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This study aimed to examine the role of green human resource management on environmental performance at Islamic universities, with the mediating effect of green cultural festivals and the moderating role of individual green values.

The research employed random sampling techniques by selecting a sample of 192 students from various Islamic universities in Indonesia. The participants were selected through an online survey. In addition, data analysis was done using the structural equation modelling-partial least squares (SEM-PLS) technique with the SmartPLS 3.0.

Implementing green human resource management has become a crucial factor in enhancing the environmental performance of Islamic universities. Moreover, green cultural festivals function as an intermediary variable. At the same time, individual green values exhibit a moderating variable that can enhance the influence between green human resource management and environmental performance.

Implementing an effective green human resource management strategy enhances environmental performance. Green human resource management has assisted universities in creating a generation of graduates with a solid commitment to ecological sustainability and raised awareness of the significance of conserving the environment. As a result, this commitment equips students to become agents of change in society upon graduation. Furthermore, campuses need to integrate environmental curriculum components into all study programs, as students need to understand the significant impact of environmental stewardship from both Islamic and scientific perspectives.

This research provides a novel perspective on how Islamic universities are exceptionally well-equipped to create environmental awareness and values that students can practically apply post-graduation using green cultural festivals, which are regularly held. This study is the first to introduce the concept of green cultural festivals in universities utilising the basis of combining green culture with cultural festivals with the theoretical background of resource-based theory.

This study investigated how green innovation (GINO), using practices like green marketing orientation (GMO), manufacturing (GMfP), investment (GINV) and HRM, improves environmental performance (EnP) in Ethiopian leather, textile and garment businesses.

The study used a cross-sectional, quantitative design. It surveyed 201 participants, selected via stratified random sampling. Researchers examined the hypothesis using PLS-SEM.

Our findings showed that green practices, especially GMP, GMO, GHRM, GINV and GINO, greatly boost firms’ environmental performance. GMP, GMO and GINV had a strong synergy on green innovation. GHRM had no significant effect. Except for GHRM, results showed that green innovation helps most green practices. It links them to better environmental performance.

For managers and policymakers working in the leather, textile and apparel industries in Ethiopia, this report provides insightful information. Strategic planning that supports and prioritizes the adoption of green practices is shown to be essential. Such activities are expected to improve corporate competitiveness and green innovation, ultimately resulting in ecologically sustainable performance.

Unique findings illuminate emerging nations’ leather, textile and apparel industries. This pioneering study reveals critical links that were previously unexplored. Its relevance extends across developing economies, offering fresh insights into these interconnected sectors.

As a little research has been conducted to understand the factors influencing users’ intentions to adopt blockchain-based telemedicine (BBT), it is important to investigate BBT acceptance as incorporation of blockchain technology can solve telemedicine-related issues. Accordingly, this study aims to investigate the factors influencing behavioral intentions (BI) to adopt BBT.

An integrated model comprising the constructs taken from technology–organization–environment framework, technology acceptance model, unified theory of acceptance and use of technology and theory of planned behavior based on their relevance to the context and the objectives of the study has been used for this research. A quantitative approach has been used to test the hypotheses, for which the data was collected from 324 respondents through a self-administered questionnaire. Partial least squares structural equation modeling has been used to test the hypotheses.

The results of the study show that relative advantage, perceived usefulness, trust and perceived ease of use have a significant impact on BI to adopt BBT, whereas regulatory support, subjective norms and facilitating conditions do not have any significant impact on the same.

As the concept of BCT in Pakistan is at its nascent stage and literature regarding this technology’s adoption is also limited, researchers and scholars can apply it to several other fields in Pakistan. For example, this study can be extended to explore the factors influencing blockchain adoption in areas such as education, logistics, transportation, finances and management. This research only considers the direct effects of constructs on BI to adopt BBT and does not consider any mediation and moderations constructs. Future researchers can also study the influence of mediation and moderation constructs on BI to adopt BCT.

Although studies on the acceptance of telemedicine exist, there is a gap concerning the acceptance of BBT, which the current study helps to bridge. From a practical standpoint, the current study makes a highly valuable contribution toward understanding acceptance factors for BBT projects, leading to help policymakers devise policies to promote telemedicine.

Artificial intelligence (AI) use is on the rise and evolving fast, which expectedly is set to transform the way we carry certain processes in accounting. This study aims to examine the use of AI in enhancing accounting efficiency in terms of AI adoption, employee competence, data quality and organizational readiness.

This study gathered data from 192 participants working in the field of accounting in Jordan to look into these factors and how they influence the efficiency of accounting processes. The research hypotheses were tested using partial least squares (PLS)-structural equation modeling.

The outcomes of this study documented that a high level of AI adoption, better data quality and competent employees can achieve better accounting efficiency. The PLS analysis also showed that accounting efficiency in Jordan could be enhanced with increased AI adoption level, mainly when organizational readiness elements such as sufficient infrastructure and positive organizational cultures are in place.

In the realm of emerging markets, this study takes a leading position as the researcher recognizes the vital importance of AI in increasing accounting efficiency across different entities. The outcomes of this study highlight the importance of aligning AI initiatives with broader organizational development strategies to fully gain the advantages of AI in accounting.