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This paper aims to explore factors impacting citizen intention toward artificial intelligence (AI) adoption, considering government regulation as a moderating variable. It focuses on the Palestinian Cellular Communications Sector in Gaza Strip, providing insights into the citizen-AI relationship dynamics. The research contributes to enhancing comprehension of AI technology from clients’ perspective.

To test the hypotheses, a questionnaire was used in an empirical study to collect primary data. In total, 347 Palestinian citizens responded to the survey.

The findings of this paper reveal that perceived usefulness, perceived ease of use, perceived risks, social influence, user experience and privacy and security concerns significantly influence citizen intention toward AI adoption. Furthermore, government regulations as a moderating variable strengthen the impact of perceived usefulness, perceived ease of use, perceived risks, social influence, user experience and privacy and security concerns on citizen intention toward AI acceptance and adoption. Thus, further research should explore specific domains and cultural contexts to gain a more comprehensive understanding of the factors shaping acceptance and adoption.

The findings of the study should be understood in the context of their limitations. First, the study ignored cultural or domain-specific subtleties in favor of generic characteristics, which calls for more research in these particular circumstances. Second, relying on self-reported data might result in biases and limitations due to subjectivity in reporting, indicating the necessity for alternate data gathering methods and approaches in future research.

Policymakers, developers and organizations working to promote the acceptability and implementation of AI applications should consider the practical implications of this study’s results. To secure the long-term use of AI technologies in a responsible and user-centric way, policymakers should give priority to public education and awareness, user-centered design and ethical AI development techniques. They should also stimulate partnerships and create monitoring systems.

This paper investigates the originality of factors that influence citizen intention toward AI acceptance and adoption. It uniquely examines the moderating role of government regulations in shaping this intention. By addressing this novel aspect, the paper contributes to advancing our understanding of the complex dynamics surrounding citizen intentions toward AI applications.

This study aims to determine the impact of forensic accounting, probability of detections, tax penalties, government spending, tax justice and tax ethics on value-added tax (VAT) evasion.

The study uses partial least squares-structural equation modeling to examine the connection between tax sanction, probability of detection, tax ethics, tax justice, forensic accounting and government spending on VAT evasion based on 248 responses collected from the retail industry in Jordan.

The findings also demonstrate that there is a negative correlation between tax sanctions, probability of detection, tax ethics, tax justice, forensic accounting, government spending and VAT evasion efficiency.

The results, considering forensic accounting and government expenditure considerations, may emphasize the importance of the tax sanction, probability of detection, tax ethics, adoption of tax justice in the public sector and tax authority. Additionally, the findings are important for regulators and decision-makers in announcing new laws and strategies for VAT evasion.

It turns out that the tax authority and public sector can definitely improve their capacity to protect public funds and limit VAT evasion practices within SMEs by adopting increased tax sanctions, probability of detection, tax ethics, tax justice, forensic accounting and government spending.

Numerous studies have been conducted at the individual level in the context of income tax on the link between tax punishment, probability of detection, tax ethics, tax justice, forensic accounting and tax evasion. This study expands on the scant evidence of this connection to the retail business in the context of VAT avoidance. Additionally, it advances prior studies by integrating fresh elements, such as forensic accounting and government expenditure, that have never been considered in connection to VAT evasion in the retail sector.

This paper aims to analyze and compare housing tenure and model housing price index (HPI) in Saudi Arabia with selected Organization for Economic Cooperation Development (OECD) countries.

The research uses quantitative data from the Saudi 2022 Statistical Census and OECD sources. Analytical methods include polynomial regression modeling for housing price trends and analysis of variance (ANOVA) to explore the relationship between housing variables, alongside descriptive and inferential statistics.

The polynomial regression analysis reveals distinct HPI trends across the studied countries, indicating stability and growth. Countries like Australia, France and the US are projected to see substantial HPI increases by 2026, reaching values around 175, signaling strong market recovery and growth. Greece’s trajectory is marked by fluctuations, recovering modestly post-2020, while Saudi Arabia’s market shows stability with a slight increase forecasted to 92.8 by 2026. The ANOVA analysis for Saudi Arabia highlights significant regional differences in housing tenure, with economic conditions and housing types significantly impacting tenure patterns.

This study fills a void in research by offering a comparative analysis of housing tenure and HPI, shedding light on how economic and demographic factors influence housing trends. The findings are crucial for policymakers to develop targeted strategies that address affordability and stability, catering to diverse demographic needs.

This paper focuses on the commitment of a leading Middle Eastern country – Saudi Arabia – to the United Nations (UN) Sustainable Development Goals (SDGs), particularly SDG13, climate preservation. This paper aims to investigate the determinants of greenhouse gas emissions by examining their correlation with economic growth, population growth, renewable energies, forest area, digitalization and monetary policy.

This research observes greenhouse gas (GHG) emissions and the potential influencing factors during 1990–2023. It employs the autoregressive distributed lag model (ARDL) after testing the stationarity of the variables.

The findings show that population growth, gross domestic product (GDP) growth, percentage of individuals using the internet and forest rents are significant determinants of carbon oxide (CO₂) emissions. Further, methane (CH₄) emissions are significantly associated with population growth, GDP growth, percentage of individuals using the internet and renewable internal freshwater resources. Nitrous oxide (N₂O) emissions depend significantly on the percentage of individuals using the internet and renewable internal freshwater resources.

This research helps policymakers in Saudi Arabia and worldwide identify the factors moderating GHG emissions, and accordingly design targeted interventions. These initiatives would substantially reduce GHG and further global climate goals. Additionally, focusing on Saudi Arabia, a significant emerging country in the Middle East, has broader implications. The findings offer insights that extend beyond its borders, providing valuable lessons for governments in the Middle East and worldwide to assess and improve their initiatives toward SDG13. Therefore, monitoring greenhouse gas emissions in this key country boosts global progress toward the UN’s 2030 Agenda for Sustainable Development. Furthermore, this paper aligns with the Principles for Responsible Management Education (PRME) by leveraging academic and managerial strategies toward sustainability and climate action initiatives.

This study adds to the limited literature on the determinants of GHG emissions in the Middle Eastern region, particularly in Saudi Arabia. In addition to CO₂, it also focuses on CH₄ and N₂O emissions. It shows the beneficial effect of renewable internal freshwater resources. It uses the ARDL model to distinguish between the short- and long-run associations.

This paper aims to examine the factors influencing the adoption of social media marketing by small and medium enterprises (SMEs) in Pakistan. By investigating the drivers and challenges/barriers affecting the adoption of social media marketing tools among SMEs, this study provides practical guidance to SMEs seeking to utilize social media platforms for marketing purposes in a developing context such as Pakistan.

Utilizing the Technology-Organization-Environment (TOE) framework as a theoretical framework, qualitative data were collected through semistructured interviews with representatives of SMEs in Pakistan, followed by thematic analysis of the data.

The research identifies several key factors influencing the adoption of social media marketing by Pakistani SMEs. These factors include doubts regarding the benefits of social media, alignment with regulatory requirements, challenges related to tracking social media performance, resistance from senior management (older employees), the positive influence of competitive pressure and the Covid-19 pandemic, political instability and increased government taxes on digital services. Stakeholders such as marketing professionals, academics, policymakers, government authorities and SME owners and managers can benefit from these findings.

This research contributes to the academic literature on the adoption of social media marketing by SMEs, especially within emerging economies. It enriches theoretical understanding of adoption processes and factors, filling gaps in existing knowledge and laying a foundation for future research in this domain. Using the TOE framework, the study reveals that when all factors are adequately considered, SMEs can transition from traditional marketing methods and embrace social media as a digital marketing strategy to enhance performance, profitability, and gain a competitive advantage over their rivals.