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Even though the end-user satisfaction construct has gained prominence as a surrogate measure of information systems performance assessment, it has received scant formal treatment and empirical examination in the data analytics systems field. In this respect, this study aims to examine the vital role of user satisfaction as a proxy measure of data analytics system performance in the financial engineering context.

This study empirically validated the proposed model using primary quantitative data obtained from financial managers, engineers and analysts who are working at Jordanian financial institutions. The quantitative data were tested using partial least squares-based structural equation modeling.

The quantitative data analysis results identified that technology quality, information quality, knowledge quality and decision quality are key factors that enhance user satisfaction in a data analytics environment with an explained variance of around 69%.

This empirical research has contributed to the discourse regarding the pivotal role of user satisfaction in data analytics performance in the financial engineering context of developing countries such as Jordan, which lays a firm foundation for future research.

Enterprise resource planning systems (ERPs) have provided new challenges in the management of organizations’ internal and external risks, and their adoption has triggered groundbreaking changes to internal audit practices. This study aims to shed light on the use of ERPs in internal auditing by identifying interrelations between postevaluations of the ERPs’ quality dimensions with internal auditors’ satisfaction, intentions to continue using such systems and perceived benefits.

Drawing on a unique data set of internal auditors’ responses on a structured questionnaire, and by using the DeLone and McLean’s (2003) Information Systems success model as the conceptual framework, this study tests the research propositions by using partial least square structural equation modeling (PLS-SEM).

The findings report statistically significant positive relationships among all three ERPs’ quality dimensions (system, information and service quality) with internal auditors’ satisfaction and intention to continue using these systems. Moreover, the study found that the benefits perceived by internal auditors were significantly influenced by their satisfaction with the system and their intention to continue using it.

The authors survey ERP postevaluation success factors in two unique contexts: internal auditors and Greece. Thus, the authors ground on previous research findings in diverse professional groups and national environments. In parallel, this study lends conceptual clarity and empirical evidence to a small but growing number of studies examining the implications of individuals’ perceptions, intentions and behavioral reactions in the context of ERP implementation.

This study examines learner satisfaction and success as mechanisms through which online learning quality translates into learners’ continuous intentions of use by extending DeLone and McLean’s information system success model. It also examines the moderating effect of perceived supervisory support and learners’ self-regulation on online learning quality in Higher Education Institutions.

Survey data were obtained from 540 students in both private and public higher institutions of learning in Ghana. The Partial Least Squares – Structural Equations Modelling (PLS-SEM) technique was used to test the hypothesised relationships.

The results revealed that system quality emerged as the single most important variable in the DeLone and McLean model, that influences learner success and satisfaction. Further, learner satisfaction has a significant positive effect on learner attitudes, whilst self-regulation was found to moderate the relationship between online learning quality and learner success as well as learner satisfaction.

The study appears to be among the first to explore the inter-relationship among online learning environment quality and learner attitudes and moderating factors perceived supervisory support and self-regulation. The study highlights insightful practical implications for students, faculty and administrators of higher institutions.

Despite the major information technology investments made by public institutions, the reuse of e-government services remains an issue as citizens hesitate to use e-government websites regularly. The purpose of this study is to investigate the cross-country determinants of e-government reuse intention by proposing a theoretical model that integrates constructs from (1) the Delone and McLean IS success model (i.e. system quality, service quality, information quality, perceived value and user satisfaction); (2) the trust and risk models (i.e. citizen trust, overall risk, time risk, privacy risk and psychological risks); and (3) Hofstede's cultural model (i.e. uncertainty avoidance, masculinity, individualism and cross-cultural trust and risk).

Based on data from interviews with 81 Kuwaiti citizens and surveys of 1,829 Kuwaiti and Polish citizens, this study conducted comprehensive, cross-cultural and comparative analyses of e-government reuse intention in a cross-country setting.

The results show that trust is positively associated with citizens' intention to reuse e-government services, whereas risk is negatively associated with citizens' perceived value. This study also found that masculinity–femininity and uncertainty avoidance are positively associated with the intention to reuse e-government services and that individualism–collectivism has no significant relationship with reuse intention. This study's findings have important implications for researchers and practitioners seeking to understand and improve e-government success in cross-country settings.

This study developed a parsimonious model of quality, trust, risk, culture and technology reuse that captures country-specific cultural contexts and enables us to conduct a comprehensive, cross-cultural and comparative analysis of e-government reuse intention in the cross-country setting of Kuwait and Poland.

Although E-learning has been in use for over two decades, running parallel to traditional learning systems, it has gained increased attention due to its vital role in universities in the wake of the COVID-19 pandemic. The primary challenge within E-learning pertains to the maintenance of sustainable effectiveness and the assurance of stakeholders' satisfaction. This research focuses on an intelligence-driven solution to recommend the most effective approach to education policymakers by considering the unique characteristics of all components within the educational system (course type, student and teacher characteristics, and technological features) to achieve a sustainable E-learning system.

Through a systematic literature review and qualitative content analysis, a conceptual model of the critical components influencing E-learning quality and satisfaction has been developed. The proposed model comprises six main dimensions: usage, service quality, learning system quality, content quality, perceived usefulness, and individual characteristics. These dimensions are further divided into 15 components and 114 sub-components. A data mining process encompassing two scenarios has been designed to prioritize the components impacting E-learning success.

In the first scenario, data mining techniques identified the most influential components based on the features outlined in the conceptual model. According to the results, the components affecting E-learning quality enhancement in the studied case are “usage purpose, system loyalty, technical and supportive system quality, and student characteristics.” The second scenario examines the impact of individuals' personality types and learning styles on E-learning satisfaction across various aspects (Average System Satisfaction, Overall System Satisfaction, Efficiency and Effectiveness, Skill Enhancement, and Personal Enhancement). The findings reveal that, with an accuracy of over 70%, E-learning satisfaction for diplomat and guard learners is influenced by the alignment between “course learning style” and “student-suggested course learning style.” Conversely, for analyzer and researcher types, satisfaction levels are impacted by the “learning style compatible with their personality type.”

Implementing a dynamic model founded on data mining enables educational institutions to personalize the E-learning experience for each individual as much as possible. The study’s findings indicate that “achieving higher satisfaction levels in the E-learning process is not necessarily contingent upon providing a learning style congruent with learners' personality types.” Rather, perceived and suggested learning styles exert a more profound influence. Consequently, providing prescriptive principles for higher education institutions seeking to enhance E-learning quality is inadvisable. Instead, adopting a dynamic, knowledge-based process that furnishes recommendations to policymakers for each course—tailored to the specific course type, teaching records, current processes and technology, and student type—is highly recommended.

Several conceptual works suggest that more digitalized information systems in management accounting have the potential to make this corporate function more effective. Against this backdrop, this study aims to investigate the impact of information systems quality in management accounting on the effectiveness of management control systems. Additionally, this study examines the moderating effect of process automation.

A cross-sectional survey of 125 German Mittelstand firms and hierarchical regression analyses were used for data collection and analysis.

The findings confirm the assumed positive effect of information systems quality in management accounting on management control effectiveness. They also confirm the assumed moderating effect of process automation. The authors find that the relationship between information systems quality in management accounting and management control effectiveness is more pronounced if the firm features a higher degree of process automation.

Several earlier case studies and a few quantitative studies indicated the potentially positive effect of high-quality information systems in management accounting on management control effectiveness. To the best of the authors‘ knowledge, this study is among the first to deliver quantitative proof of this relationship in the context of German Mittelstand firms. Moreover, the authors add to this literature the moderating effect of process automation in the relationship between information systems quality in management accounting and management control effectiveness.

The current study examines the factors that affect trust and donation intention in donation-based crowdfunding.

The present study utilized web-based questionnaires to examine the donation intention of Malaysian donors in donation-based crowdfunding, employing the information system success (ISS) framework. The collected data were investigated using partial least square structural equation modeling (PLS-SEM).

The findings of the study indicate that information quality, service quality and system quality have a significant positive effect on trust in donation-based crowdfunding. Additionally, donation intention in donation-based crowdfunding is significantly and positively influenced by information quality, service quality and trust.

The study’s results can be used by donation-based crowdfunding platforms to enhance their information, service and system quality to increase donor trust and intention to donate, including improving the platform’s design, navigation, aesthetics, comprehensibility of content, providing timely customer support and regularly updating and maintaining the system.

By exploring the relationship between information quality, service quality, system quality, trust and donation intention, this study contributes to the existing knowledge on donors’ behavior in crowdfunding.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-04-2023-0291

The purpose of this study is to ascertain service quality (halal values, assurance, meal quality, reliability, security, system and traceability) and perceived risks (financial, quality, environment, social, time, psychology and health) and its influence on satisfaction, as well as trust concerning online halal food delivery system (OHFDS).

This study uses quantitative methodology, through an online survey, by using purposive sampling across a sample size of 423 respondents. The analysis of data was conducted using SmartPLS.

The results of the findings indicate that assurance and halal values have an influence on satisfaction, as well as trust; nonetheless, only reliability has an impact on satisfaction. On the other hand, perceived health and financial risks have negative influence on trust and satisfaction toward OHFDS. In addition, perceived psychological and financial risks are found to have negative impacts on trust of OHFDS.

The theoretical value of this study is the testing of perceived service quality and risks concerning OHFDS in the same model, thereby contributing to a deeper understanding of its impact on trust and satisfaction toward the online food service delivery industry. The results of this study may appear as a starting point for researchers who wish to conduct further studies on the same topic.

This study suggests that the service providers need to boost their efforts in establishing high quality service and, simultaneously, reduce perceived risks, to develop satisfaction and trust toward OHFDS.

The long-term consequence of the business's achievement is that it makes it simpler for customers to have confidence in, be satisfied with and recommend the service providers to others.

A number of research investigations have been conducted among Muslims, specifically in the Asian region, which have yielded crucial data regarding consumer behavior toward halal products, such as food and tourism. This study, nonetheless, remains close with other studies on halal food, except that it adds together the knowledge of perceived quality and risks, as to gain a deeper understanding of the experience customers have on food, through online service delivery.

The information systems (IS) literature has indicated the importance of data analytics capabilities (DAC) in improving business performance in organizations. The literature has also highlighted the roles of organizations’ data-related resources in developing their DAC and enhancing their business performance. However, little research has taken resource quality into account when studying DAC for business performance enhancement. Therefore, the purpose of this paper is to understand the impact of resource quality on DAC development for business performance enhancement.

We studied DAC development using the resource-based view and the IS success model based on empirical data collected via 19 semi-structured interviews.

Our findings show that data-related resource (including data, data systems, and data services) quality is vital to the development of DAC and the enhancement of organizations’ business performance. The study uncovers the factors that make up each quality dimension, which is required for developing DAC for business performance enhancement.

Using the resource quality view, this study contributes to the literature by exploring the role of data-related resource quality in DAC development and business performance enhancement.

This study examines the key determinants of subscription intentions for ChatGPT Plus (paid version) in business settings, focusing on tasks such as system quality, information support, service quality, perceived intelligence, goal-congruent outcome and self-efficacy.

The study utilized a survey of office workers, analyzed through structural equation modeling, to explore these determinants.

The results demonstrate that system quality, service quality and perceived intelligence significantly influence satisfaction, while service quality and perceived intelligence also impact goal-congruent outcomes. Contrary to traditional models, satisfaction does not significantly correlate with usage. Instead, a significant relationship is observed between goal-congruent outcomes and usage. Self-efficacy emerges as a crucial predictor of subscription intentions, further underlined by the significant impact of usage on subscription intention.

The study’s focus on office workers and a single artificial intelligence (AI) chatbot type may limit generalizability. Its findings illuminate several avenues for future research, particularly in diversifying the context and demographics studied.

This research offers actionable insights for businesses and practitioners in the implementation of AI chatbots. It highlights the importance of enhancing system quality, personalization and user confidence to boost subscription intentions, thereby guiding strategies for user engagement and technology adoption.

This study pioneers in investigating subscription intentions towards AI chatbots, particularly ChatGPT, providing a novel framework that expands upon traditional user behavior theories.