The present study aimed at investigating the impact of liquidity management on profitability in the industrial companies listed on Amman Stock Exchange. Data was obtained from the financial statements of several industrial companies that were listed on Amman Stock Exchange during the period (2010-2018). The data was analyzed through using the SPSS program. The researcher analyzed several financial statements to collect data about liquidity and profitability. It was found that liquidity management affects profitability in the targeted companies.

This study aims to investigate the role of applying artificial intelligence in limiting cybercrime in the 13 Jordanian commercial banks listed in the Amman Financial Market, from the point of view of internal auditors and IT. For this purpose, a questionnaire was designed and distributed to the study sample of (849). The number of respondents to the questionnaire reached (230). The data of the questionnaire were analyzed, and their hypotheses were tested using the statistical program (SPSS) through tests of the arithmetic mean, standard deviation, linear, multiple regression, and the T-test for two independent samples. The study found a statistically significant effect for artificial intelligence with its dimensions (Expert Systems, Artificial Neural Network, Genetic Algorithm, Fuzzy logic) in limiting cybercrime in Jordanian commercial banks. It was also found that there were statistically significant differences in both genetic algorithm and cybercrime attributable to the job variable in favor of IT department employees.

This study aimed to examine the effect of applying extensible business reporting language on the performance of the internal audit. A questionnaire was used to collect the data from 115 of the top managers of firms and internal auditors. Multiple regression methods were employed through SPSS software to test the hypotheses. The results of the study show that the external entity pressure, ease of use of the system, and cost-benefit overload positively and significantly affect the performance of the internal audit. While adapting to previous systems, training their employees, and the successful implementation of the model did not affect the performance of the internal audit.

This study aimed to examine the determinants of lending interest rates of 13 Jordanian commercial banks listed on the Amman Stock Exchange for the period 2011-2018. The factors include liquidity, profitability (ROA), bank size, operating cost ratio, deposit interest rate and inflation rate. The fixed effects model was performed as suggested by Hausman test. The results of the fixed effects model show that ROA and bank size had negative significant impacts on lending interest rates. Liquidity had a negative insignificant impact. The results also show that deposit interest rate and inflation had a positive significant impact on lending interest rate of Jordanian commercial banks. Operating cost ratio also had a positive insignificant impact. Thus, the results indicate that ROA, bank size, deposit interest rate and inflation were good determinants of the lending interest rates of Jordanian listed commercial banks. The study suggests that banks should use profitability and the size of the bank as tools to reduce the lending interest rate, as it is one of the factors that can cause a further decrease in the lending interest rates.

Artificial intelligence (AI) systems have significantly changed the audit process; nevertheless, the AI revolution opponents view this growth as a step-back as many auditors will fail to adapt to this new environment and will drop behind. Our descriptive study examines the perceived ease of use, usefulness, and contribution to the audit quality of different AI’s types. To address local audit firms concerns about their readiness to use AI systems in auditing processes and to advance auditing research, we examine whether perceived ease of use, usefulness, and contribution to audit quality vary by AI systems type (Assisted, Augmented, and Autonomous). An online questionnaire was used to collect data from 124 auditors representing local audit firms in Jordan. Our results indicate that auditors perceive Assisted and Augmented AI systems as ease of use in auditing while perceiving Autonomous AI systems as complicated to use. Besides, Auditors are underestimating Autonomous AI systems’ capabilities and perceived it as not useful for auditing. The results also reveal a significant difference between the perceived contribution to audit quality by the three AI systems types. This study contributes to the existing literature on AI and auditing by developing and testing a measure for AI systems’ perceived contribution to audit quality. This study also provides empirical evidence on how Jordan local firms auditors perceive AI use in auditing.

This paper was conducted to determine the importance of applying the features of responsibility accounting in Jordanian shareholding companies in limiting occupational fraud from the point of view of internal auditors and external auditors. It focuses on comparing their opinions and attitudes towards this issue. The study used a questionnaire that was designed and distributed to a random sample of 98 internal auditors who were shareholders of the firms and 93 external auditors who audited the accounts of the companies. The data collection tool included paragraphs about the seven features of responsibility accounting represented like dividing the organizational structure of the company into responsibility centers, and the existence of a system of delegation to the managers of responsibility centers with their powers in the shareholding. Statistical analysis of the data was performed using the SPSS statistical package. It was found that there is a role to adopt and apply all the features of responsibility accounting in Jordanian shareholding companies from the point of view of both internal and external auditors in limiting occupational fraud. The study recommended the adoption of an accounting system in companies that are in line with responsibility accounting given their role in limiting occupational fraud. The study also sheds light on the importance of external auditors giving attention to reviewing and evaluating the organizational environment and administrative procedures in the company to ensure that they are consistent with integrity and honesty.

When the Corona-virus pandemic hit the world, executing and performing the jobs of the remote world became an imperative, this pandemic became as motivator to create this study which aimed to reveal the advantages and threats that encounter the implementing of Cloud Accounting Information Systems CAIS from the view point of external auditors. For that purpose, a questionnaire was developed and distributed then from 198 valid questionnaires which were analyzed by a T- test. It has been found that the main advantages are a reduction of labor and overtime costs because of the ability to access the system from anywhere, while penetration, interruption, and confidentiality are the main threats, also it was found that there is a strong relationship between implementing cloud accounting information systems (CAIS) and the limiting manipulation of financial information. The study therefore recommended upgrading the security procedures of cloud accounting systems and holding courses for auditors to enhance their abilities in auditing CAIS.

Compliance to tax payment generally results in mitigating fiscal deficit and public debt, and in turn, provides funding to meet the economic and social development. However, regardless of the directed efforts of the government to increase sales tax compliance (or value added tax as it is referred to globally), Jordanian listed firms on the Amman Stock Exchange, compliance remains an issue in light of its negative impact on the government revenues. Literature dedicated to tax rate effects on sales tax compliance in the context of listed Jordanian firms on the Amman Stock Exchange has largely been lacking and as such, the study’s main objective is to examine the effect of tax rate on sales tax compliance among such firms. The study adopted a survey method with questionnaire copies distributed to 191 listed Jordanian firms. In the tabulation of data, only 169 questionnaire copies were deemed to be valid for the analysis. The formulated study hypotheses were tested using PLS-SEM and based on the results, tax rate has an insignificant effect on sales tax compliance. Future studies are recommended to provide further insight into the study determinants. The study contributes by furnishing information to and guiding policymakers and the listed Jordanian firms in enhancing sales tax compliance.

This study aimed to demonstrate the impact of the financial policy, represented in debt policy and dividend policy, and the capital assets on the financial performance measured by return on equity, total assets turnover and market value added of 53 service companies listed on the Amman stock exchange during the period 2014–2018, using the panel data models. According to the results of testing performed on return on equities (ROE) model, total assets turnover (TAT) model, and market value added (MVA) model, it can be concluded that debt policy has a negative significant effect on market value added and total assets turnover, on the other hand, it has a negative insignificant effect on return on equity. The financial performance of the Jordanian service companies is influenced negatively by the debt ratio as a measure of financial policy; which means service companies are using heavy debt to finance the operating activities, which increases financial cost and the risk of financial failure. The study recommended that service companies can increase the volume of investment in fixed assets to generate high financial performance indicators.

This study investigates the factors that influence the sharing of information on social media platforms and examines the effects of perceived security, perceived privacy, and user awareness on users' trust in social media platforms, as well as the moderating effects of age, gender, educational attainment, and internet proficiency on information sharing. The study collected data from 837 social media users in Jordan and analyzed them using structural equation modeling (SEM), confirmatory factor analysis (CFA), and machine learning (ML) methods. The findings of the study indicate that perceived security, perceived privacy, and user awareness all have a significant impact on users' trust in social media platforms. Trust, in turn, has a significant impact on the amount of information shared on these platforms. Also, the findings of this study provide valuable insights into the dynamics of information sharing on social networks. This knowledge will be of interest to managers, policymakers, and developers of social media platforms. In addition, the findings of the study also have implications for the privacy and security of social media users. For example, social media users can be more careful about the information they share on social media platforms, and they can take steps to protect their privacy.