The research examines the factors influencing the adoption of green financing in the steel sector of Odisha, where balancing industrial growth and environmental sustainability is crucial. It places the experience of Odisha in international efforts on climate change and India's national sustainability agenda.
A mixed-methods research strategy was used, integrating survey responses from 171 participants and ordinal regression analysis. The independent variables used were initiatives in sustainable finance, opportunities for growth, green technology incentives, access barriers to financing, social responsibility (SR), government support and financial infrastructure.
Findings verify strong correlations among the determinants and rates of green finance (GF) uptake. Although the majority of the stakeholders lie within the medium adoption group, major barriers on progress, e.g. low incentives, access to finance challenges and poor governmental support – limit improvement. Financial infrastructure support and SR come across as possible facilitators.
The research finds it imperative for GF adoption to be supported by targeted incentives, robust financial infrastructure and enabling policy frameworks. With this gap filled, Odisha's steel sector can both converge with international sustainability objectives while raising industrial competitiveness.
The study focuses on various driving forces for an organization to adopt GF practices for their financial management in recent years. As financing is done at different levels, it is also very essential to understand the impact of these factors in concern with level of financing.
Introduction
The world is experiencing unprecedented effects of climate change that test long-term sustainability. The United Nations Sustainable Development Goals (SDGs) and the Paris Climate Agreement have reaffirmed the obligation of global institutions and countries to seek environmental sustainability. Yet, overexploitation of natural resources continues to drive environmental degradation globally (Orsatti, 2024). This degradation calls for the implementation of green approaches as institutional tools to reduce environmental degradation. In this context, green finance (GF) has become a key strategy, seeking to link economic development with environmental care (Brandi and Morin, 2023).
For Zhang and Umair (2023), GF is the mobilization of capital that produces quantifiable environmental impacts. Sustainable development is hence attainable through finance flows to green initiatives using tools like green bonds, investment banks, carbon markets, fiscal incentives, green funds at the community level and sustainability-linked financial policies (Ukatu et al., 2025; Sachs et al., 2023). Green investment targets, especially low-carbon sectors, renewable energy and climate resilience technologies, thereby instilling sustainability into finance practices in the industrial sector (Al Muhairi and Nobanee, 2019). As Morri et al. (2024) posit, concurrent growth in green financing and green investment is indicative of a paradigm where environmental protection meets financial returns.
At the international level, the steel sector is now a central target of low-carbon transformation. Authorities, markets and investors are squeezing steelmakers to embrace hydrogen-based options, electrification, circular resource utilization and carbon-management technology. Research underlines that large-scale decarbonization of steel will necessitate wide-scale mobilization of capital in clean energy, Direct Reduced Iron–Electric Arc Furnace (DRI–EAF) processes and policy systems that de-risk innovation (IEA, 2022).
In India, this shift overlaps with a specific setting: an infrastructure reliant on coal, growing domestic consumption and developing policy environments such as India's Green Steel Roadmap and forthcoming green taxonomy (Ghosh et al., 2022). The success of green financing infrastructure in India is hinged on three pillars: (1) transparent taxonomies and reporting frameworks, (2) financial instrument development like green bonds and sustainability-linked loans and (3) supportive state and banking interventions to address costs and risks for early-stage projects (Sharma and Jain, 2024).
Regional examples include Odisha, India's steel capital, which reflects opportunities and challenges alike. Its robust industrial prowess, renewable energy potential and green hydrogen opportunities form a platform for focused green investments (Panigrahi and Panigrahi, 2021; Rout, 2023). However, hurdles persist: restricted access to long-tenor concessional financing for small units, regulatory hurdles and the imperative for reskilling the workforce and supply-chain transformation (CEEW and RMI, 2023).
Therefore, sustainable development in India's steel clusters, and Odisha at large, rests on the decisive factors of green financing infrastructure: (1) transparent disclosure and standards, (2) blended and diversified financial instruments to take risk, (3) concessional public finance and guarantees, (4) project bankability and technical assistance and (5) industrial–energy policies that bridge cost gaps for green technologies (World Bank, 2023). While such levers are slowly unfolding, fast-tracking scaling and inclusive mechanisms are needed to extend into small and medium businesses.
The introduction emphasizes GF as crucial to Odisha's steel industry sustainability. The review of the literature now delves into global and Indian research, presenting theoretical and empirical observations on green financing infrastructure and determinants influencing sustainable industrial growth.
Literature review
Sustainable finance, being a development of traditional finance, aligns capital flows with initiatives that support sustainable development as well as climate change mitigation. Sustainable finance entails mobilizing funds from private sectors, pension funds, central banks, as well as not-for-profit organizations, usually in the form of instruments like sustainable loans, green bonds, renewable energy equity and carbon credits (Maina et al., 2024). GF, in general, places special focus on instruments such as insurance-linked funds, socially responsible investments and grants that incorporate environmental priorities into financial action (Waite, 2024). Industries continue as key players, utilizing corporate social responsibility (CSR) sources for renewable energy and sustainable transport initiatives, while banks and governments mobilize massive financing (Shin et al., 2022; Wan et al., 2024).
It is essential to group GF instruments into large, medium and small-scale because steel production industries, especially those in Odisha and India as a whole, tend to be very heterogeneous with regard to capital investment, staff size and technological capability. By correlating the size of financial instruments with organizational size, industries can utilize specific financing mechanisms that correspond with their sustainability requirements and growth capacity.
Such categorization, as per Demski et al. (2025), enables large-scale industries (such as integrated steel plants) to be financed by high-value vehicles like green bonds, infrastructure funds and ETFs, while medium and small businesses are aided by impact funds, venture capital, crowdfunding and grants. This ensures efficient allocation of financial resources and does not act as a barrier to the entry of smaller businesses Badrane and Bamousse (2025). In addition, categorization allows policymakers and banks to develop incentive structures that encourage broader uptake of sustainability measures at every level of the steel industry, thus informing India's low-carbon transition strategy (Falcone and Sica, 2019; Lalon, 2015).
GF has diversified into tools globally. Large-scale tools are Green Bonds (Gilchrist et al., 2021), Renewable Energy Infrastructure Funds (Meckling et al., 2022), Sustainable Real Estate Funds (Maltais and Nykvist, 2020) and Green ETFs (Mills, 2016). These tools have played a fundamental role in financing steel decarbonization initiatives, especially in Europe and East Asia, where funding has enabled hydrogen-based steelmaking, DRI–EAF upgrades and carbon capture initiatives (IEA, 2022).
Medium-sized financing vehicles comprise Impact Investing Funds (Miroshnichenko and Mostovaya, 2019), Green Venture Capital (Miroshnichenko and Mostovaya, 2019) and Community Renewable Energy Projects (Khaleel et al., 2023). These mechanisms have played a key role in funding technology start-ups that innovate circular economy models, digital energy-efficiency technologies and green hydrogen pilot schemes. Small-scale measures – like Green Savings Accounts (Huang et al., 2019), Crowdfunding Platforms (Wang et al., 2022), Renewable Energy Certificates (Lin et al., 2025) and Socially Responsible Investment funds – have mobilized public and retail engagement in transitions towards sustainability, indirectly rewarding steel's supply chains through renewable integration.
In addition, loans and grants continue to be influential. Green Project Loans (Lalon, 2015) and Green Business Loans (Tolliver et al., 2019) have fronted funds for industrial retrofits, while research and project grants (Chen and Huang, 2025; Nakao et al., 2007) finance clean technology innovations. Innovative techniques like Carbon Offsetting Programs (Heinkel et al., 2001) and Green Crowdfunding (Bai et al., 2024) show increasing variety in financing channels. But global literature always emphasizes that scaling these instruments demands open taxonomies, de-risking solutions and institutional backing.
In India, GF has picked up pace through policy systems like the Green Steel Roadmap and the upcoming sustainable finance taxonomy (Ghosh et al., 2024). Green bonds, sustainability-linked loans and renewable infrastructure funds have been formalized, with guidelines on environmental, social and governance (ESG) disclosures offered by the Securities Exchange Board of India (SEBI). Yet, even after the launch of green bonds, India's proportion of global green capital inflows is modest vis-a-vis advanced economies (Dutt et al., 2024).
India, the second-largest steel industry after China, faces distinct challenges in moving toward sustainability: high coal dependence, increasing domestic demand and expensive technologies. Long capital flows, blended finance and concessional lending are needed to fund hydrogen-based steelmaking, DRI–EAF systems and renewable-powered processes. But access to low-cost and long-term finance is still scarce, especially for ancillary steel industries' medium and small-scale enterprises, which constitute the industry backbone.
While some of the bigger companies have started issuing green bonds for renewable integration, venture capital and impact investing in green technology start-ups still lag behind. Likewise, while banks provide green loans, finance gaps exist because of credit risks, the absence of collateral and policy risk. This identifies a gap between India's aggressive policy blueprints and the real financial tools on offer for steel decarbonization.
Odisha, sometimes referred to as India's steel capital, offers both opportunities and challenges for the use of GF. It has top steel manufacturers and has the potential for green hydrogen clusters, the integration of renewable energy and circular use of resources (CEEW and RMI, 2023). Odisha thereby becomes an experimental ground for novel green financing products.
It is essential to group GF instruments into large, medium and small-scale because steel production industries, especially those in Odisha and India as a whole, tend to be very heterogeneous with regard to capital investment, staff size and technological capability. By correlating the size of financial instruments with organizational size, industries can utilize specific financing mechanisms that correspond with their sustainability requirements and growth capacity.
Constraints are still significant, nonetheless. Small and medium steel players are constrained from accessing concessional finance, with added factors of regulatory barriers, capital-intensive costs and limited financial awareness regarding sustainability-linked financing. Reskilling the workforce, supply chain modernization and industrial infrastructure upgradation also require significant initial capital. Financial instruments are still skewed toward large-scale players by government efforts, leaving gaps in medium- and small-scale uptake. This imbalance emphasizes the need for scalable, inclusive green financing infrastructure that can be scaled up from flagship projects to the broader ecosystem of Odisha's steel industry.
Based on the literature examined, green financing adoption may be classified as high – Green Investment aligned with the Sustainable Development Goal 1 (GISDG1), medium – Green Investment aligned with the Sustainable Development Goal 2 (GISDG2) or low Green Investment aligned with the Sustainable Development Goal 3 (GISDG3) based on capital size mobilized. They are shaped by determinants recognized in earlier research:
Table 1 below gives an operational definition of the variables involved in the research, with GF being measured as a dependent variable with three levels of thresholds: high, medium and low, defined by GISDG1, GISDG2 and GISDG3, respectively. From Table 1, important variables which affect GF as an independent variable include initiative for sustainable finance (GINV1), growth opportunities through GF (GINV2), Incentives for Green Technology (IGT) (GINV3), barriers in evaluating GF (GINV4), social responsibilities (GINV5), support from the government (GINV6) and support for the financial infrastructure (GINV7). These variables bring into focus important characteristics of an institution, finance system, society and policies. They form a holistic approach for studying the factors underlying GF in the chosen steel companies in Odisha.
Dependent variable and independent variable description
| Dependent variable | Threshold level | Symbol |
|---|---|---|
| Green finance | High | GISDG1 |
| Medium | GISDG2 | |
| Low | GISDG3 | |
| Independent variable | Names Initiative for sustainable finance | GINV1 |
| Growth prospects through green financing* | GINV2 | |
| Incentives for green technology | GINV3 | |
| Barriers in assessing green finance* | GINV4 | |
| Social responsibility* | GINV5 | |
| Government support | GINV6 | |
| Supporting financial infrastructure | GINV7 |
This level of funding could be influenced through several quantitative and qualitative aspects. In this study, some of the most cited factors are highlighted and discussed concerning the Indian steel manufacturing industries and most relevant for Odisha as per its ecological and socio-economic ecosystem.
Initiative for sustainable finance
At the international level, sustainable finance efforts have surfaced as a foundation to synchronize industrial development with climate objectives. According to Liu and Wu (2023), GF supports innovation by funding eco-friendly technologies while directly financing climate action goals under Article 2.1(c) of the Paris Agreement. Likewise, Chen et al. (2024) contend that GF supports sustainable development by facilitating policies that cut emissions and enhance the quality of the environment, an opinion shared by Brandi (2017) and Li (2024).
In the Indian context, where steel is a significant emitter, sustainable finance tools like green bonds, sustainability-linked loans and transition finance are increasingly used to finance decarbonization paths. Not only do they offer long-term capital but also guarantee a fair and equitable shift towards low-carbon technology (Selvaraju et al., 2024). By aligning financial returns with commitments to reducing emissions, India's steel sector becomes more competitive and resilient in overseas markets.
At the Odisha level, where coal-intensive steelmaking is prevailing, such schemes are particularly pertinent. Expensive green technologies like renewable energy integration, hydrogen steelmaking and sophisticated waste management systems need sustainable finance to surmount technological as well as financial challenges (Shen et al., 2024a, b; Wang et al., 2024).
This argument is important to the current study due to its demonstration of how green transition initiatives serve as the major facilitator of green transitions in Odisha's steel sectors. Absent targeted financial flows, technological innovation and sustainability avenues would be out of reach. Therefore, these initiatives constitute the basis for comprehending the structural nexus among GF, green innovation and environmental sustainability in this paper. Das and Mishra (2025).
The initiative for green finance has a remarkable effect on adopting green financial practices in the steel manufacturing industries of Odisha.
Growth prospects through green financing
On the global plane, the incorporation of GF in industrial systems has a close relationship with long-term growth prospects because green transitions maximize energy efficiency, develop low-carbon technologies and enlarge sustainable markets. Lee and Song, 2024 indicate that green financing not only provides financial returns but also enables wider socio-environmental benefits, thereby ensuring growth in line with sustainability objectives.
In an Indian scenario where steel is an economic impeller as well as a significant polluter, growth opportunities through GF are of special relevance. Research like Gilchrist et al. (2021) and Bucher Koenen et al. (2025) emphasizes that vehicles of finance, such as green bonds, renewable energy funds and green real estate funds, provide investment opportunities and ensure industrial sustainability in the long term. For Indian steel, this translates into leveraging green exports, de-carbonizing risk exposure and matching the government's goal of net-zero by 2070.
At the Odisha level, growth potential becomes nearer reality because the state boasts of large-scale units like Rourkela Steel Plant (RSP). Interviews with top officials (e.g. Dr. V.R. Murty) validate that internal financing and periodic institutional loans (State Bank of India (SBI), Kotak Mahindra, Life Insurance Corporation (LIC) of India, etc.) are channeled strategically toward eco-friendly furnaces, recycling of waste and energy-efficient processes. These instances demonstrate how green financing facilitates growth opportunities by upgrading production while maintaining competitiveness in the domestic as well as global markets.
It comes from the literature on GF products and their contribution to industrial competitiveness, as well as field experiences in Odisha's steel industry. It demonstrates that GF is not merely an environmental instrument but also a driver of growth, thereby making it pivotal to connect GF and SDGs for the steel sector. This supports the paper's hypothesis regarding the structural connection between GF, green innovation and sustainability (Kooijman et al., 2021).
Presence of possible growth prospects through GF significantly impacts the green financing practices.
Incentives for green technology
Awards at the international level, green technology adoption incentives are considered to be the enablers of industrial decarbonization. Financial incentives like subsidies, tax relief, concessional loans and R&D grants reduce the cost hurdles of risky innovations such as renewable integration, hydrogen steelmaking and advanced waste treatment, as per Endres and Rundshagen (2010). Literature also indicates that incentives minimize uncertainty and speed up the commercialization of clean technologies (Wang et al., 2024).
In the Indian situation, the government's Green Steel Roadmap (Xu et al., 2021) and transitioning green taxonomy (Hasan et al., 2013) are crafted to steer incentives to low-carbon operations. Tools such as green bonds, sustainability-linked loans and transition finance incentivize private and public parties to make investments in green technologies. Experts like Selvaraju et al. (2024) point out that these incentives are indispensable for making steel industries compatible with India's 2070 net-zero target and balancing equitable transition strategies.
In Odisha, one of India's biggest integrated steel plants, incentives take a pragmatic application. For example, RSP has been trying out energy-efficient furnaces, waste recycling units and carbon-efficient processes. Industry captains (e.g. Dr. V.R. Murty) during the field interviews stressed that access to financial incentives and concessional loans – sometimes facilitated through banks such as SBI and LIC of India – is instrumental in addressing high initial costs of eco-technologies.
This argument comes from international climate finance writing on incentive frameworks for industrial decarbonization, as well as India's policy blueprints and field experience from Odisha's steel mills. It highlights that in the absence of specific financial incentives, green technologies are still not economically viable for steel industries. This directly serves the purpose of your paper to describe how GF works as a mediator between technological innovation and sustainable development in the steel industry of Odisha (Mishra, 2017).
IGT has a positive impact on green finance practices.
Barriers in assessing green finance
At the international level, access barriers to GF still constitute one of the most urgent issues for carbon-intensive sectors such as steel. For Liu and Wu (2023) and Shen et al. (2024a, b), such barriers comprise high costs of transactions, absence of common green taxonomies, restricted disclosure channels and investor reluctance because of lengthy payback. Studies also indicate that these barriers delay green technology take-up and limit the inflow of capital into climate-conforming projects (Li et al., 2021).
In India, though instruments such as green bonds and sustainability-linked loans exist, access is hampered due to regulatory complexity, lack of concessional interest rates, poor credit enhancement facilities and low investor awareness (Raman et al., 2025). The steel industry also faces difficulties in aligning green projects with coal-based business models, and lenders are therefore cautious of perceived risks.
In Odisha, with a number of integrated steel complexes (Rourkela, Angul and Kalinga Nagar clusters), obstacles are heightened by capital intensity, restricted concessional financing and reliance on internal financing sources. Ground realities from RSP interviews indicate that while industries are interested in hydrogen clusters and renewable energy integration, they struggle to obtain long-term low-cost financing and take recourse to loans from domestic banks such as SBI and Kotak Mahindra Bank or sporadic international credit lines (Neelakantan, 2023).
This argument stems from global research on green transition finance constraints, India's market and policy GF accessibility reports and face-to-face industry interviews within the steel industry of Odisha. Barriers are essential to highlight since they account for the gap between the availability and use of GF. If these barriers are not identified, then sustainable finance initiatives are unable to be properly designed. For this research, Odisha serves as real evidence of how barriers hinder the scaling of GF as a catalyst for sustainable steelmaking (Kharb et al., 2024).
Barriers in assessing green finance have a positive impact on green financial practices in the steel sector.
Social responsibility
On the international stage, GF is strongly associated with CSR, wherein organized financial products and services aim for environmental gains such as renewable energy, waste management and efficiency of resources (Kumar et al., 2024). Investments in such a manner are essential to drive green innovation, as it cuts back on fossil fuel reliance as well as drive sustainable development (Morri et al., 2024). Nonetheless, in line with the pecking order theory (Chen and Deng, 2025), industries tend to depend on internal funds because of aversion to risk, constraining the maximum potential from external financing sources such as equity, debt and subsidies (Brown et al., 2010; Zhai and Yang, 2024).
In Indian steel, CSR and social responsibility (SR) increasingly play a key role in opening up GF. Companies embracing sustainable practices win socially responsible investors and earn global market credibility. For instance, Jindal South West (JSW) Steel's $500 million green bond, linked to the reduction of CO2 goals and the Green Steel Taxonomy by the government supporting electric arc furnaces, recycling of scrap and hydrogen steel production, both reflect how SR enhances finance, sustainability and social well-being integration (Vennila and Sushmitha, 2024).
Within Odisha, which hosts massive integrated steel plants like Rourkela, Angul and Kalinga Nagar, CSR-led initiatives go beyond complacency to dynamic environmental stewardship. Experience through field interviews attests that firms are investing in waste recycling, renewable integration and green-friendly technologies not merely to keep emissions in check but to secure their social license to operate (Hall et al., 2015). This attests to how local industries are operationalizing CSR into tangible steps that enable the flow of GF and the confidence of local communities.
This observation stems from international literature on GF and CSR, Indian industry reports regarding sustainability-linked financing and first-hand observations from Odisha's steel clusters. SR is vital as it stands between financial performance and environmental legitimacy. Demonstrating how CSR boosts GF adoption, in particular that of Odisha's steel sector, this paper addresses the social aspect of sustainability – demonstrating that funding green innovation is not just an economic imperative but a SR (Ejaz et al., 2025).
Social responsibility has a significant positive effect on green finance.
Government support
Internationally, GF is deeply linked with CSR, where concerted financial instruments and services work towards environmental benefits like renewable energy, waste disposal and resource efficiency (Guang-Wen and Siddik, 2022). Such investments are critical to promote green innovation since it reduces dependence on fossil fuels as well as promote sustainable development (Farcean et al., 2023). However, in accordance with the pecking order theory (Beladi et al., 2021), firms are likely to rely on internal capital due to risk aversion, limiting the utilization of the greatest possible from external sources of financing like equity, debt and subsidies (Brown et al., 2005; Yang et al., 2022)
In Indian steel, SR and CSR are increasingly becoming crucial in unlocking GF. Businesses adopting sustainable practices gain socially responsible investors and earn a global market reputation. For example, JSW Steel's $500 million CO2 reduction goal-linked green bond and the Green Steel Taxonomy by the government, favoring electric arc furnaces, scrap recycling and hydrogen steel manufacturing, both indicate how SR uplifts finance, sustainability and social well-being integration (Azam et al., 2023).
In Odisha, home to giant integrated steel complexes such as Rourkela, Angul and Kalinga Nagar, CSR-driven activities transcend complacency to active environmental leadership. Field interview experience bears testimony that companies are spending on waste recycling, renewable integration and green-friendly technologies and not just to contain emissions but to win their social license to operate (Indriastuti and Chariri, 2021). This is a testament to the way local businesses are translating CSR into actionable measures, allowing for GF flows and local confidence.
This conclusion is based on GF and CSR literature from global research, Indian industry reports on sustainability-linked financing and first-hand observations from Odisha's steel clusters. SR is crucial as it sits at the crossroads of financial performance and environmental legitimacy. Showing how CSR enhances GF take-up, specifically of Odisha's steel industry, this paper speaks to the social dimension of sustainability – showing that supporting green innovation is not only an economic necessity but an SR (Zhang, 2024).
Government support in the form of policies, subsidies and incentives positively influences the adoption of green financing practices in the steel manufacturing sectors of Odisha.
Supporting Financial Infrastructure-
At the international level, enabling financial infrastructure is the foundation of GF by establishing mechanisms such as green bond markets, sustainable stock exchanges, ESG-rating platforms and blended finance facilities. These platforms alleviate information asymmetry, increase investor confidence and make capital available for climate-resilient projects (Gilchrist et al., 2021; Mills-Novoa, 2023). In the absence of this infrastructure, even purposefully designed green financial instruments cannot achieve scale, particularly in high-emission sectors like steel.
In the Indian context, the SEBI has made ESG disclosures compulsory, enabling climate performance transparency of steel companies. The Indian GF Taxonomy (2025) and venues such as the green listing of the India International Exchange have provided organized routes for channeling funds into renewable energy and sustainable industrial practices (Selvaraju et al., 2024). In addition, development banks and non-banking financial companies offer blended finance structures, while transition bonds and sustainability-linked loans are increasingly used to support hard-to-abate industries such as steel.
In Odisha, financial infrastructure support is seen in partnerships among public sector banks (e.g., LIC of India, SBI), state-led industrial development corporations and private lenders (e.g., Kotak Mahindra). Interviews with sector specialists at RSP validate that concessional finance and structured loan facilities are in place, though gaps exist when it comes to long-term affordable finance and regulatory guidance. Additionally, the absence of localized ESG rating platforms and disclosure mechanisms holds Odisha's steel industries from being able to tap full access to global green funds.
This argument draws on global sustainable finance infrastructure scholarship, India's regulatory evolution and key findings among Odisha's steel industry stakeholders. Financial infrastructure is essential as it makes the accessibility, affordability and scalability of GF instruments possible. For Odisha's steel industry, a robust financial infrastructure is required in order to link local businesses to international sustainable capital markets. Without strong systems, even the most innovative financial models are not implementable effectively, and hence, this determinant is a significant variable to assess how GF is facilitating sustainability transitions within the steel industry (Faruq and Chowdhury, 2025).
Supporting financial infrastructure (SFI) has a positive impact on the adoption of green finance practices.
Table 2 below highlights the key driving factors of GF discussed in the study, accompanied by their symbols and the relevant literature. It is evident from Table 2 that the driving factors of GF include the initiative for sustainable finance (GINV1), growth prospects via green financing (GINV2) and the incentive for green technology (GINV3), among others. The table also emphasizes the challenges of assessing GF (GINV4) and SR in relation to the broader impact of the subject of the research, SR (GINV5). GS (GINV6) and the support for the financial infrastructure are also key driving factors in the subject of the research (GINV7). The use of relevant literature in the support variables increases the theoretical aspects of the concepts discussed and the rationale of the variables chosen to be used in conducting the empirical study in the paper.
Variable description
| Sl. No. | Driving factors for green finance | Symbol | Supporting literature |
|---|---|---|---|
| 1 | Initiative for sustainable finance | GINV1 | Das and Mishra (2025) |
| 2 | Growth prospects through green financing* | GINV2 | Lee and Song (2024) |
| 3 | Incentives for green technology | GINV3 | Wang et al. (2024) |
| 4 | Barriers in assessing green finance* | GINV4 | Raman et al. (2025) |
| 5 | Social responsibility* | GINV5 | Ejaz et al. (2025) |
| 6 | Government support | GINV6 | Zhang (2024) |
| 7 | Supporting financial infrastructure | GINV7 | Faruq and Chowdhury (2025) |
Green financing positively influences corporate strategies by improving financial performance, fostering innovation and enhancing stakeholder engagement, leading to greater overall sustainability and competitiveness in firms across India. It also significantly contributes to sustainable development by creating environmental activities, promoting resource efficiency and encouraging social equity among firms. Specifically, firms that increase their green financing will demonstrate improved sustainability outcomes, such as lower carbon emissions, lower resource consumption and greater community engagement compared to firms that do not prioritize GF. “From the above literature review following hypothetical framework could be developed for the study, which is analyzed further to establish its significance”.
Literature review sets theoretical arguments regarding GF and sustainability in the steel sector. Based on these findings, the research methodology sets out the systematic procedure followed to examine determinants and infrastructure facilitating Odisha's steel sector sustainability.
Proposed theoretical model
Considering the above literature review Figure 1 shows the variables and their supporting literature.
The diagram illustrates relationships around green finance. On the left, seven oval nodes are arranged vertically and labeled from top to bottom as “G I N V 1”, “G I N V 2”, “G I N V 3”, “G I N V 4”, “G I N V 5”, “G I N V 6”, and “G I N V 7”. Thin connecting arrows from each G I N V node converge toward a central oval labeled “Green Finance”. To the right of “Green Finance” are three vertically arranged rectangular boxes labeled from top to bottom as “High”, “Medium”, and “Low”. A leftward arrow from “Low” points to “Green Finance”.Thematic framework of green financing. Source: Authors’ own
The diagram illustrates relationships around green finance. On the left, seven oval nodes are arranged vertically and labeled from top to bottom as “G I N V 1”, “G I N V 2”, “G I N V 3”, “G I N V 4”, “G I N V 5”, “G I N V 6”, and “G I N V 7”. Thin connecting arrows from each G I N V node converge toward a central oval labeled “Green Finance”. To the right of “Green Finance” are three vertically arranged rectangular boxes labeled from top to bottom as “High”, “Medium”, and “Low”. A leftward arrow from “Low” points to “Green Finance”.Thematic framework of green financing. Source: Authors’ own
It is presumed in the theoretical model that the uptake of GF in Odisha steel industries can be categorized into High (GISDG1), Medium (GISDG2) and Low (GISDG3) levels, based on the intensity of specific determinants.
Independent variables (Determinants): Initiatives for Sustainable Finance (ISF) – industry/financial initiatives encouraging green funds. Growth Prospects through Green Financing (GP) – anticipated long-term industrial and eco-friendliness advantages. IGT – subsidy, tax rebate or policy incentives for eco-innovation. Barriers in Accessing GF (BGF) – financial, regulatory or operational barriers inhibiting adoption. SR – CSR and people-driven sustainable practices. GS – regulatory frameworks, policy and financial support. SFI – banks’ availability, green bonds, impact funds, etc.
Dependent variable: GF Adoption Level (GFAL) – as High, Medium or Low. All Independent Variables (ISF, GP, IGT, BGF, SR, GS, SFI) → Influence → GF Adoption Level (High/Medium/Low).
The theoretical framework is crucial as it bridges determinants of GF to adoption levels in the Odisha steel industry. It defines enabling and inhibiting factors, bridges theory and practice and offers a systematic foundation for empirical analysis and policy recommendations for sustainable industrial growth.
Research methodology
By analyzing the relation of different independent variables of GF, this study adopted a Quantitative Research Design. Data were collected through a survey method. A structured questionnaire was developed for measuring the proposed research model in the study. All the items for the questionnaire were taken from various sources of literature. It includes items related to specifying the initiative for sustainable finance, growth prospects through green financing, IGT, barriers in assessing GF, SR, GS and supporting financial infrastructures, etc.
Study site: – This study was conducted in various steel industries situated in Odisha. The study has focused on the steel manufacturing industries located within the state of Odisha, which is one of India's primary industrial hubs. Odisha is known for its rich mineral resources, particularly iron ore and therefore, an ideal place for steel production. Given its vast deposits of natural resources, many large-scale steel manufacturing plants in both public and private sectors have been attracted to the state. Odisha produces a considerable percentage of the total steel produced in India, which makes it a good place to study the GF aspect of this industry. For our study, we have taken TATA STEEL at Angul, RSP at Rourkela, Jindal Steel and Power Limited at Angul and TATA Steel at Kalinga Nagar.
Questionnaire development – A structured questionnaire was developed for measuring the proposed research model in this study. The constructs and variables for this study were selected based on a thorough review of certain literature, aligning with research objectives. All the objectives for the questionnaire were taken from various literature studies. Growth Prospect from Green financing from Flandrick and Kooijmans (2024), IGT from Wang et al. (2024), Barriers in Assessing GF from Harnett (2018), SR from Ejaz et al. (2025), GS from Zhang (2024), SFI from Murthy et al. (2024). In order to check the importance of the variables a pilot test was conducted. These sources ensured that the questionnaire was grounded in validated items from prior empirical research, which enhanced its credibility.
Data collection
A mixed-method research strategy was utilized in this study, integrating both quantitative and qualitative methods to secure overall insights. Quantitative information was gathered using a structured questionnaire, while the qualitative information was gathered through face-to-face interviews and field visits. The structured questionnaire was custom-made to quantify the suggested research model and was constructed on the basis of constructs established in the current literature on environmental sustainability and green financing. All the items in the questionnaire were tested through a seven-point Likert scale, from 1 = strongly agree to 7 = strongly disagree. To achieve internal consistency, Cronbach's Alpha was used. 171 responses were gathered through a convenient random sampling method, which is one of the most commonly used non-probability sampling techniques because of its ease of use, cost-effectiveness and practicality (Jager et al., 2017).
This study used an Ordinal regression analysis method to assess the research model. Descriptive analyses followed by inferential analysis are investigated to identify the factors contributing to GF by the steel industries. In this study, the Green Investment aligned with the Sustainable Development Goals (GISDG) is the dependent variable, with threshold values of 1, 2 and 3 and GINV1, GINV2, GINV3, GINV4, GINV5, GINV6 and GINV7 are independent variables.
Ordinal regression is utilized in this research since the GF Adoption Level (high, medium, low) dependent variable is ordinal and captures ranked outcomes rather than continuous values. This technique efficiently predicts the effects of determinants like GS, incentives and financial infrastructure on adoption levels. Existing literature affirms that it is ideal for ordered outcomes (Agresti, 2010; O'Connell, 2006), which makes it fitting for examining sustainability-associated financial structures within Odisha's steel sector.
Convenient sampling technique: Convenience sampling is employed in the study since Odisha's steel industries constitute a wide and spread population, and it is not easy to reach all respondents. Convenience sampling enables data to be gathered from readily available managers, authorities and stakeholders who know GF practices. Existing research indicates that convenience sampling works in exploratory research where time, accessibility and resource constraints restrict the use of random sampling (Etikan et al., 2016). Therefore, it offers pragmatic feasibility in exploring determinants of GF adoption in Odisha's steel industry.
Table 3 case processing summary shows the distribution of the three levels of GF adoption (GISDG) responses. From a total of 171 valid cases, 45 respondents (26.3%) reported a high degree of GF adoption (GISDG-1) and 65 respondents (38.0%) reported a medium degree of adoption (GISDG-2). The last 61 respondents (35.7%) reported a low degree of adoption (GISDG-3). There were no missing responses, providing total reliability of the data set.
Case processing summary
| N | Marginal percentage | ||
|---|---|---|---|
| GISDG-1 | 1 | 45 | 26.3% |
| 2 | 65 | 38.0% | |
| 3 | 61 | 35.7% | |
| Valid | 171 | 100.0% | |
| Missing | 0 | ||
| Total | 171 | ||
Model-fitting information is employed here to assess whether the addition of independent variables enhances the explanatory strength of the research model noticeably. It assists in establishing the goodness-of-fit of the model overall, thereby ensuring that the determinants of GF found are significant in explaining adoption levels across Odisha's steel industries.
The model fit outcomes firmly validate the hypothesis that green financing drivers are significant in impacting sustainable actions in the steel industry.
Table 4 shows the model fit statistics for the suggested research model. The “Intercept Only” model registers a −2 Log Likelihood score of 367.258, while the “Final Model” registers a considerably lower score of 201.183. Such a decrease attests to the fact that the inclusion of the independent variables pertaining to green financing significantly enhances the explanatory ability of the model.
Model fitting information
| Model | Model fitting criteria | Likelihood ratio tests | ||
|---|---|---|---|---|
| −2 log likelihood | Chi-square | df | Sig. | |
| Intercept only | 367.258 | |||
| Final | 201.183 | 166.074 | 14 | 0.000 |
Likelihood ratio test also testifies to this improvement, with the Chi-Square value being 166.074 with 14 degrees of freedom, which is statistically significant at p < 0.001. This establishes that the independent variables like ISF, growth opportunities, green technology incentives, finance access obstacles, SR, government incentives and infrastructure support for finance, all work together towards explaining the variation in the level of adoption of GF (GISDG) for the steel industries in Odisha.
This table is significant as it verifies that the determinants of GF selected – namely, incentives, barriers, GS and financial infrastructure – play significant roles in explaining the adoption rate of green financing among Odisha's steel industries. It reinforces that the research model proposed is statistically significant in researching sustainable development in the industry.
Description of Table (Goodness-of-Fit):
Table 5 contains the goodness-of-fit statistics of the model. The Pearson Chi-Square value is 2222.551 with 58 degrees of freedom and the Deviance Chi-Square value is 199.299 with 58 degrees of freedom, both significant at p < 0.001. The significance values suggest that the model explains significant variation in the data and that the independent variables have a joint effect on the adoption levels of GF (GISDG) in Odisha's steel industries.
Goodness-of-Fit
| Chi-square | df | Sig. | |
|---|---|---|---|
| Pearson | 2222.551 | 58 | 0.000 |
| Deviance | 199.299 | 58 | 0.000 |
Goodness-of-fit is important for this research since it measures how good the suggested research model fits the observed data. It ensures that the determinants of GF identified, including GS, financial infrastructure and SR, correctly capture the actual adoption levels of sustainable financing in the steel industry.
Table 6 presents the Pseudo R-Square values, which represent the explanatory power of the model. The Cox and Snell value (0.621) implies that approximately 62.1% of the variance in GF adoption is explained by the independent variables. The Nagelkerke value (0.701), an adjusted figure, reflects a higher explanatory power of 70.1%. The McFadden value (0.447) also reflects a goodness of fit for social science studies. Together, these values indicate that the model accounts for a great deal of variation in the adoption levels of green financing (GISDG) among Odisha's steel sectors.
Model fit
| Pseudo R-square | |
|---|---|
| Cox and Snell | 0.621 |
| Nagelkerke | 0.701 |
| McFadden | 0.447 |
Pseudo R-Square is significant within this paper since it measures how good the independent variables of GS, financial infrastructure and IGT explain GF adoption variations. It enhances model validity to ensure that the determinants have significant effects on green financing practices within the steel industry.
The most significant hindrances to GF uptake in Odisha's steel sectors are restricted incentives (GINV3), finance access barriers (GINV4) and poor GS (GINV6). These require immediate attention. In contrast, SR (GINV5) and financial infrastructure (GINV7) have the potential to act as positive facilitators but need to be enhanced.
The Parameter Estimates table is significant since it reveals which GF determinants play a significant role in driving the adoption levels of Odisha's steel industries. It presents clear evidence regarding the reasons why sustainable financing practices are promoted or discouraged by revealing the direction (positive/negative) and the magnitude (odds ratio) of every variable.
For this topic, the table emphasizes that access barriers to GF, insufficient incentives and poor GS are the most potent barriers, whereas SR and providing financial infrastructure support have potential positive effects. This evidence-based observation is vital for policy making, industry planning and enhancing the infrastructure of green financing to guarantee sustainable development in the steel industry.
The ordinal regression parameter estimates capture significant findings on the determinants of GF adoption in the Odisha steel sector. Plans for GF initiatives (GINV1) indicate a weak but statistically insignificant effect, which suggests that although there are plans, their influence on levels of adoption remains weak. Likewise, future growth opportunities through green financing (GINV2) indicate a weak positive correlation but remain insignificant, showing appreciation of future benefit without concrete contribution. Conversely, green technology incentives (GINV3) have a very strong negative and highly significant impact, indicating that inadequate incentives deter industries from embracing green measures. Most significantly, hindrance in access to GF (GINV4) has a very strong negative and highly significant impact, reinforcing it as the primary hindrance for uptake. SR (GINV5) is positively but weakly significant, suggesting that CSR efforts can encourage adoption, albeit inconsistently. GS (GINV6) reveals a significant negative impact, which means that existing policy or interventions are either weak or ineffective. Lastly, financial infrastructure support (GINV7) reveals mixed findings with poor significance, indicating its potential role but weak strength in encouraging adoption.
Table 7 shows the result of the multinomial logistic regression model for analyzing the effects of the identified drivers of Driving Factors of GF. In this table, we find that GINV3 – Green Technology Incentivization – has a negative and highly significant influence at a low threshold level. Another highly significant factor with a strong negative influence at all thresholds is GINV4 – Barriers in Assessing GF. Additionally, GINV6 – Government Support – has a negative and highly significant influence. It appears that GINV4 – Barriers in Assessing GF – has a strong negative influence on both parameter types. On the other hand, GINV2 – Growth Prospects with Green Financing – has a negative and highly significant influence on all thresholds. However, SR – GINV5 – has a negative and highly significant influence at all thresholds. GINV7 – Supporting Financial Infrastructure – has a negative and highly significant influence at all thresholds. On the other hand, GINV1 – Initiative for Sustainable Finance – has a negative influence in all thresholds. Therefore, Table 7 clearly indicates that barriers in terms of structure, policy support and technology enablement influence GF.
Parameter estimates
| GINV | B | Std. error | Wald | df | Sig. | Exp(B) | 95% confidence interval for Exp(B) | ||
|---|---|---|---|---|---|---|---|---|---|
| Lower bound | Upper bound | ||||||||
| 1 | Intercept | 34.531 | 8.807 | 15.373 | 1 | 0.000 | |||
| GINV1 | −0.442 | 0.370 | 1.429 | 1 | 0.232 | 0.643 | 0.311 | 1.327 | |
| GINV2 | 0.244 | 0.414 | 0.346 | 1 | 0.556 | 1.276 | 0.566 | 2.875 | |
| GINV3 | −1.335 | 0.452 | 8.733 | 1 | 0.003 | 0.263 | 0.108 | 0.638 | |
| GINV4 | −2.907 | 0.721 | 16.268 | 1 | 0.000 | 0.055 | 0.013 | 0.224 | |
| GINV5 | 0.981 | 0.533 | 3.391 | 1 | 0.066 | 2.667 | 0.939 | 7.579 | |
| GINV6 | −1.127 | 0.420 | 7.197 | 1 | 0.007 | 0.324 | 0.142 | 0.738 | |
| GINV7 | −1.079 | 0.555 | 3.772 | 1 | 0.052 | 0.340 | 0.115 | 1.010 | |
| 2 | Intercept | 54.117 | 10.407 | 27.040 | 1 | 0.000 | |||
| GINV1 | −1.398 | 0.454 | 9.472 | 1 | 0.002 | 0.247 | 0.101 | 0.602 | |
| GINV2 | 0.366 | 0.495 | 0.545 | 1 | 0.460 | 1.442 | 0.546 | 3.808 | |
| GINV3 | −2.000 | 0.520 | 14.770 | 1 | 0.000 | 0.135 | 0.049 | 0.375 | |
| GINV4 | −4.701 | 0.808 | 33.865 | 1 | 0.000 | 0.009 | 0.002 | 0.044 | |
| GINV5 | −1.258 | 0.589 | 4.555 | 1 | 0.033 | 0.284 | 0.090 | 0.902 | |
| GINV6 | −0.549 | 0.431 | 1.620 | 1 | 0.203 | 0.578 | 0.248 | 1.345 | |
| GINV7 | 0.582 | 0.558 | 1.088 | 1 | 0.297 | 1.790 | 0.599 | 5.342 | |
Note(s): a. The reference category is: 3
Table 8 displays the outcome of the likelihood ratio tests for all independent variables in the model. The Chi-Square values and p-values reflect the relative contribution of every determinant of GF to the prediction of adoption levels (GISDG).
Model fitting
| Effect | Model fitting criteria | Likelihood ratio tests | ||
|---|---|---|---|---|
| −2 log likelihood of reduced model | Chi-square | df | Sig. | |
| Intercept | 252.698 | 51.515 | 2 | 0.000 |
| GINV1 | 212.968 | 11.785 | 2 | 0.003 |
| GINV2 | 201.748 | 0.565 | 2 | 0.754 |
| GINV3 | 222.850 | 21.666 | 2 | 0.000 |
| GINV4 | 299.692 | 98.509 | 2 | 0.000 |
| GINV5 | 225.039 | 23.856 | 2 | 0.000 |
| GINV6 | 209.849 | 8.666 | 2 | 0.013 |
| GINV7 | 215.495 | 14.312 | 2 | 0.001 |
Substantial predictors (p < 0.05): GINV1 (initiative for sustainable finance), GINV3 (IGT), GINV4 (finance barriers in accessing it), GINV5 (SR), GINV6 (government incentives) and GINV7 (SFI). These factors have substantial impacts on green financing adoption.
Non-substantial predictor (p > 0.05): GINV2 (growth opportunities using green financing), which has minimal statistical significance on levels of adoption.
In general, the table establishes that green technology incentives (GINV3) and barriers in accessing finance (GINV4) are the strongest drivers, whereas growth opportunities (GINV2) are not a determining factor among Odisha's steel firms.
Conclusion and implication
At the international level, GF has become a crucial tool for integrating industrial growth with environmental sustainability. Global frameworks like the Paris Agreement and the United Nations SDGs focus on the use of sustainable financing for lowering carbon emissions and developing green technologies. Nations across the world are implementing tools like green bonds, carbon market exchanges and green investment products to support financing industrial change, especially in high-emission industries such as steel.
In India, GF has also assumed strategic significance as the government continues to urge a low-carbon economy by launching schemes such as the National Hydrogen Mission, renewable energy development and support for green steel production. Green bonds by Indian corporates and banks are becoming financial instruments to support sustainable projects. Policy momentum notwithstanding, there are still issues related to low awareness, lack of access to finances and the technological gap, especially in energy-intensive sectors.
Given that Odisha is India's steel capital, embracing GF is both a need and a challenge. With increasing production capacity, the state of Odisha is confronted with the double challenge of economic development and environmental sustainability. The state has already shown its commitment through hydrogen-ready steel plants, renewable energy initiatives and industry-government partnerships. However, mass-level adoption of GF is still in small numbers, as the study's conclusion of having a majority of stakeholders in the medium adoption level stands out.
Methodological assessment confirms that the research model is statistically valid and describes the adoption rates of GF by Odisha's steel industry satisfactorily. The tests of model fitness establish that there is substantial improvement in explanatory power with the incorporation of determinants and the goodness-of-fit and Pseudo R-Square measures establish the strength of the model. The estimates of parameters establish that finance access barriers (GINV4), low incentives (GINV3) and poor GS (GINV6) are significant hindrances, whereas SR (GINV5) and facilitation of financial infrastructure (GINV7) have the potential to act as enabling factors.
The findings align directly with the real challenges and possibilities of Odisha's steel industry. Financial access constraints, low incentives and poor government facilitation reflect actual constraints on firms in green practice adoption. On the other hand, SR and financial infrastructure enable potential highlights, increasing awareness, but in need of more vigorous institutional support. In reality, this points towards the necessity of focused government policies, streamlining green credit access and industry–finance partnerships. By filling these gaps, Odisha can speed up its green transformation, improve global competitiveness and align steel production with national climate ambitions as well as international sustainability obligations.
The research concludes that GF is crucial for Odisha's steel industry's sustainable transition, providing a route that brings together environmental stewardship and industrial competitiveness. Although there has been progress, the comparatively low percentage of high adoption cases indicates that greater financial infrastructure, specifically targeted incentives and policy intervention, is necessary. By surmounting obstacles and capitalizing on drivers, Odisha can spearhead India's green steel revolution, tying its industrial development to both national climate targets and international sustainability objectives.
The findings suggest that Odisha's future development in the steel sector relies on addressing financial access, poor incentives and a lack of GS as barriers. The improvement of financial infrastructure and encouraging SR can serve as future adoption enablers. This necessitates a need for specialized policies, creative financial products and international partnerships to help address India's climate targets. Through filling these gaps, Odisha's steel industry can achieve long-term competitiveness and become a leader in India's green steel transition.
In a very fundamental sense, the introduction of GF in the steel sector in Odisha is not merely vital for attaining environmental sustainability and financial growth but also for making the state a leader in sustainable industrialization in the world.
