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Introduction: This chapter is intended to link the embracing strategy of ‘socially responsible investment’ with the apparent cause of economic destruction ‘financial crimes’. Today’s financial world is not always associated with ethics and morality, but it does not mean rising investments cause rising financial crimes. Socially responsible investing (SRI) has been rising, and many of today’s investors are interested in tracking ethically sound companies. Investors find a great way to invest around many investment opportunities, while socially responsible investors work with little social cause. This increasing literacy over SRI notably helps to reduce investments in unethical grounds which in turn reduces financial crimes.

Design/methodology: This work is premised on desk research. Conceptual and documentary methods were used in the study. The tertiary data source has been used in the study to develop a template describing the working of SRI in fixing financial crimes.

Findings: Findings of this study detail: a breakdown of industries that comes under SRI, channels of financial crimes, impact of SRI on financial crimes, and design an action plan for more effective environmental, social, and governance (ESG)-based investments to fix problems of financial crimes in the Indian economy.

Practical implications: The model of SRI has unfolded these days. While the purpose of these funds differs, they generally swear off the weapons industry and avoid ‘sin stocks’. In-depth analysis of this study area enables building quality investment strategy among investors and thereby helps to combat financial crimes.

Grounded in the stakeholder theory and signaling theory, this study aims to broaden the research agenda on environmental, social and governance (ESG) investing by uncovering public sentiments and key themes using Twitter data spanning from 2009 to 2022.

Using various machine learning models for text tonality analysis and topic modeling, this research scrutinizes 1,842,985 Twitter texts to extract prevalent ESG investing trends and gauge their sentiment.

Gibbs Sampling Dirichlet Multinomial Mixture emerges as the optimal topic modeling method, unveiling significant topics such as “Physical risk of climate change,” “Employee Health, Safety and well-being” and “Water management and Scarcity.” RoBERTa, an attention-based model, outperforms other machine learning models in sentiment analysis, revealing a predominantly positive shift in public sentiment toward ESG investing over the past five years.

This study establishes a framework for sentiment analysis and topic modeling on alternative data, offering a foundation for future research. Prospective studies can enhance insights by incorporating data from additional social media platforms like LinkedIn and Facebook.

Leveraging unstructured data on ESG from platforms like Twitter provides a novel avenue to capture company-related information, supplementing traditional self-reported sustainability disclosures. This approach opens new possibilities for understanding a company’s ESG standing.

By shedding light on public perceptions of ESG investing, this research uncovers influential factors that often elude traditional corporate reporting. The findings empower both investors and the general public, aiding managers in refining ESG and management strategies.

This study marks a groundbreaking contribution to scholarly exploration, to the best of the authors’ knowledge, by being the first to analyze unstructured Twitter data in the context of ESG investing, offering unique insights and advancing the understanding of this emerging field.

The purpose of this study is to explore the necessity for developing Islamic sustainable and responsible investment (i-SRI) criteria based on environmental, social and governance issues.

To address the above objective, this study adopted a qualitative method via content document analysis and interviews with experts.

Based on the analysis, this study discovered five primary aspects that lead to the necessity for developing i-SRI criteria. First, Malaysia has yet to develop i-SRI criteria. Second, the absence of i-SRI criteria will eventually lead to Shariah issues. Third, any Islamic financial instrument is bound to encounter numerous issues and challenges, thereby making it difficult to be marketed globally if it does not have a proper and standardized framework. Fourth, the establishment of i-SRI criteria can serve as a key reference point for the players in the industry, including investors, policymakers and other parties. Finally, the development of i-SRI criteria can play a vital role in enhancing the current Islamic capital market products offering in Malaysia.

There are several implications identified in this study. First, continuous research on the i-SRI criteria can offer numerous benefits to the regulatory bodies and policymakers who can use the findings in their decision-making process. Second, in terms of investors, the results can help them to make better investment choices by referring to the i-SRI criteria. Third, this study will be valuable to the academicians in terms of opportunity to explore a new research area, i.e. the i-SRI criteria, besides adding to the extant literature on this topic which is still scant currently.

This study discovered five primary aspects that lead to the necessity for developing i-SRI criteria.

The purpose of this study is to evaluate the performance of mutual funds during the COVID-19 pandemic with environmental, social and governance (ESG) criteria. The main research question is whether mutual fund performance differs with respect to the level of the mutual fund’s ESG score.

The data set contains global fund data, and mutual fund performance is analyzed using two types of data envelopment analysis (DEA) models: the DEA portfolio index (DPEI) and the range direction measure (RDM) DEA. Propensity score matching and logistic regression are also applied.

The results reveal that: nonequity mutual funds present significantly higher performance compared to the performance of equity mutual funds; mutual funds with high ESG scores are associated with significantly higher performance compared to those with low to medium ESG scores; funds with high ESG scores experience higher performance irrespective of their type; and efficiency scores derived from the RDM DEA are significantly higher than those derived from the DPEI model.

Investors, fund managers and market participants can benefit from the findings of this study and improve their investment decision-making process, including more sustainable funds in their portfolios. Regulators and policymakers should further promote or even require the inclusion of more sustainable investments in the financial products offered by institutional investors. The main limitation of the study is related to data availability regarding the ESG score of mutual funds.

To the best of the authors’ knowledge, this is the first study that provides robust evidence in support of a positive association between ESG scores and mutual fund performance during the pandemic-induced crisis applying a DEA methodology.

The main goal of this paper is better understand the risk/return trade-off of investing in socially responsible investment funds (SRIF) and green investment funds (GIF).

To achieve our aim a green investment fund portfolio, a socially responsible investment portfolio and a conventional fund (CF) portfolio from the United States of America (USA) were selected to compare the efficiency of these three different portfolios, by using Value-Based Data Envelopment Analysis (DEA) methodology.

The results point out that SRIF and GIF are more efficient than CF. For five years, the CFs have not outperformed the GIF.

The results suggest that there is a growing awareness on the part of investors that sustainable companies are the companies that will allow a better quality of life and a more sustainable environment. It seems that somehow managers and investors are aware that the market will compensate them for thinking about a cleaner and more equitable world.

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.

This study investigates how the initiatives and controversies related to environmental, social and governance (ESG) explain firm efficiency.

Firstly, this study applies data envelopment analysis with the epsilon-based measure to estimate the firm efficiency of 80 companies in the Chinese energy sector in 2022. This approach accounts for the diversity and relative importance of inputs and outputs from a multidimensional perspective. Secondly, this study regresses the variables of ESG initiatives and controversies on the estimated firm efficiency scores through a generalised additive model, which can capture nonlinear patterns.

This study finds that a) the samples have i) about 49% room for improvement in efficiently optimising their resources and business outcomes and ii) the highest scores in governance initiatives, followed by social initiative. b) 69% of them have controversy scores that are greater than the average value. c) A cluster analysis indicates that companies with higher social initiatives have higher firm efficiency than their counterparts. d) ESG initiatives and controversies are nonlinearly related to firm efficiency.

The findings have practical implications for policy makers and managers who prioritise ESG, particularly regarding (i) the need to examine firm performance from a multidimensional perspective, that is, to measure multiple inputs and outputs simultaneously, (ii) the nonlinearity of the nexus between ESG and efficiency in graphical forms, and (iii) the need to balance ESG initiatives and address ESG controversies.

This study integrates statistical approaches in examining and ensuring sustainable growth and efficiency within the Chinese energy sector and beyond.

The purpose of the paper is twofold. Firstly, this study aims to investigate the factors influencing stakeholders’ intention to invest in Shariah-compliant social impact bonds (SC SIBs) in Malaysia. Secondly, this study compares the differences in the perception of different stakeholders on the importance of the factors.

Using the extended theory of planned behaviour, the study undertakes a questionnaire survey on licensed capital market investors and individuals involved in the development of the financial market (developers). A total of 260 complete and valid responses were obtained from the survey. Multiple regression and Mann–Whitney tests were carried out to achieve the two objectives, respectively.

The results reveal that attitude (β = 0.447, p < 0.01), subjective norm (SN) (β = 0.255, p < 0.01) and moral norm (MN) (β = 0.163, p < 0.01) are significantly positive predictors of intention to invest in SC SIBs. In terms of the differences in the perceptions of the two parties, the results show that the factors have more effect towards developers than investors.

The empirical evidence from this study on the factors that influence stakeholders’ participation in SC SIBs is useful to the policymakers and interested parties in taking the next steps to develop, implement and promote SC SIBs to stakeholders in Malaysia. Fund managers can use the study’s insights to promote positive attitudes, SNs and MNs towards SC SIBs, especially targeting developers who are more influenced by these factors. More importantly, the results indicate a need for different strategies to influence the stakeholder investment behaviour of SC SIB in Malaysia to ensure that it is sustainable and viable in the long run.

After almost 10 years, people wonder if green finance has been able to attain its objectives in terms of controlling climate change. Persistent global warming and climate deregulation manifested by melting glaciers, droughts and floods, are all of these determinants that have called into question the efficiency of green finance.

Green finance is a way to support climate action through investments. It has proven that this is a viable financial instrument and that it can be used by governments and private companies to plan for the future of our planet.

Based on an analysis of articles published in top international journals from 2016 to 2022, about the relationship between green technology and financial services in China, this paper aims to present an overview of green finance, its importance for the planet, its objectives and its instruments.

This study’s contribution is to shed light on the aspects that may have limited its effectiveness, such as the absence of incentives, the absence of climate costs and above all the absence of finance green standards.

The results have shown that there is still a significant gap in green finance before inclusive green growth can be achieved. Inclusive green growth. All stakeholders need to increase the level of investment in green finance. The green investment financing gap is the result of inconsistencies in sustainability and policies. Therefore, governments must intervene to impose appropriate policies and regulations to compel the financial sector to engage in sustainable development. All of these factors make the concept of green finance just an illusion.

The growing trend in environmental, social and governance (ESG) research, along with its relevance to the financial performance of firms, has gained a lot of attraction in academia and industry. This study aims to fill the existing gap in the literature by conducting a thorough systematic review with the latest research articles in this area.

This study adopted a blend of systematic literature review and bibliometric techniques. A proper search string was used to retrieve the data from the Scopus database. The final dataset comprises 296 documents used for science mapping, and the review was done of 60 articles finalised after further refining the documents.

The results of this study indicate that stakeholder, legitimacy and signalling theories are the foundation for ESG and financial performance. Social firms have a lower capital cost because of their low-risk potential. Moreover, this study provides the knowledge structure by framing four clusters, “CSR/ESG determinants and firm performance”, “Moderators and Mediators”, “Investors’ perception” and “CSR in the tourism sector”.

This study has reviewed the literature with both tools, that is, qualitative (systematic review) and quantitative (bibliometric). Moreover, this study presents the latest synthesis of the literature.