With the rapid development of society, all walks of life need the support of the Internet of Things, and the financial industry is no exception. This article integrates blockchain technology with supply chain finance and builds a supply chain financial alliance architecture based on blockchain technology and an underlying model of the Ethereum blockchain system suitable for supply chain finance. We innovated new supply chain finance models and operating mechanisms and proposed business scenarios for supply chain finance from the perspective of blockchain. Taking into account the actual operation of the blockchain supply chain financial platform, the principal-agent model and the incentive theory are applied, and the supply chain financial accounts receivable model is taken as an example in the case of complete information and incomplete information. The incentive mechanism between the service provider of the chain supply chain financial platform and the core enterprise promotes the better implementation of blockchain technology and supply chain finance. Based on the existing theoretical research, this paper identifies the key influencing factors of the supply chain’s cross-enterprise incentive mechanism. These influencing factors system includes two dimensions: transaction factors and relationship factors. Transaction factors include resource dependence, uncertainty, and cooperation experience; relationship factors include corporate reputation, trust level, and relationship commitment. Based on the nature of the incentive mechanism, information sharing and revenue sharing are extracted as the measurement dimensions of the supply chain’s cross-enterprise incentive mechanism. On this basis, this article draws on the existing enterprise life cycle division method and constructs a hypothetical model of the influencing factors of the incentive mechanism in the incubation period, the growth period, and the maturity period. Relevant data was collected through questionnaires, and SPSS and AMOS software were used to perform statistical analysis, reliability analysis, exploratory factor analysis, confirmatory factor analysis, and structural equation hypothesis testing on the data. The performance of each influencing factor in different stages of the enterprise’s life cycle and the importance of each influencing factor in the same life cycle stage are obtained.
In the industrial field, the supply chain has realized the optimal allocation of physical resources, while supply chain finance is the optimization of the supply chain’s capital flow in the financial field [
Researchers believe that supply chain finance should analyze the internal transaction structure of the supply chain, combine risk diversification measures such as core enterprises, logistics supervision companies, and capital flow guidance tools, and apply the credit model of self-compensation trade financing to provide supply chain node enterprises with credit and financial services such as settlement and wealth management [
Due to the asymmetry of information, it is often necessary to consider the existence of adverse selection problems and moral hazard problems. Therefore, this chapter studies the blockchain technology service platform’s incentive contracts for core supply chain finance companies. We design problems under information and incomplete information and design and solve the corresponding incentive contract model. This article analyzes and processes the survey data of the gestation period, growth period, and maturity period. First, we use SPSS19.0 to perform descriptive statistical analysis, reliability analysis, and exploratory factor analysis on the data; then, we use AMOS17.0 to perform confirmatory factor analysis, model correction, and hypothesis testing on the data. During the gestation period, the hypotheses H4b, H5a, H5b, H6a, and H6b did not pass the test, and the remaining hypotheses all passed the test; in the growth period, the hypotheses H2b, H3b, and H4a did not pass the test, and the other hypotheses passed the test; at the maturity stage, hypotheses H1a, H2a, H3a, H3b, and H4a have not passed the test, and the remaining hypotheses all passed the test.
The rest of this article is organized as follows. Section
The Internet of Things consists of a three-tier architecture, as shown in Figure
Architecture diagram of the Internet of Things.
From an economic perspective, as long as there is a relationship between competition and cooperation, information asymmetry will appear. This relationship is called a principal-agent relationship. There is also a difference of interest between the principal and the agent due to the difference in the effect function [
Asset exclusivity means that the funds invested in a certain business are not used for other purposes; that is, they cannot be transferred [
The theory of self-compensation trade financing means that banks and other financial institutions can effectively control credit risk by controlling logistics or tying third-party responsible persons according to the capital flow of the enterprise under the premise of effectively mastering the business cooperation background of SMEs [
In the supply chain “production-supply-sale” operation process, cash flow plays an important role in the normal operation of SMEs. Because it is in a relatively weak position in the supply chain, capital flows cannot return in a reasonable time. Without sufficient self-reserve funds, companies will be burdened with insufficient cash flow pressure and difficult-to-maintain normal production operations. This has created an urgent demand for loans from small- and medium-sized enterprises, but the limitations of their own credit strength make it difficult to obtain loans from banks or the interest on loans is high. The supply chain financial financing platform is shown in Figure
Supply chain finance financing platform architecture.
Prepayment financing is a financing model that occurs in the procurement stage of the supply chain and can be understood as “future inventory financing.” The premise of the development of this model is that the core supplier enterprises in the upstream of the supply chain must commit to repurchase, and then the financing SMEs use the purchase documents generated between the core enterprises to apply for the corresponding loan line to the bank, and the right to take delivery is controlled by the bank.
Inventory pledge financing refers to financing small- and medium-sized enterprises that use temporarily immobile goods in their inventory as pledges to apply for loans from banks. The bank entrusts the supervision and transportation of the pledged goods to third-party logistics companies to provide liquidity support to the small- and medium-sized enterprises. This can effectively reduce the capital occupation cost of financing SMEs’ inventory and the cost of warehouse use. Through inventory pledge financing, a balance between production and sales stability and liquidity can be achieved. The business process of inventory pledge financing is shown in Figure
Inventory pledge financing business process.
In the inventory pledge financing model, financing SMEs apply for loans from banks and other financial institutions with their own inventory of goods under the credit guarantee of the core enterprises with which they have a cooperative trade relationship. Banks first need to review the trade background of the supply chain where the financing SMEs are located, the credit strength of the core enterprises, and the strength of cooperation with the core enterprises. At the same time, it has entrusted third-party logistics companies with professional businesses that it does not possess, such as the evaluation of pledges, warehousing, and transportation, which greatly increases the operability of the inventory pledge financing model. After passing the professional evaluation of the third-party logistics company, the evaluation report is submitted to the bank. If the requirements are met, the bank will directly sign the pledge loan agreement with the financing SME after signing the responsibility guarantee letter with the core enterprise. After the pledged goods are delivered by the financing SME to the warehouse designated by the third-party logistics company, the logistics company issues a pledged warehouse receipt and transmits it to the bank. The bank sets a reasonable pledge rate based on various influencing factors and uses this as a benchmark for the financing company loans. After successful sales, SMEs get the money back and repay the bank loan with the money. According to the amount of repayment funds, the bank informs the logistics enterprise to issue a corresponding proportion of pledges, and this business will end until the loan is repaid.
Credit sales have become the trend of trade cooperation between enterprises. Noncore suppliers in the upstream of the supply chain cannot get the money back in time because of the gap in strength or business needs. At the same time, they cannot successfully obtain the support from bank due to the lack of qualifications or collateral. Insufficient funds will affect the company’s subsequent production and operations, causing the capital chain to break or even stop production. The act of selling on credit has brought great liquidity pressure to the cash flow of middle and upper reaches in the supply chain. The existence of the credit sale transaction has given birth to the emergence of the accounts receivable financing model.
The financing of the upstream of the supply chain between small- and medium-sized supplier enterprises and the downstream core manufacturer enterprises produces trade cooperation. After the small- and medium-sized enterprises sign the order contract with the core enterprise, the core enterprise issues accounts receivable documents to the small- and medium-sized enterprises to obtain the ownership of the goods. Subsequently, the financing SMEs can apply for loans from the bank with the accounts receivable documents as pledge. The bank needs to review the authenticity of the document, the creditworthiness of the core company, and the ability to collect funds. If the loan requirements are met, the bank will sign a transfer agreement with the financing SME and inform the core enterprise of the actual transfer. Under normal sales conditions, core enterprises receive continuous capital return and can repay the bank loans in batches or in full. When debt settlement is over, the bank will cancel the accounts receivable pledge contract with upstream financing SMEs. The development of the accounts receivable financing model has better solved the problem of rupture of the capital chain caused by the pressure of purchase and sale of upstream SMEs.
As shown in Figure
Schematic diagram of the application system of the supply chain financial platform under the blockchain architecture.
Most SMEs use indirect financing as the main financing method, but in fact, direct financing (issuing stocks and bonds) is the key problem that solves the current difficulty of financing for SMEs. As a major direct financing method, ABS (asset securitization) can play a major role in solving the financing problems of SMEs, reduce the financing costs of SMEs, improve their financing convenience, and introduce a large amount of private capital in a legal manner.
In the supply chain finance accounts receivable financing link, the relationship between the blockchain supply chain financial information service platform and the core enterprise is that the blockchain supply chain financial information service platform is the principal and the core enterprise is the agent. Based on the asymmetric information in the initial stage of the establishment of the blockchain-based supply chain financial platform, an incentive mechanism contract model based on the constraints of the blockchain supply chain financial information service platform is established. Companies improve their product quality and service quality, apply the principal-agent model to solve analysis, explore the behavioral characteristics of core companies in the financing process, help the blockchain supply chain financial information service platform to identify the sales capabilities of core companies, and promote core companies to improve their own comprehensive strength.
Assume that the sales volume of the core company on the supply chain financial financing platform based on blockchain technology is
Among them,
In real life, core companies tend to exaggerate
Assuming that the core enterprise is a risk aversion type, its utility function has an invariable absolute risk aversion feature, so its expected return function satisfies
Using the deterministic equivalent quantity method, the expected benefits of the core enterprise can be obtained as follows:
Under the condition of complete information, core enterprises package and upload their business capabilities, sales contracts, production and operation, and other information to the blockchain supply chain financial service platform; the blockchain system automatically accounts for the entire network. There is no private company in the core enterprise. Information, the blockchain supply chain financial service platform, and the core enterprise are completely information transparent, and the service platform can intuitively observe the core enterprise’s sales ability
From the model assumptions, the client’s blockchain supply chain financial service platform is a risk-neutral type, which encourages core companies to strive to improve sales. Therefore, the expected benefits of the blockchain supply chain financial service platform are
According to Stackelberg’s theory, the optimal planning problems and constraints of the blockchain supply chain financial service platform can be obtained. The optimal unit sales subsidy incentive
The optimal expected benefits of the blockchain supply chain financial information service platform will increase with the sum of the benefits brought to the information service platform by the core enterprise using the blockchain supply chain financial platform, the core enterprise’s sales revenue function, and the maturity of blockchain technology. At this time, the expected income of the core enterprise is zero. Therefore, the better operating conditions and business capabilities of core enterprises can bring better benefits to the blockchain supply chain financial information service platform.
In an incomplete information environment, before the blockchain supply chain financial information service platform signs an incentive mechanism contract with the core enterprise, the blockchain supply chain financial information service platform as the client can only know the general situation of the agent’s core enterprise information. The true capability level of the core enterprise is hidden, and blockchain supply chain finance cannot directly observe this information. Therefore, at this time, the two parties cooperating on the alliance chain have the problem of adverse selection before signing the incentive mechanism contract. When the incentive contract is signed, the core enterprise of the agent usually chooses the level of effort based on its own rationality, while the principal’s blockchain supply chain financial service platform generally has no way to know the true level of effort of the agent’s choice, so there is a certain amount of effort at this time.
Under the asymmetric information variable, its effort level
According to the assumption of the above model, the blockchain supply chain financial service platform is known to be risk-neutral, so the expected benefits of the blockchain supply chain financial service platform are
Assuming that the retained earnings of the core enterprise is zero, the individual participation constraint (IR) is
The incentive contract of the blockchain supply chain financial information service platform can promote core enterprises to improve their sales efforts on the blockchain platform. The core company’s incentive strength is analyzed, and the incentive contract is analyzed to obtain
In order to maximize its own benefits, the blockchain supply chain financial service platform provides incentive contracts for core companies as follows:
In this study, SPSS19.0 was used for reliability analysis, and for the three inverse questions in the uncertainty variable, the question data was replaced before the reliability analysis. Reliability is an indicator of the consistency or stability of the results measured through repeated tests, or the estimated error of the measurement, to reflect the actual degree of the actual quantity. The greater the reliability of the scale, the smaller the standard error of measurement. Commonly used reliability testing methods in Likert scales are Cronbach’s
Reliability analysis results of the scale.
From Figure
Confirmatory factor analysis is to further test the relationship between latent variables and observed variables on the basis of exploratory factor analysis and test the authenticity and rationality of the hypothetical model by testing the degree of fit between the data and the hypothetical model. Generally speaking, confirmatory factor analysis is a prestep or basic framework for integrated structural equation analysis. This study uses AMOS17.0 software to perform confirmatory factor analysis to prepare for the subsequent construction of structural equation models.
The basic fitness is used to test whether the model has identification problems, data file input errors or sequence errors, etc. The measurement indicators are generally the error variance in the estimated parameters, the significance of the error variation, and the factor loading. It is generally believed that there can be no negative error variables in the estimated parameters, and all error variations must reach a significant level. The factor loading degree is between 0.5 and 0.95. The larger the factor loading, the more the index variable can be explained by the construct. The index variable can effectively reflect the characteristics of the variable to be measured.
The internal structural fit of the model is mainly used to evaluate the significance of the estimated parameters in the model, the validity and reliability of each indicator variable, etc. Generally speaking, the evaluation indicators of the model’s inherent structural fit are the scale’s
The confirmatory factor analysis results of each variable of the gestational period scale and the overall model fit analysis results are shown in Figure
Confirmation factor analysis results of the gestation period scale.
According to the confirmatory factor analysis result of the gestation period scale, it can be seen that the combined reliability and AVE value of each observation variable are both greater than 0.5, which indicates that the model has a good inherent quality. According to the analysis results of the model fit, it can be seen that except for the GFI which is slightly less than 0.90, the other fit indexes meet the requirements, which indicates that the model has a good fit.
The confirmatory factor analysis results of each variable of the growth stage scale and the overall model fit analysis results are shown in Figure
Confirmatory factor analysis results of the growth stage scale.
The confirmatory factor analysis results of each variable of the maturity scale and the overall model fit analysis results are shown in Figure
The analysis results of the overall model fit of the maturity scale.
The adaptability of the sample data of the three stages of the enterprise life cycle and the hypothesis model of this study is tested separately. According to the adaptability summary table of the AMOS output report, it can be found that all the adaptability indicators in the initial hypothesis model have not reached the ideal status. However, from the revised index table, we can find that the residual correction index among the latent variables resource dependence, uncertainty, cooperation experience, corporate reputation, trust level, and relationship commitment is relatively high. Therefore, establishing the correlation between them will significantly reduce the chi-square value and increase the significance. The comparison of the fitness of the hypothetical model before and after the correction is shown in Figure
Comparison of the fitness of the premodified hypothetical model and the postmodified hypothetical model in the mature period.
Hypothesis test results of the maturity scale.
This article considers a series of influencing factors such as core enterprise sales ability, blockchain technology maturity, sales effort level, etc.; through principal-agent and incentive mechanism theory, we design the incentive contract in the blockchain supply chain financial alliance chain under the accounts receivable model. Taking into account the possibility of failure to repay on time or bad debts due to poor management of core enterprises, a good incentive contract can effectively help the blockchain supply chain financial service platform to screen the true operating conditions of core enterprises. It can appropriately stimulate the sales level and sales effort of the core enterprise and avoid the risk of repayment. With the help of enterprise life cycle theory, this research discusses the measurement dimensions and influencing factors of the supply chain’s cross-enterprise incentive mechanism, constructs research hypothesis models for different life cycle stages, and conducts empirical analysis and hypothesis testing based on survey data. It reveals the mechanism of the supply chain’s cross-enterprise incentive mechanism based on time and vertical sequence. Based on the perspective of the enterprise life cycle, this study explores the mechanism of the incentive mechanism of different life cycle stages related influencing factors from the perspective of time and vertical sequence. This is a new attempt to study the supply chain cross-enterprise cooperation relationship. Therefore, in the choice of research methods, research approaches, and research ideas in this article, it is inevitable that they will appear imperfect due to the immature theory. This research is an exploratory empirical research. It analyzes and discusses the mechanism of the incentive mechanism of the relevant influencing factors in different stages of the enterprise life cycle and identifies the important influencing factors of the incentive mechanism in different life cycle stages and the changes in the role of influencing factors at different stages trend. Based on this, it is imperative to construct a set of incentive mechanisms suitable for different life cycles of enterprises, and future research will focus on this. Based on the theory of self-compensated trade financing, supply chain finance has played down the financial analysis and access standards for financing small- and medium-sized enterprises, shifted the focus to the control of operations, and directly infiltrated the management of risks by controlling the flow of funds and logistics. This is conducive to realizing dynamic control of risks, and at the same time realizing the risk isolation of credit subjects. Banks and other financial institutions use the credit guarantees of core enterprises in the supply chain to further reduce their own credit risks, match the flow of funds in the supply chain with the trade cycle, shorten the financing cycle, and make up for the weak operating stability of SMEs. At the same time, the trade cooperation relationship of the supply chain can be used to carry out upgraded business development from point to chain to network.
Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.
Informed consent was obtained from all individual participants included in the study references.
The author declares that there are no conflicts of interest regarding the publication of this paper.