Customer satisfaction is the bedrock of e-commerce. This study identifies the factors and consequences of the perceived flow of consumers with shopping websites. The research scrutinizes the association linking purchase intentions arising from customer satisfaction, website quality and perceived flow by incorporating the model of Stimulus Organism Response. The data were collected from online shoppers using purposive sampling targeted through social media. The data from 270 respondents have been analyzed using SmartPLS incorporating the Partial Least Square-Structural Equation Modeling. The assessment showed an important beneficial impact of website usability, their security, functionality, and privacy features on the perceived flow of customers. Furthermore, perceived flow has been found to affect customers’ purchase intentions as well as satisfaction, and lastly, purchase intention is induced by how satisfied customers are with their shopping experience. The findings identify how important perceived flow functions in enhancing purchase intentions and customer satisfaction online. The findings can be noteworthy for online businesses and banks to improve online shopping experience and transactions.

Agriculture products are one of the main income sources of developing countries. This study analyzes the road transport system (network) to reveal the network’s structural properties and identifies hubs that consolidate agricultural products to export to China via the China-Laos railway. Analysis of 20 provinces in the Northeast of Thailand has found that the network has 340 districts connected by 1,015 transport routes. The network is sparse, in which all districts cannot be connected to each other. The network has low connectivity efficiency but has high intra-connectivity among districts in the same province. In addition, the network has a modularity structure that can develop the communities. Hubs consolidating agricultural products of the region are Na Khu, Kuchinaria, Mueng Chiyaphum, Nam Phong, Na Wa, Mueang Mukdahan, Prasat and Rasi Salai. The findings of the study draw implications for the government, sector and exporters to design and improve their operations and services.

Recently, due to the tremendous development in information and communication technology, the world is moving rapidly towards digitization in all areas of life. In the financial context, Financial Technology (Fintech) has the potential to transform the financial sector by offering innovative digital solutions, but its adoption depends on various individual, organizational, and environmental factors. This research paper aims to identify and analyze the determinants that influence the intention to adopt fintech. A self-administered survey was utilized to collect the necessary data. Data were analyzed using SPSS version 26 for descriptive analysis as well as SmartPLS version 3.0 by implementing the PLS algorithm and Bootstrapping techniques. This study finds that intention to adopt Fintech is affected by perceived usefulness, perceived ease of use, trust, social influence, and facilitating conditions. This study also examined the relationships between these variables. The findings will provide insights for fintech stakeholders, policymakers, and researchers to foster a conducive environment for Fintech adoption and usage.

Small and Medium Enterprises (MSEs) are one of the people's economic enterprises that have an essential role in advancing the Indonesian economy. Improving the overall, optimal and sustainable performance of SMEs business increases contribution to the economy in provinces in Indonesia, one of which is Bali Province, the province with the highest absorption of SMEs in Indonesia, namely 10 percent of its population. Denpasar City, as the capital of Bali Province, is the center of trade in Bali, especially the relatively even distribution of SMEs in every sub-district in Denpasar City. This research aims to analyze the role of live streaming in moderating the influence of entrepreneurial marketing and e-commerce on the performance of fashion SMEs in Denpasar City. The research involved 134 fashion SMEs in Denpasar City as samples. Data collection was carried out by distributing questionnaires. Then, the data was analyzed using SmartPLS. The test results of live-streaming commerce moderating the influence of e-commerce adoption on business performance show that live-streaming commerce moderates with a quasi-moderation type the influence of e-commerce adoption on business performance. Live streaming commerce moderates the influence between the independent variable e-commerce adoption and the dependent variable business performance and influences business performance.

The digital economy is a phenomenon that has emerged in today's modern era. Digitalization is expected to be able to support the progress of the economic aspect. However, it turns out that not all people in parts of the world are able to keep up with this change in the phenomenon of economic digitalization. This study aims to identify, classify, and analyze the factors that influence the conditions of acceptance of the digital economy in developed and developing countries as measured through the Digital Economy Acceptance Index (DEAI). This research used a quantitative approach with research objects from countries in the world during the past years. The methods used in this research are composite index and multivariate statistical cluster analysis. The results showed that countries with high DEAI consisted of the United States, Canada, Japan, Australia, New Zealand, Austria, Belgium, Denmark, Finland, France, Germany, Ireland, Netherlands, Spain, Sweden, Switzerland, and Singapore. Countries with moderate DEAI consist of Greece, Italy, Portugal, Brunei Darussalam, China, Indonesia, Malaysia, South Africa, Libya, Brazil, Philippines, Thailand, Vietnam, Iran. As well as countries that have low DEAI, namely Cambodia, Myanmar, Egypt, Laos, India, Pakistan, and Sri Lanka.

The high quality of public services is a guarantee for the public of easy and efficient access. Good quality public services can help increase people's productivity, reduce unnecessary bureaucracy, and encourage more active participation from all walks of life. In addition, government transparency serves as the main basis for building a relationship of mutual trust between the government and society. Through the application of information and communication technology, E-Government allows the government to provide public services more efficiently, quickly and easily. This research aims to analyze the influence of information technology, administrative management, and knowledge management practices on the success of E-Government. This type of research is quantitative research using a questionnaire. Respondents were selected using a random sampling method from various groups in the public sector in the DKI Jakarta province. A total of 380 questionnaires were distributed to respondents, and 264 questionnaires were successfully returned. However, there were 21 questionnaires that were not filled in completely. Finally, 243 questionnaires were analyzed further. Questionnaire measurements used a Likert scale of 1 - 7. The data in this study were analyzed using SmartPLS 4 software. The results of this study conclude that the implementation of information technology has a significant relationship with knowledge management practices. However, the relationship between information technology and e-government in this study was not proven to be significant. Administrative management has a significant relationship with knowledge management practices but has no significant effect on E-Government. Knowledge management practices have a significant influence on E-Government and there is interaction between information technology and knowledge management practices, as well as between administrative management and knowledge management practices on E-Government.

The increasing amount of IoT devices increases the size of network traffic data, causing an increase in the incidence of security breaches in IoT networks. Cybercriminals have developed malware to compromise the security of sensitive data, among other cyber threats. In the presence of inadequate and robust security mechanisms, sensitive data is prone to vulnerability. Hence, protecting data in the IoT environment is becoming a mandatory task. Various approaches have addressed malware detection using network data features. However, there is still room for improvement in developing superior techniques and utilizing more comprehensive datasets. This paper presents a novel lightweight ensemble voting classifier to detect malware traffic by deploying the best possible network data. The merits of the correlation coefficient and Opposition-Based Crow Search Algorithm (OCS) have been leveraged to compute the best possible features. Another advantage of this proposed experiment is its focus on a dataset tailored to malware traffic features. This focus enables highly accurate malware detection. After feature selection using OCS, the proposed malware classifier is trained and validated with both 5-fold and 10-fold cross-validation techniques. The tested results confirm that the presented malware classifier performs best using a minimal feature set, which is highly advantageous for IoT networks due to resource constraints.

Despite certain advancements, the incorporation of artificial intelligence in universities is still inadequate. The requirement for students will continue for a while, although the development of artificial intelligence-based chatbots in schools has limited the role of students. The research aimed to assess the willingness of Jordanian learners in higher education to use artificial intelligence-powered chatbots for instructional purposes. The present research suggests nine hypotheses derived from the UTAUT2 model to assess students' desire to use artificial intelligence-based chatbots in learning. The pupils' information was gathered and examined using PLS-SEM. The research results showed that nine hypotheses were confirmed. The outcomes indicate that learners are interested in adopting artificial intelligence-based chatbots into their studies. The research's findings will supply administrators at higher education with valuable insights into the effectiveness of artificial intelligence-based chatbots in learning. Moreover, the findings will help developers of artificial intelligence-based chatbots, higher learning administrators, and legislators execute artificial intelligence-based chatbots that fulfil modern educational requirements.

Advancements in technology have had a profound impact on the way we learn, teach, and access knowledge. From online learning platforms to interactive educational games and virtual reality simulations, technology has transformed the traditional classroom into a dynamic, engaging, and inclusive space for education. One of the promising advancements in the field of artificial intelligence technology is ChatGPT which offers personalized and effective learning experiences by providing students with customized feedback and explanation. The effect of ChatGPT must be compared with the effect of Google at the educational level since both present a source of information and explanation. Thus, this study aims at investigating the differences between these two learning sources to measure their effectiveness from different perspectives. The model proposed in this study was evaluated using the PLS-SEM approach, utilizing data collected from 153 university students in the UAE. The results of this evaluation indicate that the GPT (Generative Pre-trained Transformer) has a significant impact on user acceptance, mediated by information quality, system quality, perceived learning value, and perceived satisfaction. These factors play a crucial role in determining users' acceptance of the GPT. However, it is important to note that some aspects of the model were not supported, suggesting that they do not have a significant predictive effect on the use of ChatGPT. Nonetheless, the findings of this study contribute to the existing literature on AI and environmental sustainability, providing valuable insights for practitioners, policymakers, and AI product developers. These insights can help guide the development and implementation of AI technologies in a way that aligns with users' needs and preferences while considering the larger environmental context.

The main objective of this study was to examine the effectiveness of a teaching program utilizing cloud computing in enhancing the writing skills of students with autism. The research comprised a group of kids diagnosed with ASD who attended schools situated in the Al-Mafraq Governorate. The initial intention was for the experiment to last for a duration of 30 days. A total of 30 students were included in the study, with 15 students randomly assigned to the experimental group and the remaining 15 students assigned to the control group. Following the implementation of the intervention, the experimental group demonstrated a higher level of performance on assessments measuring language and content abilities compared to the control group. There were no significant differences seen in the writing proficiency scores of the experimental group, both at the follow-up assessment and immediately after the intervention.