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把握发展脉络:并购中可持续金融的全面综述

Navigating the evolution: a comprehensive review of sustainable finance in mergers and acquisitions.

作者信息

Mondal Sabyasachi, Rakshit Debdas, Jee Kishan, Tiwari Satish Chandra

机构信息

Department of Commerce, The University of Burdwan, Bardhaman, West Bengal, India.

Brainware University, Kolkata, West Bengal, India.

出版信息

F1000Res. 2025 Mar 14;14:298. doi: 10.12688/f1000research.150207.1. eCollection 2025.

Abstract

BACKGROUND

The global shift in corporate philosophy from wealth maximization to share value creation has propelled sustainable finance into the forefront of research endeavours. Despite its significance, the realm of sustainable finance, especially in the context of mergers and acquisitions, remains relatively underexplored.

OBJECTIVE

This research intends to identify the gap by conducting a cutting-edge and expansive systematic review, unravelling the intricate layers of sustainable finance concerning mergers and acquisitions.

DATA SOURCE

The data source is Web of Science to start with, yielding 41 publications. A similar search on Scopus yielded 52 articles. Not surprisingly, the 41 publications discovered via the Web of Science search were also found in the Scopus results.

STUDY ELIGIBILITY CRITERIA

Papers on business, management, environmental studies, corporate finance, economics, and ethics are featured.

STUDY APPRAISAL AND SYNTHESIS METHODS

Employing advanced methodologies including machine learning tools, our research delves into domain specific influential papers, top-contributing journals, noteworthy authors, institutions, and nations. By dissecting the context and methodologies employed in scholarly works, we aim to instil a through overview of the current body of knowledge. our study categorizes the selected scholarly research into four distinct objectives, facilitating a nuanced understanding of the diverse perspectives within the field. Each stratum of papers is meticulously analysed and discussed, offering insights into key themes and patterns. To guide future research initiatives, we present a synthesis of pertinent research questions, exploring avenues such as the incorporation of innovative financial instruments like green bonds and artificial intelligence.

RESULTS

Since the Sustainable Development Goals were introduced in 2016, sustainable finance has become an increasingly important topic in merger and acquisition research. Research is progressing at a rapid pace in China and Australia, while emerging nations are falling behind. In addition, this study specifies the necessity of conducting a more comprehensive examination of the habits of company representatives regarding sustainable investments. This aspect has been neglected in earlier research. Additionally, because global M&As are becoming more common, research on cross-border M&As must take precedence over domestic ones. Finally, there is a gap in the current body of knowledge about greenwashing, green audits, and the use of AI in sustainable finance.

CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS

Machine learning and big data analytics may help scholars get a more thorough grasp of the historical and present significance of sustainability in M&A. New era researchers may advance the potential yet unexplored topics.

摘要

背景

企业理念从财富最大化向共享价值创造的全球转变,将可持续金融推到了研究工作的前沿。尽管其意义重大,但可持续金融领域,尤其是在并购背景下,仍相对未得到充分探索。

目的

本研究旨在通过进行前沿且广泛的系统综述来找出差距,揭示并购中可持续金融的复杂层面。

数据来源

数据来源首先是Web of Science,得到41篇出版物。在Scopus上进行类似搜索得到52篇文章。不出所料,通过Web of Science搜索发现的41篇出版物也出现在Scopus的结果中。

研究纳入标准

以商业、管理、环境研究、公司金融、经济学和伦理学方面的论文为特色。

研究评估与综合方法

采用包括机器学习工具在内的先进方法,我们的研究深入探究特定领域的有影响力论文、主要贡献期刊、知名作者、机构和国家。通过剖析学术著作中使用的背景和方法,我们旨在全面概述当前的知识体系。我们的研究将所选学术研究分为四个不同目标,便于对该领域内的不同观点有细致入微的理解。对每一层论文都进行了细致分析和讨论,揭示关键主题和模式。为指导未来的研究计划,我们对相关研究问题进行了综合,探索诸如纳入绿色债券和人工智能等创新金融工具等途径。

结果

自2016年引入可持续发展目标以来,可持续金融在并购研究中已成为一个日益重要的主题。中国和澳大利亚的研究进展迅速,而新兴国家则落后。此外,本研究明确指出有必要对公司代表在可持续投资方面的习惯进行更全面的考察。这一方面在早期研究中被忽视了。此外,由于全球并购越来越普遍,跨境并购研究必须优先于国内并购研究。最后,在当前关于漂绿、绿色审计以及人工智能在可持续金融中的应用的知识体系中存在差距。

关键发现的结论与启示

机器学习和大数据分析可能有助于学者更全面地理解可持续性在并购中的历史和当前意义。新时代的研究人员可以推进尚未探索的潜在主题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa07/12041844/d80de778f1a7/f1000research-14-164752-g0000.jpg

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