Activity-based costing system (ABC) adopters reported different uses of the system, inconsistent amounts of benefits gained, and consequently varying levels of satisfaction with the system. This study aims to investigate the variation in the extent of use, the magnitude of benefits, and user satisfaction with the ABC. A structured questionnaire was sent to the manufacturing companies operating in Riyadh Province, Saudi Arabia. 75 responses from ABC implementers were received. The results of this study show that the degree of ABC implementation success positively influences the extent of its use, the magnitude of benefits that have been obtained, and the overall user satisfaction with the system. These findings imply that irrespective of the characteristics of the company or the features of the system, the way the companies implement ABC might determine how much benefits can be gained and to what extent the system could be used.

This paper examined how information quality within project management information systems is being improved through the use of blockchain technology. A conceptual framework was developed based on past findings and relevant theories. User satisfaction determinants affecting blockchain adoption success in Jordan were examined in this paper. A cross-sectional design and Random sampling technique were employed. Data collection involved the use of questionnaires. Data obtained from 393 responses were analyzed using AMOS software. The findings showed a significant impact of system quality, information quality, ease of use on user satisfaction, whereas service quality did not show a similar impact. Also, ease of use impacted blockchain adoption success, but user satisfaction did not. In addition, user satisfaction did not mediate the relationship between ease of use and Blockchain adoption success. Results had implications on blockchain use in Jordan. Several recommendations were proposed for forthcoming scholarly works and blockchain actual adoption, in Jordan especially.

The widespread adoption of mobile applications has led to a substantial increase in user feedback. Systematically extracting actionable insights from large volumes of unstructured user feedback presents a significant analytical challenge, particularly in mobile learning (m-learning) environments. This study addresses this gap through a mixed-method analysis of 36,625 Duolingo application reviews by integrating machine learning and thematic analysis. The primary objectives are to determine the predictability of user satisfaction from review text and to identify specific thematic factors that underpin user sentiment. Multiple machine learning classifiers were trained using the Bag-of-Words (BoW) model and transformer-based document embeddings to predict the binary satisfaction sentiment label. The results demonstrated that user satisfaction was highly predictable, with logistic regression and neural network models achieving accuracy exceeding 90% (AUC up to 0.968, MCC up to 0.818). Thematic analysis revealed a clear bifurcation in sentiment; core pedagogical features (e.g., internationalization, personalization, and usability) were the primary drivers of satisfaction, whereas significant dissatisfaction stemmed from technical instability (e.g., bugs and performance issues) and monetization strategies (e.g., pricing and ad intrusiveness). This mixed-method provides an interpretable satisfaction-prediction framework and delivers evidence-based recommendations for app developers aiming to maintain competitiveness through continuous user-centered enhancements.

This paper aims to evaluate the role of AI and ML-driven innovative technologies in enhancing customs operations in Jordan. This research employed a quantitative approach to develop an overall conceptual model that encompasses both the technical and behavioral aspects of intelligent system adoption. The target population consisted of customs officers, border security personnel, and IT personnel responsible for customs clearance and trade facilitation in Jordan. The structured questionnaires were administered to the respondents to measure their perceptions of system effectiveness, satisfaction, performance outcomes, and evasion behavior and yielded a total of 358 valid responses. The research was conducted with proper statistical analysis, and the statistical techniques employed included primary data collected via SPSS Version 29 and advanced modeling using Structural Equation Modeling-Partial Least Squares (SEM-PLS) through the use of SmartPLS 4.0. The results indicated that the measurement model proved to be both valid and reliable, with Cronbach's alpha values exceeding 0.82 and AVE values above 0.50, indicating good internal consistency and convergent validity. Moreover, the structural model achieved good explanatory power, with R² values of 59% for Customs Evasion, 43% for User Satisfaction, and 100% for Digital Performance Indicators. These findings underscore the significance of user satisfaction as a key outcome of system effectiveness and a valuable tool for enhancing performance and deterrence. More specifically, the results shown how Intelligent System Effectiveness presents a positive and significant impact on User Satisfaction (β = 0.656, p < 0.001), which in turn has a high positive effect on both Digital Performance Indicators (β = 1.000, p < 0.001) and Customs Evasion reduction (β = 0.770, p < 0.001). The mediation analysis also confirmed that User Satisfaction fully mediates the relationship between system effectiveness and performance outcome, as well as between system effectiveness and evasion reduction. This research contributes to theory and practice by demystifying the design and implementation of AI-driven customs systems. It illustrates the importance of valuing both technical system quality and user-centric values in achieving and maintaining optimal performance in the digital space, as well as conformance with the law.

The aim of this paper is to examine one of the most crucial factors in the “Technology Acceptance Model” proposed by Davis (perceived usefulness) in moderating the “DeLone and McLean” success model in the context of educational portal in Higher Education. Questionnaires were distributed online to 200 respondents and deserved to be analyzed. The respondents were regular students at the University of Bengkulu. Data analysis used Smart-PLS version 3.2.9. The research findings indicated an influence of “system quality, information quality, and service quality partially on user satisfaction” of the educational portal information systems. The result shows that perceived usefulness can strengthen the relationship between system quality, information quality, and service quality to the satisfaction of customer. This research contributes to the development of perceived usefulness variable as a moderating variable affecting the quality of a system, quality of information, and quality of service partially on user satisfaction and finding strategies needed by the University of Bengkulu effective and efficient information system.

Although fog computing-based logistic supply chain management (Fog computing-based LSCM) is an emerging technology that proved a high impact on services and products, little research has focused on fog computing-based LSCM. Drawing on the Kano model and organization's theory this paper investigates the effect of fog computing-based LSCM on organizational agility. And the role of user satisfaction as mediator between fog computing-based LSCM and organizational agility. A quantitative approach was used, a questionnaire was designed for data collection, Cronbach's Alpha test was performed on a pilot study to examine the internal consistency of questionnaire items. Fog computing-based LSCM was studied based on Supply chain awareness, Connectivity and Logistics, Integration Process, Seamless Supply Chain, Integration of Processes. Data was collected from a random sample of 550 employees of Al-Hassan industrial city‎ in Jordan. Building on the proposed model, Researchers show that fog computing-based LSCM has a positive impact on organizational agility, fog computing-based LSCM has a positive impact on user satisfaction and finally user satisfaction mediates the relationship between fog computing-based LSCM and organizational agility. Implications for the model are discussed.

This research aims to analyze variable service quality on e-government user satisfaction and analyze information quality variables on e-government user satisfaction at the immigration office. The research method used in this research is associative quantitative research which aims to determine the relationship between two or more variables. In this way, we can build a theory that functions to predict and control a phenomenon. The population in this study were all immigration office employees. In this research, an analysis model is used, namely Partial Least Square-Structural Equation Modeling (PLS-SEM). In this study, the number of respondents was 876 immigration office employees who used e-government. The sampling technique used in this research is non probability sampling. In this research, the data collection method used was the questionnaire method. The instrument used to measure this research variable is a 7-point Likert scale. Data processing in this research uses SmartPLS software. The stages of data analysis in this research are the outer model test which includes convergent validity, discriminant validity and composite reliability as well as inner model analysis, namely hypothesis testing. The results of this research are that variable service quality has a positive and significant relationship to e-government user satisfaction at the immigration office and the information quality variable has a positive and significant relationship to e-government user satisfaction at the immigration office.

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.

SISKEUDES is a financial system used by the village government aimed at improving accountability, creating common perceptions in the delivery and application of various laws and regulations in the form of village financial management systems and procedures. Implementation of SISKEUDES helps us improve good corporate governance of village government in Indonesia. However, in the Village Assistance Report in Badung Regency in 2018 and 2019, there were input errors from planning, budgeting, administration and financial reporting. Based on this phenomenon, this study tested the predictor of successful application of the system. The measurement of SISKEUDES success is based on DeLone and McLean information system success model. This study examines the direct effect of system quality, information quality, service quality and quality of human resource on use, user satisfaction and net benefits. The sample determination technique uses purposive sampling with criteria of all SISKEUDES users in Badung Regency Village Government with a minimum of 1 year working experience. Data analysis uses Partial Least Square with SmartPLS 3. The results show that only system quality, information quality, and service quality have positive effects on user satisfaction, while the quality of human resources has no effect on user satisfaction. The quality of information, the quality of service, and the quality of human resources have positive effects on the use, while the quality of the system has no effect on the use. The quality of information, service quality, use and user satisfaction have positive effects on net benefits.

The advent of information technology has caused people to consider how they can make effective and efficient decisions in various activities. The implementation of information technology systems is expected to be advantageous in facilitating these activities because such systems can provide decision-making support and contribute to the success of endeavors in areas such as business, economic, social politics, and education. One common tool used in learning systems is e-learning applications. This research aims to analyze the effect of e-learning on user loyalty with user satisfaction. This research, conducted in Jakarta, is explanatory in nature, targeting individuals who have utilized e-learning applications in their activities, particularly in the field of public sector activities, with a sample size of 163 public sector employees. Data was collected through online questionnaires, and hypothesis testing was conducted through the PLS-SEM method. The results indicate that service quality and perceived value have positive impacts on user satisfaction, which in turn, positively influences user loyalty.