The low altitude economy, characterized by its integration of aviation, digital technologies, and emerging applications, represents a pivotal sector in the global shift toward sustainable and innovative economic models. As nations strive to cultivate new quality productive forces, the low altitude economy stands out due to its potential to drive technological leaps, foster cross-industry collaboration, and generate substantial value. However, enterprises operating in this domain face unique challenges, including regulatory ambiguities, technological immaturity, and high operational risks. Against this backdrop, breakthrough innovation—defined as the pursuit of disruptive technological advancements—becomes essential for firms to secure competitive advantages and achieve high-quality development. This study employs a Technology-Organization-Environment (TOE) framework to investigate the multifaceted drivers of breakthrough innovation in low altitude economy enterprises and examines how these innovations contribute to sustainable growth through a complex mediation model integrating Qualitative Comparative Analysis (QCA) and regression techniques.
The low altitude economy encompasses a wide range of activities, from unmanned aerial vehicles (UAVs) to advanced air mobility solutions, all operating within low-altitude airspace. Its significance lies in its ability to catalyze innovation across sectors such as logistics, agriculture, and urban transportation. Despite its promise, the sector’s evolution is hampered by uncertainties in technology standardization and market acceptance. Existing literature has predominantly focused on macro-level governance and policy frameworks, leaving a gap in understanding micro-level enterprise behaviors. This research addresses this gap by analyzing how firms in the low altitude economy leverage technological diversification, digital transformation, and environmental factors to foster breakthrough innovations. By adopting a configurational approach, we identify multiple pathways that lead to high innovation performance and explore their indirect effects on firm productivity and growth.
In the following sections, we first review relevant theories on breakthrough innovation and the TOE framework. We then develop a theoretical model that links technological, organizational, and environmental conditions to innovation outcomes, and subsequently to high-quality development. The research design outlines the methodology, sample selection, and variable measurements, followed by empirical analyses using fsQCA and regression models. The findings reveal five distinct innovation paradigms and their differential impacts on firm performance. The conclusion discusses theoretical contributions and practical implications for enterprises and policymakers in the low altitude economy.
Literature Review and Theoretical Foundations
Breakthrough innovation refers to the development of novel technologies or processes that fundamentally alter market dynamics and create new value propositions. In the context of the low altitude economy, such innovations are critical for overcoming technical bottlenecks and establishing first-mover advantages. The TOE framework provides a comprehensive lens to analyze innovation drivers, categorizing them into technological conditions (e.g., knowledge recombination capabilities), organizational conditions (e.g., digital infrastructure), and environmental conditions (e.g., regulatory support). Previous studies have highlighted the role of knowledge absorption and R&D intensity in fostering innovation, but few have applied these concepts to the low altitude economy. Moreover, traditional linear models fail to capture the complexity of innovation pathways, necessitating the use of configurational methods like QCA.
The low altitude economy is inherently interdisciplinary, requiring integration of expertise from aviation, renewable energy, and artificial intelligence. Knowledge recombination theory posits that innovation arises from the novel combination of existing knowledge elements. Thus, technological diversification—measured through patent data—enables firms to access heterogeneous knowledge pools, enhancing their capacity for breakthrough innovations. Organizational factors, such as digitalization, facilitate real-time data exchange and agile decision-making, while environmental factors, including infrastructure and business-friendly policies, reduce entry barriers and stimulate collaborative innovation. This study synthesizes these elements into a cohesive framework to explain how low altitude economy enterprises achieve innovation excellence.
Theoretical Analysis and Model Construction
Based on the TOE framework, we propose that breakthrough innovation in the low altitude economy is driven by the interplay of multiple factors. Technological conditions include technological diversification, R&D capability, and knowledge absorption capacity. Organizational conditions encompass digitalization level and organizational slack. Environmental conditions involve infrastructure development and business environment quality. These factors do not operate in isolation; rather, they form configurations that collectively enable innovation. For instance, high technological diversification combined with strong R&D capabilities may lead to innovation through internal knowledge synthesis, whereas digitalization coupled with supportive policies may foster open innovation ecosystems.
The complex mediation model examines how these configurations indirectly influence firm performance via breakthrough innovation. The model can be represented as:
$$Y = \beta_0 + \beta_1 X + \beta_2 M + \epsilon$$
where Y denotes high-quality development (e.g., total factor productivity), X represents the innovation configurations derived from QCA, and M is breakthrough innovation. The mediation effect is tested by comparing the direct and indirect paths of X on Y. This approach allows for the identification of equivalent pathways that lead to similar outcomes, addressing limitations of traditional regression models.
| Variable Type | Construct | Measurement |
|---|---|---|
| Technological Conditions | Technological Diversification | Herfindahl-Hirschman Index based on patent data |
| R&D Capability | Ratio of R&D personnel to total employees | |
| Knowledge Absorption | R&D investment as percentage of revenue | |
| Organizational Conditions | Digitalization Level | Frequency of digital-related keywords in annual reports |
| Organizational Slack | Ratio of administrative and sales expenses to revenue | |
| Environmental Conditions | Infrastructure | Number of general aviation airports per region |
| Business Environment | Comprehensive index from city reports | |
| Outcome Variables | Breakthrough Innovation | Natural logarithm of invention patent applications |
| High-Quality Development | Total factor productivity (TFP) using OP method |
The theoretical model posits that specific combinations of these conditions are sufficient for high breakthrough innovation, which in turn mediates their effect on firm performance. For example, a configuration with high technological diversification and digitalization but low organizational slack may drive innovation through efficient resource allocation. Conversely, configurations with high environmental support might leverage external networks for innovation. The low altitude economy’s unique characteristics, such as its reliance on cross-sector collaboration and rapid technological iteration, make these pathways particularly relevant.
Research Design
This study employs a mixed-methods approach, combining fsQCA and regression analysis, to address the research questions. The sample consists of 259 enterprises listed in the low altitude economy sector, as identified from financial databases. Data were collected for the year 2022 for antecedent conditions and 2023 for outcome variables to account for lagged effects. Financial and patent data were sourced from iFind and CNRDS, while infrastructure and business environment data were obtained from official reports.
Calibration of fuzzy sets was performed using direct calibration, with anchors set at the 75th, 50th, and 25th percentiles. For instance, technological diversification was calibrated such that values above 0.887 indicate full membership, 0.794 the crossover point, and below 0.643 non-membership. Similarly, breakthrough innovation was measured using the natural log of invention patents, with higher values indicating greater innovation output. Control variables included firm size, age, leverage, and leadership structure to mitigate confounding effects.
The fsQCA analysis followed standard procedures, with a frequency threshold of 2 and consistency thresholds of 0.8 for raw consistency and 0.7 for PRI consistency. The complex mediation model was tested by first deriving innovation configurations from QCA and then using their membership scores as independent variables in regression models. Robustness checks involved alternative measures of TFP and Winsorization of extreme values.
| Variable | Mean | Std. Dev. | Min | Max |
|---|---|---|---|---|
| Technological Diversification | 0.75 | 0.12 | 0.64 | 0.89 |
| R&D Capability | 18.85 | 9.82 | 12.87 | 32.51 |
| Knowledge Absorption | 6.51 | 3.45 | 4.37 | 11.33 |
| Digitalization Level | 2.64 | 1.20 | 1.39 | 3.78 |
| Organizational Slack | 0.11 | 0.06 | 0.07 | 0.18 |
| Infrastructure | 16.00 | 15.00 | 11.00 | 41.00 |
| Business Environment | 65.93 | 3.71 | 60.83 | 68.25 |
| Breakthrough Innovation | 2.83 | 1.46 | 0.00 | 8.26 |
| TFP | 6.81 | 0.83 | 5.10 | 10.20 |
Empirical Analysis
The fsQCA results revealed seven configurations sufficient for high breakthrough innovation, which were categorized into five paradigms: R&D-driven, digital-driven, environment-driven, collaborative-driven, and innovation trial-and-error. Necessity analysis confirmed that no single condition was necessary, underscoring the equifinality of innovation paths. For example, the R&D-driven paradigm (Configuration S1) combines high technological diversification and R&D capability with the absence of high digitalization and organizational slack. This suggests that firms relying on internal knowledge synthesis can achieve innovation without extensive digital tools or slack resources.
The digital-driven paradigm (S2) emphasizes digitalization and technological diversification, indicating that data-driven agility compensates for lower R&D intensity. Environment-driven paths (S3a and S3b) highlight the role of infrastructure and business environment, where external support enables innovation despite internal limitations. Collaborative-driven configurations (S4a and S4b) integrate technological, organizational, and environmental elements, showcasing the synergy of cross-functional capabilities. The innovation trial-and-error paradigm (S5) relies on organizational slack and R&D but lacks knowledge absorption, implying that resource buffers allow for experimental innovation.
| Condition | S1 | S2 | S3a | S3b | S4a | S4b | S5 |
|---|---|---|---|---|---|---|---|
| Technological Diversification | ● | ● | ● | ● | ● | ● | ● |
| R&D Capability | ● | ⨂ | ⨂ | ⨂ | ● | ● | ● |
| Knowledge Absorption | ⨂ | ⨂ | ● | ⨂ | |||
| Digitalization Level | ⨂ | ● | ⨂ | ⨂ | ● | ● | ● |
| Organizational Slack | ⨂ | ⨂ | ⨂ | ⨂ | ⨂ | ● | |
| Infrastructure | ⨂ | ⨂ | ● | ● | ● | ● | ⨂ |
| Business Environment | ⨂ | ⨂ | ● | ● | ● | ⨂ | |
| Consistency | 0.868 | 0.817 | 0.814 | 0.828 | 0.909 | 0.833 | 0.884 |
| Coverage | 0.085 | 0.064 | 0.138 | 0.115 | 0.083 | 0.112 | 0.052 |
The complex mediation analysis tested the impact of these configurations on TFP via breakthrough innovation. Regression models showed that all paradigms except innovation trial-and-error had significant positive effects on TFP, with breakthrough innovation acting as a mediator. For instance, the R&D-driven path (S1) had a total effect of 0.896 on TFP, which reduced to 0.691 when controlling for innovation, indicating partial mediation. Similarly, digital-driven and environment-driven paths showed significant indirect effects, highlighting the importance of innovation as a conduit for performance enhancement.
The mediation effect can be formalized as:
$$\text{Indirect Effect} = \beta_{X \rightarrow M} \times \beta_{M \rightarrow Y}$$
where $\beta_{X \rightarrow M}$ is the effect of configuration X on innovation M, and $\beta_{M \rightarrow Y}$ is the effect of M on TFP Y. For S1, the indirect effect was calculated as 0.205, confirming mediation. Robustness checks using alternative TFP measures and Winsorized data yielded consistent results, reinforcing the validity of the findings.
| Configuration | Total Effect on TFP | Direct Effect (with Mediator) | Indirect Effect | Mediation Status |
|---|---|---|---|---|
| S1 (R&D-driven) | 0.896*** | 0.691*** | 0.205 | Partial |
| S2 (Digital-driven) | 0.796** | 0.707** | 0.089 | Partial |
| S3a (Environment-driven) | 0.454** | 0.475** | -0.021 | None |
| S3b (Environment-driven) | 0.415* | 0.444* | -0.029 | None |
| S4a (Collaborative-driven) | 0.728** | 0.515* | 0.213 | Partial |
| S4b (Collaborative-driven) | 0.147 | -0.056 | 0.203 | Full |
| S5 (Trial-and-error) | -0.216 | -0.550 | 0.334 | None |
These results underscore that most innovation paradigms in the low altitude economy enhance firm performance through breakthrough innovation, but the trial-and-error approach may lead to inefficiencies due to resource misallocation. The low altitude economy’s dynamic nature requires firms to balance exploration with operational efficiency to achieve sustainable growth.
Conclusion and Implications
This study demonstrates that breakthrough innovation in the low altitude economy is driven by multiple concurrent factors, with no single condition being necessary. The identified paradigms—R&D-driven, digital-driven, environment-driven, collaborative-driven, and innovation trial-and-error—highlight the diversity of strategies firms can adopt. The complex mediation model confirms that innovation acts as a critical mediator between these configurations and high-quality development, except in cases of trial-and-error where resource constraints hinder performance.
Theoretical contributions include extending the TOE framework to the low altitude economy context and introducing a novel methodology for analyzing complex mediation effects. Practical implications suggest that enterprises should align their innovation strategies with internal capabilities and external conditions, while policymakers should invest in infrastructure and regulatory frameworks to support the low altitude economy’s growth. Future research could explore longitudinal dynamics and cross-country comparisons to further elucidate innovation pathways in this emerging sector.
In summary, the low altitude economy offers immense opportunities for transformative innovation, and firms that effectively orchestrate technological, organizational, and environmental resources can achieve sustained high-quality development. As the sector evolves, continuous adaptation and strategic alignment will be key to harnessing its full potential.