Sales system based on rural e-commerce platform

Abstract

The invention 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 conformance module and an adjustment and optimization module, and the adjustment optimization module adjusts the overtime orders, transfers the orders to merchants meeting conditions, and manages the order adjustment process. The sales system based on the rural e-commerce platform provided by the invention can regularly identify orders which cannot be delivered on time, ensures that the system can timely discover and process the problems under the condition of insufficient inventory, avoids time waiting for buying parents, can timely recommend substitute merchants meeting conditions for overtime orders, and improves the sales efficiency. And secondly, the exposure rate of replacing merchants can be increased, merchants with sufficient stock but low sales ranking are helped to sell commodities more quickly, and the economic loss of the merchants is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of e-commerce platforms, and in particular to a sales system based on a rural e-commerce platform. Background Art

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

[0003] The sales systems of existing rural e-commerce platforms have significant problems in dealing with inventory management and delivery time commitments. These problems seriously affect the transaction experience of buyers and sellers. Specifically, when the merchant's products are in short supply, that is, the inventory is not enough to meet the order requirements, buyers may face a long wait after placing an order because the merchant needs time to replenish or re-produce. In this case, in order to attract customers, merchants often promise a shorter delivery time on the product page, but in fact they cannot deliver on time, causing the buyer's actual waiting time to far exceed expectations, thereby causing dissatisfaction and complaints, and seriously damaging the buyer's shopping experience; on the other hand, for those merchants with sufficient inventory but low sales rankings, especially those selling fresh fruits and vegetables and seasonal vegetables, due to the lack of effective promotion and exposure, their products are difficult to be discovered and purchased by buyers, which not only affects the sales performance of these merchants, but may also cause perishable goods to deteriorate due to unsalable goods, causing economic losses. Therefore, this problem of supply and demand imbalance and information asymmetry not only reduces buyer satisfaction, but also brings operational troubles to sellers, and overall weakens the platform's competitiveness and user stickiness.

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

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a sales system based on a rural e-commerce platform.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

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

[0008] User interface module: Use the 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, and manages order processes;

[0010] Merchant management module: supports merchant registration and authentication, background management, inventory management, order processing, logistics information setting and delivery arrangement to help merchants operate;

[0011] Logistics and distribution module: integrates logistics information, arranges distribution, provides real-time logistics tracking and distribution status updates, and manages the product distribution process;

[0012] Customer service module: provides online customer service, question answering, after-sales service and user feedback processing to solve user problems and needs;

[0013] Data analysis and optimization module: collect and analyze data, monitor system performance, and process user feedback;

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

[0015] Adjustment and optimization module: adjust overdue orders, transfer orders to eligible merchants, and manage the order adjustment process.

[0016] As a preferred technical solution of the present invention, the adjustment and optimization module includes:

[0017] Order timeout detection unit: set up an order timeout detection mechanism to regularly check the order status and determine whether the order has timed out;

[0018] Alternative merchant recommendation unit: set up a merchant recommendation mechanism, and use this mechanism to recommend qualified alternative merchants for overdue orders;

[0019] Buyer selection interface unit: a display area is set in the order details page to display recommended alternative merchant information, including but not limited to name, favorable review rate, distance, price information, and operation buttons are set in the order display interface for buyers to select;

[0020] 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;

[0021] Merchant confirmation unit: The merchant checks the order transfer request through the backend management system and sets the accept button and reject button in the merchant operation interface. The system updates the order status according to the merchant's selection;

[0022] Notification and feedback unit: Send real-time notifications to buyers through several channels to inform them of order status changes.

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

[0024] Data setting: Add the latest waiting time T for each order in the database, and the latest waiting time T is subject to the waiting time mechanism. Set the order creation time to T1, calculate the order creation time T1 plus the latest waiting time T, and record the calculated time as the delivery time.

[0025] Scheduled task settings: Use scheduled tasks to regularly check order status;

[0026] Order timeout detection: read the orders in the waiting-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 has timed out;

[0027] Update order status: Update the status of overdue orders to "pending recommendation of alternative merchants".

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

[0029] User-defined settings: On the order area settings page, provide options for users to select the latest waiting time and store this information in the order details;

[0030] Automatic system settings: Considering factors including but not limited to product shelf life, historical data, and user behavior, a calculation model for the user's latest waiting time T for delivery is set, and the value of T is calculated based on the calculation model and stored in the order details.

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

[0032] Comprehensive rating comparison: Set a rating model and compare ratings, recommending the merchant with the highest rating as an alternative merchant;

[0033] Priority screening: Get the merchant data from the database, select screening factors and prioritize the screening factors, and screen the merchants in order of priority.

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

[0035]

[0036] Among them, i represents different influencing factors, n represents the total number of influencing factors, and 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, and the output range is between 0 and 1. α represents the influence intensity adjustment parameter, which is used to adjust the influence intensity 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 interaction function between factors, β is the dynamic weight adjustment parameter, h(W, X) represents the dynamic weight adjustment function, W contains the vector of all factor weights, W = [w1, w2, w3…w n ].

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

[0038] System default order: The system prioritizes 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, allowing users to choose to rearrange the priority order of screening factors.

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

[0041] "Select this alternative merchant": When the buyer clicks this button, the system will transfer the order to the alternative merchant;

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

[0043] “Cancel Order”: When the buyer clicks this button, the system cancels the order and automatically refunds the money.

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

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

[0046] Order delivery monitoring restricted area: Set the delivery time t2, and for the transferred orders, restrict the delivery time of the alternative merchant.

[0047] As a preferred technical solution of the present invention, the processing time t1 and the delivery time t2 are both constrained by the latest waiting time T for delivery by the user.

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

[0049] 1. Solve the problem of delayed delivery: Through the order timeout detection unit, the system can regularly identify orders that cannot be shipped on time. This mechanism ensures that in the case of insufficient inventory, the system can promptly detect and handle these problems to avoid buyers waiting for a long time. 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 the buyer experience and enhancing user trust and satisfaction;

[0050] 2. Improve buyers' shopping experience: The alternative merchant recommendation unit uses a comprehensive scoring model and priority screening mechanism to intelligently recommend qualified alternative merchants to buyers. Buyers can view the information of multiple alternative merchants on the order details page, including name, praise rate, distance, price, etc., and select the appropriate merchant by pressing buttons. This method not only provides diversified choices, but also increases transparency, allowing buyers to clearly understand the situation of each alternative merchant, so as to make more informed decisions and improve the overall shopping experience;

[0051] 3. Reduce economic losses of merchants: The alternative merchant recommendation unit helps merchants with sufficient inventory but low sales rankings sell goods faster by increasing exposure. This is especially important for merchants selling fresh fruits and seasonal vegetables, because unsalable goods may cause the goods to deteriorate and cause economic losses. Through the intelligent recommendation mechanism, these merchants can get more display opportunities, thereby increasing sales speed, reducing inventory backlogs, and reducing economic losses;

[0052] 4. Improve the operational efficiency of merchants: The merchant confirmation unit allows substitute merchants to quickly respond to order transfer requests through the backend management system, accept or reject orders, and set clear limits on the response time and delivery time of substitute merchants by setting processing time and delivery time. This mechanism ensures that substitute merchants can process orders quickly, improves overall operational efficiency, reduces invalid waiting time, and enables merchants to better manage inventory and logistics;

[0053] 5. Ensure transaction fairness: The comprehensive scoring comparison mechanism recommends qualified alternative merchants based on a variety of factors through a comprehensive scoring model. This scoring mechanism ensures that all merchants are recommended on the basis of fair competition to avoid a single merchant monopolizing 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 allows buyers to customize the latest waiting time for delivery when placing an order to meet their personalized needs. The system can dynamically adjust the latest waiting time for delivery based on the user's customized settings and other factors. This flexibility enables the system to better adapt to the needs of different users, provide more personalized services, and improve user experience. At the same time, this customization option also makes the system more adaptable and flexible, able to cope with various complex situations. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A schematic block diagram of the adjustment and optimization module;

[0056] Figure 2 A flow chart of a sales system based on a rural e-commerce platform proposed by the present invention;

[0057] Figure 3 Flowchart of the order timeout detection mechanism. DETAILED DESCRIPTION

[0058] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0059] Reference Figure 1-3 , a sales system based on a rural e-commerce platform, including:

[0060] User interface module: Use the 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;

[0061] Order management module: handles order creation, status tracking, payment, cancellation, history, timeout detection, and manages order processes;

[0062] Merchant management module: supports merchant registration and authentication, background management, inventory management, order processing, logistics information setting and delivery arrangement to help merchants operate;

[0063] Logistics and distribution module: integrates logistics information, arranges distribution, provides real-time logistics tracking and distribution status updates, and manages the product distribution process;

[0064] Customer service module: provides online customer service, question answering, after-sales service and user feedback processing to solve user problems and needs;

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

[0066] Security and Compliance Module: Implement data encryption storage, access control, regular security audits and compliance checks to protect user data security;

[0067] Adjustment and Optimization Module: Adjust overdue orders, transfer orders to eligible merchants, and manage the order adjustment process. The adjustment and optimization module includes:

[0068] Order timeout detection unit: set up an order timeout detection mechanism to regularly check the order status and determine whether the order has timed out;

[0069] Alternative merchant recommendation unit: set up a merchant recommendation mechanism, and use this mechanism to recommend qualified alternative merchants for overdue orders;

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

[0071] 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;

[0072] Merchant confirmation unit: The merchant checks the order transfer request through the backend management system and sets the accept button and reject button in the merchant operation interface. The system updates the order status according to the merchant's selection;

[0073] Notification and feedback unit: Send real-time notifications to buyers through several channels such as SMS and phone calls to inform them of changes in order status.

[0074] Furthermore, the order timeout detection mechanism includes:

[0075] Data setting: Add the latest waiting time T for each order in the database, and the latest waiting time T for each order is subject to the waiting time mechanism. Ensure that the order table in the database contains at least the order ID, user ID, merchant ID, product ID, order creation time, latest waiting time T for each order, and order status information. Set the order creation time to T1, calculate the order creation time T1 plus the latest waiting time T for each order, and record the calculated time as the delivery time.

[0076] Scheduled task settings: Use scheduled tasks such as Cron Job to regularly check the order status. For example, run a check task at 1 a.m. every day.

[0077] Order timeout detection: read the orders in the waiting-to-be-delivered state from the database, obtain the current system time and set it as T2. For each order, compare the current system time T2 with the calculated delivery time and determine whether the order has timed out. If T2 is greater than the delivery time, the order has timed out. If T2 is less than or equal to the delivery time, it indicates that the order has not timed out. It should be noted that the latest delivery time that the user has to wait for is T≥ the delivery time marked by the merchant, so that a reasonable delivery time range can be set for the user and the merchant together.

[0078] Update order status: Update the status of overdue orders to "pending recommendation of alternative merchants".

[0079] Furthermore, the waiting time mechanism includes:

[0080] User-defined settings: On the order area settings page, provide an option for users to select the latest 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 to allow buyers to fill in the longest waiting time they are willing to wait, and provide clear instructions to explain the function of this field, for example: "Please fill in the longest waiting time you can accept for delivery." It is worth mentioning that the latest waiting time filled in by the user is subject to the reasonable time preset by the system administrator based on business needs and service level agreements (SLAs);

[0081] Automatic system settings: Considering factors including but not limited to product shelf life, historical data, and user behavior, a calculation model for the user's latest waiting time T for delivery is set, and the value of T is calculated based on the calculation model and stored in the order details.

[0082] Embodiment 1

[0083] This embodiment takes into account the shelf life of the product and calculates the latest waiting time T for the user to wait for delivery. The calculation model is:

[0084]

[0085] Among them, 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 between 1 week and 1 month, such as dairy products, some 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 corresponded to the longest waiting time of the user, which can reduce the deterioration and waste of the product and improve the buyer's satisfaction.

[0086] Embodiment 2

[0087] This embodiment takes historical data factors into consideration and calculates the latest waiting time T for a user to wait for delivery. The calculation model is:

[0088]

[0089] Among them, C represents the product category, T hist (C) represents the historical waiting time of different product categories, N is the number of orders placed for products in this category, T j is the actual waiting time for each order, j represents the index variable, traversing all orders from 1 to N, Represents the sum of the actual waiting time of all orders. The calculation model adopts the average method and uses historical data to calculate the latest waiting time T for delivery. It can bring many advantages, including data-driven decision-making, optimized customer experience, improved operational efficiency, optimized inventory management, enhanced forecasting capabilities, risk management and quality control, improved 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 3

[0091] This embodiment takes into account user behavior factors and calculates the latest waiting time T for a user to wait for delivery. The calculation model is:

[0092] T=(1-p)×T max +p×T min ,

[0093] Where p is the proportion of users who choose fast delivery services 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. max is the maximum waiting time, T min It 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 requirements, logistics resources can be arranged more reasonably. For example, for those users who do not mind a longer waiting time, a lower-cost delivery method can be used to achieve the purpose of optimizing resource allocation, reducing costs and improving service quality.

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

[0095] Embodiment 4

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

[0097]

[0098] Among them, i represents different influencing factors, n represents the total number of influencing factors, and 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, and the output range is between 0 and 1. α represents the influence intensity adjustment parameter, which is used to adjust the influence intensity 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 interaction function between factors, β is the dynamic weight adjustment parameter, h(W, X) represents the dynamic weight adjustment function, W contains the vector of all factor weights, W = [w1, w2, w3…w n ], α and β are both constants and can be set according to actual needs;

[0099] Specifically, select and set the influencing factors to be considered and their static weights. Select inventory status, distance between buyers and sellers, price difference, and favorable comment rate as influencing factors. The corresponding actual values ​​are x1, x2, x3, and x4, and the corresponding static weights are w1=0.3, w1=0.3, w1=0.2, and w1=0.2. Set a scoring function for each factor.

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

[0101]

[0102] For the distance factor between buyers and sellers, the score function is:

[0103] Where d max 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 overdue order;

[0106] For the favorable review rate factor, the merchant’s favorable review rate data is directly used, and the score function is:

[0107] f4(x4)=x4;

[0108] In the scoring model, the setting methods of g(X) include:

[0109] Statistical analysis: Use statistical methods such as correlation analysis and regression analysis to identify the interactions between different factors;

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

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

[0112] For example, when there is a synergistic effect between the inventory situation 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] Among them, γ is a tuning parameter used to control the strength of the interaction;

[0115] In the scoring model, the setting methods of h(W, X) include:

[0116] Feedback mechanism: Dynamically adjust weights based on user feedback or historical data performance. For example, if a factor performs poorly in actual applications, its weight can be reduced.

[0117] Adaptive algorithms: Use adaptive algorithms such as online learning and reinforcement learning to dynamically adjust weights;

[0118] Rules Engine: Adjusts weights based on predefined rules. For example, if a factor scores particularly low, its weight can be increased to improve its importance.

[0119] For example, when you need to dynamically adjust the weights based on the actual score of each factor, you can set a linear adjustment function:

[0120]

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

[0122] Embodiment 5

[0123] This embodiment recommends alternative merchants by screening in priority order. Specifically, merchant data is obtained from a database, screening factors are prioritized, and screening is performed in order of priority. The priority screening includes:

[0124] System default order: The system prioritizes the screening factors based on business logic, user experience, historical data and industry standards. For example, the system considers product quality and user preference prices, and sets the priority order of different factors as follows: praise rate, price difference, inventory status, delivery speed, and logistics service quality. This screening order can reduce user waiting time while ensuring product quality and reasonable prices.

[0125] User-defined order: The system sets up a user-defined interface, allowing users to choose to rearrange the priority order of screening factors, and provides a Save button to submit the user-defined priority order. When the user does not set it, the system default order is used.

[0126] Furthermore, the merchant confirmation unit also includes an order transfer request processing restriction area, which sets a processing time t1 and limits 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 merchant's operation time. During this time, 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 alternative merchant from the list of eligible alternative merchants;

[0130] S4: The system sends new alternative merchant information to the buyer and asks the buyer to confirm.

[0131] If the buyer confirms the new alternative merchant, the above process is repeated until a merchant accepts the order. If the buyer rejects the new alternative merchant, the system continues to select the next alternative 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. For the transferred orders, it limits the delivery time of the alternative merchant. When the merchant accepts the order but fails to deliver the order within the delivery time t2, the system will send a new alternative merchant to the buyer.

[0133] Furthermore, both the processing time t1 and the delivery time t2 are constrained by the user's latest waiting time T for delivery. This constraint mechanism is obtained through experiments and fitting data, which is conducive to the rational allocation of resources. For users whose latest waiting time T for delivery is longer, appropriately extending the processing time t1 and the delivery time t2 can, within the range acceptable to the user, allocate distribution resources, especially resources with limited preservation conditions, to other users.

[0134] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A sales system based on a rural e-commerce platform, characterized in that: include: User interface module: Use the 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; Order management module: handles order creation, status tracking, payment, cancellation, history, timeout detection, and manages order processes; Merchant management module: supports merchant registration and authentication, background management, inventory management, order processing, logistics information setting and delivery arrangement to help merchants operate; Logistics and distribution module: integrates logistics information, arranges distribution, provides real-time logistics tracking and distribution status updates, and manages the product distribution process; Customer service module: provides online customer service, question answering, after-sales service and user feedback processing to solve user problems and needs; Data analysis and optimization module: collect and analyze data, monitor system performance, and process user feedback; Security and Compliance Module: Implement data encryption storage, access control, regular security audits and compliance checks to protect user data security; Adjustment and optimization module: adjust overdue orders, transfer orders to eligible merchants, and manage the order adjustment process.

2. A sales system based on a rural e-commerce platform according to claim 1, characterized in that: The adjustment and optimization module comprises: Order timeout detection unit: set up an order timeout detection mechanism to regularly check the order status and determine whether the order has timed out; Alternative merchant recommendation unit: set up a merchant recommendation mechanism, and use this mechanism to recommend qualified alternative merchants for overdue orders; Buyer selection interface unit: a display area is set in the order details page to display recommended alternative merchant information, including but not limited to name, favorable review rate, distance, price information, and operation buttons are set in 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: The merchant checks the order transfer request through the backend management system and sets the accept button and reject button in the merchant operation interface. The system updates the order status according to the merchant's selection; Notification and feedback unit: Send real-time notifications to buyers through several channels to inform them of order status changes.

3. A sales system based on a rural e-commerce platform according to claim 2, characterized in that: The order timeout detection mechanism includes: Data setting: Add the latest waiting time T for each order in the database, and the latest waiting time T is subject to the waiting time mechanism. Set the order creation time to T1, calculate the order creation time T1 plus the latest waiting time T, and record the calculated time as the delivery time. Scheduled task settings: Use scheduled tasks to regularly check order status; Order timeout detection: read the orders in the waiting-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 has timed out; Update order status: Update the status of overdue orders to "pending recommendation of alternative merchants".

4. A sales system based on a rural e-commerce platform according to claim 3, characterized in that: The waiting time mechanism includes: User-defined settings: On the order area settings page, provide options for users to select the latest waiting time and store this information in the order details; Automatic system settings: Considering factors including but not limited to product shelf life, historical data factors, and user behavior factors, a calculation model for the user's latest waiting time T for delivery is set, and the value of T is calculated based on the calculation model and stored in the order details.

5. A sales system based on a rural e-commerce platform according to claim 2, characterized in that: The merchant recommendation mechanism includes but is not limited to: Comprehensive rating comparison: Set a rating model and compare ratings, recommending the merchant with the highest rating as an alternative merchant; Priority screening: Get the merchant data from the database, select screening factors and prioritize the screening factors, and screen the merchants in order of priority.

6. A sales system based on a rural e-commerce platform according to claim 5, characterized in that: The scoring model is: Among them, i represents different influencing factors, n represents the total number of influencing factors, and 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, and the output range is between 0 and 1. α represents the influence intensity adjustment parameter, which is used to adjust the influence intensity 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 interaction function between factors, β is the dynamic weight adjustment parameter, h(W, X) represents the dynamic weight adjustment function, W contains the vector of all factor weights, W = [w1, w2, w3…w n ].

7. A sales system based on a rural e-commerce platform according to claim 5, characterized in that: The priority order screening includes: System default order: The system prioritizes screening factors based on business logic, user experience, historical data, and industry standards; User-defined order: The system sets up a user-defined interface, allowing users to choose to rearrange the priority order of screening factors.

8. A sales system based on a rural e-commerce platform according to claim 2, characterized in that: The operation buttons include: "Select this alternative merchant": When the buyer clicks this button, the system will transfer the order to the alternative merchant; "Change to alternative merchant": When the buyer clicks this button, the system recommends a new alternative merchant for the buyer to choose; "Cancel order": When the buyer clicks this button, the system cancels the order and automatically refunds the money.

9. A sales system based on a rural e-commerce platform according to claim 2, characterized in that: The merchant confirmation unit also includes: Order transfer request processing restriction area: Set the processing time t1 to limit the response time of the alternative merchant to the order transfer request; Order delivery monitoring restricted area: Set the delivery time t2, and for the transferred orders, restrict the delivery time of the alternative merchant.

10. A sales system based on a rural e-commerce platform according to claim 9, characterized in that: The processing time t1 and the delivery time t2 are both subject to the constraints of the user's latest waiting time T for delivery.

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