This research aims to analyze the relationship between information system quality and user satisfaction, the relationship between perceived usefulness and user satisfaction and the relationship between user satisfaction and sustainable e-learning. The research method used in this research is associative research. The population in this study were all students who had undergone lectures using e-learning. In this study, the analytical model was used, namely Structural Equation Modeling (SEM) and the number of respondents was 456 high school students in Indonesia, who have undergone lectures using e-learning. The sampling technique used in this research is nonprobability sampling. The data collection method used was the questionnaire method and the instrument used to measure this research variable was a 5-point Likert scale. Data processing in this research uses SmartPLS software. The data analysis stage in this research is the outer model test including convergent validity, discriminant validity and composite reliability and inner model analysis, namely hypothesis testing. The results of the study indicate the quality of the information system has a positive effect on user satisfaction, Perceived Usefulness has a positive effect on user satisfaction and user satisfaction has a positive effect on sustainable e-learning. The implication is that every element at every level in formal educational institutions must pay serious attention to personal factors, including attention to student achievement expectations, relative excellence expected by students, student suitability with the e-learning system chosen in an institution's formal education, and the attitude of students who are willing to accept and continuously use e-learning. In this way, students will be consistent in using e-learning so that student achievement, which is the main goal of every school, can be achieved. The limitation of this research is that it does not provide prior understanding to respondents regarding the scope of the meaning of sustainable e-learning.

This study investigates the relationship between business intelligence adoption (Business Intelligence (BI), Data Analysis and Reporting (DAR), Business Process Integration (BPI), and Continuous Improvement and Innovation (CII)) and marketing effectiveness in the Jordanian telecom industry. It specifically examines the mediating role of customer satisfaction in this relationship. A survey design method using the cross-sectional survey was utilized during the research process, involving quantification. The data was collected from 285 employees across the Jordanian telecom sector via electronic response forms. As the analysis's method, the partial least squares structural equation modeling (PLS-SEM) was utilized. The results, which showed BI, DAR and CII to have a positive direct effect on marketing effectiveness, whilst BPI displayed a negative direct impact, were compelling. But clear signs of positive influence on CS by the four dimensions of BI (BI, DAR, BPI, and CII) have also been observed, and this result has been proved to be a mediator between them and business effectiveness. The above study is a source of invaluable learning for the managers of telecom companies in Jordan is a tool that managers in the Jordanian telecom industry will greatly benefit from in the sense that it brings out all the importance of integrating BI, DAR, BPI, and CII practices that emphasize high quality customer service. By properly utilizing these assets and up-to-the-market, companies can improve the effectiveness of marketing and the whole organizational efficiency. The study enhances the existing theory of the interrelationships between the adoption of business intelligence, customer satisfaction, and marketing power which can be viewed from both resource-based view (RBV) theory and expectation-based theory (EDT). It affirms an idea that the RBV was rooted in that when organizational assets are valuable, firms have a competitive advantage and better performance. Also, an EDT states that customer satisfaction increases if the expectations of customers are met. Innovation - The essay is innovative and takes an original angle to explore the multifaceted interconnectivity among business intelligence adoption, customer satisfaction, and marketing effectiveness in the framework of the Jordanian telecom industry. It highlights the steps to customer satisfaction problem solutions and the caution comes with process integration efforts, hence, helping to arrive at a full comprehension of the aspirations for organizational performance in the field.

This research aims to analyze the relationship between digital transformation and school performance and the relationship between digital innovation and school performance. The research method is quantitative through surveys, research data was obtained by distributing online questionnaires to 489 high school teachers throughout Indonesia who were selected using a simple random method. Data analysis used covariance-based structural equation modelling (CB-SEM) with SmartPLS 4.0 software to analyze research data. The independent variables are digital transformation and digital innovation, and the dependent variable is school performance. The stages of data analysis are validity testing, reliability testing, model fit testing and significance testing of hypothesis testing. The results of this research are that digital transformation has a positive and significant relationship with performance. Moreover, digital innovation has a positive and significant relationship to performance. The findings of this research support and prove the results of previous research that digital transformation has a positive effect on organizational performance and innovation and confirms the direct influence of innovation on organizational performance. The contribution of this research is aimed at various literature related to the role of digital transformation and innovation on organizational performance. Meanwhile, for practical implications, digital transformation and innovation can improve organizational performance, especially in schools.

In the digital era that continues to develop, information technology has brought significant changes to various aspects of human life. One of the clearest impacts is in the field of education. In this era, learning is no longer limited to physical classrooms and textbooks, instead, electronic learning or e-learning has become a popular alternative for accessing knowledge and learning online. This research aims to analyze the relationship between e-learning variables and school performance, the relationship between digital transformation variables and school performance and the relationship between digital innovation and school performance. The study uses a quantitative method approach and data analysis using the Partial Least Square -Structural Equation Modeling (PLS-SEM) approach. Research data was obtained by distributing an online questionnaire form via social media platforms. The questionnaire was designed to contain statement items on a Likert scale from 1 to 7. The respondents for this research were 467 school principals in Indonesia who were determined using the sample determination method, namely simple random sampling. The stages of research data analysis are validity testing, reliability testing and hypothesis testing or significance testing. The independent variables in this research are e-learning, digital transformation and digital innovation, the dependent variable in this research is school performance. The results indicate that e-learning, digital transformation, and innovation had positive and significant effects on school performance.

This study examines the relationship between the types of Artificial Intelligence (AI) technology employed and monitoring tax payments. A thorough literature review is conducted to examine different AI technologies in the context of tax administration. These include machine learning algorithms (MLA), natural language processing (NLP) technology, robotic process automation (RPA), explainable artificial intelligence (XAI), and advanced data analytics techniques (DAT). A variety of technologies, such as big data analytics, task automation, task automation, unstructured data analysis, and predictive modeling, are available to improve tax payment monitoring procedures. Recommendations for further study to expand our knowledge and use of AI in tax payment monitoring are included, along with the consequences of AI adoption for tax authorities, policymakers, and practitioners.

Company activities can yield both favorable and adverse outcomes. Among the detrimental effects are various environmental crises stemming from companies' failure to responsibly manage and uphold ethical business practices within their operational environment. This study aims to scrutinize the impact of artificial intelligence and social media on augmenting public administration decision-making and its repercussions on corporate social responsibility within enterprises situated in Sidoarjo, East Java Province, Indonesia. The sample comprises 130 respondents representing companies actively engaged in corporate social responsibility endeavors. Employing purposive sampling technique, data collected from surveys were subjected to Structural Equation Modeling-Partial Least Squares (SEM-PLS) analysis. The research outcomes and data analysis reveal that artificial intelligence significantly and directly influences corporate decision-making as well as public administration of social responsibility. Likewise, the utilization of social media by both corporations and government exhibits a direct and positive correlation with corporate decision-making and corporate social responsibility. Public administration decision-making also demonstrates a direct and significant impact on corporate social responsibility within companies in Sidoarjo, East Java Province, Indonesia. Moreover, public administration decision-making partially mediates the effects of artificial intelligence utilization and social media utilization on public administration of social responsibility within companies in Sidoarjo, East Java Province, Indonesia.

The widespread adoption of artificial intelligence (AI) technologies, including ChatGPT, into education, has become a focal point of attention in recent years. This research explores the connections among perceived usefulness (PU), perceived ease of use (PEOU), attitude toward using ChatGPT (ATUC), and intention to use ChatGPT (ITUC) within Jordanian universities. A survey was employed to gather information from 523 university students in Jordan, and the hypotheses were examined using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings revealed that perceived usefulness and perceived ease of use positively impacted attitude toward using ChatGPT and intention to use ChatGPT. Attitude toward using ChatGPT positively impacted intention to use ChatGPT. Implications from this research are crucial to provide developers, instructors, and institutions in Jordan with useful information to help them successfully incorporate ChatGPT into the educational process.

The Covid-19 pandemic which has spread across all countries, including Saudi Arabia, has caused the government to create limited curfew policies in the country that affected the economy. This policy has given rise to a new trend in society, namely the habit of shopping online. The trend of purchasing online via e-commerce increases. However, people's opinions and attitudes towards this trend vary. Therefore, this research was conducted with the aim of determining the subjectivity of public opinion or sentiment on the e-commerce activities using probability and statistical approaches, i.e.: the Naïve Bayes (NB) and Support Vector Machine (SVM) classifiers. Three experimental scenarios of dataset splitting for training and testing; 90%:10%; 80%:20%; and 70%:30%. The comparison of accuracy values was carried out using an automatic labeling method. Experimental results show that the 70%:30% split scenario provides the best result, with 89% of accuracy, 99.7% of Precision, 88% of Recall and 93.5% of F1-score for the SVM classifier.

The fast fashion business is becoming more reliant on social media marketing (SMM) as SMM enables larger data collection and communication between the brand and its consumers. This study investigates the impact of SMM aspects such as customization, entertainment, interactivity, trendiness, and eWOM on fast fashion’s online and offline purchase intentions (PI). Similarly, it investigates the moderating influence of culture on the factors mentioned above and the relationship’s utilitarian and hedonic reasons. Additionally, 360 responses were obtained from three countries, Morocco, Jordan, and Spain, using an online questionnaire. The findings revealed that customization, amusement, and trendiness influence offline and online PI favorably. Culture was also shown to have a moderating influence on the link between SMM components and PI. Motivations were also discovered to be a mediator between eWOM, trendiness, customization, and PI.

Natural disasters are one of the events that threaten food security in every region in Indonesia. Ciamis District is one of Indonesia's areas prone to natural disasters. One of the impacts of a disaster is on the agricultural sector because it will determine food security in the area and can affect the socio-economic community. This study aims to analyze the Geographically Weighted Regression (GWR) Model of the Effect of Disaster Events on Food Security. This study used quantitative methods, and data sources were obtained through secondary data searches. Data were processed using a Geographically Weighted Regression (GWR) analysis tool through a quantitative descriptive analysis approach. The results showed that the natural disasters directly or indirectly impacted food availability and security in Ciamis District. Natural disasters still occur even though food availability, affordability, and utilization are quite good. There are other factors, namely disasters, that come suddenly and cannot be predicted, thereby affecting the food security of a region. Efforts are needed to create togetherness in society to anticipate and respond to disaster events. In addition, it is expected that each individual can take the necessary actions to solve problems independently.