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Companies are increasingly implementing business process management systems (BPMSs) to support their processes. However, there is a gap in the literature regarding whether users also use BPMSs to manage the knowledge needed for processes to be completed. This study aims to analyze the factors that cause users to use BPMSs to manage the knowledge required in business processes.

The paper proposes an original model that integrates two successful information system models applied to BPMSs and knowledge management systems. To test the hypotheses derived from this new model, data were collected from 242 mature BPMS users from 12 Spanish and Latin American companies. Structural equation modeling with AMOS was used to examine the model.

Users’ perceived usefulness of a BPMS when using it for knowledge management (KM) is the only factor influencing them to use it for KM.

This study has practical implications for managers wishing to successfully implement a BPMS to support processes and for employees to use the knowledge embedded in the tool. The latter will only happen if users perceive the tool’s usefulness for KM.

To the best of the authors’ knowledge, this model is the first empirically validated model to successfully analyze BPMS users’ tendency to use BPMSs as a tool to support necessary KM in processes.

There is a growing importance of business intelligence systems (BIS) adoption in today’s digital economy age which is characterized by uncertainty and ambiguity considering the magnitude and influence of data-related issues to be solved in contemporary businesses. This study aims to investigate critical success factors that affect business intelligence efficiency based on the DeLone and McLean model in Jordanian banking industry.

A quantitative research method through a questionnaire was used to collect data from actual users who depend on business intelligence tools to make operational and strategic decisions in Jordanian banks. The data obtained were tested using the partial least squares–structural equation modeling approach.

The survey findings attest that system quality, information quality, user quality, user satisfaction and user performance are important factors and contribute to business intelligence efficiency in the Jordanian banking industry.

The findings gained from this work can help policymakers in Jordanian banks to improve the business intelligence success and organizational performance.

To the best of the authors’ knowledge, this study is the first of its kind to propose a theoretical model to assess drivers of BIS efficiency from the Jordanian banks’ perspective.

This study aims to evaluate the Accounting Information Systems (AIS) effectiveness on the organizational level by extending DeLone and McLean success model in developing countries like Jordan. Unlike other studies, this study investigates the effects of system quality, information quality, process quality, collaboration quality, service quality, individual performance and workgroup performance toward organizational performance during the period of the COVID-19 pandemic outbreak.

A self-administrated survey was used to collect data from 104 accounting managers operating in listed Jordanian firms in the Amman Stock Exchange (ASE). The partial least squares-structural equation modeling method was used for data analysis.

Eight relationships were tested, whereby six were supported as was expected. Particularly, the empirical results reveal that individual performance is positively and significantly influenced by information quality, process quality and service quality. Furthermore, workgroup performance is positively and significantly influenced by individual performance. The results also show that organizational performance is impacted by individual performance and workgroup performance.

The current study is among the first empirical studies that has extended the information systems success model to evaluate AIS success during COVID-19 pandemic. This study also offers insights into the importance of AIS success among listed Jordanian firms in ASE.

This research aims to investigate the impact of the collaborative governance mechanism on the implementation of rural governance information systems in developing countries. By integrating institutional logic theory, affordance theory and social identity theory, the authors propose modeling grassroots officials' affordance perception process and exploring the importance of multi-identities’ information technology (IT) goals in affordance perception.

Through an exploratory case study, the authors identified three affordances of rural governance information systems and investigated the mechanisms influencing the perception of these affordances among grassroots officials. Next, the authors established a research model and collected 490 valid questionnaires from grassroots officials in China and analyzed the data using structural equation modeling (SEM).

The authors' study challenges previous assumptions by integrating institutional logic, affordance and social identity theories. The authors establish a perceived affordance path for rural governance information systems, recognize substitute effects among technological affordances and extend the theory to explain social factors influencing IT perception. The authors' findings suggest providing technical training for grassroots officials to enhance IT capabilities, and governments should prioritize essential functionalities in rural governance information systems to optimize resources. Training on collaborative governance mechanisms can improve IT affordance perception, enhancing digital platform utilization in governance processes.

The study was conducted mainly in China, and therefore, the findings may not be universal to other developing countries. Researchers are therefore encouraged to test the proposal in locations with different rural cultures.

The paper includes implications for the development of IT perception in rural governance, the development of affordance perception theory and studying the relationship between IT goals and affordance perception.

Overall, this paper addresses the need to understand how grassroots officials perceive IT affordances in rural governance and study the relationship between multi-identities’ goals and affordance perception.

Upon the realization of the need for guideline in cross-organizational data integration, in an exploratory manner, this study developed a public data governance framework, specifically, the governance for integrated public data (GIPD) framework and identified the influential factors of its successful implementation. This framework was then subjected to an analysis of a real data integration case in the South Korean public sector to test its efficacy.

To develop the GIPD framework, the authors conducted an extensive meta study, focus group interviews and the analytic hierarchy process involving field experts. Further, the authors performed topic modeling on documents from Korean research and development data integration projects, and compared the extracted factors to those of the GIPD to illustrate the latter's usefulness in a real case.

Legislation, policy goals and strategies, operation organization, decision-making council, financial support size and objective, system development and operation, data integration, data generation, system/data standardization and master data management were derived as the 10 important factors in implementing the GIPD framework. The illustrative case of Korea revealed that decision-making council, financial support size and objective, legislation, data generation and data integration were insufficient.

Although this study reveals important findings, it has a few limitations. First, the potential factors for data governance might vary depending on the attribute of the “interviewee” (such as their career or experience period) and the goal and area of GIPD framework building. Second, the inherent limitation of topic modeling in determining topics from groups of extracted keywords means that topics may be interpreted in various ways, depending on the perspective of the expert.

This study is highly significant in that it provides a starting point for discussions on the issue of data integration among public institutions. Therefore, although this study examined public data governance based on R&D data, it will contribute to providing a sufficient guideline for any type of inter-institutional data governance framework, what to discuss and how to discuss between institutions.

The findings are expected to provide a roadmap to formulate practical guidelines on inter-institutional data cooperation and a diagnostic matrix to improve the existing data governance system, especially in the public sector, from the existing practice of empirical analysis using a mixed methodology approach.

This paper aims to propose a theoretical extension of the information system success model (ISSM) to evaluate enterprise resource planning (ERP) success at an organizational level in Jordan. It explores whether information quality, system quality and service quality have a positive impact on both perceived usefulness and user satisfaction as antecedents of organizational impact.

A questionnaire was undertaken to gather data from chief information officers among Jordanian firms, with a total of 134 valid returns tested via partial least squares structural equation modeling.

The results showed that most of the research hypotheses proposed are empirically supported, with the exception of the influence of service quality on user satisfaction which was extremely low.

To the best of the authors’ knowledge, this is the first empirical work that measured ERP success from an organizational perspective in Jordan. It also provides insight into how the factor of perceived usefulness is incorporated into ISSM in the mandatory system case and its influences on organizational benefits.

This research aims to gain a holistic understanding of how video conferencing (VC) apps' media characteristics influence individuals' perceptions of VC apps and, ultimately, their use and continued use in professional settings.

A conceptual research model is developed by integrating constructs from media synchronicity theory (MST), social presence theory and the unified theory of acceptance and use of technology (UTAUT2) model, as well as ubiquity, technicality and perceived fees. Structural equation modeling (SEM) is used to empirically test the conceptual model using data collected from 252 working professionals from the European Union.

The results reveal that while performance expectancy (PE) and facilitating conditions (FC) are fundamental to VC app use, these factors alone do not explain the use and continuing use of VC apps in the professional context. Media characteristics that include synchronicity, social presence, and ubiquity are equally crucial to professionals using VC apps. It also confirms the moderating effect of convergence on the relationship between synchronicity and PE and the moderating effect of technicality and perceived fees on the relationship between ubiquity and FC.

For researchers, the study offers insights into the extent to which technological and socially derived characteristics of VC apps influence the routine tasks undertaken by professionals in virtual work settings. For practitioners, recommendations pivotal to the use of VC apps are presented to promote higher acceptance and improved well-being of the professional workforce.

The purpose of this study is to propose the research model integrating the expectation-confirmation model with the views of learning engagement (LE) and extending DeLone and McLean information systems (IS) success model to examine whether quality determinants as antecedents to students' beliefs can influence students' continuance intention of massive open online courses (MOOCs).

Sample data for this study were collected from students enrolled in a comprehensive university in Taiwan. A total of 600 questionnaires were distributed, and 363 (60.5%) useable questionnaires were analyzed using structural equation modeling in this study.

This study proved that students' perceived knowledge quality, system quality, interface design quality, learner–instructor interaction quality, and collaboration quality all positively caused students' perceived usefulness, confirmation and LE in MOOCs, which jointly explained students' satisfaction with MOOCs and subsequently resulted in students' continuance intention of MOOCs.

This study fully evaluates IS-related and interaction-related quality determinants via an understanding of students' state of LE in explaining students' continuance intention of MOOCs that is difficult to expound with only their utilitarian perception of MOOCs. Hence, this study contributes to deep insights into an all-round quality evaluation in the field of MOOCs continuance intention and takes extrinsic and intrinsic motivators into account in the theoretical development of MOOCs continuance intention to acquire a more comprehensive and robust analysis.

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.

Recently, interest and necessity for cloud-based hospital information systems (HISs) have emerged as an appropriate alternative for revitalizing medical information exchange between hospitals, analyzing “big data” medical information and developing the use of new medical technologies. The purpose of this paper is to investigate factors that affect the switching of information systems in existing on-premise environments into cloud-based HISs.

A research model was developed using the push–pull–mooring model based on migration theory. The research model was analyzed using confirmatory factor analysis and path analysis using partial least squares structural equation modeling.

The results of this study showed that low compatibility, perceived value, low cost and inertia influenced the intention to switch to cloud-based HISs; low flexibility and low compatibility influenced dissatisfaction; and low cost, ease of maintenance and ease of managing indicators influenced perceived value.

This study is expected to be used as the basis for developing a research model in subsequent studies to analyze the transition to new innovative technologies. Also, in practice, it is expected to contribute to the activation of cloud computing environments in hospitals.