Abstract: The purpose of this study is to investigate the moderating role of digital marketing strategies on innovation through Artificial Intelligence (AI) mediating impact in Small and Medium Enterprises within Saudi Arabia. Advanced analytics tools analyzed data from KSA SMEs to establish the role of AI, customer behavior, and experiences in product and process innovation. Artificial intelligence boosts product and process innovation with unconventional customer knowledge. Integrating AI combined with digital marketing to improve decisions and efficiency, to increase understanding of customer dynamics for sustaining growth and promoting collaborations. Using AI-empowered digital marketing strengthens Saudi SMEs advancement by promptly reacting to market motions. Sustainability practices attract the environmentally conscious consumer. This research provides actionable insights for SMEs who want to employ digital marketing and AI strategies and contribute to building an economic environment in Saudi Arabia.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The main goal of this research is to study and investigate the impact of data management and analysis tools on improving organizational behavior within three IT service firms in Jordan. This research focuses on choosing three data management and analysis tools: Database analysis tool, data processing tool, and big data processing tool and how these tools could positively influence enhancing employee performance and organizational behavior. It accomplishes this within the distinct framework of three Jordanian IT service firms. The research supposed that combining big data analysis, integrated data processing, and database analysis is necessary to enhance organizational behavior and employee performance, as indicated by the findings. Furthermore, the research highlights the potential for IT service firms in Jordan to benefit from emerging database analysis technologies, promote the use of integrated data processing techniques, and leverage big data analysis for their own benefit. This can enhance corporate behavior and employee performance. Data was distributed and collected from three Jordanian IT service firms, and all collected data was analyzed using AMOS. The study's findings offer valuable recommendations for enhancing the operational efficiency of IT service firms in similar business environments, emphasizing the crucial importance of comprehending and purposefully employing database-related technologies for sustained prosperity.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study examines the extent of adoption of electronic payment methods in Jordanian banks and compares them with traditional alternatives. Focusing on banking customer behavior, we conducted a comprehensive survey among banking customers to uncover insights on trust, perceived benefits, financial literacy, ease of use, security and cost considerations. By analyzing the data collected using the questionnaire study tool, we reveal the motivations behind customers’ electronic payment preferences. By highlighting these factors, our research contributes to the understanding of the evolving payment landscape and provides actionable insights to enhance the adoption of electronic payment in Jordan’s financial system, in line with global technological trends. The results of the study revealed that all study variables had a significant impact (trust, ease of use, perceived security, and cost of service) on the use of electronic payment methods. In addition, gender, number of years of dealing with the bank, and type of electronic payment used more than once by customers in the banking sector did not have a significant impact.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Cryptocurrencies are crucial in modern commerce and finance, whether at the national, corporate, or individual level. They serve as fundamental currencies for buying and selling, enabling various business transactions. However, the rise of cybercrime has brought about concerns regarding their operations, potential breaches in encrypted currencies, and the security systems managing them. The frequency of attack tactics and the motivation of attackers seeking financial gain are well-known. Many cryptocurrencies lack the necessary algorithms, techniques, and knowledge to effectively detect and mitigate malware, making them vulnerable targets for hackers. In this study, machine learning techniques are employed to detect malicious code in digital currencies. Additionally, a comparison of these techniques is conducted to determine the most suitable algorithm and technology, Furthermore, this study highlights the importance of effective malware detection in securing cryptocurrencies. Three datasets of different sizes were used, each yielding distinct results based on dataset size. The AdaBoost model demonstrated superior performance when applied to the short dataset, while the decision tree model performed best with the medium-sized dataset. Conversely, the Naive Bayes model consistently produced the worst results, while the large-size KNN model achieved the highest performance.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: 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.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: 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.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: 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.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: 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.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: 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.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: 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.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: 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.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: 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.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: 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.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: 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.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The evolution of technology and the widespread adoption of smart mobile devices like smartphones and tablets have significantly altered tourists' behavior using tourism services. Based on The Unified Theory of Acceptance and Use of Technology, this research aims to investigate the factors affecting Gen-Y's inclination to use tourism apps in Vietnam. The model was tested using structural equation modeling (SEM) in quantitative methodology with 337 users from Vietnam. The result showed that five factors positively impact the intention behavior of using mobile tourism applications: performance expectancy, effort expectancy, social influence, trust, and perceived security. Moreover, the findings propose practical implications and provide valuable insights for tourism app developers, marketers and operators in developing more effective tourism apps.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The rapid progress of TICs has generated different ways to modify and transfer information, which implies the generation of new forms of knowledge. The objective of this study is to establish the relationship between digital competencies and university teaching performance in public higher education in Huancayo. The study is of a basic type with a quantitative approach and correlational level, developed with the partition as a sample of 272 teachers and 387 students who develop teaching-learning activities at the UNCP. The data were analyzed and modeled through structural equations based on PLS. The research arrived at the following results: a value of 0.890 in Spearman's Rho correlation coefficient and a significance level of .000, which shows that there is a high positive relationship between the study variables; likewise, the hypothesis is accepted. general which considers that there is a significant relationship between digital competencies and teaching performance in the classroom.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The classification of large-scale textual dataset is associated with a huge number of instances and millions of features which must be discriminated between large numbers of categories. The task requires the utilization of a defined hierarchy structure and tools that automatically classify instances within the hierarchy known as Large Scale Hierarchical Text Classification (LSHTC). Predicting the labels of instances by the employed classifiers is challenging due to the high number of features. Furthermore, the existing Dimensional Reduction (DR) approaches in cooperation with the LSHTC framework are still quite inefficient. In such a problem, an effective Hierarchical Dimensional Reduction approach can be advantageous in improving the performance of the LSHTC. Therefore, in this paper, we enhance the performance of LSHTC by proposing a Multi-stage Hierarchical Dimensional Reduction (MHDR) approach based on Modified Feature Hashing (MFH) and Hierarchical Bi-Filtering (HBF) method. In addition to alleviating bad collision and result discrepancy, experimental results show that the proposed approach has achieve the best performance in terms of micro-f1 and macro-f1 by recording average scores of 58.47% and 54.77% using TD-SVM, and average scores of 51.14% and 48.70% using TD-LR, respectively. The method also achieved 11% speed-up than the approaches compared.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Potential international students use social media platforms to acquire important information about schools and their brand reputations while making international higher education decisions. By means of a cross-sectional data from 384 international students at three universities in North Cyprus, the study aims to explore the relationship between social media engagement, information credibility and enrolment intention. Furthermore, if information credibility works as a mediator between social media engagement and enrollment intention, and the moderating role of student type. The study makes several contributions to the literature review and its recommendation helps top management at universities and policy makers in North Cyprus to pay attention to the role of social media in recruiting international students. The findings of this study indicate that credibility fully mediates the relationship between social media engagement and enrollment intention, but student type doesn’t moderate the relationship between information credibility and enrollment intention. The limitations and future studies are discussed in this study.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study investigates the mediating role of competitiveness in the relationship between FinTech adoption and banking performance in the Middle Eastern region. A quantitative research design is employed, utilizing survey data from banking professionals across multiple countries. The data is analyzed using PLS-SEM modelling. The results show a positive and statistically significant impact of FinTech integration on the competitiveness of financial institutions and the performance of banks. On the other hand, the mediation of competitiveness is involved in the process of FinTech adoption and bank efficiency, suggesting that banking institutions that can utilize FinTech advantageously have greater chances of translating the benefits of FinTech adoption into better performance. This study supports the literature by providing a practical example of the use of FinTech as a factor for competitiveness and improving the performance of banks in the Middle East. These findings have huge managerial and practical implications and can help large banks gain competitive advantage and effectively integrate FinTech platforms to achieve real improvements. The value of this research is that it fills the gap in the existing literature, i.e. the role of competition as a mediating factor. By combining studies on competitive strategy approaches with those on technological innovation theory, this study combines a complete worldview related to the performance of banks in the digital age.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This research aims to analyze the influence of e-leadership behavior on employee commitment at the immigration office, the influence of the e-Work Environment on employee commitment at the immigration office, and the influence of e-Job satisfaction on employee commitment at the immigration office. The research method used in this research is associative research. Associative research is research that aims to determine the relationship between two or more variables. In this way we can build a theory that functions to predict and control a phenomenon. The population in this study were all immigration office employees. In this research, an analysis model is used, namely Structural Equation Modeling (SEM). The respondents for this research were 678 immigration office employees who were determined using a simple random sampling method. Research data was obtained by distributing online questionnaires via social media. The instrument used in this research uses a Likert scale 7 scale. The data analysis stage of this research is testing the outer model and inner model. The outer model test consists of convergent validity, discriminant validity and composite reliability and the inner model test, namely hypothesis testing or significance testing. The results of data analysis show that e-leadership behavior has a positive and significant relationship to employee commitment at the immigration office, the e-Work Environment has a positive and significant relationship to employee commitment, and e-Job satisfaction has a positive and significant relationship to employee commitment at the immigration office.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study explores the factors affecting CliQ payment service adoption in Jordan as it represents a major shift in the Jordanian market to Fintech and mobile marketing. This study presented a distinctive model by integrating the “unified theory of acceptance” and the “technology acceptance model” TAM with the “use of technology UTAUT” to measure the behavioral intention of consumers and the satisfaction of the users towards utilizing the CliQ service. The study measured the linkage between four predictors (perceived usefulness, social influence, perceived ease of use, and financial risk) as well as both utilizers’ intention to CliQ service usage and utilizers’ satisfaction with using the service, along with observing the association between these predictors to determine their contribution to the users’ satisfaction mediated by the users’ intention to utilize the service mentioned above. A survey instrument was distributed to 604 respondents, and it was developed and validated by academics, as a pilot test. As well as a pre-test. Hypotheses were tested with multiple linear regression analysis using SmartPLS software to interpret path coefficients, and reliability and validity within the outer model were tested through correlation analysis. Additionally, internal consistency was explored by applying Cronbach’s alpha. The outcomes proved that the predictors significantly affect both utilizers’ behavioral attitudes and satisfaction with using the CliQ service, except for financial risk. The data analysis also indicated a significant indirect influence of all the independent variables on utilizers’ satisfaction through behavioral intention to utilize the CliQ service, except for financial risk, which had an insignificant indirect influence on utilizers’ satisfaction through behavioral intention for service usage. The findings of the current article close the gap found in the literature concerning measuring usability to enhance user satisfaction and adoption of Fintech services. Therefore, bank managers and policy planners can find insights for developing and improving mobile banking apps.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: With flexible learning, students are actively engaged in their own education and are held to high standards of performance. Online academic courses make it easier for students to receive personalized education because they provide students with more flexibility to concentrate on what is most important to them and give them greater control over their own education. This study’s objective was to investigate whether there is a correlation between how well students succeed in online classes and the extent to which they make use of the schedule and the geographical and resource flexibility offered by such programmes. This article uses a developing approach for predicting and classifying the flexibility in online learning of students who are at risk of failing due to academic and demographic variables. The K-nearest neighbours (KNN) method, the random forest (RF) method, and the logistic regression method were used to categorise the students participating in flexible online learning. The information for the dataset came from Kaggle, and it was gathered for use in testing machine learning. The dataset had a total of 1,875 instances representing 11 different features. Also, accuracy, precision, sensitivity and f-score metrics were applied to evaluate the system. The results show that the RF algorithm has a high accuracy percentage of 85%. The empirical findings demonstrate that students formed distinct patterns of learning time, location and access to knowledge. This suggests that flexibility was used to a significant degree. Patterns in learning time and the availability of learning materials were shown to have a substantial relationship with the accomplishments of the students. Understanding flexibility use habits may help adapt lessons and boost collaboration among similar students.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study attempts to study the impact of the moderating role of internal audit between cloud accounting and limiting creative accounting practices in commercial banks. The study utilized a descriptive and analytical approach. The target population of this research consists of all employees of the 13 Jordanian commercial banks listed on the Amman Stock Exchange, while the number of employees in commercial banks is (22,407) employees. This led to the use of a simple random sample of (400) employees. The results found that there is a positive effect of the moderating role of internal audit on the impact of cloud accounting on reducing creative accounting practices in commercial banks. The study suggests that future studies should give recommendations and proposals to improve and develop cloud accounting and internal auditing in commercial banks, increase transparency, monitoring and compliance in accounting and financial operations, and reduce the risks associated with cloud accounting and creative accounting practices.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Social cybernetics, as an interdisciplinary field, has gained increasing interest in the last decade due to the influence of information technologies in society through connectivity, Internet of things, process automation, artificial intelligence among others. This research focuses on exploring the relationship between social cybernetics (communication and control mechanisms) based on information technologies and local development, using structural equation modeling as an analytical tool. The design was non-probabilistic, with a sample of 482 people. The independent variables under study were Use of ICT for communication between local authorities and the population (CAP), Use of ICT for collaboration between public and private institutions (CPPC), Use of ICT for shared decision making (SDM), Use of ICT for local development planning (LDP) and Use of ICT for knowledge management (KM); and the dependent variable was Local Development (LD). It was determined that there is a relationship between all of them except with CAP. The direction and magnitude of the other ratios were: + 0.1390; - 0.3661; + 0.4472 and + 0.8432 respectively. The coefficient of determination (R2) was 93.69% facilitating the prediction of future results. The model has an adequate fit.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The purpose of this study is to explore how various online marketing tools, including Content Marketing, Email Marketing, Social Media Marketing, and SEO, affect customers' decisions to purchase Internet services. The study utilized a survey distributed through simple random sampling, with 410 questionnaires given to Zain Telecom customers in Zarqa city. After excluding incomplete questionnaires, 385 were analyzed using multiple regressions, descriptive analysis, and reliability tests. Results showed that all independent variables had a significant impact on customers' purchasing decisions of Internet services, with Email Marketing having the strongest relationship. The study recommends further investment in Email Marketing strategies to improve customer retention and acquisition.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This paper addresses the conceptual exploration of various issues that form an integral part of the ethical dimensions surrounding the use of artificial intelligence (AI) in the field of marketing. We critically review some of the main ethical challenges AI poses to humanity: privacy, data security, bias, transparency, and accountability. Therefore, we will discuss the delicate balance between exploiting the transformation potential of AI for personally designed marketing strategies and ethical imperatives to safeguard the rights of consumers to retain trust. Then, the present regulatory landscape responding to these ethical challenges will be assessed by building on effective regulation, like the GDPR, existing proposed legislative frameworks, and industry guidelines. To underscore the role of an ongoing dialogue between marketers, technologists, ethicists, and regulators for developing a responsible AI ecosystem in marketing. Further, strategic recommendations for implementing company-based ethical AI marketing practices. The further strong guidelines provide enhancement transparency to consumers and investment in research to remove biases from algorithms. It also underscores principal scopes of further research and development, focusing on the need for new-age solutions to guide the ethical quagmires that AI-led marketing throws up. We suggest that integration should be done proactively and collaboratively. Thus, if attention is paid more to ethics and multidisciplinary dialogue, only such hyperbolic promises can be realized by AI-driven marketing. There are promises through which AI-driven marketing will meet business goals and be huge at societies' values.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: A Distributed Denial of Service (DDoS) attack occurs when an attacker tries to disrupt a network, service or website by flooding huge numbers of packets on the internet traffic. Detecting DDoS attacks serves the goal of spotting and addressing them promptly to reduce their effects on the network, system or service being targeted. Detecting Distributed Denial of Service (DDoS) attacks is crucial, for people, companies and network managers. The detection of DDoS attacks has ranging uses in industries such as network security safeguarding websites, managing cloud services ensuring the security of online systems and services. Detecting DDoS attacks is essential for safeguarding infrastructure upholding service availability and guaranteeing the security of online systems and services. To achieve this objective, we proposed a framework to detect DDoS attacks including six steps. In step one, we start by gathering information, which includes network activity and system records, for operations as well as instances of DDoS attacks. Step two, we identify characteristics of the data collected such as patterns in network traffic, packet details, IP addresses, types of protocols used and more. Step three, we utilize algorithms for feature selection such as Salp Swarm Algorithm (SSA), Gray Wolf Algorithm (GWA), Particle Swarm Algorithm (PSO) to pinpoint the features that can distinguish between normal activities and DDoS attack patterns. After that in step four, we divide the processed dataset into sections for training and testing purposes to develop and assess the machine learning models such as SVM (support vector machine), and KNN (K-nearest neighbor). Step five we develop a classification model using machine learning techniques like decision trees, forests, support vector machines (SVM) logistic regression models or neural networks. Finally, we assess the effectiveness of models through metrics such as accuracy rates, precision levels, recall rates, and F1 scores. The results show that the proposed models achieve high results (99.9%). In summary detecting DDoS attacks is crucial for protecting networks, systems and online services against disruptions.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study conducted a thorough analysis of a dataset from a video game to reveal the relationship between game content, interactive features, and classification ratings. The project attempted to convert raw data into meaningful insights by employing Python for data processing and machine learning. The analysis uncovered strong relationships between content descriptors and ESRB ratings, indicating a market that strategically customizes game material to different demographic groupings. Moreover, the inclusion of interactive features such as 'Users Interact' and 'In-Game Purchases' suggests a transition towards gaming experiences that are more immersive and financially interactive. The highlight of this project was the creation of a web-based tool that can accurately forecast game classifications, utilizing advanced models such as XGBoost. The application offers developers and rating organizations a vital tool to achieve accuracy in game classification. The study's conclusions provide a detailed comprehension of console market dynamics, clarifying the present patterns and possible future developments in the gaming industry.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This research focuses on studying the effect of using social media platforms on customer behavior and business objectives in Jordan. The research chose three of the most famous platforms of social media and those platforms are Facebook, Instagram, and Twitter. By using a quantitative model this research collected around 350 research questionnaires using digital surveys designed by using Google drive and distributed online on previous social media platforms. The research analysis process is executed by using AMOS software, and this comprised structural equations (SEM) modeling and regression analyses. The research study output found strong effects and relationships between social media platforms engagement and a variety of consumer expenditure variables, including brand loyalty, product suggestions, and purchase decisions. Important components of each platform, including user interaction, influencer endorsements, and content relevancy, were also identified by the study as having a direct effect on consumer behavior. The research also showed how businesses may achieve their marketing objectives, boost customer engagement, and enhance their reputation by utilizing social media strategies. The significance of social media website platforms in shaping consumer behavior and propelling business success is highlighted by these studies. To reach their goals and have the most influence on customer decisions, businesses should think about using platform-specific features and investing in targeted social media advertising.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Online grocery shopping has emerged as a prominent choice, significantly accelerated by the COVID-19 pandemic. This study delves into the factors impacting customer satisfaction in the realm of online grocery shopping, focusing on the mediating influence of perceived risk. The research, conducted with a sample size of 462, employed a convenience sampling technique for data collection. The data analysis was performed using Excel, SPSS, and Structural Equation Modeling (SEM) through AMOS. The findings reveal that perceived product quality plays a pivotal role in positively and significantly influencing customer satisfaction within the online grocery shopping sphere. Conversely, perceived convenience, while positively correlated, exhibits insignificance in impacting customer satisfaction. Furthermore, this study highlights the existence of full mediation between perceived convenience and customer satisfaction, mediated by a variable, as evidenced by the non-zero values in the range of .040 to .105. This research underscores the importance for businesses engaged in online grocery retail to prioritize convenience as an essential element to enhance customer satisfaction.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The study examines how Instagram interactions impact customer response in the restaurant context using the Stimulus-Organism-Response (SOR) framework. It explores how interactions on Instagram influence customers' intention to visit a restaurant, online engagement (OEG), and customer involvement (CI). The study highlights the significance of Instagram as a platform for effective interaction and relationship-building with customers, emphasizing its role in the hospitality industry. The study focuses on restaurant pages on Instagram, utilizing structural equation modeling to analyze data from a sample of 242 Instagram users in Turkey who are restaurant customers. The findings reveal that social media (SM) interactions are positively and significantly related to OEG, CI, and visit intention (VI). Furthermore, the results suggest that OEG and CI mediate the relationship between social media interactions (SMI) and VI, supporting the hypotheses concerning the indirect relationships between these variables. This research contributes to understanding SM dynamics and provides insights for restaurant marketers to enhance customer engagement and drive business growth.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This research aims to analyze the sustainability challenges in small and medium-scale enterprises in Indonesia, focusing on marketing orientation, social media marketing, and three domains of business performance, namely economic, social and environmental aspects. Data from 238 respondents in Pekalongan, Central Java Province, Indonesia, were analyzed using the SEM-PLS method. These findings support six hypotheses revealing the impact of marketing orientation on various aspects of business performance (economic/social/environmental) and the influence of social media marketing on economic, environmental, and social dimensions. The results have significant implications for SMEs in Indonesia. The findings highlight the need for improvement in sustainability practices, such as increasing alignment between marketing orientation and social media marketing strategies.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The aim of this study is to identify the impact of live stream marketing on consumer trust. Data was collected using a questionnaire developed based on prior works and administered electronically to consumers who use live stream marketing before making their purchasing decisions in Saudi Arabia. A total of 350 responses were used for data analysis purposes, which was carried out via SmartPLS 4.0 software. The findings of the study demonstrate a significant and positive impact of live stream marketing as conceptualized in terms of five dimensions (information, attractiveness, entertainment, expert, and social interaction) on consumer trust. In accordance with the research's findings, researchers advise live stream marketers to learn everything they can about the things they are selling because doing so will enable customers to make well-informed choices.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The COVID-19 pandemic has led to different health outcomes, including long COVID (LCo) and mental health (MH) disorders, impacting millions globally. To enable early healthcare diagnosis, including the prediction of MH conditions and LCo, various research studies have utilized machine learning (ML) techniques. However, there is still a gap in understanding the mental health of recovered COVID-19 patients with long COVID using ML techniques. This study aims to bridge this gap by developing and evaluating ML models, including support vector machine, multilayer perceptron (MLP), k-nearest neighbor, gradient boosting, voting classifier, and extreme gradient boosting, tailored for mental health and long COVID datasets from recovered COVID-19 patients. Additionally, feature selection methods, e.g., Recursive Feature Elimination (RFE) and Extra Trees (ET), and optimized models with hyper-parameter tuning will be employed. Our experiments utilize the dataset of recovered COVID-19 patients. Among these ML models, the MLP with ET-based features achieved the highest accuracy and AUC scores in this dataset, with 1.00 and 0.97 ± 0.02, respectively. The research reveals the high prevalence and risk factors of mental health disorders and long COVID from the dataset. These findings will contribute to personalized healthcare strategies for individuals navigating the complexities of post-COVID-19 recovery, integrating machine learning insights into mental health and long COVID support.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Globalization entails manufacturing companies improving their competitiveness to be superior to competitors. This study investigates the role of ERP implementation in improving business performance through supply chain integration, external supply chain integration, and flexibility. The research surveyed manufacturing companies that were implementing ERP technology adequately. Data was collected from 99 manufacturing companies in East Java that have implemented ERP. The study used judgmental sampling with criteria for employees who have worked for two years and permanent employees and have a role as a critical user or end user of one of the ERP modules in the company department. Data analysis used SmartPLS software version 4.0. The results showed that ERP implementation enhances internal supply chain integration by 0.708, external supply chain integration by 0.491, and supply chain flexibility by 0.244. By responding quickly to interdepartmental needs and integrating systems between functions, internal supply chain integration affects external supply chain integration by 0.373, supply chain flexibility by 0.249, and business performance by 0.196. External supply chain integration affects supply chain flexibility by 0.445 and performance by 0.360. Moreover, supply chain flexibility, described by the flexibility of employee working hours as needed, on-time product delivery, and production processes, impacted business performance by 0.378. The study results provide practical contributions for corporate information technology managers to invest in upgrading ERP software and hardware to maintain integration with a single database in making quick and appropriate decisions. A theoretical contribution to increase competitiveness with supply chain strategy and technology integration.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Human resources that are of high quality create a competitive advantage for companies, thus Human Resource Management (HRM) and High-Performance Work Systems (HPWS) that are good become key success factors that need to be considered by every company. This study aims to investigate the influence of Human Resource Management (HRM) and High-Performance Work Systems (HPWS) on Information Technology (IT) Performance and Competitive Advantage of a company. The method used in this study is a quantitative approach with a questionnaire as the data collection method. The research sample consisted of 191 supervisors, managers, and executives of manufacturing companies located in Medan, Indonesia. Data analysis was conducted using SmartPLS 4.0 software. The results showed that Human Resource Management significantly affects IT Performance but does not directly affect Competitive Advantage. Meanwhile, HPWS Capability does not affect IT Performance but significantly affects Competitive Advantage. IT Performance significantly affects Competitive Advantage. IT Performance also mediates the relationship between Human Resource Management and Competitive Advantage. However, it is not significant in mediating the relationship between HPWS Capability and Competitive Advantage. These findings underscore that Human Resource Management (HRM) and High-Performance Work Systems (HPWS) play pivotal roles in shaping Information Technology (IT) performance and competitive advantage within companies, thus impacting the overall success and sustainability of companies.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This research investigates how social media content marketing impacts customer engagement and it gives more weight to consumer cognition as an intermediary means. According to the study, digital communication has transformed significantly in our modern era, from simple communicative and content-sharing platforms to social media networks evolved into major marketing platforms. Organizations now fundamentally bring about transformations in their interaction with consumers depending on how they choose to use these public forums. As well, this paper begins to provide a comprehensive review of the social media content marketing literature, with topics such as augmented reality, credibility of content, user-generated content, and customer perceptions. The paper has a survey sample of 350 managers from relevant organizations, selected to provide a broad representative range across fields and industries. This study, under the Technology Acceptance Model, aims to understand better, how consumers accept and employ social media content marketing. Research questions to be addressed in this forthcoming paper include an investigation into how consumer belief serves to mediate the relation between social media content marketing and customer engagement Additionally, it aims to investigate the extent to which consumer cognition intervenes in this link, and whether consumers' beliefs moderate results of an interaction with social media platform contents source (such as reading a blog or watching a video). With this theoretical framework and the related literature, the project aims to provide significant insights and make a more successful marketing practice.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Regulators and recent academics are now paying attention to digital marketing because it has become a complete marketing resource that might propel a firm toward success. As a result, the current study explores the impact of several digital advertising channels, including mobile, e-mail, and digital retargeting, on customer purchasing behavior in the Information Technology (IT) business in the UAE. The current research also examines the moderating effects of marketing tactics at the intersection of mobile advertising, digital retargeting, e-mail marketing, and customer purchasing choices in the IT sector of the UAE. To collect data for this study quantitatively, questionnaires were employed to solicit information from respondents, which was then analyzed using smart-PLS. The findings showed that digital retargeting, mobile, and e-mail marketing positively affect customer purchasing behavior in the UAE's IT sector. The results also demonstrated that marketing tactics drastically reduced the associations between mobile, e-mail, and consumer purchasing decisions in the UAE's IT sector. This study gave policymakers recommendations on better focusing on digital advertising, which could boost the organization's success.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: In the ever-evolving landscape of supply chain management, the quest for efficiency has become paramount. This abstract explores a groundbreaking solution that combines the power of permissioned blockchain technology with innovative data reduction strategies to redefine how supply chains operate. Traditional supply chain systems often grapple with data overload, causing delays, inaccuracies, and operational inefficiencies. However, this abstract presents a promising approach that unleashes efficiency by harnessing the capabilities of a permissioned blockchain. Through data reduction techniques tailored to the needs of supply chain management, this approach streamlines the flow of information while maintaining security and trust among participants. This paper seeks into the technical foundations of permissioned blockchains, highlighting their suitability for supply applications where confidentiality and controlled access are imperative. Furthermore, it examines various data reduction methodologies, emphasizing their role in minimizing redundant data, optimizing communication, and enabling real-time decision-making. The impact of this innovative approach on supply chain stakeholders is profound. It reduces data related bottlenecks, enhances transparencies, and fosters collaboration among participants. Additionally, it provides a scalable framework adaptable to diverse supply chain ecosystems. As supply chain efficiency becomes increasingly important in our interconnected world, this permissioned blockchain-driven data reduction strategy offers a compelling vision for the future. It promises to unlock a new era of streamlined operations, cost savings, and improved customer satisfaction, ultimately shaping the next generation of supply chain management.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The main objective of this research was to find out how well cloud computing works for teaching kids in the early grades to think critically. Participants in the study were a group of early childhood students from schools in the Mafraq Governorate. The duration of the trial was set at one month. Sixty students participated in the study; thirty were randomly assigned to the experimental group and thirty to the control group. Following the intervention, the experimental group performed better than the control group on tests measuring reasoning, interpretation, analysis, and assessment skills. Both in the follow-up assessment and in the time immediately after the intervention, the experimental group and the control group did not vary from one another in terms of critical thinking skill scores.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study provides an analytical view of the correlation between several factors that influence the credibility of information available through various sources on the Internet. The most critical factors include information quality, source credibility, argument strength, message credibility, and average credibility. Additionally, the study explores the impact of gender and years of experience as demographic variables on the nature and size of these relationships. The study relied on a critical review of previous related literature. In addition, it adopted an analytical approach using a sample of 300 Internet users through a questionnaire designed based on the study hypotheses. Most of these relationships were found to be at an average level, except for the relationship between source credibility and information credibility. No statistical indicators were observed. Consequently, the researchers acknowledge the need for caution when generalizing these results to society. The study also found that the gender of the recipient and the number of years of experience did not necessarily play a mediating role in the relationship between the tested factors and the credibility of information received via the Internet.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The current study aims to determine the role of artificial intelligence (AI) in developing the accounting system (AS) in Jordanian Islamic banks. Currently, Islamic banks in Jordan are included in the research population. Using a quantitative research approach, 128 workers of Islamic banks in Jordan were chosen as a sample for this study. The study used a survey questionnaire instrument that was created based on past relevant literature and studies to collect the required data. The results indicated that there is an influence of AI (big data, intelligent agents, expert systems and automation processes) on the development of the AS in Jordanian Islamic banks. Accordingly, the study recommends that to improve AS tasks and reduce associated costs, accountants and accounting companies should always increase their understanding of artificial intelligence.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Breakthroughs and advances in translation technology by virtue of AI-powered MT tools and techniques contributed significantly to providing near-perfect translation. This study aims to evaluate the accuracy of three translation technologies (Google Translate, Gemini, and ChatGPT) in translating multidisciplinary Arabic research titles in the Humanities and Social Sciences into English. A corpus of 163 titles of Arabic research articles from various disciplines, including media studies, literature, linguistics, education, and political science, was extracted from a Scopus-indexed journal, namely Dirasat: Human and Social Sciences Series. The research methodology in the present study lends itself largely to Koponen’s (2010) translation error strategy framework. Based on the data analysis, the findings showed that the renditions provided by these programs were categorically marked with either sense or syntax errors, which often rendered the translations inaccurate. Many polysemous terms with multiple related senses were mistranslated. The results showed that the Gemini translations contained the least errors. In contrast, the human translations contained the least mistranslation and diction errors. Google Translate and ChatGPT, on the other hand, contained the highest number of equivalence-based errors. Unexpectedly, the human translations contained the highest number of syntactic errors, reflecting a lack of target language proficiency. The study's conclusions and findings would be beneficial to translators, students, and scholars who may consider translating their Arabic study research titles and abstracts through the most commonly used AI tools.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This research aims to analyze variable service quality on e-government user satisfaction and analyze information quality variables on e-government user satisfaction at the immigration office. The research method used in this research is associative quantitative research which aims to determine the relationship between two or more variables. In this way, we can build a theory that functions to predict and control a phenomenon. The population in this study were all immigration office employees. In this research, an analysis model is used, namely Partial Least Square-Structural Equation Modeling (PLS-SEM). In this study, the number of respondents was 876 immigration office employees who used e-government. The sampling technique used in this research is non probability sampling. In this research, the data collection method used was the questionnaire method. The instrument used to measure this research variable is a 7-point Likert scale. Data processing in this research uses SmartPLS software. The stages of data analysis in this research are the outer model test which includes convergent validity, discriminant validity and composite reliability as well as inner model analysis, namely hypothesis testing. The results of this research are that variable service quality has a positive and significant relationship to e-government user satisfaction at the immigration office and the information quality variable has a positive and significant relationship to e-government user satisfaction at the immigration office.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Social Networking Sites (SNS) play an important role in human psychological well-being. This research explores the effects of perceived overload on the passive usage intention of SNS among Malaysian users through SNS fatigue and anxiety by employing a Cognition-Affect-Conation (C-A-C) model. Cross-sectional survey research was carried out and the research acquired responses from 383 SNS users. Data was analyzed through PLS-SEM. The outcomes noted that perceived cognitive overload, perceived information overload, SNS fatigue, and anxiety are positive antecedents of SNS passive usage intention. The research brings valuable insights into the formation of passive usage intention of SNS and provides implications for service providers and users.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study investigates the relationship between interaction, entertainment, trendiness, brand engagement, and purchase intention in the context of TikTok as a social media platform. Using a quantitative research approach, online questionnaires were distributed to 197 respondents who met specific criteria, including active usage of TikTok and being under 45 years old. The data collection period spanned from March 2023 to May 2023. Data analysis was conducted using variance-based structural equation modeling (PLS-SEM 4.0). The independent variables in the study are interaction (X1), entertainment (X2), and trendiness (X3), with brand engagement (Z) serving as the mediator variable and purchase intention (Y) as the dependent variable. The results revealed that interaction, entertainment, and trendiness significantly positively affect purchase intention, with brand engagement playing a moderating role in this relationship. This study sheds light on the influence of TikTok content attributes on consumers' purchase intention and underscores the importance of brand engagement as a key factor in shaping their purchasing decisions.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: In this digital era, all human activities have moved towards digital. The digital era has provided significant changes in all aspects of life, one of which is the educational aspect. Digital technology has opened up new education opportunities but also presents challenges that must be faced. Almost all sectors, including education in the industry 5.0 era, have digitized, namely by utilizing sophisticated information technology. Era Society 5.0, is an era that will make it easier for human life to interact and transition to the digital era. Thus, the use of digital technology for every aspect of life, especially the education sector, is very necessary since it will reflect the level of competitiveness of a country. This research aims to analyze the relationship between e-learning and performance, digital leadership and performance, and the relationship between digital innovation and performance. This type of research uses quantitative research methods. The population in this research is all high school teachers who have used e-learning platforms and have carried out digital innovation. The sampling technique used in this research was a simple random sampling technique and the total sample of respondents from this research was 489 teachers. The type of data used in this research is primary data and the data search tool used is an online questionnaire using a Likert scale. The data analysis is to use structural equation modelling. The results show that e-learning had a positive and significant relationship with performance, digital leadership had a positive and significant relationship with performance and digital innovation had a positive and significant relationship with performance.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: A large-scale cloud data center must have a low failure incidence rate and great service dependability and availability. However, due to several issues, such as hardware and software malfunctions that regularly cause task and job failure, large-scale cloud data centers still have high failure rates. These mistakes can have a substantial impact on cloud service dependability and need a large resource allocation to recover from failures. Therefore, it is important to have an efficient management of data recovery to protect organizations data from loss. This paper aims to study some factors that may improve the management of data recovery by using quantitative research design as a methodology. The results of hypothesis testing give strong evidence supporting the positive and significant correlations between the proposed hypotheses and the efficiency of data management recovery. This study finds that the presence of a data center in an organization demands the development of a solid plan for the most effective usage of a software program to handle data recovery.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Using the frameworks of the Theory of Use and Gratification (UGT) and the Unified Theory of Acceptance and Use of Technology (UTAUT2), this study explores the factors that influence individual behavior and behavioral goals in the adoption of digital banking. Partial Least Square-Structural Equation Modeling (PLS-SEM) is used in the analysis of research data using the program SmartPLS 3.2.9 professional. There are 432 people in the research sample that filled out questionnaires. The results show that behavioral intentions are strongly influenced by the integration of UGT-UTAUT2 by 60.3%. Performance and effort expectations are influenced by cognitive needs, effort expectations are influenced by affective needs, and social influence is impacted by social needs. Behavioral intentions for the use of digital banking are shaped by a combination of factors such as price value, hedonic motivation, habits, facilitating conditions, and effort expectations. The relationship between behavioral intentions, affective and cognitive needs is mediated by effort expectations. In the context of using digital banking, habits and behavioral intentions are important factors that influence behavior; in contrast, cognitive needs, affective needs, performance expectations, and social influence have no direct effect on behavioral intentions.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Information and Communication Technologies (ICT) affect all aspects of our daily lives. Using them is considered a symbol of modernization and social advancement. The global expansion and interconnection of ICT offers a significant opportunity to promote the advancement of humanity, bridge the digital gap and promote the growth of societies built on knowledge. In this study, we analyzed and identified the most influential factors in the adoption of ICT in education from the data set called “Final Survey-Digital Inclusion Teachers” of the Plurinational State of Bolivia, which consists of 871 instances and 189 columns. We performed feature selection by carefully combining the results of three feature selection methods: filter (chi-square, ANO-VA and mutual information), wrapper (RFE) and intrinsic (Classification And Regression Trees, Random Forest, Gradient Boosting and XGBoost). The results demonstrated that a teacher's motivation for curricular planning that includes ICT, teaching experience and the institutional environment are key factors in the adoption of these technologies in education. Furthermore, we identified that the Random Forest algorithm is the most appropriate for analyzing and predicting the adoption of ICT in education, we affirmed this after this algorithm obtained the highest values in four of the six metrics evaluated: a sensitivity of 77.7%, an F1 Score of 77.9%, a Cohen's Kappa coefficient of 60.8% and a Jaccard Score of 64.3%. These results suggest that Random Forest is the most effective algorithm to analyze the factors related to the adoption of ICT in educational environments.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: In the digital era the research study discusses the role of government policy, negative emotions and digital trust in cyber violence, therefore this research adds to the literature and provides references regarding the important role of government policy on cyber violence is very limited. This research aims to investigate the relationship between digital distrust and cyber violence, and the relationship between government policy and cyber violence. The research method used in this research is associative research. Associative research is research that aims to determine the relationship between the hubs of two or more variables. In this way, we can build a theory that functions to predict and control a phenomenon. The population in this study were all students who had studied using e-learning or digital platforms. In this study, the number of respondents was 543 high school students throughout Indonesia. The sampling technique used in this research is nonprobability sampling. In this research, the data collection method used was the questionnaire method. The instrument used to measure this research variable is a 5-point Likert scale. Data processing in this research uses SmartPLS software. The stages of data analysis in this research are the outer model test which includes convergent validity, discriminant validity and composite reliability as well as inner model analysis, namely hypothesis testing. The results of this research are that digital distrust has a positive and significant relationship to cyber violence, negative emotions have a positive and significant relationship with cyber violence, and government policy has a positive and significant relationship with cyber violence. This research adds to the literature and provides references regarding the important role of government policy, digital distrust, and negative emotions in cyber violence. Indonesia, the government needs to implement and evaluate new regulations related to cybercrimes. The government must establish new regulations to combat cybercrime.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The concept of the “Metaverse” is a three-dimensional virtual world that relies on simulations of reality to represent real-life experiences, and it can be classified as the next generation in using the Internet. In this research, we will examine the factors that may influence user acceptance of metaverse and the relationships between these variables highlight how different factors can be examined. The goal of understanding these factors is to determine how Metaverse developers can improve this technology to meet user expectations and enable users to better interact with this technology. To achieve this goal, a sample of 312 students’ participants from different age groups was selected to respond to an online Likert scale questionnaire ranging from) strongly disagree equal) to (strongly agree equal 5). The study found that perceived enjoyment significantly positively influences technology metaverse application. Moreover, perceived curiosity and perceived self-efficacy positively influence technology application metaverse transitions. In addition, perceived ease of use (PEOU) and perceived usefulness (PU) positively influence the attitude toward using the Metaverse technology/application, which means that all the previous factors have an overall positive effect on the attitude toward using the Metaverse technology application.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The increasing popularity of intelligence systems in accounting and auditing domains has led to the interest towards drivers of blockchain technology adoption. Consequently, this empirical study inspected the antecedent constructs with direct and indirect impact on blockchain technology adoption in the accounting domain. Data were gathered from 346 accountants employed in Information technology (IT) companies, through an online survey. Structural equation modeling with Smart PLS 4 was employed for research model testing. Out of thirteen proposed direct hypotheses, twelve were accepted. Mainly, the obtained empirical results confirmed effort expectancy impacting blockchain technology adoption the most. Furthermore, the obtained results also confirmed the mediation role of effort expectancy and performance expectancy.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The research investigates the link between technology, organization, and environment, and the uptake of artificial intelligence among SMEs in Jordan. The objective is to get a deeper understanding of the factors that promote or hinder enterprises' use of artificial intelligence during the recruitment of leaders. A total of 295 participants, who were owners or managers in several SME sectors, manufacturing, including services, construction, and agriculture, were selected via judgmental sampling. Data collection was conducted utilizing a survey instrument, and the collected data was processed employing Smart PLS. The findings demonstrated a substantial correlation between attitude toward artificial intelligence uptake and factors such as relative advantage, complexity, top management commitment, and organizational preparedness. Nevertheless, factors like competitive pressure, external assistance, a favorable regulatory environment, compatibility, and staff flexibility do not significantly influence the attitude toward the uptake of artificial intelligence. In summary, these findings provide valuable insights for decision-making and resource distribution. They underscore the significance of factors such as relative advantage, complexity, top management commitment, and organizational readiness in achieving goals in the field of artificial intelligence. Additionally, they identify areas where efforts may not result in significant effects. The practical ramifications and future study paths are emphasized according to current technological needs.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The study aimed to evaluate how cloud technology implementation would affect Jordanian industrial businesses' financial statements' integrity across a range of variables (financial condition, income, cash flow, owners' equity). The investigation involved employees from financial and internal audit departments, including various job titles. A random sample of 150 questionnaires was distributed among the study population, with a 96% response rate (145 retrieved). Respondents were scored using a Likert five-point scale on the 44-paragraph questionnaire. To accomplish its goals, the study used a descriptive-analytical methodology and statistical techniques such as path analysis (using AMOS) and simple linear regression analysis (using SPSS). According to the study, the implementation of cloud accounting has a statistically significant effect on the quality of financial statements by Dimension (statement of financial position, income statement, statement of cash flows, and list of equity), according to the study. Applying cloud accounting has a statistically significant effect on the internal control system, and the internal control system has a statistically significant impact on the accuracy of financial statements. Furthermore, cloud accounting has a statistically significant impact on the quality of financial statements in Jordanian industrial companies through the internal control system as an intermediate variable. The study made several recommendations in light of the earlier findings, the most significant of which are: determining the internal control system's current state both before and after cloud accounting was implemented; creating and executing a robust internal control system compliant with international accounting standards; and assessing the suitability of cloud accounting solutions through thorough evaluations. The report also emphasized how crucial it is to set up ongoing audit and internal control systems to evaluate how well the internal control and cloud accounting systems are working together.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The IoT ecosystem faces increasingly complex security challenges due to the rapid growth of global IoT devices. Security risks related to device identification and credential compromise are on the rise, especially with the proliferation of IoT devices in various aspects of life. This research highlights the need to address these vulnerabilities through the development of robust security protocols, aiming to create a more secure IoT ecosystem and enhance user trust in this technology. The objective of the research is the development of an innovative IoT security protocol; High-Accuracy Device Identification and Resilience Against Credential Compromise (HADIRACC). This paper contributes significantly to enhancing the security and reliability of the IoT ecosystem. The research methods employed encompass the development of security protocols, the development of a proximity-based solution, and the classification of IoT devices using data processing techniques and machine learning-based classification. This study involves the collection and pre-processing of datasets, training different classifiers using 70% of the dataset, and testing the classifiers using the remaining 30%. The proposed protocol can effectively enhance the security of IoT devices by addressing various scenario-based attacks. Furthermore, the results of the analysis of the five classifiers used in this study indicate that Random Forest has the highest F1 score accuracy, reaching 88.8%. This suggests that Random Forest, as a classifier, can make the most accurate predictions compared to other classifiers.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: In recent years, E-Commerce has experienced a very significant increase. E-commerce provides a broad overview of technology, processes and practices that can be carried out without using paper as a means of transactions. E-commerce can be a solution to the paper waste problem which is an environmental issue that can lead to social problems. Thus, e-commerce has a vital role in achieving business sustainability performance. E-commerce has had a big influence on the social and economic growth of today's society. Business management's ability to manage financial information is an important indicator in influencing Micro, Small and Medium Enterprises’ (MSME's) business performance. Good managements’ financial literacy equips MSMEs with knowledge and skill empowering MSMEs to make informed financial decisions, manage resources effectively and promote sustainable development. This research aims to analyze the relationship between E-Commerce and the sustainability performance of MSMEs and analyze the relationship between financial literacy and its positive and significant relationship with the sustainability performance of MSMEs. The research method uses a descriptive method with a quantitative approach. The population in this research are MSMEs managers in Indonesia who have comprehensive knowledge regarding the operations and performance of MSMEs. In this study, researchers used a simple random sampling technique with a sample size of 478 MSME managers. Data analysis in this research uses the Partial Least Square (PLS) technique which is an alternative method based on the variance of the variables used. The stages of data analysis are validity testing, reliability testing and hypothesis testing. The independent variables in this research are e-commerce and financial literacy, while the dependent variable is MSME sustainability performance. The results of this research show that e-commerce has a positive and significant relationship with MSME sustainability performance and financial literacy has a positive and significant relationship to MSME sustainability performance. In addition, e-commerce has a significant influence on the sustainability performance of MSMEs because the presence of e-commerce is one of the marketing alternatives used to reach more vendors and customers which can change the supply chain leads to social problem solution such as food distribution. Further, e-commerce may minimize traveling long distances for shopping resulting to the carbon footprint reduction. MSMEs have the same opportunity to use e-commerce as an alternative to maximize performance. However, not all MSMEs have the capability to use and utilize e-commerce optimally. After all, knowing good financial management will make it easier to make sustainable decisions since the higher the level of financial literacy, the MSME players can optimize their sustainability performance.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study explores the factors influencing personal brand identity and their impact on successful personal branding. It examines the positive influence of social media usage, self-expression, professionalism, and self-disclosure on personal brand identity, while also considering the inconsistent findings regarding the role of self-efficacy. The study finds that social media usage, self-expression, professionalism, and self-disclosure play crucial roles in developing a strong personal brand identity, which is essential for achieving successful personal branding. However, the findings on self-efficacy's influence on personal brand identity are inconsistent with previous research. This study contributes to the understanding of personal brand identity and provides valuable insights for individuals and organizations seeking to develop and maintain strong personal brands.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Previously, studies reported inconclusive findings while analyzing the influence of factors affecting online purchase intention. Also, most studies were conducted in the context of developed countries, limiting us to a specific context. Hence, for comprehensive understanding, this study aims at examining the factors affecting the online purchase intention in the e-commerce industry of Jordan. The survey was conducted to collect data from university students in Jordan. Structural equation modeling was employed to analyze the data. Findings show that attitude, subjective norms, perceived behavioral control are positively associated with online purchase intention. However, perceived risks are negatively associated with online purchase intention. Although all factors are significantly related to online purchase intention, the attitude has a greater influence. This study adds value to the theory of planned behavior and consumer behavior by examining attitude, subjective norm, perceived behavioral control, and perceived risks as important predictors of online purchase intention. Besides, this study suggests that online retailers must keep their commitments, promises, and customers’ interests in mind while developing e-commerce strategies.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The current research aims to expose the value of Instagram's features and content and investigate how cognitive functions mediate the relationship between Instagram's content-related elements (informative material, user-generated content, augmented reality content, entertainment, trustworthiness, sociability) and consumer affection and behavior. This study employed a random sample strategy and gathered 292 responses. The tool AMOS 22 (Analysis of a Moment Structure) examined the data efficiently. Results show that all Instagram content marketing elements affect cognitive engagement, where augmented reality content has rated the highest effect, then user-generated content, trustworthiness, informative material, entertainment, and sociability, consequently. Then cognitive engagement affects affection and behavior.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: During the innovation era and in the highly competitive environment, big data capabilities (BDCs) play a pivotal role in shaping competitive dynamics; the influence of these technologies on small and medium-sized enterprises (SMEs) operating in the retail sector is critically significant. This study is specifically focused on the retail industry, with a particular emphasis on how BDCs impact the project success, business continuity, and sustainability of SMEs within this industry. Our theoretical model was tested using a survey of 300 operations managers working in SMEs in the retail sector in the Middle East. PLS-SEM was conducted to analyze our collected data. Our results reveal that BDCs enhance project success and promote sustainability practices. The findings also reveal that BDCs have no impact on business continuity. By shedding light on the nuanced impact of BDCs on SMEs in the retail sector, this study contributes valuable insights to the existing literature, offering a deeper understanding of how these technological capabilities can drive success and sustainability in a highly competitive market environment.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This research aims to investigate the role of internet marketing, word-of-mouth and brand awareness on purchasing decisions in online stores. The respondent sampling technique used in this research is a non-probability sampling technique, which uses a purposive sampling technique. The responses to this research were from 468 online store consumers. Measurements of “Internet Marketing”, “Word of Mouth Communication”, “Brand Awareness” and “Purchasing Decisions” were carried out using a seven-point Likert scale, ranging from strongly agree (1) to strongly disagree (7). In this research, the data was analyzed using the Partial Least Square (PLS) method with SmartPLS version 3.0 software. The stages of research data analysis are outer model testing, namely unified validity and reliability, inner model testing and hypothesis testing. Based on the results of data analysis, it is concluded that internet marketing, word-of-mouth and brand awareness had positive and significant effects on purchasing decisions. Better internet marketing will improve consumer purchasing decisions, brand awareness plays an important role in consumer purchasing decisions, and consumers will carry out word-of-mouth activities and tell other people about consumer experiences after consuming products, electronic word of mouth can help consumers in making buying decisions. Based on the results of data analysis, the study provides managerial implications as follows: online stores should evaluate the Internet marketing strategy used by the company by looking for information about what is currently trending among the public and forming a special team to carry out Internet marketing strategies to make them more attractive and creative and provide more complete information regarding products are marketed so that they attract consumers to make purchasing decisions.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)