A supply chain optimization method and system based on digital equity products

Abstract

The present application relates to a supply chain optimization method and system based on digital rights products, the method includes obtaining the product collection quantity and product write-off quantity of digital rights products, and performing product supply planning for digital rights products, obtaining supply plan data, obtaining supply plans and supply operation data of all suppliers, matching each supplier with a supply plan and selecting the supplier with the highest matching degree, obtaining supplier data related to the supply plan data, analyzing the supply association relationship between supplier data and supply plan data, and combining peer marketing data of similar products to build a supply chain management model for digital rights products, obtaining the supply performance data of each supplier in the supply process, inputting the supply performance data into the supply chain management model to evaluate the supply capacity, and performing supply optimization processing according to the evaluation results. The present application has the effect of improving the timeliness of supply of digital rights products.

Description

Technical Field

[0001] The present invention relates to the technical field of supply chain optimization, and in particular to a supply chain optimization method and system based on digital equity products. Background Art

[0002] At present, with the widespread use of information technology in production and life, convenient digital products are gradually replacing paper products and becoming the mainstream form of product presentation. For example, paper coupons and points cards are converted into more convenient and environmentally friendly digital rights products. In the process of using digital rights products, in order to ensure the timeliness of product use by merchants and customers, digital rights products need to be managed and controlled.

[0003] The existing supply chain of digital rights and interests products usually involves merchants negotiating with suppliers through bidding or offline contact, obtaining coupons and discounts for corresponding products, setting up digital rights and interests products based on their own profit needs, and pushing them to every user indiscriminately. However, there is information isolation between the actual use of digital rights and interests products by users and the supply of goods by suppliers. Merchants only manually adjust between users and multiple suppliers, which is not conducive to the timeliness of product supply. Therefore, it is necessary to further optimize the supply chain management method of digital rights and interests products. Summary of the invention

[0004] In order to improve the intelligence of supply chain management of digital equity products and improve the timeliness of supply of digital equity products, the present application provides a supply chain optimization method and system based on digital equity products.

[0005] In the first aspect, the above-mentioned invention objective of the present application is achieved through the following technical solutions:

[0006] A supply chain optimization method based on digital equity products, comprising:

[0007] Obtaining a product collection quantity and a product write-off quantity of a digital equity product, and performing product supply planning for the digital equity product according to the product collection quantity and the product write-off quantity to obtain supply plan data;

[0008] Obtaining the supply plans and supply operation data of all suppliers, performing supply plan matching processing on each supplier and selecting the supplier with the highest matching degree, and obtaining supplier data related to the supply plan data;

[0009] Analyze the supply association relationship between the supplier data and the supply plan data, and build a supply chain management model for the digital equity product by combining the peer marketing data of similar products;

[0010] The supply performance data of each supplier during the supply process is obtained, the supply performance data is input into the supply chain management model to evaluate the supply capacity, and supply optimization processing is performed according to the evaluation results.

[0011] By adopting the above technical solution, the actual product supply planning is carried out in combination with the actual write-off quantity of digital equity products and the product collection quantity, so as to improve the matching degree between the supply plan and the actual supply demand. In combination with the supplier's bidding supply plan and supply operation status, the current supply plan is matched and the supplier with the highest matching degree is recommended, which helps to improve the fit between the supplier and the current supply demand, and then recommend the most suitable supplier. The supply chain model is constructed in combination with the supply relationship between the supplier and the supply plan, and the marketing data of peers of similar products is used as a reference to improve the rationality of the construction of the supply chain model. Then, the supply chain of digital equity products is intelligently managed through the supply chain management model, and the intelligent supply chain management of digital equity products is improved. The supply capacity is evaluated in combination with the supply fulfillment data in the supply process, and then the suppliers with insufficient supply capacity are replaced in time, the supply chain of digital equity products is optimized in time, and the timeliness of the supply of digital equity products is improved.

[0012] In a preferred example, the present application can be further configured as follows: obtaining the supply performance data of each supplier during the supply process, inputting the supply performance data into the supply chain management model to evaluate the supply capacity, and performing supply optimization processing according to the evaluation results, specifically including:

[0013] Conduct supply risk assessment on supply chain nodes where suppliers have insufficient supply capacity, and re-screen similar suppliers based on the risk assessment results to obtain screening results for alternative suppliers;

[0014] According to the screening results of the candidate suppliers, the subsequent supply order of the digital equity product is sent to the candidate supplier for supplier replacement processing;

[0015] The inventory exhaustion time of the current product inventory and the supply transfer time period of the alternative supplier are obtained, and the supply batch adjustment process is performed on the supply transfer time period according to the inventory exhaustion time.

[0016] By adopting the above technical solution, when a supply chain node with insufficient supplier supply capacity appears in the supply chain, the supply risk assessment is carried out in time through the supply chain management model, and similar suppliers are screened again, and alternative suppliers that meet the current supply demand are screened out from similar suppliers, which helps to replace the current suppliers with insufficient supply capacity in time, reduce the risk of product out-of-stock, and send the subsequent supply orders of digital equity products to the alternative suppliers, and timely supply replacement processing is carried out for subsequent order requirements, thereby improving the timeliness of the fulfillment of subsequent supply orders. In addition, combined with the current inventory exhaustion time and the alternative supplier's transfer time cycle, the transfer time is adjusted in batches to improve the coordination between the current inventory and the alternative supply transfer.

[0017] In a preferred example, the present application may be further configured as follows: the obtaining of the product collection quantity and product write-off quantity of the digital rights product, and performing product supply planning for the digital rights product according to the product collection quantity and the product write-off quantity to obtain supply plan data, further comprising:

[0018] Obtaining the user's browsing time and product categories of the digital rights product, and performing user interest value analysis based on the product browsing time and corresponding product categories;

[0019] According to the analysis result of the user's interest value, the surrounding related products of the product category are pushed and the user's related browsing time of the surrounding related products is obtained;

[0020] Combine the related browsing time, perform product combination processing on the surrounding related products and the current digital rights product, and analyze the maximum combination discount of the product combination;

[0021] In a preferred example, the present application may be further configured as follows: the obtaining of the user's browsing time and product category of the digital rights product, and performing user interest value analysis based on the product browsing time and the corresponding product category, specifically includes:

[0022] The user interest value is calculated by formula (1), which is as follows:

[0023]

[0024] Among them, I n represents the user interest value of the nth product, ω 1 Indicates the weight of digital rights products for page sharing and saving, S n Indicates the number of times the current digital equity product has been shared, B n Indicates the number of times the current digital equity product is claimed, ω 2 represents the browsing weight of the product page, t 停 , P停 They represent the product browsing time and the corresponding browsing page stay position, P 全 Represents the full page location of a product detail page.

[0025] In a preferred example, the present application may be further configured as follows: combining the associated browsing time, performing product combination processing on the surrounding associated products and the current digital rights product, and analyzing the maximum combined discount of the product combination, further comprising:

[0026] The maximum combined discount of the product combination is calculated by formula (2), which is as follows:

[0027]

[0028] Among them, Z max represents the maximum combined discount of the product combination, Z n represents the discount value of the nth product, Z m represents the discount value of the mth surrounding related product, k m represents the correlation coefficient between the surrounding related products and the current digital equity product, ΔT represents the time difference between the associated browsing time of the mth surrounding related product and the first browsing time of the current digital equity product, and c represents the number of browsing times of the corresponding surrounding related product.

[0029] According to the maximum combination discount, a joint supply planning process is performed on the product combination, and a supply plan optimization process is performed on the single supply plan data of the digital rights product according to the joint supply planning result.

[0030] By adopting the above technical solution, combined with the push user's browsing time and product types for digital rights products, the user's interest value is analyzed, which is helpful to create a user profile and push related peripheral products, thereby improving the rationality of product push. Combined with the user's related browsing time for surrounding related products, the surrounding related products and the current digital rights products are processed into product combinations, and the maximum combination discount is planned based on the discount strength of each product. Bundled sales are carried out through product combinations, and the surrounding related products are activated. The product selection with the best discount strength is recommended to the user, and then the combined products are processed for joint supply planning and the single supply plan data of the current digital rights product is optimized. This helps to improve the supply synergy of the supply chain of multiple digital rights products.

[0031] In a preferred example, the present application can be further configured as follows: the supply plan and supply operation data of all suppliers are obtained, supply plan matching processing is performed on each supplier, and the supplier with the highest matching degree is selected, and supplier data related to the supply plan data is obtained, specifically including:

[0032] Obtain the daily write-off data of the digital rights product and the corresponding product usage scenarios, calculate the scenario write-off forecast value of the digital rights product in each product usage scenario, and adjust the supply plan of the corresponding scenario accordingly;

[0033] According to the adjustment results of the scenario supply plan, the product write-off quantity of the corresponding scenario for the next day is predicted, and the supply plan matching processing for the next day is carried out in combination with the supply plans and supply operation data of all suppliers;

[0034] According to the supply plan matching result, the supplier with the highest matching degree with the supply plan for the next day is selected, and the supplier data related to the supply plan data is obtained.

[0035] By adopting the above technical solution, the scenario write-off forecast value is calculated through the product write-off situation in different product usage scenarios, and the supply plan under the corresponding scenario is adjusted accordingly. This helps to make reasonable supply adjustments to the actual supply needs of different usage scenarios, and through the prediction of the next day's write-off quantity, the next day's supply plan is matched, and then the supplier selection process is carried out on a daily basis to obtain supplier data related to the next day's supply plan, thereby improving the matching degree between suppliers and actual supply plans.

[0036] In the second aspect, the above invention objective of the present application is achieved through the following technical solutions:

[0037] A supply chain optimization system based on digital equity products, characterized in that the system is applied to the supply chain optimization method based on digital equity products, and the system includes:

[0038] A data planning module, used to obtain the product collection quantity and product write-off quantity of the digital rights product, and to plan the product supply of the digital rights product according to the product collection quantity and the product write-off quantity, so as to obtain supply plan data;

[0039] The supply screening module is used to obtain the supply plans and supply operation data of all suppliers, match the supply plans of each supplier and select the supplier with the highest matching degree, and obtain the supplier data related to the supply plan data;

[0040] A model building module, used to analyze the supply association relationship between the supplier data and the supply plan data, and to build a supply chain management model for the digital equity product in combination with peer marketing data of similar products;

[0041] The supply optimization module is used to obtain the supply performance data of each supplier during the supply process, input the supply performance data into the supply chain management model to evaluate the supply capacity, and perform supply optimization processing based on the evaluation results.

[0042] By adopting the above technical solution, the actual product supply planning is carried out in combination with the actual write-off quantity of digital equity products and the product collection quantity, so as to improve the matching degree between the supply plan and the actual supply demand. In combination with the supplier's bidding supply plan and supply operation status, the current supply plan is matched and the supplier with the highest matching degree is recommended, which helps to improve the fit between the supplier and the current supply demand, and then recommend the most suitable supplier. The supply chain model is constructed in combination with the supply relationship between the supplier and the supply plan, and the marketing data of peers of similar products is used as a reference to improve the rationality of the construction of the supply chain model. Then, the supply chain of digital equity products is intelligently managed through the supply chain management model, and the intelligent supply chain management of digital equity products is improved. The supply capacity is evaluated in combination with the supply fulfillment data in the supply process, and then the suppliers with insufficient supply capacity are replaced in time, the supply chain of digital equity products is optimized in time, and the timeliness of the supply of digital equity products is improved.

[0043] On the third aspect, the above-mentioned purpose of the present application is achieved through the following technical solutions:

[0044] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the supply chain optimization method based on digital equity products are implemented.

[0045] Fourthly, the above-mentioned purpose of the present application is achieved through the following technical solutions:

[0046] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the supply chain optimization method based on digital equity products.

[0047] In summary, the present application includes at least one of the following beneficial technical effects:

[0048] 1. Combine the actual write-off quantity and product collection quantity of digital equity products to carry out actual product supply planning, improve the matching degree between the supply plan and the actual supply demand, and combine the supplier's bidding supply plan and supply operation status to match the current supply plan and recommend the supplier with the highest matching degree, which will help improve the fit between the supplier and the current supply demand, and then recommend the most suitable supplier, and build a supply chain model based on the supply relationship between the supplier and the supply plan, and use the marketing data of peers of similar products as a reference to improve the rationality of the supply chain model, and then use the supply chain management model to intelligently manage the supply chain of digital equity products, improve the intelligence of the supply chain management of digital equity products, and combine the supply performance data in the supply process to evaluate the supply capacity, and then timely replace suppliers with insufficient supply capacity, timely optimize the supply chain of digital equity products, and improve the timeliness of supply of digital equity products;

[0049] 2. When a supplier's supply capacity is insufficient, timely supply risk assessment is conducted through the supply chain management model, and suppliers of the same type are screened again to select alternative suppliers that meet the current supply needs. This helps to replace suppliers with insufficient supply capacity in a timely manner, reduce the risk of product out-of-stock, and send subsequent supply orders for digital equity products to alternative suppliers. Subsequent order requirements are promptly replaced to improve the timeliness of subsequent supply orders. Combined with the current inventory exhaustion time and the alternative supplier's transfer time cycle, the transfer time is adjusted in batches to improve the coordination between the current inventory and the alternative supply transfer;

[0050] 3. Analyze the user's interest value in combination with the product browsing time and product types of the pushed digital rights and interests products, which is helpful to create a user profile and push related peripheral products, improve the rationality of product push, and combine the user's related browsing time on the related peripheral products to process the product combination of the related peripheral products and the current digital rights and interests products. Combine the discount strength of each product to plan the maximum combination discount, and sell them in bundles through product combinations. Activate the related peripheral products and recommend the best discount product options for users. Then, conduct joint supply planning for the combined products and optimize the supply plan for the single supply plan data of the current digital rights and interests products, which is helpful to improve the supply coordination of the supply chain of multiple digital rights and interests products. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a flow chart for implementing a supply chain optimization method based on digital equity products in this embodiment.

[0052] Figure 2This is a flowchart for implementing joint supply based on the supply chain optimization method for digital equity products in this embodiment.

[0053] Figure 3 This is a flowchart for implementing step S20 of a supply chain optimization method based on digital equity products in this embodiment.

[0054] Figure 4 This is a flowchart for implementing step S40 of a supply chain optimization method based on digital equity products in this embodiment.

[0055] Figure 5 This is a structural block diagram of a supply chain optimization system based on digital equity products in this embodiment.

[0056] Figure 6 It is a schematic diagram of the internal structure of a computer device used to implement a supply chain optimization method based on digital equity products. DETAILED DESCRIPTION

[0057] The present application is further described in detail below in conjunction with the accompanying drawings.

[0058] In one embodiment, if Figure 1 As shown, the present application discloses a supply chain optimization method based on digital equity products, which specifically includes the following steps:

[0059] S10: Obtain the product collection quantity and product write-off quantity of the digital equity product, and plan the product supply of the digital equity product according to the product collection quantity and product write-off quantity to obtain supply plan data.

[0060] Specifically, in the process of merchants pushing digital rights and interests products to users, the product collection quantity and the actual product redemption quantity of the digital rights and interests products are obtained. In this embodiment, the product redemption quantity on the first day is used as a reference, where digital rights and interests products include merchant coupons, commodity discounts, gifts, points, etc. The supply on the first day is predicted in combination with the product collection quantity, and the later supply demand is predicted in combination with the product redemption quantity on the first day, so as to carry out product supply planning for the digital rights and interests products, that is, the daily product supply quantity, and obtain the supply plan data of the digital rights and interests products.

[0061] In this embodiment, Figure 2 As shown, step S10 also includes:

[0062] S101: Obtain the user's browsing time and product categories of digital rights products, and perform user interest value analysis based on the product browsing time and the corresponding product categories.

[0063] Specifically, the merchant pushes the digital equity product to the user end, and when the user clicks on the details introduction page of the digital equity product, the product browsing time begins to be measured, and the user's interest value is analyzed based on the product types of digital equity products browsed by the user.

[0064] Specifically, the user interest value is calculated by formula (1), which is as follows:

[0065]

[0066] Among them, I n represents the user interest value of the nth product, ω 1 Indicates the weight of digital rights products for page sharing and saving, S n Indicates the number of times the current digital equity product has been shared, B n Indicates the number of times the current digital equity product is claimed, ω 2 represents the browsing weight of the product page, t 停 , P 停 They represent the product browsing time and the corresponding browsing page stay position, P 全 Represents the full page location of a product detail page.

[0067] S102: According to the analysis result of the user interest value, the surrounding related products of the product category are pushed and the user's related browsing time of the surrounding related products is obtained.

[0068] Specifically, combined with the results of user interest value analysis, an association analysis is performed on the surrounding related products of the product category. For example, the surrounding related products of fast food products are beverages, fruits, etc., and then combined with the results of user interest value analysis, the surrounding related products of product categories with higher interest values ​​are pushed and processed, and when the user clicks on the surrounding related products to view the details, the user's associated browsing time for the surrounding related products is obtained.

[0069] S103: Combining the surrounding related products with the current digital rights product in combination with the related browsing time, and analyzing the maximum combined discount of the product combination.

[0070] Specifically, the maximum combined discount of the product combination is calculated by formula (2), and formula (2) is as follows:

[0071]

[0072] Among them, Z max represents the maximum combined discount of the product combination, Z n represents the discount value of the nth product, Z m represents the discount value of the mth surrounding related product, k mrepresents the correlation coefficient between the surrounding related products and the current digital equity product, ΔT represents the time difference between the associated browsing time of the mth surrounding related product and the first browsing time of the current digital equity product, and c represents the number of browsing times of the corresponding surrounding related product.

[0073] S104: Process the joint supply planning of the product combination according to the maximum combination discount, and optimize the supply plan of the single supply plan data of the digital rights product according to the joint supply planning result.

[0074] Specifically, based on the maximum combination discount, a joint supply plan is made for the product combination, such as making supply arrangements for each product in the product combination in proportion, optimizing the supply plan data of the single digital rights product based on the supply arrangement of each product, and replacing the supply plan of the single digital rights product with the combined joint supply planning data.

[0075] S20: Obtain the supply plans and supply operation data of all suppliers, perform supply plan matching processing on each supplier and select the supplier with the highest matching degree, and obtain supplier data related to the supply plan data.

[0076] Specifically, obtain the bidding and supply plans of all suppliers to parse and obtain each supplier's supply plan for the current digital equity product, and combine the supply operation data provided by each supplier, that is, the supply operation capacity of the current digital equity product, to match the supply plan of each supplier, such as Figure 3 As shown, step S20 includes:

[0077] S201: Obtain the daily write-off data of digital rights and interests products and the corresponding product usage scenarios, calculate the scenario write-off forecast value of the digital rights and interests products in each product usage scenario, and adjust the supply plan of the corresponding scenario accordingly.

[0078] Specifically, based on the daily redemption data of digital equity products in each usage scenario, such as shopping malls of different sizes, and the corresponding product usage scenarios, the main differences in product usage scenarios are the differences in traffic flow and consumption levels. The ratio between the daily redemption data and the total number of product collections is used as the scenario redemption forecast value for each product usage scenario, and the supply plan for the corresponding scenario is adjusted accordingly. When the scenario redemption forecast value is smaller, the corresponding supply quantity on the second day will be reduced accordingly. When the scenario redemption forecast value is larger, the corresponding supply quantity on the second day will increase accordingly.

[0079] S202: Based on the scenario supply plan adjustment results, predict the next day's product write-off quantity of the corresponding scenario, and combine the supply plans and supply operation data of all suppliers to perform supply plan matching processing for the next day.

[0080] Specifically, according to the supply plan adjustment results of the scenario, the difference between the actual write-off quantity and the supply plan quantity of each day is obtained. When the difference is greater than or equal to the difference threshold, the actual write-off quantity of the previous day is used as the forecast value of the product write-off quantity of the next day for the corresponding scenario. When the difference is less than the difference threshold, the supply plan quantity of the previous day is used as the forecast value of the product write-off quantity of the next day for the corresponding scenario. In addition, the supply plan and supply operation data of all suppliers are combined to rematch the supply plan of the next day with the supplier's supply plan to obtain the supply plan matching result for the next day.

[0081] S203: According to the supply plan matching result, the supplier with the highest matching degree with the supply plan for the next day is selected to obtain supplier data related to the supply plan data.

[0082] Specifically, based on the supply plan matching results, the supplier with the highest degree of match with the next day's supply plan is selected, and supplier matching is carried out based on multiple dimensions such as supply speed, supply distance, supply quality, and number of cooperation times, so as to obtain supplier data related to each day's supply plan data.

[0083] S30: Analyze the supply correlation between supplier data and supply plan data, and build a supply chain management model for digital equity products by combining peer marketing data of similar products.

[0084] Specifically, the supply correlation relationship between the supplier data and the supply plan data is analyzed by combining the supplier data, that is, the supply arrangement and the corresponding supply plan planned for the current digital rights and interests product, and the supply arrangement and the supply plan data are correlated on a daily basis. The supply correlation relationship is further correlated based on the daily changes in supply fulfillment, supply inventory, and supply profit and loss. Combined with the peer marketing data of similar products, such as the coordination between the supply and shipment of the current type of products by peers, a supply chain management model for digital rights and interests products is constructed to obtain a supply chain management model for the supply chain management of digital rights and interests products.

[0085] S40: Obtain the supply performance data of each supplier during the supply process, input the supply performance data into the supply chain management model to evaluate the supply capacity, and perform supply optimization processing based on the evaluation results.

[0086] Specifically, Figure 4 As shown, step S40 includes:

[0087] S401: Conduct supply risk assessment on supply chain nodes where suppliers have insufficient supply capacity, and re-screen similar suppliers based on the risk assessment results to obtain candidate supplier screening results.

[0088] Specifically, when the supplier's supply capacity is insufficient, such as obtaining the supplier's supply performance data for the current supply plan, including compliant performance and non-compliant performance. Non-compliant performance means not supplying in accordance with the specified product quantity, quality or delivery speed, or the supplier's existing inventory cannot meet the supply plan for the next day, then the current supplier's supply capacity is judged to be insufficient, and the current supply chain node position is marked as a supply chain node with insufficient supply capacity. The supply risk assessment is performed based on the impact of the current insufficient supply capacity on upstream or downstream suppliers. When the impact on adjacent suppliers exceeds the preset value, it is judged that the current supply chain node has a supply risk, and it is necessary to re-screen similar suppliers based on the supply type of the risky supplier to obtain the screening results of alternative suppliers.

[0089] S402: Based on the screening results of the alternative suppliers, the subsequent supply orders of the digital rights products are sent to the alternative suppliers for supplier replacement.

[0090] Specifically, based on the screening results of alternative suppliers, subsequent supply orders of digital equity products will be sent to alternative suppliers for supplier replacement, that is, the alternative suppliers will replace the original suppliers and be responsible for subsequent supply orders.

[0091] S403: Obtain the inventory exhaustion time of the current product inventory and the supply transfer time cycle of the alternative supplier, and adjust the supply batch to the supply transfer time cycle according to the inventory exhaustion time.

[0092] Specifically, the inventory depletion time of the current product inventory is calculated based on the current product inventory quantity and product write-off speed, and the supply batches are adjusted based on the time period required for alternative suppliers to transfer or replenish products from other inventory points or manufacturers. For example, within the time period for the manufacturer to replenish the product, batches are adjusted from the nearest warehouse with excess inventory according to the next supply plan until the supply plan requirements for the next day are met.

[0093] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0094] In one embodiment, a supply chain optimization system based on digital equity products is provided, and the supply chain optimization system based on digital equity products corresponds one-to-one to the supply chain optimization method based on digital equity products in the above embodiment. Figure 5 As shown in the figure, the supply chain optimization system based on digital equity products includes a data planning module, a supply screening module, a model building module and a supply optimization module. The detailed description of each functional module is as follows:

[0095] The data planning module is used to obtain the product collection quantity and product write-off quantity of the digital equity product, and to plan the product supply of the digital equity product based on the product collection quantity and product write-off quantity to obtain the supply plan data.

[0096] The supply screening module is used to obtain the supply plans and supply operation data of all suppliers, match the supply plans of each supplier and select the supplier with the highest matching degree to obtain the supplier data related to the supply plan data.

[0097] The model building module is used to analyze the supply correlation relationship between supplier data and supply plan data, and to build a supply chain management model for digital equity products in combination with peer marketing data of similar products.

[0098] The supply optimization module is used to obtain the supply performance data of each supplier during the supply process, input the supply performance data into the supply chain management model to evaluate the supply capacity, and perform supply optimization based on the evaluation results.

[0099] Preferably, the supply optimization module specifically includes:

[0100] The merchant screening submodule is used to conduct supply risk assessment on supply chain nodes where suppliers have insufficient supply capacity, and to re-screen similar suppliers based on the risk assessment results to obtain screening results for alternative suppliers.

[0101] The merchant replacement submodule is used to send subsequent supply orders of digital equity products to alternative suppliers for supplier replacement processing based on the screening results of alternative suppliers.

[0102] The supply adjustment submodule is used to obtain the inventory exhaustion time of the current product inventory and the supply transfer time cycle of the alternative supplier, and adjust the supply batch to the supply transfer time cycle according to the inventory exhaustion time.

[0103] Preferably, the data planning module also includes:

[0104] The data analysis submodule is used to obtain the user's browsing time and product categories for digital equity products, and to analyze the user's interest value based on the product browsing time and the corresponding product categories.

[0105] The data push submodule is used to push related products of the product category according to the analysis results of the user's interest value, and obtain the user's related browsing time of the related products.

[0106] The product combination submodule is used to combine the surrounding related products with the current digital rights products according to the related browsing time, and analyze the maximum combination discount of the product combination.

[0107] The supply optimization submodule is used to process the joint supply planning of the product combination according to the maximum combination discount, and to optimize the supply plan of the single supply plan data of the digital rights product according to the joint supply planning results.

[0108] Preferably, the data analysis submodule specifically includes:

[0109] The user interest value is calculated by formula (1), which is as follows:

[0110]

[0111] Among them, I n represents the user interest value of the nth product, ω 1 Indicates the weight of digital rights products for page sharing and saving, S n Indicates the number of times the current digital equity product has been shared, B n Indicates the number of times the current digital equity product is claimed, ω 2 represents the browsing weight of the product page, t 停 , P 停 They represent the product browsing time and the corresponding browsing page stay position, P 全 Represents the full page location of a product detail page.

[0112] Preferably, the product combination submodule further includes:

[0113] The maximum combined discount of the product combination is calculated by formula (2), which is as follows:

[0114]

[0115] Among them, Z max represents the maximum combined discount of the product combination, Z n represents the discount value of the nth product, Z m represents the discount value of the mth surrounding related product, k m represents the correlation coefficient between the surrounding related products and the current digital equity product, ΔT represents the time difference between the associated browsing time of the mth surrounding related product and the first browsing time of the current digital equity product, and c represents the number of browsing times of the corresponding surrounding related product.

[0116] Preferably, the supply screening module specifically includes:

[0117] The plan adjustment submodule is used to obtain the daily write-off data of digital equity products and the corresponding product usage scenarios, calculate the scenario write-off forecast value of digital equity products in each product usage scenario, and adjust the supply plan of the corresponding scenario accordingly.

[0118] The plan matching submodule is used to predict the product write-off quantity of the next day for the corresponding scenario based on the supply plan adjustment results of the scenario, and to match the supply plan for the next day in combination with the supply plans and supply operation data of all suppliers.

[0119] The merchant recommendation submodule is used to recommend the supplier with the highest matching degree with the next day's supply plan based on the supply plan matching results, and obtain the supplier data related to the supply plan data.

[0120] For the specific definition of the supply chain optimization system based on digital equity products, please refer to the definition of the supply chain optimization method based on digital equity products above, which will not be repeated here. Each module in the above-mentioned supply chain optimization system based on digital equity products can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0121] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 6 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data in the process of supply chain optimization of digital equity products. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a supply chain optimization method based on digital equity products is implemented.

[0122] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of a supply chain optimization method based on digital equity products are implemented.

[0123] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0124] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0125] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A supply chain optimization method based on digital equity products, characterized in that: include: Obtaining a product collection quantity and a product write-off quantity of a digital equity product, and performing product supply planning for the digital equity product according to the product collection quantity and the product write-off quantity to obtain supply plan data; Obtaining the supply plans and supply operation data of all suppliers, performing supply plan matching processing on each supplier and selecting the supplier with the highest matching degree, and obtaining supplier data related to the supply plan data; Analyze the supply association relationship between the supplier data and the supply plan data, and build a supply chain management model for the digital equity product by combining the peer marketing data of similar products; Obtaining the supply performance data of each supplier during the supply process, inputting the supply performance data into the supply chain management model to evaluate the supply capacity, and performing supply optimization processing according to the evaluation results; The obtaining of the supply performance data of each supplier during the supply process, inputting the supply performance data into the supply chain management model to evaluate the supply capacity, and performing supply optimization processing according to the evaluation results specifically includes: Conduct supply risk assessment on supply chain nodes where suppliers have insufficient supply capacity, and re-screen similar suppliers based on the risk assessment results to obtain screening results for alternative suppliers; According to the screening results of the candidate suppliers, the subsequent supply order of the digital equity product is sent to the candidate supplier for supplier replacement processing; Obtain the inventory exhaustion time of the current product inventory and the supply transfer time period of the alternative supplier, and adjust the supply batch for the supply transfer time period according to the inventory exhaustion time; The analyzing the supply association relationship between the supplier data and the supply plan data, and combining the peer marketing data of similar products to construct a supply chain management model for the digital rights product, includes: In combination with the supplier's supply arrangements and corresponding supply plans for current digital rights and interests products, the supply correlation relationship between supplier data and supply plan data is analyzed, the supply arrangement and supply plan data are correlated on a daily basis, and the supply correlation relationship is further correlated based on the daily changes in supply fulfillment, supply inventory, and supply profit and loss. The supply chain management model for digital rights and interests products is constructed in combination with the marketing data of peers of similar products, and a supply chain management model for supply chain management of digital rights and interests products is obtained.

2. The supply chain optimization method based on digital equity products according to claim 1 is characterized in that: The obtaining of the product collection quantity and product write-off quantity of the digital rights product, and performing product supply planning for the digital rights product according to the product collection quantity and the product write-off quantity to obtain supply plan data, further includes: Obtaining the user's browsing time and product categories of the digital rights product, and performing user interest value analysis based on the product browsing time and corresponding product categories; According to the analysis result of the user's interest value, the surrounding related products of the product category are pushed and the user's related browsing time of the surrounding related products is obtained; Combine the related browsing time, perform product combination processing on the surrounding related products and the current digital rights product, and analyze the maximum combination discount of the product combination; According to the maximum combination discount, a joint supply planning process is performed on the product combination, and a supply plan optimization process is performed on the single supply plan data of the digital rights product according to the joint supply planning result.

3. The supply chain optimization method based on digital equity products according to claim 2 is characterized in that: The obtaining of the user's browsing time and product category of the digital rights product, and performing user interest value analysis according to the product browsing time and the corresponding product category, specifically includes: The user interest value is calculated by formula (1), which is as follows: （1）； in, Indicates User interest value of a product, Indicates the weight of digital rights products for page sharing and saving. Indicates the number of times the current digital equity product has been shared. Indicates the number of times the current digital rights product has been redeemed. Indicates the browsing weight of the product page. , They represent the product browsing time and the corresponding browsing page stay position respectively. Represents the full page location of a product detail page.

4. The supply chain optimization method based on digital equity products according to claim 3 is characterized in that: The combining of the associated browsing time, performing product combination processing on the surrounding associated products and the current digital rights product, and analyzing the maximum combined discount of the product combination, further includes: The maximum combined discount of the product combination is calculated by formula (2), which is as follows: （2）； in, represents the maximum combined discount for a product combination, Indicates The discount value of the product, Indicates Discount value of surrounding related products, Indicates the correlation coefficient between the surrounding related products and the current digital equity product. Indicates The time difference between the associated browsing time of the surrounding associated products and the first browsing time of the current digital equity product, Indicates the number of views of the corresponding surrounding related products.

5. The supply chain optimization method based on digital equity products according to claim 1 is characterized in that: The obtaining of the supply plans and supply operation data of all suppliers, matching the supply plans of each supplier and selecting the supplier with the highest matching degree, and obtaining the supplier data related to the supply plan data specifically include: Obtain the daily write-off data of the digital rights product and the corresponding product usage scenarios, calculate the scenario write-off forecast value of the digital rights product in each product usage scenario, and adjust the supply plan of the corresponding scenario accordingly; According to the adjustment results of the scenario supply plan, the product write-off quantity of the corresponding scenario for the next day is predicted, and the supply plan matching processing for the next day is carried out in combination with the supply plans and supply operation data of all suppliers; According to the supply plan matching result, the supplier with the highest matching degree with the supply plan for the next day is selected, and the supplier data related to the supply plan data is obtained.

6. A supply chain optimization system based on digital equity products, characterized in that: The system is applied to the supply chain optimization method based on digital equity products according to any one of claims 1 to 5 above, and the system includes: A data planning module, used to obtain the product collection quantity and product write-off quantity of the digital rights product, and to plan the product supply of the digital rights product according to the product collection quantity and the product write-off quantity, so as to obtain supply plan data; The supply screening module is used to obtain the supply plans and supply operation data of all suppliers, match the supply plans of each supplier and select the supplier with the highest matching degree, and obtain the supplier data related to the supply plan data; A model building module, used to analyze the supply association relationship between the supplier data and the supply plan data, and to build a supply chain management model for the digital equity product in combination with peer marketing data of similar products; A supply optimization module is used to obtain the supply performance data of each supplier during the supply process, input the supply performance data into the supply chain management model to evaluate the supply capacity, and perform supply optimization processing according to the evaluation results; Wherein, the supply optimization module specifically includes: The merchant screening submodule is used to conduct supply risk assessment on supply chain nodes where suppliers have insufficient supply capacity, and to screen similar suppliers again based on the risk assessment results to obtain the screening results of alternative suppliers; A merchant replacement submodule, for sending subsequent supply orders of the digital rights and interests products to alternative suppliers for supplier replacement processing according to the screening results of the alternative suppliers; A supply adjustment submodule is used to obtain the inventory exhaustion time of the current product inventory and the inventory transfer time period of the alternative supplier, and to adjust the supply batches of the inventory transfer time period according to the inventory exhaustion time; Wherein, the model building module includes: In combination with the supplier's supply arrangements and corresponding supply plans for current digital rights and interests products, the supply correlation relationship between supplier data and supply plan data is analyzed, the supply arrangement and supply plan data are correlated on a daily basis, and the supply correlation relationship is further correlated based on the daily changes in supply fulfillment, supply inventory, and supply profit and loss. The supply chain management model for digital rights and interests products is constructed in combination with the marketing data of peers of similar products, and a supply chain management model for supply chain management of digital rights and interests products is obtained.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the supply chain optimization method based on digital equity products as described in any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the supply chain optimization method based on digital equity products as described in any one of claims 1 to 5 are implemented.

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