Exploring the impact of external collaboration on firm growth capability: the mediating roles of R&D efforts

The study addresses how different types of external collaboration influence firm growth capability, particularly through internal R&D efforts, in the context of China’s dynamic and turbulent market environment. Motivated by high firm failure rates and the need for sustainable growth, the paper identifies gaps: limited attention to heterogeneous collaborator types, under-examination of firm growth capability as a multidimensional construct, lack of focus on the outside-to-inside pathway from collaboration to R&D efforts, and scarcity of evidence from emerging economies. The research examines vertical, horizontal, and competitor collaboration and their direct and indirect effects on firm growth capability via R&D intensity and R&D human capital using data from 94 top-ranking Chinese innovative enterprises. The work proposes hypotheses H1–H4 covering direct, R&D, and mediating relationships and outlines a conceptual framework to test these relationships.

External collaboration is framed within open innovation as managed knowledge flows across organizational boundaries. Prior work often measured collaboration by breadth and depth, but this approach overlooks partner heterogeneity. Integrating past categorizations, the study classifies external collaboration into: (1) vertical collaboration (with suppliers and customers), (2) horizontal collaboration (with governments, universities/educational institutions, consultancy firms, venture capitalists, trade fairs/exhibitions, and others), and (3) competitor collaboration (coopetition). R&D efforts denote a firm’s resource commitment to R&D and are conceptualized here as two dimensions: R&D intensity (financial investment ratio) and R&D human capital (share of highly skilled R&D workers). Firm growth capability is treated as a multidimensional construct capturing both financial (debt-paying, operating, profitability, development abilities) and process dimensions (R&D, manufacturing, marketing, service capabilities), addressing how firms grow rather than only how much. Hypotheses propose positive effects of collaboration on growth capability (H1), collaboration on R&D efforts (H2), R&D efforts on growth capability (H3), and a mediating role of R&D efforts between collaboration and growth capability (H4).

Design and sample: The study examines 94 Chinese innovative firms listed on the Shanghai and Shenzhen A-share markets, selected from the 2018 Global Innovation 1000 list. Exclusions included firms listed in Hong Kong, Taiwan, or the U.S. (data collection difficulty) and five mainland firms with missing data. Industries include information technology, capital goods, advanced materials, automobiles/components, consumer durables/apparel, retailing/media, healthcare, and energy; ownership includes state-owned and non-state-owned; varied firm ages and sizes. Data collection: Two stages. First, a trained panel (1 professor, 2 doctoral students) developed composite scales for external collaboration and the process dimension of firm growth capability via content analysis of firm disclosures (annual reports, CSR reports, analysts’ reports, company news, websites, announcements) from 2016–2020. Inter-rater reliability showed Pearson r=0.951 (p<0.01). Second, other variables were sourced from the CSMAR Database for 2018; data were winsorized to reduce extreme values. Due to data constraints, the analysis is cross-sectional. Measures: Independent variables—External collaboration: vertical collaboration (VC)=sum of binary indicators for supplier and customer collaboration; horizontal collaboration (HC)=sum of binary indicators for collaboration with governments, universities/educational institutions, consultancy firms, venture capital firms, trade fairs/exhibitions, others; competitor collaboration (CC)=binary indicator for competitor collaboration. Each collaboration type coded 1 if collaboration is broad/deep, 0 otherwise; aggregated for VC and HC. Mediators—R&D intensity (RI)=R&D expenditure/operating income; R&D human capital (RHC)=percentage of highly skilled R&D workers (researchers and technicians). Dependent variable—Firm growth capability (FGC): financial dimension (current ratio; inventory turnover; operating profit ratio; operating income growth rate), combined via PCA; process dimension measured with a four-item 5-point scale (global R&D platform, intelligent manufacturing, diversified/advanced online-offline sales system, advanced service system). Both dimensions normalized to [0,1] and averaged to yield FGC. Controls—Ownership (state-owned=1; others=0), age (years since founding), size (ln employees), industry (1 for advanced materials, consumer discretionary, healthcare, energy; 0 otherwise). Statistical analysis: Hierarchical regression (SPSS 24) for direct effects and PROCESS v3.3 bootstrapping (10,000 samples; 95% CI) for mediation. Models M1–M21 specify relationships for H1–H4, including combined and separate predictors, mediators, and controls. Diagnostics included VIF and Durbin–Watson.

Descriptive statistics: Significant positive correlations include RI with HC (r=0.547, p<0.01) and CC (r=0.176, p<0.1); RHC with HC (r=0.585, p<0.01); FGC with HC (r=0.545, p<0.01), CC (r=0.178, p<0.1), RI (r=0.685, p<0.01), and RHC (r=0.597, p<0.01). VIFs well below 10 (max=2.523) indicate no serious multicollinearity. Direct effects on firm growth capability (H1): In separate models, VC (β=0.403, p<0.05), HC (β=0.314, p<0.01), and CC (β=0.413, p<0.05) significantly increase FGC. In the combined model, HC remains significant (β=0.272, p<0.01), while VC (β=0.203, n.s.) and CC (β=0.278, n.s.) become insignificant, indicating HC’s dominant influence. Effects on R&D efforts (H2): For R&D intensity (RI), VC (β=0.283, p<0.1), HC (β=0.306, p<0.01), and CC (β=0.486, p<0.05) are positive in separate models; combined, HC (β=0.276, p<0.01) and CC (β=0.361, p<0.05) remain significant, VC becomes insignificant (β=0.075, n.s.). For R&D human capital (RHC), VC (β=0.285, p<0.1), HC (β=0.347, p<0.01), and CC (β=0.363, p<0.1) are positive in separate models; combined, only HC remains significant (β=0.327, p<0.01). Thus, H2 is supported, with HC exerting the strongest consistent effect, and CC notably inducing RI. Effects of R&D efforts on FGC (H3): RI (β=0.610, p<0.01) and RHC (β=0.543, p<0.01) each positively predict FGC; in the combined model both remain significant (RI β=0.452, p<0.01; RHC β=0.245, p<0.05). Mediation (H4): Bootstrapped indirect effects via RI are significant for VC (estimate=0.123; 95% CI [0.001, 0.305]), HC (0.126; [0.051, 0.233]), and CC (0.212; [0.037, 0.412]). Indirect effects via RHC are not significant for VC (0.065; CI [-0.015, 0.191]), HC (0.057; [-0.031, 0.154]), or CC (0.088; [-0.023, 0.228]). Therefore, H4 is partially supported: RI mediates, RHC does not. Additional notes: Control variables show Ownership (state-owned) and Size often negatively associated with FGC; Industry and Age effects vary across models.

Findings demonstrate that external collaboration fosters firm growth capability primarily by inducing greater R&D investments, especially financial intensity. Horizontal collaboration with institutions such as governments, universities, consultants, VC firms, and trade fairs exerts the most robust influence on both R&D inputs and growth capability and can overshadow vertical and competitor collaboration when entered jointly. Competitor collaboration particularly stimulates R&D intensity, underscoring coopetition’s role in driving investment to keep pace technologically. Both R&D intensity and R&D human capital directly enhance growth capability, but only R&D intensity functions as a consistent mediator, indicating that financial commitment to R&D is the key mechanism through which collaboration translates into growth capability improvements. The study advances open innovation and growth theories by specifying partner-type heterogeneity and clarifying the outside-to-inside pathway in an emerging economy context, with practical implications for partner selection and R&D investment strategies, and policy implications for supporting collaborative innovation ecosystems.

The study contributes by: (1) extending firm growth theory to incorporate distinct types of external collaboration (vertical, horizontal, competitor) and evidencing their positive roles in firm growth capability; (2) proposing and testing an integrated model that uncovers R&D intensity as a key mediating mechanism linking collaboration to growth capability, while distinguishing the lesser mediating role of R&D human capital; and (3) providing empirical evidence from an emerging economy, enriching open innovation literature beyond developed-country contexts. Managerially, firms should strengthen external collaborations—particularly horizontal partnerships—and strategically leverage them to induce R&D investment, while continuing to invest in both R&D intensity and human capital. Policymakers can use these insights to design programs supporting university–industry collaboration, R&D subsidies, and talent policies that reinforce collaborative innovation. Future research should incorporate longitudinal designs, cross-country comparisons, refined measures of growth capability, larger samples, and additional mediators (e.g., technological or business model innovation) and moderators (e.g., market dynamism, technological turbulence, organizational culture).

Key limitations include: (1) cross-sectional design limits causal inference; longitudinal data are needed; (2) China-only sample constrains generalizability; cross-cultural replication is recommended; (3) self-developed measurement for the process dimension of firm growth capability may require further validation via surveys/interviews; (4) relatively small sample size (N=94) compared to the broader population; (5) limited set of controls (ownership, age, size, industry) may omit other contextual variables such as internationalization or organizational hierarchy.