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The discussion about using Chat Generative Pre-Trained Transformer (ChatGPT) by teachers is making notable progress on a daily basis. This research examines the teachers' adoption intention to adopt ChatGPT by focusing on perceived trust and perceived risk. The study seeks to elucidate the impact of these two factors on teachers' adoption intentions towards ChatGPT.

This study was exclusively conducted at private higher educational institutions in Gujarat, India. Data collection was done through a cross-sectional survey design. The proposed conceptual model was examined with the help of structural equation modelling (SEM).

The outcome of the study confirms the significant contribution of perceived usefulness, perceived ease of use, perceived trust, perceived intelligence, perceived anthropomorphism and social influence to teachers' intention to adopt ChatGPT. The findings of the study show that perceived risk exerts a negative moderating effect between perceived usefulness and adoption intention as well as between perceived trust and adoption intention.

This study fills the knowledge gap about teachers’ adoption of ChatGPT at private higher education institutions, thus contributing to the existing literature. Specifically, the distinctive role of key variables like perceived risk and perceived trust helps increase the existing body of knowledge.

Several practical implications are presented on the basis of the conclusions from the outcome of the study that would help increase teachers’ adoption intention of ChatGPT in higher education institutions. These implications include recommendations to promote the integration of ChatGPT in educational set-ups to help teachers leverage its potential benefits into their teaching practices.

This research study goes deeper into the subject than previous research, which mainly focused on the possible advantages and downsides of ChatGPT applications in the field of education. It makes a substantial contribution to our understanding of ChatGPT adoption among teachers for educational purposes by investigating through the lens of perceived risk and perceived trust. The study offers fresh understandings that were previously ignored and brings new perspectives to the body of literature.

This paper presents a conceptual framework based on an extensive literature review. The aim of this study is to deepen understanding of the relationship between carbon performance and the financial market by applying qualitative research approaches.

The investigation has identified 372 articles sourced from Scopus databases, subjecting the bibliographic data to a comprehensive qualitative–quantitative analysis. The research uses established protocols for a structured literature review, adhering to PRISMA guidelines, machine learning-based structural topic modelling using Python and bibliometric citation analysis.

The results identified the leading academic authors, institutions and countries concerning carbon performance and financial markets literature. Quantitative studies dominate this research theme. The study has identified six knowledge clusters using topic modelling related to environmental reporting; price drivers of carbon markets; environmental policy and capital markets; financial development and carbon emissions; carbon risk and financial markets; and environmental performance and firm value. The results of the study also present the opportunities associated with carbon performance and the financial market and propose future research agendas on research through theory, characteristics, context and methodology.

The results of the study offer insights to practitioners, researchers and academicians regarding scientific development, intricate relationships and the complexities involved in the intersection of carbon performance and financial markets. For policymakers, a better understanding of carbon performance and financial markets will contribute to designing policies to set up priorities for countering carbon emissions.

The study highlights the critical areas that require attention to limit greenhouse gas emissions and promote decarbonisation effectively. Policymakers can leverage these insights to develop targeted and evidence-based policies that facilitate the transition to a more sustainable and low-carbon economy.

The study initially attempts to discuss the research stream on carbon performance and financial markets literature from a systematic literature review.

Recently there has been a surge in interest about the use of artificial intelligence in organisations with art galleries introducing new technological innovations that coincide with the digitalisation revolution. Virtual and immersive environments that are supported by social media and digital platforms are significantly changing customer experiences at art galleries. This is internationalising and making art gallery experiences more accessible thereby fostering the competitive advantage of art galleries.

Art gallery customers, stakeholders and managers are appreciating the use of artificial intelligence with resulting higher satisfaction rates. Building on competency and transformational entrepreneurship theory international art gallery managers were interviewed to understand the role of artificial intelligence in their organisations and the impact of internationalisation.

The data analysis revealed that the internationalisation of art galleries enabled artificial intelligence to transform in person and online visitor experience, work and marketing, and future art gallery development ideas. Results show that artificial intelligence is opening up new transformations derived from entrepreneurial behaviours.

Key managerial implications are that art gallery managers need to utilise their international networks in order to learn about artificial intelligence and other new technological innovation. Theoretical implications are that existing theory can be adapted to an art gallery and artificial intelligence context. Limitations and future research suggestions focus on the need to focus more on art galleries as cultural entities that are more likely to utilise new technology innovation such as artificial intelligence.

The concept of lean and ISO 14001 as a combined approach is an evolving strategy for streamlining operational processes and attaining environmental sustainability in the manufacturing context. This paper explores the critical success factors (CSFs) for a combined lean and ISO 14001 implementation in the manufacturing industry for achieving the operational and environmental benefits.

A systematic literature review (SLR) based on Scopus and Web of Science databases is conducted to present peer-reviewed articles on the CSFs for lean and ISO 14001 implementation in manufacturing operations. This article applies the CSF theory to classify the CSFs for a joint lean and ISO 14001 adoption.

Numerous CSFs are synthesised from the SLR across seven theoretical contexts of industry, competitive strategy, managerial position, environmental, temporal, internal/external, monitoring and building/adapting factors for a combined lean and ISO14001 implementation.

Numerous CSFs are synthesised from the SLR across seven theoretical contexts of strategic direction, competitive strategy, leadership and management, environmental, temporal, internal/external, monitoring and continuous process improvement factors for a combined lean and ISO 14001 implementation.

This paper contributes to academic scholarship by providing a theoretical perspective through classification of CSFs for a combined lean and ISO 14001 implementation to achieve operational and environmental performance. This paper also contributes to practitioners and policymakers who can use the emergent theoretical framework for application in practice for a more efficient and effective deployment of both strategies in the manufacturing industry.

To the best of author's knowledge, this study is the first to propose a theoretical framework of CSFs for a combined lean and ISO 14001 implementation based on the CSF theory and SLR findings in the manufacturing industry.