Search results

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 study aims to adopt a systematic review approach to examine the existing literature on law and LLMs.It involves analyzing and synthesizing relevant research papers, reports and scholarly articles that discuss the use of LLMs in the legal domain. The review encompasses various aspects, including an analysis of LLMs, legal natural language processing (NLP), model tuning techniques, data processing strategies and frameworks for addressing the challenges associated with legal question-and-answer (Q&A) systems. Additionally, the study explores potential applications and services that can benefit from the integration of LLMs in the field of intelligent justice.

This paper surveys the state-of-the-art research on law LLMs and their application in the field of intelligent justice. The study aims to identify the challenges associated with developing Q&A systems based on LLMs and explores potential directions for future research and development. The ultimate goal is to contribute to the advancement of intelligent justice by effectively leveraging LLMs.

To effectively apply a law LLM, systematic research on LLM, legal NLP and model adjustment technology is required.

This study contributes to the field of intelligent justice by providing a comprehensive review of the current state of research on law LLMs.

This study aims to examine the problems of the concession system that Macao has long-term adopted to regulate its gaming industry and discuss alternatives.

Theoretical reflection was used to provide qualitatively different insights about governmental supervision of the gaming industry.

Two options for reform are proposed: (1) replace the concession system with a licensing system that does not restrict the number of concessionaires or the period of concession or (2) adopt a modified form of the concession system that changes the number of concessionaires, period of concessions and methods for selecting concessionaires.

This study’s results have implications for the Macao government and other gaming jurisdictions in Asia.

This study provides a comprehensive examination of the concession system for governmental supervision of the gaming industry.

After completion of the case study, the students would be able to comprehend the crisis at hand for Milkbasket, why did it resist Reliance’s takeover in the first place, then to evaluate the pros-cons and future prospects for the organization post-acquisition; to evaluate from an ethical standpoint the process of mergers and acquisitions using ethical frameworks to understand how, when, to whom and through what processes do mergers and acquisitions qualify the test of being ethical; and to analyse different hostile takeovers, especially through tender offers, proxy contests and toehold bidding strategy in this case.

Founded in 2015, Milkbasket was a micro-delivery start-up based in Gurugram (near New Delhi), India. Milkbasket would let its subscribers order till midnight and deliver groceries, milk and other everyday essentials to its subscribers before 7 a.m. next day. It had burnt a lot of cash and was facing difficulty in getting investors; as such they were engaged in discussions with many companies. Two of them – Reliance Retail Venture Limited and BigBasket – were not accepting the proposed valuation, but Milkbasket got term sheets from other two companies.

This case study can be used for graduate courses on strategic management, business ethics and corporate governance. This case study can also be used in corporate finance course to highlight the importance of making ethical/responsible judgements to protect stakeholder interests.

Teaching notes are available for educators only.

CSS 3: Entrepreneurship.

This chapter examines the concepts of race and racism, critically reviewing their historical and contemporary applications in everyday life as well as in academic and policy debates. Racism has been extensively researched, with various theories and conceptualisations developed across social science. However, there is a great deal of disagreement regarding its nature, contemporary significance and empirical validation. This chapter examines these and attempts to synthesise some of the common definitions of racism provided in the literature. It explores related concepts and underlying themes pertaining to expressions of race and racism. Furthermore, it unpacks current knowledge about racial issues and discusses recent advances in the conceptual understanding of various forms of racism. It also elucidates the social, political and analytical applications of racism as a concept and the significance of racism in contemporary societies. The chapter concludes by highlighting how racism is a dynamic phenomenon, continuously evolving with the social, political and technological transformations in contemporary societies.

The purpose of this study is to develop a method to assess social performance. Traditionally, environment, social and governance (ESG) rating providers use subjectively weighted arithmetic averages to combine a set of social performance (SP) indicators into one single rating. To overcome this problem, this study investigates the preconditions for a new methodology for rating the SP component of the ESG by applying machine learning (ML) and artificial intelligence (AI) anchored to social controversies.

This study proposes the use of a data-driven rating methodology that derives the relative importance of SP features from their contribution to the prediction of social controversies. The authors use the proposed methodology to solve the weighting problem with overall ESG ratings and further investigate whether prediction is possible.

The authors find that ML models are able to predict controversies with high predictive performance and validity. The findings indicate that the weighting problem with the ESG ratings can be addressed with a data-driven approach. The decisive prerequisite, however, for the proposed rating methodology is that social controversies are predicted by a broad set of SP indicators. The results also suggest that predictively valid ratings can be developed with this ML-based AI method.

This study offers practical solutions to ESG rating problems that have implications for investors, ESG raters and socially responsible investments.

The proposed ML-based AI method can help to achieve better ESG ratings, which will in turn help to improve SP, which has implications for organizations and societies through sustainable development.

To the best of the authors’ knowledge, this research is one of the first studies that offers a unique method to address the ESG rating problem and improve sustainability by focusing on SP indicators.