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This study aims to identify the impact of adopting different techniques of artificial intelligence including (expert systems, machine learning, neural networks and algorithms) in improving the quality of accounting information characteristics such as; appropriateness, faithful representation and verifiability in Palestinian industrial enterprises.

Employees from 13 companies registered on the Palestine Stock Exchange for 2023 were selected. Moreover, the sample included 326 randomly chosen participants. A questionnaire was distributed to participants to collect data, and a descriptive-analytical approach was followed to achieve the study’s aim and examine its hypotheses.

The results showed that the use of artificial intelligence techniques (expert systems, machine learning, neural networks and algorithms) has a positive effect on improving the quality of accounting information characteristics (relevance, faithful representation and verifiability). Expert systems, neural network applications and algorithms contribute to developing solutions to various problems in industrial companies; discovering fraudulent practices in financial statements; and obtaining more accurate, faster and more reliable results. Machine learning also links the company’s systems together simultaneously and in an integrated and effective manner.

The research relied on the industrial sector only because expanding society is difficult due to the general conditions in Palestine, and the results may vary between different sectors due to the nature of their work and activity.

Industrial companies’ efforts to benefit from artificial intelligence applications in their work increase the quality of accounting information, which in turn reflects the company’s real situation and helps in making the necessary decisions efficiently and effectively.

This study contributes to directing the attention of financiers and accountants working in Palestinian industrial companies to the importance of applying artificial intelligence techniques to ensure the highest quality characteristics of accounting information through the preparation of accounting programmes that rely on artificial intelligence to operate, thus achieving the maximum degree of advantage in compiling financial data from its sources, operation and conversion into useful financial information for its users.

The main purpose of this study is to determine the antecedent factors of smart government service apps intention and its impact on actual use by extending the unified theory of acceptance and use of technology (UTAUT) in the Jordanian context.

To achieve the main purpose, a quantitative method was used to test collected data, and hypotheses testing through using statistical package for social sciences (SPSS) and smart partial least squares software.

The findings indicate that social media advertising has a positive effect on both social influence and peer influence. Furthermore, it demonstrated a significant effect of social influence on performance expectancy. In addition, there is a direct correlation between the government capacity, effort expectancy, facilitating conditions and the intention to use e-government services. Lastly, the results mainly show that the actual use of e-government services is significantly and positively influenced by intention and self-isolation. Next, as expected, self-isolation moderated the relationship between intention to use and actual use of e-government services via the Sanad application, and hence the related hypothesis was supported.

This study provides practical recommendations for the policy-makers in the Jordanian e-government and Ministry of Digital Economy and Entrepreneurship (MoDEE) in Jordan.

The main issue is whether customers prefer convenience over Shariah compliance or the opposite when they decide their Islamic banking needs. The purpose of this paper is to explore why customers adopt Islamic banking products and services: Shariah compliance or convenience?

Using convenience sampling, 310 respondents’ data were collected through online survey. For testing the fit and hypotheses of the proposed model, AMOS 25 software and Smart-PLS 4.0 software have been used.

Attitude, Islamic value and convenience have significant determinants of Islamic banking products and services. Shariah compliance has no direct or indirect influence on neither intention nor actual behaviour to adopt Islamic banking services. Furthermore, gender has no such differential effect on the adoption.

Managers and marketers of Islamic banks may benefit from the findings of this study, which demonstrate fresh insights regarding the factors which help in strategy formulations to promote Islamic banking services.

The growth of Islamic banks, branches and windows is remarkable in both Muslim-majority and Muslim-minority countries in the world. This paper postulates the behavioural finance studies in Islamic banking and finance research stream by extending the theory of planned behaviour of Ajzen (1985) as all the three new constructs (Islamic value, convenienc and Shariah compliance) are statistically fit for further studies. However, only Islamic value and convenience are the two significant factors which drive customers to take decision in the proposed model. This study gives insights to the bankers and authority about the consumer behaviour.

This study explored the ramifications of COVID-19 on construction operations in Malaysia.

Following a detailed literature review, 37 ramifications are identified and divided into nine aspects. A self-designed survey is then employed to seek the perceptions of construction practitioners around the Klang Valley region regarding the significance of the ramifications. A total of 203 valid responses are subjected to statistical analyses to prioritise the ramifications.

All the potential ramifications are perceived to be significant, with the five utmost critical ramifications being rescheduling the project timeline, compliance with government SOP, delay in the handover project, compulsory COVID-19 test for all workers and the extra cost incurred to provide COVID-19 test for workers.

This study highlights the ramifications of COVID-19 on construction operations and deliberately informs construction organizations regarding the shortcomings of recent construction management. Besides, the insights suggested that industry practitioners devise corresponding strategies for project sustainability in future similar crises.

The findings serve as a valuable reference and are benign to industry professionals and researchers from developing nations, especially nations that share similar characteristics to Malaysia.

Driven by the explosive growth of artificial intelligence, WealthTech has played a pivotal role in reshaping the wealth management industry in recent years. Within this context, this study aims to explain the antecedents of users’ continuance intention to use the WealthTech platform by integrating the technology continuance theory (TCT), task-technology fit (TTF) and digital nudging.

To empirically test the research model, an online survey was conducted among 337 investors who had previously used WealthTech platform. The authors used partial least squares structural equation modeling (PLS-SEM) to assess the research model and test the hypotheses.

PLS-SEM results show that the proposed model has moderate explanatory power in explaining WealthTech continuance intention. The results also found that attitude, digital nudging and satisfaction are important drivers in promoting WealthTech continuance intention. According to importance performance map analysis, digital nudging, expectation confirmation and satisfaction are critical factors in explaining continuance intention, which require managerial action.

To the best of the authors’ knowledge, this is one of the earliest studies that analyze the determinants of WealthTech continuance intention by integrating TCT with TTF and digital nudging. The study’s findings highlight the importance of fit factors and digital nudging in promoting successful WealthTech services.

The advancement of artificial intelligence (AI) has brought intelligent online shopping experiences to customers. AI-powered retail platforms deliver personalized shopping experiences through tailored recommendations, promotions and assistance. Given the increasing preference for online shopping, it is crucial to explore methods to optimize the adoption of AI-powered retail platforms. To address this, this study aims to examine the impact of technology readiness motivators (optimism and innovativeness) and inhibitors (discomfort and insecurity) on perceived trust, perceived usefulness and purchase intention toward AI-powered retail platforms.

Data were collected from 276 customers in Egypt, primarily from the millennial and Gen Z demographic segments. The collected data were then analyzed using the statistical package for social sciences (SPSS) and partial least squares structural equation modeling (PLS-SEM).

The findings revealed that optimism, innovativeness and discomfort significantly influence perceived trust, while optimism, insecurity and perceived trust significantly influence perceived usefulness. Both perceived trust and usefulness are significant predictors of purchase intention. Perceived trust mediates the effects of technology readiness motivators on perceived usefulness and purchase intention. Moreover, perceived usefulness mediates the effects of technology readiness motivators, insecurity and perceived trust on purchase intention.

To date, there are few investigations regarding the acceptance and adoption of AI-powered retail platforms in developing countries. Thus, this study offers valuable theoretical and practical implications in the context of smart retail technology adoption.

This study explores how customers' individual characteristics and perceptions affect acceptance of service robots as a hotel workforce. The Interactive Technology Acceptance Model (iTAM) has inspired us to investigate effects of customers' technological self-efficacy, perceived interactivity, sense of utility, and enjoyment-level of acceptance related to hotel-service robots as staff.

Data were collected from 224 customers via an online questionnaire conducted in the period April–June 2022 by convenience sampling, and then analyzed by using partial least squares – structural equation modeling (PLS-SEM).

The findings show that customers' technological self-efficacy and perceived interactivity with service robots enhances perceived usefulness and perceived enjoyment, serving as functional and emotional value components of service robots. They also demonstrate that robot's interactivity outweighs other robot's value components, such as perceived usefulness and perceived enjoyment for acceptance of service robots as employees in hotels.

While empirically validating the iTAM, this study emphasizes service robot interactivity as the most important aspect for customers' acceptance, and it adds a new perspective regarding the underexplored role of the customer-robot interface. Combining specific dimensions from different technology acceptance models (functional/socio-emotional/relational; utilitarian/hedonic) the study contributes to the service robot literature currently missing a more holistic understanding of consumers' experience and adoption drivers, and it provides managerial guidance on how to successfully implement service robots in hotel environments.