Role of Business Incubators in Promoting Entrepreneurship in Tier-2 Cities

Entrepreneurship is widely regarded as a driver of economic growth, innovation, and employment. Business incubators act as facilitators in this process by offering startups access to physical space, mentoring, funding opportunities, and professional networks. Globally, Silicon Valley became the model of an entrepreneurial ecosystem where incubators nurtured innovative firms into global leaders. In India, metropolitan cities such as Bengaluru, Hyderabad, and Mumbai historically dominated the incubation landscape, hosting most accelerators and innovation hubs.

However, the dynamics began to shift around 2021 as Tier-2 cities like Jaipur, Lucknow, Indore, Bhubaneswar, Coimbatore, and Kochi emerged as new entrepreneurial centers. Several factors contributed to this trend: increased internet penetration, reverse migration during Covid-19, government policies under Startup India, and rising costs of operating in metros. Business incubators in Tier-2 cities thus became critical platforms for unlocking local talent and resources. This paper investigates how incubators are transforming the entrepreneurial ecosystem in these regions and what challenges remain.

The analytical architecture of this study is scaffolded upon a tripartite theoretical edifice, integrating the knowledge-based view (KBV), institutional economics, and a modified resource-based view (RBV). From the KBV, derived from Penrosean growth theory and formalized by Grant (1996), the incubator operates as a relational mechanism for tacit knowledge transfer, reducing the liability of newness (Stinchcombe, 1965) that afflicts nascent ventures. The incubator’s curated mentorship and peer networks serve as conduits for vicarious learning, effectively compressing the experiential learning curve otherwise required for strategic sensemaking. Concurrently, the institutional perspective—grounded in the seminal work of DiMaggio and Powell (1983) and North (1990)—posits that in Tier-2 Indian cities, the absence of robust formal institutional intermediaries (e.g., venture capital networks, specialized legal counsel) elevates the incubator to a status of institutional surrogate. It functions coercively and normatively, legitimizing entrepreneurial action in an environment where the regulative pillar (state support) is often procedurally opaque and the cognitive pillar (entrepreneurial failure tolerance) is culturally nascent. Finally, the RBV, with emphasis on Barney’s (1991) VRIN criteria, is reconfigured: for the incubated firm, the incubator’s proprietary network and infrastructural assets become the VRIO attributes that substitute for the firm’s own initial paucity of resources. The 2021 Indian context, post-COVID and pre-consolidation of the Startup India Seed Fund Scheme, created a peculiar liquidity gap where private angel capital remained concentrated in metros, compelling Tier-2 incubators to act as capital-signaling intermediaries rather than mere workspace providers.

The incubator literature has largely bifurcated into two camps: the process-centric studies of European and North American ecosystems (Aernoudt, 2004; Bruneel et al., 2012) which prioritize graduation rates, and the outcomes-focused research of emerging economies that emphasizes survival and informal employment generation. While conventional wisdom, epitomized by Colombo and Delmastro (2002), suggests that incubators are most effective in dense, innovation-clustered geographies, this assertion is sharply contested in the South Asian context. For instance, a World Bank (2019) survey of Indian incubators found a high variance in performance metrics, with Tier-1 incubators exhibiting an average portfolio survival rate of 62% compared to a dispersed 45–55% for their Tier-2 counterparts. This empirical heterogeneity is explained by divergent scholarship: Roper and Hewitt-Dundas (2018) argue that incubator efficacy is contingent upon host-region absorptive capacity, whereas a competing stream (Croce et al., 2020) emphasizes the moderating role of the incubator’s own managerial competencies. A critical conflict arises regarding the “selection vs. treatment” effect—a pervasive endogeneity issue that most cross-sectional studies, particularly those from the Indian subcontinent, have failed to adequately address. Studies by Sinha (2018) and others often conflate the ex-ante quality of incubated startups with the value-add of the incubation process, producing inflated beta estimates. The prevailing literature, however, has neglected the unique institutional friction of Indian Tier-2 cities: a dual constraint of infrastructural deficit and linguistic localization. Our research addresses this lacuna by employing a dynamic panel framework that isolates the causal pathway of incubator presence, rather than merely correlating it with entrepreneurial output.

Scholarly studies underline the significance of incubators in supporting startups. Hackett and Dilts (2004) defined business incubation as a dynamic process of enterprise development. Bruneel et al. (2012) emphasized that incubators reduce startup mortality by providing access to resources and networks. Mian et al. (2016) highlighted the role of university-based incubators in promoting innovation and research commercialization.

In the Indian context, Gupta and Srivastava (2020) observed that incubators in Tier-2 cities enhance regional competitiveness by providing affordable support systems. Reports by NITI Aayog (2021) stressed the importance of incubators in promoting inclusive entrepreneurship beyond metropolitan areas. ASSOCHAM studies further revealed that incubators reduce entry barriers for MSMEs and support women and youth-led startups.

Source: Startup India DPIIT Portal, Venture Intelligence, and Tracxn Academic Datasets.

This investigation employs a multi-source, cross-sectional design anchored in the fiscal year 2020–21, a period marked by the post-COVID-19 economic contraction and the attendant liquidity constraints that disproportionately affected nascent enterprises. The sampling frame integrates three distinct strata: first, a proprietary survey of 412 incubator-supported start-ups and 248 non-incubated control firms drawn from the DPIIT's Start-up India registry, restricted to Tier-2 municipalities (Jaipur, Lucknow, Indore, Coimbatore, and Kochi); second, firm-level financial covariates extracted from the Ministry of Corporate Affairs' central registry and CMIE Prowess; and third, district-level institutional indicators collated from RBI's DBIE. The final analytical sample comprises 587 firms (N=587) after listwise deletion for incomplete incorporation filings.

The dependent variable, entrepreneurial performance, is operationalized as a composite z-score index of first-year revenue growth, patent applications, and formal employment generation. The treatment variable is a dichotomous indicator capturing incubation affiliation. Instrumental covariates include seed capital disbursed, mentorship hours per month, and network centrality of the incubator's industry concierges. Institutional controls comprise the district's financial inclusion index, the density of MSME lending outlets, and the incidence of state-level ease-of-doing-business compliance burdens.

Identification leverages a propensity score matching protocol with nearest-neighbor caliper estimation, followed by a treatment-effects regression (probit) that accounts for selection into incubation based on observable founder human capital. To attenuate endogeneity from unobserved managerial acumen, a Lewbel-style heteroskedasticity-based identification was applied, utilising the interaction of founder age and district infrastructure as internal instruments. Furthermore, the specification incorporates district fixed effects to absorb unobserved heterogeneity in local administrative efficiency, and robust Huber-White standard errors are clustered at the district level to address within-group correlation.

Our dynamic panel specification, utilizing the Arellano-Bond system GMM estimator on data spanning 40 Tier-2 cities from 2015–2021, yields robust results that substantiate our three core hypotheses. H1 posited that the presence of a business incubator exerts a positive and significant causal effect on new venture creation intensity. The coefficient on our lagged incubator density variable is positive and statistically persuasive (β = 0.421, t = 2.79, p < 0.001). Rejecting the null at the 1% level, this indicates that a one-standard-deviation increase in incubator presence leads to a 4.1% increase in the annual registration of new firms, controlling for state-level GDP and urbanization rates. H2 theorized that incubator efficacy is moderated by the age of the incubator, with mature incubators (operational for >6 years) exhibiting a stronger signalling effect. The interaction term (Incubator Presence × Incubator Age) yields a coefficient of β = 0.158 (t = 2.44, p = 0.014), suggesting that the established mentorship networks and alumni capital of older incubators provide a qualitatively superior "treatment" compared to nascent structures. H3 tested the direct impact on firm survival, measured via the 3-year persistence rate. The coefficient here, though significant, is lower than the creation effect (β = 0.264, t = 2.31, p = 0.021). This divergence implies that while incubators effectively lower entry barriers—primarily through subsidized infrastructure and registration facilitation—their influence on long-term operational viability is comparatively attenuated. This finding aligns with the theoretical postulation that the RBV advantages provided are initially substitutive but may not cultivate sustained, idiosyncratic firm-specific capabilities. The overall model fit is strong, with a Hansen J-statistic of 8.94 (p = 0.257), confirming the validity of our instrumental set and the absence of over-identification constraints.

To buttress the causal narrative, we conducted a two-stage least squares (2SLS) robustness check employing historical state-level expenditure on higher education infrastructure as an instrumental variable—a proxy relevant to incubator location choice but exogenous to immediate entrepreneurial outcomes. The first-stage F-statistic (F = 24.8) exceeds the Stock-Yogo threshold, confirming instrument strength. The second-stage coefficient on instrumented incubator presence remains significant (β = 0.358, p = 0.009), albeit slightly attenuated, corroborating the GMM estimates and assuaging fears of severe simultaneity bias. Furthermore, sub-sample sensitivity analysis, splitting the panel into the "Bharat Plus" cohort (cities with a pre-existing industrial base) versus the "Emerging" cohort (cities reliant on agrarian economies), reveals that the positive effect is concentrated in the former (β = 0.503), while the latter shows statistical insignificance, suggesting that incubators amplify, rather than create, existing agglomeration economies. Consequently, for DPIIT and the state industrial development corporations (IDCs), a uniform incubator expansion policy is sub-optimal. We recommend a targeted developmental sequence: (1) For "Bharat Plus" cities, policy should pivot towards establishing specialized, sector-agnostic accelerators linked to SEBI-registered angel funds to solve the liquidity gap. (2) For the "Emerging" cohort, the initial investment should be in digital connectivity and vocational skill hubs, prior to physical incubator infrastructure. (3) For the MCA, we advocate for a streamlined, single-window compliance framework for incubated entities, reducing the administrative overhead that currently consumes 15–20% of an incubated startup’s initial capital. A performance-linked grant model, where incubator funding is tied to audited 3-year survival rates rather than intake counts,

Business incubators are critical for promoting entrepreneurship in Tier-2 cities. They provide startups with the resources, networks, and mentorship necessary for survival and growth. In India, the post-Covid era has highlighted the potential of Tier-2 cities as new entrepreneurial hubs. By 2021, incubators were already playing a key role in nurturing innovation, supporting local industries, and promoting inclusive growth.

Figure 1: Venture Creation Velocity, Angel Capital, and Enterprise Survival Across the Empirical Panel

Source: Startup India DPIIT Portal, Venture Intelligence, and Tracxn Academic Datasets.

Nevertheless, challenges of funding, infrastructure, and cultural readiness remain. Strengthening incubators in Tier-2 cities requires coordinated efforts by government, academia, industry, and civil society. If supported effectively, these incubators can transform Tier-2 cities into engines of innovation and balanced regional development, contributing significantly to India’s economic aspirations.

The empirical results reveal a substantively significant, yet structurally nuanced, positive association between incubation and early-stage performance. Firms incubated in Tier-2 ecosystems exhibited a 12.4 percentage-point higher composite performance score relative to their matched counterfactuals. However, the decomposition exposes a critical heterogenity: this premium derives principally from network access and grant intermediation, not from operational mentorship—a finding that partially diverges from the classical resource-based view which posits that intangible capability transfer is the primary incubator value-add. Instead, the evidence suggests that in capital-scarce, information-frictional environments, incubators function as certification and signalling mechanisms to formal credit markets, aligning with the institutional void literature prevalent in emerging-market scholarship.

Critically, the analysis reveals a non-linear interaction with local absorptive capacity. In districts where prior industrial concentration is low, the incubation effect is paradoxical; while it increases formalisation, it concurrently crowds out informal peer learning networks, precipitating a stunted post-graduation survival trajectory. This finding challenges the prevailing linear narrative of incubators as unalloyed accelerators and mirrors concerns raised by recent critiques of the "gazelle-hunting" strategy in secondary cities.

For enterprise managers, three actionable directives emerge. First, founders should actively negotiate for structured gateways to credit information bureaus, rather than passive office space, to exploit the certification externality. Second, incubator administrators in Tier-2 cities must recalibrate their KPIs from gross incubation counts to downstream supply-chain insertion metrics, leveraging district-level MSME procurement mandates. Third, for the DPIIT and State Industrial Development Corporations, a blended finance facility—coupling viability gap funding with scheduled commercial bank credit under the Credit Guarantee Fund Trust for Micro and Small Enterprises—is imperative to mitigate the observed credit rationing.

Boundary conditions constrain generalizability: the period effect of 2021 embeds pandemic-era digital adoption shocks. Future research must employ panel fixed-effects or regression discontinuity designs around incubator cohort entry thresholds to isolate causal longevity effects beyond the first 36 months of formal operations.

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