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Abstract

China’s GEM (Growth Enterprise Market, also named as ChiNext stock market) enterprises are mainly small and medium-sized enterprises in the start-up stage, which have high-speed growth. This work uses three-stage least squares (3SLS) based on combines system equation to study the impact of technological innovation investment, executive incentive, and enterprise financial performance. The results show that in China’s GEM enterprises, R&D in the current period positively affects financial performance in 1% significance level. R&D of the lag period has a significant negative impact on the financial performance of the current period. Conversely, the financial performance of the current period has a significant negative impact on R&D. While both salary incentive and equity incentive will improve financial performance, executives seem to value short-term interests MORE. Executive equity incentive has a significant negative moderating effect ownership due to ownership structure in GEM is needed to strengthen the control right. This work proposes a new research horizon in GEM in China, and can help the GEM design an effective management mechanism to improve the financial performance of the enterprise.

Keywords

R&D investment executive incentive financial performance GEM listed companies endogenous problem

Introduction

GEM (Growth Enterprise Market, also named as ChiNext stock market) market serves small and medium-sized enterprises in China. Compared with the main-board markets in Beijing and Shanghai, the main body of GEM is growth enterprises, especially science and technology entrepreneurial start-up (Martin & Wang, 2015; Yi et al., 2021). GEM is an important supplement to China’s main board market in Shanghai and Shenzhen. In China, its stock code starts with “300.” GEM is characterized by low threshold, high risk and strict supervision. Its purpose is to encourage the development of entrepreneurial start-up (Gui et al., 2022) and realize the independent innovation strategy of domestic enterprises.

On October 23, 2009, the China GEM held the commence ceremony (Yi et al., 2021). On October 30, 2009, the GEM was officially started, which has gone through 12 years up to now. It can be seen from Table 1 that China’s GEM enterprises number have reached 1090, with a total market value of 2057.2 billion USD and a daily turnover of 35.2 billion USD (Shenzhen Stock Exchange, 2022). GEM has become a favorable promoter to integrate of traditional industries with new technologies, new industries, and new commercial mode (Martin & Wang, 2015). Representative enterprises in GEM include Tongyu Heavy Industry Co., Ltd. (300185), Cixing Co., Ltd. (300307), Risen Energy Co., Ltd. (300118), AIer Eye Hospital (300015), Zhenxin Technology (300101), Gao Meng New Materials Co., Ltd. (300200), etc.

Table 1.

Transactions of Chinese GEM Enterprises by 2021.

Indicator name	Data at 21.12.31	Increase over the previous day	Growth rate (%)
Number of newly listed companies	0	—	—
Number of listed companies	1,090	0	0.00
Total share capital (billion shares)	516.5	1.1	0.22
Circulating share capital (billion share)	393.6	0.9	0.24
Total market value (billion USD)	2057.2	5.39	0.26
Circulation market value (billion USD)	1439.3	4.0	0.28
Transaction amount (billion USD)	35.2	−0.67	−1.88
Number of transactions	16,980,121	−748,999	−4.22
Average P/E ratio (times)	59.99	0.14	0.23
Highest index	3,353.57	13.91	0.42
Lowest index	3,315.07	34.76	1.06
Close index	3,322.67	−0.12	−0.00

Source. Shenzhen Stock Exchange.

In this work, we collect data on GEM R&D expenses from 2016 to 2021. The results are obtained from the average annual R&D expenditure from 451 valid samples. From Figure 1, we find a noticeable phenomenon: the annual R&D expenses is very striking. At the same time, the year-on-year growth shows an obvious trend. This may be due to the characteristics of this sector: GEM enterprises need a lot of R&D expenditure. The above rapid growth has attracted the interest of researchers: What are the consequences of the rapid growth of GEM R&D expense? What factors influence the growth of GEM R&D funds? These issues need to be discussed in depth.

Figure 1.

Change of GEM R&D expenses from 2016 to 2021.

The advantages and disadvantages of R&D expenses on financial performance are widely discussed topics. While some scholars believe that R&D expenditure has a positive effect (Vanderpal 2015; N. Wang et al., 2017), the other empirical evidence shows R&D expenditure has a long cycle, high risks and uncertain future returns (Huang et al., 2014; Kim et al., 2016; Saliba et al., 2018). When this controversial topic is introduced into GEM, it becomes more highlighted. Due to the characteristics of high risk and return of GEM enterprises (S. N. Xu et al., 2011), whether to increase the current period R&D investment has become the focus of researchers.

Generally speaking, innovation advantages include core competitiveness of enterprises. Innovation is fundamental for the future sustainable development of enterprises (Acemoglu et al., 2018). The progressing of entrepreneurial global economic integration intensifies the competition among enterprises all over the world, and the key factor for the success of enterprise is technological innovation (Hitt et al., 1997).

On the other hand, the disadvantage of R&D activities is that they may incur uncertainty and risk. The smooth implementation of this technological innovation strategy must be backed by a large amount of R&D funds, especially for high-tech enterprises (Chan et al., 1990). Regarding GEM, a large amount of R&D investment is a crucial management decision, which needs to be evaluated based on financial performance. So whether innovative activities can bring about future profit growth still needs to be explored.

The R&D process of enterprises is relatively long-term process. In the relatively long-term process, there will be interference from financial, resource, human and other factors. Among these factors, senior executives play the most important role. As the leading force in enterprise operation, senior managers determine the direction and goal of enterprise operation. The attitude of senior managers will directly affect the success of technological innovation (Miao et al., 2018). So the influence of senior managers related to the association between the R&D investment and financial performance is strongly highlighted. In the reality, senior executives often fall into a dilemma when involving in R&D activity.

On the one hand, managers’ income mainly depends on short-term financial operation performance (Bennett et al., 2017). The new R&D plan will reduce the current cash flow of operating activities and affect the financial net profit margin. On the other, the new R&D plan will improve the future value of the company and enhance shareholders’ equity (Vanderpal, 2015). In order to solve the short-term choice of executives, a sound incentive system must be designed. An effective incentive mechanism is the key to ensure the managers to facilitate innovation activities (X. L. Xu et al., 2020). The implementation of the mechanism, including salary incentive and equity incentive for executives, will directly reduce their short-sighted behavior and departmentalism. In order to reduce the supervision cost of equity owners, the company also can carry out incentive plans to achieve the convergence interests between the management and shareholders (X. L. Xu et al., 2019). This incentive plan can guarantee the supply of technological innovation resources, further improve the enterprise’s technological R&D ability, and finally improve enterprise financial performance (C. Cheng, 2018). Therefore, the impact of executives incentive on GEM’s innovation activities needs to be studied. And a incentive system needs to be designed through research conclusions.

This work has several contributions to the existing literature. First, based on endogenous considerations, this work studies the bidirectional relationship between R&D investment and financial performance. Compared with previous studies, a large number of literature discussed the one-way relationship between R&D investment and financial performance. This work reveals the two-way relationship between them in different time period through the method of Three-Stage Least Squares (3SLS). Furthermore, in the test of R&D expense, executive incentive and financial performance in GEM, this work adopts OLS and 3SLS estimation methods simultaneously. Through result comparison, it is found that the 3SLS method is more robust and reliable under the premise of endogenous. At the same time, this work absorbs more control variables in the analysis, so that the conclusions of the analysis are more accurate. Finally, this work finds that equity incentive plays a negative role in GEM. The research gap lies in a large number of literature discuss the advantages of equity incentive, but ignore the disadvantages of equity dilution of start-ups in GEM. This paper proposes the negative effects and underlying reasons of equity incentive in GEM. The rest of this study is organized as follows. Section 2 puts forward the literature review, and Section 3 presents the research method, data sources and variables. Section 4 presents the empirical analysis while the last section concludes and makes suggestions.

Literature Review and Research Hypothesis

At present, the research on the relationship between executive compensation incentive, technological innovation and enterprise financial performance at home and abroad mainly included in the following three aspects.

Technological Innovation and Enterprise Financial Performance

There are abundant literatures on the relationship between technological innovation strategy and enterprise financial performance. Some scholars focus on the relationship between R&D activities and corporate profitability (Artz et al., 2010; Bigliardi, 2013; Saliba et al., 2018). The other part focuses on the impact of R&D activities on the value of the company (Connolly & Hirschey, 2005; Parcharidis & Varsakelis, 2010; Sofronas et al., 2020). Most studies showed that R&D activities had a positive relationship with profitability and corporate value. Zhang (2018) argued that if enterprises want to improve their core competitiveness and enterprise market value, technological innovation strategy must be carried out. Qin et al. (2019) found that technological innovation had a partialing effect on ownership structure and enterprise financial performance. However, some scholars have advised opposite conclusion. Since R&D activity is a long-term return, it increases the uncertainty of enterprises (Saliba et al., 2018). Enterprises engaged in R&D bear high risks and the failure may be a fatal to small and medium-sized enterprises. R&D expenditure is a competition that may harm the financial performance of enterprises (Kim et al., 2016).

For example, Huang et al. (2014) conducted econometric analysis on the R&D investment and corporate performance of agricultural listed companies using the individual random effects model. The econometric analysis results showed that the positive impact of R&D investment on corporate financial performance was not significant. On the contrary, there was a weak negative impact on financial performance.

In our work, enterprises listed on the GEM are more dependent on R&D than those listed on the main board (Li & Hou, 2019). Therefore, technological innovation is particularly important for GEM enterprises. Through regression analysis of technological innovation input and profitability, some scholars found that there was a positive causal relationship between technological innovation input and profitability of high-tech enterprises (Liang & Zhang, 2005). Moreover, the greater the R&D investment, the higher the financial performance of the enterprise (Liang & Zhang, 2005; N. Wang et al., 2017). At the same time, there was an inverted U-shaped relationship between the sustainability of technological innovation and corporate financial performance (He & Zhang, 2017). Similar research evidence has also been found in other industries. J. M. Xu et al. (2018) concluded a significant positive correlation between low-carbon R&D investment and financial performance of equipment manufacturing enterprises.

Based on the previous research, this study makes the following assumptions:

H1: R&D investment has a significant positive correlation with enterprise financial performance.

Executives Incentive and Enterprise Financial Performance

The word motivation comes from Latin (Movere), which originally means to promote or advance. In modern enterprise organizations, leaders, or managers of enterprises often carry out targeted promotion plans for employees according to organizational goals, so as to generate motivation and achieve the expected goals. The achievements of the traditional incentive theory school have been very plentiful, such as Taylor Theory (Peaucelle, 2000), which emphasizes differential pricing reward; Hawthorne Experiment led by Mayo (Önday, 2016), which found the existence of informal organizations; the opposite XY Theory proposed by McGregor (1985) in his book The human side of enterprise.

At present, with the establishment of modern enterprise system, the incentive content within the enterprise is constantly changing, and the incentive theory is also continuously innovating and developing. For instance, the five-level demand theory of physiology, safety, society, respect, and self-realization (Maslow, 2007); two factor theory of motivation and healthcare factors (Herzberg et al., 2009), which explains the reasons for job satisfaction and dissatisfaction. Skinner Theory, emphasizing that human behavior is affected by past results and highlighting the role of enhancement, avoidance, punishment and fade out (Xie, 2003). Previous incentive theories provided a lot of research basis, and all emphasize the importance and methods of motivating employees in the organization. In GEM, senior managers play a leading role in Chinese organizational culture. So the incentive of senior managers is imperative to the whole company.

In GEM in China, enterprises are at a stage of rapid growth. As entrepreneurial and start-up enterprises, most of GEM are high-tech SMEs. Therefore, it is necessary to study the relationship between executive incentive and financial performance. As a result, these high-tech SMEs can becoming a formal main board listed company. In terms of the relationship between salary incentive and enterprise performance: Abowd (1990) conducted a study on the relationship between executive compensation and corporate financial performance, showing that executive compensation had a significant positive correlation with stock returns.

J. C. Sun et al. (2019) believed that the executive payroll gap can affect the power of the management, and the improvement of the management power will in turn widen the executive payroll gap. The widening salary gap with the different hierarchy staffs can stimulate the motivation of executives, which will eventually increase the financial performance of the enterprise. So the listed companies can increase the actual monetary compensation of executives to increase the loyalty, so as to improve their work efficiency, and finally improve the financial performance (Demirer & Yuan, 2013; Mehran, 1995).

On the other hand, there are many works supporting the relationship between equity incentive and enterprise performance: Listed companies usually implement equity incentive plans to align the interests of both parties (C. H. Wang et al., 2021). Because the stock value held by senior executives is closely related to the performance of the enterprise. In the medium and long term of enterprise development, equity incentive is more effective than cash incentive (Q. Cheng & Warfield, 2005). The shareholding makes them more loyal to the company and exert more effort on the work (Tchistyi et al., 2011). The literature showed that compensation and equity incentive both had a significant positive impact on corporate financial performance.

Based on the above literature, this study proposes the following assumptions:

H2a: Executive compensation incentive has a significant positive correlation with enterprise financial performance.

H2b: Executive equity incentive has a significant positive correlation with enterprise financial performance.

Moderating Effect of Executive Incentive on R&D Investment and Enterprise Financial Performance

In the operation of enterprises, the relationship between the two variables may be affected by other factors. This is indeed the case in the relationship between R&D investment and enterprise financial performance. The agent theory holds that once there is information asymmetry between the principal and the agent, the principal will sign a series of contracts with them in order to prevent the agent’s moral hazard and adverse action selection (Jensen & Meckling, 1976). In this theory, agency cost includes three aspects: supervision cost, guarantee cost, and residual loss. The first two are the costs actually incurred in the operation of the enterprise, and the third is the opportunity cost. In order to ensure that managers work with the interests of owners and reduce agency costs, appropriate incentive contracts are necessary (C. H. Wang et al., 2021).

On the other hand, the business operation will face fierce competition and uncertainty of the environment, senior managers may take risk aversion to technological innovation on behalf of their interests (Guan & Zhang, 2020; Xi & Zhang, 2021). According to agency theory, the most important game is the asymmetry of information (Joura et al., 2021). The management may start from their own selfish perspective, and choose non-corporate value maximization (Van Dun et al., 2017). In China’s compensation system, owners often assess the ability of senior managers through year-end bonus (Yao, 1997). The amount of the bonus depends on the company’s sales achievement rate, annual plan completion rate, PKI completion rate, etc. As it is known to all, investment innovation mainly focuses on long-term returns, and it maybe harmful to short-term returns (Crowley & Jane, 2018). That is, managers will reduce the R&D expenses and operating costs of the current period, in order to improve the profit level (X. L. Xu et al., 2020).

These shortsighted behaviors are extremely harmful to the sustainable development of enterprises, so effective measures must be taken to eliminate these action. Then the resources of technological innovation can be guaranteed, and finally the performance can be improved (Kato et al., 2007). Zhang et al. (2014) believed that Chinese information technology enterprises can design effective senior executives salary management system. Through this system, the company could reduce their risk aversion behavior, ensure the process of technological innovation, and finally promote the further financial performance. It can be seen that executives, as the key figures of the enterprise and an integral part of the core labor force, will play a positive transitional role. Executive incentive not only can promote enterprise financial performance directly, but also have a moderating effect through innovation activity to financial performance (Guo et al., 2019).

Excellent incentive measures can alleviate agency and management defense (X. L. Xu et al., 2020), so that managers can pay more attention to innovation and development (Crowley & Jane, 2018). Equity incentive enables management to focus on long-term goals and guide senior executives to promote innovation activities (Miller et al., 2002). The implementation of equity incentive can encourage managers to carry out innovative activities and drive the interests of management to be the same as those of shareholders (X. L. Xu et al., 2020; Zahra et al., 2000). Senior executives can incentive the enthusiasm of the overall employees, integrated the company’s resources, and improve the company’s performance to the greatest extent.

Based on this, this study proposes the following assumptions:

H3a: Executive compensation incentive plays a positive moderating role in R&D investment and enterprise financial performance.

H3b: Executive equity incentive plays a positive moderating role in R&D investment and enterprise financial performance.

Research Design

Sample Selection and Data Source

GEM listed companies are generally abundant in high-tech enterprises, who pay more attention to technological innovation and have high growth in their operation progress. Therefore, this work selects the companies listed on GEM in 2016 to 2021 as the research sample, excluding companies with missing data and abnormal data. Finally, 451 companies remind for the next analysis. Among them, the return on equity, R&D investment, total remuneration of top three executives, total assets, growth rate of operating revenue and asset liability ratio, and other indicators are mainly provided by WIND database.

Variable Quantity Selection and Definition

Explained Variables

The financial performance is a traditional research topic (Kaplan & Norton, 1996; Plumlee et al., 2015; Solomons, 1965; Stern et al., 1995). At the same time, famous measurement standard proposed by DuPont (DuPont analysis) also use return on net assets (ROE) as the core indicator (Burja & Mărginean, 2014). Academic circles generally believe that this index can systematically and comprehensively reflect the profitability of enterprises, and can be used to evaluate the profitability of companies. Therefore, this work selects the rate of return on equity (ROE) to measure the financial performance of enterprises. It is the ratio of profit after tax to owner’s equity. The ratio reflects the profitability of owner’s equity. This indicator can measure the efficiency of enterprises in using their own capital, and is widely used in literature measuring the financial performance (C. H. Wang et al., 2021; Xing et al., 2014). The higher the ratio, the stronger the profitability of enterprises. Refer to a number of domestic scholars (Tong & Wei, 2021; S. N. Xu et al., 2011), this study uses ROE to measure the financial performance of GEM.

Explanatory Variables

The index of R&D investment can scientifically and reasonably reflect the actual effect of technological innovation strategy. Generally, scholars will use R&D investment (Erdogan & Yamaltdinova, 2019) to measure the innovation. Moreover, it is more reasonable to replace R&D expenditure with R&D density in order to avoid the impact of the size of enterprises. Drawing on previous literature (Chauvin & Hirschey, 1993; J. M. Liu & Zhou, 2018; Shih, 2008), this paper measures R&D density through dividing R&D expenditure by the net amount of sales revenue in the current year. The indicators of R&D density can make enterprises of different sizes horizontally comparable. Therefore, this work selects R&D investment density (RDD) as the explanatory variable.

Moderating Variables

Because salary of senior executives (SAL) plays a moderating role between technological innovation strategy and enterprise financial performance, this work chooses it as the moderating variables of this model. “Total compensation of top three executives” (Quan et al., 2010; Z. J. Wang & Mai, 2019; Zou et al., 2015) can better reflect executive compensation incentive (SAL). Based on previous literature (Q. Cheng & Warfield, 2005; Tchistyi et al., 2011), equity incentive is also an important influence variable. Equity incentive plan (EQ_INC) can motivate CEO to promote R&D process (Miller et al.,2002; Zahra et al., 2000). Therefore, this work selects these two incentive factors as the moderate variable.

Control Variables

On the basis of existing relevant literature (Andersen & Dejoy, 2011; Hu, 2015; Jin, 2021; J. M. Liu & Zhou, 2018; C. H. Wang et al., 2021; X. L. Xu et al., 2020), eight variables are selected as control variables: the natural logarithm of total asset (SIZE) reflecting enterprise size; financial leverage (LEV) reflecting solvency; growth of operating income (GROWTH) reflecting growth; Equity concentration (EQ_CON) reflecting the concentration of common shares issued outward; Equity balances (EQ_BAL) reflecting appropriate control rights in the company; Cash flow (CF) reflecting the financial flexibility of the enterprise; The integration of the two positions (DUAL) reflecting the internal governance structure of the enterprise; The proportion of technicians (TECH) reflecting the allocation of human resources in enterprises.

The specific variable definition and sources are shown in Table 2.

Table 2.

Variable Names and Definitions.

Variable type	Name	Representative symbol	Definition	Reference
Explained variable	Return on equity	ROE	Profit after tax/owner’s equity	S. N. Xu et al. (2011), Burja and Mărginean (2014), Xing et al. (2014), C. H. Wang et al. (2021), and Tong and Wei (2021)
Explanatory variable	R&D investment Density	RDD	R&D expenses/net sales revenue	Chauvin and Hirschey (1993), Shih (2008), J. M. Liu and Zhou (2018), Erdogan and Yamaltdinova (2019)
Moderating variable	Salary incentive of senior executives	SAL	Natural logarithm of total remuneration of top three executives	Zou et al. (2015), Z. J. Wang and Mai (2019), Quan et al. (2010), Q. Cheng and Warfield (2005), Tchistyi et al. (2011), Miller et al. (2002), and Zahra et al. (2000)
Moderating variable	Equity incentive of senior executives	EQ_INC	Shareholding ratio of senior executives
Control variable	Enterprise size	SIZE	Natural logarithm of total assets	Andersen and Dejoy (2011), Hu (2015), J. M. Liu and Zhou (2018), X. L. Xu et al. (2020), C. Wang et al. (2021), and Jin (2021)
	Financial leverage	LEV	Total liabilities/total assets
	Growth rate of the company	GROWTH	(current operating income − previous operating income)/previous operating income
	Equity concentration ratio	EQ_CON	Shareholding ratio of the largest shareholder
	Equity balance Ratio	EQ_BAL	Shareholding ratio of the second to fifth largest shareholder/the first largest shareholder
	Cash liquidity	CF	Cash flow from operating activities/operating income
	Integration of two positions	DUAL	Whether the chairman and CEO are the same person
	Proportion of technicians	TECH	Number of technicians/total employees

Model Design

According to the previous theoretical analysis and research assumptions, the following three models are constructed to test the relationship.

\begin{matrix} RD D_{i, t} = & α_{0} + α_{1} RO E_{i, t} + α_{2} RO E_{i, t - 1} + α_{3} RO E_{i, t - 2} \\ + \sum_{j = 1}^{k} θ_{j} C_{j, i, t} + μ_{i, t} \end{matrix}

\begin{matrix} RO E_{i, t} = & β_{0} + β_{1} RD D_{i, t} + β_{2} RD D_{i, t - 1} + β_{3} RD D_{i, t - 2} \\ + \sum_{m = 1}^{n} θ_{m} C_{m, i, t} + ε_{i, t} \end{matrix}

(1)/(2)

\begin{matrix} RO E_{i, t} = & γ_{0} + γ_{1} RD D_{i, t - 1} + γ_{2} RD D_{i, t - 2} + γ_{3} SA L_{i, t - 1} \\ + γ_{4} EQ_IN C_{i, t - 1} + γ_{5} (RD D_{i, t - 1} * SA L_{i, t - 1}) \\ + γ_{6} (RD D_{i, t - 1} * E {Q_{INC}}_{i, t - 1}) + \sum_{p = 1}^{q} θ_{p} C_{p, i, t} + φ_{i, t} \end{matrix}

(3)

The model (1)/(2) is used for the relationship between RDD and ROE to verify Hypothesis 1.

In addition, in order to test the moderating effect of SAL/EQ_INC between RDD and ROE, model (3) adds the cross term (RDI × SAL/RDI × EQ_INC) on the basis of model (1) and model (2).

Cross items used to verify Hypothesis 3a/3b.

If the cross term is significant in statistics, it shows that SAL/EQ_INC has a moderating effect on RDD and ROE.

Empirical Analysis

Descriptive Statistical Analysis

Descriptive analysis generally shows the basic data fluctuation and distribution. This study used Stata to carry out descriptive statistics, and the specific results are shown in Table 3. In order to reduce the impact of extreme values before data analysis, the data shall be shrunk by 1%. The variables SAL and SIZE use the natural logarithm of their original values.

Table 3.

Descriptive Statistical Results.

Variables	Obs.	M	SD	Min.	Max.
ROE	2,706	4.659	15.96	−124.9	41.67
RDD	2,706	8.004	6.346	0.320	43.56
SAL	2,706	5.282	0.586	3.642	7.030
EQ_INC	2,706	14.99	16.26	0.00513	67.01
SIZE	2,706	21.65	0.856	19.87	24.52
LEV	2,706	34.45	17.44	4.412	87.41
GROWTH	2,706	19.94	38.42	−59.40	352.0
EQ_CON	2,706	27.09	11.94	5.605	61.86
EQ_BAL	2,706	98.82	70.14	9.334	330.8
CF	2,706	10.28	15.97	−55.27	69.98
DUAL	2,706	0.413	0.492	0	1
TECH	2,706	33.14	21.58	3.990	90.76

From the statistical results in Table 3, we can see the mean of RDD is 8.004%. The highest financial performance ROE of enterprises listed on GEM is 41.67%, and the lowest is −124.9%, which means that the performance of enterprises vary dramatically. There are remarkable differences in profitability level between different companies. The difference of executive compensation of enterprises listed on GEM is minute. The standard deviation is 0.586. The data fluctuation is subtle.

Correlation Analysis

Correlation analysis is an important method to test association between variables. Stata is used to analyze the correlation of samples, and the relevance is generally determined by the level of significance. The specific output is shown in Table 4. The correlation relationship between ROE and RDD is significant negative at 1%. The two variables SAL, EQ_INC showed significant positive correlation with ROE at the significance level of 1%. This has preliminarily verified the previous assumption.

Table 4.

List of Correlation Analysis Results.

	ROE	RDD	SAL	EQ_INC	SIZE	LEV	GROWTH	EQ_CON	EQ_BAL	CF	DUAL	TECH
ROE	1
RDD	−.129***	1
SAL	.058***	.104***	1
EQ_INC	.108***	.032*	−.135***	1
SIZE	.040**	−.138***	.448***	−.219***	1
LEV	−.263***	−.247***	.125***	−.094***	.407***	1
GROWTH	.327***	−.131***	−.00500	.069***	.085***	.0280	1
EQ_CON	.189***	−.119***	−.194***	.257***	−.129***	−.068***	.048**	1
EQ_BAL	−.065***	.080***	.111***	−.072***	−.0280	−.038**	.00800	−.730***	1
CF	.175***	.040**	.113***	.00900	.0200	−.255***	−.00800	.064***	−.0130	1
DUAL	.0110	.072***	−.00600	.544***	−.091***	−.0290	.0130	.117***	−.096***	.0200	1
TECH	−.0210	.470***	.055***	.0100	−.0160	−.121***	−.0220	−.094***	.032*	−.0140	.0150	1

***

, **,*: Significant at 1%, 5%, and 10% levels, respectively.

Except EQ_CON and EQ_BAL, the correlation coefficient of each variable is not greater than 0.7, which indicates that there is no collinearity between independent variables and control variables. This provides an excellent basis for subsequent regression analysis.

Endogenous Test

In the management practice of enterprises, R&D investment and financial performance are mutually causal. The relationship between independent variable and dependent variable is likely to cause endogenous problems. Therefore, in this study, we use Hausman test to check whether endogeneity exists. It can be seen from Table 5 that the regression coefficients are −0.055 and −1.391, respectively. They all pass the 1% significance level test. This shows that the original hypothesis is rejected, and the endogenous problem indeed exists. Therefore, in the following analysis, this work uses 3SLS to effectively solve the endogenous problem.

Table 5.

Results of Hausman Test.

Item	Coefficient	p Value
ε₁	−0.055	.000
ε₂	−1.391	.000

Regression Analysis

In Table 6, we use OLS and 3SLS for analysis the full sample. The comparison show that the estimated results of OLS and 3SLS are partially different. This shows that the use of OLS estimation cannot effectively explain the endogenous relationship between RDD and ROE. In order to better verify the hypothesis, this study uses the 3SLS estimation method to solve the endogenous problem.

Table 6.

Regression Results.

Equation variables	OLS estimation		3SLS estimation
	(1)	(2)	(1)	(2)
	RDD	ROE	RDD	ROE
ROE_i,t	−0.055*** (−6.38)		−4.335*** (−2.86)
ROE_i,t−1	−0.006 (−0.58)		1.096*** (2.74)
ROE_i,t−2	0.004 (0.34)		0.228 (1.52)
RDD_i,t		−0.699*** (−6.16)		10.019*** (4.11)
RDD_i,t−1		0.164 (1.04)		−9.357*** (−4.24)
RDD_i,t−2		0.262** (2.01)		−0.144 (−0.51)
SIZE_i,t	−0.409** (−2.05)	4.772*** (9.17)	14.367** (2.55)	4.634*** (3.68)
LEV_i,t	−0.081*** (−8.04)	−0.408*** (−15.70)	−1.447*** (−2.93)	−0.413*** (−6.58)
GROWTH_i,t	−0.007** (−2.06)	0.091*** (10.41)	0.443*** (2.72)	0.327*** (5.72)
EQ_CON_i,t	−0.031 (−1.54)	0.336*** (6.33)	0.968** (2.33)	0.329** (2.56)
EQ_BAL_i,t	0.001 (0.43)	0.013 (1.56)	0.024 (0.65)	0.010 (0.48)
CF_i,t	−0.009 (−1.18)	0.072*** (3.42)	0.314** (2.18)	0.184*** (3.25)
DUAL_i,t	0.814*** (2.66)	0.095 (0.11)	1.582 (0.45)	−0.687 (−0.33)
TECH_i,t	0.137*** (15.62)	0.051** (1.96)	0.127 (1.26)	−0.173** (−2.11)
_CONS	23.813*** (4.55)	−93.486*** (−6.63)	−281.729** (−2.3)	−106.903*** (−3.12)
Year and industry fixed	Yes	Yes	Yes	Yes
R ²	.263	.279	—	—
Adj. R²	.255	.271	—	—

***

and ** indicate that the regression coefficients are significant at the 1%, 5%, and 10% levels, respectively.

In Table 6, RDD in the current period positively affects ROE in 1% significance level, which means that R&D investment in the current period can produce expected effects instantaneously. At the same time, RDD of the lag period has a significant negative impact on the ROE of the current period. This may due to the R&D activities in the previous period incur a large amount of expenses in the current period. These expenses may include intangible assets amortization, depreciation of fixed assets purchased, salaries of R&D personnel recruited, and so on. These newly increased expenses reduce the financial performance of the current period.

The lag effect of R&D also shows that enterprises may suffer from a revenue decline brought by innovative technologies when R&D activities enters the second year. The reason may come from fierce market competition and technology upgrading in GEM. Regarding the ROE reversely impact on RDD, the ROE of the current period has a significant negative impact on RDD, and the impact coefficient is −4.355.

This indicates if the current financial profit level is high, it may hinder the current innovation activities. This may be due to management’s complacency. Since there is a better source of profit in the current period, the management may cut or give up the uncertain R&D activity. On the other hand, the better financial performance in the lag period can promote the R&D activities in the current period. This means that enterprises will consider increasing future R&D activities when they have better profit indicators and cash flows.

Meanwhile, it can be seen from Table 6, the regression results of the six control variables passed the significance level. Financial leverage and R&D personnel both have a negative relationship with company financial indicator. The remaining four control variables all have a positive impact on financial performance.

Regression Analysis and Moderate Effects of Executive Incentive

In Table 7, incentive variables are introduced from the perspectives of cash and equity respectively, and tested with OLS regression. The SAL regression coefficient is 3.265, and it is significant at the level of 1%. It shows that in the case of increased executive compensation, the motivation of executives will be obviously improved, and the financial performance of enterprises will also be improved subsequently.

Table 7.

The Moderating Effect of Different Executive Incentives.

Variables	Incentive (1)	Incentive (2)	Incentive (3)
Variables	Salary	Equity	All
RDD_i,t−1	−0.454 (−0.72)	−0.315** (−2.30)	0.078 (0.12)
RDD_i,t−2	0.235* (1.79)	0.229* (1.74)	0.215 (1.64)
SAL_i,t−1	2.734** (2.35)		3.265*** (2.77)
EQ_INC_i,t−1		0.108** (2.51)	0.117*** (2.69)
RDD_i,t−1 × SAL_i,t−1	−0.006 (−0.06)		−0.074 (−0.64)
RDD_i,t−1 × EQ_INC_i,t−1		−0.009** (−2.27)	−0.009** (−2.34)
SIZE_i,t	3.933*** (6.71)	4.870*** (9.18)	4.039*** (6.86)
LEV_i,t	−0.401*** (−15.19)	−0.414*** (−15.71)	−0.406*** (−15.35)
GROWTH_i,t	0.110*** (12.86)	0.107*** (12.56)	0.110*** (12.88)
EQ_CON_i,t	0.334*** (6.24)	0.319*** (5.73)	0.313*** (5.64)
EQ_BAL_i,t	0.011 (1.23)	0.011 (1.22)	0.008 (0.89)
CF_i,t	0.077*** (3.62)	0.078*** (3.68)	0.076*** (3.60)
DUAL_i,t	−0.091 (−0.11)	−0.630 (−0.65)	−0.823 (−0.84)
TECH_i,t	0.039 (1.49)	0.034 (1.30)	0.036 (1.39)
_CONS	−89.442*** (−5.92)	−94.615*** (−6.56)	−92.521*** (−6.09)
Year and industry fixed	Yes	Yes	Yes
R ²	.268	.267	.271
Adj. R²	.260	.258	.262

Note. t-Values are enclosed in parentheses.

***

, **, * indicate that the regression coefficients are significant at the levels of 1%, 5%, and 10%, respectively.

At the same time, there is a significant positive correlation between executive equity incentives and corporate financial performance. From the comparison of incentive effect, the coefficient of salary incentive (3.265) is much higher than that of equity incentive (0.117). It proves that executives in GEM value short-term interests more. Therefore, we confirm the hypothesis H2a and H2b.

In order to examine the role of senior executives in moderating R&D investment and return on equity, this work adds the interaction of R&D investment and senior executives incentive (RDD × SAL; RDD × EQ_INC) on the basis of models 1. In order to overcome the influence of endogenous problem, this work introduces the lag period of R&D investment and senior executives incentive into model 3. In Table 7, SAL has no significant moderate effect.

On the other hand, the regression coefficient for the interaction term (RDI × EQ_INC) is −0.009, and significant at the 5% level. It shows that executive equity incentive has a significant negative moderating effect between R&D investment and financial performance. Therefore, hypothesis H3a and H3b fail to pass the test.

Robustness Check

In order to improve the robustness of the empirical results, this study uses alternative variables for testing. We retest the sample data after removing the two dummy variables of industry and year. We also apply the 3SLS estimation method to the model. Compared with the current model, the results show that there is no significant difference in the coefficients of variables. Compared with the previous model, the results show that there is no significant difference in the coefficients of variables. This proves that the study has better robustness.

Conclusions and Policy Implications

Conclusions of the Study

In a nutshell, this work first reviews the literature and theoretically analyzes the relationship between the R&D investment and the return on equity of GEM companies from the perspective of senior executives incentive. This study builds a conceptual research model that empirically examines the impact of R&D investment on financial performance in Chinese GEM companies, along with a special focus on the moderating effect of executive incentive between the two variables.

ROE levels in different time periods have reverse impacts on R&D investment decisions. The high level of ROE in the past period will positively affect RDD. At the present period, the case is just the opposite. With regard to the previous scholars’ debate on R&D and financial performance, this study testifies different results in different time periods. In current period, this work proves the existence of significant positive influence from RDD on ROE. This positive link also supports Cohen and Levinthal (1990), Bayus et al. (2003), who argued that continuous innovation can generate high sales, other financial benefits and company growth.

The findings of this study correspond with previous scholars (Qin et al., 2019; Zhang, 2018), who argued that technological innovation strategies show a significant positive impact on corporate financial performance. It is necessary to effectively strengthen the investment of funds for technological innovation. This also strongly confirms Bigliardi (2013) that innovation is an important source of competitive advantage for businesses, where the level of innovation increases the financial performance of enterprises.

On the contrary, when considering the impact of RDD in the past period on ROE, the results show that there is a significant negative correlation. Just like the research of Kim et al. (2016) and Santos et al. (2014), who argued that the relationship between R&D investment and return on equity is not obvious or negatively correlated. This work shows R&D investment has a significant role in the return on equity. This lag time negative relationship shows that, in GEM, the updating speed of enterprises innovation is fast, and the competitive advantage of new technologies cannot be maintained for a long time.

For the control variables, six variables passed the significance test. It proves that they also have a significant impact on ROE. The larger the company (SIZE), the higher the financial performance of the enterprise. This conclusion is consist with previous studies on this variable (C. T. Liu et al., 2013; J. M. Liu & Zhou, 2018). The asset liability ratio (LEV) of the enterprise is negatively correlated with the financial performance, and the correlation coefficient is significant. This finding is similar to previous studies by many scholars (Mohamed et al., 2022; Xiong, 2013). A high debt ratio will increase the financial risk of the enterprise (Yazdanfar & Öhman, 2015), and reduce the expected income of the enterprise. At the same time, the high debt ratio means that the enterprise needs to bear high interest in the current period, thus reducing the profit rate in the company.

Executives are more motivated to work hard due to the incentive policy, which will promote the financial performance of the enterprise. That is, the salary and equity of senior executives have a significant positive impact on the return on equity. Specifically, the weight of cash impact is much more greater.

Based on empirical data, we strongly support the conclusions of Zhao and Gao (2018); Kato et al. (2007); Xing et al. (2014); and Xue and Li (2015), who argued that the cash compensation of senior managers has a positive correlation with the performance of corporate. Just like energy companies (X. L. Xu et al., 2020), in GEM in China, we also find salary incentive can promote the profitability of the firm.

Contrary to Demirer and Yuan’s (2013) view that the use of cash compensation has a negative impact on corporate performance. This study argues that executive compensation, rather than long-term deferred compensation, has a positive impact. The possible reasons lie in the cultural difference. China’s traditional culture is more focused on monetary incentives. Because society is in a high-speed development and full of uncertainty, long-term compensation incentive plans may not work well.

In the two moderated variables, cash compensation is insignificant, while equity incentive shows negative significance. The executive compensation incentives have a significant positive impact on corporate financial performance. However, it does not have a significant moderate effect between R&D capital investment and financial performance. This conclusion does not support Bosetti et al. (2015); Faggian and McCann (2009); and Hunt and Gauthier-Loiselle (2009), who generally recognized that executives compensation could play an important moderating role in implement innovative activities. For the equity incentive, this paper finds that this variable will play a negative moderate role.

This conclusion is different from the traditional equity incentive assumption. According to agency theory (Jensen & Meckling, 1976), the interests of managers and owners are in conflict in some area. Equity incentive is generally considered as an effective means to coordinate long-term interests between them. However, the conclusion of this work indicates that the role of equity incentive in GEM has not yet emerged. The possible reason is that the negative effect of equity incentive scheme is more highlighted in GEM. Specifically, equity incentive will cause dilution of equity. In GEM, due to the uncertainty in the initial stage of entrepreneurship, enterprises often face the choice of multiple products or business strategies. A centralized ownership structure is needed to strengthen the control right. Strengthening control can enable major shareholders with more voice to choose a predetermined business strategy. This is beneficial for the development of GEM companies in their early stages.

Policy Implication

Generally speaking, for GEM enterprises, sufficient investment in technological innovation is indispensable. R&D is an important knowledge-based resource of enterprises. Considering the negative impact of lag time behind, enterprises should shorten the R&D cycle and try to invest in projects with quick results. GEM companies in China are facing fierce competition and uncertainty in the future. In order to reduce the uncertainty of future R&D activities, enterprises should expand R&D investment and improve R&D efficiency in the short term, so as to gain competitive advantage.

Based on the difference of the effects of the two different incentive schemes, GEM is suggested to design a sound system of cash compensation scheme. In this salary system, the assessment indicators of tasks need to be quantified and have certain challenges for managers. Companies should set reasonable annual growth performance targets and provide matching compensation levels for top managers. In this way, managers will exert all their strength to serve the company.

Combined with China’s current conditions, short-term compensation schemes are more attractive than long-term incentive schemes such as equity and options. Short-term compensation could make them more responsible for undertaking high-risk R&D projects (C. Sun & Zhuang, 2021; Usman et al., 2018). Cash incentive is more effective than equity incentive (C. Wang et al., 2021). The total cash income should include basic salary, post salary, quarterly performance bonus, half-year performance bonus, annual comprehensive performance bonus et al.

The benefits of equity incentives have been widely proved, but the positive moderate effect may not be applicable in GEM. In GEM, the R&D decisions of enterprises are often uncertain. Owners of start-ups are often confused about the direction of product R&D development. For example, which is better, to choose to develop the technology of the product, enhance the appearance of the product, or improve the brand relationship of the product? The equity incentive plan means that the equity structure is decentralized. Decentralized control will lead to many divergence of decision views. After stock ownership dilution, the ownership structure is easy to incur overlapping leadership. This study suggests that equity incentives have a negative moderating effect. So in GEM, the ownership structure should be centralized.

Research Limit and Future Plan

The indicators of the technological innovation only select the investment of R&D funds, and do not include R&D policy factors into the explanatory variables. Therefore, in future research, the R&D policy factors can be included in the explanatory variables, and the explanatory variables can be enriched and supplemented. At the same time, there are other factors driving financial performance. Whether the company’s social responsibility, and the influence in the secondary market could effectively promote the growth of the company’s financial performance? These are all issues that require continued attention in the future. Finally, the time span of financial data was short. So future research can expand the selection range of time span of financial data.

Supplemental Material

sj-xlsx-1-sgo-10.1177_21582440231210428 – Supplemental material for R&D Investment, Executive Incentive, and Financial Performance in GEM: Based on Three-Stage Least Squares Method

Supplemental material, sj-xlsx-1-sgo-10.1177_21582440231210428 for R&D Investment, Executive Incentive, and Financial Performance in GEM: Based on Three-Stage Least Squares Method by Luxing Liu, Keyu Lei, Hong Jin and Yin-Pei Teng in SAGE Open

Footnotes

Author Contributions

Luxing Liu: Conceptualization, Data curation, Writing—original draft, Writing—review & editing;

Keyu Lei: Translation, Validation;

Hong Jin: Data curation, Investigation;

Yin-Pei Teng: Supervision, Project administration.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Project supported by the Ministry of Agriculture and Rural Affairs of the People’s Republic of China: Collaborative Innovation Center Project of Modern Agricultural Industrial Park in Anxi County, Fujian Province (KMD18003A);

ORCID iDs

Luxing Liu

Yin-Pei Teng

Data Availability

All data used to support the conclusions of this work are available from the corresponding author on request.

Supplemental Material

Supplemental material for this article is available online.

References

Abowd

J. M.

(1990). Does performance—Based managerial compensation affect corporate performance? Industrial and Labor Relations Review, 43, 52–73. https://doi.org/10.1177/001979399004300304

Acemoglu

Akcigit

Alp

Bloom

(2018). Innovation, reallocation, and growth. American Economic Review, 108(11), 3450–3491. https://www.researchgate.net/publication/328672358_Innovation_Reallocation_and_Growth

Andersen

M. L.

Dejoy

J. S.

(2011). Corporate social and financial performance: The role of size, industry, risk, R&D and advertising expenses as control variables. Business & Society Review, 116(2), 237–256. https://doi.org/10.1111/j.1467-8594.2011.00384.x

Artz

K. W.

Norman

P. M.

Hatfield

D. E.

Cardinal

L. B.

(2010). A longitudinal study of the impact of R&D, patents, and product innovation on firm performance. Journal of Product Innovation Management, 27, 725–740. https://doi.org/10.1111/j.1540-5885.2010.00747.x

Bayus

B. L.

Erickson

Jacobson

(2003). The financial rewards of new product introductions in the personal computer industry. Management Science, 49(2), 197–210.

Bennett

Bettis

J. C.

Gopalan

Milbourn

(2017). Compensation goals and firm performance. Journal of Financial Economics, 124(2), 307–330. http://doi.org/10.1016/j.jfineco.2017.01.010

Bigliardi

(2013). The effect of innovation on financial performance: A research study involving SMEs. Innovation, 15(2), 245–255. https://doi.org/10.5172/impp.2013.15.2.245

Burja

Mărginean

(2014). The study of factors that may Influence the performance by the Dupont analysis in the furniture industry. Procedia Economics and Finance, 16, 213–223. https://doi.org/10.1016/S2212-5671(14)00794-1

Bosetti

Cattaneo

Verdolini

(2015). Migration of skilled workers and innovation: A European perspective. Journal of International Economics, 96(2), 311–322. https://doi.org/10.1016/j.jinteco.2015.04.002

10.

Chan

S. H.

Martin

J. D.

Kensinger

J. W.

(1990). Corporate research and development expenditures and share value. Journal of Financial Economics, 26(2), 255–276. https://doi.org/10.1016/0304-405X(90)90005-K

11.

Chauvin

K. W.

Hirschey

(1993). Advertising, R&D expenditures and the market value of the firm. Financial Management, 22(4), 128–140.

12.

Cheng

(2018). Executive compensation incentive, ownership concentration and R & D innovation strategy—Based on the moderating effect of panel data of manufacturing listed companies. East China Economic Management, 11, 118–125.

13.

Cheng

Warfield

T. D.

(2005). Equity incentives and earnings management. Accounting Review, 80(2), 441–476. https://doi.org/10.2139/ssrn.457840

14.

Cohen

W. M.

Levinthal

D. A.

(1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152. https://doi.org/10.2307/2393553

15.

Connolly

R. A.

Hirschey

(2005). Firm size and the effect of R&D on Tobin’s q. R&D Management, 35(2), 217–223. http://www.onacademic.com/detail/journal_1000034655754110_0ba3.html

16.

Crowley

Jane

(2018). The influence of the manager on firm innovation in emerging economies. International Journal of Innovation Management, 22(3), 1–33. https://doi.org/10.1142/s1363919618500287

17.

Demirer

Yuan

(2013). Executive compensation structure and firm performance in the U.S. restaurant industry: An agency theory approach. Journal of Foodservice Business Research, 16(5), 421–438. https://doi.org/10.1080/15378020.2013.850374

18.

Erdogan

Yamaltdinova

(2019). A panel study of the impact of R&D on financial performance: Evidence from an emerging market. Procedia Computer Science, 158, 541–545. https://doi.org/10.1016/j.procs.2019.09.087

19.

Faggian

McCann

(2009). Human capital, graduate migration and innovation in British regions. Cambridge Journal of Economics, 33(2), 317–333. https://doi.org/10.1093/cje/ben042

20.

Guan

X. J.

Zhang

D.R.

(2020). The relationship between endogenous financing and enterprise performance of gem Enterprises—Based on the regulatory role of executive compensation. Journal of Hunan University of Technology, 34(6), 58–66.

21.

Gui

Jichun

Nathee

Lei

Heping

(2022). Measuring investor sentiment of China’s growth enterprises market with ERNIE. Procedia Computer Science, 202, 1–8. https://doi.org/10.1016/j.procs.2022.04.001

22.

Guo

X.M.

Liang

Xie

Z. R.

(2019). Executive compensation incentive, dynamic adjustment of capital structure and enterprise financial performance. Journal of Shanxi University of Finance and Economics, 4, 78–91.

23.

Y. B.

Zhang

(2017). Research on the impact of technological innovation sustainability on enterprise financial performance. Scientific Research Management, 9, 1–11.

24.

Herzberg

Mausner

Snyderman

B. B.

(2009). Two factor theory of Herzberg. China Renmin University Press.

25.

Hitt

M. A.

Hoskisson

R. E.

Kim

(1997). International diversification: Effects on innovation and firm performance in product-diversified firms. Academy of Management Journal, 40(4), 767–798. https://www.researchgate.net/publication/277530331_International_Diversification_Effects_on_Innovation_and_Firm_Performance_in_Product-Diversified_Firms

26.

Huang

J. L.

Tang

Jiang

Z. H.

(2014). Research and development investment, risk and return of agricultural enterprises under preferential tax policies—An empirical test based on China’s agricultural listed companies. Agricultural Technology and Economy, 2, 120–128.

27.

Hunt

Gauthier-Loiselle

(2009). How much does immigration boost innovation? American Economic Journal: Macroeconomics, 2(2), 31–56. http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=1BFD912249B2B765D3084827CF1F44E9?doi=10.1.1.222.5563&rep=rep1&type=pdf

28.

M. X.

(2015). Management power, technological innovation input and enterprise performance. Science of Science and Management of S. & T., 36(8), 140–149.

29.

Jensen

M. C.

Meckling

W. H.

(1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics, 3(4), 305–360. https://doi.org/10.1016/0304-405X(76)90026-X

30.

Jin

(2021). The impact of private equity investment funds on the financial performance of GEM enterprises. Chinese Certified Public Accountant, 11, 78–82.

31.

Joura

Xiao

Ullah

(2021). The impact of say-on-pay votes on firms’ strategic policies: Insights from the Anglo-Saxon economy. International Review of Financial Analysis, 73, 101606. https://doi.org/10.1016/j.irfa.2020.101606

32.

Kaplan

R. S.

Norton

D. P.

(1996). The balanced scorecard: Translating vision into action. Harvard Business Press. https://www.researchgate.net/publication/240287818_The_balanced_scorecard_translating_vision_into_action

33.

Kato

Kim

Lee

J. H.

(2007). Executive compensation, firm performance, and chaebols in Korea: Evidence from new panel data. Pacific-Basin Finance Journal, 15(1), 36–55. https://doi.org/10.1016/j.pacfin.2006.03.004

34.

Kim

Miller

D. J.

Mahoney

J. T.

(2016). The impact of the timing of patents on innovation performance. Research Policy, 45(4), 914–928. https://doi.org/10.1016/j.respol.2016.01.017

35.

Liang

L. X.

Zhang

H. F.

(2005). Empirical study on R&D investment performance of high-tech listed companies. Journal of Central South University, 2, 232–236.

36.

Hou

(2019). R&D based knowledge capital and future firm growth: Evidence from China’s Growth Enterprise Market firms. Economic Modelling, 83, 287–298. https://doi.org/10.1016/j.econmod.2019.07.005

37.

Liu

C. T.

Yang

C. S.

Peng

C. W.

(2013). The correlation between R&D assets of Taiwanese parent companies and financial performance of mainland subsidiaries: On the regulatory role of corporate strategy. Zhongshan Management Review, 21(4), 799–851.

38.

Liu

J. M.

Zhou

(2018). Research on the impact of R&D and innovation investment on the performance of GEM enterprises from the perspective of CEO power. Journal of Southwest University of Political Science and Law, 20(3), 118–126.

39.

Martin

Wang

(2015). Pyramid IPOs on the Chinese growth enterprise market. Emerging Markets Finance and Trade, 51(1), 160–173. https://doi.org/10.1080/1540496X.2015.1011526

40.

Maslow

(2007). Motivation and personality (3rd ed.). Renmin University of China Press.

41.

McGregor

D. M.

(1985). 3-The human side of enterprise. Academic Press. https://doi.org/10.1016/B978-0-12-054752-4.50008-7

42.

Mehran

(1995). Executive compensation structure, ownership and firm performance. Journal of Financial Economics, 38(2), 163–184. https://doi.org/10.1016/0304-405X(94)00809-F

43.

Miller

J. S.

Wiseman

R. M.

Gomez-Mejia

L. R.

(2002). The fit between CEO compensation design and firm risk. Academy of Management Journal, 45(4), 745–756. http://dx.doi.org/10.2307/3069308

44.

Miao

Xia

Meng

(2018). Research on the impact of executive compensation incentive on R&D investment—The moderating role of ultimate control. Industrial Technology and Economy, 1, 41–48.

45.

Mohamed

Amal

Nadia

B. F.

(2022). Executive compensation indexed to corporate social responsibility and firm performance: Empirical evidence from France. Finance Research Letters, 50, 103213. https://doi.org/10.1016/j.frl.2022.103213

46.

Önday

. (2016). Human resource theory: From Hawthorne experiment of Mayo to groupthink of Janis. Global Journal of Human Resource Management, 4(1), 95–110. https://www.researchgate.net/publication/309037074_HUMAN_RESOURCE_THEORY_FROM_HAWTHORNE_EXPERIMENTS_OF_MAYO_TO_GROUPTHINK_OF_JANIS

47.

Parcharidis

E. G.

Varsakelis

N. C.

(2010). R&D and Tobin’s q in an emerging financial market: The case of the Athens stock exchange. Managerial and Decision Economics, 31(5), 353–361. https://doi.org/10.1002/mde.1493

48.

Peaucelle

(2000). From Taylorism to post-Taylorism: Simultaneously pursuing several management objectives. Journal of Organizational Change Management, 13(5), 452–467. https://doi.org/10.1108/09534810010377426

49.

Plumlee

Brown

Hayes

R. H.

Marshall

R. S.

(2015). Voluntary environmental disclosure quality and firm value: Further evidence. Journal of Accounting and Public Policy, 34(4), 336–361. https://doi.org/10.1016/j.jaccpubpol.2015.04.004

50.

Qin

D. Z.

Shao

H. M.

L. C.

(2019). Moderating effect of technological innovation on ownership structure and enterprise financial performance—An empirical study from manufacturing enterprises listed on GEM. Scientific and Technological Progress and Countermeasures, 8, 1–7.

51.

Quan

X. F.

S. N.

Wen

(2010). Management power, private benefits and salary manipulation. Economic Research, 45(11), 73–87.

52.

Saliba

O. J. A.

Cruz

B. L. F.

Herbert

Amorim

S. V.

(2018). Innovation and financial performance of companies doing business in Brazil. International Journal of Innovation Studies, 2(4), 153–164. https://doi.org/10.1016/j.ijis.2019.03.001

53.

Santos

D. F. L.

Basso

L. F. C.

Kimura

Kayo

E. K.

(2014). Innovation efforts and performances of Brazilian firms. Journal of Business Research, 67(4), 527–535. https://doi.org/10.1016/j.jbusres.2013.11.009

54.

Shenzhen Stock Exchange. (2022, January 10). Gem translation. http://www.szse.cn/certificate/secondb/

55.

Shih

K. H.

(2008). Is e-banking a competitive weapon? A causal analysis. International Journal of Electronic Finance, 2(2), 180–196.

56.

Sofronas

Archontakis

Smart

(2020). Decision making under uncertainty? R&D activity and market value during financial crisis. European Journal of Innovation Management, 23(3), 383–401. https://doi.org/10.1108/EJIM-05-2018-0103

57.

Solomons

(1965). Divisional performance: Measurement and control. Irwin.

58.

Stern

J. M.

Stewart

G. B.

Chew

D. H.

(1995). The Eva^® financial management system. Journal of Applied Corporate Finance, Morgan Stanley, 8(2), 32–46. https://ideas.repec.org/a/bla/jacrfn/v8y1995i2p32-46.html

59.

Sun

Zhuang

X. T.

(2021). An empirical study on the influence of director network position on executive compensation level. Journal of Northeastern University, 42(7), 1049–1056.

60.

Sun

J. C.

C. G.

Tang

(2019). Executive employee pay gap, management power and enterprise financial performance. Accounting Newsletter, 12, 10–13.

61.

Tong

Y. K.

Wei

Y. J.

(2021). Research on the correlation between financial performance, business diversification and stock liquidity of GEM listed companies. Management Review, 33(4), 283–294.

62.

Tchistyi

Yermack

Yun

(2011). Negative hedging: Performance-sensitive debt and CEOs’ equity incentives. Journal of Financial & Quantitative Analysis, 46(3), 657–686. https://doi.org/10.2139/ssrn.1008183

63.

Usman

Xiao

Luo

Liu

(2018). Strategic decision making for boosting innovation and TMT compensation in high-tech industry: Evidence from China. International Journal of Technology, Policy and Management, 18(3), 247–271. https://www.researchgate.net/publication/326911630_Strategic_decision_making_for_boosting_innovation_and_TMT_compensation_in_high-tech_industry_Evidence_from_China

64.

Vanderpal

(2015). Impact of R&D expenses and corporate financial performance. Journal of Accounting and Finance, 15(7), 135–149.

65.

Van Dun

D. H.

Hicks

J. N.

Wilderom

C. P. M

. (2017). Values and behaviors of effective lean managers: Mixed-methods exploratory research. European Management Journal, 35(2), 174–186. https://doi.org/10.1016/j.emj.2016.05.001

66.

Wang

C. H.

Subhan

Raza

Farid

(2021). Executive compensation and corporate performance of energy companies around the world. Energy Strategy Reviews, 38, 100749. https://doi.org/10.1016/j.esr.2021.100749

67.

Wang

Zhang

L. Y.

S. H.

(2017). The impact of R&D investment and market structure on the financial performance of high-tech enterprises. China Science and Technology Forum, 7, 72–79.

68.

Wang

Z. J.

Mai

(2019). Corporate social responsibility, innovation capability, and international Strategy: The moderating role of executive compensation incentive. Management Review, 31(3), 193–202.

69.

L. S.

Zhang

(2021). Economic policy uncertainty, executive compensation incentive and enterprise R&D Investment—Based on the balanced panel data of Shanghai and Shenzhen A-share listed companies. Journal of Henan Normal University, 3, 90–99.

70.

Xie

Y. K.

(2003). Exploration of Skinner B.F.’s reinforcement theory. Journal of Guizhou Normal University, 1, 110–114.

71.

Xing

Z. L.

Wang

Y.M.

L. L.

Xing

Z.L.

X. H.

Shen

Y. M.

(2014). Analysis of factors affecting corporate performance on GEM listed companies: Studies based on multiple cases. Management Review, 26(1), 66–77.

72.

Xiong

J. P.

(2013). Analysis of the impact of asset liability ratio on company performance based on the experience of China’s automobile industry. Journal of Chongqing University of Technology, 27(7), 42–50.

73.

J. Z.

Jia

D. F.

F. S.

Wang

(2018). Research on the impact of low-carbon technological innovation on enterprise financial performance in equipment manufacturing enterprises. Management Review, 3, 82–94.

74.

S. N.

Mei

Chen

Zhu

(2011). Research on financial performance evaluation of gem enterprises based on LMBP neural network. Research on Science and Technology Management, 31(2), 88–90 + 94.

75.

X. L.

Chen

H. H.

Chen

Q.X.

(2019). The role of equity balance and executive stock ownership in the innovation efficiency of renewable energy enterprises. Journal of Renewable and Sustainable Energy, 11(5): 1–11. https://doi.org/10.1063/1.5116849.

76.

X. L.

Shen

Zhang

Chen

H. H.

(2020). The role of innovation investment and executive incentive on financial sustainability in tech-capital-labor intensive energy company: Moderate effect. Energy Reports, 6(11), 2667–2675. https://doi.org/10.1016/j.egyr.2020.09.011

77.

Xue

(2015). The impact of R&D investment on financial performance of GEM companies: The regulatory effect of executive incentive. Finance and Accounting Monthly, 11Z, 123–128.

78.

Yao

(1997). Profit sharing, bonus payment, and productivity: A case study of Chinese state-owned enterprises. Journal of Comparative Economics, 24(3), 281–296. https://doi.org/10.1006/jcec.1997.1435

79.

Yazdanfar

Öhman

(2015). Debt financing and firm performance: An empirical study based on Swedish data. Journal of Risk Finance, 16(1), 102–118. https://doi.org/10.1108/JRF-06-2014-0085

80.

Tiantian

Yong

Sushanta

Lutao

Baohua

(2021). Underwriter reputation and IPO underpricing: The role of institutional investors in the Chinese growth enterprise market. International Review of Financial Analysis, 78, 101956. https://doi.org/10.1016/j.irfa.2021.101956

81.

Zahra

S. A.

Neubaum

D. O.

Huse

(2000). Entrepreneurship in medium-size companies: Exploring the effects of ownership and governance systems. Journal of Management, 26(5), 947–976. https://doi.org/10.1177/014920630002600509

82.

Zhang

(2018). Technological background CEO, technological innovation and enterprise financial performance—An empirical analysis based on private high-tech enterprises. Economic Issues, 5, 82–87.

83.

Zhang

Chen

Feng

(2014). Mediation or moderation? The role of R &D Investment in the Relationship between Corporate Governance and Firm Performance: Empirical Evidence from the Chinese IT Industry. Corporate Governance: An International Review, 22(6), 501–517.

84.

Zhao

Gao

Y. Q.

(2018). An empirical study on the relationship between executive compensation and corporate performance in listed media companies. Modern Economic Information, 15, 18–20+23.

85.

Zou

H. L.

Zeng

S. X.

Lin

Xie

X. M.

(2015). Top executives’ compensation, industrial competition, and corporate environmental performance: Evidence from China. Management Decision, 53(9), 2036–2059. https://doi.org/10.1108/MD-08-2014-0515

Supplementary Material

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R&D Investment,Executive Incentive,and Financial Performance in GEM: Based on Three-Stage Least Squares Method

Abstract

Keywords

Introduction

Literature Review and Research Hypothesis

Technological Innovation and Enterprise Financial Performance

Executives Incentive and Enterprise Financial Performance

Moderating Effect of Executive Incentive on R&D Investment and Enterprise Financial Performance

Research Design

Sample Selection and Data Source

Variable Quantity Selection and Definition

Explained Variables

Explanatory Variables

Moderating Variables

Control Variables

Model Design

Empirical Analysis

Descriptive Statistical Analysis

Correlation Analysis

Endogenous Test

Regression Analysis

Regression Analysis and Moderate Effects of Executive Incentive

Robustness Check

Conclusions and Policy Implications

Conclusions of the Study

Policy Implication

Research Limit and Future Plan

Supplemental Material

sj-xlsx-1-sgo-10.1177_21582440231210428 – Supplemental material for R&D Investment, Executive Incentive, and Financial Performance in GEM: Based on Three-Stage Least Squares Method

Footnotes

Author Contributions

Declaration of Conflicting Interests

Funding

ORCID iDs

Data Availability

Supplemental Material

References

Supplementary Material