating in global economic, cultural, and technological exchanges. However, traditional language education models often rely on teacher-centered instruction and standardized assessments, which may not fully address the diverse learning needs of students or provide sufficient opportunities for authentic communication practice. This study explores the role of artificial intelligence in empowering the development of English competence for international talents. Drawing upon theories of technology-enhanced learning, intelligent tutoring systems, and global competence development, the paper proposes a conceptual framework that illustrates how AI technologies can support language learning through multiple application scenarios. These scenarios include intelligent language tutoring systems, AI-mediated communication environments, automated language assessment systems, and data-driven learning analytics. Based on these application scenarios, the study further proposes an AI-empowered educational model that integrates artificial intelligence technologies with innovative pedagogical approaches to support the cultivation of international talents. The model emphasizes personalized learning pathways, adaptive instruction, and global communication platforms supported by AI systems. The study contributes to theoretical discussions on AI-supported language education and provides practical insights for cultivating internationally competitive talents in the era of digital transformation.

The integration of artificial intelligence into pharmaceutical research has ushered in a transformative era for drug discovery and development. Among various deep learning architectures, Convolutional Neural Networks (CNNs) have emerged as particularly powerful tools for modeling complex biological and chemical data. This paper provides a comprehensive review of CNN-based approaches in drug discovery, examining their applications in drug-target interaction prediction, adverse drug reaction forecasting, and de novo drug design. Through a systematic analysis of recent literature and experimental studies, we demonstrate that CNN architectures achieve superior performance across multiple pharmaceutical applications, with drug-target interaction prediction accuracies reaching 93-95% and adverse drug reaction detection rates of 78%. The review synthesizes findings from 2018-2025, highlighting how CNNs effectively extract spatial patterns from molecular representations, identify critical features from protein sequences, and integrate with complementary architectures such as graph neural networks and long short-term memory networks. We also address key challenges including data quality limitations, model interpretability concerns, and regulatory integration pathways. This paper concludes by outlining future research directions, emphasizing the potential of hybrid architectures, multi-modal learning, and explainable AI in advancing CNN-driven drug discovery toward clinical implementation.

In the current era of rapid urbanization and digital transformation, the efficient use of electrical energy has become an essential factor in promoting sustainable living and industrial development. The Intelligent Energy Meter with Alerting System using Arduino Uno and IoT technology is designed to provide users with real-time monitoring, control, and management of electrical power consumption. The proposed system continuously measures the power usage of household or industrial appliances and transmits the data to an IoT-based cloud platform for analysis, visualization, and reporting. The Arduino Uno serves as the central processing unit that collects data from voltage and current sensors such as the ACS712current sensor and a voltage divider circuit, calculates the power consumption, and communicates with an IoT Wi-Fi module (ESP8266) to upload the data online. When the energy usage exceeds a predefined threshold, the system automaticallygenerates alerts to the user through IoT-based notifications or buzzer indications. This threshold-based cost management mechanism helps prevent unnecessary energy wastage and high electricity bills. The system can also control or automate appliances based on user-defined parameters, thereby improving energy efficiency. Furthermore, users can remotely access detailed energy consumption analytics through the IoT platform, which provides insights into load patterns, daily or monthly usage reports, and anomaly detection. Overall, the proposedsystem enables proactive energy management, encourages conservation, and contributes to the vision of smart homes and smart grids. It represents an economical and scalable solution adaptable to both residential and industrial environments.

Abstract In the era of digital transformation, organizations increasingly rely on Business Analytics Capabilities (BAC) to enhance decision-making and improve customer-centric strategies. Customer Relationship Management (CRM) effectiveness is critical for achieving customer satisfaction, retention, and long-term profitability. This study examines the predictive impact of Business Analytics Capabilities on CRM effectiveness, using primary data collected from employees in analytics and customer management functions. A structured questionnaire was administered to 120 respondents across the service and retail sectors Customers. Regression analysis was employed to evaluate the relationship between analytics capabilities and CRM outcomes. The findings reveal that data management capability, analytical skills, and technology infrastructure significantly predict CRM effectiveness. The study contributes to the existing literature by providing empirical evidence of the strategic role of analytics capabilities in strengthening CRM performance. Managerial implications and future research directions are discussed. Keywords: Business Analytics, CRM Effectiveness, Predictive Modelling, Data Analytics Capability, Customer Management, Primary Data

The rapid advancement of technology has significantly transformed the hospitality industry, necessitating the development of innovative solutions that enhance customer experience and operational efficiency. This research report presents the design and development of an Online Hotel Reservation System (OHRS), aimed at revolutionizing the booking process for both consumers and hotel operators. The study begins with a comprehensive analysis of existing reservation systems, followed by a clear outline of the functional and non-functional requirements derived from user feedback and market trends. The design phase encompasses the formulation of a user-centric interface that facilitates easy navigation, real-time availability checks, and streamlined booking processes. Through the application of agile development methodologies, the system was iteratively developed, allowing for continuous testing and refinement. Key features of the OHRS include integrated payment processing, customizable booking options, and a robust backend management system for hotel staff, which collectively enhance user engagement and operational oversight. This report also examines the testing procedures employed to ensure system reliability, usability, and performance under various conditions. Findings indicate that the OHRS significantly improves the efficiency of hotel operations while providing customers with a seamless and satisfying booking experience. Furthermore, the anticipated impact on customer satisfaction and business growth underscores the relevance of digital solutions in the contemporary hospitality market. Ultimately, this research contributes valuable insights into the design principles and technological considerations essential for developing effective online reservation systems in the future. In the era of digital transformation, the hospitality industry is increasingly leveraging technology to improve customer service and operational efficiency. This research report details the design and development of an Online Hotel Reservation System (OHRS), aimed at streamlining the reservation process for guests and enhancing management capabilities for hotel operators. The study begins with an identification of key challenges within traditional reservation systems, including limitations in accessibility, user experience, and data management. Through a structured methodology, the project establishes a robust framework for the OHRS encompassing user interface design, database management, and integration of payment systems. The system was developed following modern software engineering practices, ensuring scalability, security, and responsiveness across various devices. Notable features include real-time room availability updates, user authentication, customizable booking options, and comprehensive backend analytics tools for hotel management. The effectiveness of the system was evaluated through rigorous user testing and feedback collections, which demonstrated significant improvements in user satisfaction and booking efficiency compared to existing frameworks. Findings indicate that the OHRS not only enhances the booking experience for customers but also equips hotel administrators with vital insights to optimize operations and marketing strategies. This research serves as a vital contribution to the ongoing evolution of hospitality technology, providing a reference point for future developments in online reservation systems. By addressing the needs of both consumers and service providers, the OHRS aims to set a new standard in hotel reservation practices.

The longitudinal relationships between Internet adaptability and usage behavior on AI-driven healthcare platforms: A cross-lagged panel network analysis.

Complex global food chains and rising demand for high-quality halal product requires better and more efficient management. Traditionally, the Halal Assurance System (HAS) and Quality Management System (QMS) have been implemented separately, resulting in overlapping processes and redundant documentation. In the era of digital transformation and Industry 4.0, integrating these systems digitally improves traceability, compliance, and overall organization’s performance. This review aimed to examine current trends, technologies, and research gaps related to the digitalization of integrated Halal and Quality Management Systems (HAS–QMS). A comprehensive literature analysis highlights the role of emerging technologies—such as blockchain, the Internet of Things (IoT), artificial intelligence (AI), cloud computing, and big data analytics—in supporting halal integrity and quality assurance across the food value chain. The findings indicated that digital integration facilitates real-time monitoring, automated documentation, and improved audit readiness. However, challenges persist in areas such as data interoperability, standard harmonization, regulatory acceptance, and the digital readiness of small and medium enterprises. The paper proposed a conceptual framework for the digitalized integration of HAS and QMS, aligning technological capabilities with halal and quality compliance requirements. To align with industry 5.0, future research should standardize models, test performance, and integrate sustainability and ethical standards.

With the increasing deployment of 5G private networks in smart manufacturing, transportation, and IoT environments, the high performance of these networks has also introduced new cybersecurity challenges. The convergence of Information Technology (IT), Operational Technology (OT), and Communication Technology (CT) significantly expands the attack surface and exposes systems to cross-domain threats such as rogue base station infiltration, distributed denial-of-service (DDoS) attacks, and lateral movement. These attacks threaten data integrity, service continuity, and user privacy. To address these issues, this study applies the MITRE FiGHT threat model to depict representative attack stages—including reconnaissance, intrusion, lateral propagation, and service disruption—and integrates CVSS 3.1 scoring with corresponding mitigation strategies. Based on these components, we construct an analytical workflow capable of quantifying risks, identifying governance deficiencies, and guiding targeted improvements. A prototype Cybersecurity Governance Maturity Model (CSGMM) tailored for 5G private networks is subsequently proposed. The proposed framework incorporates six governance domains—policy, asset management, risk defense, incident response, control practices, and supply chain management—and formalizes a three-tier structure covering strategic, tactical, and operational layers. It also defines twenty-five practice objectives aligned with international standards such as ISO/IEC 27002 and NIST CSF 2.0, improving both applicability and interoperability. Experimental validation was conducted using a Free5GC and UERANSIM testbed to simulate practical attack scenarios, including traffic-based DDoS and endpoint-level exploitation. The results show that the implementation of the governance framework, together with FiGHT-based mitigation strategies, leads to a measurable reduction in CVSS risk scores and attack success probability. These findings demonstrate that integrating governance mechanisms with technical defense measures enhances incident response, strengthens network resilience, and supports continuous security management throughout the lifecycle of 5G private network deployment. The proposed model provides a structured reference for both industry and government seeking to advance 5G cybersecurity strategies. It offers practical value for smart manufacturing and other mission-critical applications, supporting organizations in addressing increasingly complex cyber threats in the era of digital transformation.

In the era of digital transformation, vocational high school students must possess strong learning motivation to master essential technical competencies. However, fluctuations in motivation are often driven by how effectively students manage digital literacy, utilize their learning environment, and receive moral support from their families. This study aims to analyze the levels of digital literacy competence, learning environment utilization, parental support, and learning motivation among vocational high school students, while examining the partial and simultaneous influences of these factors on motivation. Employing a quantitative approach with an ex post facto design, the research sampled 150 11th-grade Computer and Network Engineering students from three public vocational schools in Makassar City, selected via proportional random sampling. Data were collected using validated Likert-scale questionnaires and analyzed through descriptive and associative regression techniques. Findings indicate that all variables—digital literacy, learning environment, parental support, and learning motivation—fall within the high to very high categories (65%–80%). Partially, digital literacy (R2=0.585), learning environment (R2=0.262), and parental support (R^2=0.575) significantly affect motivation. Simultaneously, these variables contribute 71.7% to learning motivation (F_count=123.423 > F_table=2.67), with parental support emerging as the most dominant factor (β=0.781). This study underscores that enhancing vocational motivation requires a synergy between digital proficiency and active parental involvement. Consequently, schools should develop integrated digital literacy programs that foster stronger parental participation to optimize student engagement.

Lecturer innovation is a strategic factor in improving the quality of learning, research productivity, and competitiveness of higher education institutions in the era of digital transformation. However, empirical studies on the determinants of lecturer innovation are still scattered and have not been comprehensively integrated. This study aims to systematically synthesize international literature on the role of information technology (IT) literacy, self-efficacy, achievement motivation, and knowledge management in enhancing lecturer innovation. The study used a Systematic Literature Review (SLR) approach with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Articles were obtained from the Scopus database for the period 2010–2025. After going through the processes of identification, screening, eligibility, and inclusion, a total of 46 empirical articles were analyzed thematically. The results of the study indicate that IT literacy increases the capacity for digital pedagogical innovation; self-efficacy strengthens the courage to experiment and adapt to change; achievement motivation encourages innovative performance orientation; while knowledge management acts as an institutional reinforcement that integrates individual innovation into the organizational system. This study produces an integrative conceptual framework that positions knowledge management as a structural enabler and psychological factors as proximal drivers of lecturer innovation. These findings provide theoretical contributions and strategic implications for the development of higher education policies based on sustainable innovation.

In the era of digital transformation, the utilization of information technology in business activities has become an important factor in improving operational efficiency and effectiveness. Dzikri Baby Shop, a business engaged in the sale of baby equipment, still faces challenges in managing sales transactions and inventory manually, which may lead to recording errors, process delays, and less optimal customer service. This study aims to design and develop a sales information system for Dzikri Baby Shop to support digital transformation in its business processes. The system development method used in this research is Rapid Application Development (RAD), as it enables software to be developed in a relatively short time through an iterative approach and active user involvement. The system developed includes product data management, sales transaction processing, inventory control, and report generation. The testing results using the Black Box Testing method show that all system features function in accordance with user requirements. Therefore, the implementation of this sales information system is expected to improve operational efficiency, accelerate transaction processes, minimize errors in data management, and enhance the quality of customer service.

In recent healthcare settings, digitally based smart environments—such as electronic medical records (EMRs), smart bed systems, and remote monitoring—have been rapidly expanding. As a result, nurses’ digital competencies have emerged as critical factors influencing work efficiency and patient safety. In response to these environmental changes, this study aimed to examine the effects of hospital smart environments and nurses’ digital literacy on nursing performance. Based on a review of prior studies, a research model and hypotheses were developed. The hospital smart environment was conceptualized as comprising a physical environment and an operational environment, while nurses’ digital literacy was examined in terms of technical utilization capability and technology-based collaborative competence. This study not only investigated the direct effects of the hospital smart environment on nursing performance but also further examined the moderating effects of nurses’ customer orientation on the relationship between digital literacy and nursing performance. To conduct this research, a survey was administered to nurses working in hospitals. The results indicated that higher levels of an operational smart environment significantly improved nursing performance. In addition, nurses with higher levels of digital literacy demonstrated enhanced nursing performance. Furthermore, the findings partially confirmed that nurses’ customer orientation strengthened the positive effects of the smart environment and digital literacy on nursing performance. This study provides both practical and academic implications for improving nursing performance in the era of digital transformation.

This study seeks to identify the combined impact of the dimensions of digital governance (technology infrastructure and operational processes, management and authority, accountability and transparency, and digital risk management) on digital transformation. The digital transformation era represents the "application of digital capabilities to processes, products, and assets" with the aim of "improving efficiency, enhancing customer value, managing risks, and unlocking new revenue opportunities." Similarly, digital transformation impacts not only life but also individual experiences. This study focuses on the mechanisms necessary to digitally transform the interaction between governments and citizens to ensure greater transparency, accountability, and integrity. It contributes to defining the current state of e-governance and digital maturity in government institutions.

Background In the era of rapid digital transformation, the banking sector faces increasing pressure to integrate ethical values and adaptive organizational behaviors to sustain performance and employee well-being. In Jordan, commercial banks are navigating technological advancements while maintaining moral and operational integrity, making it essential to understand how organizational morality and improvisation shape digital performance and workforce welfare. Objective This study aims to examine the impact of organizational morality and organizational improvisation on digital electronic performance and employee well-being in Jordanian commercial banks. It further explores the moderating role of organizational prestige within these relationships. Method Data were collected from managers, assistant managers, and tellers across 12 Jordanian commercial banks. A total of 261 valid responses were obtained using a purposive sampling technique. The hypotheses were tested using partial least squares structural equation modeling (PLS-SEM). Result Findings indicate that organizational morality and organizational improvisation significantly affect digital electronic performance and employee well-being. Digital electronic performance, in turn, demonstrates a strong positive relationship with employee well-being and serves as a mediating variable between organizational morality, organizational improvisation, and well-being. Furthermore, organizational prestige moderates the relationship between organizational morality, organizational improvisation, and digital electronic performance.