Impact of Firm Power on Debt Structure, Bank Loan Financing and Corporate Performance in China

Nicolas Diodji Mamadou Faye¹, El Hadji Omar Ndao², Kokou W. Tozo³, Mouanda Gilhaimé⁴, Mohammed Abdul-Latif⁵

¹Direction des Financements et des Partenariats Public-Privé, Ministère de l’Economie, du Plan et de la Coopération, Dakar, Sénégal.
²School of Economics Sciences, Management and Trade, Universite du Sine-Saloum Elhadji Ibrahima NIASS, Fatick, Sénégal.
³Institute of New Structural Economics, Peking University, Beijing, China.
⁴School of Economics, Henan University, Kaifeng, China.
⁵Newcastle Business School, University of Newcastle, Newcastle, Australia.

DOI: 10.4236/ti.2023.142004                

Abstract

This paper examines the incidence of firm value chain power on its exterior financing liabilities, bank loan financing and firm performance. Taking data from the China Stock Market and Accounting Research (CSMAR), this study has gathered cross-sectional data of 13,653 firms from 2006 to 2016. The results indicate that industries with higher power in the value chain carry a lower volume of financing liabilities. The results also show that companies with greater firm power use lower financing liabilities and aim to utilize non-cost commercial credit for financing. The study also reveals that creditors from the banks sector give more hand to large firms, and the role of firm power has merely been accepted by banks in big-scale and constant companies. Additionally, firm power has no considerable impact on the maturity of bank loans. After last, this study moreover unveils the economic outcomes of the effect of firm value chain power across the differences in firm financial performance. Low-scale, great-growth firms with bigger firm power get best financial performance.

Keywords

Company Value Chain Power, Industry Chain, Financial Liabilities, Bank Loan Financing, Firm Performance

1. Introduction

The shape of a firm in the upstream and downstream industry chain carried an effect on its business orientations. Nevertheless, not many studies have examined the effect of upstream and downstream firm value chain power relations on firm financial behavior. The goal of this paper is to construct a value-chain power measure that shows the shape of the firm’s upstream and downstream industry chains across its capital trade relations with upstream and downstream firms, and to study its effect on firm financing attitude, capital structure decisions, and firm performance. Traditional theory used to explain its link with upstream and downstream firms from the optics of firm working capital management. Yet, significant late investigations reveal that the framework of company working capital is deeply driven by the firm’s posture in the upstream and downstream industry chain. Based on this, this study builds the firm value chain power as being the report of accounts payables minus accounts receivable to sales revenue. In a simple way, the bigger this measure is, the bigger the capacity of a company to hold money of upstream and downstream firms, showing the comparatively robust competitiveness of the firm. Using this measure, this paper investigates the incidence of firm value chain power on its exterior financing liabilities, bank loan financing, and corporate performance in three distinct parts.

Part one studied the effect of firm value chain power on company exterior financing liabilities. Based on the definition, a firm with a large value chain power can get more advantages from his suppliers. In this direction, the firm’s current assets and even some long-term assets can be achieved with interest free business credit. Large firms value chain power, less dependence on exterior financing. Part two Data on bank loan financing investigates the effect of firm value chain power on bank financing scale, precisely on interest rate, loan amount and loan maturity structure. The results also show that companies with greater firm power use lower financing liabilities and aim to utilize non-cost commercial credit for financing. The study also reveals that creditors from the banks sector give more hand to large firms, and the role of firm power has merely been accepted by banks in big-scale and constant companies. Additionally, firm power has no considerable impact on the maturity of bank loans. After last, this study moreover unveils the economic outcomes of the effect of firm value chain power across the differences in firm financial performance. Low-scale, great-growth firms with bigger firm power get best financial performance.

2. Literature Review

We refer to customer power as the ability of a customer to reduce price below a supplier’s normal selling price or, more generally, the ability to obtain terms of supply more favorable than a supplier’s normal terms (Galbraith, 1952; Chen, 2008) . For instance, Porter (1974: p. 423) points out that, where retailer power is high, a manufacturer’s rate of return will be bargained down. In addition, Snyder (1996, 1998) argues that customer power can intensify competition among suppliers and lead to lower prices, which reduces suppliers’ profits. Finkelstein (1992) distinguishes four sources of power: structural power, ownership power, expert power, and prestige power. Structural power is the most frequently cited in the literature and has been found on distinct organizational structure and hierarchical authority (Brass, 1984; Hambrick, 1981; Perrow, 1970; Tushman & Romanelli, 1985) .

Trade credit is an important source of funds for both small and large firms around the world (Petersen & Rajan, 1997; Demirguc-Kunt & Maksimovic, 2002) . Many firms use trade credit both to finance their input purchases (accounts payable) and offer financing to their customers (accounts receivable). The traditional explanation for the existence of trade credit is that trade credit plays a non-financial role. That is, trade credit reduces transaction costs (Ferris, 1981) , allows price discrimination between customers with different credit-worthiness (Brennan, Maksimovic, & Zechner, 1988) , fosters long-term relations with customers (Wilson & Summers, 2002) , and even provides a warranty for quality when customers cannot observe product characteristics (Long, Malitz, & Ravid, 1993) . More recently, financial theories argue that suppliers have a lending advantage over financial institutions, due to better information (Biais & Gollier, 1997) , lower borrower’s opportunism (Burkart & Ellingsen, 2004) , or a liquidation advantage (Fabbri & Menichini, 2010) .

According to Allen et al. (2005) , China’s banking industry is mainly occupied by four major state-owned banks. La Porta, Lopez-de-Silanes, & Shleifer (2002) showed that the government owns 99.45% of the 10 largest commercial banks in China in 1995 (100% in 1970); this ownership level is one of the highest in their sample of 92 countries. Moreover, the LLS result on the negative relation between government ownership of banks and the growth of a country’s economy seems to apply to China’s State Sector and the status quo of its banking sector. However, high government ownership has not slowed down the growth of the Private Sector (Allen et al., 2005) . China’s bank loan market has mainly headed by national banks (Allen et al., 2005) . Among the 2467 bank loans (RMB 598.52 billion), RMB 238.24 billion are attributable to the Big4 national banks and RMB 360.28 billion are attributable to other banks (including national banks such as China Development Bank and Bank of Communication). (Allen et al., 2019) carried out transaction-level analyses of entrusted loans, one of the biggest elements of shade banking in China. Entrusted loans involve firms with privileged access to cheap capital channeling funds to less privileged firms, and the increase when credit is tight (Allen et al., 2019) . Still according to (Allen et al., 2019) , nonaffiliated loans have much higher interest rates than both affiliated loans and official bank loans, and they largely flow into real estate. The rating of entrusted loans, particularly of nonaffiliated loans, includes essential and in-formational risks. Stock market feedback implies that both affiliated and nonaffiliated loans are closely compensated investments. Using an independently pooled cross-section of 374 MFI-year observations for 280 MFIs in 70 countries, (Tchakoute-Tchuigoua & Soumaré, 2019) analyzed the impact of loan approval decentralization on MFI portfolio quality and out-reach, and the effects of alignment mechanisms when loan officers combine information production and decision functions. The authors’ findings revealed that effective incentive schemes and internal control systems help mitigate agency problems within MFIs, and thus increase the outreach of MFIs without altering the quality of their loan portfolio. (Wheeler, 2019) documented that loan loss accounting affects pro-cyclical lending through its impact on regulatory actions. Indeed, regulators are more likely to place banks with inadequate loan loss allowances under enforcement actions that restrict lending, leading these banks to lend less during downturns.

Corporate Performance is an intricate phenomenon and managers often encounter trade-off decisions with respect to different performance metrics and timeframes (Ambler & Roberts, 2006; Morgan, Slotegraaf, & Vorhies, 2009) . Guo, Li, & Zhong (2018) investigated whether corporate culture promotion impact firm performance in China in terms of firm market value, firm financial performance and innovation output. The authors found strong support that corporate culture promotion has negatively correlated to firm market value, positively correlated to innovation output and not significantly correlated to firm financial performance. Furthermore, the negative impact of corporate culture promotion on firm market value has operated by small firms and firms located in less developed provinces. Moreover, the authors found also that some precise corporate culture promotions, such as innovation culture promotion and integrity culture promotion, are not linked to firm value or financial profitability.

3. Research Gap

The research in this article highlights the subsequent practical involvements: first, while firms with higher value chain power do not have high external debt financing needs, their status in the upstream and downstream industry chain eases their financing in the bank sector. The impact is mainly significant for companies with high-scale and constant businesses. The innovation of this paper has showed up in the following aspects: first, most of the previous studies analyses the structure of firm financing from the view point of firm working capital management strategies and the resort to commercial credit, while this paper creatively constructs a reflecting firm value chain power based on the working capital structure. The firm value chain index of the relative location in the upstream and downstream industrial chain, and in-depth discussion of the effect on firm financing behavior, further enriched the research on the incidence of upstream and downstream industrial chain relationships on the true operation of firms. Second, the research in this paper gives direct evidence that value chain power can impact firm debt financing facilities. The research in this paper highlights that the effect of firm value chain power on various types of debt financing is heterogeneous. In bank loans financing, although the value chain power as a whole helps to increase the scale of corporate bank loans, its role in reducing loan costs is only significant in large companies with stable operations. After last, this study moreover unveils the economic outcomes of the effect of firm value chain power across the differences in firm financial performance. Low-scale, great-growth firms with bigger firm power get best financial performance.

4. Hypotheses Development

4.1. Firm Power and Debt Structure

H1. Firms with higher power in industrial chain have lower financial debt ratio (financial liability/total liability) because of their better access to trade credit (e.g. account payable), that is to say financial leverage ratio is negatively correlated with firm power.

4.2. Firm Power and Bank Loan Financing

H2. Firms with higher power in industrial chain enjoy many facilities from banks.

4.2.1. Firm Power and Interest Rate

H2a. Firms with higher power in industrial chain get loan with a lower interest rate, that is to say, the interest rate is negatively correlated with firm power.

4.2.2. Firm Power and Loan Amount

H2b. Firms with higher power in industrial chain have loan with a higher amount, i.e. loan amount is positively correlated with firm power.

4.2.3. Firm Power and Loan Maturity

H2c. Firms with higher power in industrial chain get long-term loans, i.e. loan maturity is positively correlated with firm power.

4.3. Firm Power and Corporate Performance

H3. Firms with higher power in industrial chain exhibiting good financial behaviors show good performance, that is to say, corporate performance is positively correlated with firm power.

5. Research Method

The data for this study has been taken from a single trustworthy data source which is the “China Stock Market and Accounting Research” (CSMAR) database. To test empirically the proposed hypotheses, this study has collected unbalanced cross-sectional data of 13,653 from the Bank Loan Market from 2006 to 2016. Thus, make a total 224,163 firms’ year observations.

5.1. Econometric Models

The study has winsorized all the continuous variables at 1^st and 99^th percentiles in order to control the influence of outliers. To test the developed hypotheses, the following regressions equations have been established:

5.1.1. Firm Power and Debt Structure

$\begin{array}{l}{\text{Financial\_Leverage\_Ratio}}_{it}\\ ={\beta }_0+{\beta }_{\text{1}}{\left(\text{Power\_Sales}\right)}_{it}+{\beta }_{\text{2}}{\left(\text{Rating}\right)}_{it}+{\beta }_{\text{3}}{\left(\text{Size}\right)}_{it}+{\beta }_{\text{4}}{\left(\text{leverage}\right)}_{it}\\ +{\beta }_{\text{5}}{\left(\text{Market\_Book}\right)}_{it}+{\beta }_{\text{6}}{\left(\text{Sales\_Growth}\right)}_{it}+{\beta }_{\text{7}}{\left(\text{Tangibility}\right)}_{it}\\ +{\beta }_{\text{8}}{\left(\text{Profitability}\right)}_{it}+{\mathcal{E}}_{it}\end{array}$ (1)

5.1.2. Firm Power and Bank Loan Financing

${\text{Bank\_Loan}}_{it}={\beta }_0+{\beta }_{\text{1}}{\left(\text{Firm\_Power}\right)}_{it}+{\displaystyle {\sum }_i{\text{CONTROLS}}_{it}}+{\mathcal{E}}_{it}$ (2)

1) Firm Power and Interest Rate

$\begin{array}{l}{\text{Interest\_Rate}}_{it}\\ ={\beta }_0+{\beta }_{\text{1}}{\left(\text{Power\_Sales}\right)}_{it}+{\beta }_{\text{2}}{\left(\text{Rating}\right)}_{it}+{\beta }_{\text{3}}{\left(\text{Size}\right)}_{it}+{\beta }_{\text{4}}{\left(\text{leverage}\right)}_{it}\\ +{\beta }_5{\left(\text{Market\_Book}\right)}_{it}+{\beta }_6{\left(\text{Sales\_Growth}\right)}_{it}+{\beta }_7{\left(\text{Tangibility}\right)}_{it}\\ +{\beta }_{\text{8}}{\left(\text{Profitability}\right)}_{it}+{\beta }_{\text{9}}{\left(\text{Long\_Term\_Debt\_Ratio}\right)}_{it}+{\mathcal{E}}_{it}\end{array}$ (3)

2) Firm Power and Loan Amount

$\begin{array}{l}{\text{Loan\_Amount}}_{it}\\ ={\beta }_0+{\beta }_1{\left(\text{Power\_Total\_Assets}\right)}_{it}+{\beta }_2{\left(\text{Rating}\right)}_{it}+{\beta }_3{\left(\text{Size}\right)}_{it}\\ +{\beta }_4{\left(\text{leverage}\right)}_{it}+{\beta }_5{\left(\text{Market\_Book}\right)}_{it}+{\beta }_6{\left(\text{Sales\_Growth}\right)}_{it}\\ +{\beta }_7{\left(\text{Tangibility}\right)}_{it}+{\beta }_8{\left(\text{Profitability}\right)}_{it}\\ +{\beta }_{\text{9}}{\left(\text{Long\_Term\_Debt\_Ratio}\right)}_{it}+{\mathcal{E}}_{it}\end{array}$ (4)

3) Firm Power and loan Maturity

$\begin{array}{l}{\text{Loan\_Maturity}}_{it}\\ ={\beta }_0+{\beta }_1{\left(\text{Power\_Sales}\right)}_{it}+{\beta }_2{\left(\text{Rating}\right)}_{it}+{\beta }_3{\left(\text{Size}\right)}_{it}+{\beta }_4{\left(\text{leverage}\right)}_{it}\\ +{\beta }_5{\left(\text{Market\_Book}\right)}_{it}+{\beta }_6{\left(\text{Sales\_Growth}\right)}_{it}+{\beta }_7{\left(\text{Tangibility}\right)}_{it}\\ +{\beta }_8{\left(\text{Profitability}\right)}_{it}+{\beta }_9{\left(\text{Long\_Term\_Debt\_Ratio}\right)}_{it}+{\mathcal{E}}_{it}\end{array}$ (5)

5.1.3. Firm Power and Corporate Performance

$\begin{array}{l}{\text{PERF}}_{it}\\ ={\beta }_0+{\beta }_1{\left(\text{Power\_Sales}\right)}_{it}+{\beta }_2{\left(\text{Coupon\_Rate}\right)}_{it}+{\beta }_3{\left(\text{Bond\_Amount}\right)}_{it}\\ +{\beta }_4{\left(\text{Bond\_Maturity}\right)}_{it}+{\beta }_5{\left(\text{Rating}\right)}_{it}+{\beta }_6{\left(\text{Size}\right)}_{it}+{\beta }_7{\left(\text{Leverage}\right)}_{it}\\ +{\beta }_8{\left(\text{Market\_Book}\right)}_{it}+{\beta }_9{\left(\text{Sales\_Growth}\right)}_{it}+{\beta }_{10}{\left(\text{Tangibility}\right)}_{it}\\ +{\beta }_{11}{\left(\text{Profitability}\right)}_{it}+{\mathcal{E}}_{it}\end{array}$ (6)

5.2. Variables Specification

5.2.1. Independents Variables

Table 1 highlights the different independendents variables, how they are measured and the references used for the purpose of the studies. The independents variables used are: Power, Power_Sales, Power_Total_Assets and Power_Robustness.

5.2.2. Dependents Variables

Table 2 shows the different dependents variables, how they are measured and

Table 1. Summary of independents variables.

Table 2. Summary of dependents variables.

the references used for the purpose of the study. The dependents variables are: Financial_Debt_Ratio, Interest_Rate, Loan_Amount, Loan_Maturity, Return on Asset (ROA) and Return on Equity (ROE). CSMAR (China Stock Market & Accounting Research) is a database which offers data on the China stock markets and the financial statements of China’s listed companies.

5.2.3. Control Variables

Table 3 shows a summary of the all control variables, their measurement and their references used during the study. The study employed eight (8) control variables which are: size, leverage, market_book, sales_growth, tangibility, profitability, rating and long term debt ratio.

6. Results and Discussion

6.1. Overall Descriptive Statistics

Table 4 highlights a summary statistic of all the variables used in the study. The statistic includes the number of observations, the mean, the standard deviation, the min and the max of each variable.

Table 5 shows the correlation matrix of the variables. The correlation matrix shows the correlation values, which measure the degree of linear relationship between each pair of variables. The correlation values can fall between −1 and +1. If the two variables tend to increase and decrease together, the correlation value is positive as we can see it in Table 5.

Table 3. Summary of control variables.

Table 4. Summary statistics of variables.

Table 5. Correlation matrix of variables.

With X1 = Interest_Rate; X2 = Loan_Amount; X3 = Loan_Maturity; X4 = Power_Sales; X5 = Power_Total_Assets; X6 = Power_Robustness; X7 = Size; X8 = Leverage; X9 = Market_Book (M/B); X10 = Sales_Growth (S/G); X11 = Tangibility; X12 = Profitability; X13 = Long_Term_Debt_Ratio.

6.2. Regression Results and Discussion

6.2.1. Firm Power and Debt Structure

Tables 6-8 show the regression results for the effect of firm power on financial leverage ratio while controlling for the previously mentioned control variables. As we can notice in the three tables (Tables 6-8) presented here, the effect of firm power on debt structure is pronounced among all the firms studied. The coefficient of interaction between firm power and the financial leverage ratio is negative and significative (−0.983**) as predicted in the hypothesis development. Clearly, firms with higher power, i.e. having a good financial situation, will see their financial leverage ratio (financial liability/total liability) reduced because of their better access to trade credit (e.g. account payable). In fact, firms resort to external financings like bonds and loans only when they have no choice because of the high cost of debt. This being the case, the companies showing a good financial situation that is to say having power of influence can negotiate directly with their suppliers trade credit, which will allow them to have quite reasonable payment periods.

6.2.2. Firm Power and Bank Loan Financing

1) Firm Power and Interest Rate

Tables 9-11 show the results for the effect of firm power on Interest Rate while controlling for the previously mentioned control variables. Here, the effect of firm power on interest rate is more pronounced among big size and low growth firms as we can note it among the three Tables 9-11 presented. The coefficient of interaction between firm power and interest rate is negative and

Table 6. Regression results for the effect of firm power on financial leverage ratio for all firms studied.

Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

Table 7. Regression results for the effect of firm power on financial leverage ratio for small size and high growth firms.

Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

Table 8. Regression results for the effect of firm power on financial leverage ratio for big size and low growth firm.

Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

Table 9. Regression results for the effect of firm power on interest rate for all firms studied.

Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

Table 10. Regression results for the effect of firm power on interest rate for small size and high growth firms.

Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

Table 11. Regression results for the effect of firm power on interest rate for big size and low growth firms.

Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

significant (−0.0250**) as predicted in the hypothesis development. In this case, our hypothesis is supported. We also note a significant weakness of some coefficients or even a lack of significant coefficients. This situation could be explained by a lack of data. In fact, having data on interest rates is not easy. In many banks, this information has not been made public. This situation has affected the significance of certain coefficients. Overall, the general idea of our approach to the effect of firm power on interest rate related in the development of our hypotheses is thus reported in the results. In clear, firms with a higher power in industrial chain play on their power of persuasion to be able to have loans with reduced rates. Indeed, firm power will be priced in external debt financing. It will help firms to finance more at lower cost if high powers do have demands. Furthermore, profitable firms are charged lower loan rates because higher cash flows help mitigate credit risk.

Our results go against those proposed a long time ago by (Kashyap & Stein, 1994) and (Bernanke & Blinder, 1988) . Indeed, for the authors, public borrowers that is to say firms going to the bond market are larger and more profitable firms, firms showing a higher proportion of fixed assets to total assets and having higher credit ratings than firms borrowing from either banks or non-bank private lenders. Inversely, firms that borrow from non-bank private lenders tend to be the poorest performers and have the lowest credit rating and the highest ex-ante probability of default and that also banks play a crucial role or small and medium-sized enterprises in the provision of external finance and this gives rise to the bank lending channel. Our study shows that smaller size with higher growth firms also used the bond market as a means of financing, and that bank financing also attracts large firms.

2) Firm Power and Loan Amount

Tables 12-14 show the results for the effect of firm power on loan amount while controlling for the previously mentioned control variables. In this case, the effect of firm power on loan amount is more pronounced among all the firms studied as we can remark it among the three Tables 12-14 presented. Both measures of firm power attract a positive coefficient. The statistical significance of these estimates is strong compared to other estimates. The coefficient of interaction between firm power and loan amount being positive (43,106***) as predicted in the hypothesis development, our hypothesis is therefore supported. These results suggest that firms with higher power benefit from loans with a higher amount. Indeed, thanks to their power, firms succeed in gaining the confidence of banks by presenting them good financial statements. The latter being reassured of the future profitability of the firms and their ability to pay back the loans they grant them loans, with consistent amounts.

3) Firm Power and Loan Maturity

Tables 15-17 show the results for the effect of Firm Power on Loan Maturity while controlling for the previously mentioned control variables. Here too, the effect of firm power on loan maturity is pronounced among all the firms studied as we can notice it among the three Tables 15-17 presented. The two measures of power employ show up a positive coefficient. Like for the interest rate, we also note a significant weakness of some coefficients or even a lack of significant coefficients. As pointed out early this situation could be explained by a lack of data. As for the interest rate, the data on the maturity of the loans have been downloaded with a lot of missing values. This situation had an impact on the significance of certain coefficients. All the same, the coefficient of interaction between firm power and loan maturity being positive but not significative (0.000132) contrary to our prediction, therefore our hypothesis is not supported. Clearly, our prediction according to which firms with higher power get long-term debt because of their better ability to pay back debt is not supported.

Table 12. Regression results for the effect of firm power on loan amount for all firms studied.

Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1

Table 13. Regression results for the effect of firm power on loan amount for small size and high growth firms.

Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

Table 14. Regression results for the effect of firm power on loan amount for big size and low growth firms.

Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

Table 15. Regression results for the effect of firm power on loan maturity for all firms studied.

Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

Table 16. Regression results for the effect of firm power on loan maturity for small size and high growth firms.

Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

Table 17. Regression results for the effect of firm power on loan maturity for big size and low growth firms.

Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

Table 18. Regression results for the effect of firm power on corporate performance for all firms studied.

Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

Table 19. Regression results for the effect of firm power on corporate performance for small size and high growth firms.

Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

Table 20. Regression results for the effect of firm power on corporate performance for big size and low growth firms.

Robust standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

6.2.3. Firm Power and Corporate Performance

Tables 18-20 show the results for the effect of Firm Power on Corporate Performance while controlling for the previously mentioned control variables. Here, the effect of firm power on corporate performance is more pronounced among firms that are constrained by information asymmetric as we can note it in the three Tables 18-20 presented. This is here the case for small size and high growth firms. The coefficient of interaction between firm power and RAO and ROE respectively 0.00305*** and 0.00579*** are found both to be positive and significant. These results support us in our desire to show that firms with higher power in industrial chain exhibiting good financial behaviors show good performance. As explained above, these results are the consequence of firms with good financial behaviors that have successfully raised funds in the bond market and secured loans from banks. This shows that firm power and its interactions with financing behaviors naturally influence corporate performance.

7. Conclusion

This paper investigates first the impact of Firm value chain power on firms’ financial leverage, second Bank Loan Financing, and third examines how debt financing moderates the link between firm value chain power and corporate performance. The data has been taken from the “China Stock Market and Accounting Research” (CSMAR) database, this paper has gathered cross-sectional data of 13,653 firms from the Bank Loan Market from 2006 to 2016. Running fixed effects regression, the results reveal that companies with greater value chain power, i.e. having a better financial position, will have their financial leverage ratio (financial liability/total liability) lowered due to their better access to trade credit (e.g. account payable), companies with greater value chain power enjoy large opportunities from banks. Clearly, companies with greater value chain power get access to loan with low interest rate, higher amount and long-term maturity. Finally, the results indicate that companies with greater value chain power tend to show good performance.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

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