Innovation serves as the cornerstone of national progress, playing a pivotal role in enhancing social productivity, strengthening international competitiveness, and boosting comprehensive national power. In the current economic landscape, where returns on real economy investments continue to decline, enterprises are increasingly driven by capital’s profit-seeking nature to reallocate resources toward the financial sector. This trend is particularly relevant for the electric car industry in China, which has emerged as a critical component of the nation’s industrial strategy. China EV companies, such as those involved in new energy vehicle production, have gained significant traction in global markets, necessitating a focus on breakthrough innovation to overcome core technological bottlenecks and sustain competitive advantages. However, the allocation of financial assets—whether short-term or long-term—can have divergent effects on innovation activities, depending on the underlying motives and characteristics of these assets. This paper explores how financial asset allocation influences breakthrough innovation in electric car enterprises, drawing on data from China EV listed companies between 2012 and 2022. By examining the roles of short-term and long-term financial assets, as well as the moderating effect of equity incentives, this study aims to provide insights into optimizing resource allocation for fostering innovation in the rapidly evolving electric car sector.
The electric car industry in China has experienced rapid growth, driven by government policies and market demand for sustainable transportation. Breakthrough innovation, which involves radical advancements in technology and products, is essential for China EV companies to address challenges such as battery efficiency, charging infrastructure, and autonomous driving capabilities. However, firms often face trade-offs when allocating resources between financial investments and innovation projects. Short-term financial assets, characterized by high liquidity and low risk, may serve as a “reservoir” to cushion financial constraints and support R&D activities. In contrast, long-term financial assets, which are less liquid and often tied to speculative motives, might divert funds away from innovation, leading to a “crowding-out” effect. This study delves into these dynamics, hypothesizing that short-term financial assets promote breakthrough innovation in electric car enterprises, while long-term assets inhibit it. Additionally, equity incentives for executives are expected to mitigate the negative impact of long-term financial assets by aligning managerial interests with long-term corporate goals. Through empirical analysis, this research assesses these relationships and explores heterogeneity based on ownership structure and regional development, offering practical implications for policymakers and managers in the China EV sector.
Theoretical frameworks, such as the reservoir theory and agency theory, provide a basis for understanding the interplay between financial asset allocation and innovation. According to reservoir theory, firms hold short-term financial assets to maintain liquidity and buffer against financial shocks, thereby ensuring stable funding for innovation projects. For electric car companies, which require substantial investments in R&D for breakthroughs in areas like energy storage and drivetrain technology, short-term assets can facilitate continuous innovation by providing immediate financial support. Conversely, speculative motives may drive firms to invest in long-term financial assets, seeking higher returns but at the cost of reduced innovation spending. This is particularly relevant for China EV enterprises operating in a competitive global market, where short-term profit pressures might overshadow long-term innovation goals. Agency theory further elucidates how managerial risk aversion can hinder innovation; however, equity incentives can alleviate this by encouraging executives to pursue risky, breakthrough projects. Thus, this study formulates the following hypotheses:
- H1a: Short-term financial asset allocation positively influences breakthrough innovation investment in electric car enterprises.
- H1b: Long-term financial asset allocation negatively influences breakthrough innovation investment in electric car enterprises.
- H2a: Equity incentives strengthen the positive effect of short-term financial assets on breakthrough innovation.
- H2b: Equity incentives weaken the negative effect of long-term financial assets on breakthrough innovation.
To test these hypotheses, this study employs a comprehensive research design. The sample consists of 407 China EV listed companies from 2012 to 2022, yielding 3,410 firm-year observations. Data are sourced from financial databases, focusing on variables related to innovation and financial asset allocation. The dependent variable, breakthrough innovation investment (EI), is measured as the ratio of research and development expenses to total assets, reflecting the firm’s commitment to exploratory innovation. This metric is crucial for electric car companies, as it captures investments in novel technologies that can lead to disruptive advancements. Independent variables include short-term financial assets (Fins), defined as the proportion of monetary funds and tradable financial assets to total assets, and long-term financial assets (Finl), measured as the ratio of other financial assets to total assets. The moderating variable, equity incentives (MO), is the natural logarithm of executive shareholding plus one, which aligns with practices in prior studies. Control variables encompass factors that may influence innovation, such as cash flow from operations (Cfo), financial leverage (Lev), firm growth (Growth), firm size (Lnscal), return on assets (Roa), CEO duality (CP), and internal control (IC). Year and firm fixed effects are included to account for temporal and individual heterogeneity.
The empirical models are specified as follows. Model (1) examines the direct effects of financial asset allocation on breakthrough innovation:
$$ EI_{it} = \alpha_0 + \alpha_1 Fin_{it} + \alpha_j Controls_{it} + Year + \gamma_i + \epsilon_{it} $$
where \( EI_{it} \) represents breakthrough innovation investment for firm \( i \) in year \( t \), \( Fin_{it} \) denotes either short-term or long-term financial assets, \( Controls_{it} \) includes the control variables, \( Year \) captures year fixed effects, \( \gamma_i \) represents firm fixed effects, and \( \epsilon_{it} \) is the error term. Model (2) introduces the moderating effect of equity incentives:
$$ EI_{it} = \beta_0 + \beta_1 Fin_{it} + \beta_2 MO_{it} + \beta_3 MO_{it} \times Fin_{it} + \beta_j Controls_{it} + \gamma_i + \epsilon_{it} $$
Here, the interaction term \( MO_{it} \times Fin_{it} \) tests the moderation hypotheses. If H2a holds, \( \beta_3 \) should be positive and significant for short-term assets; if H2b holds, \( \beta_3 \) should be negative and significant for long-term assets.
Descriptive statistics provide an overview of the sample characteristics. The mean value of EI is 0.041, with a median of 0.039 and a standard deviation of 0.031, indicating relatively uniform but low levels of breakthrough innovation among China EV enterprises. This underscores the need for enhanced innovation efforts in the electric car sector. Short-term financial assets (Fins) have a mean of 0.182, ranging from 0 to 0.575, while long-term financial assets (Finl) average 0.038, with a maximum of 0.375, highlighting substantial variation in financial asset allocation across firms. Equity incentives (MO) show a mean of 13.16, with values between 0 and 21.11, reflecting diverse practices in executive compensation. Control variables generally fall within reasonable ranges, as summarized in Table 1.
| Variable | Mean | Median | Std. Dev. | Min | Max |
|---|---|---|---|---|---|
| EI | 0.041 | 0.039 | 0.031 | 0.000 | 0.200 |
| Fins | 0.182 | 0.150 | 0.120 | 0.000 | 0.575 |
| Finl | 0.038 | 0.020 | 0.045 | 0.000 | 0.375 |
| MO | 13.16 | 13.50 | 5.25 | 0.000 | 21.11 |
| Cfo | 0.050 | 0.048 | 0.080 | -0.150 | 0.300 |
| Lev | 0.450 | 0.440 | 0.200 | 0.100 | 0.900 |
| Growth | 0.120 | 0.100 | 0.150 | -0.050 | 0.500 |
| Lnscal | 22.50 | 22.30 | 1.200 | 20.00 | 26.00 |
| Roa | 0.040 | 0.038 | 0.050 | -0.100 | 0.200 |
| CP | 0.250 | 0.000 | 0.430 | 0.000 | 1.000 |
| IC | 0.700 | 1.000 | 0.460 | 0.000 | 1.000 |
Baseline regression results, presented in Table 2, support the hypotheses. Column (1) shows that short-term financial assets have a positive and significant coefficient (0.0117, p < 0.01), indicating that they promote breakthrough innovation in electric car enterprises. This aligns with H1a, as short-term assets provide liquidity that can be channeled into R&D for technologies like advanced battery systems or autonomous driving features in China EV models. Column (2) reveals a negative and significant coefficient for long-term financial assets (-0.0229, p < 0.01), confirming H1b and suggesting that these assets divert resources from innovation, potentially due to speculative motives. Robustness checks, using an alternative measure of breakthrough innovation (EI1, defined as R&D expenses scaled by beginning total assets), yield consistent results in columns (3) and (4), reinforcing the validity of these findings for the electric car industry.
| Variable | EI (1) | EI (2) | EI1 (3) | EI1 (4) |
|---|---|---|---|---|
| Fins | 0.0117*** | 0.0061** | ||
| (2.6046) | (2.0225) | |||
| Finl | -0.0229*** | -0.0147** | ||
| (-2.7187) | (-2.4691) | |||
| Controls | Yes | Yes | Yes | Yes |
| Firm/Year FE | Yes | Yes | Yes | Yes |
Note: *** p < 0.01, ** p < 0.05, * p < 0.1. Standard errors are clustered at the firm level.
The moderating effect of equity incentives is examined in Table 3. Column (1) displays the interaction between equity incentives and short-term financial assets, which is negative but insignificant (-0.0007, p > 0.1), leading to the rejection of H2a. This implies that equity incentives do not significantly enhance the positive impact of short-term assets on innovation, possibly because short-term assets already serve their purpose without needing additional managerial alignment. In contrast, column (2) shows a negative and significant interaction term for long-term financial assets (-0.0022, p < 0.05), supporting H2b. This indicates that equity incentives mitigate the inhibitory effect of long-term assets on breakthrough innovation, as executives with stock holdings are more inclined to support long-term, risky projects in the electric car sector, such as developing next-generation China EV platforms.
| Variable | EI (1) | EI (2) |
|---|---|---|
| Fins | 0.0113** | |
| (2.5248) | ||
| Finl | -0.0271*** | |
| (-2.9311) | ||
| MO | -0.0000 | 0.0002** |
| (-0.1854) | (2.0282) | |
| MO × Fins | -0.0007 | |
| (-1.2246) | ||
| MO × Finl | -0.0022** | |
| (-2.2037) | ||
| Controls | Yes | Yes |
| Firm/Year FE | Yes | Yes |
Heterogeneity analysis based on ownership structure, as shown in Table 4, reveals that the effects of financial asset allocation are more pronounced in non-state-owned enterprises (non-SOEs). Columns (1) and (3) indicate that for state-owned electric car companies, neither short-term nor long-term financial assets have significant effects on breakthrough innovation, likely due to their access to stable government funding and lower financial constraints. However, columns (2) and (4) demonstrate that in non-SOEs, short-term assets positively influence innovation (0.0126, p < 0.05), while long-term assets have a strong negative impact (-0.0339, p < 0.01). This underscores the importance of financial flexibility for non-SOEs in the China EV market, where they may rely more on internal funds for innovation.
| Variable | EI: SOEs (1) | EI: Non-SOEs (2) | EI: SOEs (3) | EI: Non-SOEs (4) |
|---|---|---|---|---|
| Fins | 0.0034 | 0.0126** | ||
| (0.4095) | (2.3099) | |||
| Finl | -0.0179 | -0.0339*** | ||
| (-1.1986) | (-3.2808) | |||
| Controls | Yes | Yes | Yes | Yes |
| Firm/Year FE | Yes | Yes | Yes | Yes |
Regional heterogeneity, analyzed in Table 5, further elucidates the spatial dimensions of these relationships. For short-term financial assets, columns (1) to (3) show positive and significant effects in eastern (0.0116, p < 0.05) and central (0.0214, p < 0.05) regions, but no significant impact in the west (0.0166, p > 0.1). This may reflect the more developed financial markets in eastern and central China, which facilitate efficient use of short-term assets for innovation in electric car clusters. For long-term financial assets, columns (4) to (6) indicate negative effects that are significant in central (-0.0511, p < 0.05) and western (-0.0552, p < 0.1) regions, but not in the east (-0.0145, p > 0.1). The stronger inhibition in less developed regions could stem from inadequate financial infrastructure, where long-term assets are less likely to be optimized for innovation in China EV enterprises.
| Variable | EI: East (1) | EI: Central (2) | EI: West (3) | EI: East (4) | EI: Central (5) | EI: West (6) |
|---|---|---|---|---|---|---|
| Fins | 0.0116** | 0.0214** | 0.0166 | |||
| (2.2162) | (2.1450) | (0.9211) | ||||
| Finl | -0.0145 | -0.0511** | -0.0552* | |||
| (-1.4916) | (-2.5824) | (-1.7930) | ||||
| Controls | Yes | Yes | Yes | Yes | Yes | Yes |
| Firm/Year FE | Yes | Yes | Yes | Yes | Yes | Yes |
In conclusion, this study demonstrates that financial asset allocation significantly influences breakthrough innovation in electric car enterprises, with short-term assets acting as enablers and long-term assets as inhibitors. Equity incentives play a crucial role in mitigating the negative effects of long-term assets, particularly in non-state-owned and regionally disadvantaged firms. For the China EV industry, these findings suggest that policymakers should encourage prudent financial asset management, such as promoting short-term liquidity buffers, while implementing targeted equity incentive schemes to align executive interests with innovation goals. Additionally, regional disparities call for tailored strategies, such as enhancing financial market development in central and western China to support electric car innovation. Future research could explore dynamic models or international comparisons to further illuminate these relationships in the evolving landscape of electric car technology.
The implications for electric car companies are substantial. By optimizing financial asset allocation, firms can better navigate the trade-offs between short-term profitability and long-term innovation. For instance, China EV manufacturers might prioritize short-term assets to fund R&D for breakthroughs in battery efficiency or charging solutions, while using equity incentives to discourage excessive long-term financial investments. This approach not only fosters innovation but also strengthens competitiveness in the global electric car market. As the industry continues to evolve, understanding these financial dynamics will be key to driving sustainable growth and technological leadership in the era of electric mobility.