Credit data barriers are a prominent problem in the credit information systems of supply chains, affecting the transmission efficiency of credit records among financial institutions and financing subjects (Wang-Mlynek & Foerstl, 2020), as well as the interactions between core enterprises and SMEs (Alora & Barua, 2019). Credit-data interconnection is challenging on diversified networks; different enterprises, systems, and multiple components become isolated information clusters in SCF due to information asymmetry (Gomber et al., 2018; Kesharwani et al., 2021; Shih et al., 2021). Credit data and financial intermediaries should be made available for potential enterprises with financing needs to properly process their credit records. Nevertheless, commercial banks and other financial institutions function on their self-interest maximization to protect their business interests (Bris & Cantale, 2004). Meanwhile, credit-data barriers exist between core and SMEs in SCF, further weakening the support for SMEs to obtain financing from financial institutions (Abdulsaleh & Worthington, 2013; Gao et al., 2021; Rivera-Trigueros & Olvera-Lobo, 2021; Trappey et al., 2021). Trust transmissions must be linked between financial institutions, upstream and downstream SMEs, and core enterprises for all individual rational entities with particular information protection needs (Ada et al., 2021; Ruan et al., 2021; Yuan et al., 2019; Zhang et al., 2021a). Therefore, it is critical to comprehensively evaluate the credit subject's credit level and find a way to overcome the credit data barriers with the help of emerging technology.

The integrity of credit records and information refer to the comprehensive and multidimensional data used to evaluate the credit of stakeholders of SCF in credit evaluation (Ali et al., 2019; Meso et al., 2021; Zhu et al., 2021). From a theoretical standpoint, stakeholders get quality credit records that aim to promote their financing needs. Furthermore, credit records from financial institutions to the core enterprise allow them to gain full credit levels of suppliers and dealers. Core enterprises can transfer credit to upstream and downstream SMEs. Therefore, credit transfers ensure financial credit records’ integrity throughout the supply chain (Al-Taie et al., 2021; Graafland & van de Ven, 2011; van Rensburg, 2021; Zhang et al., 2021b; Zheng et al., 2021b). Nowadays, the laborious development process, complex enterprise data, and limited technology appeal often result in low-quality information from financial institutions. The nerve center function of core enterprises is also limited in practice, which leads to insufficient credit record integrity of the financial subject of the whole supply chain (Wang et al., 2019a). The intermediary role of credit finance in the financial chain of the supply chain is not entirely played (Jin et al., 2019). It cannot accurately and effectively evaluate the changing trajectory of credit information for all links in the life cycle of financial transaction activities (Wang et al., 2020a; ZareRavasan & Krčál, 2021). Notably, adequate support for the financial strength of the credit data transmission for SMEs is lacking.

As an innovative way of combining industry and finance, SCF spans industrial chain and financial activities. Finance is naturally leveraged and risky, and false credit information is easy to breed. The primary reason is the prominence of fictitious transactions (Firth et al., 2005). For instance, low-quality supervision, arbitrage, tax arbitrage, and foreign exchange arbitrage are frequent among enterprises, financial institutions, and other service entities. Second, it is due to the lack of reliable identification of warehouse receipts (Su & Wang, 2020). Some enterprises use this regulatory loophole to obtain credit lines using false and repeated pledge warehouse receipts (Hofmann et al., 2018). Third, it may be caused by the need for extending multichannel default access to SCF funds (Zhen et al., 2020). Primarily, enterprises obtain external funds through their business in SCF. Alternatively, they may carry out supply chain businesses early and change business goals in the middle and later stage accordingly, such as expanding performance and listing operations. Therefore, it is crucial to fully use fintech to effectively curb the false information transmission of relevant fields of SCF to enhance confidence and improve transaction efficiency (Chen et al., 2020; Vyas et al., 2019).

The security of credit data will significantly affect the regular transactions of SCF-related subjects.

Credit data storage security In the SCF system, the security of credit data storage is related to every stakeholder who participates in financial services activities and impacts the orderly operations of regular financial transactions (Anagnostopoulos, 2018). From an internal perspective of SCF, core, upstream, and downstream supply chain enterprises are motivated to tamper with their credit data to increase their earnings (Ma et al., 2019). From an external perspective of SCF, all enterprises have the possibility of credit data being attacked and stolen (Xu, 2016). The current SCF credit system cannot eliminate such risks.

Credit data assurance to generate value SCF reinforces credit support to SMEs in a relatively weak position through the trust transmission of core businesses, aiming to solve the problems of financing difficulty and costly finance for SMEs (Fayyaz et al., 2020). Therefore, the role of core enterprises is critical as they take advantage of their special status, take moral risks in using and transmitting credit data, and engage in self-serving behaviors (Papadimitri et al., 2020). Other businesses in a relatively weak position cannot effectively obtain safe credit data and force the capital of SMEs (Liang et al., 2018). Therefore, the whole SCF could be severely unbalanced.

Tamper-proof ability means that under the constraint of an intelligent algorithm, each block's information input is traceable so that one-way tampering is prohibited (Wu et al., 2019). Blockchain structure can check the order information, credit information, financing request, and operation progress of the SCF business while converting paper vouchers such as enterprise orders, contracts, and bills into digital assets to generate smart contracts (Chong et al., 2019; Liu et al., 2020a). Diverse subjects use blockchain data from the same source to improve the liquidity of collaterals or collaterals in the traditional SCF market, promoting the further release of core business creditability and effectively mitigating the problem of the lacking credit certificates for SMEs (Wang et al., 2019b).

Blockchain integrates the advantage of untampered data into the credit data records and forms the credit economy recognized by stakeholders in SCF (Maesa & Mori, 2020). The credit data of the trading entity's financial service activities are recorded objectively by each node of the blockchain, which is traceable and credible (Wang et al., 2020b). They cannot be tampered with in one direction, thus playing a supervision warning role. Therefore, this is conducive to effectively integrating enterprise credit assessment, nurturing confidence in the current SCF credit investigation system, and improving credit record storage integrity (Baillette & Barlette, 2020; Guo & Wang, 2020; Li et al., 2020; Wang et al., 2020c).

A decentralized, distributed storage strategy is to prevent data service centers and other traditional mediation. The data exchange between all shared nodes safeguards credit data integrity (Ma et al., 2020). The rights and obligations are equal; a single node that suspends operation does not affect the system's operation, effectively improving the credit data security and conveniently lowering maintenance costs (Rouibah et al., 2020; Yang et al., 2019). After introducing blockchain technology service for a final order of multiple vendors, core businesses and financial institutions form a chain block, extending to all levels involved in accounts receivables and the business credit information, such as the full records on this blockchain. Financial institutions provide information to any level of trading suppliers, create the core business, and facilitate payment credit agreements for accounts payable on the entire supply chain multistage transmission (Ensslin et al., 2020; Kopyto et al., 2020).

Blockchain technology serves as a transparent and credit transmission technology by (i) promoting the SCF credit-data swap while supporting a viable core business to the upstream and downstream SMEs’ credit limited situations, (ii) recognizing the rights and interests of stakeholders, and (iii) improving service level quality of SCF (Du et al., 2020).

Disclosure transparency means that the supplier of blockchains has its subdatabase. Based on the shared and open characteristics, all participants can obtain and apply data through the public entrance and form an open credit data record (Casino et al., 2019). On the one hand, blockchain technology has its identical mathematical algorithm, and the credit data of each node is automatically exchanged, integrated, and consistent (Niranjanamurthy et al., 2019). Each financial entity of the supply chain can effectively distinguish the authenticity of credit data through the blockchain ledger, reasonably avoid the generation of participants’ malicious behaviors, and control the overall loss to a minimum. On the other hand, each SCF subject has relatively symmetrical credit data information (Li et al., 2020). The core enterprise's monopoly advantage over unique credit data is weakened. The participants’ motivation for breaching a contract due to a lack of contract spirit will be effectively restrained. Therefore, the blockchain is seen as a technology with openness and transparency that is conducive to enterprises strengthening their performance spirit and improving the credit coefficient (Saberi et al., 2019).

Reliability means that blockchain, as a trust segmentation instrument, provides a stable environment for financial transactions (Kshetri, 2018). It establishes a trust basis by endorsing in a purely mathematical way and can reasonably judge whether credit data is adequate, manages financial risks, controls costs, and reduces credit risks. Credit data storage and application have multinode distribution characteristics under blockchain technology (Liu & Zou, 2019), bringing the synergistic effect into play. Failure or destruction of one node will not affect the entire network's regular operation (Du et al., 2020), making it difficult for a single risk to spread to the entire SCF system.

The “blockchain + supervision” pattern of SCF will gradually take shape to grasp in-depth supervision and accurate services that can reasonably control credit risks (Wong et al., 2020). Under the traditional SCF system, commodity trading and business financing exist as independent links in financial services. Suppliers, core enterprises, and financial institutions have credit blind spots and credit transmission problems. After introducing blockchain technology, the credit information of suppliers, core enterprises, and financial institutions is recorded within the blockchain, reducing the time, labor, and transaction cost and effectively avoiding the generation of credit risks (Morkunas et al., 2019).

At present, the value of blockchain technology for enterprises and industries is most impacted by the public and the market. This research area mainly addresses the questions of which markets or industries will be affected by blockchain systems, how to design business models to derive economic value from blockchain, and how to measure these values.

For the industry value of blockchain, the financial field is often the area most examined by researchers. For example, in the SCF field, researchers found that blockchain technology not only can effectively solve the pain points, according to decentralization, trust, stability, safety, increased production, improved supply chain of each member's income and accounts receivable financing benefit maximization.

The industry value of blockchain is most commonly discussed in financial markets, but other areas, such as logistics and public services, are also becoming a focus of attention. With the development of blockchain technology, industry decision-makers are also aware of the value-added potential of this technology. In addition, the transportation and power industries have also been widely impacted. The existing research results provide the theoretical basis for this study and theoretical support for improving blockchain technology. However, there is little mention in existing studies of how to improve systems and services for blockchain applications in specific situations.

The existing blockchain consensus mechanism has low security and large resource consumption, so it is particularly important to design a new consensus mechanism to serve the credit investigation system. In this study, blockchain data sharing and traceability can be realized by improving the consensus mechanism to improve the existing credit investigation service system. Our findings help optimize the existing supply chain financial credit system and enhance the efficiency of supply chain financing.

The data entity is the credit information belonging to the structure that should have the right to control. Financial institutions such as credit institutions, electronic commerce, and nonfinancial institutions, such as telecommunications operators and government departments, store credit information. When it is necessary to collect personal credit information, its use must be fully informed and authorized.

Credit bureaus systematically collect, sort out, process, and analyze credit information about enterprises or individuals, provide them with credit reports, and offer diversified credit investigation services. Generally, they do not generate credit investigation data. Collecting and sorting out comprehensive and accurate credit information is the key prerequisite of providing credit reports.

Credit information providers are banks, securities, and other financial institutions with credit sales and lending information as well as other nonfinancial institutions such as telecommunications operators and government departments. These institutions have corporate or personal credit information. Therefore, they share it, and the agencies generate credit reports, thus providing credit reporting services.

Cloud service providers provide cloud storage, cloud computing, and other services. The credit data are shared by credit information providers to credit agencies. As the information is relatively large, data management benefits by uploading credit information to the cloud server first; then, credit reference agencies shall download the shared data from the cloud server after verification.

It offers rights assurance to all subjects involved in the credit-data information exchange and the platform's regular operation. The model establishes a regulatory agency to deal with all parties’ objections in the sharing process, such as the objection of the information related to the credit information uploaded by the credit information sharers.

The credit investigation agency must first obtain the user's authorization for the requested data. The credit investigation agency can then request the credit information provider's corresponding data under the authorization signed by the information subject.

After receiving a request per the specific data-format requirements, the credit information providers upload data encryption to the cloud server to protect credit information providers’ rights and interests. The credit information providers include the object request, metadata, and other information transaction to blockchain nodes to load documents while uploading data. The records require user authorization, and the data and information uploaded by credit information providers are recorded on the blockchain. The blockchain has the characteristics of being a tamper-proof and untraceable instrument. Multiple nodes maintain it, so it can be used to deal with conflicts and provide a fair and credible credit investigation information sharing environment.

There will inevitably be disputes in sharing credit investigation information, so the model includes a regulatory agency as the authority to deal with the conflicts and protect each participant's rights and interests.

The credit bureaus need to obtain the user's authorization for the requested data first, and then the credit bureaus can request the credit information provider to obtain the corresponding data by relying on the authorized information signed by the information subject.

After receipt of a request and following the requirements for certain data formats, upload data encryption to cloud the server. To protect the rights and interests of credit information providers, credit information providers include uploading data, the request object, metadata, and other information to blockchain nodes to upload documents. The request records of user authorization and credit investigation agencies, as well as the data uploaded by credit information providers, are recorded on the blockchain. The blockchain has the characteristics of being imitable and traceable and is jointly maintained by multiple nodes. Therefore, it can serve as the basis for contradiction handling and provide a fair and credible environment for sharing credit information.

There will inevitably be some disputes in the sharing of credit information, so the model includes the regulatory agency as the dispute settlement authority to protect each participant's rights and interests.

The enterprise credit information sharing model's basic framework based on blockchain technology is shown in Fig. 1.

Fig. 1.

Basic framework of the enterprise credit information sharing model.

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According to each node's roles and functions in the model, the business as a consensus node is divided into enterprise audit and service alliances. Both members are generated by the enterprise credit ranking from high to low.

Blockchain information alliance

The Blockchain Information Alliance (BIA) is mainly responsible for verifying whether the credit information provider uploads valid transaction information. If the transaction is verified to be valid, it endorses the credit information provider's transaction. The specific working process of BIA is as follows:

• Step 1: The credit information provider initiates the transaction, broadcasting to all BIA nodes.

• Step 2: The BIA node verifies the transaction and endorses the transaction if the transaction format and summary information are correct; it broadcasts the endorsed transaction.

• Step 3: A transaction is considered legal only if enough signatures endorse it.

Blockchain consensus alliance

The Blockchain Consensus Alliance, or BCA, is responsible for reaching a consensus on the deal to form untamable credentials. The main process of the consensus mechanism is shown in Fig. 2. The specific working process of BCA is as follows:

• Step 1: The master node in BCA sorts the collected legitimate transactions, packages the sorted transactions into blocks, and generates the block proposal.

• Step 2: The primary node sends the preprepared message << PRE-PREPARE, v, n, d>, m> to the slave node, where v represents the view number, m is the block message, d is the summary of the request message, and n is the height of the new block.

• Step 3: The preprepared message is verified from the slave node. In the verification passes, the prepared message will be broadcasted to other consensus nodes, where “i” represents the information from the slave node and receives the prepared message sent by other consensus nodes.

• Step 4: If a node receives more than 2f prepare messages, v, n, d> sends a commit message to other consensus nodes.

• Step 5: When a node receives the confirmation message “2f + 1”, it indicates that the consensus node has reached an agreement on the proposal, records the new block in the proposal in the local blockchain ledger, and transmits the block to the entire node network. The ordinary node can receive the contents of the block and record it in its blockchain ledger. The entire workflow model is represented in Fig. 3.

  
  

  Fig. 3.

  Model's workflow.

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Fig. 2.

RPBFT Consensus flow chart.

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After the transaction broadcast, the BIA node first verifies whether the data is uploaded completely and whether the data transaction format is correct. After the successful verification by the BIA node, the transaction will be signed and endorsed. The transaction will be considered legal only after a sufficient number of BIA nodes endorses the transaction. In the BCA node, the master node packages and verifies the legitimate transaction within a period of time and broadcasts it to the slave node in the form of a block, which enters the three-stage consensus stage. After completing the three stages, each node will add the block to its own blockchain ledger. Once the transaction appears on the blockchain, it indicates that the task requested by the exchange has been uploaded and completed. The credit investigation agency uses the key to access the shared data.

Consensus to achieve

I BIA transaction verification

In this model, six enterprises, respectively initiated six transactions after uploading their credit information. The BIA node first accepts the transaction, verifies the transaction structure and the accuracy of the uploaded information, signs the transaction after verification, encapsulates the transaction's data structure, and then broadcasts it to the master node in BCA. Fig. 4 shows the specific verification process of BIA nodes for transactions.

Fig. 4.

Transaction validation process.

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II ESA block generation and consensus reached

This model produces four blocks in three intervals, including the founding block that contains only original transaction information. For instance, Enterprise 1 uploads transactions to the second block; Enterprises 2 and 3 upload transactions to the third block; and Enterprises 4, 5, and 6 upload trading jointly to the fourth block. Fig. 5 shows the information for the entire blockchain query.

Fig. 5.

Block generation and consensus process.

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