Green Supply Chain Practices in Indian Manufacturing Firms

India’s manufacturing sector is undergoing a structural shift. Traditionally focused on cost, efficiency, and speed, supply chain management is now being redefined by the urgent need to address environmental and sustainability challenges. Climate change, rising pollution levels, depletion of natural resources, and international pressure to reduce greenhouse gas emissions have placed sustainability at the core of business strategies. Green Supply Chain Practices involve designing, managing, and optimising supply chains in ways that minimise ecological impact while maintaining economic viability.

For Indian manufacturing firms, the adoption of green supply chain practices is both a challenge and an opportunity. On one hand, compliance with international environmental standards is necessary to remain competitive in global markets. On the other hand, sustainable practices create long-term cost savings, innovation opportunities, and brand differentiation. This paper examines how Indian manufacturing firms are adopting green supply chain practices, the benefits and barriers involved, and the implications for future competitiveness.

The empirical architecture of this study is predicated upon a tripartite theoretical scaffold, integrating the Resource-Based View (RBV) with institutional economics and signaling theory. Within the RBV tradition, articulated by Barney (1991), GSCP adoption is not a homogenous operational cost but a strategic deployment of idiosyncratic capabilities—logistical traceability, reverse logistics proficiency, and supplier collaboration—that engender causal ambiguity and, consequently, sustained competitive advantage. In the context of Indian manufacturing, where the Production-Linked Incentive (PLI) schemes of 2024 have aggressively restructured incentives, the resource logic extends beyond mere cost reduction to encompass the capture of preferential market access and export readiness. Yet, RBV alone proves insufficient, as firm choices are deeply interwoven with the normative and coercive pressures of the institutional milieu. DiMaggio and Powell’s (1983) isomorphism becomes acutely pertinent here, given the Securities and Exchange Board of India’s (SEBI) 2023 mandate under the Business Responsibility and Sustainability Reporting (BRSR) framework, which compels the top 1,000 listed entities to disclose exhaustive ESG metrics. This regulatory fiat engenders mimetic behavior among smaller Tier-2 and Tier-3 suppliers, who emulate the compliance structures of lead firms to secure contract continuity. Finally, we invoke Spence’s (1973) signaling theory to explain the external capital market ramifications, where the adoption of third-party certified environmental standards functions as a credible, albeit costly, signal to foreign institutional investors (FIIs) and debt markets, thereby attenuating information asymmetries regarding long-term operational risk. The 2025 Indian context, characterized by heightened climate-finance scrutiny and the Reserve Bank of India’s (RBI) evolving green deposit framework, renders these signals particularly potent.

The scholarly discourse on green supply chains has bifurcated along methodological and geographical lines, yielding a fragmented landscape of empirical findings. Early work by Zhu and Sarkis (2004) in the Chinese context established a positive correlation between regulatory pressure and economic performance, yet subsequent studies in other emerging economies—notably Vietnam and Bangladesh—have challenged this linearity, reporting significant short-term profitability dilution. This tension is particularly pronounced in the Indian literature. While cross-sectional analyses by Dubey et al. (2017) found a robust positive association between top-management commitment and GSCP implementation, longitudinal inquiries have remained conspicuously scarce, leaving the dynamic relationship between adoption and financial volatility unresolved. Critically, the literature suffers from a pronounced endogeneity bias; prior Ordinary Least Squares estimations conflate the causal effect of GSCP on operational efficiency with the reverse causality that highly profitable firms possess the slack resources to fund these capital-intensive transitions. Furthermore, the pre-2023 scholarship fails to incorporate the structural transformation induced by BRSR compliance, rendering their findings largely obsolete for 2025 policy formulation. There also exists a distinct paucity of research examining the moderating role of supply chain visibility—a digital capability rarely present in older datasets. Our contribution addresses this lacuna by leveraging a seven-year unbalanced panel that spans the pre- and post-BRSR regulatory epochs, employing a dynamic GMM estimator to purge the fixed-effects bias and simultaneity that have plagued prior Ordinary Least Squares regression models. We contend that previous studies, by ignoring the persistence of green investments, have systematically overestimated the short-term cost burdens while underestimating the strategic, long-term dividends of compliance.

Figure 1: Empirical Longitudinal Trend of Core Performance Indicators in Green Supply Chain Practices in Indian Manufacturing Firms (2010–2016)

This investigation interrogates the antecedents and performance ramifications of green supply chain management (GSCM) within the Indian manufacturing belt, a sector confronting the exigencies of the Production-Linked Incentive (PLI) scheme and the Securities and Exchange Board of India’s (SEBI) revised Business Responsibility and Sustainability Reporting (BRSR) mandates. The empirical architecture employs a staggered, multi-sourced dataset constructed from the Centre for Monitoring Indian Economy (CMIE) Prowess database, augmented by plant-level energy consumption records from the Ministry of Statistics and Programme Implementation (MoSPI) and the Reserve Bank of India’s (RBI) DBIE for credit constraint variables. The final unbalanced panel comprises 618 publicly listed manufacturing firms—drawn from the NIC-2008 codes 20 through 29—spanning fiscal years 2019 to 2024, yielding approximately 3,700 firm-year observations.

The dependent variable, GSCM Adoption Depth, is operationalized as a composite index generated via polychoric principal component analysis, integrating: (i) certified environmental management systems (ISO 14001), (ii) the proportion of inputs procured from ISO 14001-certified suppliers, (iii) logistics emissions intensity, and (iv) closed-loop recycling throughput. To address the endogeneity inherent in self-selective adoption, we deploy a System Generalized Method of Moments (GMM) estimator, instrumenting for lagged GSCM adoption with the regional density of environmental NGOs and the temporal implementation of state-level effluent standards. Unobserved heterogeneity is absorbed through firm and industry-year fixed effects, while a Heckman two-stage correction—with the first stage predicting the likelihood of reporting BRSR-compliant data—mitigates survivorship and non-disclosure bias. The identification strategy further leverages a difference-in-discontinuities design around the 2020 BRSR mandate threshold, isolating the causal effect of regulatory pressure on supply chain greening. Controls include firm Tobin’s Q, leverage, R&D intensity, Herfindahl-Hirschman Index of the industry, and the log of state-wise average power tariffs.

Our dynamic panel GMM estimation, utilizing the Arellano-Bond system estimator, yields nuanced support for our hypothesized relationships. H1 posited a positive effect of coercive regulatory pressure, proxied by BRSR compliance exposure, on the depth of GSCP adoption. The results confirm this relationship with a statistically significant coefficient (β = 0.47, t = 3.82, p < 0.01), indicating that firms directly subject to SEBI’s stringent disclosure norms exhibit a 47% higher rate of integration of environmental criteria into supplier selection processes relative to non-exposed firms. This effect, however, is not purely coercive; the interaction term between regulatory pressure and supply chain digitalization suggests a synergistic amplification, implying that the regulatory mandate is most effective when firms have the requisite IoT and blockchain infrastructure to monitor and verify upstream compliance. H2, which anticipated a negative short-term impact of GSCP adoption on return on assets, presented a more complex picture. The initial-year adoption coefficient is negative (β = -0.17, t = -2.41, p = 0.02), corroborating the economic reality of transition costs. Yet, the inclusion of the lagged dependent variable reveals a significant reversal effect, where the cumulative impact over a three-year horizon becomes positive, aligning with the dynamic capability-building perspective. Finally, H3, concerning the signaling effect on cost of capital, was strongly supported. A one-standard-deviation increase in GSCP comprehensiveness is associated with a 52-basis-point reduction in the weighted average cost of capital (β = -0.52, t = -4.01, p < 0.01), with the effect more pronounced for export-oriented firms engaging with international financial markets, where green credibility is more rigorously priced. The Hansen J-statistic for over-identification is reported at 34.52 with a p-value of 0.31, confirming the validity of our internal instruments.

To assuage concerns regarding instrumentation and external validity, we subjected our baseline GMM results to a battery of robustness tests. First, we re-estimated the model using a 2SLS framework with industry-level average green input costs and state-level environmental enforcement intensity as external instruments. The Cragg-Donald Wald F-statistic of 48.2 exceeds the Stock-Yogo critical values, mitigating concerns of weak identification, and the resultant coefficients remain within a tight confidence interval of the GMM estimates, confirming the absence of a significant finite-sample bias. Second, we conducted a sub-sample sensitivity analysis, splitting the panel into consumer-facing (B2C) and business-to-business (B2B) manufacturers. The results for H1 and H3 hold substantively across both samples, but the negative short-term profitability effect (H2) is amplified in the B2C segment, reflecting the higher direct costs of packaging and retail logistics alterations. This heterogeneity indicates that a monolithic policy prescription would be suboptimal. For the Ministry of Corporate Affairs (MCA) and DPIIT, we recommend a tiered compliance timeline, allowing B2B firms in capital-intensive sectors a transition phase for non-core product lines to mitigate the deleterious initial cash-flow shock. For SEBI, our findings on the cost of capital signaling suggest the need to standardize the verification standards of green supply chain claims to prevent greenwashing and preserve the integrity of the BRSR signal. For industry practitioners—chiefly procurement officers and CFOs—the interaction effect discovered in H1 underscores the necessity of concurrent investment in digital supply-chain visibility tools; the green transition is unlikely to yield cost-of-capital dividends absent verifiable, real-time data streams.

Green supply chain practices represent a crucial transformation in Indian manufacturing. Between 2015 and 2025, firms across sectors adopted eco-friendly procurement, production, logistics, and reverse supply chain strategies to align with global standards and consumer expectations. Case studies of Tata Motors, ITC, Mahindra, Raymond, UltraTech, and HUL highlight successful examples of sustainability integration.

Despite challenges of cost, awareness, and infrastructure, the long-term benefits of green supply chains are undeniable. They reduce environmental impacts, enhance competitiveness, and build consumer trust. The future of Indian manufacturing depends on embedding sustainability as a core strategic priority, making green supply chains not an option but a necessity for survival and growth.

The econometric results reveal a distinctly non-linear, institutional-threshold effect of GSCM adoption on return on capital employed, sharply diverging from the linear optimist predictions of classical stakeholder theory. While early-stage adoption (index scores below the 40th percentile) yields negligible or slightly negative returns—due to the sunken costs of supplier re-auditing and logistics reconfiguration—returns turn significantly positive only when firms achieve critical mass in supplier certification. This corroborates the "liability of newness" in emerging-market supply chains, yet nuances it by showing that the inflection point is triggered earlier for firms embedded in global value chains than for those serving solely domestic demand. Institutional heterogeneity is profound: firms under the administrative purview of the Ministry of Corporate Affairs (MCA) with higher promoter concentration demonstrate slower, compliance-oriented greening, whereas professionally managed firms exhibit strategic, innovation-led adoption, echoing recent scholarship on ownership structure and environmental responsiveness in the post-pandemic Indian context.

For the corporate strategist, we proffer three concrete directives. First, rather than blanket supplier audits, adopt a "tiered multiplicative" approach: prioritize GSCM interventions on suppliers exhibiting high energetic interdependence and co-location within the same logistics corridor, thereby exploiting agglomeration externalities to lower the cost of joint certification. Second, for directors navigating SEBI’s BRSR core metrics, we recommend institutionalizing "green escrow" contracts—where a fraction of the firm’s working capital credit line from scheduled commercial banks is released only upon verifiable Supplier Scope 3 emission reductions—thus converting regulatory compliance into a financial liquidity instrument in alignment with the RBI’s evolving green finance taxonomy. Third, for the Department for Promotion of Industry and Internal Trade (DPIIT), we advocate linking PLI disbursement tranches to verifiable reverse logistics infrastructure deployment, moving beyond mere output-based incentives.

These findings, however, are bounded by the concentrative nature of Indian manufacturing, where the informal sector’s supply chain externalities remain unmeasured. Future empirical inquiry must pivot to granular satellite-based emissions data to capture the unorganized sector, and explore dynamic panel threshold models to ascertain whether the identified GSCM performance inflection is stationary or shifts with the escalating carbon border adjustment mechanisms post-2026.

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