Continuous usage is crucial for ensuring the longevity of technological advancements. The success of e-government is contingent upon its ongoing use, rather than its initial acceptance. Nevertheless, there has been a dearth of scholarly research on the ongoing use of e-government services. The objective of this study was to identify the primary factors that influences the continued use of e-government services in Indonesia. The research model was created by integrating both Expectation Confirmation Model and Technology Acceptance Model, two theories that are frequently employed in the adoption of technology. The data was obtained by administering an online survey to 217 Indonesian citizens who had previously utilized the Online Citizen Aspiration and Complaints Service (LAPOR) e-Government services. The results indicate that perceived ease of use had a substantial impact on citizen satisfaction and perceived usefulness. In contrast to previous research conducted in the context of e-Government, it was found that perceived usefulness did not have a significant correlation with the intention to continue using the system. The most significant predictor of continued intention to use was citizen satisfaction. Surprisingly, satisfaction was more significantly influenced by perceived ease of use than perceived usefulness. The implications of these findings are elaborated upon.

Amid the unfolding Fourth Industrial Revolution, the integration of Logistics 4.0 with agribusiness has emerged as a pivotal nexus, harboring potential for transformational change while concurrently presenting multifaceted challenges. Through a meticulous content analysis, this systematic review delves deeply into the existing body of literature, elucidating the profound capacities of Logistics 4.0 in alleviating supply chain disruptions and underscoring its pivotal role in fostering value co-creation within agro-industrial services. The study sheds light on the transformative potential vested within nascent technologies, such as Internet of Things (IoT), Blockchain, and Artificial Intelligence (AI), and their promise in shaping the future landscape of agribusiness. However, the path forward is not without impediments; the research identifies cardinal barriers, most notably the absence of robust governmental policies and a pervasive lack of awareness, which collectively stymie the seamless incorporation of Industry 4.0 technologies within the realm of agribusiness. Significantly, this inquiry also highlights advancements in sustainable supply chain management, drawing attention to pivotal domains including digitalization, evolving labor paradigms, supply chain financing innovations, and heightened commitments to social responsibility. As we stand on the cusp of technological evolution, the study offers a forward-looking perspective, anticipating a subsequent transition towards Industry 5.0, characterized by the advent of hyper-cognitive systems, synergistic robotics, and AI-centric supply chains. In its culmination, the review presents prospective avenues for future research, emphasizing the indispensable need for relentless exploration and pragmatic solutions. This comprehensive synthesis not only sets the stage for future research endeavors but also extends invaluable insights for practitioners, policymakers, and academicians navigating the intricate labyrinthstry of Logistics 4.0 in agribusiness.

This research was conducted with the intention of investigating and analyzing the factors that influence the views that consumers have of advertising on social media platforms. The goal of this study is to look at the many ways that new media ads affect consumers’ purchasing behavior. An evaluation of the validity and reliability of the measures has been carried out with the assistance of confirmatory factor analysis. In addition, the quantitative research approach makes use of both simple random sampling and statistical sampling. The information was gathered via the use of a questionnaire that was issued to fans of new media. Using a Likert scale with five points, the questionnaire’s questions were evaluated to ensure that they were appropriately worded. The total sample size that is employed is 359. The purchase behavior of consumers of new media has been evaluated based on five variables, including the ability to attract attention, provide amusement, establish legitimacy, emphasize creative character qualities, and evoke emotional appeal. The objective of this study paper is to investigate the impact that advertisements broadcast via new media have on consumers’ decision-making processes regarding the acquisition of goods and services. The research’s findings show that when consumers are weighing their options for purchase, advertisements having the largest impact on their purchasing decisions in new media. With the goal of offering important insights into the new media advertising industry, the author seeks to link these results with pertinent ideas from the theoretical framework.

Recently, carbon nanocomposites have garnered a lot of curiosity because of their distinctive characteristics and extensive variety of possible possibilities. Among all of these applications, the development of sensors with electrochemical properties based on carbon nanocomposites for use in biomedicine has shown as an area with potential. These sensors are suitable for an assortment of biomedical applications, such as prescribing medications, disease diagnostics, and biomarker detection. They have many benefits, including outstanding sensitivity, selectivity, and low limitations on detection. This comprehensive review aims to provide an in-depth analysis of the recent advancements in carbon nanocomposites-based electrochemical sensors for biomedical applications. The different types of carbon nanomaterials used in sensor fabrication, their synthesis methods, and the functionalization techniques employed to enhance their sensing properties have been discussed. Furthermore, we enumerate the numerous biological and biomedical uses of electrochemical sensors based on carbon nanocomposites, among them their employment in illness diagnosis, physiological parameter monitoring, and biomolecule detection. The challenges and prospects of these sensors in biomedical applications are also discussed. Overall, this review highlights the tremendous potential of carbon nanomaterial-based electrochemical sensors in revolutionizing biomedical research and clinical diagnostics.

This study conducts a systematic literature review to analyze the integration of artificial intelligence (AI) within business excellence frameworks. An analysis of the findings in the reviewed articles yielded five major themes: AI technologies and intelligent systems; impact of AI on business operations, strategies, and models; AI-driven decision-making in infrastructure and policy contexts; new forms of innovation and competitiveness; and the impact of AI on organizational performance and value creation in infrastructure projects. The findings provide a comprehensive understanding of how AI can be integrated into organizational excellence emerged frameworks to address challenges in infrastructure governance, and sustainable development. Key questions addressed include: how AI affects consumer behavior and marketing strategies. What AI’s capabilities for businesses, especially marketing and digital strategies? How can organizations address the drivers and barriers to help make better use of AI in these business operations? Should organizations even do anything with these insights? These questions and more will be tackled throughout this discussion. This paper attempts to derive a comprehensive conceptual framework from several fields of human resources, operational excellence, and digital transformation, that can help guide organizations and policymakers in embedding AI into infrastructure and development initiatives. This framework will help practitioners navigate the complexities of AI integration, ensuring profitability and sustainable growth in a highly competitive landscape. By bridging the gap between AI technologies and development-related policy initiatives, this research contributes to the advancement of infrastructure governance, public management, and sustainable development.

This study investigates the factors influencing student satisfaction at higher education institutions in Pathum Thani Province, Thailand. The research uses structural equation modeling (SEM) to analyze the connections among College Reputation, Student Expectation, Perception Value, and Student Satisfaction based on a sample of 660 students. The results indicate that the student population is diverse, with most students enrolled in the Faculty of Business Administration in their first year. The Pearson’s correlation matrix and structural equation modeling (SEM) findings indicate significant positive correlations between the dimensions, emphasizing the crucial influence of College Reputation on both Student Expectation and Student Satisfaction. The goodness-of-fit indices validate the model’s strength, indicating a significant correspondence between the theoretical components and the observed data. This study enhances the comprehension of how student satisfaction changes in Thai higher education and offers practical suggestions for institutional policies to improve student’s educational experiences and achievements. Higher education institutions may create a more fulfilling and effective learning environment by prioritizing reputation improvement, ensuring student expectations match reality, and providing perceived value to improve education quality and equality for Thailand.