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Buried pipelines under various soil embankment heights are cost-effective alternatives to transporting liquid products. This paper aims to assist pipeline architects and professionals in selecting the most cost-effective buried reinforced concrete pipelines under deep embankment soil with minor structural reinforcement while meeting shear stress requirements, safety and reliability constraints.

It is unfeasible to experimentally assess pipeline efficiency with high soil fill depth. Thus, to fill this gap, this research uses a dependable finite element analysis (FEA) to conduct a parametric study and carry out such an issue. This research considered reinforced concrete pipes with diameters of 25, 50, 75, 100, 125 and 150 cm at depths of 5, 10, 15 and 20 m.

According to this research, the proposed best pipeline diameter-to-thickness (D/T) proportions for soil embankment heights 5, 10, 15 and 20 m are 8.75, 4.8, 3.5 and 3.1, correspondingly. The cost-effective reinforced concrete (RC) pipeline thickness dramatically rises if the soil embankment reaches 20 m, indicating that the soil embankment depth highly influences it. Most of the analyzed reinforced concrete pipelines had a maximum deflection value of less than 1 cm, telling that the FEA accurately identified the pipeline width, needed flexural steel reinforcement, and concrete crack width while avoiding significant distortion.

The cost-effective thickness for the analyzed structured concrete pipes was calculated by considering the lowest required value of steel reinforcement. An algorithm was developed based on the parametric scientific findings to predict the ideal pipeline D/T ratio. A construction case study was also shown to assist architects and professionals in determining the best reinforced concrete pipeline geometry for a specific soil embankment height.

Efficient management of earthmoving equipment is critical for decision-makers in construction engineering management. Thus, the purpose of this paper is to prudently identify, select, manage and optimize the associated decision variables (e.g. capacity, number and speed) for trucks and loaders equipment to minimize cost and time objectives.

This paper addresses an innovative multiobjective and multivariable mathematical optimization model to generate a Pareto-optimality set of solutions that offers insights of optimal tradeoffs between minimizing earthmoving activity’s cost and time. The proposed model has three major stages: first, define all related decision variables for trucks and loaders and detect all related constraints that affect the optimization model; second, derive the mathematical optimization model and apply the multiobjective genetic algorithms and classify all inputs and outputs related to the mathematical model; and third, model validation.

The efficiency of the proposed optimization model has been validated using a case study of earthmoving activities based on data collected from the real-world construction site. The outputs of the conducted optimization process promise the model’s originality and efficiency in generating optimal solutions for optimal time and cost objectives.

This model provides the decision-maker with an efficient tool to select the optimal design variables to minimize the activity's time and cost.

Heavy equipment residual value forecasting is dynamic as it relies on the age, type, brand and model of the equipment, ranking condition, place of sale, operating hours and other macroeconomic gauges. The main objective of this study is to predict the residual value of the main types of heavy construction equipment. The residual value of heavy construction equipment is predicted via deep learning (DL) and machine learning (ML) approaches.

Based on deep and machine learning regression network integrated with data mining, random forest (RF), decision tree (DT), deep neural network (DNN) and linear regression (LR)-based modeling decision support models are developed. This research aims to forecast the residual value for different types of heavy construction equipment. A comprehensive investigation of publicly accessible auction data related to various types and categories of construction equipment was utilized to generate the model's training and testing datasets. In total, four performance metrics (i.e. the mean absolute error (MAE), mean squared error (MSE), the mean absolute percentage error (MAPE) and coefficient of determination (R2)) were used to measure and compare the developed algorithms' accuracy.

The developed algorithm's efficiency has been demonstrated by comparing the deep and machine learning predictions with real residual value. The accuracy of the results obtained by different proposed modeling techniques was comparable based on the performance evaluation metrics. DT shows the highest accuracy of 0.9111 versus RF with an accuracy of 0.8123, followed by DNN with an accuracy of 0.7755 and the linear regression with an accuracy of 0.5967.

The proposed novel model is designed as a supportive tool for construction project managers for equipment selling, purchasing, overhauling, repairing, disposing and replacing decisions.

This study aims to examine the role of blockchain technology (BCT) in trust in financial reporting (TFR) and the use of smart contracts (USC). It aims to ascertain the mediating role of USC in the relationship between BCT and TFR, thereby contributing to the limited empirical literature in this domain.

Based on a sample of the accountants’ familiarity with BCT, a structural equation model was constructed and analyzed using AMOS 24. The model proposes and tests relationships between BCT, USC and TFR.

The study highlights BCT’s significant positive influence on TFR, with USC mediating this effect. It provides empirical evidence that supports the transformative potential of BCT and USC in enhancing TFR.

These findings have significant implications for practitioners, regulatory bodies and policymakers. By highlighting the effectiveness of BCT and USC in fostering TFR, the study makes one aware of strategies to mitigate financial malpractices. It promotes the adoption of BCT in accounting practices.

This study addresses a gap in the literature by investigating the complex interplay of BCT, USC and TFR. It offers a unique perspective by exploring the mediating role of USC, thereby enhancing our understanding of the mechanisms through which BCT can foster TFR.

The Metaverse is an immersive virtual world where individuals interact with each other using an avatar. The Metaverse is promised to offer several potentials for different sectors. While the Metaverse promotes innovative interaction between individuals (e.g. learners), there is a scarcity of knowledge on what influences its acceptance and use in higher educational institutions (HEIs), particularly in developing countries. Thus, this paper aims to identify the factors that affect the users' intentions toward Metaverse technology for educational purposes in the HEIs in Jordan.

A study model was created by incorporating variables from the unified theory of acceptance and use of technology (UTAUT) (performance expectancy, PE; effort expectancy, EE; social influence, SI; and facilitating conditions, FC) and information system success (ISS) model (user satisfaction, SAT; system quality, SQ; service quality, SVQ and information quality, IQ) with perceived curiosity (PC) and hedonic gratification (HG) constructs. Both PC and HG were added as context-related factors that could contribute to improving the applicability of UTAUT and ISS to a wide range of technology use contexts. Data were gathered from 441 Jordanian university students using an online questionnaire.

The analysis of the structural model revealed that users' behavioural intentions toward using Metaverse were significantly affected by user satisfaction (SAT), performance expectancy (PE), facilitating conditions (FC) and hedonic gratification (HG). Also, information quality (IQ) and services quality (SVQ) were revealed to have a significant influence on user satisfaction. Likewise, the results illustrated a significant impact of systems quality (SQ), information quality (IQ) and service quality (SVQ) on PE. Lastly, a significant effect of PC on the EE factor was found.

This study will shed light on a number of practical implications for developers, designers, service providers and decision-makers supporting the acceptance and adoption of the Metaverse technology in the educational context. Also, it will contribute to developing the right strategies, and Metaverse content which will draw the attention of learners.

As per the surveyed literature and the researcher's prior knowledge, this is one of the first studies that integrate the UTAUT model, ISS model and two contextual factors (PC and HG) besides testing the proposed model in a developing country (Jordan). This paper is one of the few in which the individuals' acceptance behaviour of Metaverse technology was examined in the HEIs context.

This article aims to extend the Unified Theory of Acceptance and Use of Technology (UTAUT) model to understand the factors affecting the usage behavior of Blockchain from accountants' and auditors’ perspectives and its impact on their performance.

A quantitative research approach employing a web-based questionnaire was applied, and the empirical data were gathered from 329 potential and current users of Blockchain in the accounting and auditing profession in Jordan. The analytical model was based on structural equation modeling (SEM) using AMOS 25.0.

The experimental findings of the structural path confirmed that performance expectancy (PE), social influence (SI), Blockchain transparency (BT) and Blockchain efficiency (BE) were significantly affecting individuals’ behavioral intention (BI) toward the use of Blockchain-based systems and helped to explain (0.67) of its variance. Also, BE has a positive significant impact on PE. Whereas, in contrast to what is anticipated, the influence of effort expectancy (EE) on BI was not supported. Additionally, users’ intentions were found to affect the actual usage (AU) behavior and helped to explain (0.69) of its variance. The outcome variables proposed in this study: knowledge acquisition (KACQ) and user satisfaction (USAT) were significantly influenced by the AU of Blockchain technology.

This study outlines practical implications for government, policymakers, business leaders and Blockchain service providers aiming to exploit the advantages of Blockchain technology (BCT) in the accounting and auditing context.

To the best of the authors’ knowledge, this article is one of the few studies that offer an evidence-based perspective to the discussions on the effect of disruptive and automated information and communication technologies (ICTs), on the accounting and auditing profession. It applies an innovative approach to analysis through the integration of UTAUT, contextual factors: BT and BE, besides two outcome factors: KACQ and USAT within its theoretical model. This study extends and complements the academic literature on information technology/information systems acceptance and use by providing novel insights into accountants' and auditors’ views.

The COVID-19 outbreak has disrupted the habits of customers as well as their shopping behavior. This study aims to critically examine the associated benefits and challenges of online shopping from the perspective of customers in the COVID-19 pandemic.

A systematic review of the relevant literature published between 2020 and 2022 was conducted via performing comprehensive search query in leading scholarly databases “Scopus and Web of Science” with the restriction of their predefined subject category of “Business.” Overall, 30 research studies were selected for the review and a significant number of studies were published in 2021 (n = 15).

The research findings revealed that customers are motivated to shop online because of perceived benefits such as time-saving, convenience, 24/7 accessibility, interactive services without physical boundaries, trust, website attractiveness and cost-saving. However, challenging factors such as financial scams, privacy concerns, poor quality of products and services, fake promotions and reduced social interaction have hindered the growth of online shopping. The recommendations regarding designing marketing strategies, secured transaction, multiple payment options, trust building, protection of privacy, promotion via social media, effective mechanism to secure and timely delivery of product are helpful to improve the service quality of online shopping.

The outcomes of this research are valuable to online retailers and policymakers, as it highlights how the benefits can enhance customers’ shopping intentions and minimize the impact of associated challenges. This study also recommends the redesigning of user-friendly interfaces of online shopping websites and ensures their privacy, security and performance on a regular basis.

This paper aims to explore the intention to adopt the Metaverse in Islamic banks, with a particular focus on evaluating perceived usefulness, ease of use, user satisfaction and the influence of religiosity. Integrating the technology adoption model (TAM) and religiosity intention model, this study will dissect the multidimensional aspects influencing the acceptance of Metaverse technologies.

Surveying Islamic bank professionals in Jordan, this study used a structured questionnaire and data augmentation to analyze Metaverse adoption factors. Using partial least squares-structural equation modeling, the relationships between ease of use, usefulness, religiosity and satisfaction were explored.

The study identifies pivotal relationships among perceived usefulness, ease of use, user satisfaction and religiosity in the context of adopting metaverse technologies in Islamic banks in Jordan. Evidence highlights the dominant role of perceived usefulness and ease in influencing both intention to use and satisfaction levels. Religiosity, while not a direct influencer, plays a collaborative role, underscoring a balanced mix of technological and religious elements that will potentially shape the adoption trajectory of metaverse technologies within this specific banking sector.

Integrating metaverse technologies in Islamic banks necessitates balancing technological advances with Sharia compliance. The study underscores the importance of aligning user experience with religious values and fostering innovation within Islamic ethical guidelines.

This study uniquely integrates the TAM and religiosity-intention model to explore metaverse adoption in Islamic banks, unveiling a nuanced interplay between technology and religious values. It offers practical insights for tailoring innovations in the Islamic financial ecosystem.

This study aims to examine the influence of corporate governance (CG) mechanisms and ownership structures on corporate governance disclosure (CGD) in listed Mauritian companies.

Multivariate regression techniques, both static and dynamic panel data models, were employed to analyse the effect of the determinants on the CGD level of 42 Mauritian listed companies (38 non-financial and four financial firms) from 2009 to 2019.

In the static model comprising 42 firms, CG attributes such as board size, board meeting frequency, CG committee meeting frequency and audit committee meeting frequency are major determinants of CGD, whereas ownership structure variables such as managerial ownership and institutional ownership do not influence CGD. In the dynamic model, only the CG meeting frequency is a major determinant. The determinants of CGD vary between non-financial and financial firms.

This study is limited to CGD in listed firms, excluding mandatory disclosures and unlisted firms. Future research can use qualitative approaches to better understand CGD behaviour with an extension to mandatory disclosures and non-listed firms.

Policymakers can rely on determinants to draw policy measures to raise CG standards further. Domestic and foreign investors may also depend on the determinants of their expectations of CGD while making investment and credit decisions.

This study contributes to the extant literature by examining a new determinant of CGD: CG committee meeting frequency. It also investigates any differences in the determinants between financial and non-financial firms with different listing status.