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This work serves to propose a national electronic health system based on the Big Data approach. First of all, we assessed the practice of health information systems (HIS) in Morocco and their obstacles. We performed a survey that was founded on 24 questions to specify the necessary details on this topic. This study shows that there is a primary need for the establishment of an HIS that facilitates the control, analysis, and management of health data in Morocco. For this reason, we have proposed the implementation of the Moroccan Health Data Bank (MHDB). This system will be based on powerful big data technologies that save, manage, and process health data with greater efficiency. The information present in this proposed system can provide the necessary resources for several actors to exploit this wealth, which is embodied in this massive data. We have developed a general description of the MHDB, its components, its conceptual architecture, and an example of a use case.

Heart failure is a severe medical ailment that significantly impacts patients’ well-being and the healthcare system. For improved results, early detection and immediate treatment are essential. This work aims to develop and evaluate predictive models by applying sophisticated ensemble learning techniques. In order to forecast heart failure, we used a clinical dataset from Kaggle. We used the well-known ensemble techniques of bagging and random forest (RF) to create our models. With a predicted accuracy of 82.74%, the RF technique, renowned for its versatility and capacity to handle complex data linkages, fared well. The bagging technique, which employs several models and bootstrapped samples, also demonstrated a noteworthy accuracy of 83.98%. The proposed model achieved an accuracy of 90.54%. These results emphasize the value of group learning in predicting cardiac failure. The area under the ROC curve (AUC) was another metric to assess the model’s discriminative ability, and our model achieved 94% AUC. This study dramatically improves the prognostic modeling for heart failure. The findings have extensive implications for clinical practice and healthcare systems and offer a valuable tool for early detection and intervention in cases of heart failure.

This study investigates the relationship between the user interface and problem-solving towards the continuous intention to use the services. New products or services will always face tough challenges for the customer, especially when the new procedures require them to learn and change some behaviors. Chatbots are also facing the same situation in Malaysia, where customers refuse to accept using chatbots to represent their physical presence. To understand customer behaviors, a quantitative survey was designed. Four hundred twenty-two data were collected from the online survey method. As per the results, the predictors of chatbot continuous intention are user interface and problem-solving. Apart from that, this study also measures the role of mediator, namely trust and customer satisfaction. This study contributes to unique academic and practical insights that can be used to explore the effectiveness of chatbots. The results revealed that both predictors were significant towards the continuous intentions. Besides, the role of the mediator was found to be significant and relevant in the relationship between trust and customer satisfaction and customer satisfaction and trust towards continuous attention.

Purpose: The purpose of this study was to prioritize the factors affecting consumer-buying behavior in online social media marketing.Method: The analysis and validation of indicators were conducted using the mixed method of structural equation modeling and partial least squares. Additionally, the IPMA matrix was utilized to determine the importance and type of performance of each factor. The research data were influenced by consumer information, predominantly consisting of women with a master's degree aged between 36 and 50 years. The study employed a non-probability sampling method common for online surveys, and 466 individuals were examined using Cohen's effect size formula.Findings: The research findings indicated that consumer engagement was the most important factor, and ease of use exhibited the highest level of performance in the overall social media model. Furthermore, consumer engagement was identified as the most important factor, while electronic word-of-mouth (EWOM) demonstrated the highest performance level on Instagram. Conversely, EWOM was deemed the most important factor, with consumer engagement displaying the highest performance level on Telegram. These results can be utilized by marketers to influence consumer purchasing behavior and craft online marketing strategies accordingly.Conclusion: Companies utilizing online social media platforms are advised to enhance consumer engagement and performance by implementing short-term techniques and effective strategies, such as incorporating online chat functionalities in the user environment. Instagram, being the most widely used social media platform and an online shopping hub for consumers, showcased acceptable performance in terms of consumer engagement. Hence, companies need to take measures to elevate performance levels to match their importance. In the case of Telegram, EWOM emerged as the most crucial factor among others, with a commendable performance rating. Businesses can bolster their Customer Relationship Management (CRM) units and enhance WOM initiatives to the fullest extent possible.

Green information technology is in the spotlight for organizations, helping them save money by using information technology (IT) to achieve the highest efficiency and thus reduce environmental impacts. One of the ways that can help organizations planning for deploying green IT is to evaluate green information technology maturity (GITM). Previous studies have referred to various criteria for green IT evaluation, most of which are qualitative criteria that are difficult to measure and evaluate in ambiguous conditions. The main objective of this study is to identify crucial criteria that affect the GITM level and to design a fuzzy inference system to assess the GITM level in any organization. While using a Mamdani Inference system, inputs can be verbal expressions or crisp values, and the output shows the level of maturity of green information technology. Since green IT knowledge is not modeled in previous studies, modeling it in the current study is a valuable step for organizations confused about various factors they should consider for going green. The main system criteria are the conditions of the data center, office environment, work practice, procurement, and corporate citizenship. Due to the generality of the model used for the knowledge base system development, organizations can use this system for the green IT maturity level determination. The presented inference system helps organizations understand their status of being IT green and plan for the following steps to accomplish their desired maturity level. The proposed inference system has been tested, validated, and used to determine the maturity level of Tehran municipality.

Information technology (IT) governance has become a crucial area of study because of the growing corpus of research in the area. This study aims to conduct both a literature review and bibliometric analysis focusing on three specific research questions: (RQ1) examining the trends in publications and citations, (RQ2) recognizing the most impactful countries, journals, and authors, and (RQ3) investigating popular research areas and trending topics in IT governance. Data surrounding IT governance research were obtained through the Scopus database, with a total of 1,510 documents published from 1995 to February 2023. The extracted documents were analysed using Harzing’s Publish or Perish, VOSviewer, and Bibliometrics sub-tool Biblioshiny software. Publications have continued to rise since 2004 when the United States has had the greatest influence over IT governance publication and research collaboration, while Indonesia is the most prolific. Primary sources on IT governance research were taken from conference proceedings related to IT topics. As for authors, Pereira R from Portugal is at the top of the list while Van Grembergen W from Belgium is the most influential. This study is the first to identify and propose themes and current hotspots in IT governance research which serves as a guide for future researchers and professionals.

This study investigates Ghanaian students' adoption of Mobile Learning (ML) by extending the technology acceptance model with a subjective norm variable. Specifically, this study focuses on the moderating effect of gender using the Measurement Invariance of Composite Models for the analysis. The study used a purposive sampling technique to collect the data for the study from sec-ond-year diploma students at the University of Professional Studies in Accra. SmartPLS 3.3.3 was used to analyze the data from 330 respondents. The findings of the study suggest that perceived ease of use, perceived usefulness, and subjective norm have a significant influence on the behavior-al intention to adopt mobile learning for the complete data set. In addition, the results suggest that the impact of the subjective norm was not significant for female students but for male students. Also, the impact of perceived ease of use and perceived usefulness on behavioral intention were insignificant. Furthermore, the findings suggest that behavioral intention influences students' actual use of mobile devices to access learning materials. Finally, gender moderates the relationship be-tween subjective norms and behavioral intention. The findings demonstrate group heterogeneity, therefore, investigations on technology adoption must always incorporate group dynamics to un-derstand how different groups respond to its adoption. The findings of the study hold significance for both policy and research implications.

Purpose: Start-up businesses have attracted considerable attention regarding the new approach in the modern economy The present study was conducted to investigate the factors affecting the improvement of customers’ online shopping experience in e-commerce start-ups in the healthcare sector.Method: This is an applied research conducted as a descriptive-survey. The target population includes all customers who used the electronic start-up services in the healthcare sector; out of which a sample of 384 individuals was selected using the Morgan table. A self-administered questionnaire was developed to collect the data which were analyzed using partial least squares and Smart-PLS software.Findings: All research hypotheses were confirmed, and it was proved that factors such as customer respect, customer enjoyment, importance of time, information security, convenience, perceived experience, valuable experience, and perceived image experience have a positive effect on improving customers’ online shopping experience in e-commerce start-ups.Conclusion: Applying the proposed model helps e-start-ups increase their performance   by eliminating their shortcomings and boosting their strengths.

Purpose: The purpose of this research was to provide a model for Validating and Presenting Brand-Customer Interaction Model in Digital Platform in the Cosmetics Industry.Method: This research was applied in its purpose and utilized a mixed approach (qualitative and quantitative). In this regard, this study was conducted with the aim of presenting and validating the brand-customer interaction model in Instagram Platform. The present study is a descriptive survey in terms of its practical-developmental purpose and data collection method. The statistical population in the qualitative section includes marketing professors and cosmetics industry managers, 20 of whom were selected by purposive sampling. The statistical population in the quantitative section also includes customers of cosmetics and health products, 384 participants were selected using the convenience sampling. The data collection tools were a semi-structured interview and a researcher-made questionnaire. First, thematic analysis method was used to analyze the expert interviews. Next, the identified pattern was validated using partial least squares method. Thematic analysis and partial least squares were done with MaxQDA software and Smart PLS software, respectively.Findings: The criterion to achieve data saturation has been to achieve repetition in extracting codes. 235 codes were identified in the open coding stage. Finally, three overarching themes, eight organizing themes, and 49 basic themes were obtained through axial coding. Based on the structural equation model, the proposed model was fitted and confirmed.Conclusion: Based on the results, effective marketing and digital content marketing are the basic elements of the model, which increase brand recognition and brand identity among customers by increasing interaction with customers. Brand recognition and identity contribute to positive word-of-mouth marketing, which in turn affects brand positioning on Instagram. Finally, in this way, it is possible to create a constructive and interactive brand-customer relationship.

The present research examines the benefits of implementing knowledge management (KM) principles in the Jordanian banking sector to enhance performance. The study emphasizes the significance of Artificial Intelligence (AI) and how Jordanian banks utilize it to improve the quality of customer service they provide. This study targets managers at all levels and focuses on the Jordanian banking sector as its research environment. A questionnaire is created to gather information from a random sample to achieve the research's objectives. The study involves a sample of 250 managers. Additionally, the research adopts a descriptive methodology, and SPSS is used to analyze the data. The statistical findings provide robust evidence for the importance of performance expectations, social influence, and perceived risk in influencing consumer intentions. Marketers and decision-makers within the banking industry can leverage these insights to shape their long-term strategies for effectively utilizing and maximizing AI technology in the banking sector. Furthermore, by providing policymakers and practitioners of Jordanian commercial banks with insight into the variables influencing user satisfaction, the findings will help these complex institutions operate more effectively.

In terms of storage and consumption, blockchain technology is poised to transform the way we manage healthcare data. The primary goal is to empower individuals to take charge of their health records, allowing them to become independent of the institutions or organizations they use. Elec-tronic Health Records (EHRs) can be tracked in a novel and unique way through blockchain tech-nology and smart contracts. This technology can give patients more control over their data. Health practitioners and institutions, such as hospitals, may be granted access to patient data controlled by other organizations. This research highlights how blockchain technology can be used to manage EHRs while improving operational efficiency through process simplification and transparency. Additionally, the study proposes an architecture for managing and sharing healthcare data across enterprises. The suggested approach could significantly reduce the time required to transfer patient data among various health organizations while lowering overall costs.

Purpose: The libraries of medical sciences universities have much more diverse goals and services than can be publically conceived, so providing services related to information resources is one of the most important challenges facing these organizations.Method: The present study is an applied research based on its purpose and descriptive-analytical as regards method. The study utilized the semi-structured interview method to obtain the factors affecting the provision of health information resources services. Sampling was conducted based on a purposeful method and experts’ viewpoints. The sampling was carried out the fuzzy Delphi technique which aimed to provide a solution for the issues. A researcher-made questionnaire was used to check the factors obtained from 62 central libraries of medical sciences.Findings: In general, six types of services were determined as health information resource services in specific central libraries, including tools for exploring the online book registration network, selection tools, interlibrary loan, free educational tools, additional book publishing tests, and content evaluation. Additionally, eight factors were identified, including providing services of specialized bibliographic review by librarians, consultation services to users, dissemination and provision of selective information services on Persian and Non-Persian sources, overcoming the weaknesses of librarians without library education, increasing the diversity of medical sciences library services, utilizing new technologies to compensate for deficiencies and lack of resources, improving the social function of the library as a social institution, and offering various electronic services such as databases and digital resources. These identified factors were found to influence the provision of health information resources.Conclusion: Various factors may affect the provision of health information resources services in universities of medical sciences, most importantly improvement of the social functions of libraries.

Purpose: The purpose of this research is to present and explain the establishment pattern of the fifth-generation university in Islamic Azad Universities. Future thinking and the university system's policy in higher education have become necessary with the effectiveness of virtual and electronic learning. Higher education based on digital developments has entered a new era where competition and quality are its main characteristics. One of the challenges facing universities in the new millennium is the concept of the fifth-generation universityMethod: This research was conducted using a qualitative-inductive approach and the Strauss-Corbin grounded theory method. The research tool (data collection) is a semi-structured interview. Using the grounded theory method, the data obtained from the interviews, conducted with 10 professors and managers of Islamic Azad University, were analyzed during three stages of open, central, and selective codingFindings: 20 general categories in the form of a paradigm model including factors including causal conditions ( knowledge development; new social needs; internal organizational factors; external organizational factors; mechanisms of first-generation universities, second-generation universities, third-generation universities, and fourth generation universities) central phenomenon (establishment of the fifth generation university), underlying conditions (creating social, cultural and political in the university; economic development of the university; organizational support platforms), intervening conditions (the existence of a dynamic environment and structure in the university) and strategies (changing the educational approach; environmental re-engineering; academic effectiveness; development architecture) and consequences (elite development; comprehensive effectiveness of the university; The emergence of the characteristics of the fifth generation university) is the result of this investigationConclusion: The establishment of a fifth-generation university in higher education can lead to the optimization of the resource allocation behavior of different stakeholders and prevent the waste of resources (financial resources, life or time of students, etc.), which leads to the overall effectiveness of the university; The establishment of the fifth generation university and the development of civilization. 

Purpose: The field of providing information and the method of publishing information has permanently been subject to modification and alteration, and as we know, with the introduction of computer technology in the field of librarianship and the change in the way of providing services, the imperative task of information dissemination has been reserved for librarians. The dissemination of information technology into the education system has led to the emergence of a new concept called e-learning. The task of libraries is to provide infrastructures for information retrieval through the production of integration, organization, and distribution of knowledge. The methods that libraries employ for e-learning include learning collections, tools, and facilities necessary for studying, improving the quality of reference services, and ensuring universal access to books. Therefore, this research aims to identify the factors influencing e-learning in information retrieval.Method: This current research is developmental was conducted using a qualitative approach and grounded theory. The population of the study consisted of 20 experts in the field of information technology in public libraries across the country, who were selected through purposive non-probability sampling. Data were collected through interviews and analyzed through three stages of open, axial, and selective coding, based on which the research model was designed.Findings: The findings showed that e-learning in information retrieval contains of six main dimensions, 45 sub-dimensions, and 85 concepts, which are presented in a paradigm model including causal factors (quality of e-learning website design, quality of education in e-learning environments, employees' enthusiasm for developing knowledge capabilities, employees' belief in continuous training), contextual factors (suitable technical equipment (hardware, software, and network), availability of necessary infrastructure, high accessibility, periodic purchase of required equipment, ease of learning and simplicity of teaching platforms (instructors)), interveners (competence of instructors in course delivery, course development based on indigenous data, organizational culture and atmosphere), central factors (strategies for enhancing the quality of e-learning in information retrieval, processes for improving the quality of e-learning in information retrieval, infrastructures for improving the quality of e-learning in information retrieval), strategic factors (existence of an appropriate incentive system for promoting knowledge sharing (systemic strategy), security of software used (educational approach), efficient support and feedback mechanisms (responsiveness strategy)), and consequences (consistency of goals and plans, adequate understanding of e-learning, formulation of standards, capability in information retrieval).Conclusion: Based on the dimensions, main factors, and sub-factors, the impacts of e-learning in information retrieval can be measured and managed in the studied community.

This research delves into the socio-economic aspects of online gambling in Iran, exploring the underlying cultural drivers that have contributed to its rapid growth in recent years. Online gambling's prevalence is intricately linked to cultural norms and values, both overt and covert, which have shaped its emergence in the country. Despite the religious, legal, and cultural taboos associated with gambling in Iran, this study investigates the cultural motifs that have challenged these obstacles, particularly among the youth. To unravel the psychological mechanisms at play among young online gamblers, this study adopts a qualitative approach, employing in-depth interviews with 17 male online gamblers aged between 20 and 40, alongside participatory observations. The data is analyzed thematically, with a focus on cultural motifs that reinforce mental accounting biases, drawing from the principles of behavioral economics. Notably, the central theme that emerges from this analysis is the "psychology of success", a worldview that influences the mindset and actions of individuals engaged in online gambling. The findings of this study reveal a significant thematic alignment between the teachings of the psychology of success and the cultural elements that bolster cognitive biases in the speech and conduct of online gamblers. The psychology of success, which emphasizes a sense of agency and empowerment, appears to drive cultural change and contributes to the widespread acceptance of online gambling despite its illegitimate status. Furthermore, the study highlights a connection between the prevalence of online gambling and the devaluation of the national currency.

In healthcare, a diagnosis is reached after a thorough physical assessment and analysis of the patient's medicinal history, as well as the utilization of appropriate diagnostic tests and procedures. 1.7 million People worldwide lose their lives every year due to complications from chronic kidney disease (CKD). Despite the availability of other diagnostic approaches, this investigation relies on machine learning because of its superior accuracy. Patients with chronic kidney disease (CKD) who experience health complications like high blood pressure, anemia, mineral-bone disorder, poor nutrition, acid abnormalities, and neurological-complications may benefit from timely and exact recognition of the disease's levels so that they can begin treatment with the most effective medications as soon as possible. Several works have been investigated on the early recognition of CKD utilizing machine-learning (ML) strategies. The accuracy of stage anticipations was not their primary concern. Both binary and multiclass classification methods have been used for stage anticipation in this investigation. Random-Forest (RF), Support-Vector-Machine (SVM), and Decision-Tree (DT) are the prediction models employed. Feature-selection has been carried out through scrutiny of variation and recursive feature elimination utilizing cross-validation (CV). 10-flod CV was utilized to assess the models. Experiments showed that RF utilizing recursive feature removal with CV outperformed SVM and DT.

In today’s world, there is a notable focus on incorporating disabled people within the community and the workplace. Advancements in artificial intelligence (AI) have the potential to significantly impact empowering individuals with disabilities to enhance inclusivity and autonomy for this demographic in the era of Society 5.0. This paper aims to offer a bibliometric analysis of the increasing number of publications addressing the potential impact of AI on disabled individuals and their future employment. To conduct this analysis, Scopus served as the bibliographic source, using Disability, Employment, and Future Workforce as the search terms, yielding 203 publications on the subject of study from 1973 to 2024. The analysis was conducted using VOS viewer. The results indicate that as Society 5.0 evolves, advancements in AI have the potential to significantly empower individuals with disabilities, enhancing inclusivity and autonomy for this demographic.

Purpose: The purpose of this research was to provide a model for dynamic knowledge management in Iranian government organizations.Method: This research is applied in terms of purpose, survey-exploratory in terms of approach, and qualitative in terms of type. The statistical population of this research was a group of experts, including university professors, and senior managers of the Zanjan Province Industry, Mining and Trade Organization, and based on theoretical sampling, 11 of them were selected as a statistical sample and were interviewed. The approach adopted in this research to analyze the interviews was theme analysis.Findings: The results of the research led to the presentation of a new model in the field of dynamic knowledge management in Iranian government organizations, including five main variables (including: promotional levers of dynamic knowledge management, intra-organizational factors of dynamic knowledge management, extra-organizational factors of dynamic knowledge management, executive levers of dynamic knowledge management, and expected consequences of dynamic knowledge management).Conclusion: The results of this research showed that if dynamic knowledge management is implemented well in Iran's government organizations, it can be expected that organizational productivity and agility and the satisfaction of stakeholders will improve.