درخت حوزه‌های تخصصی

With the rapid advancement of information and communication technology (ICT), public administration has adopted the concept of e-government. The academic literature produced many studies in the field of E-government (E-GOV) services, however, there is limited research on such services from the perspective of bibliometric and Network analysis. Therefore, this study aims to present a bibliometric and network analysis of the E-government services literature review obtained from the Scopus database, published between 2011 to 2021. This study uses a five-step method including (1) defining keywords, (2) initializing search outcomes, (3) inclusion and exclusion of some elements of the initial result, (4) compiling initial data statistics, and (5) undertaking analysis of data. The analysis starts by identifying more than 4,880 published articles related to E-government services published between 2011 and 2021. The study findings revealed that the highest number of publications on the E-government Service was in 2019 (102 articles), the top contributing affiliation was Brunel University London, the leading influential country was the USA, and the top contributing Source was Electronic Government. Furthermore, Lu J. occupied the first rank in the list of the most influential authors in terms of citations, while Weerakkody V. occupied the list of the top authors with high publications 20 papers. Likewise, this study showed that there is a collaboration among some authors. This research identified four research clusters by which researchers could be encouraged to widen the research of E-government services in the future. The bibliometric and network analysis of E-government services helps to graphically display the publication's assessment over time and identify domains of current studies' interests and potential directions for further studies. Finally, this research draws a roadmap for future investigation into E-government services.

Purpose: The growth of Smartphone applications has led to the development and transformation of business sector. The present work aimed to assess factors influencing the intention to use shopping applications.Method: A structural model was formulated for analyzing and testing the existing factors among shopping application users. The statistical population of the research comprised of the users of shopping applications in a public university in Iran. This study employed a questionnaire survey, which consisted of two sections. The first section included general demographic details of the target respondents, while the second section comprised 30 items to measure the constructs of our conceptual model. All items of constructs were adopted from previous literature. A total of 288 questionnaires provided usable data.Findings: The results revealed that factors such as Convenience, Perceived Ease of Use, Trust, and Perceived usefulness affect the intention to use shopping applications, while factors such as Perceived Innovativeness, Perceived Risk, Perceived Enjoyment, and Social Influence were found to be non-influential.Conclusion: This research was conducted based on a comprehensive review of the research literature and identification of influential constructs with the approach of creating an integrated model of factors affecting the intention to use shopping applications. Based on the research results, focusing on ease of use and creating the experience of perceived usefulness along with the use of tools that lead to the improvement of trust is critical for practitioners.

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.

Today, gamification is being used in various areas such as education, health, and business to enhance engagement and increase the system's efficiency. Despite significant scholarly interest, in many cases, undesirable results have been achieved using gamified solutions. This highlights the need for further research to explore these challenges through innovative methodologies and to devise new solutions. Addressing this gap, we conducted a systematic review of the literature on the emerging and growing subject of gamification using the PRISMA methodology and proposed a novel model for the strategic development of future gamification studies. The research led to the identification of 48 qualified empirical studies which have been analyzed to outline the existing views, gaps, and consequently the implications for future research. Through the analysis, we delineate the impact and effectiveness of gamification, highlighting its potential to transform user experience positively when implemented with strategic finesse. Consequently, we propose a novel model for the strategic development of future gamification studies, presenting it in three main dimensions: Contexts, Users, and Elements, and for each dimension, significant and less-paid topics are discussed. In addition, we represent six main suggestions for the design of the entire gamified system: Decision-Making Methods, Success Factors, Validation Methods, Dynamic Design Approach, Timeframe, and Modern Technology. Our proposed model not only facilitates a deeper understanding of gamified systems but also offers actionable insights and guidelines for both academics and practitioners. It is meticulously designed to assist researchers and practitioners in crafting more effective gamified systems that are customized to meet specific user needs and environmental contexts. By doing so, it aims to maximize the sustainable benefits of gamification, ensuring that these systems deliver significant and lasting impacts. This strategic approach integrates the latest advancements in technology and dynamic design principles, establishing a robust framework for the future of gamification research and application.

The adoption of E-learning in academic environments, particularly in Iran, has accelerated over the past decades. However, the lack of established guidelines for instructional design seems to have hindered the creation of effective online educational environments. Therefore, this study aimed to conduct a comprehensive qualitative research synthesis (QRS) to identify the criteria for an optimal online learning environment for Iranian university students. The study followed Major and Savin-Baden's three-phase QRS model and included 12 studies with 252 participants and 42 researchers. The synthesis integrated findings from multiple studies to gain insights into experts’ opinions and students’ perceptions, preferences, and experiences within online learning environments. The research identified four overarching themes: targeted learning, effective teaching management, socio-affective engagement, and learner empowerment. Targeted learning focuses on problem-oriented and need-oriented teaching; effective teaching management emphasizes balanced content and time management, clear objectives, and diverse presentation and evaluation methods; socio-affective engagement involves interactive feedback, social presence, and emotional communication; learner empowerment stresses autonomy, agency and active learning, including experiential and discovery learning. Applying these findings seems to offer a genuine contribution, leading to the development of culturally relevant and high-quality E-learning experiences and addressing the challenges posed by the nascent E-learning system in Iran.

The advancement of artificial intelligence (AI) and its growing societal importance are reshaping decision-making processes and policy analysis roles. This study examines the readiness of manufacturing companies in Malaysia to embrace AI technology, considering its potential to enhance decision-making, productivity, quality control, job automation, and data analysis. Focusing on the Technology, Organization, and Environment (T-O-E) readiness framework, the research investigates the relationship between these dimensions and AI adoption readiness among manufacturing companies in Shah Alam, Selangor, Malaysia. AI adoption readiness serves as the dependent variable, while technological, organizational, and environmental readiness dimensions act as independent variables. The study applies the T-O-E framework to AI readiness and proposes a framework for assessing AI readiness at the manufacturing level. It identifies factors influencing readiness within the technological, organizational, and environmental dimensions, including relative advantage, compatibility, resources, competitive pressure, top management support, and government regulations. Through rigorous analysis, patterns, trends, and correlations are revealed, highlighting a significant link between the T-O-E readiness dimensions and AI adoption readiness. Notably, organizational readiness emerges as a key driver of AI adoption in Malaysian manufacturing companies. The results of this investigation have broad implications, offering suggestions to improve organizational preparedness and unlock AI’s potential benefits for businesses in the industrial sector. Additionally, the research lays the groundwork for further studies on AI readiness across various industries and international contexts. As AI becomes increasingly integrated into manufacturing processes, adaptive businesses gain competitive advantages on a global scale. These advantages include increased productivity, informed decision-making, streamlined quality control, improved customer satisfaction, and potential contributions to economic growth. The study concludes by recommending strategies to reinforce organizational readiness and emphasizes the need for future research to deepen understanding of AI adoption readiness in the manufacturing industry. The integration of AI technology offers benefits such as enhanced productivity, decision-making, quality control, and customer satisfaction, granting businesses a competitive edge in the digital landscape and increasing stakeholder interest.

The eXtensible Business Reporting Language (XBRL) functions as an independent, open platform that facilitates efficient information transmission over the Internet, improving business information utilization. Despite its widespread adoption and numerous benefits, unresolved assurance issues undermine its effectiveness, revealing a significant research gap. This study explores the complex landscape of XBRL data assurance challenges within the Malaysian Business Reporting System (MBRS). Utilizing a qualitative case study methodology, the research highlights key challenges in XBRL data assurance and presents strategic, innovative solutions. Through semi-structured interviews and document analysis, insights from diverse stakeholders are captured, revealing the development of artificial intelligence-enhanced audit software aimed at improving the quality of XBRL filings in Malaysia. Despite its potential, awareness of this advanced software among preparers remains disappointingly low. This research serves as a valuable resource for practitioners and researchers, offering an in-depth analysis of XBRL data assurance challenges and pioneering solutions, thereby making a significant contribution to this critical field.

For investors, predicting stock market changes has always been attractive and challenging because it helps them accurately identify profits and reduce potential risks. Deep learning-based models, as a subset of machine learning, receive attention in the field of price prediction through the improvement of traditional neural network models. In this paper, we propose a model for predicting stock prices of Tehran Stock Exchange companies using a long-short-term memory (LSTM) deep neural network. The model consists of two LSTM layers, one Dense layer, and two DropOut layers. In this study, using our studies and evaluations, the adjusted stock price with 12 technical index variables was taken as an input for the model. In assessing the model's predictive outcomes, we considered RMSE, MAE, and MAPE as criteria. According to the results, integrating technical indicators increases the model's accuracy in predicting the stock price, with the LSTM model outperforming the RNN model in this task.

The introduction of information technology in the structure of procedural legal relations contributes to the full implementation of the principles of procedural law and optimization of civil proceedings. The purpose of this study is to develop scientifically sound proposals and recommendations for the latest concept of optimization of civil justice by means of information technology. The study of the impact of information technology in civil proceedings was conducted on the basis of integrated use of general and special methods of scientific knowledge. The optimization of civil proceedings as a system of theoretical ideas and views on civil procedural activity from the standpoint of means, methods and techniques of its improvement is considered. The basic elements of the latest concept are the provisions of the general methodological basis for studying the problem of optimization, the concept and structural characteristics of optimization, civil jurisdiction in terms of optimization and ensuring the right to due process, optimization of procedures for preparation and trial of civil cases, cassation in the system of instance review of court decisions. It has proved that the search for a harmonious combination of protective and conciliatory functions of civil proceedings, as a characteristic concept of modern procedural systems, determines the main directions of optimizing the preparation of civil cases for trial. It has established that in the reform of the judiciary of Ukraine it is important not only to digitize existing processes. The most important thing is to change the approach to justice itself, making it simpler and more accessible to all with the help of information technology. In this sense, the introduction of affordable online court involves not only the introduction of innovative technologies, but also the revision and significant simplification of procedural rules.

Nanotechnology, at the intersection of science and engineering, holds immense promise for revolutionizing various aspects of our lives. This study employs the Partial Least Squares Structural Equation Modelling (SEM AMOS) algorithm to comprehensively analyze the effects of nanotechnology on the future living standards of society. We examine how nanotechnology innovations in fields such as medicine, energy, materials, and electronics are poised to reshape our quality of life. Through an extensive review of existing literature and empirical data, we provide insights into the potential benefits and challenges associated with the widespread adoption of nanotechnology. Our findings suggest that nanotechnology has the potential to significantly enhance future living standards by enabling advancements in healthcare, sustainable energy solutions, and cutting-edge materials. However, we also identify key considerations, including ethical and safety concerns that must be addressed to ensure the responsible development and utilization of nanotechnology. This research contributes to a better understanding of the multifaceted impacts of nanotechnology on society, offering valuable insights for policymakers, researchers, and stakeholders seeking to harness its transformative potential for the benefit of humanity.