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Research on the relationship between internal control quality and company investment efficiency based on data mining.

1. Introduction

Investment is the driving force of economy, efficiency is an important factor in an impregnable position in nowadays competition environment, and how to improve the investment efficiency is the focus of attention of the practical and academic circles (Hyeesoo, 2013; Chung, 2015; Delgado, 2015). Combining normative analysis and empirical analysis, the paper selects 359 Chinese manufacturing listed companies as the research object. The paper gets the results that internal control quality not only has a direct but also has an indirect by financing constraints on investment efficiency. In the end, suggestions are put forward for the improvement of investment efficiency according to the results. Data mining, also known as database knowledge discovery, it is from a large number of incomplete, noisy, fuzzy, random data, extraction implied in them, people do not know in advance, but is potentially useful information and knowledge process. Data mining is a new technique to extract hidden predictive information from a large number of databases or data warehouses. Speaking of the enterprise, data mining can help to find the trend of business development, reveal the known facts and predict unknown results, and help enterprises to analysis the key factor to complete a task required, in order to increase revenue, reduce costs, enhance the enterprise's competitive advantage (Ioan, 2014; Kuei, 2014). Data mining technology is usually divided into two categories: statistical model and machine learning techniques and statistical models are applied to data mining is mainly evaluated, statistical techniques commonly used statistical analysis, associations, and sequence analysis, cluster analysis and so on (Peng, 2015; Pereira, 2015). Machine learning is a branch of artificial intelligence, also known as inductive reasoning, by learning from the training data set, it is found that the model parameters, and find out the rule of implied, commonly used machine learning method such as artificial neural network, decision tree and genetic algorithm in data dig dug is widely used.

[FIGURE 1 OMITTED]

According to mining technology is the use of a variety of analysis methods, through the disorder, the surface of the information from the massive database to dig out the inherent knowledge and rules. After digging out a lot of information, the enterprise can design the mathematical model according to these rules or use these information to predict the occurrence of behavior, to provide the basis for business decision-making, market planning. The application of data mining technology in CRM from the business process perspective mainly includes three aspects: sales data mining is effective for a variety of marketing activities for real-time tracking and analysis, so that sales staff can timely grasp the sales opportunity, greatly improves the work efficiency; customer service with network and information access the automation of data mining can help service center to accurately understand customer concerns, to meet the personalized needs of customers; the market and the enterprise internal management, analysis and mining through collected in from the customer contact information, marketing personnel can find the potential customer classification, followed by gold customers, give up no value customers, company executives can carry out the assessment and evaluation of staff performance.

[FIGURE 2 OMITTED]

2. Analyze the factors affecting the quality of internal control

In this paper, the internal control quality is defined as: Integrated measurement of internal control capability and operational effectiveness. Internal control quality is affected by a number of factors, mainly including external factors and internal factors, considering factors relate to the external environment, firm characteristics, corporate governance and external audit. External environmental factors use the legal level, the level of government intervention, the degree of market processes to measure (Peng Guiying, 2015), because the data are not easy to obtain, this article does not carry on the analysis to it. Finally we obtain 27 factors, as shown in the following table.

Hypothesis H11: the firm age and quality of internal control have a positive association. Hypothesis H12: the firm size and the quality of internal control have a positive correlation. Hypothesis H13: business complexity and internal control quality have a negative correlation.

Hypothesis H21: the nature of state controlling shareholders and the quality of internal control have a positive correlation. Hypothesis H22: the negative relationship between ownership concentration and the quality of internal control have a positive correlation. Hypothesis H23: equity balance degree and the quality of internal control have a positive correlation. Hypothesis H24: institutional investors' shareholding ratio and the quality of internal control have a positive correlation. Hypothesis H25: the board size has a significant impact on the quality of internal control. Hypothesis H26: the degree of diligence and the quality of internal control have a positive correlation. Hypothesis H27: director compensation and internal control quality is the positive correlation. Hypothesis H28: independent director compensation and internal control quality is the positive correlation. Hypothesis H29: independent directors' shareholding ratio and internal control quality have a positive correlation. Hypothesis H210: the independent director proportion and the quality of the internal control have a positive correlation. Hypothesis H211: independent directors' specialization and the quality of internal control have a positive correlation. Hypothesis H212: the joining together of two and the quality of internal control have a positive correlation. Hypothesis H213: executive compensation has a significant impact on the quality of internal control. Hypothesis H214: the proportion of executive stock ownership and the quality of internal control have a positive correlation. Hypothesis H215: the negative correlation between the gender ratio and the quality of the internal control has a positive correlation. Hypothesis H216: the positive correlation between the average age of the top management and the quality of the internal control has a positive correlation. Hypothesis H217: the average educational level and the quality of the internal control have a positive correlation. Hypothesis H218: the importance of management to employee competency and the positive correlation between internal control quality have a positive correlation. Hypothesis H219: the board of supervisors scale and the quality of internal control has a positive correlation. Hypothesis H220: the supervisory education background and the internal control quality have a positive correlation. Hypothesis H221: supervisor salary and the quality of internal control have a positive correlation. Hypothesis H222: to set up to audit committee can improve the quality of internal control. Hypothesis H223: audit committee diligence and the quality of internal control have a positive correlation.

Hypothesis H31: the top four audit institutions and the internal control quality have a positive correlation.

3. Analyze the factors affecting the investment efficiency

The main factors that affect investment efficiency are corporate governance, agency costs, financing constraints and the quality of accounting information for a total of 30, as shown in the following table.

Hypothesis H1A: the equity nature of state controlling shareholders and the investment efficiency have a relationship between. Hypothesis H1B: the number of shareholders' meeting has a significant impact on investment efficiency. Hypothesis H1C: equity concentration has a significant impact on investment efficiency. Hypothesis H1D: the positive correlation between stock ownership restriction and investment efficiency has a positive correlation between. Hypothesis H1E: institutional investor shareholding ratio and investment efficiency have a positive correlation. Hypothesis H1F: board size has a significant impact on investment efficiency. Hypothesis H1G: the board of directors has a significant impact in the efficiency of investment. Hypothesis H1H: independent directors accounted for positive correlation with investment efficiency. Hypothesis H1I: the independent director's salary and the investment efficiency have a positive correlation. Hypothesis H1J: the proportion of directors to receive compensation and investment efficiency has a positive correlation. Hypothesis H1K: the board of supervisor's scale and investment efficiency has a positive correlation. Hypothesis H1L: the supervisory education background and the investment efficiency have a positive correlation. Hypothesis H1M: supervisor salary and investment efficiency have a positive correlation. Hypothesis H1N: the proportion of supervisors to receive remuneration and the investment efficiency has a positive correlated. Hypothesis H1O: the joining together of two jobs and investment efficiency have a negative correlation. Hypothesis H1P: the proportion of executive stock ownership has a significant impact on investment efficiency. Hypothesis H1Q: executive compensation has a significant impact on investment efficiency. Hypothesis H1R: the sex ratio of the senior management has a significant impact on the investment efficiency. Hypothesis H1S: the average age of the executives and the investment efficiency has a positive correlation.

Hypothesis H2A: capital occupying by major shareholders and investment efficiency have a negative to association; H2B: management fee rate and the efficiency of investment is negative to association; H2C: financial expense ratio and the efficiency of investment have a negative correlation.

Hypothesis H3A: debt ratio has a significant impact on investment efficiency. Hypothesis H3B: short-term debt ratio has a significant impact on investment efficiency. Hypothesis H3C: commercial credit ratio has a significant impact on investment efficiency. Hypothesis H3D: bank loan ratio has a significant impact on investment efficiency. Hypothesis H3E: cash holdings have a significant impact on investment efficiency; H3F: cash flow uncertainty and investment efficiency have a negative correlation.

Hypothesis H4A:AIQ1 and investment efficiency is positive correlation; one is AIQ2 defined as Francis (2004) that calculation of earnings smoothing index reciprocal. Hypothesis H4B:AIQ2 and the investment efficiency are positively correlated.

4. An empirical study on the relationship between internal control quality and investment efficiency of the company

Selecting 359 Chinese manufacturing listed companies as the research object, an empirical and empirical analysis are put forward.

4.1. Research hypothesis and test method design

The quality of internal control not only has a direct impact on investment efficiency, but also has an indirect impact. The indirect impact affects that internal control quality through the financing constraints, agency costs and the quality of accounting information produce a certain impact and then affect the efficiency of investment. One is the 'shareholders and managers' first agency problem will lead managers for the establishment of 'empire' sacrifice the interests of shareholders, to enhance the prestige of the additional of self-interest by the investment myopia behaviour; the second agency problem in 'controlling shareholders and minority shareholders' will be due to the controlling shareholder of excessive centralization of state power to dig a tunnel to seek their own interests against the interests of small shareholders eventually leading to inefficient investment.

Structural equation modelling was used to establish the model. Internal control quality H11 ~ H13, H21 to H223, H31 hypothesis and the efficiency of investment Hia to HiS, H2A to H2C, h3a to H3F, h4a to hypothesis H4B use multiple regression analysis to verify, and select the key influence factors as the outcome measure of internal control quality and investment efficiency.

4.2. Hypothesis test of influencing factors based on multiple regression analysis

Hypothesis test of influencing factors on the quality of internal control, through principal component analysis extract 11 principal components, whose accumulation contribution rate is 86.288%, as table 4 shows. Then, according to the score of each principal component, the comprehensive score of the research object is F, that is, the internal control quality.

Hypothesis test of influencing factors of internal control quality, In the calculation of the internal quality control as the dependent variable, with the characteristics of the company, corporate governance and external audit, a total of 27 factors as the independent variables establish multiple regression model, in order to eliminate the multicollinearity effect, The stepwise regression was used to analyze the regression analysis, according to the results in the final institutional investors, independent director compensation and board of education background have important influence and passes the test, which assumes H24, h28, h220 is verified, and other hypothesis has not been verified.

Investment efficiency above mentioned is the dependent variable, and the influencing factors the characteristics of the company, corporate governance, agency cost, the quality of accounting information, financial constraints are independent variables, thus, a multivariate regression model is established. Using stepwise regression method carries on the regression analysis. The regression results show that, the proportion of institutional investors holding, cash holdings, the independent directors for ratio, executive compensation, equity balance degree, ratio of commercial credit, bank loans ratio of investment efficiency have an important influence in investment efficiency, that assumption H1E, H3E, H1H, H1Q, H1d, H3C, H3d is validated, rest on the assumption that is not get support.

4.3.Research on the relationship of structural equation model

By structural equation model, the relationship trade between the investment efficiency and the quality of internal control, the degree of correlation and the significance of influencing factors.

Representation of latent variables and observed variables, In this paper, the latent variables and observed variables are represented by the SEM symbols to the relevant variables, as shown in Table 7.

There are 4 potential variables in this paper, including 3 latent variables, and the structural equation form is shown in (1):

[[eta].sub.1] = [[beta].sub.12] [[eta].sub.2] [[eta].sub.2] = [[gamma].sub.21] [[xi].sub.21] [[eta].sub.2] = [[beta].sub.31] [[eta].sub.1] + [[eta].sub.2] (1)

The observed variables are in the equation as (2):

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (2)

The measurement model is shown in (3):

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (3)

According to the modified structural equation model, the related factors affecting are eliminated, and the research hypothesis of the potential variables is removed, and the basic path research hypothesis, as shown in Table8, is finally obtained.

In this paper, AMOS17.0 is used to carry out the operation of the correction model, and the model is estimated by using the maximum likelihood method, the following table shows that the important fitting indices are better,absolute fit index is 2.567 x2/df, less than the standard value of 3, matching ideal, the numerical value of AGFI and GFI are both greater than 0.9, and the suitable degree of adaptation is ideal, RMSEA value is 0.066, less than the standard value, suitable for the ideal; the added fitness index of TLI, CFI, and IFI equivalent fitness index of value are better, in the acceptable range; The simple fitness index PGFI, PNFI, PCFI three index values are 0.626, 0.534, 0.602, the value is greater than the standard value of 0.5, which indicates that the degree of adaptation is ideal. Although some index is not particularly desirable, but overall, the revised structural equation model better fit.

To see the relationship between the latent variables and latent variables in the model, the relationship between the latent variables and observed variables, the regression coefficient of the former is the path coefficient and the regression coefficient of the latter is known for load coefficient. The critical ratio (C.R.) is obtained by the ratio of the parameter estimates and the standard error (S.E), and the significance of the correlation coefficient can be assessed by the size of the P. We find both the path coefficient and load coefficient reach the significant level, indicating that the model is good.

Through the evaluation of the model, we can get the inner quality of the internal control quality and investment efficiency, and then explain the results of the model.

1. The relationship between latent variables and latent variables

Hypothesis Hi for corporate governance and internal control quality has a significant positive correlation, the corporate governance quality impact of internal control is 0.163 and is positive correlation, hypothesis Hi was established. Assuming that H2 is positive correlation between corporate governance and investment efficiency, the impact of corporate governance on investment efficiency is 0.305, assuming H2 is established. For the H2, Hi assumption are established, we can get that the corporate governance on the quality of internal control and investment efficiency have an impact, and by affecting the quality of internal control and then affect the efficiency of investment.

Hypothesis H3 for internal quality control has a significant effect on the financing constraints, it maybe positive correlation or negatively related, but through the research, the quality of internal control of financing constraints degree of influence is 0.304, and it is positive correlation, indicating that higher internal quality control to obtain more external financing; Hypothesis H4 of financing constraints on investment efficiency has a significant impact, degree effect of financing constraints on investment efficiency is 0.702, and the effect is large visibly.

Hypothesis H5 for internal control quality and investment efficiency has a positive correlation, the quality of internal control of investment efficiency is 0.26, the improvement of internal control would improve the investment efficiency directly.

2. The relationship between latent variables and observed variables

The corporate governance latent variables have six observed variables, including the proportion of institutional investors holding, equity balance degree, independent directors, independent directors will compensation, supervisors will education background and executive compensation, their load coefficient followed by 0.505, 0.257, 0.487, 0.142, 0.125 and 0.214.Corporate governance has a significant impact on the quality of internal control and investment efficiency.

The potential variable of financing constraints is the intermediate variable between internal control quality and investment efficiency, which plays an important role. The commercial credit ratio of the load factor is 0.100, the load factor of the bank loan ratio is 0.554, and the load factor of the cash holdings is 0.512.

5. Conclusion

Based on the previous theoretical analysis and empirical analysis, we found that corporate governance has an important influence on both the quality of internal control and investment efficiency, and the degree of influence is 0.163 and 0.305 respectively; Internal quality control has a direct effect on the efficiency of investment and the influence degree is 0.26; indirect influence on efficiency of investment by financing constraints, internal control quality of financing constraints degree of influence is 0.304, the impact of financing constraints on investment efficiency is 0.702. Therefore, to improve the quality of internal control, and ultimately to improve the efficiency of investment, we should improve the following aspects: the corporate governance structure, internal control institution, financing structure, the level of financing management, function of the supervision organization.

Recebido/Submission: 02/04/2016

Aceitacao/Acceptance: 10/05/2016

Acknowledgments

The work of this paper is supported by Project of science and Technology Department of Hebei Province (15456134); Hebei philosophy and Social Science Fund Project(HBi6MK029); Project of Tangshan City science and Technology Bureau(2013cx4).

References

Chung, H., Fuyan, L. (2015). Analysis of earnings management influence on the investment efficiency of listed Chinese companies. Journal of Empirical Finance, 34, 60-78.

Delgado, A., Velthuis, M. (2015). Proposal for a continuous improvement IT governance framework at financial institutions. RISTI--Revista Iberica de Sistemas e Tecnologias de Informacao, (15), 51-67.

Hyeesoo, H. (2013). Litigation risk, accounting quality, and investment efficiency. Advances in Accounting, 29, 180-185.

Ioan, O. (2014). Investigations Upon the Correlations between the Efficiency of Investment Strategies and the Market Performances of the Romanian Financial Investment Companies. Procedia Economics and Finance, 15, 609-616.

Kuei, F., Yi, P. (2014). Directors' and officers' liability insurance and investment efficiency: Evidence from Taiwan. Pacific-Basin Finance Journal, 29, 18-34.

Pereira, C., Ferreira, C. (2015). Identification of IT Value Management Practices and Resources in COBIT 5. RISTI--Revista Iberica de Sistemas e Tecnologias de Informacao, (15), 17-33.

Peng, G. (2015). Empirical study of external environment and internal control quality. Commercial Accounting, (10), 78-80.

Hongwei Du (1,2), *, Juan Li (1), linjie Lei (1)

* Duhongwei_163@163.com

(1) North China University of Science and Technology, Tangshan 063009, China

(2) Chinese Academy of Governance, Beijing 100089, China
Table 1--Summary table of influence factors of the
internal control quality

influence factor

             Company age
company      company size
features     Business complexity
             Controlling shareholder equity
             Ownership concentration
             Equity balance degree
             Institutional investors shareholding
             Size of the board of directors
             Board of directors diligence
             Directors' remuneration
             Independent director salary
             Proportion of independent directors
             Proportion of independent directors
             Independent director professional

corporate    Leadership structure
governance   Executive compensation
             Shareholding ratio of top management
             Senior management sex ratio
             Average age of senior executives
             Average level of executive education
             The importance of management to the competency of employees
             The scale of the board of supervisors
             Supervisory education background
             Supervisor salary
             The establishment of the audit committee

External     Audit committee industry
audit        Audit quality

influence
factor       Calculation method or description

             Time of establishment of the company
company      Natural logarithm of total assets
features     Number of industry
             Controlling shareholder equity nature of the State-Owned
                Company to take 1, non State-Owned Company
             Largest shareholder/Total shares
             Second to five largest shareholder shareholding ratio
             Institutional investor shareholding ratio
             Total number of directors
             Number of meetings of directors
             Directors' remuneration
             Total remuneration of independent directors
             Independent directors/The total number of shares.
             Number of independent directors/Total number of directors
             The number of independent directors with financial,
                financial and accounting background

corporate    The chairman of the board of directors and the general
governance   manager of the same person as the take 1, and vice
                versa for 0
             General manager salary (10000 yuan)
             General manager shares and the ratio of total shares
             Team members assigned to the male is 1, female is 0, the
                average value
             The average age of all the members of the executive team
                to represent
             The average value of the degree (Master's degree and above
                6 points, 3 points, junior college and the following
                0 points)
             Employees with college or above, accounting for the
                proportion of all employees
             Total number of supervisors
             The average value of the degree (Master's degree and above
                6 points, 3 points, junior college and the following
                0 points)
             Total remuneration of supervisors
             Set up to take 1, and instead take 0

External     Independent directors should take the number of meetings
audit           as a substitute variable
             If the listing Corporation hired the first four major
                audit institutions to 1, otherwise 0

Table 2--Summary table of influence factors of the
investment efficiency

influence factor

               Controlling shareholder equity
               Number of shareholders' meeting
corporate      Ownership concentration
governance     Equity balance degree
               Institutional investor shareholding ratio
               Size of the board of directors
               Board of directors diligence

               Proportion of independent directors
               Independent director salary
               Proportion of directors to receive remuneration
               The scale of the board of supervisors
corporate      Supervisory education background
governance     Supervisor salary
               Proportion of supervisors to receive remuneration
               Leadership structure
               Shareholding ratio of top management
               Executive compensation
               Senior management sex ratio

agency cost    Average age of senior executives
               Management expense ratio
               Financial expense ratio

               Debt ratio
               Short-term debt ratio
Financing      Commercial credit ratio
constraints    Bank loan ratio
               Cash holdings
               Cash flow uncertainty

Accounting     AIQ1
information    AIQ2
quality

influence
factor         metering method

               Controlling shareholder equity nature of the
                  State-Owned Company to take 1, non State-
                  Owned Company 0
               Number of shareholders' meeting
corporate      Largest shareholder/Total shares
governance     Second to five largest shareholder shareholding
                  ratio
               Equity ratio held by institutional investors
               Total number of directors
               Number of meetings of the board of directors

               Number of independent directors/Number of directors
               Total remuneration of independent directors
               Number of directors to receive remuneration/Total
                  number of directors
               Number of supervisors
corporate      The average of the degree (Master's degree and
governance        above 6 points, 3 points, junior college and
                  the following 0 points)
               Total remuneration of supervisors
               Number of supervisors to receive remuneration/The
                  total number of supervisors
               The chairman of the board of directors and the
                  general manager of the same person as the take
                  1, and vice versa for 0
               General manager shares and the ratio of total
                  shares
               Executive compensation
               Team member men assigned to 1, women 0, and then
                  the average

agency cost    The average age of all the members of the
                  executive team to represent
               Management expenses/Main business income
               Financial expenses/Main business income

               Total liabilities/Total assets
               Total short-term liabilities/Total liabilities
Financing      (Accounts receivable+Notes payable+Accounts
constraints       receivable)/ total assets
               (Short term loan+Long term loan)/total assets
               Cash and cash equivalents/(total assets-Cash and
                  cash equivalents)
               Cash flow standard deviation of operating
                  activities in the last three years

Accounting     Negative value of the residual absolute value of
information       the Jones model
quality        The reciprocal of the earnings smoothness index
                  calculated by Francis

Table 3--Research hypothesis of initial overall path

influence factor          research hypothesis

Company characteristics   Corporate characteristics have a significant
                          impact on the quality of internal control

corporate governance      Positive correlation between corporate
                          governance and internal control quality

                          Positive correlation between corporate
                          governance and investment efficiency

External audit            External audit has a significant impact on
                          the quality of internal control

agency cost               The quality of internal control and agency
                          costs are negatively correlated

                          Agency cost has a significant impact on
                          investment efficiency

Financing constraints     The quality of internal control has a
                          significant impact on Financing Constraints

                          Financing constraints have a significant
                          impact on investment efficiency

Accounting information    The internal control quality and the
quality                   accounting information quality are positively
                          related

                          Positive correlation between accounting
                          information quality and investment efficiency

Positive correlation between internal control quality and
investment efficiency

Table 4--Principal components variance contribution rate
of internal control quality

Ingredients        Initial eigenvalue

                       % of
              total    variance   Cumulative%

1             2.109    14.057     14.057
2             1.921    12.808     26.865
3             1.345    8.965      35.831
4             1.245    8.298      44.129
5             1.077    7.180      51.309
6             1.029    6.862      58.171
7             0.980    6.535      64.706
8             0.914    6.096      70.802
9             0.854    5.691      76.494
10            0.775    5.167      81.660
11            0.694    4.628      86.288
12            0.659    4.396      90.684
13            0.559    3.729      94.413
14            0.443    2.953      97.366
15            0.395    2.634      100.000

Ingredients   Extraction square and loading

                       % of
              total    variance   Cumulative%

1             2.109    14.057     14.057
2             1.921    12.808     26.865
3             1.345    8.965      35.831
4             1.245    8.298      44.129
5             1.077    7.180      51.309
6             1.029    6.862      58.171
7             0.980    6.535      64.706
8             0.914    6.096      70.802
9             0.854    5.691      76.494
10            0.775    5.167      81.660
11            0.694    4.628      86.288
12
13
14
15

Table 5--Multiple regression analysis of influence
factors on internal control quality

                 Non standardized    standardized
                 coefficient         coefficient

                         Standard
                 B       error       Beta    t       Sig.

Institutional    .007    .002        .155    3.000   .003
investor
shareholding
ratio

Independent      .005    .001        .120    4.879   .000
director
salary

Supervisory      .020    .004        .111    4.963   .000
education
background

Table 6--Multiple regression analysis of influence
factors on investment efficiency

                 Non standardized     Standard
                 coefficient          coefficient

                          Standard
                 B        error       Beta      t        Sig.

Institutional    .006     .001        .198      5.982    .000
investor
shareholding
ratio

Proportion of    .008     .002        .231      4.001    .000
independent
directors

Executive        -.025    .009        -.115     -2.783   .006
compensation

Equity           .001     .000        .118      2.972    .003
balance
degree

Bank             .138     .025        .136      5.534    .000
loan
ratio

Commercial       -0.011   .000        -.111     -2.215   .027
loan
ratio

Table 7--SEM representation of latent variables
and observed variables

Symbol           Latent variable    symbol   Observable variable

                                    1        Institutional investors
                                             shareholding
[[xi].sub.1]     corporate
                 governance         2        Equity balance degree
                 (Exogenous
                 latent variable)   2        Proportion of
                                             independent directors

                                    4        Independent director
                                             salary

                                    5        Supervisory education
                                             background

                                    6        Executive compensation

[[eta].sub.1]    Financing                   Commercial credit ratio
                 constraints                 Bank loan ratio
                 (Internal                   Cash holdings
                 potential
                 variable)

[[eta].sub.2]    Internal                    Internal control
                 control quality             quality 1
                 (Internal
                 potential                   Internal control
                 variable)                   quality 2

[[eta].sub.3]    Investment                  Investment
                 efficiency                  efficiency 1
                 (Internal
                 potential                   Investment
                 variable)                   efficiency 2

Table 8--Research hypothesis of basic path

Hypotheticalresearch hypothesis

[H.sub.1]   Positive correlation between corporate governance and
            internal control quality

[H.sub.3]   The quality of internal control has a significant impact on
            Financing Constraints

[H.sub.4]   Financing constraints have a significant impact on
            investment efficiency

[H.sub.5]   Positive correlation between internal control quality and
            investment efficiency
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Author:Du, Hongwei; Li, Juan; Lei, Linjie
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Date:Aug 1, 2016
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