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The acceptance of Islamic banking services by non-Muslim customers is not promising in the Malaysian context. Thus, this study aims to examine the effect factors that may motivate this customer group to adopt the Islamic banking services in the Malaysian context.

A self-administered questionnaire was used to collect data through google docs from 188 respondents. Structural equation modelling partial least squares (PLS-SEM) was used to analyze the hypothetical model of this study.

The result of this study found that knowledge about Islamic banking exerts a positive effect on non-Muslim beliefs (attitudinal, control and norm). Moreover, this study found a significant relationship between attitude, subjective norm, perceived behavioral control with non-Muslim Intention towards Islamic banking services. Furthermore, the mediating effect of attitude, subjective norm and perceived behavioral control was supported.

This is a pioneer study that contributes to the consumer behavior literature by extending the theory of planned behavior by incorporating knowledge in the model. In addition, this study develops comparatively new relationships, practically the mediation role of beliefs (attitudinal, control and norm) between knowledge and intention.

This study aims to examine the impact of client information technology (IT) capabilities on audit report lag and audit fees in Jordanian companies listed on the Amman Stock Exchange (ASE) during the COVID-19 pandemic.

This study analysed financial and non-financial data from 72 Jordanian public shareholding companies listed on the ASE between 2014 and 2021. Using fixed- and random-effects models, the authors examined the impact of client IT capabilities on audit report lag and audit fees. The authors also examined how the COVID-19 pandemic might affect audit report lag and audit fees. The analysis incorporated various control variables specific to the Jordanian context to ensure accuracy.

Empirical evidence indicates that client IT capabilities do not significantly impact audit report lag and audit fees. In contrast, the COVID-19 pandemic has positively impacted audit report lag and audit fees, leading to an increase in audit report lag of 60 to 67 days and an increase in audit fees of approximately 15%. It is worth noting that these effects are more pronounced when influenced by factors including return on assets, company losses and audits conducted by the Big 4 firms.

The scope of this study, which focuses on Jordanian firms, may limit the generalisability of the findings to other contexts. Reliance on aggregate IT infrastructure and software assets as proxies for IT capabilities might not fully capture their multifaceted nature, overlooking the qualitative aspects crucial for audit outcomes. Furthermore, excluding external factors such as governmental regulations underscores the need for future research to explore the nuanced interplay between IT capabilities, internal control systems and regulatory environments, enriching our understanding of audit practices.

This study contributes to auditing literature by examining the interplay between IT capabilities and audit processes during the COVID-19 pandemic in Jordan. This study highlights the unexpected finding that IT capabilities have minimal impact on audit report lags and fees, opening new avenues for research on how pandemics and similar crises can reshape auditing practices and influence regulatory policies in an evolving economic environment.

The current chapter proposes a theoretical framework to assess the sustainability of economic growth in the Gulf Cooperation Council (GCC) States. The authors integrate insights from endogenous growth models and consider the unique socioeconomic characteristics of the GCC region to provide a comprehensive and tailored approach to understanding the determinants of economic growth and formulating effective policy measures to foster sustainable development and growth. This chapter highlights the environmental challenges faced by GCC; based on this, the authors suggested indicators to construct a theoretical framework (Economic Growth, Climatic Indicators, Energy Indicators, Social Indicators, and Economic Resources Indicators). The authors propose that policymakers and researchers in GCC States should take these factors into account when devising policies or conducting research aimed at fostering sustainable economic growth. Overall, this chapter presents significant insights for policymakers, researchers, and stakeholders involved in promoting the sustainable economic advancement of the GCC States.

Pedagogical classes within the general secondary education system in Russia have been practised for almost two centuries. They have been recognised as an effective teacher training method in complicated stages of national history and as a part of the vocational guidance of school students. Modern pedagogical classes, on the one hand, can be a significant element of the system of continuous teacher education. On the other hand, they contribute to the understanding of the meaning and content of the teacher's profession, and solve the problems of vocational guidance and professional identity. The purpose of pedagogical classes of the late 20th to early 21st century is to have students prepared for choosing a teaching profession and further study in teacher training institutions and universities.

The primary purpose of this research is to conceptualise and validate the comprehensive framework for effectively measuring and managing employee-based brand equity (EBBE) benefits. The study endeavours to integrate professional and socio-emotional facets of employees' into the proposed model, lending it a more holistic approach.

The study focusses on the banking sector in Kosovo, employing structural equation modelling to analyse data from a sample of 325 employees.

Both professional and socio-emotional perspectives significantly influenced brand knowledge, positively impacting EBBE benefits such as employee satisfaction, retention and positive word of mouth (WOM). These findings provide empirical support for the theoretical assumptions concerning the role of professional and socio-emotional perspectives in building EBBE.

Theoretically, this research could bridge marketing and organisational behaviour theories by highlighting employees' role in building brand equity. Moreover, it might expand the social identity theory within an organisational context, emphasising employees' identification with the brand as a crucial element.

The study offers practical implications for the banking industry and similar contexts, suggesting robust internal marketing strategies prioritising professional development and socio-emotional connectivity. Theoretically, this research could bridge marketing and organisational behaviour theories by highlighting employees' role in building brand equity. Moreover, it might expand the social identity theory within an organisational context, emphasising employees' identification with the brand as a crucial element.

The paper presents an original contribution to the field of brand equity research by proposing and validating a novel framework for EBBE that uniquely integrates both professional and socio-emotional dimensions of employees' experiences. This approach is particularly innovative within the context of the banking sector, offering new empirical insights.

Construction organisations cannot underestimate the improvement in public–private partnership (PPP) projects’ implementation. At the same time, construction organisations cannot overlook the risk arising from engaging in PPP construction projects. Hence, this study aims to establish the influence of risk resource management (RRM) in managing PPP risk in the construction industry in Ghana.

The researchers adopted qualitative and quantitative research methods to achieve the aim of the study, in which Delphi questions and a close-ended questionnaire were developed. A total of 650 construction specialists, including procurement officers, consultants, project managers, quantity surveyors, site engineers and planning officers were chosen using random and purposive sampling techniques. Recovered data were analysed using descriptive statistics and confirmatory factor analysis (CFA). The CFA maximum likelihood estimation extractor compresses 19 variables into 3 pattern matrices.

The results of the study revealed three factors that measure RRM in Ghana’s PPP construction industry, including financial resource management which was influenced by communicating the budget to project team members and project partners understanding the budget, and material resource management which was influenced by the provision of materials transportation and provision of delivery programs and labour resource management which was impacted by a commitment to pay social security and taxes and provision of good salaries, to address RRM in PPP construction organisations.

To incessantly improve the PPP risk management (RM) in construction through RRM, there should be a strong liaison between the universities, government agencies and the construction industry, and such collaboration will assist the industry to obtain first-hand information regarding the study findings and how they can be implemented to help the development of RM in the construction industry. This study is limited to Ghana and CFA and further study should explore structural equation model to determine the structure and measurement model of the risk resource variables.

The study may be valuable to industry stakeholders looking for new approaches to improve RM in their construction activities, particularly in PPP projects. Also, to assist reduce PPP risk, construction companies should use RRM in their organisations.

Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.

The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.

A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.

The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.

Agriculture commodity price forecasts have long been important for a variety of market players. The study we conducted aims to address this difficulty by examining the weekly wholesale price index of green grams in the Chinese market. The index covers a ten-year period, from January 1, 2010, to January 3, 2020, and has significant economic implications.

In order to address the nonlinear patterns present in the price time series, we investigate the nonlinear auto-regressive neural network as the forecast model. This modeling technique is able to combine a variety of basic nonlinear functions to approximate more complex nonlinear characteristics. Specifically, we examine prediction performance that corresponds to several configurations across data splitting ratios, hidden neuron and delay counts, and model estimation approaches.

Our model turns out to be rather simple and yields forecasts with good stability and accuracy. Relative root mean square errors throughout training, validation and testing are specifically 4.34, 4.71 and 3.98%, respectively. The results of benchmark research show that the neural network produces statistically considerably better performance when compared to other machine learning models and classic time-series econometric methods.

Utilizing our findings as independent technical price forecasts would be one use. Alternatively, policy research and fresh insights into price patterns might be achieved by combining them with other (basic) prediction outputs.

The manufacture of polymer composites with a lower environmental footprint requires incorporation of sustainably sourced components. In addition, the incorporation of novel components should not compromise the material properties. The purpose of this paper is to demonstrate the use of a synthetic amine functional toluidine acetaldehyde condensate (AFTAC) as a modifier for fiber-reinforced epoxy composites. One of the fiber components was sourced from agricultural byproducts, and glass fiber was used as the fiber component for comparison.

The AFTAC condensate was synthesized via an acid-catalyzed reaction between o-toluidine and acetaldehyde. To demonstrate its efficacy as a toughening agent for diglycidyl ether bisphenol A resin composites and for the comparison of reinforcing materials of interest, composites were fabricated using a natural fiber (mat stick) and a synthetic glass fiber as the reinforcing material. A matched metal die technique was used to fabricate the composites. Composites were prepared and their mechanical and thermal properties were evaluated.

The inclusion of AFTAC led to an improvement in the mechanical strengths of these composites without any significant deterioration of the thermal stability. It was also observed that the fracture strengths for mat stick fiber-reinforced composites were lower than that of glass fiber-reinforced composites.

To the best of the authors’ knowledge, the use of the AFTAC modifier as well as incorporation of mat stick fibers in epoxy composites has not been demonstrated previously.

For over 25 years, the United States Green Building Council (USGBC) has significantly influenced the US sustainable construction through its leadership in energy and environmental design (LEED) certification program. This study aims to delve into how Baton Rouge, Louisiana, fares in green building adoption relative to other US capital cities and regions.

The study leverages statistical and geospatial analyses of data sourced from the USGBC, among other databases. It scrutinizes Baton Rouge’s LEED criteria performance using the mean percent weighted criteria to pinpoint the LEED criteria most readily achieved. Moreover, unique metrics, such as the certified green building per capita (CGBC), were formulated to facilitate a comparative analysis of green building adoption across various regions.

Baton Rouge’s CGBC stands at 0.31% (C+), markedly trailing behind the frontrunner, Santa Fe, New Mexico, leading at 3.89% (A+) and in LEED building per capita too. Despite the notable concentration of certified green buildings (CGBs) within Baton Rouge, the city’s green building development appears to be in its infancy. Innovation and design was identified as the most attainable LEED benchmark in Baton Rouge. Additionally, socioeconomic factors, including education and income per capita, were associated with a mild to moderate positive correlation (0.25 = r = 0.36) with the adoption of green building practices across the capitals, while sociocultural infrastructure exhibited a strong positive correlation (r = 0.99).

This study is beneficial to policymakers, urban planners and developers for sustainable urban development and a reference point for subsequent postoccupancy evaluations of CGBs in Baton Rouge and beyond.

This study pioneers the comprehensive analysis of green building adoption rates and probable influencing factors in capital cities in the contiguous US using distinct metrics.