How Does Supply Chain Information Disclosure Relate to Corporate Investment Efficiency? Evidence from Chinese-Listed Companies

Abstract

Supply chain information disclosure is a vital factor for corporate investment efficiency and can signal a corporation’s long-term sustainable development. However, little attention has been paid to its significance. In this paper, we investigate how supply chain information disclosure affects corporate investment decisions. Using a sample of Chinese-listed firms, we find that firms that disclose nonfinancial information are more likely to have a high level of investment efficiency. We also identify the mechanism underlying the effect by examining the mediating effect of financial constraints and agency costs. Increasing a firm’s supply chain information disclosure can improve its investment efficiency by reducing its financial constraints and agency costs. We further find that this positive impact is more pronounced for non-state-owned enterprises (non-SOEs) and firms located in regions with a high degree of marketization. Our findings imply that supply chain information disclosure plays an important role in corporate investment efficiency and sustainable development. Our study emphasizes the importance of nonfinancial information disclosure, contributing to the literature investigating the role of supply chain management in corporate decision-making on sustainable development.

1. Introduction

With a slowdown in global economic development, enterprises are faced with many challenges that require them to take action due to adaptation in the context of sustainable development. Investors are not only concerned about the operation and financial benefits of companies but are also interested in the sustainable practices adopted by the corporations [1]. Investment efficiency is an important factor leading to a corporation’s long-term sustainable development [2]. Under certain conditions, efficient investment can continuously increase corporate profits, thus promoting the company’s sustainable growth. On the contrary, investment mistakes and project failures will inevitably lead to declines in profitability, market share, and company value, and ultimately lead to a loss of sustainable growth opportunities. In this context, the disclosure of nonfinancial information is an important signal of corporate efforts to achieve sustainable development [3], and information that reflects the characteristics of supply chain transactions can be useful for investors and other stakeholders [4,5]. Although a growing body of literature contributes to our understanding of whether and how supply chain information affects firm performance and corporate strategic decisions [6,7,8], little attention has been paid to the impact of supply chain information disclosure on investment strategies.

Supply chain information encompasses important topics, such as corporate operations and future development [9]. The status of a firm’s customer base and the relationship with its suppliers are useful indicators for investors when assessing a firm’s operational risks. Supply chain information has an important impact on the information environment of the capital market. Disclosing such private and valuable information can provide clear signals to the market, even though some of this information may also benefit competitors [10]. In addition, supply chain information is closely related to the concept of upstream and downstream industries. For instance, an auditor’s or analyst’s knowledge of a firm’s supply chain information can help them obtain information about the firm’s operational status, thereby saving information collection costs, and can enable them to make more accurate judgments regarding the development and forecast of the firm’s industry [7,11]. Scholars have long argued that firms may not want to disclose their supply chain information due to the high proprietary cost and the possibility of exposing operational risks [12].

For a long time, Chinese-listed companies have been asked by regulators to improve the quality of their supply chain information disclosure in order to reduce the collection and transaction costs incurred by information asymmetries in the capital market. In 2001, the China Securities Regulatory Commission (CSRC) issued Document No. 2, which outlines standards for the content and format of the information disclosure of companies that offer securities to the public; this document requires public firms to disclose the total amount of purchases and sales of top suppliers and customers with purchase or sales ratios exceeding 50%. In 2006, Document No. 6 revised the guidelines regarding the disclosure of names of suppliers or customers in the prospectuses of listed companies. Subsequently, the 2012 revision of Document No. 2, described above, encouraged listed companies to disclose the names of their top five suppliers and customers, as well as the amounts of their purchases and sales, in their annual reports (Website of China Securities Regulatory Commission (CSRC) http://www.csrc.gov.cn/pub/newsite/) (accessed on 1 January 2023). The supply chain information of listed companies is categorized as voluntary disclosure information.

Scholars argue that the main factors that cause inefficiency of investment are information asymmetries and agency conflicts in the capital market [13,14,15,16]. On the one hand, the financial constraints introduced by information asymmetries are closely related to underinvestment problems. For example, information asymmetry between agents and shareholders within a company can easily lead to managers engaging in risk-averse activities, such as perk consumption [17] and foregoing investment opportunities with positive net present value (NPV) [18], resulting in corporate underinvestment. On the other hand, agency conflicts could lead to overinvestment problems within a company. For example, managers may invest in projects with negative NPV or engage in unnecessary investment practices contrary to shareholders’ interests [14]. Managers are often strongly motivated to make additional investments in inefficient investment projects because diversifying their investments can help reduce bankruptcy risk. Accordingly, this would result in corporate overinvestment [19,20]. A firm’s investment efficiency can be influenced by information disclosure related to stakeholders, such as the disclosure of information related to corporate social responsibility (CSR), ownership type, and creditor rights [21,22,23,24]. Despite the positive impact of supply chain information on improving the information environment of the capital market, the relevance of supply chain information disclosure in the context of corporate investment behavior remains largely unexplained. According to document 131 of the SFAS (statement of financial accounting standards), “an enterprise shall disclose its dependence on major customers. If the revenue from sales to customers reaches or exceeds 10%, the identity and sales proportion of the customer must be disclosed at the same time.”).

This study seeks to understand how supply chain information disclosure is related to investment efficiency. The results indicate that there is a positive association between voluntary supply chain disclosure and investment efficiency; firms that disclose their supply chain information can increase their investment efficiency and thereby decrease underinvestment. This positive relationship remains significant after controlling for firm characteristics and other observable corporate governance characteristics. This positive nexus is also robust to alternative measures of investment inefficiency and model specifications and endogeneity concerns. Moreover, in terms of heterogeneous effects, we find that the positive impact of supply chain information disclosure on underinvestment is more pronounced for non-SOEs and firms located in regions with a higher degree of marketization. Additionally, we further examine the mechanisms underlying the effect of supply chain information disclosure on investment inefficiency, indicating that voluntary supply chain disclosure increases a firm’s level of underinvestment efficiency by decreasing its financing constraints and agency costs. Our findings prove that supply chain information disclosure is an important factor in determining a firm’s long-term sustainable development.

Our research contributes to the literature in several ways. First, this study represents the first attempt to investigate the effect of corporate supply chain information disclosure on investment efficiency. Previous studies documented that the frequency of annual report-based risk disclosure [25], ownership type [21], creditor rights [23], and corporate social responsibility (CSR) [22,24] of a firm are significant determinants of its investment efficiency. Our study enriches the literature, showing that supply chain information disclosure is also a crucial determinant of investment efficiency. Second, our study contributes to the growing body of literature investigating the effects of supply chain management on corporate sustainable decision-making. The existing literature has investigated the impact of supply chain management on earnings management [26], the cost of capital [6], mergers and acquisitions [27,28], innovation [29,30], and profitability [8]. These studies analyzed supply chain management only from the perspective of customer concentration, while we analyzed it from the perspective of supply chain information disclosure, which is also an important factor of supply chain management. Third, our study emphasizes the importance of the nexus between nonfinancial information and investment efficiency. Previous research on nonfinancial information disclosure mainly focuses on environmental information disclosure [31,32], employee-related information disclosure [33], CSR disclosure [24,34,35], voluntary compensation-related disclosure [36], and corporate performance information disclosure. By digging into the mechanisms, we show that the supply chain information disclosure was found to affect corporate investment efficiency by reducing the firm’s financial constraints and agency costs. Our study focuses on another crucially important type of nonfinancial information, supply chain information, and we find that supply chain information disclosure also has a significant effect on a firm’s investment behavior.

The remainder of this paper is organized as follows. Section 2 presents the literature review and hypothesis development. Section 3 describes the data and introduces the variables. Section 4 presents the empirical results and discusses the findings. Section 5 concludes this paper.

2. Literature Review and Hypotheses Development

2.1. Literature Review

Supply chain information, which reflects a company’s long-term development and customer–supplier relationship, is a significant information collection for the investors’ and auditors’ decision-making [4,6,7]. It can help improve the quality of analysts’ forecasts [11] and optimize the information environment [37]. However, individual firms still encounter trade-offs when they make disclosure choices in the context of customer and supplier information. First, supply chain information disclosure has a positive externality in terms of competitors in the same industry, and it may help potential entrants find their own competitive prospects [38]. Through the learning effect, the information disclosed by peer firms can help reduce uncertainty about growth opportunities available to related firms, especially when a firm is affected by common demand and supply conditions [39]. Second, compared with other information, supply chain information disclosure comes with a higher proprietary cost. Customer purchasing power and supplier layout will affect the price strategy, operation and product design, and marketing and customer service activities, and then affect the cost structure and profits [26,28]. The presence of major customers and suppliers is conducive to maintaining supply chain stability; increasing the marginal revenue, asset turnover, and capital recovery of the enterprise and reducing management and advertising costs; furthermore, they can establish a stable supply chain relationship through exclusive investment [6,8,9]. However, proprietary investment is a sunk cost; once there is a risk of supply chain rupture, disclosure of supply chain information involves higher proprietary costs [12]. Third, disclosing supply chain information could expose operational risks of the firm, which could have a negative impact on its relationship with customers, suppliers, and partners and result in the loss of business opportunities [16,40]. Along the supply chain, since risk information primarily refers to negative news, firms might be unwilling to fully share supply chain information with their customers or suppliers privately if they are not obliged to do so.

In addition, the construction of an information disclosure system in China’s capital market has the same characteristics as that in other emerging market countries, which will require a long-term process for full and effective implementation. Although Chinese-listed firms are encouraged to disclose detailed information regarding supplier and customer performance, the vagueness of supply chain disclosure standards affects the quality of supply chain information. The role that supply chain information disclosure plays in firms’ decision-making efficiency is not clear. Therefore, combined with the basic situation of supply chain information of listed companies in China, it is of great benefit to explore the substantial impact of information disclosure behavior on firms’ investment decisions as the regulations evolve.

In an imperfect capital market, the information problem is a key driver of investment inefficiency, thereby information asymmetry in the investment decision-making process becomes a crucial factor that leads to adverse selection and moral hazards [15,41]. Information asymmetries between a company and its external investors can quickly cause financial constraints. Myers and Majluf [15] argue that firms usually pay more to obtain external financing than internal financing. Therefore, when firms with financial constraints make investment decisions, they are more likely to depend on their internal capital [42,43]. When a firm faces high financing costs when investing in a positive NPV project, it is more likely to encounter underinvestment problems [44]. Fazzari et al. [42] found that greater financing constraints are associated with higher investment–cash flow sensitivity. Recently, scholars have become more concerned with endogeneity problems. Some of them use the interest coverage ratio [45] and company size [46] as proxies for financing constraints [47,48] that extend the current research on corporate investment efficiency.

Agency theory suggests that self-interested managers tend to increase agency costs and may destroy shareholder value [41]. When seeking to meet their personal needs and accommodate their investment preferences, managers have an empire-building motive to invest in negative NPV projects or forfeit positive NPV projects due to risk aversion, resulting in overinvestment or underinvestment [14,19,49]. In these cases, firms may deviate from their optimal investment level and thus encounter problems related to investment inefficiency. Overall, the previous literature on this topic implies that severe financing constraints and agency conflicts caused by information asymmetries are the two main sources of friction related to investment efficiency. Namely, they always play mediating roles in transmitting the impact of information asymmetries on investment efficiency.

According to the discussion above, firms may be unwilling to disclose detailed information about their supply chain due to the externality with regard to other competitors in the same industry, the high proprietary cost, and the possibility of exposing operational risks. In that situation, companies will face more information asymmetry, leading to external financing difficulties. However, it is helpful for a firm to disclose nonfinancial information when it needs more external financing [21,50]. The extant literature suggests that the disclosure of customer information plays a fundamental role in strategic investment decisions by influencing the firm’s financial constraints [5,51,52] and reducing information asymmetry between a supplier and its creditors; this is consistent with the certification hypothesis [53,54,55]. Hence, firms with a concentrated customer base will have lower equity costs [6]. Therefore, the voluntary disclosure of supply chain information can mitigate the financial constraints of a firm, which could help reduce underinvestment.

From the perspective of agency conflict, it is possible that managers will consider the costs and benefits of supply chain information disclosure and decide whether to voluntarily disclose information or not. According to agency theory, managers and shareholders typically have incentives that are not aligned. Roychowdhury et al. [56] noted that managers may exploit their discretion to issue low-quality reports and engage in inefficient investments that allow them to pursue their own private interests as opposed to shareholders’ interests. Since disclosing supply chain information could result in high proprietary costs and business risks, self-interested managers do not have the incentive or the opportunity to engage in such behavior. Managers normally make information disclosure decisions to maximize their own interests and will conceal relevant supply chain information, which could damage the interests of the shareholders and lead to higher agency costs.

In other words, supply chain information disclosure can be used as an external governance mechanism to reduce information risk and agency costs. The disclosure of a firm’s major customers and suppliers has a spillover effect [6,7,11]. In a supply network, a company that exposes more information has an advantage over its business partners, which may contribute to decreasing the company’s agency costs. Some recent studies provide supportive evidence for this phenomenon. Crawford et al. [57] argued that it is more cost-effective for firms to communicate corporate information to a diverse set of customers through public channels than to engage in private communication with each customer. Firms can provide and obtain relevant information efficiently, which will allow them to protect themselves from business operating risks and decrease the cost of raising capital [6].

In particular, customers and suppliers can function as monitors and certifiers of supply chain stability. Major customers are strongly incentivized and can monitor their suppliers with the aim of stabilizing business relations with them [53,55]; such actions are good relationship investments that can benefit suppliers in highly competitive markets [52]. Corporate governance can provide a way to reduce the contracting costs encountered in customer–supplier relationships, partially alleviating the agency problem [58,59]. Thus, disclosing information to customers and suppliers improves governance and the monitoring of managers, which can help the shareholders of a company supervise the private investment behavior of its managers.

2.2. Hypotheses Development

According to the existing literature, for firms characterized as having concentrated customers or suppliers, investment inefficiency is manifested mainly as underinvestment. First, firms with a higher customer or supplier concentration are more likely to have higher business risk. Once major customers or suppliers fall into financial distress, the firms will lose large orders and the supply of raw materials, resulting in a sharp drop in sales revenue and a huge business crisis. Wang [60] argued that a firm could save more liquid assets and improve its overall financial flexibility to mitigate the negative effect of high financial distress costs produced by supply chain relationships. Risk aversion makes managers tend to be conservative in investment decisions, resulting in underinvestment [61]. Second, the uncertainty of the business environment caused by supply chain risk will increase the private costs of managers, such as the time cost of collecting information, the management cost of supervising project operations, and so on, which could lead them to give up some projects with positive net present value [62]. Third, the strong bargaining power of customers or suppliers can induce hold-up problems, sabotage firms’ business strategies, and result in underinvestment [29]. Major customers or suppliers will occupy the funds of the enterprise, affecting the accounts receivable and accounts payable, which will reduce the liquidity of the assets. However, free cash flow is an important source of investment decisions [49]. In that case, some projects with positive NPV will have to be abandoned, resulting in underinvestment. Prior studies have provided empirical evidence of underinvestment, especially concerning the effect of business risk and bargaining power (reflected in supply chain information) on managers’ investment decisions. We thus argue that disclosing supply chain information is more conducive to moderating underinvestment than reducing overinvestment.

Considering all of this information, the central question explored in this paper is whether the voluntary disclosure of supply chain information is a relevant determining factor of a firm’s investment efficiency. It could help companies mitigate their financing constraints and agency conflicts. The above discussion suggests that supply chain information disclosure plays a prominent role in investment decisions. Thus, firms that disclose supply chain information achieve a relatively higher level of investment efficiency. Our first hypothesis is as follows:

Hypothesis 1 (H1).

Supply chain information disclosure improves a firm’s investment efficiency, especially by reducing underinvestment.

For Chinese-listed firms, supply chain information disclosure can increase their transparency and have a positive impact on investment behavior. Chen et al. provide evidence that a firm’s investment efficiency is affected by its ownership type. State-owned enterprises (SOEs) are found to have more severe agency problems than non-SOEs, which leads to more investment distortions [21]. According to prior research on this topic, government ownership is associated with a lower quality of financial reporting and financial transparency [21,63,64,65]. These issues are likely to produce greater information asymmetry problems.

It has also been shown that firms with state ownership typically serve the interests of politicians; they have weak corporate governance and limited monitoring of management, and they do not effectively maximize shareholder wealth or efficiently allocate resources. In particular, for SOEs, these agency and information asymmetry problems are likely to distort firm investments, leading to investment inefficiency [65]. In the context of supply chain competition, natural politics gives SOEs substantial bargaining power. Non-SOEs might bear more risks related to financial distress and cash flow breaks in market competition. These firms pay more attention to the stability of their supply chain relationships, make a greater effort to transfer high-quality supply chain information to the capital market, and mitigate against underinvestment caused by financing constraints and entrusted agency problems. Thus, we expect that supply chain information disclosure has a different effect on the investment behavior of SOEs than non-SOEs. The above discussion leads to our second hypothesis:

Hypothesis 2 (H2).

The effect of supply chain information disclosure on underinvestment tends to be more evident for non-SOEs than SOEs.

According to the theory of new institutional economics, institution and market mechanisms play equally important roles in economic decisions and resource allocation. The marketization degree in China not only reflects the role of market mechanisms in the allocation of resources but also shows the perfection of the system in China’s economic growth [66].

First, the marketization degree affects the transparency of information. As the marketization process is improved, the role of the country’s administrative plan is reduced; consequently, more economic resources will be allocated by the market. As the liquidity of the factor market and the product market is enhanced, the investment-related decision-making of enterprises will depend more on the signal mechanisms, as reflected by prices in the market. Thus, the higher a region’s degree of marketization, the higher its information transparency [67]. The inefficient investment behaviors of firms can be corrected by reducing the information asymmetry and moral hazard risk through the provision of a better information environment. In contrast, more information asymmetries exist in areas with low levels of marketization; thus, it is very difficult for stakeholders, such as investors and creditors, to obtain supply chain information in these areas.

Second, the protection of property rights differs among the regions of China. Better protection and enforcement of property rights motivate more effective investment decisions by firms and are conducive to firms’ long-term development [68,69]. It can be seen that stable improvement of investment efficiency requires a good legal and property rights protection environment; investment efficiency decreases as the degree of government intervention becomes stronger.

Third, the financial constraints faced by enterprises vary with the different degrees of marketization among the regions of China. In areas with high levels of marketization, the capital market is more developed, channels for enterprises to obtain funds are more abundant, and there is less information asymmetry between enterprises and financial institutions. Therefore, regions with a relatively higher degree of marketization usually achieve better financial development and may be less likely to face problems related to financing constraints. To a certain extent, the marketization degree of a region can strengthen the correlation between supply chain information disclosure and the underinvestment of firms. These concepts motivate the third hypothesis:

Hypothesis 3 (H3).

The effect of supply chain information disclosure on underinvestment tends to be more evident in regions with a relatively higher degree of marketization.

3. Data and Models

3.1. Data

The sample of data was mainly retrieved from the China Stock Market and Accounting Research Database (CSMAR). We manually collected the related supply chain information of the observed listed companies from their financial statement annotations. The top five major customer and supplier information includes the data of ranking orders, names, and amounts of customers and suppliers. Our primary sample consisted of all listed firms on the Shanghai Stock Exchange (SHSE) and the Shenzhen Stock Exchange (SZSE) from 2008 to 2016. Following other researchers who have examined investment efficiency [49], this paper focused on the manufacturing industry. Financial companies and special treatment (ST) companies were excluded because of their industry and financial status. Companies that went public in the same year were also excluded. We also excluded observations for which financial information was missing. After the screening process, a final sample of 1687 firms with 9200 firm-year observations remained. The variables are winsorized at the top and bottom 1%.

3.2. Variables

3.2.1. Dependent Variable

The dependent variable is corporate investment efficiency (INVEFF). To measure investment efficiency, we followed Richardson [49] and Stoughton et al. [70], estimating each firm’s normal level of investment and calculating the deviation from the expected investment. In the model developed by Richardson [49], investment efficiency includes underinvestment and overinvestment, and the residual of the model’s regression is used to capture the firm’s deviation from expected levels of investment. Our dependent variable, ${INVEFF}_{i,t}$, is the absolute value of residuals; a high value reflects a high level of investment inefficiency. Specifically, if a firm’s residual is positive, it is categorized as overinvesting, ${Over\_Invest}_{i,t}$; if the residual is negative, it is categorized as underinvesting, $\mathrm{U}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{r}\_{Invest}_{i,t}$.

3.2.2. Explanatory Variables

To gauge the impact of the quality and availability of information, we used dummy variables to measure the disclosure of supply chain information, following the related literature [12,36]. The first measure, ${Disclosure1}_{i,t}$, takes a value of 1 if the examined company discloses the names of its top five suppliers or customers for the current year and a value of 0 otherwise. Since China’s commodity competition is characterized as a buyer’s market and the bargaining power of the customers is stronger than that of the suppliers, we also used another dummy, ${Disclosure2}_{i,t}$, to ensure robustness; this variable identifies whether a listed company discloses the names of its customers.

3.2.3. Mediating Variable

We hypothesis that supply chain information disclosure will increase corporate investment efficiency by reducing firms’ financial constraints and agency costs. Following Kaplan and Zingales [47], we used the KZindex to measure financial constraints. The greater the KZ score, the more severe a firm’s financial constraints. Following Huang et al. [71], we used the proportion of management expenses to total assets COST as a proxy for agency costs.

3.2.4. Control Variables

The control variables include a firm’s financial and governance characteristics, which are typically used as determinants of investment inefficiency [24]. A series of time-varying firm characteristics are controlled. According to previous literature, the proxy for firm size (Size) is the natural logarithm of total assets. As a proxy for profitability, ROA is measured as net profit scaled by total assets. Firm leverage (Lev) is measured as liabilities scaled by total assets and sales growth (Growth) is an annual rate. Firm liquidity (Cash) is the ratio of the firm’s cash and short-term investments scaled by its total assets. Firm age (Firmage) is the number of years the firm has been incorporated. Ownership structure (Top1) is the shareholding ratio of the largest shareholder. CEO duality (Dual) is a dummy variable, which equals 1 if the chairman is also the CEO, and 0 otherwise. We also controlled for industry and year-fixed effects.

3.3. Basic Empirical Model

To examine H1–H3, we employed an investment model following the work of Biddle et al. [16] and Liu and Tian [24], which is given as:

$${INVEFF}_{i,t}=\alpha +{\beta }_1{Disclosure}_{i,t}+{\beta }_2{Control}_{i,t}+Industry+Year+{ϵ}_{i,t}$$

(1)

$$\begin{gathered} {INVEFF}_{i,t}=\alpha +{\beta }_1{Disclosure}_{i,t}+{\beta }_2{Disclosure}_{i,t}\times {NonSOE}_{i,t}+{\beta }_3{NonSOE}_{i,t} \\ +{\beta }_4{Control}_{i,t}+Industry+Year+{ϵ}_{i,t} \end{gathered}$$

(2)

Equation (1) is run separately for underinvestment ($Under\_{Invest}_{i,t}$) and overinvestment (${Over\_Invest}_{i,t}$). This design allowed us to test whether supply chain disclosure mitigates both or is more conducive to alleviating one type of investment inefficiency. (For the residual of the model developed by Richardson [49], if the residual is negative, it is categorized as engaging in underinvestment. This paper takes the absolute value of Under_Invest to indicate the degree of underinvestment.) We would expect ${\beta }_1$ to be positive when the firm overinvests and negative when the firm underinvests.

To examine Hypothesis 2, we used SOE and NonSOE to measure a firm’s state ownership. NonSOE takes a value of 1 if the firm is not a state-owned enterprise, and 0 otherwise. The interaction term ${Disclosure}_{i,t}\times NonSOE$ captures the moderating effect of state ownership on the impact of supply chain information disclosure on investment inefficiency. If Hypothesis 2 is valid, then ${\beta }_2$ will be negative. For H3, following Fan et al. [66], we replace NonSOE with a province-level marketization index (MKTindex). If H3 is valid, then ${\beta }_2$ will be negative. In addition, control variables include firm size (${Size}_{i,t}$), return on assets (${ROA}_{i,t}$), leverage (${Lev}_{i,t}$), growth opportunities (${Grow}_{i,t}$), firm liquidity (${Cash}_{i,t}$), ownership structure (${Top1}_{i,t}$), firm age (${Firmage}_{i,t}$), and CEO duality (${Dual}_{i,t}$). All variable definitions are presented in detail in Appendix A.

Researchers have highlighted that non-financial information could enhance firm investment levels by helping firms address agency problems and information asymmetry problems. To quantify the mediating effects of supply chain information disclosure on investment decisions through financial constraints, we use the following equations to conduct a mediation analysis [22]:

$${INVEFF}_{i,t}={\alpha }_0+{\alpha }_1{Disclosure}_{i,t}+{\alpha }_2{Controls}_{i,t}+Industry+Year+{ϵ}_{i,t}$$

(3)

$${Mediator}_{i,t}={\gamma }_0+{\gamma }_1{Disclosure}_{i,t}+{\gamma }_2{Controls}_{i,t}+Industry+Year+{ϵ}_{i,t}$$

(4)

$${INVEFF}_{i,t}={\mu }_0+{\mu }_1{Disclosure}_{i,t}+{\mu }_2{Mediator}_{i,t}+{\mu }_3{Controls}_{i,t}+Industry+Year+{ϵ}_{i,t}$$

(5)

where ${Mediator}_{i,t}$ represents the mediating variable. The mediating variables are KZindex and COST. Controls refer to the control variables. The effects of industry and year are also controlled.

3.4. Descriptive Statistics

Table 1. Descriptive statistics of the main variables used in the regression analysis, including investment efficiency measures, proxies for supply chain information, and control variables.

Descriptive Statistics
Variable	Mean	Sd	Min	P50	Max	N
INVEFF	0.041	0.181	0.000	0.028	11.550	9200
Over_Invest	0.048	0.049	0.000	0.033	0.489	4155
Under_Invest	0.036	0.240	0.000	0.025	11.550	5045
Disclosure1	0.397	0.489	0.000	0.000	1.000	9200
Disclosure2	0.379	0.485	0.000	0.000	1.000	9200
Size	21.791	1.177	19.114	21.671	25.655	9200
ROA	0.031	0.066	−0.258	0.030	0.202	9200
Lev	0.454	0.213	0.051	0.448	0.990	9200
Grow	0.276	1.107	−0.796	0.084	11.771	9200
Cash	0.172	0.120	0.007	0.141	0.645	9200
Firmage	14.974	4.834	4.000	15.000	30.000	9200
Top1	0.346	0.145	0.024	0.329	0.900	9200
Dual	0.234	0.423	0.000	0.000	1.000	9200

shows the descriptive statistics. Over the sample period, the mean of supply chain information disclosure ${Disclosure1}_{i,t}$ and ${Disclosure2}_{i,t}$ is 39.7 and 37.9%, respectively. This indicates that approximately 39.7% of the listed firms examined disclosed the names of their top five suppliers or customers, and 37.9% of firms disclosed the names of their customers; the corresponding standard deviations are 48.9 and 48.5%, respectively. On the one hand, we can infer that the level of information disclosure of the supply chain in China needs to be improved, and on the other hand, it is clear that the amount of attention being paid to the disclosure of customer and supplier information has increased. Regarding investment efficiency measures, ${INVEFF}_{i,t}$ has a mean of 0.041, a minimum of 0, and a maximum of 11.55; this suggests that there are substantial differences among the levels of inefficient investment of the examined listed firms. The mean of overinvestment $Over\_{Invest}_{i,t}$ is about 0.048, while the mean of firm underinvestment $Under\_{Invest}_{i,t}$ is about 0.036. The average firm size is 21.791. The average (median) ${ROA}_{i,t}$ is 3.1% (3.0%), while the average (median) ${Lev}_{i,t}$ is 45.4% (44.8%, with a standard deviation of 0.213); this indicates that the examined firms have high levels of leverage. The average of ${Grow}_{i,t}$ is 27.6%, and the average of ${Cash}_{i,t}$ is 17.2%. In addition, the average ${Firmage}_{i,t}$ among the listed companies is 14.974 years and the average ${Top1}_{i,t}$ is 34.6%. CEO duality, denoted by ${Dual}_{i,t}$, has an average value of 0.234.

4. Empirical Results

4.1. Main Results

4.1.1. Supply Chain Information Disclosure and Investment Efficiency

Table 2. The effect of supply chain information disclosure on investment efficiency. The dependent variable in regressions (1) and (2) is investment inefficiency (INVEFF), in regressions (3) and (4) it is overinvestment (Over_Invest), and in regressions (5) and (6) it is underinvestment (Under_Invest). The Independent variable in these regressions is Disclosure. Definitions of all variables are in Appendix A. All standard errors (in parentheses) are clustered at the firm level. ***, **, and * denote significance at the 1%, 5%, and 10% level, respectively.

Dependent Variable	INVEFF		Over_Invest		Under_Invest
	(1)	(2)	(3)	(4)	(5)	(6)
Disclosure1	−0.009 *		−0.001		−0.014 **
	(−2.261)		(−0.482)		(−1.972)
Disclosure2		−0.010 **		−0.002		−0.014 *
		(−2.350)		(−1.055)		(−1.891)
Size	−0.013 ***	−0.013 ***	0.000	0.000	−0.020 ***	−0.020 ***
	(−6.991)	(−6.995)	(0.462)	(0.413)	(−6.434)	(−6.422)
ROA	0.263 ***	0.263 ***	0.018	0.018	0.371 ***	0.371 ***
	(7.915)	(7.917)	(1.167)	(1.167)	(6.717)	(6.721)
Lev	0.114 ***	0.114 ***	0.002	0.002	0.178 ***	0.178 ***
	(10.066)	(10.085)	(0.310)	(0.369)	(9.469)	(9.466)
Grow	0.013 ***	0.013 ***	0.001	0.001	0.023 ***	0.023 ***
	(7.817)	(7.822)	(1.088)	(1.091)	(7.850)	(7.858)
Cash	0.083 ***	0.083 ***	−0.032 ***	−0.032 ***	0.156 ***	0.155 ***
	(4.840)	(4.839)	(−4.284)	(−4.265)	(5.358)	(5.343)
Firmage	0.000	0.000	−0.000	−0.000	0.001	0.001
	(1.048)	(1.060)	(−1.624)	(−1.589)	(1.429)	(1.445)
Top1	−0.021	−0.021	−0.002	−0.002	−0.028	−0.028
	(−1.574)	(−1.557)	(−0.355)	(−0.314)	(−1.181)	(−1.170)
Dual	0.003	0.003	0.005 ***	0.005 ***	0.003	0.003
	(0.677)	(0.672)	(3.045)	(3.028)	(0.344)	(0.339)
Cons	0.246 ***	0.246 ***	0.051 ***	0.052 ***	0.342 ***	0.341 ***
	(6.424)	(6.425)	(2.958)	(3.003)	(5.319)	(5.305)
Year	Yes	Yes	Yes	Yes	Yes	Yes
Industry	Yes	Yes	Yes	Yes	Yes	Yes
Firm	Yes	Yes	Yes	Yes	Yes	Yes
N	9200	9200	4155	4155	5045	5045
Adj.R2	0.028	0.028	0.022	0.022	0.046	0.045
F-test	13.761	13.783	4.879	4.927	12.624	12.607

presents the results of the ordinary least squares (OLS) model estimated using Model (1). Columns 1 and 2 show the effect of supply chain information disclosure on investment inefficiency. The coefficient estimates of Disclosure1 and Disclosure2 are −0.009 and −0.010, respectively, and both are significant at the 5% level. The coefficients of the variables denoting supply chain information disclosure indicate that after controlling for several other determinants of investment efficiency, firms that disclose their supply chain information have higher investment efficiency than firms that do not. Regarding the control variables, the results show that investment inefficiency is negatively related to firm size and positively related to the return on assets, leverage, growth opportunities, and cash holdings of a firm. These estimates are consistent with the results of previous studies on this topic, except that we did not find that firm age, the equity ratio of the largest shareholder, or CEO duality was significant.

Then, we partition the total sample into overinvestment and underinvestment subsamples. In columns 3 and 4, overinvestment (Over_Invest) is used as the dependent variable, and columns 5 and 6 follow the same pattern but use underinvestment (Under_Invest) as the dependent variable. Columns 3 and 4 in Table 2 show the regression of supply chain information disclosure on overinvestment. The coefficients of Disclosure1 and Disclosure2 are −0.001 (column 3) and −0.002 (column 4), but they are not statistically significant. In the overinvestment subsample, the coefficients of Disclosure1 and $Disclosure2$ are statistically significant and negative. The results provide evidence that supply chain disclosure is more conducive to moderating underinvestment than reducing overinvestment. These results regarding the negative relationship between supply chain information disclosure and investment inefficiency support Hypothesis 1.

4.1.2. The Effect of Supply Chain Information disclosure on Investment Efficiency for SOEs and Non-SOEs

As mentioned in Section 2.2, the effect of supply chain information disclosure on investment efficiency varies based on the firm’s ownership type. We expect that the effect of supply chain information disclosure on investment inefficiency would tend to be more evident for non-SOEs than SOEs.

Table 3. Estimation results regarding the impact of firm type on the association between supply chain information disclosure and underinvestment. The primary variable of interest is interaction term $Disclosure\times nonSOE$, where nonSOE takes a value of 1 if a firm is not an SOE and 0 otherwise. The dependent variable in regressions is underinvestment (Under_Invest), and the independent variable is disclosure. Definitions of all variables are in Appendix A. All standard errors (in parentheses) are clustered at the firm level. ***, **, and * denote significance at the 1%, 5%, and 10% level, respectively.

Dependent Variable	Under_Invest
	(1)	(2)
Disclosure1	0.000
	(0.714)
Disclosure2		0.000
		(0.406)
Disclosure1×Nonsoe	−0.002 **
	(−2.429)
Disclosure2×Nonsoe		−0.002 *
		(−1.920)
Nonsoe	0.002 *	0.002 ***
	(4.354)	(4.060)
Size	0.002 ***	0.002 ***
	(10.281)	(10.304)
ROA	−0.021 ***	−0.021 ***
	(−5.797)	(−5.791)
Lev	0.011 ***	0.011 ***
	(9.381)	(9.377)
Grow	0.000 **	0.000 **
	(2.042)	(2.034)
Cash	0.008 ***	0.008 ***
	(4.991)	(4.993)
Firmage	−0.001 ***	−0.001 ***
	(−14.538)	(−14.519)
Top1	0.001	0.001
	(0.435)	(0.436)
Dual	0.000	0.000
	(0.095)	(0.113)
Cons	−0.013 ***	−0.013 ***
	(−3.268)	(−3.270)
Year	Yes	Yes
Industry	Yes	Yes
Firm	Yes	Yes
N	5045	5045
Adj.R2	0.170	0.170
F-test	44.032	43.951

presents the estimates and test results for firms with different ownership types, given by Equation (2). In columns 1 and 2, we can see that the interaction term $Disclosure\times nonSOE$ is negative and statistically significant at the 1% level. This result is consistent with previous studies, indicating that firms with state ownership are more likely to encounter agency problems and information asymmetry [21]. The coefficients of the interaction terms indicate that the effect of supply chain information disclosure on underinvestment tends to be more evident for non-SOEs than SOEs. The results support Hypothesis 2.

4.1.3. The Impact of the Degree of Marketization on Supply Chain Information Disclosure and Investment Efficiency

Since firms with a lower degree of marketization have more information asymmetry and higher moral hazard risk, as well as a poorer legal and property rights protection environment, we expect that the impact of supply chain information disclosure on investment efficiency would differ based on the firm’s institutional environment. We divide the whole sample according to the median value of the province-level marketization index (MKTindex), which is produced by the NERI [66] and includes the interaction term Disclosure × MKTindex. As shown in

Table 4. Estimation results regarding firm type on the association between supply chain information disclosure and underinvestment. The primary variable of interest is the interaction term Disclosure × MKTindex, where MKTindex is the province-level marketization index produced by NERI [66]. The dependent variable in regressions is underinvestment (Under_Invest) and the independent is disclosure. Definitions of all variables are in Appendix A. All standard errors (in parentheses) are clustered at the firm level. ***, **, and * denote significance at the 1%, 5%, and 10% level, respectively.

Dependent Variable	Under_Invest
	(1)	(2)
Disclosure1	0.007
	(0.788)
Disclosure2		0.008
		(0.843)
Disclosure1×MKTindex	−0.031 **
	(−2.471)
Disclosure2×MKTindex		−0.033 ***
		(−2.671)
MKT	0.018 *	0.019 *
	(1.680)	(1.746)
Size	−0.005 *	−0.005 *
	(−1.833)	(−1.842)
ROA	0.661 ***	0.661 ***
	(13.434)	(13.444)
Lev	0.133 ***	0.133 ***
	(8.047)	(8.058)
Grow	0.008 ***	0.008 ***
	(3.267)	(3.277)
Cash	0.190 ***	0.190 ***
	(7.467)	(7.437)
Firmage	0.001	0.001
	(1.063)	(1.096)
Top1	0.025	0.026
	(1.181)	(1.219)
Dual	−0.005	−0.005
	(−0.734)	(−0.749)
Cons	0.104	0.103
	(1.475)	(1.469)
Year	Yes	Yes
Industry	Yes	Yes
Firm	Yes	Yes
N	5045	5045
Adj.R2	0.270	0.270
F-test	74.319	74.395

, the coefficients for Disclosure × MKTindex are significant and negative for both supply chain information disclosure measures. These results indicate that firms in regions with a higher degree of marketization usually have higher levels of financial development with fewer financing constraints; this is conducive to the firm’s ability to optimally allocate resources and effectively invest. Thus, Hypothesis 3 is supported. Overall, the main results suggest that supply chain information disclosure improves the level of investment efficiency.

4.2. Endogeneity Issues

The above empirical results imply that supply chain information disclosure improves investment efficiency in China. However, some omitted or unobservable variables might be associated with supply chain information disclosure and investment efficiency; for example, firms with high-level investment efficiency may be more willing to disclose detailed information on large customers and suppliers. It is possible that the endogenous problem from our earlier OLS regression results remains.

4.2.1. Instrumental Variable (IV) Approach

To address the potential problems raised by omitted or unobservable variables and other endogeneity issues, we use an IV approach. We use the average level of supply chain information disclosure within an industry during the previous year, denoted by the variables Indu_Disclosure1 and Indu_Disclosure2, as the instrumental variable $Indu\_Disclosure$ is the number of companies that disclosed supply chain information within an industry during the previous year divided by the total number of listed companies in that industry during the previous year. There is evidence that the disclosure behavior of a firm is largely affected by the standards of its industry; therefore, these instruments are highly correlated with the independent variable and are likely to affect the firm’s investment decision variable only through their effects on the disclosure measure.

Table 5. Estimation results of the instrumental variable approach. $Indu\_Disclosure1$ and $Indu\_Disclosure2$, as instrumental variables, denote the average level of supply chain information disclosure within each industry during the previous year. Columns 1 and 2 show the results of first-stage regressions, and columns 3 and 4 report the results of second-stage regressions. All standard errors (in parentheses) are clustered at the firm level. ***, **, and * denote significance at the 1%, 5%, and 10% level, respectively.

Dependent Variable	Pre_Disclosure1	Pre_Disclosure2	Under_Invest
	(1)	(2)	(3)	(4)
Pre_Disclosure1			−0.047 **
			(−2.372)
Pre_Disclosure2				−0.047 **
				(−2.350)
Indu_Disclosure1	2.498 ***
	(3.302)
Indu_Disclosure2		2.488 ***
		(3.256)
Size	−0.095 ***	−0.090 ***	−0.004 **	−0.004 **
	(−5.363)	(−5.076)	(−2.280)	(−2.307)
ROA	−0.675 **	−0.661 **	0.021 **	0.020 *
	(−2.180)	(−2.123)	(1.965)	(1.915)
Lev	0.375 ***	0.385 ***	0.023 ***	0.022 ***
	(3.585)	(3.662)	(2.838)	(2.810)
Grow	0.004	0.009	0.000	0.000
	(0.217)	(0.525)	(0.420)	(0.503)
Cash	−0.284 *	−0.386 **	0.023 ***	0.020 ***
	(−1.742)	(−2.345)	(2.951)	(2.601)
Firmage	−0.003	−0.001	−0.010 *	−0.011 *
	(−0.730)	(−0.147)	(−1.751)	(−1.783)
Top1	−0.081	−0.029	−0.007	−0.006
	(−0.598)	(−0.213)	(−0.725)	(−0.622)
Dual	−0.090 *	−0.105 **	−0.001	−0.002
	(−1.929)	(−2.228)	(−0.378)	(−0.854)
Cons	0.454	0.322
	(1.205)	(0.848)
Year and industry	Yes	Yes	Yes	Yes
Firm	Yes	Yes	Yes	Yes
N	5045	5045	2827	2827
R2			0.466	0.161
F-test			12.851	15.952
Anderson canon. corr. LM statistic			24.422	24.331
p-value			0.017	0.018
Cragg–Donald Wald F statistic			39.769	105.991
p-value			0.000	0.000
Sargan statistic			0.859	0.897

shows the regression results for the IV Indu_Disclosure. Columns 1 and 2 show the first-stage regression results, and we find that our variable Indu_Disclosure is positive and significant at the 1% level. Columns 3 and 4 show that the coefficient estimates of the instrumented variable Pre_Disclosure are negative and significant.

4.2.2. The Difference-In-Differences (DID) Analysis

Since omitted variables could bias our main findings, we carry out a DID analysis to alleviate the endogeneity concern. Specifically, listed firms that disclose customer information during a specific year usually choose to do so in the following years as well. Therefore, a regression design similar to a DID can be carried out, as shown in Model (2). ${Treat}_{i,t}$ takes a value of 1 if a firm has disclosed the names of its customers or suppliers; otherwise, it takes a value of 0. ${Disclosure\_Post}_{i,t}$ indicates the years before and after the supply chain information disclosure, taking values of 0 and 1, respectively.

Table 6. Regression results from difference-in-differences (DID) and propensity score matching (PSM) procedures. Treat takes a value of 1 if a firm discloses the names of customers or suppliers; otherwise, it takes a value of 0. Disclosure_Post indicates the years before and after the firm’s supply chain information disclosure, taking values of 0 and 1, respectively. Columns 1 and 2 show DID regression results corresponding to firms that voluntarily disclose the names of customers and suppliers. Regression analysis using PSM samples is presented in columns 3 and 4. ***, **, and * denote significance at the 1%, 5%, and 10% level, respectively.

Dependent Variable	Under_Invest
	(1)	(2)	(3)	(4)
Treat1	0.007
	(0.663)
Disclosure1_Post	−0.027 **
	(−2.121)
Treat2		0.007
		(0.740)
Disclosure2_Post		−0.030 **
		(−2.338)
Disclosure1			−0.022 **
			(−2.042)
Disclosure2				−0.021 *
				(−1.882)
Size	−0.006 **	−0.006 **	−0.030 ***	−0.017 ***
	(−2.027)	(−2.027)	(−6.038)	(−3.171)
ROA	0.659 ***	0.659 ***	0.574 ***	0.680 ***
	(13.400)	(13.404)	(6.779)	(7.806)
Lev	0.133 ***	0.133 ***	0.245 ***	0.240 ***
	(8.057)	(8.070)	(8.580)	(8.231)
Grow	0.008 ***	0.008 ***	0.033 ***	0.025 ***
	(3.250)	(3.261)	(7.591)	(5.788)
Cash	0.166 ***	0.166 ***	0.244 ***	0.201 ***
	(6.062)	(6.062)	(5.235)	(4.257)
Firmage	0.190 ***	0.189 ***	0.002	0.001
	(7.459)	(7.437)	(1.335)	(1.099)
TOP1	0.001	0.001	−0.054	−0.015
	(1.058)	(1.092)	(−1.425)	(−0.393)
Dual	0.025	0.025	0.007	0.007
	(1.164)	(1.186)	(0.526)	(0.540)
Cons	0.084	0.083	0.489 ***	0.185
	(1.412)	(1.404)	(4.733)	(1.627)
Year	Yes	Yes	Yes	Yes
Industry	Yes	Yes	Yes	Yes
Firm	Yes	Yes	Yes	Yes
N	5045	5045	3167	3071
R2	0.270	0.270	0.068	0.082
F-test	84.361	84.444	12.041	13.705

shows the regression results of Equation (3). Our variable of interest is ${Disclosure\_Post}_{i,t}$. Column 1 shows that the coefficient of ${Disclosure1\_Post}_{i,t}$ is significantly negative, indicating that the disclosure of supply chain information reduces the investment efficiency of firms. Similar results were found regarding the disclosure of customer information, shown in column 2; the coefficient of ${Disclosure2\_Post}_{i,t}$ is also significantly negative. These DID results further alleviate concerns regarding endogeneity and support our main hypothesis.

4.2.3. Propensity Score Matching (PSM) Procedure

However, there is a possibility that firms with certain characteristics will have a relatively greater tendency to disclose customer information and are thus more likely to avoid inefficient investment decisions. Therefore, we attempted to alleviate these concerns by using the propensity score matching (PSM) procedure.

Following previous studies on this topic [16,24], we include the following firm-specific characteristics that determine investment efficiency: firm size (Size), firm performance (ROA), leverage (Lev), cash holdings (Cash), and firm age (Firmage), as well as corporate governance characteristics measured by ownership structure (Top1) and CEO duality (Dual). Using the PSM procedure, we match a group of firms that disclosed their supply chain information (treatment group) with a group of firms that did not (control group), according to the principle of 1:1 proximity matching. After matching these firms and calculating the propensity matching score, we find that there are no significant differences between firm-level characteristics in the treatment and control groups, indicating that our model is correctly specified. The results of the regression analysis using the PSM samples are presented in columns 3 and 4 of Table 6. These columns show that Disclosure1 and Disclosure2 are negatively correlated with $Under\_Invest$ at the 5% and 10% level, respectively; these variables have coefficients of −0.022 and −0.021. Therefore, the results of the PSM procedure verify that the disclosure of supply chain information restrains the inefficient investment behavior of firms. Overall, these results are consistent with the idea that supply chain information disclosure reduces underinvestment.

4.3. Mechanism Analysis

4.3.1. Does Supply Chain Information Disclosure Reduce the Financial Constraints?

In this section, we further examine the mechanisms underlying the effect of supply chain information disclosure on investment inefficiency. Notably, information disclosure is closely related to the investment efficiency of listed companies. Biddle et al. [16] find that companies with low information disclosure quality tend to underinvest when facing financing constraints. As stated in Section 2.2, investment decisions generally require stable financing channels, as these decisions involve both increased firm-specific internal capital and decreased external financing costs. Therefore, financing constraints restrict investment productivity [15,42,43]. In addition, the number of corporate financing constraints reflects the company’s risk of information asymmetry. If a company discloses operation-related information in a timely manner, investors will be able to learn more about the development of the company’s supply chain competitiveness, which reduces the risk of information asymmetry [40]. It has been proven that supply chain information transmits signals, as it reflects a firm’s cash flow and credit risk; this profoundly affects the terms, scale, and cost of financing and alleviates the financing constraints introduced by information asymmetry [5,6,51,52]. Following this argument, we examined whether firms’ supply chain information disclosure affects their investment efficiency by reducing financial constraints. If supply chain information is a valuable asset, it would be able to relieve a firm’s financial constraints. We perform the first step of the analysis (Equation (3)) by establishing the significant effects of supply chain information disclosure on underinvestment (Table 2). Then, the results of the second step (Equation (4)) were used to investigate whether supply chain information disclosure significantly affects a firm’s financial constraints. In the final step, the KZ score is included in the regression of supply chain information disclosure on investment inefficiency (Equation (5)). The main variable of interest in this analysis is the reduction in the effect of supply chain information disclosure on underinvestment.

The regression results of the mechanism test are presented in

Table 7. Regression results of the mechanism analysis used to identify differential mechanisms of the impact of supply chain information disclosure on underinvestment. Panel A: Indirect effects of supply chain information disclosure on investment decisions through financial constraints. Panel B: Indirect effects of supply chain information disclosure on investment decisions through agency conflicts. Definitions of all variables are in Appendix A. All standard errors (in parentheses) are clustered at the firm level. ***, **, and * denote significance at the 1%, 5%, and 10% level, respectively.

Panel A: Supply Chain Information Disclosure, Financial Constraints, and Under-Investment
	Under_Invest	Kzindex	Under_Invest	Under_Invest	Kzindex	Under_Invest
	(1)	(2)	(3)	(4)	(5)	(6)
Disclosure1	−0.014 **	−0.192 ***	−0.003 **
	(−1.972)	(−5.678)	(−2.174)
Disclosure2				−0.014 *	−0.184 ***	−0.003 **
				(−1.891)	(−5.393)	(−2.001)
Kzindex			0.083 ***			0.083 ***
			(12.409)			(12.424)
Cons	0.342 ***	0.357 ***	1.736 ***	0.341 ***	0.354 ***	1.738 ***
	(5.319)	(3.550)	(13.063)	(5.305)	(3.516)	(13.076)
Year	Yes	Yes	Yes	Yes	Yes	Yes
Industry	Yes	Yes	Yes	Yes	Yes	Yes
Firm	Yes	Yes	Yes	Yes	Yes	Yes
N	5045	5045	5045	5045	5045	5045
R2	0.046	0.286	0.100	0.045	0.286	0.100
F	12.624	112.045	28.022	12.607	111.801	27.982
Sobel Z(p-value)			2.997 (0.000)			2.987 (0.000)
Panel B: Supply Chain Information Disclosure, Agency Conflicts, and Under-Investment
	Under_Invest	COST	Under_Invest	Under_Invest	COST	Under_Invest
	(1)	(2)	(3)	(4)	(5)	(6)
Disclosure1	−0.014 **	−0.022 ***	−0.003 **
	(−1.972)	(−2.664)	(−2.286)
Disclosure2				−0.014 *	−0.022 ***	−0.003 **
				(−1.891)	(−2.685)	(−2.065)
COST			0.030 ***			0.030 ***
			(13.638)			(13.644)
Cons	0.342 ***	1.119 ***	0.057 ***	0.341 ***	1.118 ***	0.056 ***
	(5.319)	(15.107)	(4.886)	(5.305)	(15.103)	(4.856)
Year	Yes	Yes	Yes	Yes	Yes	Yes
Industry	Yes	Yes	Yes	Yes	Yes	Yes
Firm	Yes	Yes	Yes	Yes	Yes	Yes
N	5045	5045	5045	5045	5045	5045
R2	0.046	0.101	0.105	0.045	0.101	0.104
F	12.624	29.712	34.530	12.607	29.718	34.467
Sobel Z(p-value)			3.037 (0.000)			2.919 (0.000)

, Panel A. The effect of supply chain information disclosure on firm underinvestment is given in columns 1 and 4. The results of Model 5 are reported in columns 2 and 5 of Table 5. The coefficient estimates of Disclosure1 and Disclosure2 are −0.192 and −0.184, respectively, and both are significant at the 1% level; this indicates that, ceteris paribus, firms that disclose supply chain information have approximately 19% fewer financial constraints than those that do not. Additionally, significant channeling effects can be found in columns 3 and 6. Furthermore, the coefficient for the effect of the KZindex on investment inefficiency is positive and significant. The results of the Sobel test examining the mediating effect is significant, which suggests that a firm’s supply chain information disclosure can reduce corporate underinvestment caused by financial constraints.

4.3.2. Does Supply Chain Information Disclosure Alleviate Agency Conflicts Efficiently?

In the previous section, we argued that supply chain information disclosure may help firms mitigate against the agency conflicts that occur between managers and shareholders, thereby easing investment inefficiency. Then, we examined whether supply chain information disclosure alleviates agency conflicts.

Due to the existence of the principal–agent problem, managers have short decision horizons [72]. Thus, self-interested managers make investment decisions at the expense of company prospects, and this increases agency costs and destroys shareholder value [14,19]. However, the supply chain information of listed companies could facilitate information flow and function as a form of corporate governance, leading to long-term certification [52,58]. In addition, executives in related upstream and downstream industries are well-suited to reducing the information gaps that exist in supply chain relationships [73]. We predicted that supply chain information disclosure will decrease agency costs. Following Huang et al. [71], we used the proportion of management expenses to total assets cost as a proxy for agency cost.

Table 7, panel B, reports the OLS regression results of the mechanism analysis. As shown in columns 1 and 4, Disclosure is positively associated with the measure of investment inefficiency Under_Invest. Similarly, columns 2 and 5 in Table 6 show that the coefficient estimate of both Disclosure1 and Disclosure2 is −0.022, which is significant at the 1% level; this indicates that an increase in the quality of supply chain information disclosure will decrease a firm’s agency cost ratio. These results show that the disclosure of supply chain information enhances a firm’s ability to overcome challenges related to inefficient investment by alleviating agency conflicts.

4.4. Robustness Tests

4.4.1. Alternative Investment Efficiency Model Specifications

To verify that supply chain information disclosure affects corporate investment behavior, we examined whether our primary results were robust by applying alternative measures and modifying the sample’s composition. Following Biddle et al. [16], we reexamined our results by employing alternative estimation models of investment. The results are reported in

Table 8. Robustness tests of the effect of supply chain information disclosure on underinvestment. Panel A: Alternative methods used to identify investment efficiency. Following Biddle et al. [16], we reexamined the results by employing alternative estimation models of investment efficiency. Panel B: Alternative methods used to identify supply chain information disclosure. We used $Disclosure\_score$ as the dependent variable, which is calculated by weighing the importance of customers and suppliers. Panel C: Results obtained by including additional control variables ***, **, and * denote significance at the 1%, 5%, and 10% level, respectively.

Panel A: Alternative Methods of Identifying Investment Efficiency
	Under_Invest_R
	(1)	(2)
Disclosure1	−0.001 **
	(−2.115)
Disclosure2		−0.001 **
		(−2.050)
Control	Yes	Yes
Year	Yes	Yes
Industry	Yes	Yes
N	5045	5045
R2	0.124	0.123
F-test	37.265	37.249
Panel B: Alternative Methods of Identifying Supply Chain Information Disclosure
	Under_Invest
	(1)	(2)
Disclosure_score1	−0.001 **
	(−2.167)
Disclosure_score2		−0.001 **
		(−2.233)
Control	Yes	Yes
Year	Yes	Yes
Industry	Yes	Yes
N	5045	5045
R2	0.109	0.109
F-test	32.468	32.486
Panel C: Additional Control Variables
	Under_Invest
	(1)	(2)
Disclosure1	−0.013 *
	(−1.793)
Disclosure2		−0.012 *
		(−1.696)
Control	Yes	Yes
Year	Yes	Yes
Firm	Yes	Yes
N	5045	5045
R2	0.062	0.062
F-test	14.483	14.467

, panel A, showing the connection between supply chain information disclosure and underinvestment using alternative inefficiency measures. As shown in columns 1 and 2, the coefficients of Disclosure1 and Disclosure2 coefficients are significantly negative, indicating that supply chain information disclosure is associated with better investment efficiency.

4.4.2. An Alternative Proxy for Identifying Supply Chain Information Disclosure

We also use an alternative proxy for identifying supply chain information disclosure. When disclosing its supply chain information, a company will also disclose the ranking order of its top five customers or suppliers. We reexamined our results by employing the alternative proxies Disclosure1_score and Disclosure2_score, which were obtained by considering the individual ranks of a firm’s customers or suppliers. (To be specific, each firm receives a score based on the rank of its top five customers or suppliers and is then assigned a score as follows: 0.9 for the disclosure of its largest customer or supplier; 0.7 for the disclosure of its second-largest customer or supplier; 0.5 for the disclosure of its third-largest customer or supplier; 0.3 for the disclosure of its fourth-largest customer or supplier; and 0.1 for the disclosure of its fifth-largest customer or supplier. A listed firm with no supply chain disclosures receives a score of zero. Thus, we obtain supply chain information disclosure scores corresponding to a number of dimensions of the sampled firms.) Table 8, panel B, shows that there is a significant relationship between supply chain information disclosure and investment inefficiency. Our mean results do not change, and all estimated coefficients of the measures of supply chain information disclosure are negative, suggesting that supply chain information disclosure matters in the context of effective governance.

4.4.3. Additional Control Variables

Additional variables representing the characteristics of corporate governance were included to ensure the robustness of our results. Following prior studies on this topic [16,24,58], we argue that the corporate governance mechanism is closely related to investment efficiency. The corporate governance variables used were Boardsize, which denotes the total number of board seats in a firm, and Independence, which represents the proportion of independent directors on the board. The results of this robustness test are presented in Table 8, panel C. Overall, the main results are not affected by the inclusion of these additional control variables.

5. Conclusions

5.1. Major Findings

One of the manifestations of sustainable development of enterprises is the achievement of high-level investment efficiency. Supply chain information connects the whole supply chain network, and firms with relatively higher-quality supply chain information disclosure can transmit information and allocate resources more effectively when making investment decisions. The characteristics of a firm’s supply chain information transmission should include not only vertical upstream and downstream communication but also horizontal transmission to potential investors in the capital market. Thus, it is important to identify how the disclosure of customer and supplier information affects a firm’s ability to make efficient investments.

This paper suggests that supply chain information disclosure plays an important role in investment decisions. We empirically document that supply chain information disclosure is negatively associated with investment inefficiency and is more conducive to moderating underinvestment than reducing overinvestment. The effect of supply chain information disclosure on investment inefficiency tends to be more evident for non-SOEs. This supports our hypothesis that the firm’s ownership type has a moderating effect on supply chain information disclosure and investment efficiency. Considering the financial distress risks and cash flow breaks inherent in market competition, non-SOEs might make more of an effort than SOEs to transmit high-quality supply chain information to the capital market, thus decreasing the occurrence of inefficient investments. We also find that the impact of supply chain information disclosure on investment inefficiency is more pronounced for firms in regions with higher degrees of marketization. Such firms usually benefit from information transparency, the protection of property rights, and financial development, as these factors are conducive to enabling them to optimally allocate their resources and make effective investments. Our findings prove that the institutional environment also acts as a mediator between supply chain information and investment efficiency.

In addition, we document that firms disclosing supply chain information can decrease their level of corporate investment inefficiency by reducing their financial constraints, and they can overcome challenges related to inefficient investments by alleviating their agency costs. We also verify the effect of supply chain information disclosure on firm investment inefficiency through various robustness tests, such as employing alternative investment efficiency model specifications, utilizing alternative methods of identifying supply chain information disclosure, and including additional control variables.

5.2. Policy Recommendations

At present, China’s listed companies are facing problems, such as insufficient supply chain information disclosure and difficulties in information identification. It is urgent to improve the supply chain information disclosure system and to increase investors’ abilities to identify information. To some extent, this study has some important implications for firms and policymakers in terms of highlighting the importance of supply chain information disclosure in the context of firm investment activities.

Standardizing the disclosure of supply chain information will help the market regulators become more sensitive to the specific situation of listed companies, allowing them to fully play in terms of information dissemination and corporate supervision and governance, thereby promoting the sustainable development of the capital market. Government departments should be clearer about industrial policy guidance and policy support strategies in order to encourage innovation activities of enterprises and upgrade the synergy of supply chain relations, and consequently promote the sustainable development of the supply chain. Investors should further learn about the relationship between enterprises, suppliers, and customers at different levels according to the disclosure of listed companies and supply chain information to avoid the possible failure of investments.

Voluntary information disclosure will not only have a significant effect on facilitating the information flow within a firm’s supply chain network but can also build mutual trust in the capital market. Thus, the results show that the disclosure of nonfinancial supply chain information plays an important role in supply chain management, and this type of disclosure is advantageous for long-term sustainable development.