Entrepreneur was the key factor of venture capital-backed star-ups, and control rights serve as an important incentive to attract entrepreneurs’ human capital investment.
In this article, we investigate the ways in which the specificity and exclusiveness of entrepreneurs’ human capital impact the allocation of residual control right (RCR) and specific control right (SCR) in entrepreneurial firms, based on the comprehensive effect of various control right benefits.
Using panel data for a mixed regression model, we test theoretical hypotheses with survey data collected from entrepreneurial firms in various industries in China.
We find that when the venture capitalist’s (VC) strategic benefits are less than the entrepreneur’s private benefits, the VC’s RCR is negatively related to the specificity of the entrepreneur’s human capital and is positively related to the exclusiveness of the entrepreneur’s human capital. The VC’s SCR is positively related to the specificity and is negatively related to exclusiveness. When the VC’s strategic benefits are greater than the entrepreneur’s private benefits, the VC’s RCR is positively related to the specificity of the entrepreneur’s human capital and is negatively related to the exclusiveness. The VC’s SCR is positively related to both the specificity and exclusiveness.
The impacts of specificity and exclusiveness of human capital are more significant for high-tech companies than for traditional companies. It is necessary for different types of VC-backed firms to implement classified governance over the control rights.
Entrepreneurial firms are typically characterised as human capital–intensive enterprises, and thus, the entrepreneurs’ human capital represents a primary source of the firms’ sustainable competitive advantage and plays a crucial role in their innovative performance (Coff
Entrepreneurial firms are primarily financed by venture capital funds and thus are subject to the principal–agent problem. While entrepreneurs assume the risk of being stuck in firms because of their specific human capital, venture capitalists or venture capital companies (VCs) are concerned that the exclusiveness of entrepreneurs’ human capital enables entrepreneurs to ‘hold-up’ the VCs by threatening to leave the firm (Hart & Moore
This article explores the ways in which specificity and exclusiveness of entrepreneurs’ human capital impact the allocation of residual control right (RCR) and specific control right (SCR) – the two types of contractual rights according to the incomplete contract theory (Grossman & Hart
There is a rich body of literature on the relationship between human capital and enterprise control rights. Focusing on the IT industry, Jørgensen, Kort and Dockner (
The current literature has studied the control power distribution from the views of human capital and control right benefits. What is missing in the literature is how various control benefits can affect the mechanism through which the specificity and exclusiveness of the entrepreneur’s human capital influence control rights in entrepreneurial firms.
The contributions of this study are threefold. Firstly, at the theoretical level, we disentangle the control right benefits of the entrepreneur and the VC and discuss how the interaction between private benefits and pecuniary benefits of the two parties shifts with their bargaining power and thus affects the sharing of RCR and SCR. Secondly, we explore simultaneously the effects of specificity and another key dimension of human capital, its exclusiveness, which is even more important in determining enterprise control rights (Yang & Yang
In their discussion of controlling shareholders’ motives, Grossman and Hart (
In modern corporate governance, shareholders generally enjoy the benefits of RCR, management enjoys the benefits of SCR and creditors receive the benefits of contingent control right (Liu & Sun
The exclusiveness of human capital implies that, once the owner of such human capital withdraws from the enterprise, the productivity of the firm would deteriorate quickly and the company may even dissolve. This possibility is especially evident in early stages of new enterprises – when the entrepreneur with highly exclusive and innovative technology leave the company, the company may have to be closed. Such a feature explains the strong bargaining position of the entrepreneur and the weak position of the VC.
Because the entrepreneur’s private benefits are relatively large and the VC’s strategic benefits are relatively small, the entrepreneur values more the SCR for private benefits and the VC places more value on the RCR for pecuniary benefits. As the entrepreneur’s human capital becomes more exclusive, he would gain stronger bargaining power and request more SCR. To compromise and maintain the VC’s financial capital and other inputs, the entrepreneur would be willing to transfer some RCR to the VC with pecuniary benefits. Thus, we have the following hypothesis:
Hypothesis 1: When the entrepreneur’s private benefits are greater than the VC’s strategic benefits, the VC’s RCR is positively related to the exclusiveness of the entrepreneur’s human capital and SCR is negatively related to exclusiveness.
In this situation, the VC places more value on the SCR that can bring more strategic benefits and the entrepreneur values more on RCR for pecuniary benefits. As the exclusiveness of the entrepreneur’s human capital increases, the entrepreneur gains more bargaining power over the VC. With an emphasis on pecuniary benefits, the entrepreneur demands more RCR from the VC and is willing to transfer some SCR to the VC to maintain the collaborative relationship, compensating the VC with strategic benefits. Thus, we have the following hypothesis:
Hypothesis 2: When the VC’s strategic benefits are greater than the entrepreneur’s private benefits, the VC’s RCR is negatively related to the exclusiveness of the entrepreneur’s human capital, and the VC’s SCR is positively related to the exclusiveness.
Intuitively, specificity measures the degree to which the entrepreneur relies on other parts of the enterprise including the VC, and exclusiveness measures the degree to which the enterprise relies on the entrepreneur. Specificity and exclusiveness may transform into each other as the business develops. When the entrepreneur’s exclusive human capital becomes more firm-specific, he is somewhat ‘locked’ in the firm. On the other hand, the entrepreneur’s specific human capital can further develop so that he can gain stronger bargaining power in the firm, that is, his human capital can become somewhat exclusive. In all enterprises, the entrepreneur and the VC rely on each other to different degrees, and specificity and exclusiveness should be understood in relative terms. Because specificity and exclusiveness have a reciprocal relationship, their effects on RCR and SCR should be just opposite to each other.
Hypothesis 3: the VC’s RCR and SCR are related to the specificity of the entrepreneur’s human capital in the opposite ways as they are related to its exclusiveness.
Compared to traditional enterprises, high-tech enterprises especially value human capital and intangible assets. Given that financial capital and physical capital are relatively less important in high-tech enterprises, the owner of exclusive human capital is capable of establishing a new firm to compete with existing firms. The particular importance of human capital in high-tech enterprises increases the potential threat to the interest of non-human capital, so it is important to constrain the behaviours of the entrepreneur. On the other hand, significantly increased bargaining power enables the owners of exclusive human capital to seek greater control in enterprises. We propose the following hypothesis:
Hypothesis 4: The impacts of specificity and exclusiveness of the entrepreneur’s human capital on control rights are more pronounced for high-tech enterprises than for traditional companies.
Following Yang and Yang (
Non-pecuniary strategic benefits of venture capital companies: According to a survey on global corporate venture capital projects by Ernst and Young (
Summary of measures of key variables.
Variables | Measures | Sources of reference |
---|---|---|
Specificity of human capital | Not widely available in the labour market Would be very difficult to replace Not available to our competitors Widely considered the best in our industry Unique to our organisation Difficult for our competitors to imitate or duplicate Customised to our particular needs Distinguish us from our competition |
Frank and Obloj ( |
Exclusiveness of human capital | Ability to identify and achieve profitable market opportunities Possession of some key technology with perspective of large commercial profit Possession of a large amount of currency capital in an environment where such capital is scarce Possession of special social capital that can produce significant commercial opportunities |
Hatch and Dyer ( |
Entrepreneurs’ private benefits | Social status On-the-job consumption Professional reputation Peer recognition |
Helwege and Packer ( |
VCs’ strategic benefits | Windows on technology developments Utilisation efficiency of technological platforms Support in the industrial chain New market development Corporate diversification Economies of scale Economies of scope |
Ernst and Young ( |
VC, venture capital company.
Note: This table presents the measures of specificity of human capital, exclusiveness of human capital, entrepreneurs’ private benefits, and VCs’ strategic benefits in entrepreneurial firms.
In this study, we control several variables at the enterprise level to separate their influence from the effect of the entrepreneur’s human capital. Kaplan and Stromberg (
This study employs survey and interview methodologies. In this section, we discuss the design of the survey and test its applicability.
Because there is no public database on entrepreneurial firms in China, we collect the required data through field studies and surveys. In a preliminary round, a small number of field studies and interviews are conducted to gain insight into the current status of control rights in Chinese entrepreneurial firms. Then, a large-sample survey is conducted with mid- to high-level managers in VC companies to collect detailed information for the empirical analyses.
The design of the formal survey follows the issue-oriented principle and is based on the hypotheses to be tested. The questionnaire adopts the popular Likert scale (Dawes
This study focuses primarily on high-tech enterprises financed by VC companies, which are also the research subject of most existing literature. In recent years, VC companies in China have supported not only high-tech enterprises such as Internet of Things and new energy sources but also traditional enterprises such as manufacturing and financial businesses, chain restaurants, and education and training institutions. These traditional types of enterprises are also included in our survey so that the results can be compared to those of high-tech enterprises.
The survey sample includes regions with different levels of economic and market development, and such regional balance can ensure the generality of analytical results. This project selects representative cities from three regions: east, central and west China. In the east region, we selected Jinan, Shenzhen, Nanjing and Wuxi; in the central region, we selected Hefei; and in the west, we selected Xi’an and Wuzhou, where entrepreneurial investment has developed fairly quickly in recent years.
Most existing literature on corporate governance targets only top managers in their surveys. However, in our field studies, we realise that besides top-level managers, the mid-level managers, such as investment managers and project managers in VC firms, are also appropriate survey subjects. These managers maintain direct contact with entrepreneurial firms and thus are quite familiar with entrepreneurs and their firms. For this reason, the survey subjects include top- and mid-level managers and investment decision committee members.
The survey in this project was conducted in two stages. The first stage was in the period of July to September 2009. Survey questionnaires were distributed via local networks (such as local entrepreneur associations or municipal government branches) in the target regions. In total, 450 copies of surveys were distributed, and 205 copies were later collected, with an overall response rate of 45.56%. Among the returned surveys, 98 were invalid for various reasons including incomplete information, bankruptcy of entrepreneurial firms or disqualification of the respondents. Therefore, 107 valid completed surveys were received, with an effective response rate of 23.78%. The sample size is sufficient for our statistical analysis. The second stage of the survey was conducted in the period from July to December 2011, which was meant to follow up with the 107 respondents in the valid sample from the previous survey. The second round of the survey revealed that among the 107 respondents, VCs exited successfully from 12 entrepreneurial firms, 9 firms were bankrupt, 15 firms received the second- or third-round investment from VCs and the remaining 71 were still working with the VC companies. The two rounds of survey yielded a valid sample size of 193, including 121 in strategic emerging or high-tech industries and 72 in traditional industries.
Prior to the empirical analysis, reliability and validity checks are conducted to ensure the quality of the data. Cronbach α is the most popular measure of reliability assessment. It has a value between zero and one, and the bigger the value, the higher the reliability. Generally speaking, Cronbach α on the measures of the same subject should be above 0.7.
Reliability and validity checks of survey data.
Measure | α coefficient | Factor load | % of variance explained |
---|---|---|---|
0.713 | 62.56 | ||
Not widely available in the labour market | 0.719 | ||
Would be very difficult to replace | 0.761 | ||
Not available to our competitors | 0.856 | ||
Widely considered the best in our industry | 0.849 | ||
Unique to our organisation | 0.705 | ||
Difficult for our competitors to imitate or duplicate | 0.639 | ||
Customised to our particular needs | 0.830 | ||
Distinguish us from our competition | 0.789 | ||
0.801 | 72.46 | ||
Ability to identify and achieve profitable market opportunities | 0.819 | ||
Possession of some key technology with perspective of large commercial profit | 0.799 | ||
Possession of a large amount of currency capital in an environment where such capital is scarce | 0.763 | ||
Possession of special social capital that can produce significant commercial opportunities | 0.685 | ||
0.799 | 64.51 | ||
Social status | 0.796 | ||
On-the-job consumption | 0.819 | ||
Professional reputation | 0.802 | ||
Peer recognition | 0.750 | ||
0.808 | 72.69 | ||
Windows on technology developments | 0.845 | ||
Utilisation efficiency of technological platforms | 0.882 | ||
Support in the industrial chain | 0.786 | ||
New market development | 0.668 | ||
Corporate diversification | 0.851 | ||
Economies of scale | 0.767 | ||
Economies of scope | 0.810 |
VC, venture capital company.
Popular validity tests include convergent validity and discriminant validity (Tan & Litschert
The discriminant validity is tested with two methods. Firstly, for any two factors, we calculate the change in χ2 between two scenarios: when their correlation is one and when their correlation is free. Tests show that the change in χ2 is significant. Secondly, we calculate the 95% confident interval for the correlation coefficient between any two factors and notice that the interval does not include 1.0. These tests show that factors display satisfactory discriminant validity.
To test our hypotheses, we consider the following two models:
The notations in
After the pre-screening and reliability and validity tests, we calculate the average of measures for each factor as its overall measure. The descriptive analysis is conducted for the variables in the regression models; the results are reported in
Descriptive statistics.
Variable | Observations | Mean | SD | Min. | Max. |
---|---|---|---|---|---|
RCR | 193 | 0.247 | 0.076 | 0.162 | 0.367 |
SCR | 193 | 0.425 | 0.204 | 0.133 | 0.630 |
ResidualClaim1 | 193 | 0.243 | 0.084 | 0.15 | 0.4 |
ResidualClaim2 | 193 | 0.664 | 0.131 | 0.4 | 0.8 |
Specificity | 193 | 3.684 | 0.463 | 1 | 5 |
Exclusiveness | 193 | 3.857 | 1.019 | 1 | 5 |
RCR, residual control right; SCR, specific control right; SD, standard deviation.
Correlation matrix.
Variable | RCR | SCR | Residual Claim1 | Residual Claim2 | Specificity | Exclusiveness |
---|---|---|---|---|---|---|
RCR | 1 | - | - | - | - | - |
SCR | 0.089 | 1 | - | - | - | - |
ResidualClaim1 | −0.262 | 0.518 | 1 | - | - | - |
ResidualClaim2 | 0.265 | −0.405 | −0.229 | 1 | - | - |
Specificity | −0.274 | −0.561( |
−0.488( |
−0.298 | 1 | - |
Exclusiveness | 0.023 | 0.665( |
0.445( |
0.293 | −0.518( |
1 |
RCR, residual control right; SCR, specific control right; VC, venture capital company.
Note: This table reports the descriptive statistics of the explained and the explanatory variables in our models, as well as the correlation matrix of these variables.
indicates that correlation is significant at the 1% level (2-tailed).
In view of our hypotheses, we separate the sample into two groups based on whether the VC’s strategic benefits (
Residual control right when entrepreneur’s private benefits outweigh venture capital companies’ strategic benefits
Regression analysis of residual control right in entrepreneurial firms.
Variables | ||||||
---|---|---|---|---|---|---|
M1.1 | M1.2 | M1.3 | M1.4 | M1.5 | M1.6 | |
Size | −0.226 |
−0.388 |
−0.436 |
−0.223 |
−0.249 |
−0.291 |
Industry | 0.110 |
0.122 |
0.164 |
0.053 |
0.061 |
0.078 |
Stage | 0.424 |
0.461 |
0.494 |
0.236 |
0.245 |
0.268 |
Ln(Investment) | 0.434 |
0.552 |
0.588 |
0.31 |
0.35 |
0.456 |
IC | - | 0.219 |
0.22 |
- | 0.201 |
0.212 |
ResidualClaim1 | - | −0.59 |
−0.663 |
- | −0.144 |
−0.175 |
ResidualClaim2 | - | 0.107 |
0.128 |
- | 0.097 |
0.111 |
Specificity | - | - | −1.33 |
- | - | 0.073 |
Specificity2 | - | - | −0.287 |
- | - | 0.138 |
Exclusiveness | - | - | 0.083 |
- | - | −0.079 |
Exclusiveness2 | - | - | 0.339 |
- | - | −0.182 |
Sample size | 106 | 106 | 106 | 87 | 87 | 87 |
Adjust- |
0.151 | 0.227 | 0.433 | 0.126 | 0.211 | 0.346 |
5.88 | 14.467 | 8.31 | 4.11 | 4.09 | 5.144 | |
Omitted variable | 0.487 | 0.533 | 0.559 | 0.393 | 0.491 | 0.525 |
Heteroscedasticity | 0.075 | 0.091 | 0.112 | 0.062 | 0.077 | 0.094 |
Multicollinearity | 2.81 | 2.52 | 2.43 | 3.17 | 2.99 | 2.86 |
RCR, residual control right; VC, venture capital company.
Note: This table reports the estimation results for Model 1.
indicate significance at 10%, 5% and 1%, respectively.
Model M1.1 only considers the effects of control variables. The estimated coefficient of investment is positive and significant, indicating that the higher the investment amount, the more RCR the VC has in the firm. Other variables are insignificant.
M1.2 adds to M1.1 residual claims of the VC and the entrepreneur as well as industry character as explanatory variables, which increase the explanatory power of the model (adjust-
M1.3 adds to M1.2 the specificity and exclusiveness of entrepreneurs’ human capital, as well as the squared terms of specificity and exclusiveness for potential nonlinear effects. The model’s adjust-
Residual control right when venture capital companies’ strategic benefits outweigh entrepreneur’s private benefits
M1.4 is the baseline model of this situation that includes control variables only, and its result resembles that of M1.1. Adding residual claims and industry character as independent variables to M1.4 forms M1.5, which shows increased explanatory power (adjust-
As in M1.3, M1.6 adds the quadratic effects of the specificity and exclusiveness of the entrepreneur’s human capital. The effects of control variables remain the same. The effect of specificity is significantly positive (at 10%) although nonlinear, and the effect of exclusiveness is just the opposite (negative at 10%). Such results show that the VC’s RCR is positively related to the specificity of the entrepreneur’s human capital and is negatively related to the exclusiveness.
To ensure the reliability of the results in
To test Hypothesis 4, we decompose the sample into two subsamples, one with observations for enterprises in high-tech industries and the other for enterprises in traditional industries. The estimated results using the two subsamples are reported in
Residual control right when entrepreneur’s private benefits outweigh venture capital companies’ strategic benefits
Regression analysis of residual control right in high-tech versus traditional enterprises.
Variables | High-tech enterprises |
Traditional enterprises |
||
---|---|---|---|---|
Size | −0.266 |
−0.291 |
−0.193 |
−0.197 |
Industry | 0.202 |
0.206 |
0.155 |
0.157 |
Stage | 0.407 |
0.289 |
0.364 |
0.305 |
Ln(Investment) | 0.592 |
0.368 |
0.506 |
0.479 |
ResidualClaim1 | −0.699 |
−0.386 |
0.483 |
0.569 |
ResidualClaim2 | 0.15 |
0.118 |
0.104 |
0.114 |
Specificity | −0.107 |
0.087 |
−0.123 |
0.135 |
Speciality2 | −0.226 |
0.213 |
−0.209 |
0.18 |
Exclusiveness | 0.19 |
−0.307 |
0.152 |
−0.186 |
Exclusiveness2 | 0.463 |
−0.237 |
0.276 |
−0.233 |
Sample size | 69 | 52 | 37 | 35 |
Adjust- |
0.501 | 0.394 | 0.363 | 0.327 |
7.815 | 5.372 | 3.064 | 2.653 |
RCR, residual control right; VC, venture capital company.
Note: This table reports the estimation results for Model 1 for high-tech versus traditional enterprises. SBVC stands for the VC’s strategic benefits, and PBe stands for the entrepreneur’s private benefits. The explained variable is RCR, the VC’s RCR. The explanatory variables are as follows. Size is firm size; Industry is industry; Stage is development stage; Ln(Investment) is the logarithm of investment amount; IC is industry character. ResidualClaim1 and ResidualClaim2 are the residual claims of the VC and the entrepreneur, respectively. Specificity and Exclusiveness are the specificity and exclusiveness of the entrepreneur’s human capital, respectively.
indicate significance at 10%, 5% and 1%, respectively.
Based on the results in
The estimated coefficients on
Residual control right when venture capital companies’ strategic benefits outweigh entrepreneur’s private benefits
In this scenario, the effects of control variables and residual claims are almost the same as they are in the previous scenario. The effect of the specificity of the entrepreneur’s human capital is positive in both subsamples, while the effect of the exclusiveness is negative in both subsamples. The effects of specificity and exclusiveness are stronger for high-tech enterprises than for traditional enterprises, which are consistent with the predictions in Hypothesis 4. Additionally, the exclusiveness seems to have a stronger general impact (judged by significance of coefficients) than the specificity on the VC’s RCR.
Regression analysis of SCR for different types of enterprises.
Variables | ||||||
---|---|---|---|---|---|---|
Complete sample | High-tech sample | Traditional sample | Complete sample | High-tech sample | Traditional sample | |
Size | 0.202 |
0.321 |
0.124 |
0.218 |
0.324 |
0.136 |
Industry | 0.051 |
0.06 |
0.039 |
0.077 |
0.062 |
0.055 |
Stage | −0.179 |
−0.212 |
−0.137 |
−0.217 |
−0.256 |
−0.157 |
Ln(Investment) | 0.211 |
0.257 |
0.197 |
0.301 |
0.376 |
0.255 |
IC | 0.337 |
- | - | 0.367 |
- | - |
Specificity | 0.131 |
0.148 |
0.141 |
0.343 |
0.357 |
0.332 |
Specificity2 | 0.276 |
0.367 |
0.366 |
0.067 |
0.112 |
0.102 |
Exclusiveness | −0.343 |
−0.431 |
−0.317 |
0.044 |
0.048 |
0.039 |
Exclusiveness2 | 0.053 |
0.086 |
0.12 |
0.386 |
0.437 |
0.248 |
Sample size | 106 | 69 | 37 | 87 | 52 | 35 |
Adjust- |
0.386 | 0.479 | 0.462 | 0.371 | 0.433 | 0.419 |
8.374 | 9.00 | 4.873 | 6.641 | 5.87 | 4.957 | |
Omitted variable | 0.466 | 0.557 | 0.408 | 0.438 | 0.544 | 0.4 |
Heteroscedasticity | 0.087 | 0.113 | 0.094 | 0.082 | 0.104 | 0.088 |
Multicollinearity | 2.797 | 2.716 | 3.035 | 2.763 | 2.71 | 2.973 |
SCR, specific control right; VC, venture capital company.
Note: This table reports the estimation results for Model 2 for different types of enterprises. SBVC stands for the VC’s strategic benefits, and PBe stands for the entrepreneur’s private benefits. The explained variable is SCR, the VC’s SCR. The explanatory variables are as follows. Size is firm size; Industry is industry; Stage is development stage; Ln(Investment) is the logarithm of investment amount; IC is industry character. Specificity and Exclusiveness are the specificity and exclusiveness of the entrepreneur’s human capital, respectively.
indicate significance at 10%, 5% and 1%, respectively.
In this case, among the control variables, firm size and industry are insignificant for all samples. Stage is marginally negative (10% level) in two samples, and investment amount is positively significant. The effect of specificity is strongly positive in a convex fashion for all three samples, while the effect of exclusiveness is linear and negative. These effects are generally stronger in the high-tech sample than in the traditional company sample, which supports Hypothesis 4.
In this case, compared to the results reported in the last subsection, the effects of all control variables are largely unchanged except that the investment amount becomes more significant, especially in the sample of high-tech enterprises. The industry character is highly positive, suggesting significant difference in SCR between high-tech and traditional enterprises. The effect of specificity is significantly positive for all three samples, which is inconsistent with the negative relationship as hypothesised. The impact of exclusiveness is strongly positive in a convex fashion in all cases. Similar to the case in which entrepreneur’s private benefits outweigh VC’s strategic benefits, these effects are generally stronger in the high-tech sample than in the traditional company sample. Collectively, the preceding results generally support (in three out of four cases) our hypotheses about the ways in which specificity and exclusiveness of the entrepreneur’s human capital are related to the VC’s SCR.
To ensure the reliability of the results, robustness checks are conducted for the regressions in
This article investigates the ways in which the specificity and exclusiveness of entrepreneurs’ human capital affect the allocation of RCR and SCR in Chinese entrepreneurial firms. We find that the exclusiveness and specificity of the entrepreneur’s human capital have dramatically different effects on control right allocations in enterprises invested by VC. More specifically, we find that when the entrepreneur’s private benefits are greater than the VC’s strategic benefits, the VC’s RCR is negatively related to the specificity of the entrepreneur’s human capital and is positively related to the exclusiveness of the entrepreneur’s human capital. The VC’s SCR is positively related to the specificity and is negatively related to the exclusiveness. When the entrepreneur’s private benefits are less than the VC’s strategic benefits, the VC’s RCR is positively related to the specificity of the entrepreneur’s human capital and is negatively related to the exclusiveness of the entrepreneur’s human capital. The VC’s SCR is positively related to the specificity and exclusiveness. Overall, our hypotheses are supported by empirical findings in seven out of the eight relations studied. In either situation, the impacts of specificity and exclusiveness of human capital are more significant for high-tech companies than for traditional companies. Finally, we discover that in high-tech entrepreneurial firms the VC’s RCR and residual claims have a complementary relationship, while in traditional entrepreneurial firms the VC’s RCR and residual claims are positively correlated.
The findings in this study suggest that VCs and entrepreneurs value control rights differently because of variations in control right benefits in entrepreneurial firms. Venture capitalists and entrepreneurs also prioritise RCR and SCR differently at different stages of enterprise development. For those firms with more strategic benefits for VCs, entrepreneurs should be primarily motivated with RCRs, inducing entrepreneurs to transform their exclusive human capital to enterprise-specific human capital in order to improve the firms’ competence in technology innovation and support. When VCs’ strategic benefits are less than entrepreneurs’ private benefits, entrepreneurs should be granted more SCR in early development stages to encourage the transformation of exclusive human capital to enterprise-specific human capital. When entrepreneurs’ private benefits are less than VCs’ strategic benefits, entrepreneurs should be granted more RCR in early development stages to encourage their increasing input of specific human capital. In high-tech entrepreneurial firms, if VCs’ strategic benefits are less than entrepreneurs’ private benefits, the VCs should be encouraged to increase specific investment to inspire entrepreneurs. Specific investments from both parties can alleviate hold-up and free-ride problems so as to improve innovation efficiency and financial performance.
This research is sponsored by the Ministry of Education in China, Project of Humanities and Social Sciences (17YJAZH080) and Jiangsu Qing Lan Project (Su Teacher [2017]15).
The authors declare that they have no financial or personal relationships which may have inappropriately influenced them in writing this article.
L.W. was responsible for theory analysis, survey design, sample selection and empirical analyses. Y.A. and J.Y. were responsible for hypothesis development and research methodology.