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Child labour abolition is one of the four essential human rights identified by the International Labour Organisation and sustainable development goals. Although public organisations and governments have implemented a variety of actions to control business activity and protect children’s rights, cases of child labour adoption continue to be documented. This paper aims to establish multinational companies’ disclosure procedures regarding child labour and to identify some potential determining factors.

A content analysis approach is used on sustainability reports from multinational companies throughout the world to assess the overall amount of disclosure concerning child labour adoption and to generate a child labour disclosure (CLD) score. In addition, to better understand this issue, an empirical investigation was conducted on a sample of 85 multinational companies to identify the factors that influence CLD.

The findings show that there is a low degree of disclosure on this issue throughout the world and that stakeholder engagement has a positive impact on disclosure levels. In contrast, the existence of a corporate social responsibility (CSR) committee and a CSR-based compensation policy has a negative influence on CLD.

The statistical results provide a unique viewpoint as they illustrate the amount of CLD using impression management theory, confirming the notion of negative event omission and text manipulation in developing the business image. These findings have important implications for literature development, as well as for managers, policymakers and stakeholder groups.

This study is motivated by the rising regulatory demand for new digital solutions enabling searchable and comparable sustainability corporate information. It aims at uncovering the antecedents of the technological major benefits highlighted by the ongoing scientific debate on the digitalization processes implemented by firms. Therefore, this paper focuses on the factors related to the emergence of digital accounting, reporting and disclosure of sustainability corporate information.

Following the Technology-Organization-Environment framework, the authors review and classify the factors identified by current academic literature that may enable or constraint the use of digital solutions for collecting, reporting and disclosing corporate non-financial information. A total of 86 sources were retrieved from Scopus and Web of Science and reviewed following a systematic approach.

Results show an increasing interest in the digitalization of corporate sustainability accounting and reporting and highlight some related drivers with a predominance of technological and environmental enablers (e.g. compatibility, stakeholders pressure) along with organizational constraints (e.g. need for technical and training programmes) influencing the ongoing adoption of new technologies for both internal and inter-organizational purposes.

The authors provide several research directions for enhancing the academic interest in corporate accounting digitalization.

This paper offers practical contributions to regulators and companies concerning the challenges they should face in applying new technologies for non-financial reporting purposes.

To the best of the authors’ knowledge, this is the first systematic literature review on the enablers and constraints of digitalization of sustainability accounting, reporting and disclosure.

Using AI to strengthen creativity and problem-solving capabilities of professionals involved in innovation management holds huge potential for improving organizational decision-making. However, there is a lack of research on the use of AI technologies by innovation managers. The study uses the theory of appropriation to explore how specific factors – agile leadership (AL), innovation orientation (IO) and individual creativity (IC) – impact innovation managers' use of generative AI tools, such as ChatGPT (CGA).

The research model is tested through a large-scale survey of 222 Italian innovation managers. Data have been analyzed using structural equation modeling following a two-step approach. First, the measurement model was assessed to ensure the constructs reliability. Subsequently, the structural model was analyzed to draw the conclusions on theorized model relationships and their statistical significance.

The research findings reveal positive associations between IO and IC with CGA, demonstrating that innovation managers who exhibit strong innovation orientations and higher Individual Creativity are more likely to adopt and personalize ChatGPT. However, the study did not confirm a significant association between AL and CGA.

Our findings have important implications for organizations seeking to maximize the potential of generative AI in innovation management. Understanding the factors that drive the adoption and customization of generative AI tools can inform strategies for better integration into the innovation process, thereby leading to enhanced innovation outcomes and improved decision-making processes.