A sales system based on a rural e-commerce platform

Abstract

The application relates to the technical field of e-commerce platforms, and discloses a sales system based on a rural e-commerce platform, which comprises a user interface module, an order management module, a merchant management module, a logistics and distribution module, a customer service module, a data analysis and optimization module, a security and conformity module and an adjustment and optimization module; the adjustment and optimization module adjusts overdue orders, transfers the orders to qualified merchants and manages the order adjustment process. The sales system based on the rural e-commerce platform can periodically identify orders that cannot be shipped on time, ensure that the system can timely discover and handle these problems in the case of insufficient inventory, avoid long waiting time of buyers, timely recommend qualified replacement merchants for the overdue orders, improve the satisfaction of the buyers, increase the exposure rate of the replacement merchants, help the merchants with sufficient inventory but low sales ranking to sell goods faster, and reduce the economic loss of the merchants.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of e-commerce platforms, and particularly relates to a sales system based on a rural e-commerce platform. BACKGROUND

[0002] The sales system based on a rural e-commerce platform is an e-commerce platform specially designed and optimized for rural areas, aiming to promote the sale of agricultural products, increase farmers' income, and improve the economic situation in rural areas. This system usually combines Internet technology, logistics distribution, payment solutions, and market promotion functions to meet the special needs of the rural market.

[0003] The existing sales system of the rural e-commerce platform has significant problems in handling inventory management and delivery time commitments, which seriously affect the transaction experience of buyers and sellers. Specifically, when a merchant's product is in short supply, i.e., the inventory is insufficient to meet the order demand, the buyer may face a long waiting time after placing an order, because the merchant needs time to restock or reproduce. In this case, the merchant often promises a shorter delivery time on the product page to attract customers, but in fact, it cannot deliver on time, resulting in the actual waiting time of the buyer far exceeding the expected time, thus causing dissatisfaction and complaints, seriously damaging the shopping experience of the buyer. On the other hand, for those merchants with sufficient inventory but low sales ranking, especially those selling fresh fruits and vegetables and seasonal vegetables, their goods are difficult to be discovered and purchased by buyers due to the lack of effective promotion and exposure, which not only affects the sales performance of these merchants, but also may cause perishable goods to deteriorate due to unsalability, resulting in economic losses. Therefore, this imbalance between supply and demand and information asymmetry not only reduces the satisfaction of buyers, but also causes operational difficulties for sellers, which overall weakens the competitiveness and user stickiness of the platform.

[0004] Therefore, it is necessary to design a sales system based on a rural e-commerce platform to solve the above problems. SUMMARY

[0005] The purpose of the present application is to solve the problems existing in the prior art and to provide a sales system based on a rural e-commerce platform.

[0006] In order to achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0007] A sales system based on a rural e-commerce platform, comprising:

[0008] User interface module: using a front-end framework to build responsive web pages and mobile applications, providing product display, search and filtering, shopping cart management, order submission, personal center and customer service functions;

[0009] Order Management Module: handles order creation, status tracking, payment, cancellation, history, timeout detection, manages order flow;

[0010] Merchant Management Module: supports merchant registration and authentication, back-end management, inventory management, order processing, logistics information setting, and shipping arrangement, helping merchants operate;

[0011] Logistics and Delivery Module: integrates logistics information, arranges delivery, provides real-time logistics tracking and delivery status updates, and manages the delivery process of goods;

[0012] Customer Service Module: provides online customer service, problem solving, after-sales service, and user feedback processing, addressing user problems and needs;

[0013] Data Analysis and Optimization Module: collects and analyzes data, monitors system performance, and processes user feedback;

[0014] Security and Compliance Module: implements data encryption storage, access control, regular security audits, and compliance checks to protect user data security;

[0015] Adjustment Optimization Module: adjusts orders that have exceeded the time limit and transfers them to eligible merchants, managing the order adjustment process.

[0016] As a preferred technical solution of the present application, the adjustment optimization module comprises:

[0017] Order Timeout Detection Unit: sets up an order timeout detection mechanism, regularly checks the status of orders, and determines whether the order has exceeded the time limit;

[0018] Alternative Merchant Recommendation Unit: sets up a merchant recommendation mechanism, which is used to recommend eligible alternative merchants for orders that have exceeded the time limit;

[0019] Buyer Selection Interface Unit: sets up a display area in the order details page to show the recommended alternative merchant information, including but not limited to name, rating, distance, and price information, and sets up operation buttons on the order display interface for the buyer to choose;

[0020] Order Transfer Processing Unit: for the alternative merchant selected by the buyer, the system updates the order status to "transferred" and records the alternative merchant information, and sends an order transfer request to the alternative merchant;

[0021] Merchant Confirmation Unit: the merchant views the order transfer request through the back-end management system and sets up an accept button and a reject button in the merchant operation interface, and the system updates the order status according to the merchant's choice;

[0022] Notification and Feedback Unit: sends real-time notifications to the buyer through various channels to inform the buyer of the changes in the order status.

[0023] As a preferred technical solution of the present application, the order timeout detection mechanism comprises:

[0024] Data setting: add user's latest waiting time for delivery T for each order in the database, and the setting of the user's latest waiting time for delivery T is constrained by the waiting time mechanism, set the order creation time as T1, calculate the order creation time T1 plus the user's latest waiting time for delivery T, and the calculated time is recorded as the delivery time;

[0025] Timing task setting: use a timing task to periodically check the order status;

[0026] Order timeout detection: read the order in the to-be-delivered state from the database, obtain the current system time and record it as T2, compare the current system time T2 with the calculated delivery time and determine whether the order is overdue;

[0027] Update the order status: update the status of the overdue order to "to-be-recommended alternative merchant".

[0028] As a preferred technical solution of the present application, the waiting time mechanism comprises:

[0029] User self-defined setting: provide an option for the user to select the latest waiting time in the order area setting page, and store the information in the order details;

[0030] System automatic setting: set a calculation model of the user's latest waiting time for delivery T considering factors including but not limited to the shelf life of goods, historical data and user behavior, calculate the value of T according to the calculation model and store it in the order details.

[0031] As a preferred technical solution of the present application, the merchant recommendation mechanism comprises but is not limited to:

[0032] Comprehensive score comparison: set a scoring model and compare the scores, and recommend the merchant with the highest score as the alternative merchant;

[0033] Priority order screening: obtain the data of the merchants from the database, select the screening factors and prioritize the screening factors, and screen the merchants according to the priority order.

[0034] As a preferred technical solution of the present application, the scoring model is:

[0035]

[0036] wherein i represents different influencing factors, n represents the total number of influencing factors, w i represents the static weight of the i-th factor, and satisfies x i represents the actual value of the i-th factor, fi (x i ) is the score function of the i-th factor, the output range is between 0-1, alpha represents the influence strength adjustment parameter, which is used to adjust the influence strength of the interaction between factors, X is a vector containing the actual values of all influencing factors, X=[x1, x2, x3…x n ], g(X) represents the function of the interaction between factors, beta is the dynamic weight adjustment parameter, h(W, X) represents the dynamic adjustment weight function, W contains a vector of all factor weights, W=[w1, w2, w3…w n

[0037] As a preferred technical solution of the present application, the priority order screening includes:

[0038] System default order: the system prioritizes the screening factors based on business logic, user experience, historical data and industry standards;

[0039] User-defined order: the system sets up a user-defined interface to allow users to rearrange the priority order of the screening factors.

[0040] As a preferred technical solution of the present application, the operation button includes:

[0041] "Select this alternative merchant": the buyer clicks this button, and the system transfers the order to the alternative merchant;

[0042] "Replace alternative merchant": the buyer clicks this button, and the system recommends a new alternative merchant for the buyer to choose;

[0043] "Cancel order": the buyer clicks this button, and the system cancels the order and automatically refunds.

[0044] As a preferred technical solution of the present application, the merchant confirmation unit further includes:

[0045] Order transfer request processing limit area: set the processing time t1 to limit the response time of the alternative merchant to the order transfer request;

[0046] Order delivery monitoring limit area: set the delivery time t2 to limit the delivery time of the alternative merchant for the transferred order.

[0047] As a preferred technical solution of the present application, the processing time t1 and the delivery time t2 are both subject to the user's latest waiting delivery time T.

[0048] The present application has the following beneficial effects:

[0049] ​1. Solving the problem of delayed delivery: Through the order timeout detection unit, the system can regularly identify orders that cannot be delivered on time. This mechanism ensures that in the case of insufficient inventory, the system can promptly identify and handle these problems, avoiding long waiting times for buyers. Once a timeout order is detected, the system can immediately take measures such as recommending alternative merchants, thereby reducing the impact of delayed delivery on buyer experience and enhancing user trust and satisfaction;

[0050] 2. Improving the shopping experience of buyers: The alternative merchant recommendation unit uses a comprehensive scoring model and priority order filtering mechanism to intelligently recommend eligible alternative merchants to buyers. Buyers can view information about multiple alternative merchants on the order details page, including name, praise rate, distance, price, and other information. By operating the keys, buyers can choose the appropriate merchant. This approach not only provides a variety of choices, but also increases transparency, allowing buyers to clearly understand the situation of each alternative merchant and make more informed decisions, thereby improving the overall shopping experience;

[0051] 3. Reducing economic losses for merchants: The alternative merchant recommendation unit helps merchants with sufficient inventory but low sales rankings to sell their goods more quickly by increasing exposure. This is particularly important for merchants selling fresh fruits and vegetables and seasonal vegetables, as slow sales can lead to product deterioration and economic losses. Through the intelligent recommendation mechanism, these merchants can gain more display opportunities, thereby increasing sales speed, reducing inventory accumulation, and reducing economic losses;

[0052] 4. Improving the operational efficiency of merchants: The merchant confirmation unit allows alternative merchants to quickly respond to order transfer requests through the back-end management system, accept or reject orders, and set processing and delivery times to clearly limit the response time and delivery time of alternative merchants. This mechanism ensures that alternative merchants can quickly handle orders, improving overall operational efficiency and reducing unnecessary waiting time, allowing merchants to better manage inventory and logistics;

[0053] 5. Ensuring transaction fairness: The comprehensive scoring comparison mechanism uses a comprehensive scoring model to recommend eligible alternative merchants based on multiple factors. This scoring mechanism ensures that all merchants are recommended on the basis of fair competition, avoiding the monopoly of a single merchant in the market. The dynamic weight adjustment function dynamically adjusts the weights of different factors based on user behavior analysis and historical data, making the scoring more reasonable and fair, further ensuring the fairness of transactions;

[0054] 6. Flexible user customization options: User customization settings allow buyers to customize the maximum waiting time for shipment when placing orders to meet their individual needs. The system can dynamically adjust the maximum waiting time for shipment based on user customization settings and other factors. This flexibility allows the system to better adapt to the needs of different users, providing more personalized services and improving user experience. At the same time, this customization option also makes the system more adaptable and flexible, capable of dealing with various complex situations. BRIEF DESCRIPTION OF DRAWINGS

[0055] Fig. 1 A schematic block diagram of the adjustment and optimization module is shown in Figure 6.

[0056] Fig. 2 A flowchart of a sales system based on a rural e-commerce platform is shown in Figure 7.

[0057] Fig. 3 A flowchart of the order timeout detection mechanism is shown in Figure 8. DETAILED DESCRIPTION

[0058] The technical solutions in the embodiments of the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, not all.

[0059] Referring to Figs. 1-3 A sales system based on a rural e-commerce platform includes:

[0060] User interface module: Use front-end framework to build responsive web pages and mobile applications, provide product display, search and filtering, shopping cart management, order submission, personal center and customer service functions;

[0061] Order management module: Handle order creation, status tracking, payment, cancellation, history, timeout detection, and manage order process;

[0062] Merchant management module: Support merchant registration and authentication, back-end management, inventory management, order processing, logistics information setting and shipment arrangement, help merchants operate;

[0063] Logistics and distribution module: Integrate logistics information, arrange distribution, provide real-time logistics tracking and distribution status update, manage commodity distribution process;

[0064] Customer service module: Provide online customer service, problem solving, after-sales service and user feedback processing, solve user problems and needs;

[0065] Data analysis and optimization module: Collect and analyze data, monitor system performance, handle user feedback;

[0066] Security and compliance module: implement data encryption storage, access control, regular security audit and compliance check to protect user data security;

[0067] Adjustment optimization module: adjust the overtime order, transfer the order to the eligible merchant, manage the order adjustment process, the adjustment optimization module includes:

[0068] Order overtime detection unit: set up an order overtime detection mechanism, regularly check the order status, and determine whether the order is overtime;

[0069] Alternative merchant recommendation unit: set up a merchant recommendation mechanism, use the mechanism to recommend eligible alternative merchants for overtime orders;

[0070] Buyer selection interface unit: set up a display area in the order details page for displaying the recommended alternative merchant information, including but not limited to name, praise rate, distance, price information, set operation buttons in the order display interface for the buyer to choose, the operation buttons include "select this alternative merchant", "change alternative merchant" and "cancel order", the buyer clicks the "select this alternative merchant" button, the system transfers the order to the alternative merchant, the buyer clicks the "change alternative merchant" button, the system recommends a new alternative merchant for the buyer to choose, the buyer clicks the "cancel order" button, the system cancels the order and automatically refunds;

[0071] Order transfer processing unit: for the alternative merchant selected by the buyer, the system updates the order status to "transferred" and records the alternative merchant information, and sends an order transfer request to the alternative merchant;

[0072] Merchant confirmation unit: the merchant checks the order transfer request through the background management system, and sets up an accept button and a reject button in the merchant operation interface, and the system updates the order status according to the merchant's choice;

[0073] Notification and feedback unit: send real-time notifications to the buyer through channels such as SMS, phone, etc. to inform the order status change.

[0074] Further, the order overtime detection mechanism includes:

[0075] Data setting: add user's latest waiting for delivery time T for each order in the database, and the setting of user's latest waiting for delivery time T is constrained by the waiting time mechanism, to ensure that the order table in the database at least contains order ID, user ID, merchant ID, product ID, order creation time, latest waiting for delivery time T and order status information, set the order creation time as T1, calculate the order creation time T1 plus the user's latest waiting for delivery time T, and the calculated time is recorded as the delivery time;

[0076] Timing task setting: use timing tasks such as Cron Job to periodically check order status, for example, run a check task once a day at 1 am;

[0077] Order timeout detection: read orders in the to-be-shipped state from the database, get the current system time and set it as T2, for each order, compare the current system time T2 with the calculated shipment time and determine whether the order is overdue, if T2 is greater than the shipment time, the order is overdue, if T2 is less than or equal to the shipment time, it indicates that the order is not overdue, it should be noted that the user's maximum waiting time T is greater than or equal to the merchant's marked shipment time, and then set a reasonable shipment time range for the user and the merchant together;

[0078] Update order status: update the status of the overdue order to "to-be-recommended alternative merchant".

[0079] Further, the waiting time mechanism includes:

[0080] User-defined settings: in the order area settings page, provide options for users to select the maximum waiting time, and store this information in the order details, specifically, add an input box on the product details page, shopping cart checkout page, or order payment interface, allowing buyers to fill in the maximum waiting time they are willing to accept, and provide clear explanatory text to explain the function of this field, for example: "Please fill in the maximum waiting time you can accept for shipment", it is worth mentioning that the user's maximum waiting time is limited to the reasonable time preset by the system administrator according to business needs and service level agreement (SLA);

[0081] System automatic settings: consider factors including but not limited to product shelf life, historical data, and user behavior to set a calculation model for the user's maximum waiting time T for shipment, calculate the value of T according to the calculation model and store it in the order details.

[0082] Embodiment one

[0083] This embodiment considers the shelf life of the product to calculate the user's maximum waiting time T for shipment, and the calculation model is:

[0084]

[0085] Where S represents the shelf life of the product, specifically, the shelf life is divided into short shelf life, medium shelf life and long shelf life, short shelf life refers to products with a shelf life of less than 1 week, such as fresh fruits and vegetables, fresh meat, etc., medium shelf life refers to products with a shelf life of between 1 week and 1 month, such as dairy products, partially processed foods, etc., long shelf life refers to products with a shelf life of more than 1 month, such as dry goods, canned goods, electronic products, books, etc., in this way, the shelf life of the product is matched with the maximum waiting time of the user, reducing the deterioration and waste of the product, and improving the satisfaction of the buyer.

[0086] Embodiment Two

[0087] This embodiment takes into account historical data factors to calculate the user's maximum waiting time T, and the calculation model is as follows:

[0088]

[0089] Where C represents the category of goods, T hist (C) represents the historical waiting time of different goods categories, N is the number of orders under this category, T j is the actual waiting time of each order, j represents the index variable, and all orders are traversed from 1 to N, represents the sum of the actual waiting time of all orders, this calculation model uses the average method, and the maximum waiting time T calculated based on historical data can bring many advantages, including data-driven decision-making, optimizing customer experience, improving operational efficiency, optimizing inventory management, enhancing prediction ability, risk management and quality control, improving transparency and trust, and cost-effectiveness, this method not only improves the flexibility and responsiveness of the system, but also provides customers with a more reliable and satisfactory delivery experience.

[0090] Embodiment Three

[0091] This embodiment takes into account user behavior factors to calculate the user's maximum waiting time T, and the calculation model is as follows:

[0092] T = (1-p) x T max + p x T min ,

[0093] Where p is the proportion of users who choose fast delivery service in their historical purchase records, if users often choose fast delivery, p is close to 1, if users rarely choose fast delivery, p is close to 0, T max is the maximum waiting time, T min is the minimum waiting time, setting the waiting time according to the user's historical behavior and preferences can provide more personalized services, by predicting the user's waiting time demand, it can more reasonably arrange logistics resources, for example, for those users who do not mind longer waiting time, it can adopt a lower-cost delivery method, achieving the purpose of optimizing resource allocation, reducing cost and improving service quality.

[0094] Further, the merchant recommendation mechanism includes but is not limited to comprehensive score comparison and priority order screening method.

[0095] Embodiment Four

[0096] The embodiment adopts a comprehensive score comparison method to recommend a substitute merchant. Specifically, a score model is set and scores are compared, and the merchant with the highest score is recommended as the substitute merchant. The score model is:

[0097]

[0098] where i represents different influencing factors, n represents the total number of influencing factors, w i represents the static weight of the i-th factor, and satisfies x i represents the actual value of the i-th factor, f i (x i ) is the score function of the i-th factor, the output range is between 0-1, a represents the influence intensity adjustment parameter, which is used to adjust the influence intensity of the interaction between factors, X is a vector containing all actual values of influencing factors, X = [x1, x2, x3…x n ], g(X) represents the function of the interaction between factors, β is a dynamic weight adjustment parameter, h(W, X) represents a dynamic adjustment weight function, W contains a vector of all factor weights, W = [w1, w2, w3…w n ], and α and β are both constants, which can be set according to actual needs;

[0099] Specifically, the influencing factors and their static weights that need to be considered are selected and set, the inventory situation, the distance between the buyer and the seller, the price difference, and the praise rate are selected as the influencing factors, and the actual values corresponding thereto are x1, x2, x3, and x4, respectively. The static weights corresponding thereto are w1=0.3, w1=0.3, w1=0.2, and w1=0.2, respectively. The score function is set for each factor.

[0100] For the inventory situation factor, the score function is:

[0101]

[0102] For the distance between the buyer and the seller factor, the score function is:

[0103] where d max is the maximum distance between the buyer and the seller;

[0104] For the price difference factor, the score function is:

[0105] where P0 represents the price of the product of the timeout order;

[0106] For the praise rate factor, the praise rate data of the merchant is directly used, and the score function is:

[0107] f4(x4) = x4;

[0108] In the scoring model, the method for setting g(X) includes:

[0109] Statistical analysis: Identify the interaction between different factors through statistical methods such as correlation analysis, regression analysis;

[0110] Machine learning model: Use machine learning models such as decision trees, random forests, neural networks, etc. to capture complex relationships between factors;

[0111] Domain knowledge: Combine professional knowledge in the business field to define specific interaction functions.

[0112] For example, when there is a synergistic effect between inventory conditions x1 and the distance between buyers and sellers x2, a product term can be set to represent this interaction:

[0113] g(X) = γ·f1(x1)·f2(x2),

[0114] Where γ is a tuning parameter that controls the strength of the interaction;

[0115] In the scoring model, the method for setting h(W, X) includes:

[0116] Feedback mechanism: Dynamically adjust the weight according to user feedback or historical data performance, for example, if a certain factor performs poorly in actual application, its weight can be reduced;

[0117] Adaptive algorithm: Use adaptive algorithms such as online learning, reinforcement learning to dynamically adjust the weight;

[0118] Rule engine: Adjust the weight based on predefined rules, for example, if the score of a certain factor is particularly low, increase its weight to increase its importance.

[0119] For example, when the weight needs to be dynamically adjusted according to the actual score of each factor, a linear adjustment function can be set:

[0120]

[0121] Where σ i is the dynamic adjustment coefficient of each factor, used to control the amplitude of weight adjustment.

[0122] Example five

[0123] This embodiment adopts the priority order screening method to recommend alternative merchants, specifically, obtaining merchant data from the database, prioritizing the screening factors, and screening in order of priority. The priority order screening includes:

[0124] System default order: the system prioritizes the filtering factors based on business logic, user experience, historical data, and industry standards. For example, considering the quality of goods and user preference for price, the system sets the priority order of different factors as follows: good review rate, price difference, inventory situation, delivery speed, and logistics service quality. Such filtering order can ensure reasonable quality and price while reducing user waiting time.

[0125] User-defined order: the system sets a user-defined interface to allow users to rearrange the priority order of filtering factors. A save button is provided to submit the user-defined priority order. When the user does not set it, the system default order is used.

[0126] Further, the merchant confirmation unit also includes an order transfer request processing restriction area, which sets a processing time t1 to limit the response time of the substitute merchant to the order transfer request. Specifically, the implementation process is as follows:

[0127] S1: the current merchant receives the order transfer request and displays a notification in the system;

[0128] S2: the system sets a processing time t1 to limit the operation time of the merchant, within which the merchant needs to choose to accept or reject the order;

[0129] S3: if the merchant does not respond within the specified time, the system automatically marks the order as "unresponsive" and selects a new substitute merchant from the list of eligible substitute merchants;

[0130] S4: the system sends the new substitute merchant information to the buyer and asks for confirmation.

[0131] If the buyer confirms the new substitute merchant, repeat the above process until a merchant accepts the order. If the buyer refuses the new substitute merchant, the system continues to select the next substitute merchant and repeats the above process.

[0132] The merchant confirmation unit also includes an order delivery monitoring restriction area, which sets a delivery time t2 to limit the delivery time of the substitute merchant for the transferred order. When the merchant accepts the order, if the delivery time t2 is not delivered, the system will send a new substitute merchant to the buyer.

[0133] Further, the processing time t1 and the delivery time t2 are both subject to the user's maximum waiting delivery time T. This constraint mechanism is derived through experimental and fitting data, which is conducive to the rational allocation of resources. For users with a longer maximum waiting delivery time T, appropriately extending the processing time t1 and the delivery time t2 can allocate delivery resources, especially resources with limited preservation conditions, to other users within the scope of the user's acceptance.

[0134] The above merely describes preferred specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art, according to the technical solution and inventive concept of the present application, makes equivalent replacement or change within the technical range disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A sales system based on a rural e-commerce platform, characterized in that, include: User Interface Module: Uses front-end frameworks to build responsive web pages and mobile applications, providing functions such as product display, search and filtering, shopping cart management, order submission, user center, and customer service; Order Management Module: Handles order creation, status tracking, payment, cancellation, historical records, timeout detection, and manages the order process; Merchant Management Module: Supports merchant registration and authentication, backend management, inventory management, order processing, logistics information settings, and shipping arrangements to help merchants operate their businesses. Logistics and Delivery Module: Integrates logistics information, arranges delivery, provides real-time logistics tracking and delivery status updates, and manages the goods delivery process; Customer service module: Provides online customer service, Q&A, after-sales service and user feedback processing to resolve user problems and needs; Data Analysis and Optimization Module: Collects and analyzes data, monitors system performance, and processes user feedback; Security and Compliance Module: Implements encrypted data storage, access control, regular security audits, and compliance checks to protect user data security; Adjustment and optimization module: Adjusts overdue orders, transfers orders to eligible merchants, and manages the order adjustment process; The adjustment and optimization module includes: Order Timeout Detection Unit: Set up an order timeout detection mechanism to periodically check the order status and determine whether the order has timed out; Alternative Merchant Recommendation Unit: Set up a merchant recommendation mechanism to recommend qualified alternative merchants for overdue orders; Buyer selection interface unit: Set up a display area on the order details page to display recommended alternative merchant information, including but not limited to name, positive review rate, distance, and price information. Set up operation buttons on the order display interface for buyers to select. Order transfer processing unit: For the alternative merchant selected by the buyer, the system updates the order status to "transferred", records the alternative merchant information, and sends an order transfer request to the alternative merchant; Merchant Confirmation Unit: Merchants can view order transfer requests through the backend management system and set accept and reject buttons in the merchant operation interface. The system updates the order status according to the merchant's selection. Notification and Feedback Unit: Sends real-time notifications to buyers through several channels to inform them of changes in order status.

2. The sales system based on a rural e-commerce platform according to claim 1, characterized in that, The order timeout detection mechanism includes: Data settings: Add a maximum waiting time T for shipment to each order in the database. The setting of the maximum waiting time T is constrained by the waiting time mechanism. Set the order creation time to T1. Calculate the order creation time T1 plus the maximum waiting time T. Record the calculated time as the time to be shipped. Scheduled task settings: Use scheduled tasks to periodically check order status; Order timeout detection: Read orders in the pending shipment status from the database, obtain the current system time and record it as T2, compare the current system time T2 with the calculated due time and determine whether the order has timed out; Update order status: Update the status of overdue orders to "Pending alternative merchant recommendation".

3. A sales system based on a rural e-commerce platform according to claim 2, characterized in that, The waiting time mechanism includes: User-defined settings: On the order area settings page, provide an option for users to select the latest waiting time, and store the user's selected latest waiting time in the order details; The system automatically sets up a calculation model for the user's latest waiting time for delivery, taking into account factors including but not limited to product shelf life, historical data, and user behavior. The value of T is calculated based on the calculation model and stored in the order details.

4. A sales system based on a rural e-commerce platform according to claim 1, characterized in that, The merchant recommendation mechanism includes, but is not limited to: Overall rating comparison: Set up a rating model and compare ratings, recommending the merchant with the highest rating as an alternative merchant; Priority-based filtering: Retrieve merchant data from the database, select filtering factors and prioritize them, then filter merchants in order of priority.

5. A sales system based on a rural e-commerce platform according to claim 4, characterized in that, The scoring model is as follows: ， Where i represents different influencing factors, n represents the total number of influencing factors, and w i Let represent the static weight of the i-th factor, and satisfy . x i f represents the actual value of the i-th factor. i (x) i ) is the score function for the i-th factor, with an output range between 0 and 1. α represents the influence strength adjustment parameter, used to adjust the influence strength of the interactions between factors. X is a vector containing the actual values ​​of all influencing factors, X = [x1, x2, x3…x...]. n Let g(X) represent the interaction function between factors, β be the dynamic weight adjustment parameter, h(W,X) represent the dynamic weight adjustment function, and W be a vector containing the weights of all factors, W = [w1, w2, w3…w...]. n ].

6. A sales system based on a rural e-commerce platform according to claim 4, characterized in that, The priority order filtering includes: System default order: The system prioritizes the selection factors based on business logic, user experience, historical data, and industry standards. User-defined order: The system has a user-defined interface that allows users to rearrange the priority order of filter factors.

7. A sales system based on a rural e-commerce platform according to claim 1, characterized in that, The operation buttons include: "Select Alternative Merchant" button: When a buyer clicks this button, the system will transfer the order to an alternative merchant; "Change Alternative Vendor" button: When a buyer clicks this button, the system will recommend new alternative vendors for the buyer to choose from; "Cancel Order" button: When the buyer clicks this button, the system cancels the order and automatically refunds the money.

8. A sales system based on a rural e-commerce platform according to claim 1, characterized in that, The merchant confirmation unit also includes: Order transfer request processing restriction area: Set processing time t1 to limit the response time of alternative merchants to order transfer requests; Order shipment monitoring restriction area: Set the shipment time t2 to restrict the shipment time of the alternative merchant for the transferred order.

9. A sales system based on a rural e-commerce platform according to claim 8, characterized in that, Both the processing time t1 and the shipping time t2 are constrained by the user's latest waiting time for shipping T.

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