Abstract: The aim of this research was to evaluate the impact of decentralization and electronic participatory budgeting on managerial performance. Additionally, the study sought to investigate the management accounting system's role in strengthening the effect of decentralization and electronic participatory budgeting on managerial performance. This quantitative research involved 30 regional units, using primary data collected through questionnaires of 108 fund management officials. The findings of this study demonstrated that decentralization and electronic participatory budgeting both have a positive and significant effect on managerial performance. Furthermore, the management accounting system was found to act as a moderator between decentralization and performance, but not between electronic participatory budgeting and 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: Tuberculosis (TB) is still a major public health concern in many regions of the world, including Indonesia's West Java Provinces. Accurate TB risk factor prediction can enhance overall TB control efforts by directing focused therapies. In this study, utilizing a combination of Negative Binomial Mixed Models (NBMMs) and Feed-Forward Neural Networks (FFNNs), we offer a unique method for the predictive modeling of TB risk variables. A variety of sociodemographic, behavioral, and environmental factors that are known to be linked to TB are included in the dataset utilized in this investigation. To correct for overdispersion and include both fixed and random effects in the model, we first fitted an NBMM major problem in epidemiological investigations is modeling count data with overdispersion, and the NBMM component of the model offers a versatile and effective framework for doing so. Following that, we include an FFNN component in the model, which helps us to detect relevant predictive features and alter the model's weights accordingly. Backpropagation methods are used by the FFNN to adjust model parameters and enhance accuracy. The resulting Negative Binomial Mixed Model Neural Network (NBMMNN) model has a high accuracy value of up to 0.944. Our research suggests that the NBMMNN model outperforms conventional models that are frequently used to predict TB risk factors. By contrast to simpler models, the NBMMNN model can capture complicated and nonlinear interactions between predictors and outcomes. Additionally, the inclusion of random variables in the model enables us to take into account potential sources of variability in the data as well as unmeasured confounding. This work emphasizes the opportunity to enhance TB risk prediction and control efforts by integrating NBMMs with FFNNs. In West Java Provinces and other comparable contexts, the NBMMNN model might be a helpful tool for identifying and resolving TB risk factors, guiding targeted interventions, and enhancing overall TB control efforts.

	© 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 perceived risks, i.e., financial risk, product risk, and convenience risk, as well as the COVID-19 pandemic situation on online shopping behavior among Malaysians. This study uses convenience sampling techniques and comprises 185 respondents who have experience buying online. In addition, the study setting was non-contrived, and data was gathered using a closed-ended questionnaire through an online survey. Descriptive analysis was conducted using SPSS version 25.0 software and SmartPLS version 3.2.8 to test the proposed hypotheses. This study found that perceived risk factors such as financial, product, and convenience risk did not influence online shopping behavior. In contrast, the COVID-19 pandemic positively influences online shopping behavior among consumers. It showed a new development in the theory of online shopping behavior, where users continue to make purchases despite being aware that there may be various risks due to the spread of COVID-19. The role of the ministry, business owners, and consumer associations needs to be given attention to form a sustainable electronic commerce system and protect the rights of consumers. This research can help consumers understand their rights.

	© 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 development of technology and smart mobile devices such as phones and tablets has changed the behavior of tourists when booking tourism services. Based on the technology acceptance model, this study aims to explore the factors influencing the intention to use mobile applications for accommodation booking among GENZ in Vietnam. The analysis of 218 users revealed that four factors influence the behavior of using mobile applications for booking: performance expectancy, effort expectancy, social influence, and hedonic motivation. In addition to identifying the factors affecting usage intention, this study also proposes implications to assist developers and providers in improving their applications and developing suitable product strategies for the future.

	© 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 a confirmatory study, researchers are expected to employ the covariance-based structural equation modeling (CB-SEM). One of the key presumptions when utilizing CB-SEM is that the data is multivariate normal. Nevertheless, a perfect normal distribution is rarely observed in real-life data. To resolve this, the unweighted least square (ULS) is designed to specifically deal with non-normal data in SEM. However, ULS often yields improper solutions like negative, or boundary estimates of unique variances since it considers measurement errors in observed variables. The disturbance in SEM is reflected in unique variance, which is random error due to unreliability or measurement error and reliable variation in the item that indicates unknown latent causes. Consequently, this can generate bias in indicator loadings estimates. As an action to disentangle this issue, the present study proposes the implementation of regularization parameters by adding small positive values to the variance-covariance matrix. The ratio of bias to variance in a model can be improved to obtain the best estimation performance. Pro-Active Monte Carlo simulation was used to produce multivariate non-normal data with designated sample sizes and population characteristics. The data were analyzed using R Programming Environment by employing “psych”, “MASS”, “foreign”, “mvrnonnorm”, “purr”, and “semTools” packages with 1000 replications to produce multivariate non-normal data. Next, the “lavaan” package was used for SEM and regularized SEM analyses. The outcome of this study proves the capability of regularized ULS to improve parameter estimation.

	© 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: Credit card fraud poses a significant challenge for both consumers and organizations worldwide, particularly with the increasing reliance on credit cards for financial transactions. Therefore, it is crucial to establish effective mechanisms to detect credit card fraud. However, the uneven distribution of instances between the two classes in the credit card dataset hinders traditional machine learning techniques, as they tend to prioritize the majority class, leading to inaccurate fraud pre- dictions. To address this issue, this paper focuses on the use of the Elbow Fuzzy Noise Filtering SMOTE (EFN-SMOTE) technique, an oversampling approach, to handle unbalanced data. EFN-SMOTE partitions the dataset into multiple clusters using the Elbow method, applies noise filtering to each cluster, and then employs SMOTE to synthesize new minority instances based on the nearest majority instance to each minority instance, thereby improving the model’s ability to perceive the decision boundary. EFN-SMOTE’s performance was evaluated using an Artificial Neural Network model with four hidden layers, resulting in significant improvements in classification performance, achieving an accuracy of 0.999, precision of 0.998, sensitivity of 0.999, specificity of 0.998, F-measure of 0.999, and G-Mean of 0.999.

	© 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: Gold is one of the most attractive commodities and popular investments. Investment experts often recommend investing in gold because gold is one of the safest investments. It is a stable classic hedge, although the conditions of currency volatility or global markets are depreciated. However, the gold price fluctuations can be influenced by some other factors, such as the USD Index, which reflect and measure the strength of the US Dollar currency, and the Index of Dow Jones Industrial Average (DJIA) or a reflection of the political and economic conditions of the stock market. In this study, we conduct a global gold price forecast (USD) based on the USD Index, the DJIA Index, and the influence of time trends. Based on the data's characteristics, we face the fact that the data is nonlinear, contains outliers, and its pattern is not easy to specify parametrically. Due to the complexity of the model, we then propose a more flexible, robust modeling technique called the Bayesian Nonparametric Quantile Generalized Additive Model method. According to the results for the median case, the proposed method shows an accurate forecasting category due to the value of the Mean Absolute Percentage Error, MAPE less than 10 percent.

	© 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: Companies today strive to integrate manufacturing processes with the environment to strike a balance. This study aims to examine the impact of green implementation for companies on the performance of manufacturing companies. Data was collected using Google Forms distributed online to the manufacturing companies domiciled in East Java. The criterion for the companies is that they have been committed to implementing a green approach to the production process, procurement of environmentally friendly raw materials, and green products. The partial least square technique analyzed data from as many as 115 respondents, with the position as senior staff level and higher, who have worked for at least two years and are permanent employees. The results showed that the implementation of eco-design has an impact on green purchasing and green manufacturing. Eco-design and green information systems implemented by the company can improve manufacturing performance by producing adequate overall product quality, and the number of products produced varies according to market demand. Therefore, the green information system affects green manufacturing and purchasing in manufacturing companies. Therefore, green manufacturing and green purchasing can impact manufacturing performance. The research results contribute to practitioners, especially top management, in committing to implementing Green which affects the performance of manufacturing companies. The theoretical contribution of the research is to enrich green supply chain management and sustainable performance for manufacturing companies.

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

Abstract: The aim of this study is to examine the impact of digital marketing on consumer behavior in the fast fashion industry in the Kingdom of Saudi Arabia (KSA). The fast fashion industry has been growing rapidly in the KSA, and digital marketing has played a significant role in changing consumer behavior in this industry. The study adopted a quantitative research design and used online surveys as the primary data collection method. The sample consisted of a convenient sample of participants who had purchased fast fashion products in the KSA. The data was analyzed using various statistical methods, including descriptive statistics, correlation analysis, and regression analysis. This study's findings shed new light on how digital marketing has affected customer behavior in the fast fashion sector in the KSA. Consumers in the KSA have a good reaction to digital marketing methods in the fast fashion industry, and this effect is significant.

	© 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 the current study is to examine the impact of accounting information systems (AIS) on enhancing financial information security in Jordanian banks by the moderating role information technology (IT) governance. The sample of the study includes 149 administrative employees in banks operating in Jordan and a questionnaire is used as the tool of the study. The results indicate that there is an effect for accounting information systems on enhancing financial information at operating banks in Jordan on information systems' operating, inputs, and outputs. The results also indicated in effect the level for information technology governance on the relationship between accounting information systems in achieving information security at the banks operating in Jordan. Considering the result obtained, the study concluded with a group of recommendations the most important among which was to work on establishing departments to protect and secure accounting information, as well as securing qualified cadres to monitor the systems.

	© 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 was to find out how business intelligence systems, AI, and digital leadership affect how satisfied employees are with their jobs and how much value they add to companies in the Greater Amman Municipality. After the study samples were taken and looked at, a total of 246 samples were approved to be used in the PLS software-based analysis. The results of this study showed that putting in place business intelligence tools, artificial intelligence, and digital leadership all made employees happier with their jobs and gave businesses more value. The research showed that there are four key parts to digital leadership: commander, communicator, collaborator, and co-creator. The main parts of business intelligence are Data Warehouse, Data Mining, Business Process Management, and Competitive Intelligence. Findings show that digital transformation is made up of three key parts: changing processes, developing business models, and changing domains. The results also show that an employee's level of job satisfaction, which includes things like business success, work commitment, and job thinking, is linked to how much value they add to the company. Intriguingly, the current results go against those of earlier studies, which said that the variables of interest have no effect on how happy employees are with their jobs or how much value companies add for their customers. When the results of this study are looked at as a whole, they say that businesses should start doing things that make employees happier at work and increase the value of the business. The current study is innovative because it focuses on the most important parts of business intelligence, artificial intelligence, and digital leadership in order to improve employee satisfaction at work and the quality of business learning with added value in Greater Amman Municipality.

	© 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 mediating effect of information technology on the relationship between internal control system's costs and enhancing confidence in the quality of accounting information in banks working in Jordan. To achieve the objectives of the study, the researchers designed a 56-items questionnaire and 200 versions of this questionnaire were distributed on a random sample from the study population represented by all employees of the internal control departments in banks operating in Jordan, and 152 questionnaires were retrieved, and 4 questionnaires were excluded because they were not valid for analysis so, the valid questionnaires for analysis were 148 questionnaires. Effect was assessed using the Multiple Regression Analysis and after the appropriate statistical treatment, the study concluded with a group of results the most important among which that there was a mediating effect of information technology on the relationship between internal control system's costs and increasing confidence in accounting information in banks working in Jordan in terms of internal control environment costs, internal control activities' costs, internal risk assessment's costs, internal monitoring and follow-up costs, information and internal communication costs among banks working in Jordan that use internal control systems. In light of the results revealed, the researchers recommended the need for implementing internal control systems within certain cost limits in banks because of their significant role in increasing confidence in accounting information through the aforementioned variables.

	© 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 examined the effect of social media on post-purchase behavior on electrical device buyers in Jordan. Drawing on resource-based and knowledge-based previous studies, the mediating effects of customer awareness were also tested. Data were collected from 385 participants from the segment targeted group of customers in Jordan, and hypotheses were tested through partial least squares structural equation modeling using Smart PLS 4.0. The results showed that the mediating role of customer awareness influences enhancing the relationship between social media and promotion mix on the one hand, and post-purchase behavior (exit, voice, and loyalty) on the other hand. Our findings contribute to the existing literature by explaining and strengthening this relationship, which is also referred to as the black box through the mediation of customer awareness. Marketers should recognize the importance of this relationship to develop modern promotional tools in multiple social media to positively enhance the customers’ post-purchase behavior by giving them a competitive advantage.

	© 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 evaluate the impact of effective emotional intelligence on the work of auditors in Ho Chi Minh City, Ho Chi Minh. The authors conducted a survey for 355 auditors at companies and organizations operating in the field of auditing. The results show that there were 4 factors of emotional intelligence that affect job performance, arranged in the following sequence: (1) Perception of emotions, (2) Positive thinking with emotions, (3) Understand emotions, (4) Control emotions. This is the basis for the authors to give some implications to improve the emotional intelligence characteristics of auditors towards work 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: The purpose of this study is to analyze the influence of digital marketing, word of mouth, and service quality on purchasing decisions through a quantitative questionnaire using an accidental sampling method. The research is designed to find out the relationship between the influence of digital marketing, word of mouth and service quality on consumer purchasing decisions using a quantitative approach method. The variables in this study consist of independent variables and dependent variables. The variables studied include digital marketing, word of mouth, service quality and consumer purchasing decisions. The research was conducted at food SMEs in Jakarta, Indonesia. Sources of data in this study were primary data including consumer responses to digital marketing, word of mouth, service quality and purchasing decisions obtained from the results of distributing online questionnaires. The sample size used in this study was 680 people. The data collection method used in this study was an online questionnaire distributed by social media. The data were analyzed using SPSS software and structural equation modeling (SEM) with SmartPLS software tools. The results of this study indicate that the higher the digital marketing, word of mouth, and service quality, the higher the purchasing decision. SMEs must further optimize the use of digital marketing in marketing their companies such as uploading interesting content on one of the existing social media. From a word-of-mouth point of view, companies must promote more to their closest circle of benefits what they get from using SEMs products. Service quality must continue to provide excellent service to consumers or customers so that these consumers feel comfortable and satisfied.

	© 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: Plastic bags are used by many people because they are inexpensive, lightweight, durable, and waterproof. Plastic bags, on the other hand, do not break down and can pollute the environment if not handled properly. Indonesia produces a lot of plastic waste and is one of the top ten countries that has a problem with plastic waste. In this study, we used three months of data of real transactions from a grocery store. This study shows how the decision tree can identify patterns on plastic bag usage at a small grocery store by using demography and products purchase. The attribute weights showed that in the hometown, the total of several products bought were the factors that affected the use of plastic bags.

	© 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 evaluate tourists' reviews of gastronomy tourism expressed in Google reviews according to the CAC model (Cognitive, Affective, and Conative), and to examine the inter-correlations between CAC model components. The study was applied to traditional restaurants in Amman downtown. The research then extracts the main themes from the textual reviews as well as a sentiment score of an affective image of traditional Amman downtown restaurants. The results of machine learning experiments suggest that the proposed approach can identify traditional restaurant reviews in Amman downtown into CAC model components. The results also show that the Random Forest algorithm performed best in the cognitive and cognitive dimensions, whereas the Neural Network algorithm performed best in the affective dimension. ML classifier revealed that most of the reviews were classified as cognitive (such as the type of food, and services) while the remaining reviews were classified as affective (such as pleasure and arousal) and conative (such as intention to recommend, and positive word of mouth) respectively. The highest probability of the cognitive components was the traditional food topic reflecting the unique image of Jordanian traditional food. Affective images formed by users were mainly positive emotions, indicating that the destination image spread well.

	© 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: Bali's culture is synonymous with its inhabitants' practice of celebrating religious holidays. Hindu women in Bali often purchase ritual equipment. This research aims to identify the determinants of impulsive buying among Hindu women in the retail industry, as well as the impact of Customer Relationship Management (CRM) on managing this behavior. The research method used is quantitative, with a sample size of 250 respondents analyzed using Smart PLS. The results show that the hedonic shopping value has a favorable and substantial influence on impulsive purchasing, as does the desire to buy impulsively. Self-control has the potential to adversely moderate the effect of the desire to acquire on impulsive purchasing. Hedonic shopping value is important to consider, thus marketing programs should accommodate the hedonic shopping value that Hindu women in Bali seek when shopping for Galungan (yadnya) preparations.

	© 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 banking sector around the globe has witnessed a huge development in its services and products. The electronic banking services are considered as a competitive advantage for the banking sector. The purpose of this paper is to evaluate the effectiveness of e-banking service quality on customer satisfaction in the context of Saudi Arabian commercial banks. Both quantitative and qualitative research methods were used in the study. A sample of 308 customers from the banking sector participated in this study. The researchers have developed a self-structured questionnaire to collect the relevant data. In addition, secondary data was gathered from published sources, including websites, journal papers, and publications of the chosen commercial banks. The findings of this study show that the eight service quality dimensions; reliability, transactional efficiency, customer support, service security, ease of use, performance, satisfaction with service quality and service content have a significant impact on the level of user's satisfaction with e-banking in the Saudi Arabian commercial banks.

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

Abstract: The purpose of this study is to investigate the impact of using artificial intelligence applications on the performance of accountants and audit firms. The final sample for this study comprises 38 audit firms. This study uses a survey-based methodology in the context of Saudi Arabia. The results of the multiple regression revealed that the audit firms using artificial intelligence applications perceive them as useful instruments that increase the performance of accountants and audit firms. They can reduce the cost, effort, and time of the audit process, achieve a competitive advantage for the audit firms, help auditors better determine materiality, achieve a competitive advantage, improve the performance of the audit team, carry out the continuous audit process better than the traditional audit, enable auditors to select audit samples with high efficiency, improve the quality of control procedures on electronic transactions and files used by the client, contribute to the management of operations and tasks with more sophisticated and intelligent mechanisms, increase the efficiency and effectiveness of the audit process and the efficiency and effectiveness of planning and supervising the audit process, reduce uncertainty and audit risk. The results reported by this study can be valuable for the accounting and auditing professions, audit firms, and standards and auditing regulators to deeply understand the extent to which artificial intelligence applications influence the performance of accountants and audit firms.

	© 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: Financial technology, also known as Fintech, continues to transform the financial services sector globally. Fintech adoption has been delayed in some places, particularly in the Middle East, despite the potential positive benefits. This study investigates the mediating effect of perceived ease of use on the relationship between seamless transactions, financial risk, legal risk, security risk, perceived risk, and the intention to use financial technology in Middle Eastern countries. Data was collected from 500 respondents from five Middle Eastern countries (Jordan, Kuwait, Saudi Arabia, Qatar, and the United Arab Emirates) using a structured questionnaire, and partial least squares structural equation modelling (PLS-SEM) was used to test the research model. The findings demonstrate that perceived ease of use strongly mediates the links between seamless transactions, financial risk, legal risk, security risk, perceived risk, and the intention to use financial technology. The study shed light on the significance of perceived ease of use in influencing people's intention to utilize financial technology as well as the function it serves in minimizing the effects of perceived risks. The findings of this study could be useful for financial technology companies operating in Middle Eastern countries, policymakers, and researchers interested in the adoption of financial technology.

	© 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: Digital entrepreneurship can be a potential alternative solution for addressing challenges faced by young people and future workers in Asia. Additional studies are required to enhance comprehension of digital entrepreneurship given the insufficiency of research conducted in this domain. This research seeks to uncover possible determinants that could impact the desire to engage in digital entrepreneurship, with a specific focus on personal traits, resilience, and the level of educational services. The participants in this study are university students as they represent the potential future workforce and potential digital entrepreneurs. A total of 517 sample data (212 Malaysian, 305 Indonesian) were collected through online surveys towards students in Malaysia and Indonesia. The study used a brief version of The Big Five Personality Traits, CD-RISC resilience scale, Liñán & Chen entrepreneurship intention scale, and Parasuraman, Zheitaml, Berry SERVQUAL to gather data. To analyze the data, the study employed structural equation modeling. The results suggest that the intention to pursue digital entrepreneurship is affected by both an individual's openness to experience and their resilience. Additionally, the study revealed that service quality is a factor that affects both digital entrepreneurship intention and resilience. This study provides new understanding of digital entrepreneurship intention antecedents and implies that improvement on education quality service can foster student’s intention to digital entrepreneurship and their resilience.

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

Abstract: This paper examines speakers’ systematic errors while speaking English as a foreign language (EFL) among students in Arab countries with the purpose of automatically recognizing and correcting mispronunciations using speech recognition, phonological features, and machine learning. Accordingly, three main steps are implemented towards this purpose: identifying the most frequently wrongly pronounced phonemes by Arab students, analyzing the systematic errors these students make in doing so, and developing a framework that can aid the detection and correction of these pronunciation errors. The proposed automatic detection and correction framework used the collected and labeled data to construct a customized acoustic model to identify and correct incorrect phonemes. Based on the trained data, the language model is then used to recognize the words. The final step includes construction samples of both correct and incorrect pronunciation in the phonemes model and then using machine learning to identify and correct the errors. The results showed that one of the main causes of such errors was the confusion that leads to wrongly utilizing a given sound in place of another. The automatic framework identified and corrected 98.2% of the errors committed by the students using a decision tree classifier. The decision tree classifier achieved the best recognition results compared to the five classifiers used for this purpose.

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

Abstract: The rapid growth of social media platforms has revolutionized marketing communications, and the recent trend of how people use social media led to the inception of the term "influencer marketing" as an increasingly popular approach for brands across markets. This development has been driven by the unparalleled increase in influencers’ presence on social media platforms, which has generated new venues for companies to connect with their desired demographic and interact with them in a more genuine and significant manner. Understanding the factors that drive the effectiveness of influencers has become increasingly important for both marketers and researchers. Numerous studies have been conducted on the topic of celebrity endorsements. However, the use of "traditional" celebrities is losing its appeal in the digital era of social media, as brands increasingly turn to social media influencers instead. Nonetheless, there is still a lack of understanding about how marketers can effectively utilize this new marketing phenomenon. This study aims to examine the role of trustworthiness, expertise, and information quality of social media influencers in shaping consumer purchase intention, with a specific focus on the mediating role of brand attitude. A total of 309 complete responses were collected via convenience sampling between January and February 2023 then the model examined by using SPSS and AMOS software. The results showed that all attributes of the influencers are affecting brand attitude as well as purchase intention, while brand attitude partially mediated the relationships. Implications, limitations and future research have also been 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: The study aimed at bridging or reducing the knowledge gap between digital marketing di-mensions and customer’s happiness, by diagnosing both the level of digital marketing adoption and the level of customer’s happiness achievement, determining the nature of the relationship between digital marketing and customer’s happiness, and recognizing the level of effect and contribution of digital marketing dimensions in achieving customer’s happiness. This is based on the main idea that digital marketing activities are the main basis for achieving customer’s happiness, when designing digital services. Opinions of (360) customers in Amman five-star hotels were surveyed and viewed to achieve this direction, by designing and distributing a questionnaire. The most important results of the study showed that all digital marketing dimensions positively affect customer’s happiness, as well, the level of using dimensions of both digital marketing, and achieving customer happiness is lower than the required level, by five-star hotels in Amman. The most important recommendations were using of distinguished digital channels tools to respond to attract customers, such as the use of advertisements that accustom customers to use of products or services based on virtual reality or through the applications that use live streaming marketing system (photos or video) in order to bring customers close to what services the hotel offers. Using creative, and effective methods in communicating with customers through human emotions to create delicious marketing for customers, which makes them engaged with the offers they receive, whether through e-mail or SMS. Interest in providing real and effective content to digitally marketed service, in order not to create a gap between hotel and its customers as a result of the mismatch between what is advertised and what is actually provided. Determining success indicators of a hotel digital marketing campaigns by knowing customer’s feelings and their happiness (i.e. through customers’ positive feedback).

	© 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 era of IoT gaining traction, attacks on IoT-enabled devices are the order of the day that emanates the need for more protected IoT networks. IoT's key feature deals with massive amounts of data sensed by numerous heterogeneous IoT devices. Numerous machine learning techniques are used to collect data from different types of sensors on the objects and transform them into information relevant to the application. Furthermore, business and data analytics algorithms help in event prediction based on observed behavior and information. Routing information securely over the internet with limited resources in IoT applications is a key problem. The study proposes a model for detecting network anomalies in IoT devices to enhance the security of the devices. The study employed the IoT Botnet dataset, and K-fold cross-validation tests were used for validating the values of evaluation metrics. The average values of Accuracy, Precision, Recall, and F Score was 97.4.

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

Abstract: The increasing popularity of smartphones has led to the rise of e-wallets, which allow users to store their payment information on their devices and complete financial transactions conveniently and securely. This research extended the unified theory of acceptance and use of technology (UTAUT2) model to investigate the main factors influencing users’ intention to accept e-wallets in Jordan, where little research focused on such apps. Using a quantitative method, a sample of 181 users was utilized, and an instrument of 32 items was used. Findings revealed that price value, hedonic motivations, social influence, performance expectancy and perceived trust are major predictors of users' intention to use e-wallets apps. In contrast, facilitating conditions and effort expectancy are not significant toward the adoption process. Finally, conclusions and future work are presented in the last section of the study.

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

Abstract: This study aimed to demonstrate the impact of big data analytics techniques on reducing information asymmetry in industrial companies listed on the Amman Stock Exchange from the point of view of workers in Jordanian financial intermediation companies. Two approaches have been adopted to achieve the target of this research. The first approach is the analytical descriptive approach through a survey to collect primary data that measures the elements of the independent variable related to big data analytics techniques (Volume, Velocity, Variety, and Veracity). The second approach is an applied approach that measures the dependent variable of information asymmetry based on the financial statements of industrial companies listed on Amman Stock Exchange for the period (2015-2021). The statistical program (SPSS) has been used to analyze data and test the hypotheses through multiple regression testing. Based on the results of the statistical analysis of the data and the opinions of the research community, it was found that the huge volume of big data has become difficult to process using traditional data processing applications. Furthermore, there is a statistically significant relationship between big data analytics techniques and the reduction of information asymmetry from the point of view of employees in intermediation firms in Jordan. Consequently, it is necessary for those in charge of the industrial companies listed on the Amman Stock Exchange to develop modern techniques capable of analyzing big data with high efficiency. It can also assist in providing target groups including investors, stakeholders, and other beneficiaries with reliable and efficient data required to make rational decisions, as well as to reduce the risks of information asymmetry.

	© 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 use of data mining to predict early employment readiness of students is gaining importance due to the expansion of data production in various industries. This study aims to address the employability issue in Middle Eastern nations by utilizing an Adaptive Neuro-Fuzzy Inference System (ANFIS) data mining technology. The experimental investigation used data from tracer studies conducted by three Jordanian universities, consisting of 22 parameters. Results showed that despite achieving an accuracy of 94% for the graduate dataset, ANFIS exhibited high complexity due to the large number of attributes used. The study has implications for selecting relevant variables and investigating multiple aspects. Data mining has various applications, including classification, clustering, regression, association rule development, and outlier analysis. As data production continues to expand, this study provides insights into the potential use of ANFIS in predicting early employment readiness of students in Middle Eastern nations.

	© 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: Big data has become much more widely used in recent years, particularly in the banking sector. Banks have begun to use big data to enhance customer experience, optimize operations, and create novel products and services. This study investigates the effect of big data governance on financial technology in Jordanian commercial banks. The study focuses on the four dimensions of big data governance: strategy and planning, ethics and social responsibility, data quality and management, and infrastructure and architecture. Additionally, the study considers the mediating role of organizational culture in the relationship between big data governance and financial technology. Primary data were collected from 250 IT employees working in Jordanian commercial banks, and the data were analyzed using PLS-SEM. The study findings indicate that big data governance has a significant positive effect on financial technology in Jordanian commercial banks. Additionally, it has been discovered that organizational culture partially mediates the relationship between big data governance and financial technology, emphasizing the significance of creating a culture that encourages the efficient use of data in fintech. In the context of Jordanian commercial banks, this study presents empirical evidence for the connection between big data governance and financial technology. The results indicate that big data governance measures should be applied while taking organizational culture into account as a potential mediator of the effects on financial technology. This study offers guidance on how to successfully integrate big data governance policies in commercial banks to advance financial technology for bank managers and policymakers.

	© 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: Repurchasing in the future reflects the success of a business that can build customer loyalty, which happens because the company can meet the needs and expectations of consumers. The dynamics of changes in consumer behavior in choosing products encourage companies to be able to provide satisfying products. Satisfied consumers will feel a bond with the product. Purpose of the study is to examine Self-Brand Connection (SBC) as a mediating variable between customer satisfaction on repurchase intention and the role of love mark in moderating SBC for intention to repurchase. The sample used in the study was 210 and analysed quantitatively via SmartPLS3. The study found that customer satisfaction affects repurchase intentions. Customer satisfaction positively affects self-brand connection. The SBC affects repurchase intention. Love for culinary brands cannot moderate self-brand connection on repurchase intention. Brand respect can moderate SBC on repurchase intention.

	© 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 find out how much the ways that blockchain technology helps in different parts of the supply chain affect how SMEs use blockchain technology. Moreover, the research examines the correlation between blockchain use and overall performance. The data was obtained from the SMEs' owners and managers, who have the authority to implement blockchain technology. Two follow-up phone calls yielded 145 usable replies from 500 prospective respondents, for a response rate of 29%, which was analysed employing structural equation modelling (SEM). The results demonstrated that the contributions of blockchain adoption to task technology fit, task characteristics, technology characteristics, operational supply chain transparency, and supply chain agility influenced the acceptance intentions of SME managers and that there is a significant positive correlation between blockchain adoption and overall performance. The results aid vendors and policymakers in formulating strategies and effective plans to accelerate blockchain adoption by SMEs. Furthermore, the findings provide owners/managers of SMEs with reason to believe that blockchain technology might be a source of competitive advantage.

	© 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 examines the debated relationship between quality management and innovation using a multidimensional quality management perspective. The quality performance that is supposed to result from the adoption of quality management is investigated further as a possible mediator between quality management and innovation in the higher education sector. The data needed to test the hypotheses was gathered by sending a survey via the internet to the faculty members at universities in the United Arab Emirates. Applying the approach of structural equation modelling with partial least squares, the hypothesised associations between 175 respondents are evaluated. According to the findings, implementing rigorous quality management has a direct as well as indirect impact on innovation performance via its impact on quality performance. The impacts of soft quality management on hard quality management have indirect consequences on innovation performance. The association between rigorous quality management and innovation performance is moderated in part by quality performance. This study provides one of the initial studies to apply the multidimensional method of quality management in higher education and has the potential to assist directors in better comprehending the interdependencies between soft and hard quality practices.

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

Abstract: This study has examined factors, such as technology and employee influence on artificial intelligence (AI) adoption of e-innovative projects in the United Arab Emirates. The present study revealed the success or failure of e-innovation adoption in the public sector of the UAE and hinted at potential e-innovative projects to consider essential factors before adopting it. The study's sample covered the government sector, and the data collection method was a survey questionnaire with a sample size of 1037 responses made up of government employees. This paper was mainly built upon the diffusion of innovation and technology acceptance theories. The analysis findings showed that technology (an external factor) significantly and positively contributed to adopting AI e-innovation technology. Further analysis revealed that employee (internal factor) proxies directly influenced the adoption of AI e-innovation technology. Overall, internal and external factors contributed to adopting e-innovation technology in the United Arab Emirates. For future directions, additional factors related to the market should be considered to explore their contribution.

	© 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 analyse the bibliographic characteristics and content of articles on Data Visualization published in journals indexed by Scopus written by researchers from throughout the world. We conducted a bibliometric and content analysis of publication in the Scopus database. We only retrieved articles written in English. We conducted content analysis using the VOSviewer software and visualized the co-occurrence of keywords and bibliographic coupling of sources and countries. Following the study protocol, we found 862 articles on Data Visualization over the past 30 years. The most productive journal that published these articles was Lecture Notes In Computer Science (n=32). The most productive country was the United States (n=305). Based on citations, the most influential authors, and journals were Thorvaldsdóttir et al., (2013) [Thorvaldsdóttir, H., Robinson, J. T., & Mesirov, J. P. (2013). Integrative Genomics Viewer (IGV): High-performance genomics data visualization and exploration. Briefings in Bioinformatics, 14(2), 178–192.] (n=4699), and IEE Transactions on Visualization and Computer Graphics (n=656). The keywords of research on Data Visualization formed 7 clusters (e.g. Data Visualization, Visualization, and Human). From a global perspective, Data Visualization research in the past 30 years has increased significantly. There were European published journals nominated publications. Thus, Asian countries need to conduct more active research on this topic.

	© 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 advent of information technology has caused people to consider how they can make effective and efficient decisions in various activities. The implementation of information technology systems is expected to be advantageous in facilitating these activities because such systems can provide decision-making support and contribute to the success of endeavors in areas such as business, economic, social politics, and education. One common tool used in learning systems is e-learning applications. This research aims to analyze the effect of e-learning on user loyalty with user satisfaction. This research, conducted in Jakarta, is explanatory in nature, targeting individuals who have utilized e-learning applications in their activities, particularly in the field of public sector activities, with a sample size of 163 public sector employees. Data was collected through online questionnaires, and hypothesis testing was conducted through the PLS-SEM method. The results indicate that service quality and perceived value have positive impacts on user satisfaction, which in turn, positively influences user loyalty.

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

Abstract: Using advanced technology in business has created hyper-competition among organizations to satisfy customers' needs. Using advanced technology aims to provide customers with quality products/services at suitable prices in the right place better than competitors. Therefore, the current study's purpose is to explore the influence of cloud computing services on Jordanian commercial organizations’ competitive advantages, organizations which use cloud computing services. The study uses quantitative, cause-effect, and cross-sectional methods and uses a convenience sampling approach to collect the data by questionnaire from 111 managers and/or owners of commercial organizations. The collected questionnaires are examined and inserted into SPSS. The instrument validity, normal distribution, and reliability are verified, then descriptive analysis is performed, the relationship between independent and dependent variables is tested, and finally multiple regressions are used to test the hypotheses. The findings indicate that commercial organizations are concerned about cloud computing services as well as competitive advantage sub-variables. The results also show that there was a significantly strong correlation between cloud computing services and competitive advantage. Moreover, cloud computing services influence the dimensions of competitive advantages (quality, cost, reliability, innovation, and responsiveness) of commercial organizations, where cloud computing services have the most significant influence on quality followed by cost and responsiveness, respectively. However, cloud computing services do not significantly influence innovation and reliability. Finally, the study recommends doing comparable research on other sectors, and industries as well as in other countries to test the results' generalizability.

	© 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 purpose of this study is to investigate how group reference, perceived usefulness, and product quality influence online shoppers' desire to purchase and final purchase decisions. Multiple methods of quantitative analysis and processing of data are used to evaluate and validate the study's hypotheses. Using a Structural Equation Model, the study's theories were tested and analyzed. Customers of digital market websites in Jordan participated in this study by responding to an online poll. Data was compiled from 220 study questionnaires using a systematic sampling strategy. Data analysis with the Structural Equation Model revealed significant favorable effects of group reference, perceived usefulness, and product quality on both purchase intent and final online purchase decisions. The authors chose to center their study around the perspectives, comments, attitudes, and impressions of groups of individuals. Perceived usefulness can be gauged along the aspects of experience, enjoyment, and subjective norm. The words customer expectations, real product specifications, and the quality of the service received all shed light on the product's quality. The originality of this study rests in the model that was created to explain the relationship between group reference, perceived usefulness of products, and product quality as they relate to purchase intent and digital market website use 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: This study aimed at testing the impacts of social responsibility on customers’ switching behavior in using products and services. The research method was quantitative based on the structural equation modeling SEM with the sample size of 551 individual customers in small and medium enterprises in Vietnam. Research findings demonstrated that social responsibility put both direct and indirect impacts on customers’ switching behavior in using products and services. This relationship was proved with two intermediary factors, namely enterprises’ brand value and customer loyalty. These conclusions not only revealed the research’s contributions but also laid the foundation for further studies. Based on the research findings, the author proposed recommendations to avoid customers’ switching and minimize business loss due to customers’ switching behavior in using products and services.

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

Abstract: The expression "social media" refers to a software-based platform developed for users’ benefit. People use it to gain social power, market their products, conduct online business, and share information and ideas. This digital ecosystem has become helpful in various ways, but research indicates that it does not come for free. Addiction, depression, and anxiety are some of the adverse conditions discussed in many studies. The purpose of this study is to mark if there is a relationship between using social media networks and the numbering of people with anxiety or depression. Also, by addressing the need to learn more about what makes people use social networks and how that use affects anxiety and depression in Arabic-speaking users in Jordan, we can help people from different cultures understand each other better. This research uses TAM, telepresence, and survey data from 1050 people, mainly from Jordan. The research looks at how the usage of social media is related to supposed usefulness, supposed ease of use, trust, social influence, age, gender, level of education, marital status, the time spent on the internet, preferred social media network, and perceived usefulness of SNS. AMOS 20 methods of confirmatory factor analysis (CFA), structural equation modeling (SEM), and machine learning (ML), such as SMO, ANN, random forest, and the bagging reduced error pruning tree (RepTree), were used to test the proposed model hypotheses. According to the results, the researchers found high correlations between social network usage and depression and anxiety. The use of social networking sites is also affected by how useful they are seen to be, how easy they are to use, trust, social influence, and telepresence. Also, the moderator's age, gender, level of education, marital status, amount of time spent on the internet, experience with the internet, and favorite social networks all affect how they plan to use social networks.

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

Abstract: The purpose of this study was to investigate how public sector workers in Indonesia use e-learning systems and how they can benefit from them. The researchers analyzed five variables that contribute to the effectiveness of e-learning: system reliability, information sharing, service quality, user satisfaction, and net benefit. Structural Equation Model analysis was used to analyze the data collected from 203 respondents who were public sector employees in Indonesia. The findings of this study revealed that information sharing, and service quality significantly impact user satisfaction, which in turn has a significant effect on net benefits. Additionally, system reliability was found to significantly impact user satisfaction. This theoretical implication suggests that there is a direct relationship between the level of information sharing and service quality provided by a public sector organization and the level of user satisfaction experienced by its usage of e-learning. The practical implication of the finding is that public sector organizations must prioritize the reliability of their e-learning systems. This includes investing in regular maintenance and updates, ensuring proper testing and quality control procedures, and addressing any issues or downtime quickly and effectively.

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

Abstract: The purpose of this study was to analyze the effect of digital marketing on purchasing decisions, word of mouth on purchasing decisions as well as the effect of service quality on online shop purchasing decisions. The variables studied include digital marketing, word of mouth, service quality and consumer purchasing decisions. The types in this study used quantitative survey research. This study used data collection techniques using online questionnaire methods distributed among online shop consumers. The number of samples in this study were 630 online shop consumers. The research used simple random sampling techniques. Variable measurement used a Likert scale from 1 to 5. The data analysis technique in this study implemented Structural Equation Modeling (SEM) analysis tool. The results of this study indicated that digital marketing had a positive and significant effect on purchasing decisions, Word of mouth had a positive and significant effect on purchasing decisions, and service quality had a positive and significant effect 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: The purpose of this study is to analyze the relationship between public service and community satisfaction as well as the relationship between e-service quality and community satisfaction in government organizations. The study uses quantitative descriptive research. In addition, the study also collects data to test hypotheses or to answer questions related to the variables to be studied. The study uses a data collection technique questionnaire method which is given to respondents whose contents are in the form of written statements related to the research object, namely public services, e-service quality and community satisfaction. The population studied in this study is the community. The number of samples in this study is 470 people. The study uses a purposive sampling technique. Purposive sampling is a sampling technique with considerations that meet the criteria. The criteria are people who have downloaded and used internet-based service applications provided by the Government. Variable measurement is based on a Likert scale. Each respondent's answer choices are given a score of values arranged in stages based on a Likert Scale arranged as follows: Strongly agree (5), agree (4), Neutral (3), disagree (2) and strongly disagree (1). The data analysis technique in this study uses the Structural Equation Modeling (SEM) analysis tool from the IBM SPSS AMOS 26 statistical software package in the model and hypothesis testing. The stages of structural equation modeling and analysis are divided into seven steps, namely: (1) theoretical model development, (2) compiling a path diagram, (3) converting a path diagram into a structural equation, (4) choosing an input matrix for data analysis, (5) assessing the identification of the model, (6) evaluating the estimation of the model, (7) interpretation of the model. Based on the results of the analysis, the results show that there is a significant positive effect of public service on community satisfaction in government organizations, and there is a significant positive effect of e-service quality on people's satisfaction in government organizations. Government leaders should pay attention to the factors that are considered to influence community satisfaction. Such as paying attention to service procedures for the community, improving procedures for service, including during the process of complaints, criticism and suggestions from the community, then paying attention to the time the service process is carried out, since efficiency in solving community problems also contributes to the comfort or satisfaction felt by the community.

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

Abstract: The current mobile network core is built based on a centralized architecture, including the S-GW and P-GW entities to serve as mobility anchors. Nevertheless, this architecture causes non-optimal routing and latency for control messages. In contrast, the fifth generation (5G) network will redesign the network service architecture to improve changeover management and deliver clients a better Quality-of-Experience (QoE). To enhance the design of the existing network, a distributed 5G core architecture is introduced in this study. The control and data planes are distinct, and the core network also combines IP functionality anchored in a multi-session gateway design. We also suggest a control node that will fully implement the control plane and result in a flat network design. Its architecture, therefore, improves data delivery, mobility, and attachment speed. The performance of the proposed architecture is validated by improved NS3 simulation to run several simulations, including attachment and inter- and intra-handover. According to experimental data, the suggested network is superior in terms of initial attachment, network delay, and changeover management.

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

Abstract: An increased sense of job performance and better job satisfaction can be achieved by receiving social support. In order to fulfil this purpose, this study aimed to determine the relationship between social support on the one hand and job performance and job satisfaction on the other hand for the Jordanian insurance industry employees. Survey data were gathered from 269 employees from the Jordanian insurance industry. The PLS 3.0 software was used to process data using the structural equation modelling method. The study’s findings revealed that all social support factors were positively and significantly related to job performance and job satisfaction, including manager support, peer support, friends support, and others’ support. Hence, job performance and job satisfaction in the Jordanian insurance industry can be predicted by studying the existence of social support. The study’s findings concluded that the higher the social support, the higher the job performance and job satisfaction.

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

Abstract: This study aimed to quantify the relationship between factors influencing the investment outcomes of airport infrastructure development in Vietnam. On that premise, suggesting the ideas for applying information technology systems to maximize resources to improve investment outcomes in Vietnam's airport infrastructure development. Data for the study were gathered from the Airports Corporation of Vietnam's annual report and a survey of 316 officials involved in the investment and development of airport infrastructure in Vietnam. The linear regression model is used to quantify the impact of various factors. According to the research findings, the most influential variable according to the survey subject's opinion is the contractor (NT), with an adjusted beta coefficient value of roughly 0.3915.

	© 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)