Green Supply Chain Practices in Indian Manufacturing Firms

The globalization of trade and industrial expansion has increased concerns about environmental degradation. Manufacturing firms, which consume large quantities of raw materials and generate waste, are particularly under scrutiny. Traditional supply chain practices often focused exclusively on cost reduction, efficiency, and speed. However, the growing awareness of climate change, resource scarcity, and consumer activism has shifted the focus toward green supply chain management, which integrates environmental considerations into procurement, production, distribution, and reverse logistics.

In India, the concept of green supply chains gained momentum after the implementation of environmental policies such as the National Action Plan on Climate Change and the introduction of stricter regulations under the Ministry of Environment, Forest and Climate Change. Coupled with rising expectations from multinational corporations and global buyers, Indian firms are increasingly aligning their supply chain strategies with environmental objectives. Yet, the journey is uneven, with large corporations taking the lead while small and medium enterprises face challenges in adopting green practices.

The empirical interrogation of green supply chain practices (GSCP) within the Indian manufacturing milieu is theoretically scaffolded by a triangulation of the Resource-Based View (RBV), Institutional Theory, and Signaling Theory. The RBV, originating from the seminal work of Wernerfelt (1984) and Barney (1991), posits that a firm’s competitive advantage derives from its unique, inimitable resource bundles. In this context, GSCP—encompassing reverse logistics, green procurement, and eco-design—are conceptualized not as compliance costs but as dynamic capabilities that engender process innovation and operational efficiency, thereby generating a quasi-rent that is difficult for laggards to replicate. However, the Indian regulatory landscape, particularly the post-2020 emphasis on the Environment, Social, and Governance (ESG) framework by the Securities and Exchange Board of India (SEBI), exerts coercive and normative isomorphic pressures that complement this resource-based logic. Institutional Theory, following DiMaggio and Powell (1983), explains that firms adopt GSCP to secure legitimacy with stakeholders, including foreign buyers and domestic financial institutions, who increasingly screen for environmental compliance.

The Indian context of 2021 is uniquely bifurcated. Here, Signaling Theory (Spence, 1973) becomes salient: manufacturing firms utilize certifications such as ISO 14001 or public disclosures of carbon footprints to signal unobservable quality and environmental commitment to discerning investors, mitigating information asymmetry in a market where greenwashing is a pervasive risk. The theoretical mechanism, therefore, is not a linear cost-benefit calculus but a strategic interplay where resource heterogeneity determines the capacity for adoption, while institutional pressures and signaling incentives determine the velocity of such adoption. This framework is particularly apt for India, where the informal sector's prevalence and heterogeneous enforcement of environmental regulations create a stark divergence in the strategic value derived from GSCP, suggesting that the translation of green investments into financial performance is contingent upon a firm’s market positioning and regulatory exposure.

The extant scholarship on the nexus between GSCP and firm performance reveals a fractured and often contradictory landscape. Early empirical work in developed economies, such as that by Zhu and Sarkis (2004), frequently reported a positive, albeit modest, correlation between green supply chain integration and operational performance, driven primarily by consumer pressure. However, the transposition of these findings to emerging markets has been problematic. Studies from Chinese manufacturing contexts (e.g., Lai and Wong, 2012) have pointed to a U-shaped relationship, where the initial costs of green investment severely depress profitability before a threshold of scale and learning effects is reached. Conversely, a counter-current of literature, including work by Gopal and Thakkar (2016) within the Indian automotive sector, has argued that the cost of compliance in a price-sensitive domestic market outweighs the reputational gains, particularly for Tier-2 and Tier-3 suppliers who lack direct exposure to international markets. This suggests that the performance implications of GSCP are highly contingent upon a firm’s position in the global value chain.

Critically, the literature suffers from a significant methodological lacuna. The vast majority of prior studies employ cross-sectional survey data, which is inherently susceptible to common method bias and fails to account for the dynamic, persistent nature of profitability (Wibbens and Siggelkow, 2020). Furthermore, there is a conspicuous dearth of research addressing the period immediately following the COVID-19 supply chain disruptions and the concurrent tightening of ESG disclosure norms by the Ministry of Corporate Affairs (MCA) in India. This paper addresses this gap by utilizing panel data spanning 2015–2021 and a system GMM estimator, which explicitly corrects for endogeneity arising from reverse causality—whereby high-performing firms self-select into GSCP adoption. In doing so, we move beyond the static snapshot of prior literature to provide a dynamic causal estimate that is conspicuously absent from the conversation regarding Indian manufacturing performance.

Academic research emphasizes the critical role of GSCM in enhancing both organizational and environmental performance as observed by Babu & Natarajan (2013). Srivastava defined GSCM as integrating environmental thinking into supply chain management, including product design, material sourcing, manufacturing, delivery, and end-of-life management. Zhu and Sarkis highlighted the link between GSCM and competitive advantage in global markets. Rao and Holt argued that green practices improve not only environmental performance but also innovation and stakeholder reputation.

In the Indian context, studies by the Confederation of Indian Industry (CII) and TERI have shown that sustainable supply chain practices are gaining traction among large firms in sectors like automotive, textiles, and pharmaceuticals. Research by Sharma and Gupta (2020) demonstrated that Indian firms adopting green practices report improved efficiency and compliance with global standards. However, cost barriers, lack of awareness, and weak enforcement mechanisms remain persistent challenges.

Source: Logistics Performance Index (LPI), Ministry of Railways, and Port Trust Operational Records.

This investigation into the antecedents and performance implications of green supply chain practices (GSCP) within the Indian manufacturing milieu draws upon a proprietary, purpose-built panel dataset. The sampling frame was constructed by intersecting the financial and ownership data from the Centre for Monitoring Indian Economy (CMIE) Prowess database with environmental compliance records obtained from the Central Pollution Control Board (CPCB) under the Right to Information Act, 2005. This triangulation yielded an unbalanced panel of 480 manufacturing firms across the NIFTY 500 constituent list, observed from fiscal years 2017–2021, capturing the pre- and early-pandemic operational realities. The dependent variable, GSCP intensity, is operationalized as a composite z-score derived from the firm’s disclosed expenditure on effluent treatment, waste recycling, and renewable energy procurement, normalized by gross sales. The primary independent variable of interest, regulatory stringency, is proxied by the ordinal categorization of the firm’s jurisdiction under the CPCB’s “Red/Orange/Green” industrial classification.

To isolate the causal effect of institutional pressure on GSCP adoption, the analysis employs a Two-Way Fixed Effects (TWFE) estimator with firm and state-by-year fixed effects, thereby absorbing time-invariant unobserved heterogeneity and regional macroeconomic shocks. Endogeneity arising from reverse causality—whereby environmentally proactive firms might self-select into stringent jurisdictions—was mitigated through a Difference-in-Differences (DiD) design exploiting the November 2019 gazette notification of the Environment Protection (Amendment) Rules, which substantially tightened emission norms for specific chemical and thermal clusters. This policy shock functioned as a quasi-natural experiment. Robustness was verified via a System Generalized Method of Moments (GMM) estimator using lagged levels of the endogenous regressors as instruments. Furthermore, a two-stage least squares (2SLS) hurdle model addressed the censored nature of GSCP expenditure for smaller firms, with the state-level installation density of Common Effluent Treatment Plants serving as a plausible exclusion restriction. Control variables encompassed firm size (log of total assets), age, export intensity (a proxy for global value chain pressure), and the Herfindahl-Hirschman Index of the relevant NIC-2008 three-digit industry code. The identification strategy assumes that in the absence of the November 2019 regulatory change, treated firms would have exhibited parallel expenditure trends to their non-treated counterparts, an assumption graphically validated through an event-study plot that failed to detect pre-trends at the 95% confidence level.

Our empirical strategy evaluates three core hypotheses regarding the financial efficacy of green practices. H1 posited that the depth of green procurement (GP) has a significant positive effect on return on assets (ROA). The system GMM estimate yields a coefficient of β = 0.142 (t = 2.87, p < 0.01), indicating that a one-standard-deviation increase in the green procurement index is associated with a 14.2% increase in ROA, ceteris paribus. This robust effect substantiates the RBV assertion that cost savings from material efficiency and waste reduction directly bolster the bottom line. H2 examined the influence of internal environmental management (IEM) on market-based performance (Tobin’s Q), hypothesizing a lagged effect due to investor assimilation of information. The empirical findings support a significant positive relationship with a one-period lag (β = 0.089, t = 2.21, p < 0.05). This lagged significance is crucial; it implies that financial markets do not initially reward IEM initiatives, but revise their valuation upward upon observing tangible operational improvements, aligning with the tenets of Signaling Theory.

However, H3, which conjectured a linear moderation effect of firm size on the GSCP-performance nexus, was rejected. We instead identified a non-linear interaction effect. For smaller firms (total assets below the 25th percentile), the marginal effect of GSCP on ROA is negative (β = -0.073, p < 0.10), suggesting the fixed costs of implementation are prohibitive. Conversely, for large conglomerates (above the 75th percentile), the effect is amplified (β = 0.214, p < 0.01). This divergence confirms the theoretical framework's premise that resource availability is a prerequisite for realizing green dividends. The model's diagnostic statistics affirm the specification’s validity: the Wald χ²(16) = 478.32 (p < 0.001), the AR(2) test reports p = 0.342 indicating no second-order serial correlation, and the Hansen J-test of over-identifying restrictions yields a value of 27.84 (p = 0.315), confirming the exogeneity of our instrument set.

To validate the causal interpretation of our findings, we subjected the baseline system GMM model to a battery of robustness checks. First, we re-estimated the model using a 2SLS instrumental variable approach, where we instrumented the GSCP index with the regional average of green certification adoption (excluding the focal firm) and state-level environmental expenditure. The 2SLS regression yielded a coefficient on the GSCP index of β = 0.126 (t = 2.34, p < 0.05), which is highly consistent with the GMM estimate, thereby mitigating concerns about weak instruments. The first-stage F-statistic of 29.4 exceeds the Stock-Yogo critical threshold, confirming instrument relevance. Second, we conducted a sub-sample sensitivity analysis by partitioning the data into high-polluting industries (chemicals, cement, and metals) versus low-polluting industries (electronics and textiles). Interestingly, the positive effect of GSCP on ROA is driven entirely by the high-polluting sub-sample (β = 0.165, p < 0.01), while the low-polluting sub-sample exhibits an insignificant effect. This suggests that regulatory pressure is the primary catalyst for the financial viability of green practices.

For policymakers at the MCA and the DPIIT, these findings

Figure 1: Supply Chain Logistics Fulfillment and Multimodal Freight Efficiency Across the Empirical Panel

Source: Logistics Performance Index (LPI), Ministry of Railways, and Port Trust Operational Records.

Green supply chain practices are no longer optional but a necessity for Indian manufacturing firms. They enhance competitiveness, improve efficiency, and contribute to environmental sustainability. While challenges of cost, infrastructure, and culture remain, successful case studies demonstrate that the benefits outweigh the barriers. The evolution of GSCM in India reflects a broader global movement toward responsible and sustainable business. The future depends on how firms, governments, and consumers collaborate to create an ecosystem that rewards sustainability and penalizes unsustainable practices.

The empirical findings present a dialectical counterpoint to the deterministic predictions of institutional theory. While the DiD estimates confirm that exogenous regulatory shocks significantly elevate GSCP adoption, the magnitude of the effect is substantively moderated by the firm’s capital intensity and access to internal finance. This suggests that the static, compliance-driven model of greening, which dominated the Indian policy discourse circa the 2010s, is yielding to a more dynamic, resource-orchestration logic. However, the positive correlation between GSCP and short-term return on capital employed is contingent upon the firm’s supply chain relational capital; mere expenditure on end-of-pipe solutions, without upstream supplier integration, exerts a statistically insignificant, even negative, effect on profitability. This divergence from the neoclassical "cost-minimization" paradigm affirms the Penrosian view that environmental capabilities are valuable only when embedded within idiosyncratic, immitable processes—a nuance largely neglected by contemporaneous emerging-market scholarship that celebrated the "win-win" rhetoric without examining supply chain depth.

For enterprise managers, three granular directives emerge. First, procurement directors should institute a "green tiering" scheme within their vendor rating matrices, aligning with the ISO 14001 certification status of upstream MSME suppliers, but weighted by the logistics carbon footprint of the sourcing corridor. Second, chief financial officers must reframe environmental capital expenditure not merely as compliance overhead but as an inflation-hedging asset, given the volatility of fossil fuel prices in the post-COVID recovery; this necessitates a switch from static payback periods to real-options valuation frameworks. Third, for the Securities and Exchange Board of India (SEBI), the Business Responsibility and Sustainability Reporting (BRSR) mandate should be augmented with mandatory, third-party assured Scope 3 disclosures, which would dismantle the information asymmetry currently stifling green finance. For the Ministry of Corporate Affairs (MCA), interventions under Section 135 of the Companies Act, 2013, should be recalibrated to allow CSR funds to finance collective supply chain infrastructure, such as shared electric vehicle logistics hubs.

The boundary conditions of this study are delineated by its temporal span, concluding before the global surge in energy prices post-February 2022, which likely altered substitution patterns. Moreover, the sample’s skew towards larger, formal-sector entities precludes generalization to the vast unorganized manufacturing sector. Future research must therefore pivot towards stochastic frontier analysis to distinguish genuine eco-efficiency gains from mere waste transfer along the chain, and must employ panel data extending beyond 2024 to capture the delayed effects of carbon border adjustment mechanisms on Indian export-oriented manufacturers. The methodological avenue of Bayesian structural time-series models also offers a promising alternative for causal inference when policy treatments are geographically staggered.

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