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Article
Publication date: 5 July 2024

Sudhi Sharma, Vaibhav Aggarwal, Reepu and Gitanjali Kaur Mehta

This study aims to investigate into the dynamic connection between ESG scores and the volatility term structure for Indian companies listed BSE. The study divides the BSE-100…

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Abstract

Purpose

This study aims to investigate into the dynamic connection between ESG scores and the volatility term structure for Indian companies listed BSE. The study divides the BSE-100 listed companies into two panels based on their median ESG scores in 2022, creating high and low ESG scoring groups to capture volatility structure.

Design/methodology/approach

The study employs time-varying symmetric and asymmetric GARCH models and followed by continuous Wavelet to capture volatility structure and explore comparative resilience behavior.

Findings

The study found similar volatility patterns regardless of ESG scores, nudging doubt on the direct impact of ESG on volatility. Additionally, both high- and low-ESG-scored companies displayed high vulnerabilities during the pandemic, raising questions about the effectiveness of ESG frameworks in capturing risks. Finally, by examining the resilience behavior of ESG-scored companies during the pandemic, our study contributes to the evolving understanding of the intersection between ESG performance and crisis response.

Practical implications

The study carries vital implications for investors and policymakers. It highlights the urgent need to strengthen the ESG framework and scores to shield investors from short- and long-term volatilities and economic vulnerabilities.

Originality/value

To the best of the authors’ knowledge, this is the first study investigating the Indian market by examining the volatility structure and resilience behavior of high- and low-ESG-scored companies during the pandemic.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2024-0113

Details

International Journal of Social Economics, vol. 52 no. 3
Type: Research Article
ISSN: 0306-8293

Keywords

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Book part
Publication date: 6 March 2025

Ram B. Ramachandran and Chabi Gupta

Purpose: There has been a growing debate on whether generative AI can serve as the modern-day equivalent of white-collar knowledge workers. In a recent post, technology magnate…

Abstract

Purpose: There has been a growing debate on whether generative AI can serve as the modern-day equivalent of white-collar knowledge workers. In a recent post, technology magnate Bill Gates boldly proclaimed that ChatGPT would soon become the quintessential white-collar worker of tomorrow (Dean, 2023). This is indeed an exciting prospect, as generative AI advances at breakneck speed.

Need for the Study: This research delves upon the implications of such advancements for industries reliant on skilled employees. It raises questions about how these individuals will adjust their skillset going forward, given the proliferation of generative AI solutions poised to disrupt traditional roles previously occupied by humans.

Methodology: The study uses an exploratory framework to understand AI’s implications on job roles, productivity, and skill requirements. It introduces generative AI and its relevance, focusing on how it could transform white-collar jobs.

Findings: One thing seems clear: its impact on future employment opportunities. However, this technology still has limitations, potentially leading to unintended consequences. While capable of performing certain functions precisely and accurately, it cannot fully replace the reasoning abilities or cognitive flexibility innate in human workers tasked with knowledge-based work.

Practical Implications: The potential implications for workforce development, policy-making, and future research in AI and labor economics are highlighted. This will also help gain insights into the integration process, benefits, challenges, and the changing nature of white-collar work due to generative AI.

Details

Financial Landscape Transformation: Technological Disruptions
Type: Book
ISBN: 978-1-83753-751-8

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Book part
Publication date: 12 February 2025

Abstract

Details

Green Wealth: Navigating towards a Sustainable Future
Type: Book
ISBN: 978-1-83662-218-5

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