Frontiers in Business, Economics and Management 
ISSN: 2766-824X | Vol. 18, No. 3, 2025 

 

158 

Can Customer Digital Transformation Facilitate 
Supplier Innovation Disclosure? 

-- A Double Peer Effect Perspective 

Meng Yao 

School of Modern Posts, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China 

 

Abstract: Digital transformation is an important starting point to drive the high-quality cultivation of new-quality productivity, 
while supply chain is the key conduction mechanism of digitally empowered enterprise innovation. This paper utilizes the supply 

chain data of A-share listed companies from 2012 to 2022 to explore the impact of digital transformation of customer enterprises 

on the disclosure of supplier enterprises' innovation information from the perspective of direct and indirect peer effects, a nd to 

explore ways to break through the dilemma of enterprise innovation information. The study reveals that: (1) customer digital 

transformation significantly improves the level of supplier innovation information disclosure, which helps to alleviate the 

supplier innovation information dilemma; (2) Mechanism analysis shows that the supply chain information relief effect is mainly 

transmitted along the supply chain through two channels: the “direct peer effect” of customers' innovation information disclosure 

and the “indirect peer effect” of suppliers' digital transformation; (3) The heterogeneity test shows that the supply chain 

information relief effect of digital transformation is more significant when there are overlapping investment institutions, 

geographic proximity and closer cooperation between customers and suppliers. This paper provides a new perspective for 

understanding the impact of digital transformation and supply chain participation, and provides policy insights for cracking the 

enterprise innovation information dilemma and then realizing innovation development. 

Keywords: Digital transformation, Innovation disclosure, Information relief effect, Supply chain, Peer effect. 

 

1. Introduction 

Science and technology are the foundation of national 

strength, and innovation is the soul of national progress. The 

Third Plenary Session of the 20th CPC Central Committee 

listed “strengthening the status of enterprises as the mainstay 

of scientific and technological innovation” as an important 

part of “deepening the reform of the scientific and 

technological system”, and proposed to build a scientific and 

technological financial system compatible with scientific and 

technological innovation, and to strengthen financial support 

for the major national scientific and technological tasks and 

scientific and technological small and medium-sized 

enterprises. It also proposes to build a financial system for 

science and technology in line with scientific and 

technological innovation, strengthen financial support for 

major national scientific and technological tasks and science 

and technology-based small and medium-sized enterprises 

(SMEs), and improve the support policy for long-term capital 

to be invested in early stage, small scale, long term, and hard 

technology. Innovation activities are usually characterized by 

long cycle, high risk and high uncertainty, and enterprises 

can't carry out innovation without the support of external 

funds, but external investors face the risks of incomplete 

disclosure of enterprise innovation information and difficulty 

in recognizing the authenticity of the information, which 

affects their willingness to invest [1]. At the same time, 

enterprise innovation information disclosure will produce 

strong repercussions in the capital market, product market and 

internal market of enterprises [2], and its high proprietary cost 

attributes often limit the disclosure choices of enterprises and 

lead to insufficient disclosure of innovation information, 

which leads to the innovation information dilemma between 

the enterprise and the external capital link [3, 4]. How to 

alleviate the innovation information dilemma, promote the 

acceleration of innovation resources to enterprises, and then 

help enterprises to continuously improve the ability of 

scientific and technological innovation is an important and 

urgent practical issue in the implementation of innovation-

driven development strategy. 

At present, the construction of digital China is accelerating, 

and digital transformation is becoming an important hand in 

cultivating new productivity and innovation-driven high-

quality development. Recent studies have pointed out that 

enterprise digital transformation can significantly inhibit 

information disclosure violations [5] and improve the quality 

of information disclosure [6], and produce information “relief 

effect” [7], the role of information governance of enterprise 

digital transformation for innovation information dilemma 

provides a new important feasible direction. 

Some studies have confirmed that the digital 

transformation of customer enterprises can effectively 

promote the innovation [8] and digital transformation [9] of 

supplier enterprises, improve the total factor productivity [10] 

of supplier enterprises, and realize the value co-creation 

among enterprises, but they have not yet touched on the 

important topic of whether there is a supply chain information 

relief effect of the digital transformation of customer 

enterprises, and the research on this issue can provide feasible 

paths for solving the innovation information dilemma of 

enterprises. The research on this issue can provide a feasible 

way to solve the enterprise innovation information dilemma. 

Therefore, it is of great significance to systematically analyze 

and empirically test whether and how the digital 

transformation of enterprises in the supply chain can alleviate 

the innovation information dilemma, in order to grasp the 

opportunities of digital technological change and make use of 

the supply chain transmission mechanism to strengthen the 



 

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governance of the innovation information dilemma of 

enterprises, to empower enterprise innovation, and to help 

achieve a high level of scientific and technological self-

reliance and self-improvement. 

Based on this, this paper uses the supply chain data samples 

of A-share listed companies from 2012 to 2022 to explore the 

impact of digital transformation of customer enterprises on 

the disclosure of suppliers' corporate innovation information 

under cross-firm relationships, and further discusses the 

mechanisms of “direct cohort effect” and “indirect cohort 

effect”, in order to provide a better understanding of the 

impact of digital transformation on suppliers' corporate 

innovation information disclosure. We further discuss the 

mechanisms of “direct cohort effect” and “indirect cohort 

effect” to expand the effective path for breaking the 

innovation information dilemma. 

2. Mechanism Analysis and Hypothesis 
Formulation 

2.1. The Impact of Digital Transformation of 
Customer Firms on Supplier Corporate 

Innovation Disclosure 

Digital transformation through the depth of the application 

of digital technology, can realize the enterprise internal and 

external massive information deep mining, and non-

standardized, unstructured data coding output for structured, 

standardized information, enhance the degree of information 

availability [11] and ensure the attribution of information, and 

then through the “information effect” to enhance the level of 

information disclosure. Social network theory. According to 

the social network theory, in the supply chain network 

relationship, upstream and downstream enterprise decision-

making may imitate and learn from the decision-making or 

behavior of other enterprises in the same network [12], thus 

forming the cohort effect. Specifically, the customer 

enterprise innovation information disclosure has a positive 

effect of mitigating information asymmetry, attracting 

strategic alliances, mitigating agency conflicts and so on [12], 

which will lead to profound changes in the information 

environment faced by the supplier enterprise, in order to 

undertake the product change demand of the customer 

enterprise, to maintain the stability of the supply chain, and to 

enhance the value of the specialized assets, the supplier 

enterprise will take the initiative to enhance the level of 

innovation disclosure, and to form an information disclosure 

“Cohort effect”; the knowledge, experience, path and other 

information related to the digital transformation of customer 

enterprises will be spread along the supply chain, supplier 

enterprises based on their own interests, will follow the 

customer enterprises to carry out digital transformation, 

forming the ‘cohort effect’ of digital transformation. The 

“cohort effect” of digital transformation will be formed. 

2.1.1. Direct Cohort Effect 
The digital transformation of client enterprises can enhance 

their innovation information disclosure level through the 

“information effect”. On the one hand, from the perspective 

of information increment, as the degree of digital 

transformation continues to deepen, the ability of enterprises 

to use digital technology to mine data, obtain information, and 

process information has been rapidly improved, such as data 

acquisition, storage and analysis technology based on big data 

and cloud computing, which can transform massive 

information into standardized and structured information in a 

short period of time, and at the same time, the application of 

blockchain technology can realize the whole chain of 

enterprise data, ensuring information attribution and accuracy. 

tracking and verification, ensuring the attribution and 

accuracy of information. Based on this, enterprises rely on 

digital technology to build an information interaction 

platform, which can deliver incremental information on 

enterprise innovation activities to external stakeholders in real 

time and reduce the risk of adverse selection by external 

investors [13]. On the other hand, from the perspective of 

willingness to disclose information, digital transformation 

can influence management's disclosure decision by enhancing 

their perception of the costs and benefits of innovation 

information disclosure. The digital transformation of 

enterprises can promote the transformation of organizational 

form from vertical to flat organization, and information can 

be transmitted in real time between various departments, 

which strengthens internal collaboration. Under a good 

organizational system, management's opportunistic behavior 

and moral hazard are effectively restrained. On this basis, 

management disclosure of more innovative information can 

reduce the degree of information asymmetry with 

shareholders and external investors [14], and the benefits of 

information disclosure may be higher than the costs for 

management. Therefore, digital transformation can stimulate 

management's willingness and behavior to proactively 

disclose innovative information. 

Innovation disclosure behavior of customer firms promotes 

innovation disclosure of supplier firms through the “cohort 

effect”. The theory of cohort effect originated from sociology 

points out that in order to pursue the legitimacy of behavior, 

individuals will be influenced by the choices of individuals of 

the same or similar status in their decision-making, i.e., “those 

who are close to Zhu are red” [14]. Vertical links between 

enterprises upstream and downstream of the same supply 

chain network can form a cohort network, in which there is 

not only information interaction and learning and imitation 

among enterprises, but also a spillover effect of behavioral 

effects through direct interest and business transactions [15]. 

First, innovation disclosure by customer enterprises will 

provide external information about their technological 

strength, business strategy and future development direction, 

including information related to market demand, product 

competitiveness and so on. Supplier enterprises may use this 

as the basis for their own production plans, R & D direction 

to adjust to better cooperate with the customer enterprise, but 

also a comprehensive assessment of their own external risks 

and the implementation of risk management measures, a good 

way is to share information with the supply chain upstream 

and downstream enterprises and the establishment of a 

collaborative mechanism to jointly deal with [16], which also 

requires supplier enterprises to disclose more innovation 

information. Second, in order to establish and maintain good 

relationships with customers and keep long-term cooperation 

with them, supplier firms invest in relationship-specific assets 

as a commitment to express their confidence in cooperation 

with customer firms to maintain a stable and trustful 

relationship. These relationship-specific assets are used to 

produce products or services uniquely designated by the 

customer, due to the short-term difficult to move to other uses 

and has a strong irreversibility, so the supplier company will 

take the initiative to receive and pay attention to the 

customer's corporate development strategy, competitive 



 

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strategy and product technology requirements and other 

information, and actively respond to customer needs to carry 

out changes. At the same time, in order to maintain the trust 

and cooperation between the two sides, release their own and 

customer technology synchronization and innovation of 

positive signals, supplier enterprises will choose to disclose 

more innovation information; Finally, the customer disclosure 

of innovation information will produce information spillover 

effect. Through the economic linkage and business 

transactions between enterprises in the supply chain network, 

supplier enterprises can obtain relevant production, 

technology and investment information of customer 

enterprises, perceive the future development trend of the 

industrial chain [17], and thus adjust their business decisions. 

For example, in order to reduce business risks, maintain the 

stability of the supply chain and the competitive position of 

the enterprise, the supplier enterprise will be proactive and 

timely layout of technological innovation, increase 

investment in research and development, etc. In this case, 

supplier companies will voluntarily disclose more innovation 

information in order to obtain investors' attention and policy 

support to reduce the degree of information asymmetry with 

the outside world. 

2.1.2. Indirect Cohort Effect 
The digital transformation of the customer's enterprise is 

facilitated by the supply chain “cohort effect” of the supplier's 

enterprise digital transformation. From the customer's 

perspective, suppliers are deeply embedded in their interests, 

and the behavior of customers will have a significant impact 

on suppliers. On the one hand, customer enterprises will 

provide support to help suppliers carry out digital practices 

based on self-interest [18]. Through digital transformation, 

customer enterprises can strengthen the connection and 

communication with suppliers in terms of business practices 

to realize efficient supply chain interconnection. However, 

when the digitalization level of suppliers differs greatly from 

that of customers, i.e., there is a “digital divide”, the 

effectiveness of customer digital transformation 

empowerment will be significantly reduced [8]. In order to 

improve the operational efficiency of the supply chain and 

fully release the effectiveness of digital transformation, 

customers may take the initiative to help suppliers to carry out 

digital transformation, such as sending digital technicians to 

suppliers and providing digital transformation related 

experience [2], thus improving the efficiency of suppliers' 

digital transformation. On the other hand, changes in 

customer demand will force suppliers to adopt flexible 

response strategies. Consumers' green awareness, diversified 

needs, and increased demand for product technology have led 

to changes in customer companies' production. Through the 

use of digital technology, customers are able to process 

consumer market information efficiently and form a 

standardized and practical demand for change, which includes 

changes in the demand for intermediate goods provided by 

suppliers and increased monitoring of supplier innovation 

[19]. In response to customer demand, suppliers will 

implement digital transformation at the production level; in 

addition, the digital transformation of customer enterprises 

will increase the demand for real-time and accurate 

transaction data, which will force supplier enterprises to pay 

attention to the generation, storage and flow of data elements. 

Therefore, the demand feedback can form the driving force of 

customer digital transformation on supplier enterprises' 

digital transformation. 

From the supplier enterprise's point of view, it needs to 

continuously improve the resource allocation efficiency and 

collaborative processing ability, and enhance the dynamic 

ability to adapt to the external market environment [8]. On the 

one hand, customer digital transformation can form the 

information spillover effect, providing suppliers with ways to 

imitate and learn. Customer digital transformation can 

broaden the access to information and knowledge [20], 

increase the connectivity and richness of the information 

network, so that suppliers can access the interactive, shared 

data and information provided by the customer [21], to 

provide efficient learning and communication channels for 

suppliers, to promote the digital transformation of 

information in the supply chain collaborative network within 

the spillover, which will help suppliers to obtain more digital 

knowledge. Top managers will actively imitate and learn from 

customers' digital transformation strategy practices when 

making relevant decisions. On the other hand, competitive 

pressure among supply chains is also an important source of 

digital transformation cohort effect. There may be a non-equal 

interest exchange relationship between supply chain 

enterprises, at this time there is a certain degree of extrusion 

relationship between the vertical industry chain subjects, this 

extrusion relationship is reflected in the hidden information 

seeking opportunistic behavior. Digital transformation 

amplifies customers' advantages in terms of rights, resources, 

or status, and in order to quickly adapt to customers' demands 

for efficiency and collaboration, and to alleviate competitive 

pressures within the supply chain, suppliers will choose a 

digitalization strategy that is aligned with their customers. In 

addition, supply chain linkage is a “survival of the fittest” in 

the process of continuously satisfying customers' dynamic 

demands. The application of digital technology by the 

customer allows the aggregation and integration of a huge 

amount of information about suppliers and companies in the 

same industry, which will bring great uncertainty to the 

original cooperative relationship. In order to prevent 

competitors from encroaching on the market and stabilize 

supply chain customer relationships, suppliers will actively 

engage in digital transformation activities. 

Consistent with the preceding analysis, the implementation 

of digital transformation by supplier firms will lead to the 

disclosure of their own innovation information through the 

“information effect”. 

Combining the above analyses, this paper puts forward the 

hypothesis that the digital transformation of customer 

enterprises will promote the disclosure of supplier enterprises' 

innovation information. 

3. Data and research design 

3.1. Sample Selection 

Drawing on the study of Qingyuan Li et al, this paper 

selects the top five customer relationship data of A-share 

listed companies in Shanghai and Shenzhen from 2012 to 

2022 as the research sample, and retains the observation 

samples in which both suppliers and customers are listed 

companies. After processing, 2579 supplier-customer year 

observations are finally obtained. 

3.2. Variables and Models 

3.2.1. Definition and measurement of key variables 
Explained variable: corporate innovation disclosure 

(Inno_Disc). In this paper, we refer to the practice of Zhou et 



 

161 

al [4], and adopt the word frequency analysis method of seed 

word set + Word2vec similar word expansion to measure the 

level of supplier innovation disclosure. The word frequency 

of technological innovation vocabulary was obtained by 

summarizing the natural language processing and text 

analysis of the WinGo financial text data platform, and the 

proportion of the calculated keyword word frequency in the 

text of the enterprise's annual report was multiplied by 1,000, 

and the magnitude of the value reflected the richness of the 

enterprise's disclosure of innovation information. 

Explanatory variable: the degree of digital transformation 

of client companies (Cus_digital). This paper adopts the 

digital transformation data of listed companies provided by 

CSMAR, which helps to comprehensively measure the level 

of digital transformation of enterprises. 

3.2.2. Research model 
In order to investigate the impact of customers' digital 

transformation on suppliers' corporate innovation disclosure, 

the article constructs the following model: 

   

Where Inno_Disc is the level of innovation disclosure of 

supplier firms in the ith supply chain at year t; Cus_digital is 

the digital transformation of customer firms at year t-1; 

Controls denotes the micro characteristics of supplier firms; 

this paper focuses on the coefficient β of the coefficient 

Cus_digital, and if β is significantly positive, it suggests that 

the customer's digital transformation can facilitate the 

supplier firms' innovation disclosure, which in turn supports 

the hypothesis. 

4. Empirical Results  

Table 1 reports the regression results of the effect of digital 

transformation of customer firms on the level of innovation 

disclosure of supplier firms. Specifically, column (1) is 

regressed using only the digital transformation of customer 

enterprises on supplier enterprises' innovation information 

disclosure, and the results show that the regression coefficient 

is 0.0794 and is significant at the 1% level, which indicates 

that the higher the degree of digital transformation of the 

customer enterprises, the supplier enterprises tend to 

externally disclose more innovation information. Columns 

(2)-(4) are regressed based on column (1) by adding 

enterprise-related control variables in turn, and the customer 

enterprise digital transformation index (Cus_digital) is still 

significant. The hypotheses of the article are verified, in 

which each unit increase in the digital transformation of 

customer firms increases the level of innovation disclosure of 

supplier firms by 0.0351 units. 

 

Table 1. The Impact of Customer Digital Transformation on Supplier Corporate Innovation Disclosure 

 (1) (2) (3) (4) 

Variables Inno_disc Inno_disc Inno_disc Inno_disc 

Cus_digital 
0.0794*** 0.0722*** 0.0698*** 0.0351*** 

(10.2052) (10.0770) (9.6199) (4.3315) 

Size 
 -0.5051*** -0.4161*** -0.1647** 

 (-8.4798) (-5.6444) (-2.3381) 

Lev 
 -3.7379*** -3.7446*** -3.5254*** 

 (-9.2433) (-9.1274) (-8.7075) 

Roa 
 -2.9687*** -2.9171*** -3.2290*** 

 (-4.9011) (-4.6485) (-4.9289) 

Age 
 -2.4776*** -2.5149*** -1.8989*** 

 (-10.2643) (-10.2867) (-7.4294) 

Cashflow 
 1.2454 1.6413 2.7792*** 

 (1.1401) (1.5041) (2.6779) 

TobinQ 
 -0.0123*** -0.0111*** -0.0104*** 

 (-5.2804) (-5.2913) (-6.6212) 

Board 
  0.2888 1.0361** 

  (0.5674) (2.0260) 

Indboard 
  0.0236 0.0318** 

  (1.5426) (2.0594) 

Top1 
  -0.0021 0.0174*** 

  (-0.3107) (2.7773) 

Institution 
  -0.0102** -0.0062 

  (-2.2716) (-1.4526) 

_cons 
5.5029*** 25.7553*** 22.9588*** 14.0915*** 

(18.5287) (19.1742) (12.2162) (6.3120) 

Industry/Year No No No Yes 

N 2579 2579 2579 2579 

Adj. R2 0.0410 0.1901 0.1927 0.3250 

To eliminate other omitted variables and factors that create 

endogeneity between the core variables, for example, market 

structural pressures can have a simultaneous effect on the 

digital transformation of customer firms and the disclosure of 

supplier firms' innovations, which can bias the estimation of 

causality. Therefore the article eliminates the endogeneity 



 

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effect through instrumental variables. 

The first one is to borrow the research treatment of Lewbel 

[22] and use the third power of the difference between the 

difference between the customer digital transformation index 

and the mean value of the digital transformation index by 

industry secondary code and province as an instrumental 

variable (Lewbel IV); and the second one is to use the mean 

value of the same province and the same industry in the same 

year, except for the customer firms, as an instrumental 

variable (Digital_IV). Firstly, the positive correlation test of 

instrumental variables on explanatory variables, the results 

are shown in column (1) and column (2) of Table 2, the 

regression coefficients are significantly positive, 0.0048 and 

0.8767, respectively, and the F-statistics are greater than 10, 

which excludes the possibility of weak instrumental variables. 

Second, the results of the exclusion constraint test of 

instrumental variables as shown in Table 2 columns (3) and 

(4) show that the instrumental variables are not significant for 

the level of disclosure of innovation information of suppliers' 

firms of the explanatory variables, which is in line with the 

exclusion requirement. Finally, the coefficients of customer 

digital transformation as shown in the results of Column (5) 

and Column (6) are 0.0342 and 0.0458, respectively, which 

are both significantly positive at the 1% level, which is more 

in line with the results of the benchmark regression, 

suggesting that the results of the positive facilitation of the 

digital transformation of the customer firms on the level of 

supplier firms' disclosure of innovation information are robust. 

 

Table 2. Instrumental variable test results 

 (1) (2) (3) (4) (5) (6) 

Variables Cus_digital Cus_digital Inno_disc Inno_disc Inno_disc Inno_disc 

Lewbel IV 
0.0048***  -0.000    

(46.0)  (-0.11)    

Digital_IV 
 0.8767***  0.0133   

 (24.7)  (0.85)   

Cus_digital 
  0.0360*** 0.0305*** 0.0342*** 0.0458*** 

  (3.17) (3.11) (3.04) (2.90) 

_cons 
36.1375*** 8.0728 14.0616*** 13.9357*** 14.1256*** 13.8128*** 

(7.87) (1.46) (6.24) (5.86) (6.32) (5.79) 

Ctrs Yes Yes Yes Yes Yes Yes 

N 2579 2215 2579 2215 2579 2215 

Adj. R2 0.6073 0.4826 0.3248 0.3414 0.3250 0.3409 

 

Table 3. Mechanism of action tests 

 (1) (2) (3) (4) 

variable Cus_inno_disc Inno_disc Digital Inno_disc 

Cus_digital 0.099*** 0.029*** 0.168*** 0.0177** 

 (11.8320) (3.5739) (9.9095) (2.2345) 

Cus_inno_disc  0.0421*   

  (1.8812)   

Digital    0.103*** 

    (10.6004) 

_cons 7.503*** 15.04*** -1.4182 14.22*** 

 (3.1561) (6.2869) (-0.3276) (6.6103) 

Solel Z  1.983**  7.82*** 

Ctrs Yes Yes Yes Yes 

N 2532 2532 2579 2579 

Adj. R2 0.1836 0.3481 0.4202 0.3554 

Digital transformation of customer enterprises and 

innovation disclosure level of supplier enterprises: First, the 

direct cohort effect in supply chain network, i.e., the digital 

transformation of customer enterprises will increase the 

willingness to disclose innovation information, and improve 

their own innovation disclosure level (Cus_inno_disc), and 

then increase the innovation disclosure level of supplier 

enterprises through the “direct cohort effect” in the supply 

chain network. Then through the “direct cohort effect” in the 

supply chain network, it will enhance the level of innovation 

information disclosure of supplier enterprises. The second is 

the indirect cohort effect in the supply chain network, i.e., the 

digital transformation of customer enterprises first promotes 

the digital transformation of supplier enterprises through the 

“indirect cohort effect”, and then enhances the level of 

innovation information disclosure of supplier enterprises. 

Like the measurement of independent variables and 

dependent variables, the level of innovation disclosure of 

customer companies and the degree of digital transformation 

of supplier companies can be obtained. The results of the 

cohort effect mediation mechanism test are reported as shown 

in Table 3. The Cus_digital coefficient in column (1) is 

significantly positive at the 1% level, indicating that customer 

digital transformation helps to improve the level of innovation 

disclosure of the firm itself. Both Cus_digital and 

Cus_inno_disc coefficients in column (2) are significantly 

positive, and the Cus_digital coefficient is slightly smaller 

than that of the benchmark regression in Table 3, which 

indicates the existence of partial mediation effect, and also the 

Sobel test supports the existence of mediation effect; similarly, 

the Cus_digital coefficient in column (3) is significantly 

positive at 1% level, which suggests that customer digital 

transformation can promote the digital transformation of 

supplier firms. The coefficients of Cus_digital and Digital in 

column (4) are both significantly positive, and the coefficient 

of Cus_digital is slightly smaller than that of the benchmark 



 

163 

regression in Table 1, which indicates that there is also a part 

of the mediation effect, and the Sobel test also supports the 

existence of the mediation effect. 

5. Conclusion 

Based on the supply chain network relationship, this paper 

empirically analyzes and tests the relief effect of digital 

transformation of customer enterprises on supplier 

enterprises' innovation information disclosure, using supply 

chain enterprises listed on A-share stock companies from 

2012 to 2022 as samples. It is found that: (1) digital 

transformation of customer firms significantly promotes the 

improvement of supplier firms' innovation information 

disclosure level and helps to alleviate supplier firms' 

innovation information dilemma, which is valid in a series of 

endogeneity tests and robustness tests such as instrumental 

variable method, replacing the measurement method of 

explanatory variables and changing the regression model. (2) 

The information relief effect arises mainly through two 

mechanisms of action. First, the direct cohort effect, i.e., 

customers' digital transformation will enhance their own 

innovation information disclosure level through the 

information effect, which will then be transmitted along the 

supply chain through the cohort effect, thus promoting 

suppliers' enterprises to disclose more innovation information. 

The second is the indirect cohort effect, i.e., customers' digital 

transformation will promote suppliers' digital transformation 

through the cohort effect, which will enhance suppliers' 

innovation information disclosure level through the 

information effect. (3) Heterogeneity test results show that the 

supply chain information relief effect of digital 

transformation varies significantly across supply chain 

relationships. Specifically, the promotion effect of customer 

digital transformation on supplier innovation information 

disclosure level is more significant when there are supply 

chain overlapping investment institution shareholding of the 

customer and supplier, the physical office of the customer and 

supplier is in the same province and the closer the supply 

chain cooperation relationship, i.e., the higher degree of 

importance of the customer. 

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