The Measurement of Blockchain Technology in Financial Reports in Commercial Banks

The objective of the present study is to measure the impact of blockchain technology on financial reports. The study utilizes a time series analysis covering eleven commercial banks listed on the Amman Stock Exchange from 2009 to 2019. Two key measures, namely other operating expenses and customer deposits are employed in the Return on Assets (ROA). The findings indicate that blockchain technology can be quantified by 0.038 of other operating expenses. However, there are no discernible indications of measuring blockchain technology through customer deposits. The study suggests that blockchain technology is a double-edged sword; when not utilized as required, it leads to increased expenses, and conversely, its effective exploitation can have cost-reducing effects. In other words, operational inefficiencies or heterogeneity are associated with elevated costs associated with implementing blockchain technology.   Doi: 10.28991/HIJ-2024-05-02-014 Full Text: PD

The impact of using types of artificial intelligence technology in monitoring tax payments

This study examines the relationship between the types of Artificial Intelligence (AI) technology employed and monitoring tax payments. A thorough literature review is conducted to examine different AI technologies in the context of tax administration. These include machine learning algorithms (MLA), natural language processing (NLP) technology, robotic process automation (RPA), explainable artificial intelligence (XAI), and advanced data analytics techniques (DAT). A variety of technologies, such as big data analytics, task automation, task automation, unstructured data analysis, and predictive modeling, are available to improve tax payment monitoring procedures. Recommendations for further study to expand our knowledge and use of AI in tax payment monitoring are included, along with the consequences of AI adoption for tax authorities, policymakers, and practitioners

Do Uncertainty and Financial Development Influence the FDI Inflow of a Developing Nation? A Time Series ARDL Approach

The study focuses on investigating the long-term and the short-term effect of uncertainty, and financial development on the FDI inflow of Pakistan during the period 2001–2019. To achieve the objective of this study, we obtained the data from World Development Indicators (WDI) and the European policy uncertainty index’s websites. The dependent variable was FDI inflow. Experimental variables of the study are uncertainty and financial development. The stationarity testing revealed that FDI and Economic Policy Uncertainty (EUP) have weak significance and FD has no significance. However, by taking the first difference, all the variables become highly significant. Similarly, it is further indicated that the optimal lag level is four. Additionally, the bound test confirmed that a long-term relationship (co-integration) existed between the variables of the study. The ARDL estimations conclude that uncertainty and financial development have long-run as well as short-run effects on FDI inflow for Pakistan during the period of study. The uncertainty plays a strong part in decreasing the FDI inflow, whereas financial development plays a strong part in enhancing the FDI inflow in Pakistan during the period of study

The effect of spatial distribution on the composition of the middle social class in the Kingdom of Saudi Arabia: A spatial econometric analysis

This article examines the formation of the Saudi middle class using econometric models and a national survey of household budget and consumption data from 44,000 households in 2019. The study compares the spatial offset model (SAR) and spatial error model (SEM) with the Space Turbine Model (SDM) and Space Turbine Error Model (SDEM), finding that the SDM and SDEM models offer better benefits and options. The SDEM model exhibits the best-fit quality based on the Akaike information criterion. The results reveal a positive spatial effect indicating that human capital accumulation is vital in knowledge diffusion and technological transfer. The study also identifies spatial inequalities in the distribution of the middle class, with a concentration in urban areas like Riyadh and the Eastern Province. While the poor class is concentrated in rural areas which surround the main cities such (e.g., Rumah, Tawala, Hanak, Araar and Aljof) while the wealthy class is concentrated in urban areas, particularly Riyadh. The article emphasizes the importance of regional development and suggests measures to reduce inequality and enhance the middle class's role in the economy. In effect, the Saudi government should increase access to quality education and training by investing in the education system to provide citizens with the skills needed for a modern economy, including higher education, vocational training, and apprenticeships. Nevertheless, the Kingdom should promote entrepreneurship by creating an environment that encourages entrepreneurship and supports small business growth through tax incentives, access to capital, and start-up support. Moreover, the most important is improving access to finance by making it easier for businesses, especially small ones, to access finance through loan guarantees and support programs

Do Uncertainty and Financial Development Influence the FDI Inflow of a Developing Nation? A Time Series ARDL Approach

The study focuses on investigating the long-term and the short-term effect of uncertainty, and financial development on the FDI inflow of Pakistan during the period 2001–2019. To achieve the objective of this study, we obtained the data from World Development Indicators (WDI) and the European policy uncertainty index’s websites. The dependent variable was FDI inflow. Experimental variables of the study are uncertainty and financial development. The stationarity testing revealed that FDI and Economic Policy Uncertainty (EUP) have weak significance and FD has no significance. However, by taking the first difference, all the variables become highly significant. Similarly, it is further indicated that the optimal lag level is four. Additionally, the bound test confirmed that a long-term relationship (co-integration) existed between the variables of the study. The ARDL estimations conclude that uncertainty and financial development have long-run as well as short-run effects on FDI inflow for Pakistan during the period of study. The uncertainty plays a strong part in decreasing the FDI inflow, whereas financial development plays a strong part in enhancing the FDI inflow in Pakistan during the period of study

Evaluating the D&M IS Success Model in the Context of Accounting Information System and Sustainable Decision Making

The Accounting Information System (AIS) is generally employed for the automation of operational processes and the enhancement of company efficiencies, but more recently, AIS developments have had a great effect on the process of sustainable decision-making among organizations. However, previous research on the AIS and its capabilities attributed its success to critical success factors. Therefore, in the current work, De Lone and Mc Lean’s Information System (D&M IS) Success Model is evaluated in terms of AIS in Jordanian organizations. The current study primarily aimed to determine the influence of system quality, service quality, information quality, system use and user satisfaction on AIS use, which is argued to eventually enhance the quality and sustainability of decision-making. The study employed a quantitative approach using a self-administered questionnaire for data collection involving 101 decision-makers who are familiar with AIS usage. Following the collection of data, it was validated using Structural Equation Modeling (SEM)—PLS. Based on the obtained results, system quality and information quality significant affected system use, but service quality did not. In turn, AIS was found to have a significant effect on user satisfaction. Furthermore, system use and user satisfaction had positive effects on AIS, which eventually affected the sustainability of decision-making, representing the net AIS benefits. The study contributes to existing IS literature, particularly in the field of determining the factors that influence the AIS net benefits, with the proposed model validated in Jordanian organizations using AIS. The study can be used as a guide to shed light on the importance of AIS and it also provides implications, limitations and opportunities for future studies

A New Technological Model on Investigating the Utilization of Mobile Learning Applications: Extending the TAM

Mobile learning has become increasingly important for higher education due to its numerous advantages and transformative potential. The aim of this study is to investigate how students perceive and utilize mobile learning (m-learning) services in universities. To achieve this objective, a conceptual model was developed, combining the TAM with additional new determinants, including perceived security, perceived trust, perceived risk, and service quality. The primary goal of this model is to assess the adoption of m-learning apps among users in university settings. To evaluate the proposed model, SEM was utilized to test the research model. The findings of the study highlight the critical roles of perceived security, perceived trust, and service quality in promoting the adoption of m-learning apps. Moreover, the results indicate that perceived risk negatively impacts both students’ trust and their attitudes towards using mobile learning services. The study reveals that the perceived trust, and service quality factors positively influence students’ attitudes towards adopting m-learning apps. These research findings hold significant implications for universities and academia, offering valuable insights to devise effective strategies for increasing the utilization of m- learning services among students. By gaining a deeper understanding of students’ perceptions and acceptance, universities can optimize their m-learning offerings to cater to students’ needs and preferences more effectively

Perception of Occupational and Environmental Risks and Hazards among Mineworkers: A Psychometric Paradigm Approach

This study aims to assess workers’ perception of occupational and environmental risks and hazards using the psychometric paradigm. For this purpose, data were collected using survey questionnaires from 360 mineworkers recruited from mineral and sand mines. Respondents were asked to evaluate eight occupational and environmental risks and hazards on nine commonly used risk characteristics. The principal component analysis revealed that two components, “Dreaded” and “Unknown”, explained 73% percent of the total variance in workers’ risk perception. The results also showed that the risk of developing an occupational disease was perceived as the most dreaded and unknown type of risk, while landslide, occupational noise, and vibration exposure were the least familiar to the respondents. A practical implication of this research is that the results may offer an insight into the employees’ perceptions of the hazards and risks associated with their working environment. This could help risk management develop and implement effective risk management and communications strategies

Environmental Transformational Leadership and Green Innovation in the Hotel Industry: Two Moderated Mediation Analyses

This research aims to investigate the relationships between transformational environmental leadership (ETL), organizational citizenship behavior for the environment (OCBE), and green innovation (GI). At the same time, green perceived organizational support (GPOS) and promotion focus (PF) roles were examined as moderators. Integrating transformational leadership, ability-motivation-opportunity (AMO), social exchange, expectancy, and regulatory focus theories, a quantitative research-based methodology was adopted with structural equation modelling (SEM), and smart partial least squares (PLS) program to analyze the obtained data from 388 guest-contact employees. The results show that ETL positively affects OCBE; in return, OCBE mediated the association between ETL and GI. The results also approved the positive moderation effects of the GPOS and PF variables on the association between ETL and OCBE. In the context of the hotel industry, we discuss the implications that these results have for both research and practice