Abstract: Smart contracts offer automation for various decentralized applications but suffer from vulnerabilities that cause financial losses. Detecting vulnerabilities is critical to safeguarding decentralized applications before deployment. Automatic detection is more efficient than manual auditing of large codebases. Machine learning (ML) has emerged as a suitable technique for vulnerability detection. However, a systematic literature review (SLR) of ML models is lacking, making it difficult to identify research gaps. No published systematic review exists for ML approaches to smart contract vulnerability detection. This research focuses on ML-driven detection mechanisms from various databases. 46 studies were selected and reviewed based on keywords. The contributions address three research questions: vulnerability identification, machine learning model approaches, and data sources. In addition to highlighting gaps that require further investigation, the drawbacks of machine learning are discussed. This study lays the groundwork for improving ML solutions by mapping technical challenges and future directions.

	© 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 aimed to investigate the effect of cloud computing (CC) and company size on accounting information quality. Data were collected using an online questionnaire which followed the Technology Acceptance Model (TAM). The research sample consisted of 178 respondents from accountants and audit offices in the Emirate of Riyadh. The study adopted a Smart PLS in hypothesis testing. The study's results indicated just a positive relationship between perceived benefit and quality of accounting Information. In addition, there was a clear influence of company size on the relationship between CC and accounting information quality.

	© 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 aims to examine the complex dynamics of short video marketing, social sharing, and consumer engagement specifically within the tourism sector in Jordan. The study used AMOS software for analysis, gathering data from a total of 468 participants, including both internal and external tourists. The results emphasize the significant impact of short video marketing in stimulating social sharing behaviors among travelers, prompting them to share their experiences on various social platforms, thus expanding the reach of tourism-related content. Moreover, the research reveals the mutual relationship between social sharing and consumer engagement, indicating that sharing behaviors play a crucial role in increasing levels of engagement among tourists. The novelty of this research resides in its concentrated investigation of these associations within the unique context of the Jordanian tourism sector. The study's significance lies in its ability to expand comprehension of digital marketing dynamics in the tourism industry, providing practical insights for marketers seeking to improve brand visibility and engagement in digital spaces. This study enhances the current knowledge base by employing a quantitative approach, establishes a basis for future research endeavors, and offers valuable insights for marketers aiming to maximize the effectiveness of digital 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: In the dynamic realm of facility management in the UAE, this study investigates the uptake of digital facility management systems among managers operating locally. The study aims to uncover the influential factors affecting technology acceptance within this sector. Its primary objective is to identify and understand the determinants that impact the adoption of these systems, utilizing a structured framework to analyze influential factors and their implications. The initial phase involves a systematic review to reveal trends in integrating digital technologies, focusing specifically on digital twin technology. Subsequently, quantitative surveys are conducted with 407 facility managers, guided by the UTAUT framework, employing statistical analyses to pinpoint key factors. Notably, Effort Expectancy and Performance Expectancy emerge as significant influencers, particularly influenced by the managerial level. This study provides detailed insights into the nuanced factors that drive acceptance, emphasizing the crucial role of constructs like Performance Expectancy and Effort Expectancy moderated by managerial level, shaping Behavioral Intention and Use Behavior. These findings offer practical implications for devising strategies to encourage the adoption of Digital Facility Management Systems in the UAE, laying the groundwork for future research and industry advancements.

	© 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: Fintech, characterized by the intersection of finance and technology, has globally transformed the financial landscape, reshaping traditional banking models as its innovations continue to unfold. The current study seeks to provide a comprehensive examination of the impact of fintech on the financial performance of Saudi banks. Nine Saudi national banks were investigated. The data were gathered from the annual reports from 2017 to 2022. The study followed multiple regression to test the relationship between factors. The study found that there was no notable impact of FinTech tools, such as Banking messages, Internet banking, Mobile applications, and Digital transfers, on return on assets (ROA) and return on equities (ROE) when looking at each tool individually. Nevertheless, when considering all these tools collectively, there is a considerable influence of 93.2% on ROA, and 84.2%, on ROE.

	© 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 the consumer cyborg's engagement with social media, online shopping, and tourism activities. The objective is to explore the effect of narcissism, social media addiction, and self-esteem on online shopping and tourism addiction. The survey involved 221 participants chosen through the convenient sampling method. The data was processed using exploratory and confirmatory factor analysis and structural equation models. The findings of this study indicate that narcissism significantly influences social media addiction and self-esteem. Besides, social media addiction has a considerable effect on self-esteem. In addition, self-esteem significantly impacts both online shopping addiction and tourism addiction. These findings provide new insights into cyborg marketing and consumer addiction theory.

	© 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 practical application of business data analytics in human resource (HR) management activities is still limited and underutilized. The primary reason for this is the requirement for more analytical skills, which can be acquired through data literacy. These skills are necessary to ensure obtaining the potential benefits of human resource analytics linked to desired positive employee outcomes, such as fostering innovative behavior. To address this issue, this quantitative study has been conducted to delve into the prospective moderating role of data literacy in the interaction between human resource analytics and employees’ innovative behavior. The core objective of this study is to examine whether human resource professionals’ data literacy level significantly impacts the correlation between human resource analytics and the inclination of employees towards innovative behavior. A sample of 250 HR specialists from large companies in Jordan has been used to address this inquiry. A correlational-predictive design has been used in this study. Regression analysis using the SPSS macro-PROCESS software has been utilized to address the study hypotheses. The study reveals a positive connection between HR analytics and employees’ innovative behavior. Moreover, it uncovers a noteworthy moderating influence of data literacy on this association. These findings suggest that heightened data analysis proficiency among HR professionals amplifies the potential benefits derived from analytics, thereby enhancing employees’ innovative capabilities. As a result, the research suggests that companies upgrade their technical infrastructure for HR functions and concurrently utilize data analytics for informed HR decisions. Further, these insights do serve as necessary inputs in understanding HR analytics and their implications for prudent business strategy. In view of this dynamic nature of HR analytics, the contributions made by the study are immensely valuable; hence, further exploration is needed to fill in gaps within existing knowledge.

	© 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 aims at exploring the effect of artificial intelligence as measured by machine learning capability and expert systems capability on patient satisfaction. As informant participants, medical staff workers in healthcare institutions in KSA comprise the population of the study. Hence, a sample consisting of 300 participants was used to gather research data via a questionnaire developed based on previous works. By means of Smart PLS 3.0 software, the results indicate that both machine learning and expert systems have significant effects on patient satisfaction. The study concluded that artificial intelligence capability is a cornerstone of patient satisfaction. such a statement encompasses theoretical and empirical implications as stated at the end of 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 qualitative study examined the impact of social media characteristics on the attitude of users toward the use of e-services by the Department of Lands and Survey. The study population comprised users of Department of Lands and Survey e-service, while the study sample comprised 407 users. Data from respondents were analyzed using SEM run using Amos (23). Results showed reliability, security, website design, ease of use, awareness, and digital divide as direct significant antecedents of user attitude toward the use of e-services from the Department of Lands and Survey. Also, all antecedents showed direct significant relationships with user attitude. Results showed a direct significant relationship between user attitude and the use of e-services from the Department of Lands and Survey. Through mediation of user attitude, five indirect significant relationships between the antecedents and the use of e-services from the Department of Lands and Survey were found. The inclusion of new antecedents such as privacy and site content may enhance the understanding of how users use e-services provided by the Department of Lands and Survey.

	© 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 world of the Internet of Things (IoT), even though it is continuously morphing as a fresh paradigm at the intersection of technology and education, is still struggling with several difficulties that prevent its absorption into the e-learning platforms of higher education institutions (HEIs). The breadth of Internet of Things implementation in developing countries, particularly Jordan, Malaysia, Iran, Saudi Arabia, Iraq, and Bangladesh, remains behind, even though industrialized nations have made significant advancements in their utilization of IoT, with the United Kingdom, the United States of America, China, and Japan acting as prominent examples. In the realm of research that focuses on the progression of the IOT integration into the e-learning systems of economically challenged countries, there is a substantial disparity. In particular, the focus of this research is on Jordan to shed light on the primary variables that are either facilitating or hindering the adoption of the IoT within the e-learning sector of Jordan's HEIs. A comprehensive analysis of previous research has been undertaken as a first stage in this investigation. The goal of this analysis is to identify important factors that are involved in the process of IOT adoption. Following that, we used an inferential technique, collecting data from 306 respondents who were enrolled in Jordanian higher education institutions. During our investigation, we discovered that the rate of the IOT integration was significantly influenced by factors such as accessibility, usability, technical assistance, and individual capabilities. In addition, our findings suggest that factors such as attitude, behavior, financial preparedness, dependability, and training have a substantial impact on the adoption of the IOT. On the other hand, the study seemed to indicate that characteristics such as class capacity, awareness, system resources, and course design had a minor influence on the adoption rates inside HEIs. In conclusion, this study provides tangible suggestions to strengthen the integration of the IoT inside Jordanian HEIs. These recommendations provide significant insights that can be used by policy architects, government entities, and higher education institutions to overcome the challenges that relate to the deployment of IoT in the higher learning sector.

	© 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 employed quantitative methods to evaluate the influence of adaptive learning technology on the cognitive flexibility of students with special needs. Participants were recruited from special education schools using a purposive selection strategy. The Wisconsin Card Sorting Test (WCST) was utilized as a tool to assess cognitive flexibility. The data was analyzed using descriptive statistics, paired-samples t-test, correlation analysis, and regression analyses. The findings demonstrated a notable enhancement in WCST scores after the intervention, suggesting that adaptive learning technologies have a beneficial effect on cognitive flexibility. Regression studies revealed that various types of adaptive learning technologies had varied levels of efficacy, with Tech A showing the most significant beneficial impact. Surprisingly, demographic factors such as age, gender, and educational attainment demonstrated little and statistically insignificant associations with alterations in cognitive flexibility levels. The findings emphasize the potential of adaptive learning technologies as effective therapies for improving cognitive flexibility in kids with special needs. It underscores the significance of evaluating specific characteristics and design principles to maximize their efficacy.

	© 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 investigates the impact of product quality and social media marketing on brand loyalty through customer satisfaction in the context of Japanese restaurants in Jakarta. Utilizing primary data from 203 respondents who frequented these restaurants, collected via questionnaires employing purposive sampling, the research employs partial least squares (PLS) analysis through SmartPLS 3.3.3 software. Results indicate direct positive relationships among variables. However, no direct positive relationship was found between product quality or social media marketing and brand loyalty. Instead, both product quality and social media marketing indirectly influence brand loyalty through customer satisfaction. The study highlights direct positive associations between product quality and customer satisfaction, social media marketing and customer satisfaction, and customer satisfaction and brand loyalty. Nevertheless, no direct positive link was found between product quality or social media marketing and brand loyalty. The indirect effects reveal that product quality affects brand loyalty through customer satisfaction and social media marketing influences brand loyalty through customer satisfaction as well. These findings underscore the significance of customer satisfaction as a mediator in the relationship between product quality, social media marketing, and brand loyalty in the hospitality 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 aimed to analyze the relationship between electronic human resources (e-HRM) and sustainable competitive advantage, organizational agility and sustainable competitive advantage, and sustainable innovation and sustainable competitive advantage in the manufacturing industry in Indonesia using a quantitative approach. The population of this research was managers of manufacturing companies in Indonesia. A total of 800 online questionnaires were sent using a simple random sampling method and 540 valid questionnaires were received. The questionnaire contains statement items using a Likert scale from 1 to 7. To measure the structural model and to test research hypotheses, the research used the PLS-SEM method with WarPLS 7.0 software. The stages of data analysis in this research were reliability and validity tests, significance tests and hypothesis testing. This research concludes that e-HRM had a positive and significant relationship with sustainable competitive advantage, Organizational Agility had a positive and significant relationship with sustainable competitive advantage and sustainable innovation has a positive and significant relationship with sustainable competitive advantage. The research emphasizes that e-HRM practices encourage sustainable innovation and organizational agility to achieve competitive advantage. The study also provides a more comprehensive understanding that e-HRM practices contribute to sustainable competitive advantage by driving continuous innovation and strengthening organizational agility. The research emphasizes the importance of utilizing digital technology for human resource management (HRM) processes, organizations must implement digital transformation by adopting e-HRM practices to increase manufacturing efficiency and effectiveness thereby increasing performance and competitiveness. This research encourages companies to increase continuous innovation to increase sustainable competitiveness.

	© 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 effect of marketing via Instagram on Generation Z’s preference for gyms in Jordan, so it would be helpful for marketers of gyms to be aware of using Instagram to attract Generation Z as their potential customers. Moreover, a sample questionnaire was carried out with 138 respondents, which were mostly female respondents (74%) and male respondents (26%). Additionally, 51% of the total number of respondents were 21-24 years old. Therefore, the data was analyzed by applying various statistical techniques such as Cronbach’s alpha for testing the reliability of the data, and multiple regression using SPSS version 22 for examining the hypotheses. Likewise, the results showed that Instagram and these variables (entertainment, interaction, trendiness, and customization) have an effect on customers' brand choice, but trendiness did not have a significant effect on the consumer's brand choice, but after testing the effect of the brand image, it became clear that it has significant effect, and therefore it was concluded that brand image has an important effect on customer’s brand choice.

	© 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: Arabic handwritten script recognition presents an energetic area of study. These types of recognitions face several obstacles, such as vast open databases, boundless diversity in individuals' penmanship, and freestyle writing. Thus, Arabic handwriting requires effective techniques to achieve better recognition results. On the other hand, Multilayer Perceptron (MLP) is one of the most common Artificial Neural Networks (ANNs) which deals with various problems efficiently. Therefore, this study introduces a new technique called Block Density and Location Feature (BDLF) with MLP, namely BDLF-MLP, which aims to extract novel features from letter images and estimate the letter's pixel density and its location for each equal-sized block in the image. In other words, BDLF-MLP can deal with various styles of Arabic handwritten, such as overlapping letters. The BDLF-MLP starts with the Block Feature Extraction (BFE) of the image by dividing the image into sixteen parts. After that, it calculates the density and location of each block (i.e., BDLF) by finding the sum of all values inside blocks. Finally, it determines the position of the greatest pixel density to obtain better recognition accuracy. The dataset containing 720 images is used to evaluate the efficiency of the proposed technique. Also, 1440 letters are used for training and testing divided evenly between them. The experiment results illustrate that BDLF-MLP outperformed the other algorithms in the literature with an accuracy of 97.26 %.

	© 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 goal of this study is to find and analyze the factors that affect teachers' digital competence, consisting of teacher personal characteristics (gender, age, experience, vocational teachers, and attitudes towards technology) and school context (school status, school accreditation, school leadership support, and curriculum support). The research method uses a quantitative approach with a causal design. The study included a total of 444 teachers from vocational high schools (SMK) located in western Indonesia. The characteristics of teachers that influence digital competence are attitudes towards technology and vocational teachers, and this means that teachers who teach vocational subjects have better digital competence than teachers who teach general basic subjects and local content. Curriculum support has a significant impact on vocational school instructors' digital competency. Improved curricular support enhances teachers' digital competence through effective lesson design, execution of teaching and learning activities, and utilization of digital-based practical resources. Meanwhile, age, gender, and school status are not determinants of teacher digital competence. The findings of this investigation recommend that the government, especially the Ministry of Education and the director general of vocational education, include teacher digital competence in evaluating teacher performance and become a consideration for school principals and related offices to improve technology facilities and improve the digital literacy of vocational teachers. This study distinguishes itself from previous research by investigating the determinants that impact teachers’ digital proficiency in vocational education. It specifically considers the influence of school status and vocational school accreditation, taking into account the unique combination of school-based and work-based education with diverse teaching approaches.

	© 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 relationship between information system quality and user satisfaction, the relationship between perceived usefulness and user satisfaction and the relationship between user satisfaction and sustainable e-learning. The research method used in this research is associative research. The population in this study were all students who had undergone lectures using e-learning. In this study, the analytical model was used, namely Structural Equation Modeling (SEM) and the number of respondents was 456 high school students in Indonesia, who have undergone lectures using e-learning. The sampling technique used in this research is nonprobability sampling. The data collection method used was the questionnaire method and the instrument used to measure this research variable was a 5-point Likert scale. Data processing in this research uses SmartPLS software. The data analysis stage in this research is the outer model test including convergent validity, discriminant validity and composite reliability and inner model analysis, namely hypothesis testing. The results of the study indicate the quality of the information system has a positive effect on user satisfaction, Perceived Usefulness has a positive effect on user satisfaction and user satisfaction has a positive effect on sustainable e-learning. The implication is that every element at every level in formal educational institutions must pay serious attention to personal factors, including attention to student achievement expectations, relative excellence expected by students, student suitability with the e-learning system chosen in an institution's formal education, and the attitude of students who are willing to accept and continuously use e-learning. In this way, students will be consistent in using e-learning so that student achievement, which is the main goal of every school, can be achieved. The limitation of this research is that it does not provide prior understanding to respondents regarding the scope of the meaning of sustainable e-learning.

	© 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 business intelligence adoption (Business Intelligence (BI), Data Analysis and Reporting (DAR), Business Process Integration (BPI), and Continuous Improvement and Innovation (CII)) and marketing effectiveness in the Jordanian telecom industry. It specifically examines the mediating role of customer satisfaction in this relationship. A survey design method using the cross-sectional survey was utilized during the research process, involving quantification. The data was collected from 285 employees across the Jordanian telecom sector via electronic response forms. As the analysis's method, the partial least squares structural equation modeling (PLS-SEM) was utilized. The results, which showed BI, DAR and CII to have a positive direct effect on marketing effectiveness, whilst BPI displayed a negative direct impact, were compelling. But clear signs of positive influence on CS by the four dimensions of BI (BI, DAR, BPI, and CII) have also been observed, and this result has been proved to be a mediator between them and business effectiveness. The above study is a source of invaluable learning for the managers of telecom companies in Jordan is a tool that managers in the Jordanian telecom industry will greatly benefit from in the sense that it brings out all the importance of integrating BI, DAR, BPI, and CII practices that emphasize high quality customer service. By properly utilizing these assets and up-to-the-market, companies can improve the effectiveness of marketing and the whole organizational efficiency. The study enhances the existing theory of the interrelationships between the adoption of business intelligence, customer satisfaction, and marketing power which can be viewed from both resource-based view (RBV) theory and expectation-based theory (EDT). It affirms an idea that the RBV was rooted in that when organizational assets are valuable, firms have a competitive advantage and better performance. Also, an EDT states that customer satisfaction increases if the expectations of customers are met. Innovation - The essay is innovative and takes an original angle to explore the multifaceted interconnectivity among business intelligence adoption, customer satisfaction, and marketing effectiveness in the framework of the Jordanian telecom industry. It highlights the steps to customer satisfaction problem solutions and the caution comes with process integration efforts, hence, helping to arrive at a full comprehension of the aspirations for organizational performance in the field.

	© 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 relationship between digital transformation and school performance and the relationship between digital innovation and school performance. The research method is quantitative through surveys, research data was obtained by distributing online questionnaires to 489 high school teachers throughout Indonesia who were selected using a simple random method. Data analysis used covariance-based structural equation modelling (CB-SEM) with SmartPLS 4.0 software to analyze research data. The independent variables are digital transformation and digital innovation, and the dependent variable is school performance. The stages of data analysis are validity testing, reliability testing, model fit testing and significance testing of hypothesis testing. The results of this research are that digital transformation has a positive and significant relationship with performance. Moreover, digital innovation has a positive and significant relationship to performance. The findings of this research support and prove the results of previous research that digital transformation has a positive effect on organizational performance and innovation and confirms the direct influence of innovation on organizational performance. The contribution of this research is aimed at various literature related to the role of digital transformation and innovation on organizational performance. Meanwhile, for practical implications, digital transformation and innovation can improve organizational performance, especially in schools.

	© 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 that continues to develop, information technology has brought significant changes to various aspects of human life. One of the clearest impacts is in the field of education. In this era, learning is no longer limited to physical classrooms and textbooks, instead, electronic learning or e-learning has become a popular alternative for accessing knowledge and learning online. This research aims to analyze the relationship between e-learning variables and school performance, the relationship between digital transformation variables and school performance and the relationship between digital innovation and school performance. The study uses a quantitative method approach and data analysis using the Partial Least Square -Structural Equation Modeling (PLS-SEM) approach. Research data was obtained by distributing an online questionnaire form via social media platforms. The questionnaire was designed to contain statement items on a Likert scale from 1 to 7. The respondents for this research were 467 school principals in Indonesia who were determined using the sample determination method, namely simple random sampling. The stages of research data analysis are validity testing, reliability testing and hypothesis testing or significance testing. The independent variables in this research are e-learning, digital transformation and digital innovation, the dependent variable in this research is school performance. The results indicate that e-learning, digital transformation, and innovation had positive and significant effects on school 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 examines the relationship between the types of Artificial Intelligence (AI) technology employed and monitoring tax payments. A thorough literature review is conducted to examine different AI technologies in the context of tax administration. These include machine learning algorithms (MLA), natural language processing (NLP) technology, robotic process automation (RPA), explainable artificial intelligence (XAI), and advanced data analytics techniques (DAT). A variety of technologies, such as big data analytics, task automation, task automation, unstructured data analysis, and predictive modeling, are available to improve tax payment monitoring procedures. Recommendations for further study to expand our knowledge and use of AI in tax payment monitoring are included, along with the consequences of AI adoption for tax authorities, policymakers, and practitioners.

	© 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: Company activities can yield both favorable and adverse outcomes. Among the detrimental effects are various environmental crises stemming from companies' failure to responsibly manage and uphold ethical business practices within their operational environment. This study aims to scrutinize the impact of artificial intelligence and social media on augmenting public administration decision-making and its repercussions on corporate social responsibility within enterprises situated in Sidoarjo, East Java Province, Indonesia. The sample comprises 130 respondents representing companies actively engaged in corporate social responsibility endeavors. Employing purposive sampling technique, data collected from surveys were subjected to Structural Equation Modeling-Partial Least Squares (SEM-PLS) analysis. The research outcomes and data analysis reveal that artificial intelligence significantly and directly influences corporate decision-making as well as public administration of social responsibility. Likewise, the utilization of social media by both corporations and government exhibits a direct and positive correlation with corporate decision-making and corporate social responsibility. Public administration decision-making also demonstrates a direct and significant impact on corporate social responsibility within companies in Sidoarjo, East Java Province, Indonesia. Moreover, public administration decision-making partially mediates the effects of artificial intelligence utilization and social media utilization on public administration of social responsibility within companies in Sidoarjo, East Java Province, Indonesia.

	© 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 widespread adoption of artificial intelligence (AI) technologies, including ChatGPT, into education, has become a focal point of attention in recent years. This research explores the connections among perceived usefulness (PU), perceived ease of use (PEOU), attitude toward using ChatGPT (ATUC), and intention to use ChatGPT (ITUC) within Jordanian universities. A survey was employed to gather information from 523 university students in Jordan, and the hypotheses were examined using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings revealed that perceived usefulness and perceived ease of use positively impacted attitude toward using ChatGPT and intention to use ChatGPT. Attitude toward using ChatGPT positively impacted intention to use ChatGPT. Implications from this research are crucial to provide developers, instructors, and institutions in Jordan with useful information to help them successfully incorporate ChatGPT into the educational process.

	© 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 which has spread across all countries, including Saudi Arabia, has caused the government to create limited curfew policies in the country that affected the economy. This policy has given rise to a new trend in society, namely the habit of shopping online. The trend of purchasing online via e-commerce increases. However, people's opinions and attitudes towards this trend vary. Therefore, this research was conducted with the aim of determining the subjectivity of public opinion or sentiment on the e-commerce activities using probability and statistical approaches, i.e.: the Naïve Bayes (NB) and Support Vector Machine (SVM) classifiers. Three experimental scenarios of dataset splitting for training and testing; 90%:10%; 80%:20%; and 70%:30%. The comparison of accuracy values was carried out using an automatic labeling method. Experimental results show that the 70%:30% split scenario provides the best result, with 89% of accuracy, 99.7% of Precision, 88% of Recall and 93.5% of F1-score for the SVM classifier.

	© 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 fast fashion business is becoming more reliant on social media marketing (SMM) as SMM enables larger data collection and communication between the brand and its consumers. This study investigates the impact of SMM aspects such as customization, entertainment, interactivity, trendiness, and eWOM on fast fashion’s online and offline purchase intentions (PI). Similarly, it investigates the moderating influence of culture on the factors mentioned above and the relationship’s utilitarian and hedonic reasons. Additionally, 360 responses were obtained from three countries, Morocco, Jordan, and Spain, using an online questionnaire. The findings revealed that customization, amusement, and trendiness influence offline and online PI favorably. Culture was also shown to have a moderating influence on the link between SMM components and PI. Motivations were also discovered to be a mediator between eWOM, trendiness, customization, and PI.

	© 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: Natural disasters are one of the events that threaten food security in every region in Indonesia. Ciamis District is one of Indonesia's areas prone to natural disasters. One of the impacts of a disaster is on the agricultural sector because it will determine food security in the area and can affect the socio-economic community. This study aims to analyze the Geographically Weighted Regression (GWR) Model of the Effect of Disaster Events on Food Security. This study used quantitative methods, and data sources were obtained through secondary data searches. Data were processed using a Geographically Weighted Regression (GWR) analysis tool through a quantitative descriptive analysis approach. The results showed that the natural disasters directly or indirectly impacted food availability and security in Ciamis District. Natural disasters still occur even though food availability, affordability, and utilization are quite good. There are other factors, namely disasters, that come suddenly and cannot be predicted, thereby affecting the food security of a region. Efforts are needed to create togetherness in society to anticipate and respond to disaster events. In addition, it is expected that each individual can take the necessary actions to solve problems independently.

	© 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 effect of web design on the generation of electronic word of mouth (E-WOM) through the satisfaction of e-commerce consumers in the retail sector. To this end, three main objectives were proposed: (1) Evaluate the effect of web design on the perception of security, perceived enjoyment, perceived usefulness and perceived risk of the e-commerce consumer in the retail sector; (2) Evaluate the effect of customer service, perception of security, perceived enjoyment and perceived usefulness on consumer satisfaction in e-commerce in the retail sector; and (3) Explain the positive effect of customer satisfaction and the negative effect of perceived risk on the generation of E-WOM. A study was carried out using a quantitative approach with a non-experimental and cross-sectional design. Through non-probabilistic convenience sampling, a total of 422 questionnaires from consumers in the retail sector were collected. A partial approach was used to analyze the data. Least Squares PLS-SEM by using SmartPLS. The results show the significant positive effect of web design on the perceptions of security, customer service, and customer satisfaction. And a negative effect on risk perception. Furthermore, this study revealed the mediating effects of risk perception, security perception, and quality of customer service in the retail sector. This study has theoretical, practical, social, and customer management implications, so it will be useful in academic, social, and business areas. The results show the positive and significant effect of web design on the perception of security, enjoyment, and usefulness of online shopping. The negative and significant effect of web design on risk perception was also demonstrated; furthermore, this study revealed the positive and significant effect of perceived usefulness, enjoyment, security, and electronic service on customer satisfaction in online shopping. Finally, the negative and significant effect of risk perception on the generation of electronic word of mouth and the positive and significant effect of satisfaction on the generation of electronic word of mouth were demonstrated.

	© 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 integration of blockchain technology into estate governance has the potential to revolutionize transparency, efficiency, and security in estate management. Traditional governance structures often grapple with inefficiencies, lack of transparency, and security issues in estate management. This paper comprehensively explores the impact of blockchain on estate governance, and then risk management and business sustainability. This research centers on the role of risk management on business sustainability to mediate and moderate the effect of estate governance on business sustainability. The results indicate that effective real estate governance positively affects risk management practices in real estate. However, both real estate governance and risk management contribute to business sustainability. Moreover, there are still gaps in the literature that require further investigation. Where policymakers and practitioners can develop informed strategies to strengthen governance structures, mitigate risks, and promote sustainable practices in real estate; Thus, promoting long-term success and resilience in the real estate industry. It is worth noting that future research should focus on empirical testing of the proposed hypotheses to provide a better understanding of these dynamics and their implications for risk management that can affect business sustainability.

	© 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 understand how farmers, especially those with limited technological knowledge, utilize social media in their agricultural activities. The study also aims to identify the impact and responses of farmers to the use of social media in their agricultural practices. Additionally, the research discusses a conceptual framework that integrates internal and external factors in understanding social media user behavior. The research methodology employed is a systematic literature review using scientometric analysis. Bibliometric approaches, machine learning, and social network analysis are utilized to achieve research objectives. Data were obtained from the Scopus database, consisting of high-quality articles published between 2011 and 2023.The findings indicate that social media plays a significant role in influencing farmers' responses to the information they receive and their levels of trust, subsequently affecting their willingness to adopt smart agricultural technologies. Furthermore, the research highlights internal and external factors influencing social media user behavior in the agricultural context. The novelty of this research lies in its holistic approach that integrates cognitive and behavioral factors in understanding social media user behavior. Additionally, the study complements previous literature by addressing antecedents, mechanisms, and consequences of social media use by farmers, as well as identifying barriers they face in leveraging social media.

	© 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 primary objective of this research was to find out how using augmented reality technology in the Abha Governorate affected children with learning disabilities' ability to think creatively. A cohort of students associated with educational establishments in the Governorate of Abha was the subject of a study. The study was given a month's duration. The study involved thirty students in all, fifteen of whom were each from the experimental and control groups. The experimental group did better on post-tests assessing initial imagination, perceptive imagination, and transformative imagination than the control group, indicating a significant improvement in the study's results. There was no statistically significant difference between the experimental group and the control group's scores on imaginative thinking during the follow-up evaluation or in the immediate post-intervention period.

	© 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 scrutinizes the motivational factors of e-commerce adoption using the Integrated Model of E-commerce Adoption in SMEs (IMAES) and analyzes its impact on business performance. This is quantitative research. Survey technique used to collect data. The Special Region of Yogyakarta, Indonesia, was chosen purposively as the center of traditional drinks, and 330 SMEs of traditional drinks in all districts/cities were proportionally taken as samples. Structural Equation Modeling was used as the data analysis method with PLS tools. This study shows that buyer, competitor behavior, relative advantage, organizational readiness, perceived ease, benefit observability, compatibility, ICT organizational, and innovativeness level significantly and positively influence e-commerce adoption. Risk perception and complexity have a significant and negative effect on e-commerce adoption. E-commerce adoption has a significant and positive impact on business performance, operational performance, financial performance, and marketing performance. Stakeholder collaboration is required to increase e-commerce adoption.

	© 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 media influencers have become important motivators in shaping tourist attitudes and behaviors. This study analyzed how exposure to influencer content impacts key outcomes for the destination Jordan. A survey of tourists who visited Jordan in the past 3 years measured their perceptions of influencer credibility, content quality, awareness/interest, trust/engagement, destination image, general tourism behavior, and intentions to revisit. Results of SEM analysis found significant positive effects of influencer marketing on both destination image and visit intentions. Awareness/interest and trust/engagement were most impactful, highlighting influencers' role in sparking early motivation. Content quality additionally predicted visit intentions by informing decisions. Perceived credibility made recommendations more persuasive. Furthermore, usage intensity positively moderated the mediated relationships, amplifying effects among heavy social media users. Findings provide theoretical validation of how influencers act as digital opinion leaders. By enhancing destination image through compelling portrayals, influencers shape audience travel interests and behaviors. Managerial implications suggest destinations should invest in influencer campaigns for reach and inspiration while ensuring content quality. Performance tracking informs optimal platform and demographic targeting. Overall, influencer marketing demonstrated significant persuasive appeal for potential tourists. This quantitative study pioneer’s measurement of influencer marketing's tangible impacts on key tourist metrics. The results empirically substantiate the ability of strategically leverage influencers to motivate visitation and guide decision-making. As practitioners refine partnerships for audience growth and branding, academic research must also advance a nuanced understanding of this emerging phenomenon at the confluence of social media and tourism consumer 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: Previous research states that viral marketing has an important role in increasing consumer purchasing intentions, viral marketing can also encourage increased brand awareness. This research aims to analyze the relationship between Viral marketing and purchasing decisions, Brand awareness and purchasing decisions, and Viral marketing and purchasing decisions. This research method is quantitative through surveys, research data was obtained by distributing online questionnaires to 720 selected online shop customers in Indonesia using a simple random sampling method, and the online questionnaire was designed using statement items with a Likert scale of 1 to 7. Data analysis used a structural equation model based on covariance (CB-SEM) with SmartPLS 4.0 software to analyze research data. The independent variables are viral marketing and brand awareness, and the dependent variable is purchasing decisions. The stages of data analysis are validity testing, reliability testing, model fit testing, and significance testing of hypothesis testing. The results of this research are that Viral marketing has a positive and significant relationship with purchasing decisions, Brand awareness has a positive and significant relationship with purchasing decisions, and Viral marketing has a positive and significant relationship with purchasing decisions. Viral marketing is one of the factors that can influence purchase intentions. Viral marketing is expected to have multiple effects because many people who receive the message can convey it to tens or even hundreds of other internet users. Brand awareness can influence consumers toward purchasing decisions, which states that brand awareness has a significant influence on 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: Research has shown the effect of student engagement, teacher leadership, and curriculum on the effectiveness of the use of learning technologies and the online learning environment. The study included a total of 382 samples that included both teachers and students. Survey respondents are qualified teachers with at least 10 years of teaching experience, as determined through sampling. Participants responded to a study questionnaire that was used to collect data. Data were collected using Smart PLS software, which included validity and reliability assessments and hypothesis tests. The results of the study indicated that the dissemination of learning technology is directly affected by teacher leadership and student participation, which affects its effectiveness. Instructor leadership, student engagement, and successful use of learning technologies directly impact the online learning environment. The use of learning technology is influenced by teacher leadership, curriculum, and student engagement, which ultimately impacts the online learning environment. This study suggests two main results. To enhance the efficiency of learning technology deployment, the focus of public policy should be on enhancing teacher leadership and student performance. Moreover, enhancing the efficient use of learning technology is a critical policy goal to improve the quality of the online learning environment. Students and teachers with enhanced skills should collaborate to share their technological learning materials and management practices to improve students' online learning experiences. Subsequently, modifications were made to the curriculum and there was an increase in teacher leadership.

	© 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 quantitative study investigates the relationships between Management Information Systems (MIS), Business Intelligence (BI), and Strategic Planning (SP) within Jordanian Public Listed Companies, with a focus on the mediating role of BI. The target population comprises employees from the 108 public shareholding companies listed on the Amman Stock Exchange, totaling an estimated 1,080 senior managers involved in strategic planning. A random sample of 285 employees was surveyed to achieve a 95% confidence level with a 5% margin of error. Data were collected using a structured questionnaire with multi-item scales adapted from prior studies. Structural equation modeling (SEM) was employed to test the conceptual framework and hypothesized relationships, utilizing the two-step SEM approach with AMOS software. The results reveal significant positive relationships among MIS, BI, and SP. Specifically, MIS exhibits a statistically significant positive effect on SP, supporting previous research indicating MIS provides comprehensive data for informed planning. Furthermore, MIS significantly influences BI capabilities, underscoring the importance of robust MIS infrastructure for advanced BI analytics. BI, in turn, positively impacts SP, aligning with literature suggesting BI tools enhance planning agility and effectiveness through data-driven insights. Bootstrapping analysis demonstrates that BI partially mediates the relationship between MIS and SP. While BI acted as a significant mediating variable, MIS had a significant direct impact on SP, implying that though MIS has a direct impact on SP, it has an indirect impact, through BI, as well. Further analysis revealed that the constructs are interconnected, and that the mediation of BI is a necessary part of the process in Jordanian Public Listed Companies. As such, acknowledging the relevance of MIS, BI, and SP and the mediating role of BI, organizations can adapt their decision-making to achieve sustained competitive advantage within the dynamic business environment in Jordan.

	© 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: Internal audit is a bulwark ensuring the integrity of financial statements, a linchpin for stakeholder trust and informed corporate decision-making. With the proliferation of complex financial transactions, audit teams face mounting challenges in deciphering voluminous transactional data to safeguard financial reporting quality. Machine learning has the potential to identify signifiers of financial reporting quality. Within the Design Science Methodology framework, we apply the Random Forest Classifier technique to metrics such as the error rate to enhance financial reporting. We find that the Random Forest Classifier identifies that certain parameters are critical to error detection, which enhance account receivable accuracy, lower receivable account control risk. This research advances the argument that technologically-enhanced internal audit procedures can play a pivotal role in ensuring that financial reporting mirrors the economic reality of the company.

	© 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 how e-learning can raise the caliber of education provided in Jordanian higher education institutions. The study looks into how e-learning affects educational quality by taking into account individual demands, perceived learning value, and technological and electronic requirements. Using a questionnaire, information was gathered from professors at six Jordanian private universities in Amman. The findings underscore the significance of e-learning mandates and the moderating function of upper management backing in augmenting academic achievements. Faculty members should be empowered, and tools should be made available to maximize learning results.

	© 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 media has recently drawn the attention of regulators and current research because of its importance in meeting client demand and improving an organization's marketing success. Because of this, the current study investigates how social media strategy, analysts, and active involvement affect social media performance and how social platforms' results affect advertising outcomes for the UAE's electronic industry. This research also examines how customer satisfaction impacts the connections between marketing performance and social media. It also explores how social media performance mediates the intersection of social media tactics, experts, consistent presence on social media, and advertising performance. Data were collected via questionnaires, and data analysis was done using smart-PLS. The findings showed a favorable correlation between social media performance and social media strategies and active participation, as well as a good correlation between social media performance and marketing effectiveness. Additionally, the findings indicated that consumer satisfaction significantly regulates the link between social media performance and advertising effectiveness. They also highlight that social platform efforts positively mediate the link between social media tactics, analysts, active social media use, and performance. This study aided the regulatory agencies in their decision-making and directed them to sharpen their attention on social media to improve marketing efficiency.

	© 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 analyzes the tourism network and destinations after the COVID-19 pandemic using social network analysis (SNA). Analysis of 789 destinations in Thailand has found that the destinations are connected by 1,1175 tourism routes. The network is a sparse network with a low network density. It seems to have a scale-free property that reflects that most destinations have low connectivity and a small number of destinations have high connectivity. The network has a large average path length and low clustering coefficient. Different roles of destinations are identified based on degree, betweenness and closeness centrality. The findings draw implications for vitalizing the sector.

	© 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 identify the impact of digital transformation and analyze the obstacles and complexities facing the integration of digital technologies into Jordanian Customs and their subsequent impact on achieving strategic flexibility. The study aims to uncover challenges, evaluate their effects, and suggest recommendations to enhance adaptive strategies within Jordanian Customs considering digital transformations. The study included employees in Jordanian General Customs, including customs officials, IT staff, and administrative staff working on digital initiatives. A population of 670 individuals was identified, from whom a purposive sample of (465) directly involved in digital transformation efforts was selected to participate in the study. The study used the descriptive analytical approach to comprehensively investigate the challenges of digital transformation within Jordanian Customs. Surveys, interviews, analysis of regulatory documents formed data collection methods. Quantitative data were subjected to descriptive analysis and regression modeling, while qualitative insights were thematically analyzed to provide a comprehensive understanding of the challenges faced. The analysis revealed the results, the most important of which is that digital transformation has a positive, statistically significant impact in its four dimensions (strategy, organizational culture, transformational leadership, and human resources) in achieving strategic agility in Jordanian Customs, and reveals multi-faceted challenges prevailing within Jordanian Customs, including structural constraints. Infrastructure, resistance to change, cyber security vulnerabilities, and skills gaps among the workforces. The regression analysis highlighted the significant impact of these challenges in hindering the achievement of strategic flexibility within the Customs Department. Based on the results of the study, Jordanian Customs is recommended to take proactive measures to confront the challenges identified. This includes investing in a robust technology infrastructure, implementing targeted training programs to improve employee skills, promoting a culture of innovation, and establishing cross-departmental collaboration to enhance adaptability and strategic flexibility. The study recommended increasing attention to training workers and raising their capabilities to deal with digital transformation positively and improve 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: Mobile Applications offer a new style to service sectors, for instance, in higher education, mobile applications are utilized to provide access to academic resources and academic services. Despite the wealth of mobile applications, they encounter various challenges that have attracted the interest of academia and software developers. The usability issues of mobile applications may cause performance degradation, resulting in the company's loss in terms of cost. This study aims to investigate the usability of the Prince Sattam bin Abdulaziz University (PSAU) mobile application by adopting data mining as a descriptive and predictive process. The first step was gathering data of the usability of the PSAU mobile application using the system usability scale. Afterwards, data was preprocessed into a suitable format to apply data mining methods. Specifically, the explanatory model has been employed to describe and investigate insights related to the usability factors and features of the PSAU mobile application. Furthermore, this study adopted the Four Clustering methods to segment the usability levels of the PSAU mobile application into homogenous groups based on user behavior. Additionally, the predictive model was used to build models for predicting the usability level and Grade and five classification algorithms were employed to predict the usability level and Grade. Most algorithms have given positive results in all performance indicators, where the accuracy rate achieved is 98% to 95% for most methods. The results revealed that the PSAU mobile application has an acceptable usability level, and the data mining methods helped to discover hidden patterns. Furthermore, the findings will help the developers and policymakers understand users' and stakeholders' behavior to find the most common usability problems for each group, and customize the PSAU mobile 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: Reputation management is of more significant consideration for organizations across the globe. However, for relevant purposes, Public Relations accompanied by Artificial Intelligence further play a significant role. Mainly supported by the social exchange theory, this study also focuses on Public Relations practices and Artificial Intelligence as facilitating the pathway to reputation management for online retail organizations in the United Arab Emirates. The researchers selected a sample of n= 330 individuals and analyzed it using Structural Equation Modelling to test the proposed conceptual model. Results revealed that Public Relations practices significantly affect Competitive Value, Online Communication, and Behavior Change. Besides, the effect of Artificial Intelligence on Competitive Value, Online Communication, and Behavior Change also remained significant. Further, the three relevant factors (Online Communication and Behavior Change) significantly affect reputation management, indicating the overall effect of PR practices and AI on reputation management in online retail organizations in the UAE. Hence, it is concluded that PR practices and AI technology have a substantial role in ensuring reputation management. Besides, factors including Competitive Value, Online Communication, and Behavioral Change have a positive role in reputation management, further ensuring attaining the organizational goals. Finally, the researchers discussed the results and highlighted the theoretical implications accordingly.

	© 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 the adoption of Information and Communication Technology (ICT) by Micro, Small, and Medium-Sized Corporations (MSMEs) in Jordan. The research formulates and examines hypotheses on factors affecting ICT adoption morals via the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology Acceptance Model (TAM). The suggested concept, which utilizes Structural Equation Modelling (ESM), highlights the critical responsibilities that social influence and perceived utility play in affecting choices to adopt ICT. It is noteworthy that MSMEs confront a multiple of obstacles when it comes to adopting ICT, encompassing restrictions in terms of infrastructure and resources, shortages of human capital, and hardships in the technology environment. Data were gathered from 305 MSMEs, and outcomes shed light on important factors to boost the impact of ICT integration in the special setting of Jordanian MSMEs.

	© 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 AI bias in financial technology (FinTech)-based supply chain management in Pakistan. The study employs Structural Equation Modeling (SEM) to analyze data from diverse respondents. Hypotheses examine the relationships between AI integration, algorithm diversity, employee training, data quality, regulatory compliance, organizational culture, and AI bias. The findings reveal that higher AI integration leads to increased AI bias, Algorithm diversity reduces AI bias, while employee training decreases bias, Quality and diversity of data negatively correlate with AI bias, and regulatory compliance lowers bias. In addition, organizational culture mediates the relationship between AI integration and AI bias. This research contributes a holistic understanding of AI bias factors, guiding ethical AI adoption. Policymakers can use these insights to shape regulations, and industry practitioners can make informed 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: Social media usage has increased tremendously in recent years. However, when users cannot control their social media usage, it might have some negative impacts on personal and social life, which lead to the cyberloafing phenomenon. This study aims to examine the influence of cyberloafing activities (sharing, shopping, gaming, accessing online content, real-time updating) and social media addiction among netizens. This study utilized Uses and Gratification Theory (U&G) as a theoretical basis to explain the framework. The quantitative method was implemented in this study. An online survey questionnaire was used to collect data and 318 valid respondents were generated. Partial Least Square Structural Equation Modelling via Smart-PLS was used to analyze the data. The study showed that two cyberloafing activities, namely real-time updating and sharing significantly impact social media addiction. However, the other cyberloafing activities (accessing online content, gaming, shopping) do not contribute to social media addiction. This study may help students and employees to be cognizant of the symptoms of cyberloafing and social media addiction. In addition, it also helps government agencies such as Malaysian Communication and Multimedia Commission (MCMC) to produce strategies that can address addiction among netizens and youths. Conclusion, implications, and future research directions were discussed.

	© 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 India, higher education institutions (HEIs) are realizing the value of green interaction, which includes using social media (S.M.) in an environmentally responsible manner. However, there needs to be more consistency on the adoption's present status, the particular tactics used, and the advantages that follow. The current research investigates the various aspects of sustainable communication and its benefits in HEIs throughout India. Through a questionnaire approach, the research enrolled learners across India. The study model's conceptual structure was validated, and its assumptions were proven through the implementation of a quantitative survey. The number of accepted samples was calculated using a conceptual model, and data analysis was performed using the structural equation model (SEM). There were 500 respondents in the study, ranging in age and academic degree and from different institutions of higher learning. The age range of 280 women and 220 men was 80% between 19 and 28. Respondents employed prominent S.M. sites (Twitter, LinkedIn, and Facebook) with purpose and had robust computer abilities. The results demonstrated that inspiration for employing S.M., S.M. characteristics, and information exchange had a favorable impact on students' opinions of user-friendliness and the benefits of digital learning platforms, raising their adoption of them. The research strategy in this investigation delivers suggestions for additional exploration into how HEIs in India may maximize the advantages and utilization of digital learning systems and can be an efficient structure for similar study ventures.

	© 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: Research on e-government and good governance is still rarely carried out, even though e-government and good governance are important factors in government companies. This research aims to analyze the relationship between e-government and financial performance, the relationship between employee competency variables on financial performance, and the relationship that good governance variables have on financial performance. The method of this research is quantitative through surveys, research data was obtained by distributing online questionnaires to 590 managers of government companies who were selected using a simple random sampling method, and an online questionnaire was designed using statements item with a Likert scale from 1 to 7. Data analysis used Structural Equation Modelling (SEM) with the SmartPLS 3.0 software tool to analyze research data. The stages of data analysis are validity testing, reliability testing, and significance testing of hypothesis testing. The results of this research show that e-government had a positive and significant effect on financial performance, and employee competence had a positive and significant effect on financial performance. Moreover, good governance had a positive and significant effect on financial performance. The novelty of this research is the creation of a new model of the relationship between e-government and financial performance, employee competence and financial performance, and good governance and financial performance which has not existed in previous studies. The practical implication of this research is that to improve the financial performance of government companies, we must implement e-government by increasing employee competency and implementing good governance.

	© 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: Businesses heavily depend on social media to engage with customers, utilizing various platforms for interaction, feedback, and promoting products. The influence of social media on customer trust, loyalty, and satisfaction is a prominent subject. This study seeks to comprehend how businesses leverage social media to attain these objectives, utilizing both qualitative and quantitative methods. The initial exploratory phase collected qualitative data from 24 business enterprises, employing grounded theory techniques such as open, axial, and selective coding to pinpoint the primary factors affecting customer trust, satisfaction, and loyalty. Building on the insights from the exploratory study, the research proposes a model and hypotheses. The subsequent confirmatory study employs a quantitative approach, collecting data from 300 respondents in Jordan and utilizing Structural Equation Modeling (SEM) for analysis. Results underscore the pivotal roles of personalization, user-generated content, communications, word-of-mouth, emotions, promotions, and customer support as social media directions in shaping customer trust, satisfaction, and loyalty. This research provides valuable insights into the dynamics of how social media shapes customer relations, offering guidance to businesses navigating this ever-evolving landscape.

	© 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: Currently, school sustainability is the focus of attention of all parties, including education quality management experts, which is related to schools' weaknesses in using big data and artificial intelligence (AI). The aim of this research is to analyze the role of using big data and AI in improving the quality of education quality management in Indonesia and its impact on school sustainability. The research design uses a quantitative approach, especially correlational, verification or hypothesis testing based on empirical data in the field. The research population was all teachers, principals and high school supervisors in Palangkaraya City, Central Kalimanan, totaling around 5,423 people. The sample size used the Hair formula and obtained a sample size of 178 people. Data was collected using a questionnaire which was distributed to selected samples using a Google form. Primary data was analyzed using SMART PLS. The results shows that the use of big data had an impact on the quality education management, it also has an impact on school sustainability, while artificial intelligence had an impact on the quality education management, it also had an impact on school sustainability, In addition, quality education management had an impact on school sustainability and it mediated the relationship between the use of big data and school sustainability, and finally, quality education management mediated the relationship between artificial intelligence and school sustainability.

	© 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 future of the Internet lies in the utilization of contemporary virtual technology, the metaverse is a virtual ecosystem for communication and interaction. This study aims to determine how the metaverse can enhance customer awareness, interest, engagement and experience. The study population consists of customers of retail clothing stores. A questionnaire was developed to collect study data and distribute it electronically. The number of respondents reached (77) customers. Using path coefficients, the results indicate that metaverse can enhance customer awareness, interest, engagement and experience.

	© 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 seeks to analyze the impact of digital marketing, social media, and digital transformation on the development of digital leadership abilities and the resulting enhancement of employee performance. The research examines the complex connections between digital elements and their influence on organizational dynamics, using a case study done at the Amman Stock Exchange as a basis for analysis. The inquiry explores the impact of digital marketing strategies on leadership skills, the use of social media platforms to promote digital leadership, and the transforming influence of digital initiatives on employee performance. In addition, the study evaluates the interaction of these characteristics and their combined impact on organizational success. Evidence suggests that digital methods have a complex and wide-ranging effect on leadership and performance, including factors such as adaptation, communication, and strategic decision-making. The study highlights the capacity of companies, specifically within the framework of the Amman Stock Exchange, to utilize digital tools for the purpose of developing leadership skills and improving performance. The findings obtained from this study provide important insights for enhancing digital ecosystems in comparable organizational contexts, highlighting the importance of a thorough comprehension and strategic integration of digital components in order to attain long-lasting 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: The aim of this study was to evaluate the impact of social media, big data, and data mining on the development of organizational behavior within the telecommunications industry in Jordan. The main objective of this study was to investigate the effects of technological components on the alteration of organizational behavior in the communications sector of Jordan. To accomplish this objective, a thorough empirical investigation was undertaken, encompassing the collecting of data from key stakeholders within the telecommunications sector in Jordan. A sample size of 412 participants, encompassing people from diverse roles within the communications sector, was chosen for the purpose of this study. The participants' replies and perspectives were gathered via the administration of surveys and conducting interviews, resulting in a comprehensive data set suitable for analysis. This study investigated the intricate relationship between the utilization of social media, the application of big data analytics, and the implementation of data mining techniques in influencing the dynamics of organizational behavior. The study's results underscored the substantial impact that social media platforms have on communication patterns and collaboration within telecommunication firms. Furthermore, the utilization of big data analysis has emerged as a significant catalyst for the enhancement of informed decision-making processes, exerting influence on diverse facets of organizational behavior, including strategic planning, employee engagement, and customer interactions. Data mining techniques have been identified as having a crucial function in extracting significant patterns and trends from extensive datasets, hence helping to the improvement of organizational learning and adaptation. The research findings indicated that the incorporation of social media, big data, and data mining technologies had a beneficial effect on the development of organizational behavior within the telecommunications industry in Jordan. The findings underscore the importance for enterprises to proactively utilize these technologies to cultivate a work environment that is characterized by increased agility, responsiveness, and collaboration. This study provides significant contributions to the subject of organizational behavior by examining the impact of social media, big data, and data mining within the specific context of the telecommunication sector in Jordan. The research sheds light on the transformative consequences of these technological advancements. The consequences of these findings have broad relevance for organizational leaders, politicians, and researchers, serving as a basis for further investigations in the dynamic realm of technology-driven organizational 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: Technology has significantly transformed knowledge, education, and access to information by introducing online learning platforms, interactive games, and virtual reality simulations in traditional classrooms, creating a dynamic, engaging, and inclusive learning environment. The ChatGBT project (a pre-developed transformer for training) is a remarkable achievement in artificial intelligence technology. It allows students tailored and efficient learning experiences by providing individual feedback and explanations. ChatGPT e-learning platform has been extensively studied for its adoption and acceptance, but there is a significant gap in research on its acceptability and use, highlighting the need for further exploration. The goal of this work is to bridge this disparity by introducing a comprehensive model that includes three basic elements: performance expectation, expected effort, and social impact. A total of 241 graduate students were surveyed and their data were analyzed using structural equation modeling techniques. The results indicate that “expectation of performance and expected effort” have the greatest impact and importance in determining students’ intentions to use learning platforms via ChatGPT, while social influence does not play an important role. This study enhances the current body of knowledge related to artificial intelligence and environmental sustainability, and provides important insights for professionals, policymakers, and producers of artificial intelligence products. These observations may provide guidance for creating and implementing artificial intelligence technologies to match consumers’ needs and preferences more effectively, while also taking into account broader environmental conditions.

	© 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: Stock prices of different companies frequently display similar temporal fluctuations because of common influencing factors. Accurate prediction of stock prices is of utmost importance for investors in determining their investment strategies. Utilizing multivariate forecasting, which involves analyzing multiple time series, has been shown to be highly effective and efficient when applied to stocks that exhibit similar temporal patterns. It is possible to model the relationship between shares by using a shared temporal model approach. Nevertheless, it is important to note that not all stocks selected for prediction demonstrate a strong correlation; certain stocks may deviate from expected patterns. Therefore, the direct implementation of a comprehensive shared temporal component model is not universally applicable. This study presents a new method called the Semi-Shared Temporal Model, which focuses on the correlation structure among variables that have similar patterns, while also modeling all stocks simultaneously. This methodology is applied to the three leading stocks of 2023: Amazon (AMZN), Alphabet (GOOG), and MercadoLibre (MELI). Based on monthly data collected from January 2010 to December 2023, the study forecasts the stock prices for the months of January to December 2024. The analysis findings suggest that the temporal patterns of AMZN and GOOG shares are highly similar, which supports the idea of modeling them together with shared temporality. Three forecasting methods are utilized: univariate models, full shared temporal models, and semi-shared temporal models. The analysis determines that the semi-shared temporal model approach produces the most precise forecasting outcomes, with a Mean Absolute Percentage Error (MAPE) of 17.97%, surpassing both univariate and full shared temporal models. The forecast for 2024 indicates a favorable trajectory for all three stocks.

	© 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: Technological advancements in Indonesia have been on the rise, and the advent of technology has brought about significant changes in various aspects of society. The integration of technology into human life has greatly enhanced various activities, making information exchange and communication more accessible. As we observe the continuous evolution of technology, it has created new business prospects for companies to harness the power of the internet in providing online shopping services that connect consumers, service providers, and intermediary traders. E-commerce has emerged as a vital platform supporting commercial transactions via the internet. Prior to making a purchase, consumers frequently turn to social media for product reviews, where electronic word of mouth enables users to share their product-buying experiences. This study seeks to investigate the impact of user-generated information through electronic word of mouth on purchase intentions within the e-commerce landscape of Indonesia, utilizing the Information Acceptance Model (IACM). Employing a causal descriptive research approach, this study targeted e-commerce users in Indonesia, with 155 respondents participating. Data collection was carried out through Google Forms, and the collected data was analyzed using SmartPLS 3. Hypothetical testing included t-tests, p-tests, and path coefficient assessments. The study's findings revealed that variables such as information quantity, information needs, attitudes toward information, information usability, and information adoption all play a significant role in influencing purchase intentions, while information quality and information credibility had no discernible impact on purchase 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: The welfare of people has always piqued our interest, and it remains the primary goal of nations around the world in their development endeavors. To effectively drive development efforts, it is critical to understand the diverse welfare features that exist in different locations. Thus, the purpose of this statistical analysis is to classify Indonesian provinces based on a comprehensive set of People's Welfare Indicators, which includes Population Density (PD), Percentage of Poor Population (PPP), Life Expectancy Rate (LER), and Average Years of Schooling (AYS). The methodology used in this study is Hierarchical Cluster Analysis, which employs five distinctive techniques: Single Linkage, Average Linkage, Complete Linkage, Ward's Linkage, and the Centroid Method. The data for this study was obtained from reliable secondary sources, notably the official website of the Central Bureau of Statistics (BPS), and it provides insights on Indonesia's welfare picture in 2021. The average linkage approach shows as the most suitable of the five hierarchical cluster analysis methods used, with the closest cophenetic correlation to 1. The analysis reveals three distinctive clusters within the Indonesian context. Cluster 1 demonstrates a tendency toward low PWI (People's Welfare Index) status, while Cluster 2 exhibits a notably high PWI status. Cluster 3 occupies an intermediate position, characterized by moderate PWI status. These findings not only give useful classification but also act as an important reference point for the Indonesian government. They provide an in-depth insight into each province's distinct welfare features, supporting smart resource allocation and prioritizing aid distribution in regions of highest need. As a result, this research is an essential resource for creating equitable and effective policies and methods to improve people's well-being throughout Indonesia.

	© 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 present research endeavours to explore the efficacy of gamified pedagogy in the realm of early childhood education within the context of Jordan, while simultaneously examining its intricate relationship with parental engagement. The examination of data uncovers a discernibly elevated degree of student involvement in the realm of gamified education, thereby suggesting the effectiveness of employing gamified methodologies in captivating the attention and interest of youthful scholars. Moreover, the presence of a moderate degree of parental involvement implies the possibility of proactive parental participation in the scholastic odyssey. The empirical evidence consistently demonstrates a robust and affirmative association between parental involvement and student engagement, underscoring the crucial and influential position that parents occupy in augmenting student motivation and active involvement in gamified educational endeavors. The present study serves as a valuable contribution towards enhancing our comprehension of the intricate relationship between gamified education and parental involvement. Its findings hold significant implications for educators, policymakers, and parents alike, as they strive to maximize the effectiveness of early childhood education.

	© 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: Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as the multi-objective first time as unsupervised Feature Selection (WDOFS) and the second time as a Clustering algorithm (WDOC). For example, the WDOC outperformed Harmony Search and Particle Swarm in terms of F-measurement by 93.3%; in contrast, text clustering's performance improves 0.9% because of using suggested clustering on the proposed feature selection. With WDOFS more than 50 percent of features have been removed from the other examination of features. The best result got the multi-objectives with F-measurement 98.3%.

	© 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 intricate relationships among Critical Thinking Skills, IT-Based Learning Innovation, Students' Mastery of Materials, and Academic Achievement in the context of education. The study employed a quantitative research approach to investigate the relationships. The hypotheses examined reveal significant findings. Firstly, IT-Based Learning Innovation positively impacts both Students' Mastery of Materials and Academic Achievement, emphasizing the pivotal role of technology in modern education. Secondly, Critical Thinking Skills influenced Students' Mastery of Materials and Academic Achievement, underscoring the importance of fostering these skills in students. Additionally, Students' Mastery of Materials was identified as a crucial factor positively affecting Academic Achievement. Moreover, the study confirmed that Students' Mastery of Materials mediates the relationship between IT-Based Learning Innovation and Academic Achievement, highlighting the indirect impact of innovative IT-based learning methods on Academic Achievement through enhanced material mastery. However, in contrast, Students' Mastery of Materials was not found to mediate the relationship between Critical Thinking Skills and Academic Achievement, suggesting a potential direct link between these factors. Theoretical implications encompass enriching educational theory by emphasizing the significance of Critical Thinking Skills and the multifaceted nature of academic achievement. Practical implications include curriculum revisions, pedagogical approaches, and assessment strategies that promote critical thinking and effective technology integration. Bridging the digital equity gap is crucial, and future research should explore intervention strategies and international comparisons to inform evidence-based educational practices. Overall, this study contributes to a comprehensive understanding of the complex dynamics in education, offering insights for both researchers and educators.

	© 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 direct and indirect influence of the use of Big Data and Cloud Computing Platforms on the smooth processing of financial accounting system data and its implications for the success of village development. This research used quantitative methods, using Saturation sampling techniques, and obtained a sample of 131 respondents who were village financial information system operators, consisting of 131 villages in Pringsewu Regency, Lampung Province, Indonesia. The data collected from the surveys was then analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS). The research and data analysis demonstrate that Cloud Computing Platforms significantly enhance the efficiency of processing financial accounting system data. Additionally, Cloud Computing Platforms have a direct and positive influence on the success of village development. Moreover, the efficient handling of financial accounting system data directly and significantly impacts the progress of village development. Furthermore, the application of Big Data has a direct and substantial impact on the effective processing of data in financial accounting systems, as well as on the achievement of success in village development. Ultimately, the efficient data processing of the Financial Accounting System serves as a partial intermediary between the utilization of Big Data and Cloud Computing Platforms, and the achievement of village development in Pringsewu Regency, Lampung Province, Indonesia. Because the independent variable is able to significantly influence both directly and indirectly the dependent variable.

	© 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)