The Power of Technological Leapfrogging: Insights for Latecomers
In the dynamic landscape of the technology industry, the ability of latecomers to catch up with industry leaders has become a topic of increasing fascination. As the digital economy continues to evolve, traditional management approaches are giving way to data-driven decision-making, and artificial intelligence is emerging as a transformative force. In this context, the strategic choices of latecomers, particularly their adoption of path-creating strategies, can hold the key to unlocking rapid technological advancement and market leadership.
This article delves into the underlying mechanisms governing the relationship between path-creating strategies and the technological catch-up performance of latecomers. Drawing on a comprehensive analysis of high-tech manufacturing enterprises in China, we explore the nuanced interplay between various factors, including technological capabilities, innovation appropriability, and technological cumulativeness. By combining traditional econometric methods with the power of causal machine learning, we uncover complex patterns and heterogeneous effects that shed new light on this critical topic.
Understanding the Sectoral Innovation System
The framework of the sectoral innovation system provides a comprehensive and dynamic lens through which to examine the catch-up strategies of latecomers. This framework, which has been widely adopted in the study of developing countries, encompasses four key aspects: the knowledge and technology regime, demand conditions (or market regime), the actors and their interactions, and institutional factors.
Latecomers, faced with the dual disadvantages of technology and market access, must navigate this complex innovation ecosystem to overcome the barriers set by industry leaders. By leveraging their latecomer advantages, such as cost competitiveness, these enterprises can seek to narrow the gap with incumbents through faster innovation or more impactful breakthroughs.
The Path-Creating Strategy: A Promising Approach
Among the various catch-up strategies available to latecomers, the path-creating strategy has gained significant attention. This approach involves latecomers exploring their own technological development trajectories, often by adopting the latest generation of technologies or pursuing disruptive innovations. By carving out a distinct path from that of industry leaders, latecomers can harness their latecomer advantages and capitalize on the weaknesses or inertia of incumbents.
Existing research has highlighted the potential of path-creating strategies to enable latecomers to achieve nonlinear catch-up and even surpass industry leaders. When faced with technological or market discontinuities, latecomers unencumbered by the constraints of incumbents can leverage their agility and innovative capabilities to leapfrog the competition.
Hypotheses and Research Model
Building on the insights from the sectoral innovation system framework and the existing literature, this study proposes the following hypotheses:
H1a: Latecomers’ path-creating strategy positively impacts their technological catch-up performance.
H1b: Technological capability plays a positive mediating role between path-creating and technological catch-up performance.
H2a: Technological innovation appropriability positively moderates the relationship between path-creating and technological capability.
H2b: Technological innovation appropriability positively moderates the effect of technological capability on technological catch-up.
H3: Technological innovation cumulativeness negatively moderates the relationship between path-creating and technological catch-up.
The research model, adapted from the work of Lee and Lim (2001) and Lee et al. (2017), aligns these hypotheses within the broader context of the sectoral innovation system, capturing the interplay between technology regime, market regime, government, and the various actors involved.
Methodology and Data
This study utilizes a combination of traditional econometric methods and causal machine learning techniques to explore the underlying mechanism of path-creating strategies and their impact on the technological catch-up of latecomers.
The sample consists of 283 high-tech manufacturing enterprises listed on the Shanghai and Shenzhen stock exchanges in China, with data spanning from 2007 to 2019. The variables constructed encompass aspects of the technology regime, market regime, and enterprise characteristics, including technological catch-up performance, path-creating, technological capability, technological innovation appropriability, technological innovation cumulativeness, and various control factors.
To ensure the robustness of the feature selection process, three different machine learning algorithms – SelectKBest, Permutation Importance, and Random Forest – were employed. This multi-faceted approach helped identify the most relevant features for the subsequent analysis.
Empirical Findings
The results of the OLS linear regression model provide support for the hypotheses proposed in this study. Specifically, the findings indicate:
- Path-creating has a positive impact on latecomers’ technological catch-up performance (H1a supported).
- Technological capability plays a positive mediating role between path-creating and technological catch-up performance (H1b supported).
- Technological innovation appropriability positively moderates the effect of path-creating on technological capability, and the effect of technological capability on technological catch-up (H2a and H2b supported).
- Technological innovation cumulativeness negatively moderates the relationship between path-creating and technological catch-up (H3 supported).
These results shed light on the complex interplay between the path-creating strategy, technological capabilities, and the innovation environment faced by latecomers.
Insights from Causal Machine Learning
The integration of causal machine learning techniques provided further insights beyond the linear regression analysis. The average treatment effect (ATE) calculation confirmed the positive impact of the path-creating strategy on latecomers’ technological catch-up performance, consistent with the econometric findings.
However, the individual treatment effect (ITE) analysis revealed a more nuanced picture. While many latecomers successfully adopted the path-creating strategy to achieve technological catch-up, there were also instances where the strategy proved ineffective. The Shapley value graph highlighted the complex interplay of various factors, such as technological capability, cumulativeness, and appropriability, in determining the success or failure of the path-creating approach.
Furthermore, the decision tree analysis uncovered a set of intricate conditions and decision paths that can guide latecomers in determining the appropriate strategic choices. For instance, the decision tree model suggests that the path-creating strategy tends to be more effective for latecomers with high technological capabilities, but it may not be the optimal choice in cases of moderate appropriability or insufficient absorptive capacity.
Implications and Strategic Considerations
The findings of this study offer valuable insights for latecomers navigating the technology-intensive landscape. Several key implications emerge:
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Developing Robust Technological Capabilities: Latecomers should prioritize the development of their technological capabilities, as this plays a crucial role in enhancing the effectiveness of path-creating strategies and driving technological catch-up.
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Navigating the Innovation Environment: Latecomers must carefully consider the innovation regime they operate within, particularly the levels of technological appropriability and cumulativeness. These factors can significantly impact the viability and success of path-creating strategies.
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Leveraging Causal Machine Learning Insights: By integrating causal machine learning analyses, latecomers can gain a deeper understanding of the complex interplay of factors influencing the effectiveness of their strategic choices. This can inform more tailored and data-driven decision-making.
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Adaptability and Strategic Flexibility: Given the heterogeneous nature of the path-creating strategy’s effectiveness, latecomers should maintain a flexible and adaptable approach, continuously assessing the appropriateness of their strategic decisions based on the evolving innovation ecosystem.
Conclusion
In the rapidly evolving digital economy, the ability of latecomers to catch up with industry leaders has become increasingly critical. This study’s exploration of the underlying mechanisms governing the path-creating strategy and its impact on technological catch-up performance provides a valuable framework for latecomers to navigate this complex landscape.
By combining traditional econometric methods and causal machine learning techniques, this research offers a multifaceted perspective on the strategic choices and innovation dynamics faced by latecomers. The findings emphasize the significance of developing robust technological capabilities, navigating the nuances of the innovation environment, and leveraging data-driven insights to inform strategic decision-making.
As the technology industry continues to transform, latecomers armed with a deep understanding of the mechanisms driving technological catch-up will be poised to seize the windows of opportunity and emerge as the industry leaders of the future.
