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.

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.

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.

Altman Z score is an effective tool for measuring a company's financial strength and the possibility of bankruptcy. In this study, the Z score formula was utilized to measure the Indian automobile industry's financial soundness. The financial data of ten automobile companies listed in the National Stoke Exchange (NSE) was taken to analyze both original and emerging market formulae of the Altman Z score. Results suggest that companies of the industry listed in the NSE are financially sound. The study concluded that the Indian automobile industry is sound and robust, and the automobile companies are not prone to financial distress or bankruptcy in the near future.

The Indian cement industry has adopted various environmental protection technologies, but adoption of these new environmental technologies and development of working model could not resolve many issues related to environmental concern among Stakeholders. This paper examined the current technologies used by the cement companies and the challenges they are facing in adoption of these technologies. This research describes the effects of cement manufacturing on global warming, water, coal and other pollution emissions during cement production process and involves environmental manufacturing technologies. The study measures the challenges of introducing environmental technologies by creating a model of challenges. including challenges in perceived usability of technology, challenges in perceived utility, challenges in user engagement, and challenges in intent to use behaviour. The study examines the challenges of introducing environmental technologies into the Indian cement industry to mitigate air, water, and energy pollution and to highlight the new environmental technologies and development of the model. The data from 1540 professionals responsible for using the environmental technology were gathered and analysed with t test and regression analysis. The final outcome of the research is the model expressing the challenges in adoption of environmental technologies in India.

This study aims to examine the effect of company experience on audit committee diligence among manufactured listed companies on Saudi Stock Exchange (Tadawul) for the period 2015-2017. The final sample of this study consists of 191 firm-year observations. Using the Pooled OLS regression, the study finds that there was a positive impact of company experience on audit committee diligence. The study provides insightful evidence to policy makers on the determinants influencing the audit committee diligence among manufacturing companies.

This paper investigated the impact of corporate governance on enhancing the financial performance of industrial companies. The sample of the research consisted of 55 industrial companies listed at the Amman Stock Exchange (ASE) during the period 2014-2018. Data were collected from the firms' annual financial statements using content analysis approach. The results confirmed that the audit committee and ownership structure had positive and significant effects on two dimensions of financial performance. In view of research findings, the study recommends companies to raise some awareness about the importance of corporate governance, in addition to strengthening supervisory procedures by legislators.

This paper aims to contribute to the literature by examining whether audit committees' attributes affect risk disclosure practiced by Jordanian listed companies. Selecting a sample of 94 Jordanian companies listed on Amman Stock Exchange, the authors carried out a manual content analysis on annual reports to determine the level of risk disclosure. Random effect model was employed in the analysis. Empirical results show that the audit committee size had a positive effect on the level of risk disclosure. However, there was no evidence that the frequency of the audit committee meetings, expertise or overlapping of the audit committee membership were significantly related to the risk disclosure. The findings are important for standard setters to improve their comprehension about the influence of audit committee in disclosing risk information and reconsider the effective monitoring role played by audit committee.

The importance of computer-assisted auditing techniques (CAATs) is widely acknowledged by auditors. However, the current usage of CAATs is not as broad as expected. In this work, the technology–organization–environment framework is used to establish and analyze the organizational factors affecting the post-adoption usage of CAATs. This study also determines whether or not the use of CAATs enhances the audit process. Top management commitment is introduced as a variable that moderates audit firms’ use of CAATs and audit performance. The data used in this work were obtained from auditors of audit firms in Jordan. Analysis results reveal that CAAT usage is affected by the cost–benefit of technology, firm size, readiness and competitive pressure. By contrast, technology compatibility and the complexity of the accounting information systems of clients do not appear to influence CAAT usage. Top management directly influences audit performance and is thus crucial in dictating how auditors utilize CAATs. However, it does not exert a moderating effect (top management × audit firm’s use of CAATs) between audit firms’ use of CAATs and audit performance. Moreover, the use of CAATs improves the overall audit process of audit firms.

The study proposed a multi-criterion decision model from benefit, opportunity, cost, risk aspects of SME family business to develop logical investment priorities for northeast Indian family entrepreneurs. The data was collected from 368 northeast entrepreneurs and analytical hierarchy process was applied to develop weights and priorities of every criteria and sub-criteria. The study found employment opportunity; business growth; reputation; stability and succession planning as top priorities. The findings provide heuristic judgment for entrepreneurs and infer to entrepreneurs while taking strategic investment decisions and also to local governments, policymakers, and industrialists. Further, the limitations and research directions were presented.