Conceptualizing green finance: Findings from textual and network analysis

Abstract

Green finance has seen increased attention from academic researchers and policymakers due to its relevance in mitigating climate change and achieving environmental sustainability goals. Despite the exponential rise in its research publications and policy articles, there remains a lack of uniformity in the scholarly understanding of green finance. The lack of proper understanding and fragmented definitions further impede this domain's theoretical and practical advancements. Thus, it brings much subjectivity to green finance research as it becomes manipulated through different definitions. The current study addresses this significant research gap by systematically analyzing 126 green finance definitions sourced from research articles and different organizational reports of international repute. Through advanced textual analysis, co-word network analysis, and topic modelling through latent dirichlet allocation, the present study identifies the key dimensions of green finance and their interrelationships, culminating in a better understanding of these definitions. The study findings reveal ten core dimensions: environmental, sustainability, energy, finance, economic, institutional, technology, green, societal and sectoral, highlighting their centrality in shaping the existing green finance research definitions. The present study makes a significant critical contribution to advance the scholarly discourse on green finance by providing a strong foundation through the data-driven analysis of the existing definitions. It has significant practical implications, offering a standardized conceptual framework that policymakers, financial institutions, and international organizations can adopt to design sustainable financial products, align regulatory frameworks, and foster global collaboration.

1. Introduction

Green finance has become quite essential in recent years as it addresses many sustainability concerns like climate change mitigation, renewable energy adoption, energy security, and a move towards a green economy [1]. As the popularity of green finance continues to rise in recent times, it has come to notice that it has started to become subjective due to its different scholarly interpretations, which distorts its conceptualization and implementation. Researchers have often pointed out that it has different contexts for others [2,3]. Therefore, the green finance concept has received massive traction from various stakeholders and needs much clarity before losing its true essence. This overarching need to define green finance has been mentioned several times [[4], [5], [6], [7], [8]]. The main problem is not the lack of a green finance definition but the reverse. Due to the various existing definitions of green finance, primarily based on qualitative findings or subjective opinions, it has become challenging to understand which definition to follow. Moreover, green finance definitions have changed over time, leading to a lack of conceptual clarity [6,[9], [10], [11], [12], [13], [14], [15]].

Issues about improper concept definition usually hinder its future growth potential [[16], [17], [18]]. Once the conceptual underpinning of a research concept through the identification of its key dimensions has been done, then only the true essence of the concept can be understood [19]. The need for proper definition also arises as it is crucial for building a strong theoretical framework and conducting meaningful empirical research. The existence of different definitions of green finance further poses difficulty in comparison to the results coming out from various empirical studies. Therefore, the development of the green finance research domain is limited due to multiple interpretations and definitions. Hence, it can be considered that there is a lack of standard agreement as to what green finance means. This research gap suggests a need to systematically analyze the existing definitions of green finance to study its core dimensions. Also, at the initial developmental stage of any research field, such uniform definitions can bring much clarity. Otherwise, it leads to much confusion in the later period, which will only hinder the development and advancement of this particular research field.

This study is crucial as it captures this burgeoning research domain of green finance through such a systematic quantitative analysis. Moreover, it sets the foundational ground by identifying the core key dimensions of the green finance concept and their relationship strength. Therefore, this study provides a much-needed strong basis for green finance research to move forward continuously from strategic and tactical perspectives. However, it should be noted that the primary purpose of this study is not to provide any form of literature review, as many such scholarly review studies already exist [2,[20], [21], [22], [23]]. This study is more about unpacking and analyzing the proposed definitions of green finance in the extant literature that academicians, think tanks, and industry experts have given. The primary purpose of this study is to systematically conduct a quantitative analysis of green finance definitions to address the following research questions (RQs).

• RQ1: What are the core dimensions of the existing green finance definitions?

• RQ2: How are these dimensions related to each other?

• RQ3: What insights can be drawn from the green finance definitions?

The rest of the study has been structured in the following manner: Section 2 presents the underlying definitional challenges associated with the green finance research theme, Section 3 presents the research methods, and Section 4 discusses the data findings. Section 5 concludes the study with its contributions, limitations, and future scope.

2. The definition challenge

As the extant research availability on green finance continues to expand, so does the tendency to understand and know what this concept means. The question- 'What is green finance?' has become a subject of several studies. As a result, various studies and organizational reports have given numerous definitions that are either overlapping or diverse. It has become an issue, creating much scope for misinterpretation and misuse. It has also come to notice that an authoritative definition of green finance remains absent, which poses a significant challenge to the scholarly community in understanding what it is. Therefore, several attempts have been made to define it, and with time, it has lost its true essence.

The emerging area of green finance has ignited curiosity and interest amongst the scholarly community. It is not just restricted to academia but has gained momentum from developmental institutions, environmental think tanks, and the government. The rapid growth of the green finance research domain can also be seen through the publication trend (Refer to Fig. 1). A Scopus database search query with the keyword ‘green financ∗’ returned 3019 documents (as of August 2024). Since the year 2020 itself, the publications have seen massive growth, contributing more than 90 % to the total corpus. It can be seen that the publications specific to this domain have been relatively stagnant till 2015. However, the green finance research domain started getting attention after adopting the Paris Climate Agreement, an internationally legally binding treaty among the 196 countries to combat climate change. Researchers and practitioners have considered green finance as a funding mechanism to mitigate climate change. As a result, there has been a surge of green finance-related articles. This rise in green finance-related studies is also because it can help to achieve the sustainable development goals (SDGs) to limit the climate change effect by lowering the planet's temperature to less than 2 °C of the pre-industrial levels [24]. As interesting as it seems, it has also ignited debates and invited criticism amongst academicians because there is no standard definition of green finance. It has continuously changed due to the changing perspectives and context. It makes understanding and identifying green finance's relevant dimensions and characteristics difficult.

Fig. 1.

Year-wise research publication trend of green finance.

The extant literature has often mentioned this research gap in defining green finance. For example, Zhang et al. (2019) conducted extensive bibliometric analysis and stated that “… green finance per se, however, remains vaguely defined and is often mixed with climate finance …. It is often hard to distinguish between green finance and climate finance … Though subtly different in definitions, at the heart of both terms is the financing tools for coping with climate change and others for sustainability … Given the fact that a clear conceptual definition of green finance is lacking, we concentrate on three keywords search, namely green finance, climate finance and carbon finance.” Similarly [25], explicitly points out that "The concept of green finance is not yet clear, and researchers have yet to reach a consensus on its definition”. But later, points out that “… it is clear that ‘climate mitigation finance’ fits in the purview and context of green finance.” Also [26], points out, “Although green finance does not yet have a uniform definition and overlaps with environmental, climate, and carbon finances, it is a core financing tool for addressing environmental change.”

The present study draws its motivation from several similar studies [18,[27], [28], [29], [30], [31]], which tried to define certain particular concepts and terminologies. These studies have defined the complex concepts in the evolution stage through systematic analysis of the definitions like Circular Economy [18], Circular Construction [27], Construction 4.0 [28], Social Entrepreneurship [29], Corporate Social Responsibility [30], Digital Product Passport Ecosystem [31]. Various scholars have also tried to clarify the complexities attached to various terms by examining their multiple existing definitions and fragmented interpretations. The studies made similar definition analysis attempts to define terms like green marketing [32], sustainability [33], green and sustainable supply chain management [34], green economy [35], green innovations [36], Industry 4.0 [37], and sustainable development [16]. The current study takes motivation from these previous studies to address the definitional ambiguity surrounding the concept of green finance. The present study uses a four-stage research method process. Therefore, these studies serve as the methodological benchmark by effectively demonstrating how the fragmented terminologies can be understood for scholarly academic interest. These seminal studies provide a methodological basis and highlight the significance of definitional clarity in advancing interdisciplinary research. Moreover, these studies collectively highlight the complexities in the definitional ambiguity of the concepts that may be in a nascent stage. It has been found that the absence of unified conceptual frameworks can impede the practical application of research ideas and foster misinterpretation. These studies have made scholarly contributions through systematic analysis of definitions. The present study's investigation aligns with the aforementioned approach by leveraging advanced analytical methodologies, including textual analysis, topic modelling, and network structure analysis, to examine the domain of green finance.

The current study has attempted to cover all the available definitions of green finance to draw some conclusive remarks. The present study is expected to foster discussions amongst the researchers, non-profit organizations, practitioners and several government agencies to facilitate their resources further and implement initiatives where the funds can be channelled judiciously.

3. Research method

There has been a lot of ambiguity, which has been identified and mentioned in several studies about the lack of uniform green finance definition. Despite the three-decades-old green finance literature, no progressive attempt has been made to decipher this concept. Engaging only in qualitative studies like systematic literature reviews can significantly enhance our understanding of green finance concepts. However, such a study does not answer the question of identifying the key dimensions of green finance. Therefore, this problem can only be solved by following the systemic and quantitative approach to analyzing the definitions. The present study conceptualized a uniform definition of green finance by analyzing 126 definitions through textual analysis and natural language processing (NLP).

The current study focuses on research that provides unique and original definitions of green finance rather than simply citing prior ones. Many recent studies reframe existing definitions or do not offer a novel conceptualization. Therefore, although recent studies may discuss green finance extensively, they often do not contribute new definitional insights. The selection of 126 definitions includes the most relevant and concrete definitions drawn from high-quality academic and institutional sources, ensuring that our sample is representative of the diversity of perspectives on green finance. Many recent studies re-iterate similar concepts or do not offer novel definitions. The set of 126 definitions comprehensively covers the domain of green finance, and adding more recent studies would likely introduce redundancy rather than new insights. Finally, the dataset size of 126 definitions is adequate, as it covers relevant, unique definitions from academic and institutional sources, ensuring that the study offers a comprehensive, data-driven conceptualization of green finance.

3.1. Stage 1: identification of the research gap

Initially, the scoping exercise was done to understand the quantum of the literature availability in green finance. Bibliometric analysis unpacked the vast scientific data on green finance. The bibliometric analysis method has grown in popularity due to its rigorous nature in exploring and analyzing such extensive scientific data [38]. In green finance, bibliometric analysis was extensively performed [2]. Bibliometric analysis is a valuable tool for unravelling and charting the accumulated scientific knowledge and the subtle changes that occur over time in established fields. This is achieved by systematically organizing and interpreting vast unorganized data. Hence, well-executed bibliometric research has the potential to establish robust foundations for propelling the research domain field forward in significant ways. It empowers scholars to obtain a comprehensive overview. In other words, by rigorously making sense of massive unstructured data, bibliometric analysis is valuable for decoding and charting the cumulative scientific knowledge and evolutionary nuances of established areas. The current study uses the search keyword “Green Financ∗” on the Scopus database, the largest available database [39,40].

3.2. Stage 2: creating green finance definitional database

The existing definitions were collated from 1997 to 2024 to develop a database of the green finance definition. This stage helps in creating a definitions database. The entire process of making the green finance definitions database is mentioned in Fig. 2. Based on stage 1, it is noticed that the first green finance-related publication came in 1997. However, while making the definitions database, it was found that the first ever academic green finance definition was given in the year 2012 [4]. Since there is no compilation of such definitions in one place, different journals of international repute and non-academic definitions were explored to provide different perspectives. It was understood that merely focusing only on the journals would be quite restrictive and may exclude various important definitions of green finance. The journal articles with such green finance definitions were found to overlap mostly in databases like EBSCO, ProQuest, Scopus, and Google Scholar. Therefore, the extraction process was limited to Scopus only, as it happens to be the most exhaustive database [40]. However, over time, it was felt that there could be some research articles that may not have been indexed in the Scopus database and hence they might have been skipped in this process. Therefore, this similar search strategy was also run on the Google Scholar database to cover the definitions that may have been skipped in the previous step.

Fig. 2.

The process used for the compilation of definitions from the extant literature.

While identifying such research articles, emphasis was given to those explicitly defining green finance. It was also noticed that many studies quoted the definitions suggested by major international organizations like ADB, OECD, UNDP, etc. Hence, extracting all such relevant definitions is crucial, as including them would add a much broader perspective to the definitional analysis. All these identified articles were manually screened and reviewed to see if they referenced any previously cited definitions or gave a new definition. The ones which merely cited definitions of previous studies were not taken to be part of the definitional dataset as it would mean the duplication of definitions. Only those studies which offered an original and new definition were included in the analysis for the present study.

The comprehensive database of green finance definitions has been challenging (Refer to Fig. 2). Given the long history of green finance as a research discipline, it has been filled with many academic publications. Over time, several articles have tried to give different interpretations of green finance. The literature search for green finance definitions, as depicted in Fig. 2, was conducted in two stages to ensure comprehensive coverage and reliability. In the 1st stage, the initial database search was primarily conducted using the Scopus database to leverage its advanced search function. This included keyword-based queries in the title, abstract, and keywords fields by using different sets of common definitional phrases in the search terms such as “green finance refers to”, “green finance means”, “green finance can be defined as”, “green finance stands for”, “green finance may be defined as”, “green finance could be defined”, “green finance is broadly defined”, etc., as mentioned in Fig. 2. These queries aimed to identify studies that explicitly define or discuss green finance. In the 2nd stage, the full-text screening was done to recognize the limitations of database search functions that may not cover the full text of articles; the full texts of all identified articles from the Scopus search were manually reviewed to ensure the extraction of accurate and relevant definitions. This step helped to capture definitions provided within the main text, which may not have been evident from the title, abstract, or keywords alone. Lastly, the search was extended to Google Scholar and institutional reports from organizations such as the United Nations and the World Bank to supplement this. The same two-step process of database querying followed by full-text screening was also applied to these additional sources. This two-tier approach ensures that the present study does not overlook critical definitions and addresses the limitations of searching the databases.

It should also be mentioned that the search was strictly limited to “Green Finance” only. The phrases like “Green Funds”, “Green Credit”, “Green Capital”, “Green Investments” etc were not considered to be part of the definitions database. Similarly, various green finance products like “Green Banking”, “Green Bonds”, “Green Loans”, and “Green Insurance” etc were also kept out of the purview of the definitions search strategy. Similarly, the definitions database was restricted to green finance only, and it does not overlap with the other related terminologies like climate finance, carbon finance, and sustainable finance.

3.3. Stage 3: textual analysis

In this stage, definitions were made concise for their detailed analysis. Using the NLTK Package in Python, the entire definitional database was read and broken down into individual words. As a preprocessing step, stop-words like ‘and’, ‘also’, ‘the’, etc., were removed from the definitions. The definitions were also made concise by removing the common definition search phrases. For example, if the definitions had similar phrases like ‘green finance can be defined as’ or ‘green finance refers to’ etc., they were removed to make the definitions more concise. Lastly, some words had variations in their spellings as per the American and British usage of English, which were made uniform throughout the definitional database. Finally, some words, which may be prepositions, conjunctions, and determinants, were removed as they do not contribute to the study of green finance definitions. Now, the resulting textual corpus was utilized to generate the co-occurrence graphs. For this, the preprocessing technique was followed [19]. This stage involves manually assessing every definition from the definitional database to identify their significant keywords, which were later clubbed together under their relevant “core dimensions”. This way, ten major dimensions of green finance definitions were found which are namely: ‘Environmental’, ‘Sustainability’, ‘Energy’, ‘Finance’, ‘Economic’, ‘Institutional’, ‘Technology’, ‘Green’, ‘Societal’, and ‘Sectoral’.

The present study provides two kinds of analysis for these ten core dimensions using Python's Matplotlib library. Firstly, the total number of constituent keywords within each core dimension was compared by expressing them as the percentage of the total number of keywords in the entire corpus. Additionally, the rate of occurrences of each of these core dimensions within the whole corpus of the green finance definitions was shown for primary analysis of definitions. The ten core dimensions were then manually coded to every green finance definition. The Gephi software was utilized to understand the network structure of these core dimensions and their interrelationship, determining their strength. Python was used to create a matrix of the core dimensions and their frequency as the weights to get the co-occurrence analysis. This co-occurrence matrix is later exported to Gephi for the resulting co-occurrence graph. It should be noted that the nodes represent the core dimensions, whereas the edges represent their co-occurrence to the definitional database. The thickness and intensity of the colour of these edges represent their centrality in the entire corpus of the definitions. Network analysis visualization was done using the Gephi software tool [41] to understand how the coded dimensions of all the definitions have been linked together. This tool is quite helpful as it aids in drawing more clarity on how complex data is related [42]. The social network [43,44] makes the interconnected data more interpretable. It further helps to visualize how these networks have evolved.

3.4. Stage 4: topic analysis

To reconcile the ten core dimensions of green finance definitions, a natural language toolkit in Python was used to perform latent dirichlet allocation (LDA), a Bayesian topic modelling technique to obtain broad topics and their constituent keywords. LDA is one of the probabilistic models used in natural language processing (NLP) and text analysis for topic modelling [45,46]. When applied to the corpus of data, LDA can help uncover the main topics and identify the key areas of interest. It summarizes the significant content by extracting the most prominent themes. The process of automatically identifying topics in a text corpus is known as topic modelling. LDA is a popular method for detecting hidden thematic structures in extensive collections of documents. It's an excellent tool for text classification and other types of text analysis. Topic modelling is the process of automatically identifying topics in a text corpus. LDA is a well-known technique for discovering hidden thematic structures in extensive collections of documents [47,48]. It is a fantastic tool for text classification and other forms of text analysis. LDA is mainly used to find latent topics in a corpus. These topics are not predefined but are discovered through data analysis. This makes LDA suitable for unsupervised text analysis, in which the categories are unknown in advance.

4. Result findings and discussions

4.1. Content analysis through bibliometric approach

Bibliometric analysis of the green finance research field helps to provide the intellectual structure of the research field. [2] conducted a bibliometric analysis to give clarity and an overview of the philosophical structure of the green finance research field. It also mentioned the definitional challenges of green finance. A lot has changed since then. After (Zhang et al., 2019) study, the green finance research field has grown at an explosive rate (refer to Fig. 1), and so have the multiple definitions, which are primarily subjective without any empirical support. The beginning of green finance studies can be traced to (Meyer, 1997) and (Wilson, 1997), but they have merely touched upon it by referencing sustainable development without explicitly discussing green finance. Similarly [49], discussed green finance in the context of reforms related to the financial sector. On further studying the entire corpus of bibliometric data, it was found that there have been multiple attempts to cover the green finance research field through systematic literature reviews (Refer to Table 1) to unravel the associated areas and sub-domains of green finance. Despite this, the definitional ambiguity remains as it is. What comes as a surprise is that out of all these publications, there has been no attempt to define the term green finance so far. However, the need to explain it has been felt over and over many times. The present study tries to analyze the green finance-related studies corpus data extracted from the Scopus database from 1997 to 2024 (refer to Table 1).

Table 1.

Existing review studies related to the domain of green finance.

#	Study	Studies Reviewed	Focus
1.	[2]	381	A bibliometric analysis approach was used to summarise green finance concepts.
2.	[50]	130	Conceptualize the role of green finance in a move towards a circular economy and examine their interlinkages.
3.	[21]	506	Explains the role and linkage of green finance with carbon trading activities.
4.	[51]	280	It presents a summary of green and socially responsible finance.
5.	[22]	46	Critical examination of the role of green finance products in the banking sector.
6.	[52]	56	Integrates green finance with green building for environmental protection.
7.	[20]	195	Conceptualization of the role of green finance in venture capital investments.
8.	[39]	196	Emphasizes the role of green finance to facilitate the Industry 5.0 transition.
9.	[53]	146	Explores the role of green finance for inclusive green growth.
10.	[54]	60	Identifies major research hotspots and the applications of green finance to the specific field.

The top twenty-five most used keywords in the green finance publication studies (refer to Table 2) and Fig. 3 depict how the green finance theme research has been centred. It can be seen that China is the only country that has extensively published and discussed the relevance of green finance for its economy. A closer look at Table 2 shows that green finance studies have consistently talked about ‘sustainable development’, ‘renewable energy’, ‘green bonds’, ‘sustainability’, ‘climate change’, ‘carbon emissions’, ‘economic growth’, ‘green credit’, and ‘financial development’. Post 2020, few studies have linked the ‘Covid-19’ pandemic to green finance. Also, the research has now been linked to ‘fintech’ and ‘carbon neutrality’, ‘green technological innovations’, and ‘environmental regulations’. A close look at these keywords depicts that the studies use similar words, such as green finance and green financing, sustainable development and sustainability, green bond and green bonds. Also, since 2010, green finance studies have continuously referenced the context of the ‘green economy’. It can also be seen that in very recent years, green finance-related studies have shifted their attention to ‘green innovations’. However, many studies have defined green finance without proper reasoning (refer to Table 3). This research gap warrants academic attention to examine existing definitions to understand them better.

Table 2.

Frequency of the main keywords as per their occurrences in the Green Finance publications.

Year	GF	SD	Ch	RE	GBs	GF∗	S	CC	GI	SF	C-19	GE	EE	FD	GB	GC	EG	CE	ER	ESG	GI	GTI	CN	CF	F
2010	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0
2011	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0
2012	2	1	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0
2013	3	1	0	0	1	1	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0
2014	4	2	0	0	1	2	0	0	0	1	0	1	1	1	0	0	0	0	0	0	0	0	0	0	0
2015	5	2	1	0	1	2	1	0	0	1	0	1	1	1	0	0	0	0	0	0	0	0	0	0	0
2016	9	3	1	1	3	6	3	0	0	1	0	1	1	1	0	0	1	0	0	0	1	0	0	1	0
2017	14	6	1	1	4	8	3	2	0	2	0	1	1	2	0	1	1	1	0	0	1	0	0	1	0
2018	30	11	4	2	5	12	9	3	0	2	0	3	1	3	3	2	1	2	0	2	2	0	0	3	0
2019	62	13	8	5	12	17	12	11	1	2	0	7	3	4	4	3	2	2	0	2	2	0	0	6	0
2020	102	27	11	9	18	19	19	16	1	8	0	13	5	5	5	5	4	3	0	3	5	0	0	9	1
2021	203	48	22	16	36	27	29	26	3	19	5	20	8	13	12	7	7	6	6	6	9	1	2	13	6
2022	479	82	58	43	60	59	50	45	25	32	29	28	25	25	28	20	21	14	22	16	15	14	9	22	14
2023	901	149	142	110	107	103	74	72	65	53	46	46	42	42	42	42	40	36	34	30	31	31	29	29	28

Where GF: Green Finance, SD: Sustainable Development, Ch: China, RE: Renewable Energy, GBs: Green Bonds, GF∗: Green Financing, S: Sustainability, CC: Climate Change, GI: Green Innovations, SF: Sustainable Finance, C-19: Covid-19, GE: Green Economy, EE: Energy Efficiency, FD: Financial Development, GB: Green Bond, GC: Green Credit, EG: Economic Growth, CE: Carbon Emissions, ER: Environmental Regulation, GI: Green Investment, GTI: Green Technology Innovation, CN: Carbon Neutrality, CF: Climate Finance, F: Fintech.

Fig. 3.

Primary keywords in the green finance publication studies.

Table 3.

Top cited articles which have tried to define the term without any background support.

S.No.	Authors	Journal	Citations	Green finance Definition
1.	[55]	Energy Procedia	466	“green finance is an innovative financial pattern aimed at the environmental protection and the accomplishment of sustainable utilization of resources.”
2.	[56]	Environmental Science and Ecotechnology	224	“green finance refers to financial investments targeted at environmental protection initiatives.”
3.	[57]	Resources Policy	164	“green finance refers to the way of resource allocation to environmental pollution control, aiming to reduce the environmental damage of enterprise operation and realize sustainable development.”
4.	[58]	SSRN Electronic Journal	136	“green finance is defined as comprising all forms of investment or lending that consider environmental effect and enhance environmental sustainability.”
5.	[59]	Economic Research-Ekonomska Istraživanja	134	“green finance refers to investment making in the environmental and social friendly projects that are carried out by commercial entities both on the private or state level.”
6.	[60]	Sustainability	126	“green finance can be defined as the whole of “financial investments flowing into sustainable development projects and initiatives, environmental products, and policies that encourage the development of a more sustainable economy.” Accordingly, green finance is not limited to climate finance (i.e. the set of financial tools specifically aimed at mitigating greenhouse gas emissions and adapting to climate change), but includes all financial products and services aimed at a wider range of environmental objectives, such as industrial pollution control and water, sanitation and biodiversity protection.”
7.	[61]	Energy Economics	118	“green finance refers to financial services provided for economic activities that are supportive of environment improvement, climate change mitigation and more efficient resource utilization”
8.	[62]	Energy Policy	94	“green finance refers to the behavior of financial institutions to actively support the financing of energy conservation and environmental protection projects.”
9.	[63]	Energy Policy	91	“In general, green finance refers to the finance policy instrument providing concessional finance for project investment and operation in the fields of environmental protection, energy conservation, renewable energy, green transportation and building.”
10.	[64]	Resources Policy	75	“green finance means that with deterioration from environmental pollution, the government adopts the concept of environmental protection by enacting policies, introducing operating guidelines for financial institutions, and supporting the development of green enterprises by providing them with loans and subsidies and restricting the development of high-polluting enterprises to achieve the goal of reducing environmental pollution.”

Table 4 lists definitions of green finance from several reputable international institutions. It highlights the range of diversity towards green finance interpretations. A close analysis of these definitions provides several critical insights. It can be observed that most of these definitions emphasize the environmental benefit of green finance applications through pollution reduction and their integral role in supporting the targets of SDGs. It can also be inferred that organizations like IDFC and UNEP encompass climate finance within green finance as it goes beyond climate mitigation and renewable energy consumption. A deeper look into these definitions points out that green finance relies heavily on several private and public financial instruments like insurance, bonds, loans and private equity to ensure the implementation of green initiatives. Furthermore, it can be witnessed that institutions like ADB and the China Bureau of Statistics stress the sector-specific application of green finance, such as environmental protection and pollution control in the industrial sector. Similarly, the European Commission broadens the scope of green finance by including social dimensions like inequality and inclusiveness.

Table 4.

Green Finance Definitions by several International Organizations.

S.No.	Institution(s)	Green Finance Definition(s)
1.	Organization for Economic Co-operation and Development (OECD)	“Green finance is finance for achieving economic growth while reducing pollution and greenhouse gas emissions, minimizing waste and improving efficiency in the use of natural resources”
2.	People Bank of China (2015)	“Green finance policy refers to a series of policy and institutional arrangements to attract private capital investments into green industries such as environmental protection, energy conservation and clean energy through financial services including lending, private equity funds, bonds, shares and insurance.”
3.	Price Waterhouse Coopers (PWC) (2013)	“For the banking sector, green finance is defined as financial products and services, under the consideration of environmental factors throughout the lending decision making, ex-post monitoring and risk management processes, provided to promote environmentally responsible investments and stimulate low-carbon technologies, projects, industries and businesses.”
4.	International Finance Corporation (IFC) (2013)	“Green finance is defined as financing of investments that provide environmental benefits.”
5.	G20 Green Finance Study Group	“Green finance is defined as financing of investments that provide environmental benefits in the broader context of environmentally sustainable development.”
6.	IDFC (2011)	“Green finance is a broad term that can refer to financial investments flowing into sustainable development projects and initiatives, environmental products, and policies that encourage the development of a more sustainable economy. Green finance includes climate finance but is not limited to it. It also refers to a wider range of other environmental objectives, for example industrial pollution control, water sanitation, or biodiversity protection.”
7.	United Nations Economic and Social Commission for Asia and the Pacific (UNESCAP)	“definition of green finance refers to environment-oriented financial products or services, such as loans, credit cards, insurances or bonds.”
8.	Asian Development Bank (ADB)	“Green finance is a type of future-oriented finance that simultaneously pursues the development of financial industry, improvement of the environment, and economic growth”
9.	China Bureau of Statistics	“Green finance refers to investment in industrial sector to curb pollution”
10.	World Economic Forum (WEF)	“Green finance refers to structured financial activity devoted to improving environmental outcomes”
11.	European Commission (EC)	“Green Finance (and Sustainable finance) generally refers to the process of taking due account of environmental and social considerations in investment decision-making, leading to increased investments in longer-term and sustainable activities. More specifically, environmental considerations refer to climate change mitigation and adaptation, as well as the environment more broadly and related risks (e.g. natural disasters). Social considerations may refer to issues of inequality, inclusiveness, labour relations, investment in human capital and communities.”
12.	UNEP Inquiry (2016)	“Green finance includes climate finance but also includes other environmental objectives necessary to support sustainability, particularly aspects such as biodiversity and resource conservation. ‘Green finance’ is generally used to convey something broader than climate finance in that it addresses other environmental objectives and risks. It tends to be understood with a greater focus on greening broad flows of private investment rather than mainly concerning public and public-leveraged financial flows.”
13.	International Institute for Sustainable Development (IISD) (2013)	“Green finance is often used interchangeably with green investment. Green finance represents a wider lens than green investment. It includes capital cost and, unlike green investment, includes operational costs such as project preparation and land acquisition costs.”
14.	Global Environment Facility (GEF)	“financial investments flowing into sustainable development projects and initiatives, environmental products, and policies that encourage the development of a more sustainable economy. Green finance includes climate finance, but is not limited to it. It also refers to a wider range of other environmental objectives, such as industrial pollution control, water sanitation or biodiversity protection.”

Green finance has gained attention from academic scholars and policymakers in recent years as a critical tool to combat climate change and achieve environmental sustainability. Despite this, there are plenty of inconsistencies, ambiguity, and a lack of consensus on green finance (refer to Table 3, Table 4). This further hinders the application and its future understanding. Although Table 4 effectively demonstrates several underlying core objectives of green finance, it also points out the need to focus on the newer emerging dimensions like societal impacts and technological innovations, which remain underexplored in several definitions. Table 4 definitions highlight that the green finance term is quite multidimensional, with its relevance spanning across several sectors and stakeholders. In the context of these diverse definitions, the current study attempts to present a comprehensive analysis.

4.2. Descriptive analysis of the green finance definitions database

It can be observed that the rise of green finance definitions (refer to Fig. 4) and green finance publications (refer to Fig. 1) reflects similar explosive growth trends. The rise of green finance definitions post-2020 also reflects the urgent need to tackle this research gap and bring much more clarity. Failing to address it will result in more ambiguities in the green finance definitions in the coming future, which will add more confusion about which green finance definition to follow. A deeper investigation into these definitions was done to see which publication outlets have published at least two or more such green finance definitions. As can be seen from Fig. 5, the journal ‘Resources Policy’ has the maximum number of studies that attempt to define green finance, followed by ‘Environmental Science and Pollution Research’ and ‘Renewable Energy’ respectively. The current study also tries to understand which research article received the maximum number of citations out of all the existing green finance definitions. This helps to understand the research impact of that particular study. From the green finance definitions database, it is observed that the studies which are heavily cited are [55,57,65], with a total of 466, 224 and 164 citations so far.

Fig. 4.

Publication trend of 105 academic definitions. (Note: Organizational definitions have been excluded since most of their years of origin were not mentioned in the reports).

Fig. 5.

Journal Distribution of Green Finance Definitions (with at least two definitions).

4.3. Textual analysis of definitional database

The content analysis of the definitions after their stop words and standard definitional search terms have been removed shows us the most frequently occurring words. The current study has highlighted this through unigrams and bigrams analysis of the green finance definitional database. It uses Python's ‘word cloud’ library to construct separate word clouds for unigrams and bigrams to obtain the word clouds. For the unigram analysis (refer to Fig. 6), the study does not preprocess the n-gram-phrasal levels. In contrast, the bigram analysis (refer to Fig. 7) uses the bigram function of the NLTK library in Python to generate the most frequently occurring bi-grams (phrases of precisely two words each). While the unigram word cloud gives us an overall picture of the most occurring words (and possibly phrases, if they're very frequent), the bi-gram analysis helps us to focus specifically on the significant concepts highlighted in the textual corpus. This is important for our study because bigrams like ‘Sustainable development’, ‘Resource conservation’, ‘Economic growth’, etc., constitute essential dimensions of the definition's corpus and the overall concept.

Fig. 6.

Unigrams analysis.

Fig. 7.

Bigram analysis.

The keywords were assigned a particular core dimension based on what they represented and were closely aligned to. The present study divided the primary keywords of the 126 green finance definitions into ten core dimensions (refer to Table 5). Although ‘Environmental’ and ‘Sustainability’ found a close association, it divided the keywords based on their explicit mention of the environment and their relatability to sustainable development. Also, it was observed that several keywords highlighted two aspects of ‘Finance’; one set of keywords was related to the ‘mechanisms and the process’, while the other set of keywords talked about the relevant ‘tools and financing instruments’. These two sub-dimensions were combined to form one core dimension, ‘Finance’.

Table 5.

Green Finance Definitions coded to the core dimensions if they are related to ‘ … ’

S.No.	Dimensions	Elements/Keywords
1	Environmental	Environmental protection, pollution control, ecological, preservation, degradation, resources conservation, resource allocation, biodiversity, environmental emissions, environmental improvement, nature/natural, climate change, carbon absorption, ecological sustainability, ecology resources, recycling, environmental pollution, environmental protection rights, environmental damage, environmental damage, environmental concerns, environmental quality, environmental performance, environmental activities, environmental products, environmental improvements, environmental activities, environmental assessment, environmental issues, environmental impact, greenhouse gas emissions
2	Sustainability	air, land, water, circular, SDGs, climate, pollution, waste, sustainable, climate mitigation, climate adaption, emissions, industrial pollution control, resource efficiency, sustainable development, sustainable economy, sustainable energy, sustainable infrastructure, clean projects, sustainable initiatives,
3	Energy	Clean energy, carbon emissions, carbon neutrality, low-carbon, clean energy, renewable energy, energy adaptation, energy-efficiency, GHGs, alternative energy, green energy, energy conservation, energy saving, coal, clean production,
4.1	Financing Mechanism and process	Financing, investing, investments, capital, credit, funds, disincentives, subsidies, benefits, costs, risks, financial incentives, responsible investments, financial support, climate finance, financial institutions, financial products, financial services, financial markets, financial activity, financial innovations, financial activity, financial tools, financial model, financial system, financial transactions, financial provisions, financial gain, monetary resources, financial support
4.2	Financing tools and instruments	Bonds, bank/banking, assets, stocks, funds, invest, investing, equity, shares, securities, loans, products, credit, lending, insurance, green bank, green debt, green investments, private investments, climate fund, financial aid, financial assets, financial tools, financial derivatives, financial products, financial services, financial investments, financial activity, carbon market instruments,
5	Economic	Market, economies/economy, infrastructure, development, resources, services, growth, industry/industrial, infrastructure improvement, transportation, projects, businesses, green economy, economic activities, green transportation, green buildings, commercial operations, economic performance, green economic growth, business activities, financial industry
6	Institutional	Institutions, Enterprises, government, companies, firms, banks/banking, factories, industries, businesses, organizations, financial markets, public-private partnerships,
7	Social/Societal	society, social security, poverty, agriculture, forestry, waste management, transportation, sanitation, hygiene,
8	Technology	Technologies, technological advancement, innovation, creation, innovative, eco-innovations
9	Green	Green industry, green economy, green bank, green transportation, green buildings, green credit, green bonds, green development, green securities, green investments, green engineering, green preferences, green projects, green development project, green technology, green enterprise, green funds, green debt, green climate fund, green debt securities, green activity, green consumption, green economic growth, green business activities, green stocks, green insurance, green investments
10	Region/Sectoral	Sectors, Local, country, national, transnational, financial sector

Note: The finance dimension has two sub-dimensions: Financing mechanism/process (4.1) and financing tools and instruments (4.2). Keywords coming under these sub-dimensions have been combined to form the finance dimension.

Moreover, the present study also observed that significant definitions discussed ‘greening’ aspects such as green buildings, green projects, green industry, green activities, etc. Therefore, adding them into the core dimension 'Green' was considered better. This process was iterated many times by adding the keywords into these core dimensions. It should be noted that the present study didn't consider the frequency of these keyword occurrences. As can be seen from Fig. 6, Fig. 7, many of these have been repeatedly used. Therefore, keywords were considered irrespective of their occurrences. This step helps to put all the desired keywords into a particular core dimension. At a later stage, the percentage of keywords within each dimension and the percentage of occurrences of each of these keywords were considered to get a better picture (refer to Fig. 6, Fig. 7).

For Fig. 6 unigram analysis, the most frequent keywords observed from the definitions are ‘green’, ‘financial’, ‘environmental’, ‘investment’, ‘financing’, and ‘environment’. These are followed by words of almost similar frequencies such as ‘climate’, ‘ecological’, ‘energy’, ‘environmental protection’, ‘emission’, ‘sustainable’, ‘economic’, ‘efficiency’, ‘instrument’, ‘economy’, ‘fund’, ‘enterprise’, ‘development’, ‘policies’, ‘product’, ‘credit’, ‘fund’, ‘private’, ‘activities’, ‘social’, ‘financial service’, ‘risk’, etc.

Similarly, for Fig. 7 bigram analysis, it can be noticed that the most frequently used keywords are ‘climate change’, ‘financial services’, ‘sustainable development’, ‘environmentally sustainable’, ‘energy conservation’, ‘environmental protection’, ‘renewable energy’, ‘financial institutions’, ‘economic growth’, and ‘economic activities’. These are followed by keywords of fewer occurrences such as ‘environmental benefits’, ‘environmental pollution’, ‘energy efficiency’, ‘financial activity’, ‘greenhouse gas’, ‘environmentally friendly’, ‘financial sector’, ‘financial investments’, ‘natural resources’, ‘pollution control’, ‘gas emissions’, ‘ecological environment’ and ‘green finance’. Moreover, a quick comparison between the unigrams and bigrams reveals that the following words have found their place in Fig. 6, Fig. 7: ‘climate change’, ‘financial service’, ‘sustainable development’, and ‘environmental protection’. Also, most bigrams make sense for our green finance definitions database as these keywords occur in phrases jointly, which may be skipped in unigram analysis.

The bar chart (refer to Fig. 8) gives an idea about the distribution of various keywords within each core dimension (refer to Table 5) from the green finance definitions database. It can be seen that ‘Finance’ with its sub-group ‘mechanism’ and ‘tools and instruments’ is the most significant dimension regarding the distribution of the keywords. This is followed by the ‘Green’ and ‘Environmental’, which also have a substantially large diversity of keywords. A stark contrast is seen in the dimensions of ‘Social’, ‘Technology’ and ‘Region/Sectoral’, which have very little diversity in the constituent keywords.

Fig. 8.

Percentage of Keywords/Elements within each core dimension.

The bar chart (refer to Fig. 9) represents the percentage of occurrences of a particular core dimension in the green finance definitions database. The score is obtained by the simple formula as follows:

Fig. 9.

Percentage of occurrences of each dimension within the Green Finance definitions database.

Percentage Occurrence = 100∗(Number of definitions mentioning at least one keyword of a given dimension)/Total number of definitions.

It can be inferred that ‘Environmental’ (89.06 %) and ‘Finance’ (81.25 %) are the most mentioned dimensions among the definitions, forming the core of the green finance concept. The dimensions such as ‘Sustainability’, ‘Green’, ‘Economic’, ‘Institutional’ and ‘Energy’ are moderately important based on their mentioning in the definitions, whereas the ‘Social’, ‘Technology’ and ‘Region/Sectoral’ dimensions are almost at the periphery of the green finance concept of which depict their negligible importance in terms of their mention in the definitions database.

The network structure phase (refer to Fig. 10) involves co-occurrence-based network analysis of the dimensions of the green finance definitions. This step helps in the centrality of one dimension over another and amongst themselves [19,66]. In this co-occurrence network, the edges of the dimensions become red and thicker, which signifies their maximum weightage for the other dimensions. The network structure of the ten dimensions arising out of the green finance definitions database (refer to Fig. 10) highlights their inter-relationship and the degree of centrality among them. The network structure coverage of all 126 definitions shows that they are mostly connected on the ‘Environmental’ and ‘Finance’, the two most often co-occurring concepts (refer to Fig. 10), as highlighted in the bar chart analysis. Moreover, ‘Sustainability’ and ‘Economic’ are also strongly tied to the core of the green finance concept, while ‘Institutional’, ‘Green’ and ‘Energy’ dimensions form the semi-periphery of the green finance concept. It comes as a matter of surprise that the ‘Technology’, ‘Social’ and ‘Sectoral’ dimensions have not had enough attention from researchers and institutions for defining green finance, and thus, they form the periphery of the concept, and their inclusion within a definition of green finance can therefore be debated and reconsidered.

Fig. 10.

Network structure of the dimensions.

After a close look at the definitions database, it is noticed that the ‘Technology’ dimension is still in its infancy. Many existing definitions have not emphasized the role of cutting-edge technologies in implementing green finance-based solutions. Similarly, the ‘Sectoral’ and ‘Social’ dimensions are least stressed in the green finance definitions when they should be given maximum priority as most of the SDGs can be achieved only directly through their direct involvement. The dimension ‘Green’ is connected to every element. It has a strong relationship with ‘Sustainability’, ‘Environment’, ‘Economics’, and ‘Finance’. It can be seen that the ‘Energy’ dimension is connected with the ‘Environment’, ‘Sustainability’ and ‘Economic’ dimensions, highlighting that green finance is playing a crucial role towards renewable energy adoption in the form of energy-efficient solutions.

4.4. Topics extraction through LDA analysis

Table 6 briefly summarizes the nine topics from the LDA analysis of 126 definitions. Each of these LDA topics gives out a set of keywords that represent the central theme of the topic and indicate what a particular topic reflects. The distribution of these nine topics shows their prevalence within the definitional database. Some definitions can show strong associations only with a specific topic, while others show mixed perspectives on multiple LDA topics. The topics were interpreted based on a review of the top keywords, followed by finding a common theme or concept. This then gives a core idea of what these topics represent. The LDA topics were labelled after the common themes amongst the keywords were identified. Some topics overlap or are closely related, while others are distinctly different.

Table 6.

LDA topics of definitions.

S.No.	LDA Topic Keywords (weights in descending order)	LDA theme	Description/Interpretation
1.	Sustainable, financial, environmental, investment, green, development, project, energy, resource, environmentally	Sustainable development and green energy	This topic encompasses sustainable financial development, emphasizing investments in green projects. It explores the financial aspects of environmentally responsible development by highlighting the importance of resource sustainability.
2.	Green, resource, promote, climate, environment, economic, environmental, production, support, finance	Green economic and environmental support	This topic focuses on initiatives that promote economic activities with a strong emphasis on climate support. It underlines the economic benefits of environmentally responsible green practices.
3.	Green, environmental, financial, achieve, fund, energy, investment, protection, development, support	Green investment and environmental protection	Centred on green financial initiatives, this topic aims to achieve environmental protection through strategic investment and fund allocation. It emphasizes financial support for the efforts towards the development of environmentally responsible energy.
4.	Energy, environmental, project, protection, financial, climate, change, financing, support, resource	Energy and environmental protection financing	This topic is concerned with financing projects related to energy and environmental protection, particularly in the context of climate change. It addresses the financial aspects of climate mitigation and resource conservation.
5.	Financial, environmental, activity, climate change, support, service, resource, development, gas	Financial activities for climate support	This topic focuses on financial activities and services that support the efforts towards climate change mitigation and environmental resource development. It highlights the financial sector's role in sustainability.
6.	Financing, help, sector, achieve, financial, economy, fund, strategic, green, emission	Financing green sectors for emission reduction	This topic discusses financing for green sectors to reduce emissions and achieve strategic environmental goals. It highlights the financial incentives and strategic importance of reducing emissions.
7.	Green, environment, finance, industry, protection, development, investment, environmental, effect, resource	Green finance for industry and environmental protection	This topic discusses the role of green finance for environmentally conscious initiatives within industries, emphasizing development and resource protection. It highlights the financial support needed for the industry's environmental efforts.
8.	Environmental, financial, finance, activity, climate, economic, change, improvement, outcome, better	Environmental finance for economic improvement	Concentrating on environmental finance, this topic connects it to economic enhancement and better outcomes, particularly in the context of climate change. It underscores the financial aspects of achieving environmental and economic improvement.
9.	Investment, environmental, financial, project, green, financing, climate, energy, protection, development	Investment in green energy and environmental protection	This topic concerns financial investment in projects to protect the environment and promote green energy solutions. It emphasizes the role of investment in supporting environmental protection and sustainable development efforts.

Therefore, these themes and their interpretations have been based on the significant keywords from the LDA analysis. Hence, their description is context-specific. A brief glimpse (refer to Table 6) helps us to understand the area of green finance based on the several existing definitions in this domain. A quick snapshot of the LDA topics and their themes brings excellent insight into the definitions of green finance. The findings help to draw many similarities and differences between the topics extracted from the LDA analysis of the definitions. In terms of similarities, it can be inferred that: Firstly, these topics incorporate words like ‘environment/environmental’ and ‘climate change’, which demonstrate that many of these definitions have shared emphasis on environmental sustainability and various climate-related aspects. Secondly, financial words like ‘investment’, ‘fund’, ‘finance/financial/financing’, etc, highlight the critical role of finance. Thirdly, a common concern for resource management and sustainable development can be observed through ‘resource’, ‘development’, ‘project’, ‘energy’, etc. Finally, the multiple references to the ‘green’ keyword also reflect the focus towards environmentally friendly practices. From the above statements, it can be concluded that these definitions are focused on the environment and emphasize the role of finance in green initiatives, resource efficiency, and sustainable development.

Apart from the commonalities amongst these LDA topics, it has several distinct features. Firstly, every topic has a unique combination of keywords, which can help us distinguish one from the others. Despite similarities in their reference towards ‘Finance’ and ‘Environment’, these topics have a different thematic focus. Also, it can be seen that there are some topics which appear to be very broad by encompassing different ranges of terms, while other topics are specific and narrow. For example, topic 7 mentions ‘Industry’. Along the same lines, topic 6 explicitly discusses the strategic approach for ‘emission reductions’. Similarly, topic 2 discusses the ‘economic aspect’, and topic 8 is oriented more towards the ‘outcome’ and bringing out the ‘improvement’. These similarities and differences help to highlight the multifaceted nature of green finance definitions through various aspects, as listed in the 9 distinct topics. Therefore, understanding them can help provide us with valuable insights to have different perspectives and prioritize the development of the green finance research field.

5. Conclusion

The present study addresses the significant research gap of the definitional ambiguity of green finance. It systematically analyses the definitions through their extraction from textual analysis, followed by network structures of the core dimensions and the topic modelling. The findings provide a strong theoretical understanding and set the foundation for policymakers to apply it. The existing confusion in the definitions has been removed by the clarity and consistency of the findings that can support the stakeholders to align their efforts towards the global sustainability targets.

The government and regulators can leverage the insights from the present study to design clear and consistent policies promoting sustainable investments. It will help the policymakers avoid ambiguity and misinterpretation, ensuring that green financial initiatives can better align with sustainability goals under the Paris Climate Agreement. Moreover, green finance dimensions, like environmental and financial aspects, can enable financial institutions to develop their products, projects, and policies better, tailored to mitigate climate risks while ensuring economic returns. Also, it can provide a benchmark for the better assessment and certification of green projects, which can, in turn, enhance the project's credibility and investor confidence. Lastly, dimensions like societal and institutional can facilitate the multi-stakeholder collaboration between governments, financial institutions, and businesses to channel the resources into projects that address climate change, renewable energy adoption, and societal well-being.

5.1. Quick reflection on the key findings

It can be observed that despite many definitions, a strong relationship exists towards the end objective of ‘environment’ through ‘finance’, along with ‘sustainability’ among all the existing dimensions. This highlights a consensus among scholars that the green finance should be primarily utilized for environmental sustainability. Financial investment resulting in environmentally-friendly outcomes must be considered under ‘Green finance’. This study presents a systematic and quantitative analysis of 126 definitions of green finance extracted from the extant literature from 1997 to 2024. Although green finance was mentioned for the very first time in literature in 1997, its first academic definition can be traced back to 2011. This study intends to address the significant research gap identified and discussed recently. It identifies the key dimensional features of the various green finance definitions through qualitative literature review and quantitative analysis procedures. It further seeks to understand how the concept of green finance reflects sustainability and where the focus needs to be put, for example, ‘technology’ and ‘sectoral’.

The study's key findings are as follows: Firstly, it identifies the ten core dimensions that consistently emerged across the definitions. These dimensions provide a comprehensive view of the various facets of green finance. The findings reveal that the ‘Environmental’ and ‘Finance’ dimensions are central to the understanding of green finance, while ‘Sustainability’, ‘Energy’, and ‘Economic’ aspects are closely aligned with the core definition. Other dimensions, such as ‘Technology’, ‘Institutional’, and ‘Societal’, provide valuable supporting elements that enrich the concept. Secondly, a co-word analysis of these dimensions reveals their interrelationships and the strength of connections. Thirdly, the LDA analysis uncovered multiple latent topics within the definitions, such as climate change mitigation, renewable energy investments, and sustainable financial products. These topics reflect the major thematic areas that define green finance. Lastly, it offers a standardized framework to guide academic research and practical applications in policy-making, financial product development, and institutional practices.

5.2. Contribution of the study

The study clarifies the concept of green finance through several contributions. Firstly, the qualitative nature of the bibliometric analysis helps to enhance the understanding of the historical evolution of green finance by providing valuable research insights. This was done to dive deep into this rapidly rising field, whose last bibliometric analysis was done in 2019. It can be seen that a lot has changed since then, with the majority of the empirical studies and definitions coming after that. Secondly, the quantitative analysis of the definitions of green finance brings objectivity to the data findings, which are usually lacking in bibliometric analysis and systematic literature reviews. This helps to identify the significant keywords and their associated core dimensions, which can help capture the concept. Thirdly, the network structure of the core dimensions followed by the LDA topic analysis is critical as it helps provide support for a comprehensive understanding of the definitions that capture the dimensions that underpin the concept of green finance. It further lays a strong foundation for future research agenda work. Also, it aids policymakers with policy formulation (with respect to climate goals like SGDs), evaluation (tracking the achievement of objectives), and medium (like institutions).

5.3. Limitations

Even though the present study significantly contributes to the subject domain, it has a few limitations. Firstly, no matter how exhaustively the core dimensions have been created, there still lies the possibility of adding several new dimensions in the future, as this field of study is seeing a considerable rise in publication trends. Secondly, researchers can try to replace keywords amongst the core dimensions to create several new sub-groups. Such shifting of the keywords and new core dimensions can influence the definition of green finance. Thirdly, it was observed that a new dimension could be created, namely ‘Behavioural/Nudge’, but since there were only a few keywords like ‘decision making’, ‘financial decisions’, etc., the current study didn't count it as a separate dimension. However, it should be understood that behavioural psychology plays a crucial role in green finance projects and their successful implementation. Therefore, new definitions should definitively take into consideration this parameter.

Fourthly, one major limitation of this study is that it did not include terms of similar context. For example, green credit, green funds, green investments, etc., were ignored while collecting the definition. The definitions database was exclusively restricted to the green finance word only. Similarly, many such green finance products (namely green fintech, green banking, green bonds, green insurance, etc.) were not considered. Therefore, there could have been many such scholarly articles which did not define green finance but attempted to define the associated green finance products. Their exclusion was done to restrict the definitions solely to green finance only. Finally, many studies interchangeably use climate finance and sustainable finance with the term green finance. They have also not been included, as it would have diluted the context of the green finance definition. Therefore, some additional definitions have not been considered. However, because the present study captures an extensive sample of green finance definitions, it is safe to assume that the data analysis will not be altered.

5.4. Future directions

The green finance research area is exploding, and there are many publications. In the future, researchers can explore green finance through the current study's findings to further bring more refinement. The empirical studies can be designed around the core dimensions of green finance identified in this study to study and understand their impact on green finance. Also, international organizations can try to channel their funds through their green finance projects based on these core dimensions. Future researchers can use more quantitative analyses to study green banking, bonds, and insurance concepts. Also, this methodology can be replicated across similar terminologies like sustainable finance, environment finance, and climate finance to clarify their definitions better. Another possible future research work is to draw the commonalities and differences between green finance-related terms by comparing their definitions. Moreover, it can be seen that the impact of green finance is context-dependent. It brings out different outcomes for industrialized nations, developed nations, and emerging countries. Therefore, researchers can aim to study the relative relevance of any of the dimensions from different contexts for various countries.

CRediT authorship contribution statement

Karambir Singh Dhayal: Writing – review & editing, Writing – original draft, Visualization, Validation, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Srijan Shashwat: Visualization, Validation, Formal analysis. Arun Kumar Giri: Writing – review & editing, Validation, Supervision, Resources, Project administration, Funding acquisition, Data curation, Conceptualization.

Consent to participate

As the Corresponding Author, I confirm that the manuscript has been read and approved for submission by all the authors.

Data availability

Data not used in this article.

Availability of data and materials

No datasets were used during the current study.

Ethical approval

Not applicable.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.