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This study explores the profound influence of social and cultural factors on the financial conduct of indigenous tribes and groups. Anchored in Vygotsky's sociocultural theory, the analysis delves into the intricate interplay between cultural elements, such as bricolage, and the immediate availability of financial resources, illuminating their collective impact on the tribes' financial behaviour. Typically residing in proximity, these communities exhibit homogeneity by forming groups exclusive to their clans, lacking access to conventional financial services and tangible assets that dissuade banks from extending loans. Crucially, the social capital embedded within the group dynamics, often referred to as the peer mechanism, emerges as a pivotal conduit for members to secure capital and bank credit. The synergy of bricolage, representing the adept use of available social capital, facilitates access to finance and credit. Despite the existence of social capital and financial literacy programmes, a stark reality persists – a significant proportion of indigenous people remain financially excluded. This chapter endeavours to scrutinise the ramifications of these factors on tribal financial behaviour, employing the Partial Least Squares Structural Equation Modelling (PLS-SEM) method. Proposing a paradigm shift in financial attitudes, the research underscores the imperative of fostering financial inclusion within indigenous tribes and communities.

The study aims to determine whether a relationship exists between the potential significance of corporate controversies for stakeholders and how organisations respond to them in their annual and sustainability reports.

This paper employs content analysis on annual and sustainability reports of 48 listed companies from the Refinitiv database. The logit regression was used to estimate the model.

The study revealed that the main factors increasing the probability of a controversial issue being addressed in a corporate report are the controversy’s potential significance, companies’ financial performance and lawsuits.

Our study has three major limitations. These are a relatively small sample of companies and reports, focusing on disclosures made in corporate reports and omitting other channels of communication, for example, social media, and a certain amount of subjectivity in the process of coding information.

Former studies show that corporations face a serious risk of their hypocritical strategies becoming too evident for stakeholder groups. Our findings suggest that the risk is already materialising and may undermine the idea of CSR and sustainability reporting.

Our research focuses on high-profile adverse incidents widely reported in the media, the omission of which from corporate reports seems to constitute a particular case of organised hypocrite. It also demonstrates that companies use an impression management strategy to defuse adverse publicity and that major controversies cause minor ones to be omitted from their reports.

This paper presents pyBibX, a Python library devised to conduct comprehensive bibliometric and scientometric analyses on raw data files sourced from Scopus, Web of Science and PubMed, seamlessly integrating state-of-the-art artificial intelligence (AI) capabilities into its core functionality.

The library executes a comprehensive exploratory data analysis (EDA), presenting outcomes via visually appealing graphical illustrations. Network capabilities have been deftly integrated, encompassing citation, collaboration and similarity analysis. Furthermore, the library incorporates AI capabilities, including embedding vectors, topic modeling, text summarization and other general natural language processing tasks, employing models such as sentence-BERT, BerTopic, BERT, chatGPT and PEGASUS.

As a demonstration, we have analyzed 184 documents associated with “multiple-criteria decision analysis” published between 1984 and 2023. The EDA emphasized a growing fascination with decision-making and fuzzy logic methodologies. Next, network analysis further accentuated the significance of central authors and intra-continental collaboration, identifying Canada and China as crucial collaboration hubs. Finally, AI analysis distinguished two primary topics and chatGPT’s preeminence in text summarization. It also proved to be an indispensable instrument for interpreting results, as our library enables researchers to pose inquiries to chatGPT regarding bibliometric outcomes. Even so, data homogeneity remains a daunting challenge due to database inconsistencies.

PyBibX is the first application integrating cutting-edge AI capabilities for analyzing scientific publications, enabling researchers to examine and interpret these outcomes more effectively. pyBibX is freely available at https://bit.ly/442wD5z.