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In today’s competitive business landscape, organizations are increasingly recognizing the strategic advantage of implementing sustainable practices to gain a competitive edge. This study aims to investigate the effect of green artificial intelligence (AI) on achieving a green competitive advantage, examining the mediating roles of green organizational learning, green product innovation and green process innovation. Additionally, the research explores the moderating role of perceived green climate in the relationship between green AI and these mediating factors.

This research examined companies in Isfahan, Iran, that have varying levels of artificial intelligence adoption within their business processes. The target population consisted of 148 senior managers from these companies. This study uses structural equation modeling to examine the proposed model.

Green AI positively impacted green organizational learning and green process innovation but not green product innovation. In addition, the results showed that green organizational learning, green product innovation and green process innovation had positive effects on green competitive advantage. Finally, the results showed that the perceived green climate did not play a moderating role in the relationship between green AI and these mediating factors.

Organizations should prioritize green AI initiatives, foster a culture of green learning and invest in green innovation to achieve sustainable growth and outpace competitors in the environmentally conscious marketplace.

This study positions itself at the forefront of research on green AI and green competitive advantage. It offers a unique framework by examining the combined effects of green AI, green learning and both product and process innovation on achieving a sustainable competitive advantage.

This paper aims to explore the integration of technology platforms of Fintech service providers in Bangladesh and its outcome on the users’ acceptance and intention to use it. It has considered Bangla QR, a Bangladesh-specific unified payment platform, for the said purpose.

The study investigates the usage and acceptance of Bangla QR’s financial service application by collecting data on user demographics and usage patterns. The data have been collected from Bangla QR users who have firsthand experience using a unified payment system in Bangladesh. Structural equation modeling (SEM) has been used to analyze the data and investigate the relationships between latent constructs, such as Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Hedonic Motivation (HM) and Behavioral Intention (BI).

Results reveal that the experience of users from earlier platforms and their expectation of improved technologies have a positive and significant relationship with the behavior intention of users regarding the acceptance of a fresh fintech platform. Specifically, PE, EE and FC have a significant effect on HM. Moreover, HM mediates the relationship between PE and BI, EE and BI and FC and BI. Startlingly, SI does not affect HM and BI.

The study posits that users of Bangla QR are embracing the unified payment scheme willingly. Experience with new technology in the financial aspects has given them the confidence to continue this in the future. However, social awareness about the intrinsic worth of unified payment should be raised by financial institutions and regulators in Bangladesh. The lack of Bangla QR’s accessibility limits the number of respondents, and its newness hinders the researchers from focusing on price value and habit constituting BI.

First, this is the first paper to explore the fintech users’ intention to continue a unified payment platform in Bangladesh. Second, it uses the UTAUT2 model with modifications as per the requirement of the study. Finally, this study theorizes specific reasons to develop the overall scenario of a unified payment system in the future in Bangladesh.

The purpose of this study is to examine how users’ intention to adopt online banking is influenced by perceived trust (PT), awareness (AWE) and social influence (SI) and to assess whether customer relationship management (CRM) moderates the impact of these factors on adoption intentions.

Data were collected from 565 respondents in Pakistan using a stratified sampling technique. The analysis was conducted using Partial Least Squares Structural Equation Modeling with SmartPLS-4 to examine the proposed relationships.

This study’s findings reveal that PT, AWE and SI do not directly influence users’ intention to adopt online banking. Trust impacts intention through perceived ease of use, while AWE and SI affect intention via both perceived usefulness and ease of use. CRM negatively moderates SI but positively moderates the effects of PT and AWE on users’ intention.

This study explores the novel role of CRM as a moderator, offering fresh insights into how CRM enhances the impact of PT, AWE and SI on online banking adoption.

This study aims to test the empirical Islamic bank customer loyalty model with the perspective of mosques as customers.

The type of research used is quantitative to collect data from mosque customers; 93 questionnaires were analyzed using partial least square-structural equation modeling.

This research found a significant relationship between service quality and perceived value, service quality and brand image, perceived value and customer satisfaction, brand image and customer loyalty and customer satisfaction with brand image.

First, this study only collects data from certain organizations or communities so that further research can develop the model by adding several other communities or organizations. Second, this research does not include several other important variables that influence customer loyalty, such as product innovation and company capabilities.

Islamic bank customer loyalty models have been widely explored from the perspective of individual customers only. This research offers new attributes that influence customer loyalty models in the context of organizations or communities, namely, mosques.

This paper aims to analyze the impact of COVID-19 on foreign direct investment (FDI) in Arab economies.

This study uses the pooled ordinary least squares estimator, alongside panel static techniques, two-stage least squares estimation and the system generalized method of moments estimator, to ensure robust results. The analysis is based on a panel data set from 18 Arab countries over the period 2017–2022.

The study reveals a significant negative relationship between COVID-19 and FDI inflows and outflows. Higher infection rates lead to substantial reductions in FDI activity, highlighting the pandemic’s disruptive effect on the region’s investment landscape. Government responses, including lockdown measures and fiscal stimulus, are crucial in shaping FDI dynamics, with varying impacts across different sectors and economic contexts.

The findings provide valuable insights for policymakers, emphasizing the need for effective pandemic preparedness, strategic economic growth initiatives, exchange rate management and labor market reforms. These measures are essential to foster FDI and ensure economic stability in Arab economies.

This study is the first to examine the impact of COVID-19 on FDI in Arab economies, addressing a significant research gap. It contributes to the broader discourse on the pandemic’s economic effects by offering comprehensive insights into how the crisis has affected FDI flows. By incorporating a range of COVID-19 pandemic indicators, analyzing government response impacts and exploring sectoral and economic heterogeneity, this research enriches our understanding of the multifaceted financial implications of the pandemic.

This paper examines the impact of green human resource management (GHRM) practices on employees’ pro-environmental behavior in Pakistan’s hospitality industry. It attempts to identify the critical success factors involved in promoting GHRM and pro-environmental behaviors at the workplace using Interpretive Structural Modeling (ISM) and cross-impact matrix multiplication applied to classification (MICMAC) approaches. Later, based on the ability-motivation-opportunity (AMO) model, the study also categorizes the identified critical factors into three categories: ability, motivation and opportunity.

The ISM approach was applied to determine the contextual relationship among the identified critical success factors responsible for promoting GHRM. MICMAC, a structural technique to analyze and validate the ISM-based model, was used to determine the autonomous, dependent, linkage and independent factors based on expert opinions and judgments. The goal was to determine the role of GHRM in transforming the pro-environmental behavior of employees.

The study’s findings show that the proper integration of effective GHRM practices significantly impacts pro-environmental employee behavior. The hierarchical model introduces innovation in the field of GHRM because ISM-based hierarchical models are flexible enough to include or exclude practices according to the green organizational objectives in the hospitality industry within the context of Pakistan. The results offer a comprehensive illustration of the importance of GHRM practices in facilitating, encouraging and promoting employees to take green initiatives and achieve business sustainability.

The study utilizes the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) technique to identify key success criteria for GHRM, while the innovative approaches of ISM and MICMAC techniques were used to investigate employee pro-environmental behaviors. This novel method gives GHRM research an analytical direction by providing an organized framework for evaluating the impact of GHRM initiatives on environmental outcomes. Additionally, by focusing on developed economies rather than emerging ones, our study within Pakistan’s hospitality sector fills a knowledge vacuum on the dynamics of GHRM in a developing nation.

This study highlights the significance of managers in the hospitality sector serving as role models for implementing GHRM practices to encourage pro environmental behavior among employees. Prioritizing green structural capital, establishing standard environmentally friendly criteria for hiring and evaluating prospective employees and initiating green projects to promote a psychologically green environment are some of the key recommendations. Improving environmental performance, employee satisfaction and loyalty in the hotel industry requires constant communication, training and employee participation in sustainability decision-making.

The GHRM practices have been extensively discussed by academics and researchers. However, there is a notable absence of discussion on the key factors that play a role in transforming employees’ attitudes and behaviors.

This study aims to assess the impact of determinants on the effectiveness of internal audit (IA) within the banking industry of Bangladesh.

The data was obtained through 152 survey questionnaires from a total of 43 privately owned and six state-owned commercial banks in Bangladesh. The analysis was conducted using structural equation modeling.

The findings demonstrate that the independence of internal auditors and the quality of IA substantially impact enhancing the efficiency of IA. On the other hand, the competence of internal auditors and management support in IA functions do not significantly impact the effectiveness of IA.

The study’s findings may have significant policy implications for the government, regulators, internal auditors, management committees and other stakeholders in establishing programmes to enhance the efficacy of IA as a component of banking audit management reforms.

This study makes three distinct contributions to the existing literature. Firstly, previous literature focused on the determinants affecting the external audit efficiency of the public companies and banking sectors in Bangladesh (Hasan, 2018; M. M. U. Reza, 2021). In this study, the author enhances the research by presenting empirical findings on the IA effectiveness of banks. Secondly, the author expands the research by incorporating both private and state-owned commercial banks as samples. Thirdly, the study is unique given that it investigates the effectiveness of IA in response to the recent financial scandals in the banking industry of Bangladesh (The Daily Star, 2023).