The decision equilibrium point of online supply chain finance is realized in a multi-party game with linkage characteristics [1]. The model is embodied as multi-dimensional variables with correlation under comprehensive operational decision-making. The content includes production decisions of core enterprises, financing choices, ordering and sales decisions, pledge rate and interest rate decisions of financing platforms, action choices, and pricing decisions of third-party logistics enterprises. Under this multi-dimensional equilibrium, this paper will study the achievable benefit coordination of individuals and the overall achievable value increase.

1) Manufacturer ^{m}^{s}^{l}^{m}^{m}^{s}^{s}^{l}^{l}

Other symbols and variables used by the model are defined as follows:
^{m}^{s}^{l}^{s}^{m}^{s}^{l}^{m}^{s}^{l}

Proposition 1: The retailer's final financing amount

When

The supplier's income comes from two aspects: one is the sales profit

In the game between the supplier and the retailer in the supply chain, the supplier expects the retailer to pay the optimal level of sales effort to maximize the individual benefit.
^{s}

When the sales revenue realized under the order quantity

Substitute the above formula into formula (1) when

When

The order quantity
^{s}

Under this financing limit, the principal-agent relationship between the supplier and the retailer is still given by the objective function in Eq. (5). Substitute the suboptimal solution

The financing limit

Proposition 2: When faced with financing constraints

The establishment of an online supply chain financing platform is conducive to establishing a multi-level financial service system and promotes the reform of the financial system [9]. The benefits of the SME financing market development in the supply chain are mainly reflected in the following aspects: First, the intermediate business income

According to the utility functions of suppliers and retailers in equations (3) and (4), we can get:
_{m}_{n}

When

Equations (15) and (16) respectively represent the correlation between the unknown coefficient
^{s}

At time

When the wholesale price and the sales price are a certain stable value, the order quantity under the optimal solution of the two sets of game relations can be determined simultaneously [10]. At this time, financing platforms and suppliers can obtain maximum benefits. At this point, the retailer gets the average industry rate of return. The following proposition gives the above conclusion:

Proposition 3: When the financing limit stipulated by the financing platform does not have a substantial impact
^{s}

The income distribution coefficient ^{s}

Warehousing companies have only two actions to choose from, and each action is a one-dimensional variable representing the level of effort. The probability that the financing platform observes that the warehousing enterprise's effort level is
^{l}

The utility functions of warehousing companies in the first two cases are:

The platform hopes that warehousing companies can choose the optimal effort level

Among them, the retention utility of warehousing enterprises is reflected in the average income in the industry under the effort cost, namely:

When ^{l}^{l}

This formula can calculate the maximum value of ^{l}

In summary, the following propositions can be obtained:

Proposition 4: The platform pays the warehousing enterprises corresponding rewards with the income distribution coefficient ^{l}^{l}

According to formula (1), the data simulation of self-owned funds is carried out. Suppose that market demand

The retailer's financing amount changes with its funds when there is no financing constraint

Serial number | Private capital | Financing amount | Initial margin | Own funds for self-ordering |
---|---|---|---|---|

1 | 250 | 1166.67 | 250 | 0 |

2 | 290 | 1266.67 | 290 | 0 |

3 | 400 | 1222.22 | 400 | 0 |

4 | 440 | 1451.71 | 425.42 | 0 |

5 | 500 | 1265.71 | 409.71 | 90.29 |

6 | 550 | 1294.29 | 299.29 | 161.71 |

7 | 650 | 1151.42 | 245.42 | 204.57 |

8 | 790 | 965.71 | 299.71 | 490.29 |

9 | 990 | 665.71 | 199.71 | 790.29 |

10 | 1200 | 265..71 | 109.71 | 1090.29 |

11 | 1456 | 0 | 0 | 1456 |

12 | 1500 | 0 | 0 | 1456 |

When there is no substantial financing limit, the optimal order quantity
^{s}

If the financing limit

Benefit Comparison of Retailers Financing or Not Without Financing Constraints

Private capital | Financing amount | Expected sales | Earnings from financing | Earnings without financing |
---|---|---|---|---|

250 | 72 | 68 | 426.67 | 252 |

280 | 78 | 75 | 450.67 | 276 |

400 | 82 | 78 | 478.61 | 200 |

440 | 81 | 86 | 508.41 | 224 |

500 | 81 | 86 | 516.26 | 272 |

550 | 81 | 86 | 521.88 | 408 |

650 | 81 | 86 | 522.41 | 480 |

780 | 81 | 86 | 548.26 | 576 |

880 | 81 | 86 | 572.26 | 672 |

1200 | 81 | 86 | 586.22 | 800 |

1456 | 81 | 86 | 1082 | 1082 |

1500 | 81 | 86 | 1082 | 1082 |

At this time, from Proposition 3, it can be known that the revenue sharing coefficient available to suppliers is 0.06. When the revenue-sharing coefficient is constant, the available revenue of the supplier is consistent with the change of the revenue function realized by the retailer.

When the financing limit constitutes a financing constraint for the retailer, the retailer can only realize the suboptimal solution under the financing constraint.

The retailer's available financing and sub-optimal order volume change with its funds under financing constraints

Private capital | Ideal financing amount | Financing amount under financing limit | Order amount |
---|---|---|---|

400 | 1333.33 | 1280 | 81 |

440 | 1451.43 | 1280 | 83 |

500 | 1365.71 | 1280 | 87 |

550 | 1294.29 | 1280 | 90 |

The retailer can only achieve sub-optimal order quantities when the financing limit has a substantially limiting effect. Out-of-stock losses make it impossible to achieve the maximum profit under the optimal order quantity.

The research of this paper explores the feasibility of the “online supply chain finance + revenue-sharing contract” business model. In this context, all parties involved can achieve symbiosis and co-prosperity. The transaction decision and benefit distribution coefficient value determined by the game share the value-added after the financing of the industrial chain is out of trouble. The research theory of the article provides a reference for the financing dilemma of industrial enterprises that needs to be solved in the process of financial system reform and development and industrial transformation and upgrading.

#### Benefit Comparison of Retailers Financing or Not Without Financing Constraints

Private capital | Financing amount | Expected sales | Earnings from financing | Earnings without financing |
---|---|---|---|---|

250 | 72 | 68 | 426.67 | 252 |

280 | 78 | 75 | 450.67 | 276 |

400 | 82 | 78 | 478.61 | 200 |

440 | 81 | 86 | 508.41 | 224 |

500 | 81 | 86 | 516.26 | 272 |

550 | 81 | 86 | 521.88 | 408 |

650 | 81 | 86 | 522.41 | 480 |

780 | 81 | 86 | 548.26 | 576 |

880 | 81 | 86 | 572.26 | 672 |

1200 | 81 | 86 | 586.22 | 800 |

1456 | 81 | 86 | 1082 | 1082 |

1500 | 81 | 86 | 1082 | 1082 |

#### The retailer's available financing and sub-optimal order volume change with its funds under financing constraints

Private capital | Ideal financing amount | Financing amount under financing limit | Order amount |
---|---|---|---|

400 | 1333.33 | 1280 | 81 |

440 | 1451.43 | 1280 | 83 |

500 | 1365.71 | 1280 | 87 |

550 | 1294.29 | 1280 | 90 |

#### The retailer's financing amount changes with its funds when there is no financing constraint

Serial number | Private capital | Financing amount | Initial margin | Own funds for self-ordering |
---|---|---|---|---|

1 | 250 | 1166.67 | 250 | 0 |

2 | 290 | 1266.67 | 290 | 0 |

3 | 400 | 1222.22 | 400 | 0 |

4 | 440 | 1451.71 | 425.42 | 0 |

5 | 500 | 1265.71 | 409.71 | 90.29 |

6 | 550 | 1294.29 | 299.29 | 161.71 |

7 | 650 | 1151.42 | 245.42 | 204.57 |

8 | 790 | 965.71 | 299.71 | 490.29 |

9 | 990 | 665.71 | 199.71 | 790.29 |

10 | 1200 | 265..71 | 109.71 | 1090.29 |

11 | 1456 | 0 | 0 | 1456 |

12 | 1500 | 0 | 0 | 1456 |

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