Inquiry method based on supply and demand transaction

Abstract

The invention provides an inquiry method based on supply and demand transaction. The inquiry method comprises the following steps: acquiring an inquiry list published by a buyer on a pre-created supply and demand transaction platform; according to evaluation indexes of suppliers registered by the supply and demand transaction platform, matching the inquiry list to obtain a target supplier, and sending the inquiry list to the target supplier; obtaining a quotation list submitted by the target supplier on the supply and demand transaction platform, and pushing the quotation list to a buyer of the supply and demand transaction platform; obtaining a final supplier selected by the buyer from the target suppliers, and forming an order between the buyer and the final supplier based on the supply and demand transaction platform; tracking the progress state of the order, and feeding back the progress state to the buyer and the final supplier; when the completion information of the order is obtained, providing an evaluation list for the buyer; and obtaining the evaluation result of the evaluation list, and feeding back the evaluation result to the final supplier, so that the buyer demand and the supplier can be efficiently and accurately matched, the transaction efficiency is improved, and the transaction cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of e-commerce, and particularly to an inquiry method based on supply and demand transactions. Background Art

[0002] In the wave of today's global economic integration, the market environment in which enterprises are located is becoming increasingly competitive, and the efficient operation of the supply chain has become a key factor for enterprises to gain competitive advantages. However, the traditional source inquiry and quotation mode has many drawbacks in terms of efficiency, information symmetry, and user experience.

[0003] Specifically, for example, the traditional inquiry method mainly relies on manual screening and matching, making it difficult to accurately find the most suitable suppliers, resulting in low procurement efficiency and easy omission of high-quality suppliers. At the same time, the procurement process is cumbersome, buyers need to manually fill in a large amount of information, and there is a lack of effective tool support when evaluating supplier quotations, increasing the operation difficulty and time cost. In addition, there is information asymmetry between buyers and sellers. It is difficult for buyers to obtain detailed information about suppliers, and it is also difficult for suppliers to accurately grasp buyers' needs, resulting in a lack of basis for procurement decisions and an increase in procurement risks. Summary of the Invention

[0004] The present invention provides an inquiry method based on supply and demand transactions to solve the technical problem in the prior art that it is impossible to efficiently and accurately match corresponding suppliers for buyers.

[0005] On the one hand, the present invention provides an inquiry method based on supply and demand transactions, including: Obtaining an inquiry list published by a buyer on a pre-created supply and demand trading platform; wherein, the inquiry list includes product specifications, quantity, price range, delivery date, and quality standards; Matching the inquiry list according to the evaluation indicators of the suppliers registered on the supply and demand trading platform to obtain target suppliers, and sending the inquiry list to the target suppliers; wherein, the evaluation indicators include historical performance, product quality, price competitiveness, and delivery ability; Obtaining a quotation list submitted by the target suppliers on the supply and demand trading platform, and pushing the quotation list to the buyers on the supply and demand trading platform; wherein, the quotation list includes price, quantity, and estimated delivery date; Obtaining the final supplier selected by the buyer from the target suppliers, and forming an order between the buyer and the final supplier based on the supply and demand trading platform; Tracking the progress status of the order, and feeding back the progress status to the buyer and the final supplier; When obtaining the completion information of the order, providing an evaluation list to the buyer; Obtain the evaluation results of the said evaluation list and feedback them to the said final supplier.

[0006] The inquiry method based on supply-demand transactions provided by the present invention matches the inquiry list according to the evaluation indicators of the suppliers registered on the supply-demand transaction platform, obtains the target suppliers, sends the inquiry list to the target suppliers, obtains the quotation list submitted by the target suppliers on the supply-demand transaction platform, and pushes the quotation list to the buyers on the supply-demand transaction platform. It obtains the final supplier selected by the buyers from the target suppliers and forms an order between the buyers and the final suppliers based on the supply-demand transaction platform. By realizing the full-process management from obtaining the inquiry list to forming an order and tracking the progress of the order on the supply-demand transaction platform, it can efficiently and precisely match the buyer's needs with the suppliers, quickly screen out the appropriate target suppliers and push the inquiry list, enabling the suppliers to respond in a timely manner and submit the quotation list. Then the buyers select the final suppliers based on the quotation list and form an order. Moreover, it can also track the progress of the order and feedback the status, and provide an evaluation mechanism after the order is completed. This full-process closed-loop management improves the transaction efficiency, reduces the transaction cost, enhances the transaction experience of both the supply and demand sides, and promotes the smooth progress of supply-demand transactions. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0008] Figure 1 It is a schematic flowchart of the inquiry method based on supply-demand transactions provided by the embodiments of the present invention; Figure 2 It is a schematic structural diagram of the inquiry device based on supply-demand transactions provided by the embodiments of the present invention; Figure 3 It is a schematic structural diagram of the electronic device provided by the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0009] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention with reference to the accompanying drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0010] Figure 1It is a schematic flowchart of an inquiry method based on supply-demand transactions provided by an embodiment of the present invention. The execution subject of this method can be a computer, a tablet computer, a smart wearable device, etc.

[0011] See Figure 1 , the inquiry method based on supply-demand transactions may include the following steps.

[0012] Step 101: Obtain the inquiry list published by the buyer on the pre-created supply-demand trading platform; wherein, the inquiry list includes product specifications, quantity, price range, delivery date, and quality standards.

[0013] In this step, the product specifications may include model, size, performance parameters, etc. The quality standards may include ISO9001 standard, ISO 22000:2018, etc., or may be defined by the buyer's requirements, and will not be listed one by one. Example 1 of the inquiry list: Purchase 1000 electronic products with the model XJ-2023, the expected unit price is between 50-70 yuan, the delivery date is within 30 days, and the quality standard needs to meet ISO 9001. Example 2 of the inquiry list: Purchased product: mobile phone; specifications: 256GB, blue; quantity: 1000 units; price range: 5000-6000 yuan per unit; delivery date: before March 15, 2025; quality standard: original factory genuine product, brand new and unopened. The inquiry list may also include other information, such as customized packaging and specific after-sales services, which will not be listed here.

[0014] Step 102: Match the inquiry list according to the evaluation indicators of the suppliers registered on the supply-demand trading platform to obtain the target suppliers, and send the inquiry list to the target suppliers; wherein, the evaluation indicators include historical performance, product quality, price competitiveness, and delivery ability.

[0015] In this step, the historical performance may refer to the on-time delivery rate (such as 90%) and the favorable comment rate (such as 95%) in the past period (such as one year, one quarter, or one month). The product quality may refer to the product qualification rate (such as 95%) and the free replacement period, etc. The price competitiveness may refer to the comparison result between the supplier's quotation and the market average price, such as the quotation is 10% lower than the market average price. The delivery ability may refer to the output per unit time, for example, the monthly production capacity is 5000 units. The evaluation indicators may also include other information, which will not be listed here.

[0016] Step 103: Obtain the quotation list submitted by the target supplier on the supply-demand trading platform and push the quotation list to the buyer on the supply-demand trading platform; wherein, the quotation list includes price, quantity, and expected delivery date.

[0017] In this step, an example of the quotation list is as follows: "Product: Mobile phone; Specifications: 256GB, blue; Quantity: 1000 units; Quotation: 5500 yuan per unit; Estimated delivery date: March 10, 2025. The quotation list may also include other information, which will not be listed here.

[0018] Step 104: Obtain the final supplier selected by the buyer from the target suppliers, and form an order between the buyer and the final supplier based on the supply and demand trading platform.

[0019] In this step, an example of the order is as follows: Order number: 20250301-001; Purchased product: Mobile phone; Specifications: 256GB, blue; Quantity: 1000 units; Unit price: 5500 yuan; Total price: 5.5 million yuan; Delivery date: March 10, 2025. The order may also include other information, which will not be listed here. It can be understood that the order is generated based on the inquiry list and the quotation list, or it can be filled out according to the order template after being agreed upon between the buyer and the supplier.

[0020] Step 105: Track the progress status of the order and feedback the progress status to the buyer and the final supplier.

[0021] In this step, the progress status of the order may include the production progress, such as 80% completed; it may also include the logistics transportation status, for example, the goods have been shipped and are expected to arrive in 3 days.

[0022] Step 106: Provide an evaluation list to the buyer when the completion information of the order is obtained.

[0023] In this step, the evaluation list may contain the following contents: Product quality evaluation, Delivery date evaluation, Service attitude evaluation, Price reasonableness evaluation, etc.

[0024] Step 107: Obtain the evaluation results of the evaluation list and feedback them to the final supplier.

[0025] In this embodiment, according to the evaluation indicators of the suppliers registered on the supply and demand trading platform, the inquiry list is matched to obtain the target suppliers, and the inquiry list is sent to the target suppliers. The quotation list submitted by the target suppliers on the supply and demand trading platform is obtained, and the quotation list is pushed to the buyers on the supply and demand trading platform. The final supplier selected by the buyers from the target suppliers is obtained, and an order is formed between the buyers and the final suppliers based on the supply and demand trading platform. By implementing the full-process management from obtaining the inquiry list to forming an order and tracking the order progress on the supply and demand trading platform in this embodiment, the buyer's needs can be efficiently and accurately matched with the suppliers, the appropriate target suppliers can be quickly screened out and the inquiry list can be pushed, enabling the suppliers to respond in a timely manner and submit the quotation list. Then, the buyers select the final suppliers based on the quotation list and form an order. Moreover, the order progress can be tracked and the status can be fed back, and an evaluation mechanism can be provided after the order is completed. This full-process closed-loop management improves the trading efficiency, reduces the trading costs, enhances the trading experience of both the supply and demand sides, and promotes the smooth progress of the supply and demand transactions.

[0026] The specific example is as follows: Suppose an electronic manufacturing enterprise (buyer) needs to purchase a batch of electronic components. It publishes an inquiry list on the supply and demand trading platform, which details the specifications of the required electronic components (such as model, size, performance parameters), quantity (1000 pieces), price range (50 - 70 yuan per piece), delivery period (within 30 days), and quality standard (meeting ISO 9001 standard). The platform matches according to the evaluation indicators of the registered suppliers (such as historical supply performance, product quality qualification rate, price competitiveness, delivery punctuality rate), screens out several eligible target suppliers, and sends the inquiry list to these suppliers. Suppliers A, B, and C submit their quotation lists respectively, including the prices (60 yuan, 65 yuan, and 58 yuan per piece respectively) and the estimated delivery dates (all 25 days). After the buyer views these quotation lists through the platform, it selects Supplier C as the final supplier and generates an order through the platform. The platform then tracks the production progress and logistics transportation status of the order and feeds back this information to the buyer and Supplier C in real time. After the order is completed, the platform provides an evaluation list to the buyer, and the buyer evaluates aspects such as the product quality, delivery period, and service attitude of Supplier C, and the evaluation results are fed back to Supplier C for improvement.

[0027] In an embodiment of this specification, according to the evaluation indicators of the suppliers registered on the supply and demand trading platform, matching the inquiry list to obtain the target suppliers and sending the inquiry list to the target suppliers includes: The first step: Based on the data collection and preprocessing subsystem of the supply and demand trading platform, collect various types of data of the suppliers, perform data cleaning and standardization processing on the various types of data, and obtain the target data.

[0028] Step 2: Based on the feature extraction and model training subsystem of the supply and demand trading platform, the target data is converted into feature vectors, and model training is performed based on the feature vectors to obtain the supplier evaluation model.

[0029] Step 3: Based on the real-time matching and recommendation subsystem of the supply and demand trading platform, the inquiry list is converted into a demand vector, and the demand vector and the evaluation model are matched using a similarity matching algorithm to obtain a supplier group that matches the demand vector. The suppliers in the supplier group are sorted in descending order according to the comprehensive score, and the top N suppliers are selected as target suppliers, and the inquiry list is sent to the target suppliers; N is an integer greater than 1.

[0030] In this embodiment, in the first step, on the one hand, suppliers need to submit detailed basic information of the enterprise when entering the platform, such as enterprise scale, production capacity, business scope, qualification certificate, etc.; product catalog information, including product name, model, specification, detailed parameters, picture display, price system, etc.; and historical transaction records (that is, historical performance data), such as transaction time, transaction amount, product quantity, customer information, delivery time, quality feedback, etc. of past orders. On the other hand, the platform obtains market data such as the supplier's credit rating, financial status, legal dispute record, etc. from third-party authoritative credit institutions, and collects industry standards, technology development trends, market supply and demand dynamics and other information from industry associations and professional research institutions to enrich the data dimension. After entering the platform, the above raw data will first undergo a strict data cleaning process, using data filtering algorithms to remove duplicate, invalid, erroneous or incomplete data records, such as deleting product parameters with incorrect formats and correcting obviously unreasonable price data. Next, through data standardization processing, data in different formats and units are converted into a standard format, such as unifying all date formats into "YYYY-MM-DD" and converting currency units into RMB, etc., to ensure data consistency and availability, laying the foundation for subsequent analysis and processing.

[0031] In the second step, for the historical performance data of suppliers, by calculating indicators such as on-time delivery rate (the ratio of the number of orders delivered on time to the total number of orders), product quality pass rate (the ratio of the number of qualified products to the total number of products delivered), customer repeat purchase rate (the ratio of the number of customers who repurchase to the total number of customers), and customer complaint rate (the ratio of the number of complaint orders to the total number of orders), etc., they are quantified into specific characteristic values; for product quality-related data, key technical indicators in the production process (such as the chip manufacturing process of electronic products, the machining accuracy of mechanical products, etc.), key elements in the quality control system (such as whether it has passed quality management system certifications such as ISO9001, the sampling ratio and frequency of internal quality inspections, etc.), and the quantity and level of various authoritative certifications obtained by the product are taken as characteristics; for price competitiveness, characteristics such as the deviation rate of the supplier's product price from the market average price, price fluctuation range, and cost profit rate are calculated; for delivery ability, factors such as the production capacity utilization rate of production equipment, inventory turnover rate, average response time and on-time rate of logistics distribution are analyzed, so as to construct a comprehensive and accurate feature vector set reflecting the comprehensive capabilities of suppliers. Based on these feature vectors, various machine learning algorithms are used for model training. For example, classification algorithms based on decision trees are used for preliminary screening of suppliers meeting basic conditions, and regression algorithms based on neural networks are used for accurate prediction of the comprehensive scores of suppliers. By continuously adjusting the parameters and structure of the model and using a large amount of historical data for repeated training and verification, the performance and accuracy of the model are optimized, and finally an efficient and accurate supplier comprehensive evaluation model and demand matching model are constructed.

[0032] In the third step, natural language processing technology and semantic analysis algorithms are used to parse the buyer's inquiry list, extract key demand information such as product features, quantity, price range, delivery period, etc., and convert them into standardized demand vectors with the same dimension as the supplier feature vectors. Then, the demand vectors are compared and calculated with the trained supplier comprehensive evaluation model, and similarity matching algorithms are used to find the group of suppliers that best match the demand. During the matching process, according to the pre-set weights of each feature (these weights can be dynamically adjusted and optimized based on the big data accumulated by the platform and the experience of industry experts), the performance of suppliers in each dimension is weighted and scored. For example, for a procurement demand with strict requirements for the delivery period, the weight of the delivery ability feature will be correspondingly increased. Finally, the suppliers are ranked in descending order according to the comprehensive scores, and a list of high-quality suppliers with top rankings is selected, and their detailed information (including basic enterprise information, product information, quotation information, comprehensive scores and scores in each dimension, etc.) is recommended to the buyer. At the same time, a detailed analysis report on the matching degree between each supplier and the demand is provided to the buyer to help the buyer deeply understand the advantages and characteristics of the recommended suppliers, so as to make a more informed decision.

[0033] In the process of matching the target supplier in this embodiment, the data acquisition and preprocessing subsystem cleans and standardizes various types of supplier data to ensure the accuracy and consistency of the data; then the feature extraction and model training subsystem converts the data into feature vectors and trains an evaluation model, which can more accurately evaluate the comprehensive strength of the supplier; finally, the real-time matching and recommendation subsystem uses the similarity matching algorithm combined with the evaluation model to screen out the top N target suppliers according to the comprehensive score ranking. This data-driven intelligent matching method can evaluate suppliers more scientifically and comprehensively than traditional manual screening or simple matching methods, improve the matching accuracy of the target supplier, and provide better supplier choices for buyers.

[0034] In an embodiment of this specification, obtaining the quotation list submitted by the target supplier on the supply and demand trading platform and pushing the quotation list to the buyers on the supply and demand trading platform includes: Obtaining the quotation link of the supply and demand trading platform clicked by the target supplier and displaying the quotation submission page; wherein, the quotation submission page includes a quotation template provided by the supply and demand trading platform for the target supplier, and the quotation template pre-fills some information and provides a reference cost price range, the market average transaction price within a preset period, and a recommended profit margin range; Obtaining the quotation list submitted by the target supplier; wherein, the quotation list includes the price filled in by the target supplier according to the quotation template and the expected delivery date; Based on the supply and demand trading platform, verifying the quotation list submitted by the target supplier and pushing the verified quotation list to the buyers on the supply and demand trading platform.

[0035] In this embodiment, providing a quotation template with pre-filled information and reference data for the supplier can help the supplier fill in the quotation list more quickly and accurately, reducing errors and uncertainties in the quotation process; at the same time, the platform verifies the submitted quotation list before pushing it to the buyers, ensuring the quality and compliance of the quotation list, avoiding invalid or incorrect quotations from interfering with the buyers' decisions, thereby improving the efficiency and accuracy of the quotation link and accelerating the transaction process.

[0036] Specifically, for example, the target supplier clicks on the quotation link of the supply and demand trading platform, and a quotation submission page is displayed. The page shows a quotation template provided by the platform for this supplier, and some information is pre-filled in the template, such as basic information like product specifications and quantities in the inquiry list. At the same time, the platform also provides the following reference information. For example, the reference cost price range: According to market analysis, the cost price range of this product is 100 yuan per piece to 120 yuan per piece; the average market transaction price within the preset period: In the past 3 months, the average market transaction price of this product is 130 yuan per piece; the recommended profit margin range: The profit margin range recommended by the platform is 10% to 20%. The content of the quotation list can be as follows: Price: 135 yuan per piece (the price determined by the supplier after comprehensive consideration of cost, average market transaction price, and recommended profit margin); Estimated delivery date: March 15, 2025 (the delivery date estimated by the supplier based on its own production capacity and current order situation).

[0037] In an embodiment of this specification, obtaining the final supplier selected by the buyer from the target suppliers and forming an order between the buyer and the final supplier based on the supply and demand trading platform includes: Based on the supply and demand trading platform, display an evaluation and selection page to the buyer; wherein, the evaluation and selection page includes a quotation summary list and supplier information; Obtain the weights of each evaluation criterion set by the buyer through the supply and demand trading platform; wherein, the evaluation criteria include product quality, price, delivery date, after-sales service, and supplier reputation; Based on the supply and demand trading platform, determine the comprehensive score of each target supplier according to the weights set by the buyer and the actual performance of the supplier, and generate an evaluation report and a comparison chart; Obtain the final supplier selected by the buyer according to the evaluation report and the comparison chart, and form an order.

[0038] In this embodiment, by providing the buyer with an evaluation and selection page, displaying the quotation summary list and supplier information, and allowing the buyer to set the weights of the evaluation criteria, and then generating an evaluation report and a comparison chart according to the weights and the actual performance of the supplier, it helps the buyer evaluate each target supplier more intuitively and comprehensively, so as to be able to more scientifically select the final supplier that best meets their own needs and form an order. This decision-making support method based on multi-dimensional evaluation and visual display enhances the buyer's decision-making basis, improves the accuracy and satisfaction of decision-making, and helps to establish a better supply and demand cooperation relationship.

[0039] Specifically, product quality can refer to the performance of the products provided by the supplier in terms of quality standards, performance, durability, consistency, product qualification rate, etc. Delivery time refers to the speed and punctuality of the supplier to complete the order and deliver the products. After-sales service refers to the support and services provided by the supplier after the product is delivered, including response time, problem-solving ability, service attitude, warranty period, etc. Supplier reputation refers to the reputation and word-of-mouth of the supplier in the market, including customer evaluations, credit ratings, historical transaction records, etc. Customer evaluation can refer to the comprehensive evaluation of the supplier by past customers. Credit rating can refer to the rating of the supplier by a third-party credit rating agency. Historical transaction records can refer to the completion status of the supplier's past orders, customer satisfaction, etc.

[0040] Actual performance refers to the real situation and historical records of the supplier in past transactions, production operations, customer service, etc. These performances are measured by specific data and facts. For example, product quality: whether the supplier's products meet the quality standards, the frequency and severity of historical quality problems. Price: the price level provided by the supplier, as well as the stability and competitiveness of the price. Delivery time: whether the delivery time promised by the supplier is punctual, and the response ability in case of emergencies. After-sales service: the response time, problem-solving ability and customer satisfaction of the supplier after the product is delivered. Supplier reputation: the word-of-mouth, credit rating and historical transaction records of the supplier in the market. Specifically, for Supplier A, quality certification: passed ISO9001 certification; historical quality problems: in the past year, the quality problem feedback rate was less than 2%; quality qualification rate: 98% of the products passed the quality inspection. For Supplier B, quality certification: did not pass ISO9001 certification; historical quality problems: in the past year, the quality problem feedback rate was 5%; quality qualification rate: 95% of the products passed the quality inspection.

[0041] In an embodiment of this specification, tracking the progress status of the order and feeding back the progress status to the buyer and the ultimate supplier, including: Based on the data interaction mechanism between the pre-established supply-demand trading platform and the production management system and logistics distribution system of the supplier, obtaining the production progress information and logistics transportation status information of the ultimate supplier; Based on the supply-demand trading platform, updating the production progress information and logistics transportation status information to the status page of the order in real time and presenting them to the buyer and the ultimate supplier in a visual manner; When it is monitored that the production progress information and logistics transportation status information are abnormal, based on the supply-demand trading platform, starting the early warning mechanism, sending an abnormal notice to the buyer and the ultimate supplier, and providing a solution.

[0042] In this embodiment, based on the data interaction mechanism between the supply and demand trading platform and the production management system and logistics distribution system of the supplier, it is possible to obtain the production progress and logistics transportation status information in real time, and present it to the buyer and the supplier in a visual manner, enabling both parties to timely understand the order progress; when anomalies are detected, an early warning mechanism can be activated and solutions can be provided. This real-time tracking and early warning function enhances the transparency and controllability of order management, reduces risks caused by information asymmetry, improves the success rate of on-time order delivery, and ensures the smooth progress of transactions.

[0043] Specifically, for example, assume that a buyer purchases a batch of electronic products from a supplier through the supply and demand trading platform, and the order number is 20250211-001. Platform operations: The supply and demand trading platform establishes a data interaction mechanism with the supplier's production management system (such as ERP) and logistics distribution system (such as TMS) to obtain the production progress and logistics status of the order in real time. The platform obtains the production progress information from the supplier's ERP system. For example, the raw material procurement progress: 80% completed. The completion status of the production process: 50% completed. The estimated completion time: 3 days later. The platform obtains the logistics information from the logistics system. For example, the shipping time: It is estimated to be shipped on the 2nd day after production is completed. The location of the goods in transit: Not shipped yet. The estimated arrival time: It will arrive 5 days after shipment. The platform updates the above production progress and logistics status information to the order status page in real time and presents it to the buyer and the supplier in a visual manner. There are various ways of visual display. For example, progress bars: showing that the production progress is 50% and the raw material procurement progress is 80%. Map tracking: showing that the goods have not been shipped yet, the estimated shipping time and arrival time.

[0044] The platform monitors the production progress and logistics status in real time and activates the early warning mechanism when anomalies are found. For example, production delay: The platform detects that the supplier's production progress is delayed and is expected to not be completed on time. Logistics anomaly: The platform detects that there is a detention of goods during the logistics transportation process. The platform sends text messages to the buyer and the supplier with the content: The production progress of order 20250211-001 is delayed, and the estimated delivery time is postponed by 3 days. The platform pops up a prompt box on the login interfaces of the buyer and the supplier, showing detailed anomaly information and solution suggestions. For example: It is recommended that the supplier increase the workforce to speed up the production progress or negotiate with the buyer to adjust the delivery date.

[0045] In an embodiment of this specification, the method further includes: Based on the supply and demand trading platform, cleaning, preprocessing, and analyzing the procurement behavior data of the buyer, the sales data of the supplier, and the market price data to generate a market trend analysis report and optimization suggestions for procurement strategies; Based on the supply and demand trading platform, providing the market trend analysis report and optimization suggestions for procurement strategies to the buyer and the supplier.

[0046] In this embodiment, by cleaning, preprocessing, and analyzing the buyer's procurement behavior data, the supplier's sales data, and the market price data, a market trend analysis report and suggestions for optimizing procurement strategies are generated and provided to the buyer and the supplier. This can help both parties better understand the market dynamics and their own transaction situations, formulate reasonable procurement and sales strategies in advance, optimize resource allocation, reduce procurement costs and inventory risks, improve market competitiveness, and thus enhance the efficiency and effectiveness of the entire supply-demand transaction ecosystem.

[0047] In an embodiment of this specification, based on the supply-demand transaction platform, the buyer's procurement behavior data, the supplier's sales data, and the market price data are cleaned, preprocessed, and analyzed to generate a market trend analysis report and suggestions for optimizing procurement strategies, including: Based on the data collection module of the supply-demand transaction platform, the buyer's procurement behavior data, the supplier's sales data, and the market price data are collected; among them, the procurement behavior data includes procurement time, product type, quantity, amount, procurement frequency, distribution of procurement source and usage locations, and the sales data includes sales quantity, sales amount, sales price trend, sales area distribution, customer type and distribution. Based on the data cleaning module of the supply-demand transaction platform, the procurement behavior data, the supplier's sales data, and the market price data are denoised, de-duplicated, missing values are filled, error values are corrected, and the format is standardized. Based on the data analysis module of the supply-demand transaction platform, the clustering analysis algorithm is used to classify the buyers and suppliers according to the procurement behavior data, the supplier's sales data, and the market price data, including: classifying the buyers into high-frequency high-value, high-frequency low-value, low-frequency high-value, and low-frequency low-value according to the procurement frequency and procurement amount, and analyzing their procurement preferences, demand trends, and price sensitivities for different types of buyer groups. Based on the data analysis module of the supply-demand transaction platform, the association rule mining algorithm is used to detect the association relationships in the dataset, including: detecting the association between the raw material price fluctuations and the finished product price fluctuations, and other related products that the buyer will purchase as a set after purchasing a product. Based on the data analysis module of the supply-demand transaction platform, the time series analysis model is used to predict the market price trend, demand change trend, and seasonal fluctuation law, including: predicting the price change trend of various products within a preset future time period by modeling and analyzing historical data, and informing the buyer and the supplier in advance of the possible direction of the market price.

[0048] In this embodiment, the specific methods and contents of data collection, cleaning, and analysis are further refined. By collecting comprehensive procurement behavior and sales data, performing cleaning operations such as denoising and duplicate removal, and then applying various data analysis algorithms such as clustering analysis, association rule mining, and time series analysis to classify buyers and suppliers, mine association relationships, and predict market trends, the data value can be more deeply explored, providing more powerful support for generating accurate market trend analysis reports and procurement strategy optimization suggestions, making these reports and suggestions more targeted and practical, and better serving the decision-making needs of buyers and suppliers.

[0049] Specifically, for example, procurement time: the specific date and time when the buyer makes a purchase. Product category: the category of products purchased by the buyer. Quantity: the quantity of products purchased each time. Amount: the total amount of each purchase. Procurement frequency: the number of times the buyer makes a purchase within a certain period. Distribution of procurement source and usage location: the geographical locations of the shipping and usage locations of the products purchased by the buyer. Sales quantity: the quantity of products sold by the supplier. Sales amount: the total amount obtained by the supplier through sales. Sales price trend: the change trend of the supplier's product price over time. Sales region distribution: the distribution of the sales regions of the supplier's products. Customer type and distribution: information such as the industries, scales, and registered addresses of the customers who purchase the supplier's products.

[0050] Market price data refers to the price information of similar products or services in the market, which reflects the market supply and demand relationship and price fluctuations. For example, raw material price: the price of raw materials required for product production. Finished product price: the market price of the final product. Price fluctuation trend: the change trend of price over time. Industry dynamic information: the impact of new technology R & D, policy and regulation changes, competitor market share, etc. on price.

[0051] A market trend analysis report can refer to a report generated through the analysis of procurement behavior data, sales data, and market price data, regarding market dynamics, demand changes, price trends, etc. For example, price trend: the prediction of future market prices. Demand trend: the prediction of future market demand. Regional analysis: the sales and demand situations in different regional markets. Industry dynamics: the impact of new technologies and policy and regulation changes on the market. For example, the price of electronic products has shown an upward trend in the past year, and it is expected that the price will remain between 110 - 120 yuan per piece in the next three months, and the demand reaches a peak in the third quarter of each year. It is recommended that buyers stock up in advance.

[0052] Optimization suggestions for procurement strategies can refer to suggestions provided to buyers on how to optimize the procurement process, reduce costs, and improve efficiency based on the results of market trend analysis. For example, cost optimization: how to reduce costs by reasonably arranging the procurement time, quantity, etc. Supplier selection: how to select suppliers with high cost performance and good reputation. Inventory management: how to reasonably arrange inventory according to demand trends. Risk management: how to cope with market price fluctuations and supply risks. For example, it is recommended that Buyer A increase the procurement quantity when the price is low (such as in the first quarter) to reduce costs. It is recommended that Buyer A consider establishing a long-term cooperative relationship with Supplier B because it has strong price competitiveness and a high degree of matching between its sales area and the buyer's demand.

[0053] Error values may include format errors, unreasonable values, duplicate data, missing values, and logical errors, etc. Denoising: removing outliers or noise in the data. Duplicate removal: deleting duplicate data records. Filling missing values: filling in missing data based on historical data or statistical methods. Correcting error values: correcting incorrect or unreasonable data. Format standardization: unifying the data format into a standard format. High-frequency and high-value refers to high procurement frequency and large procurement amount; high-frequency and low-value refers to high procurement frequency and small procurement amount; low-frequency and high-value refers to low procurement frequency and large procurement amount; low-frequency and low-value refers to low procurement frequency and small procurement amount.

[0054] The platform's functional modules for in-depth analysis of the cleaned data to extract valuable information. For example, clustering analysis: grouping data with similar characteristics. Association rule mining: discovering association relationships in the data. Time series analysis: predicting the changing trend of data over time. Visualization display: presenting the analysis results in the form of charts, reports, etc.

[0055] In an embodiment of this specification, it further includes: After the buyer publishes an inquiry list, based on the supply and demand trading platform, automatically recommend other products or services related to the current inquiry list by analyzing the buyer's historical procurement behavior and preferences; Based on the supply and demand trading platform, analyze the production capacity and inventory level of suppliers and provide suggestions for the buyer to optimize the procurement plan.

[0056] In this embodiment, after the buyer publishes an inquiry list, automatically recommending relevant products or services based on the platform's analysis of the buyer's historical procurement behavior and preferences can help the buyer expand the procurement vision, discover potential procurement needs, and improve the integrity and coordination of procurement; at the same time, analyzing the production capacity and inventory level of suppliers to provide suggestions for the buyer to optimize the procurement plan helps the buyer reasonably arrange the procurement time and quantity, avoid the risks of over-purchasing or out-of-stock, further enhances the scientificity and rationality of the procurement plan, and optimizes the procurement process and costs.

[0057] Specifically, for example, historical procurement behavior may refer to the records left by a buyer during past procurement activities through the platform. For example, procurement time: the specific date of each procurement; procurement product type: the product categories purchased in the past; procurement quantity: the quantity of products purchased each time; procurement amount: the total amount of each procurement. Procurement frequency: the number of procurements within a certain period of time; distribution of procurement source and usage location: the shipping location and usage location of the procured products. Procurement preference may refer to the preferences and habits demonstrated by the buyer during the procurement process. For example, product preference: the type or brand of products that the buyer tends to procure; price preference: the buyer's sensitivity to price and the expected range; delivery period preference: the buyer's expectation for the delivery time; quality preference: the buyer's requirements for product quality; service preference: the buyer's expectation for after-sales service.

[0058] Related products or services may refer to other products or services that are directly related to the products or services in the buyer's current inquiry list. For example, complementary products: products that are used in conjunction with the main product, such as chargers, data cables, etc.; alternative products: products with similar functions but different brands or specifications; value-added services: such as installation services, after-sales services, customization services, etc.

[0059] Production capacity may refer to the quantity of products that a supplier can produce within a certain period of time. For example, equipment utilization rate: the usage efficiency of production equipment. Production progress: the completion status of the current production task. Production capacity ceiling: the maximum production capacity when the equipment is operating at full capacity. Example: The production equipment utilization rate of Supplier B is approximately 80%, the current production progress is normal, and the production capacity ceiling is 1,000 electronic products per month. Inventory level may refer to the quantity of products currently held in stock by the supplier. For example, existing inventory quantity: the actual quantity of products stored in the current warehouse. Expected replenishment time: the time when the next batch of goods is expected to arrive. Inventory turnover rate: the turnover speed of inventory, reflecting the liquidity and sales situation of inventory.

[0060] Suggestions for optimizing the procurement plan may refer to the suggestions provided by the platform to the buyer on how to optimize the procurement plan based on the supplier's production capacity and inventory level. For example, procurement time suggestion: suggesting to the buyer when to place an order to ensure on-time delivery. Procurement quantity suggestion: suggesting the specific quantity for the buyer to procure to avoid inventory backlog or out-of-stock situations. Batch procurement suggestion: suggesting whether the buyer needs to conduct batch procurement, as well as the procurement time and quantity for each batch. Risk reminder: alerting the buyer to possible supply risks, such as production delays or insufficient inventory.

[0061] In an embodiment of this specification, obtaining the inquiry list posted by the buyer on the pre-created supply and demand trading platform includes: Obtaining the login instruction of the buyer on the supply and demand trading platform and displaying the page of the inquiry list; When receiving the completion instruction of the buyer's inquiry list, based on the verification system of the supply and demand trading platform, verify the information in the inquiry list; When receiving the identity confidentiality requirement of the buyer's inquiry list, generate a unique anonymous identifier for the buyer's identity; When receiving the identity disclosure requirement of the buyer's inquiry list, generate a name for registration and use for the buyer's identity.

[0062] In this embodiment, when obtaining the buyer's inquiry list, the platform can not only verify the information to ensure the accuracy and integrity of the inquiry list, but also generate an anonymous identifier or public name for the buyer's identity according to the buyer's needs, meeting the buyer's privacy protection and information disclosure requirements in different situations, enhancing the flexibility and user-friendliness of the platform, enabling the buyer to release the inquiry list more reassuringly, and improving the attractiveness and usage rate of the platform.

[0063] In an embodiment of this specification, after forming an order between the buyer and the final supplier based on the supply and demand trading platform, it further includes: When the buyer confirms the order, the supply and demand trading platform automatically triggers the electronic contract generation process, and generates an electronic contract based on the standardized contract template and the order of both parties; Based on the supply and demand trading platform, provide the electronic signature function for the buyer and the final supplier, and conduct real-name authentication and encrypted backup for the signing process; Store the signed electronic contract in the storage repository of the platform, generate a unique number and a QR code for reference and download; Based on the contract terms review module of the supply and demand trading platform, automatically detect legal risks in the contract; Based on the supply and demand trading platform, real-time track the contract performance situation, and remind both parties to fulfill their obligations at preset nodes.

[0064] In this embodiment, after forming the order, the platform automatically triggers the electronic contract generation process, generates an electronic contract based on the standardized template and the order, and provides functions such as electronic signature, real-name authentication, encrypted backup, etc., as well as contract terms review and performance situation tracking reminder services. This full-process electronic contract management method not only improves the efficiency and convenience of contract signing, reduces the cumbersome and errors of manual operations, but also enhances the legal effect and security of the contract, reduces the risk of contract disputes. At the same time, by real-time tracking the contract performance situation, it ensures the smooth execution of the contract, safeguards the legitimate rights and interests of both the supply and demand parties, and provides a strong guarantee for the successful completion of the transaction.

[0065] Specifically, for example, the electronic contract generation process can refer to the process of contract generation automatically triggered by the platform after the buyer confirms the order. For example, standardized contract template: a contract template preset by the platform, covering common procurement terms and legal regulations. Data filling: automatically fill in the contract content according to the details agreed upon by the buyer and the supplier during the inquiry, quotation, and negotiation processes. After buyer A confirms the order with supplier B, the platform automatically triggers the electronic contract generation process. The contract template is automatically filled with detailed information such as product specifications, quantity, price, delivery date, etc., generating a complete electronic contract.

[0066] The electronic signature function can refer to the function provided by the platform for signing electronic contracts, supporting multiple electronic signature methods. For example, digital certificate signature: a signature method based on digital certificates. Electronic conversion of handwritten signature: converting a handwritten signature into an electronic form. SMS verification code signature: confirming the signature through an SMS verification code. The platform provides the electronic signature function for buyer A and supplier B. Buyer A selects the electronic conversion of the handwritten signature, and supplier B selects the SMS verification code signature. After both parties complete the signature, the contract comes into effect. Real-name authentication can refer to the process by which the platform verifies the identities of both parties signing the electronic contract. For example, identity information verification: verifying the identity information of the signer to ensure the authenticity of the signing act. Legal effect: ensuring that the electronic signature has legal effect. When signing an electronic contract, the platform requires buyer A and supplier B to provide their ID numbers and mobile phone numbers for real-name authentication. After the verification passes, the electronic signatures of both parties have legal effect.

[0067] The contract clause review module can refer to the functional module on the platform for automatically detecting legal risks in electronic contracts. For example, clause review: checking whether the contract clauses comply with legal regulations and industry standards. Risk reminder: reminding both parties of the potential legal risks existing in the contract. The contract clause review module of the platform detects that the liability for breach of contract clause is missing in the contract and automatically prompts buyer A and supplier B to supplement the relevant content to avoid potential legal risks. Contract performance tracking can refer to the real-time monitoring of the contract performance process by the platform. For example, preset node reminder: reminding both parties to fulfill their obligations at key nodes of the contract performance. Performance record: recording the detailed process of contract performance, including information such as delivery and payment. The platform sets multiple preset nodes during the contract performance process, such as the delivery date and the payment date. Three days before the delivery date, the platform reminds supplier B to deliver the goods on time; three days before the payment date, the platform reminds buyer A to make the payment on time. At the same time, the platform records the specific situation of each delivery and payment to ensure the smooth performance of the contract.

[0068] In some other embodiments of this specification, the obtaining of the inquiry list published by the buyer on the pre-created supply and demand trading platform further includes: Virtual reality (VR) / augmented reality (AR) assisted inquiry function: The platform provides virtual reality or augmented reality tools, allowing buyers to display and experience the actual application scenarios of products in a virtual environment. Through VR / AR technology, buyers can more intuitively display product requirements, including the product's installation location, usage environment, and coordination with other equipment, etc., to help suppliers understand the requirements more accurately and improve the accuracy of quotations.

[0069] Intelligent voice interactive inquiry: The platform supports voice input and voice interaction functions. Buyers can publish inquiry lists through voice commands. The platform automatically converts voice content into text through voice recognition technology, and performs intelligent verification and supplementation. At the same time, the platform can also feedback the verification results and suggestions of the inquiry list to buyers through voice synthesis technology, providing a more convenient interactive experience.

[0070] Dynamic adjustment of demand and real-time feedback: After the inquiry list is released, the platform allows buyers to adjust the inquiry content according to market changes or their own needs, such as modifying product specifications, quantity, price range, etc. The platform pushes the adjusted inquiry list to the matched target suppliers in real time and records the feedback information of the suppliers to ensure that both parties can respond to demand changes in a timely manner and improve the flexibility and adaptability of transactions.

[0071] Blockchain-based inquiry list evidence storage: The platform uses blockchain technology to store the inquiry list published by the buyer to ensure that the inquiry list cannot be tampered with and is traceable. Blockchain evidence storage provides a legal basis for subsequent transactions, enhances the security and trust of transactions, and provides reliable data support for resolving potential disputes.

[0072] In some other embodiments of the present specification, the correlation between the price fluctuation of raw materials and the price fluctuation of finished products, as well as other related products that buyers will purchase after purchasing products, is detected, including: Association rule mining: Construct a data set containing raw material price fluctuations and finished product price fluctuations. Each data point includes the raw material price, finished product price, and the corresponding timestamp.

[0073] Statistical methods are used to calculate the correlation between raw material price fluctuations and finished product price fluctuations, and time series analysis methods are used to determine the causal relationship between raw material price fluctuations and finished product price fluctuations.

[0074] Use association rule mining algorithms (such as Apriori algorithm or FP-Growth algorithm) to mine the association rules between raw material price fluctuations and finished product price fluctuations, set minimum support and confidence thresholds, and screen out statistically significant association rules.

[0075] For example, through correlation calculation, it is found that there is a strong positive correlation between the price fluctuations of raw material A and the price fluctuations of finished product B. The correlation coefficient is 0.85, exceeding the preset correlation threshold. Using the Granger causality test, it is determined that the price fluctuations of raw material A have a significant causal relationship with the price fluctuations of finished product B, that is, an increase in the price of raw material A usually leads to an increase in the price of finished product B within one month. The algorithm mines the association rule: if the price of raw material A increases by 10%, then the probability that the price of finished product B will increase by 8% in the next month is 70%, which also exceeds the preset probability threshold, so there is an association.

[0076] Analysis of supporting procurement: Extract procurement records from the procurement behavior data of buyers, including information such as the types of products purchased, procurement time, and procurement quantity.

[0077] Perform preprocessing operations on the procurement behavior data, such as denoising, duplicate removal, and filling missing values, and group by buyers.

[0078] Use the association rule mining algorithm to analyze the procurement behavior data of buyers, mine other products that buyers usually purchase in a supporting manner after purchasing a certain product, set the minimum support and confidence thresholds, and screen out the supporting procurement rules with statistical significance.

[0079] For example, analyze the procurement behavior: analyze the procurement records of buyers and find that after buyers purchase finished product B, they usually purchase finished product C or finished product D in a supporting manner. Mine the supporting procurement rule: if a buyer purchases finished product B, then the probability of purchasing finished product C in the next month is 60%, and the probability of purchasing finished product D is 40%, both exceeding the preset probability threshold, so there is an association.

[0080] Result presentation and application: Present the association rules between the price fluctuations of raw materials and the price fluctuations of finished products, as well as the supporting procurement rules mined in an intuitive way to users, for example, display the correlation curve and the supporting procurement association network diagram through visual charts.

[0081] Provide decision-making support for suppliers and buyers according to the association rules and supporting procurement rules. For example, suppliers adjust production plans and pricing strategies according to the price trend prediction of finished products based on the price fluctuations of raw materials, and buyers optimize procurement plans to reduce costs according to the supporting procurement rules.

[0082] In some other embodiments of this specification, through the modeling and analysis of historical data, predict the price change trends of various products within a preset future time period, and inform buyers and suppliers in advance of the possible trends of market prices, including: Data collection and preprocessing: Collect historical market price data, including information such as the prices of various products, timestamps, sales volumes, market supply and demand situations, etc. Clean the collected data to remove duplicate, incorrect, or missing data records, and standardize the formats to ensure data consistency and usability.

[0083] Feature engineering: Extract features related to price changes, including time features (such as seasons, months, weeks), market supply and demand features (such as inventory levels, sales growth rates), macroeconomic features (such as inflation rates, interest rates), etc. Calculate statistical features of historical prices, such as mean, variance, volatility, etc., as input features for the model.

[0084] Model selection and training: Select models suitable for time series forecasting, such as ARIMA (Autoregressive Integrated Moving Average), LSTM (Long Short-Term Memory Network), Prophet, etc. Use historical market price data to train the model and adjust the model parameters to optimize the forecasting performance. Evaluate the accuracy and generalization ability of the model through methods such as cross-validation to ensure the forecasting effect of the model in different time periods.

[0085] Price forecasting: Use the trained model to forecast the prices of various products within a preset future time period and generate price forecasting curves. Combine market dynamic factors (such as raw material price fluctuations, policy changes, etc.) to adjust the forecasting results and improve the forecasting accuracy.

[0086] Result presentation and notification: Present the forecasting results to buyers and suppliers in the form of visual charts (such as line charts, bar charts) to intuitively show the future price change trends. Notify buyers and suppliers in advance of the possible directions of market prices, including information such as the magnitude of price increases or decreases and the duration of trends, to help them formulate procurement or sales strategies in advance.

[0087] Dynamic update and feedback: Regularly update the model, retrain the model by combining the latest market price data to adapt to market changes. Collect feedback from buyers and suppliers on the forecasting results to further optimize the model and forecasting process and improve the practicality and accuracy of the forecasting.

[0088] For example, assume that the platform has collected the price data of a certain electronic product in the past year, including information such as the average monthly price, sales volume, inventory level, etc. Price forecasting is achieved through the following steps.

[0089] Data collection and preprocessing: The collected data includes: in January 2024, the price was 500 yuan, the sales volume was 1000 pieces, and the inventory level was 2000 pieces; in February, the price was 520 yuan, the sales volume was 1200 pieces, and the inventory level was 1800 pieces, etc. Clean the data, remove outliers (such as data points with abnormally large price fluctuations), and unify the data format.

[0090] Feature engineering: Extract time features: month, season. Extract market supply and demand features: monthly sales growth rate, inventory level change rate. Calculate statistical features such as price volatility.

[0091] Model selection and training: Select the ARIMA model for time series prediction. Use the data of the past 12 months to train the model, and optimize the prediction performance by adjusting the model parameters (such as autoregressive terms, differencing terms, moving average terms). Evaluate the accuracy of the model through cross-validation to ensure that the prediction errors of the model within different time periods are within a reasonable range.

[0092] Price prediction: Use the trained ARIMA model to predict the price change trend in the next 3 months and generate a prediction curve. Adjust the prediction results in combination with the raw material price fluctuations (such as a 5% increase in raw material prices), and predict that the prices in the next 3 months will increase by 3%, 4%, and 5% respectively.

[0093] Result presentation and notification: Show the price prediction curve for the next 3 months in the form of a line chart to clearly present the upward price trend. Notify buyers and suppliers in advance, and suggest that buyers increase their purchase volume before the price increase, and suggest that suppliers adjust their production plans and pricing strategies according to the price trend.

[0094] Dynamic update and feedback: Update the model monthly, retrain the model in combination with the latest market price data to ensure the timeliness and accuracy of the prediction results. Collect feedback from buyers and suppliers, such as evaluations of the accuracy and practicality of the prediction results, and further optimize the model and prediction process.

[0095] Based on the same general inventive concept, the present invention also protects an inquiry device based on supply and demand transactions, as Figure 2 shown, Figure 2 is a schematic structural diagram of the inquiry device based on supply and demand transactions provided by an embodiment of the present invention. The inquiry device based on supply and demand transactions provided by the present invention will be described below, and the inquiry device based on supply and demand transactions described below can be mutually referred to with the inquiry method based on supply and demand transactions described above.

[0096] The inquiry device based on supply and demand transactions includes an inquiry list module 201, a matching module 202, a quotation list module 203, an order module 204, a tracking module 205, an evaluation module 206, and a feedback module 207.

[0097] The inquiry list module 201 obtains the inquiry list published by the buyer on a pre-created supply and demand trading platform; wherein, the inquiry list includes product specifications, quantity, price range, delivery period, and quality standards. The matching module 202 matches the inquiry list according to the evaluation indicators of the suppliers registered on the supply and demand trading platform to obtain the target suppliers, and sends the inquiry list to the target suppliers; wherein, the evaluation indicators include historical performance, product quality, price competitiveness, and delivery ability. The quotation list module 203 obtains the quotation list submitted by the target supplier on the supply and demand trading platform and pushes the quotation list to the buyer on the supply and demand trading platform; wherein, the quotation list includes price, quantity, and estimated delivery date. The order module 204 obtains the final supplier selected by the buyer among the target suppliers and forms an order between the buyer and the final supplier based on the supply and demand trading platform. The tracking module 205 tracks the progress status of the order and feeds back the progress status to the buyer and the final supplier. When the evaluation module 206 obtains the completion information of the order, it provides an evaluation list to the buyer. The feedback module 207 obtains the evaluation results of the evaluation list and feeds them back to the final supplier.

[0098] Figure 3 It is a schematic structural diagram of the electronic device provided by the embodiment of the present invention. As Figure 3 shown, the electronic device may include: a processor 310, a communication interface 320, a memory 330, and a communication bus 340. Among them, the processor 310, the communication interface 320, and the memory 330 communicate with each other through the communication bus 340. The processor 310 can call the logical instructions in the memory 330 to execute the inquiry method based on supply and demand transactions.

[0099] In addition, when the logical instructions in the above-mentioned memory 330 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0100] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the inquiry method based on supply and demand transactions provided by the above-mentioned various methods.

[0101] On another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is implemented to execute the inquiry method based on supply and demand transactions provided by the above-mentioned various methods.

[0102] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative labor.

[0103] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the technical solution, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disks, optical discs, etc., and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An inquiry method based on supply and demand transactions, characterized in that, Including: Obtain the inquiry list posted by the buyer on a pre-created supply and demand trading platform; wherein, the inquiry list includes product specifications, quantity, price range, delivery date, and quality standards. Match the inquiry list according to the evaluation indicators of the suppliers registered on the supply and demand trading platform to obtain target suppliers, and send the inquiry list to the target suppliers; wherein, the evaluation indicators include historical performance, product quality, price competitiveness, and delivery ability. Obtain the quotation list submitted by the target suppliers on the supply and demand trading platform, and push the quotation list to the buyers on the supply and demand trading platform; wherein, the quotation list includes price, quantity, and estimated delivery date. Obtain the final supplier selected by the buyer from the target suppliers, and form an order between the buyer and the final supplier based on the supply and demand trading platform. Track the progress status of the order, and feedback the progress status to the buyer and the final supplier. When the completion information of the order is obtained, provide an evaluation list to the buyer. Obtain the evaluation results of the evaluation list and feedback them to the final supplier.

2. The inquiry method based on supply and demand transactions according to claim 1, wherein The step of matching the inquiry list according to the evaluation indicators of the suppliers registered on the supply and demand trading platform to obtain target suppliers, and sending the inquiry list to the target suppliers includes: Based on the data collection and preprocessing subsystem of the supply and demand trading platform, collect various types of data of the suppliers, perform data cleaning and standardization processing on various types of data to obtain target data. Based on the feature extraction and model training subsystem of the supply and demand trading platform, convert the target data into feature vectors, and perform model training based on the feature vectors to obtain an evaluation model of the suppliers. Based on the real-time matching and recommendation subsystem of the supply and demand trading platform, convert the inquiry list into a demand vector, and use a similarity matching algorithm to match the demand vector and the evaluation model to obtain a group of suppliers that match the demand vector. Sort the suppliers in the group of suppliers according to the comprehensive score from high to low, and select the top N suppliers as target suppliers, and send the inquiry list to the target suppliers; N is an integer greater than 1.

3. The inquiry method based on supply and demand transactions according to claim 1, characterized in that, The step of obtaining the quotation list submitted by the target suppliers on the supply and demand trading platform, and pushing the quotation list to the buyers on the supply and demand trading platform includes: Obtain the quotation link of the supply and demand trading platform clicked by the target supplier, and display a quotation submission page; wherein, the quotation submission page includes a quotation template provided by the supply and demand trading platform for the target supplier, the quotation template pre-fills some information, and provides a reference cost price range, the market average transaction price within a preset period, and a recommended profit margin range. Obtain the quotation list submitted by the target supplier; wherein, the quotation list includes the price and estimated delivery date filled in by the target supplier according to the quotation template. Based on the supply and demand trading platform, verify the quotation list submitted by the target supplier, and push the quotation list that passes the verification to the buyers on the supply and demand trading platform.

4. The inquiry method based on supply and demand transactions according to claim 1, characterized in that Obtaining the final supplier selected by the buyer from the target suppliers and forming an order between the buyer and the final supplier based on the supply and demand trading platform includes: Based on the supply and demand trading platform, presenting an evaluation and selection page to the buyer; wherein, the evaluation and selection page includes a quotation summary list and supplier information; Obtaining the weights of each evaluation criterion set by the buyer through the supply and demand trading platform; wherein, the evaluation criteria include product quality, price, delivery date, after-sales service, and supplier reputation; Based on the supply and demand trading platform, determining the comprehensive score of each target supplier according to the weights set by the buyer and the actual performance of the supplier, and generating an evaluation report and a comparison chart; Obtaining the final supplier selected by the buyer according to the evaluation report and the comparison chart and forming an order.

5. The inquiry method based on supply and demand transactions according to claim 1, characterized in that, Tracking the progress status of the order and feeding back the progress status to the buyer and the final supplier includes: Based on the pre-established data interaction mechanism between the supply and demand trading platform and the production management system and logistics distribution system of the supplier, obtaining the production progress information and logistics transportation status information of the final supplier; Based on the supply and demand trading platform, updating the production progress information and the logistics transportation status information to the status page of the order in real time and presenting them to the buyer and the final supplier in a visual manner; When it is monitored that the production progress information and the logistics transportation status information are abnormal, starting an early warning mechanism based on the supply and demand trading platform, sending an abnormal notice to the buyer and the final supplier, and providing a solution.

6. The inquiry method based on supply and demand transactions according to claim 1, characterized in that The method further includes: Based on the supply and demand trading platform, cleaning, preprocessing, and analyzing the procurement behavior data of the buyer, the sales data of the supplier, and the market price data, and generating a market trend analysis report and procurement strategy optimization suggestions; Based on the supply and demand trading platform, providing the market trend analysis report and procurement strategy optimization suggestions to the buyer and the supplier.

7. The inquiry method based on supply and demand transactions according to claim 6, characterized in that, Based on the supply and demand trading platform, cleaning, preprocessing, and analyzing the procurement behavior data of the buyer, the sales data of the supplier, and the market price data, and generating a market trend analysis report and procurement strategy optimization suggestions, includes: Based on the data collection module of the supply and demand trading platform, collecting the procurement behavior data of the buyer, the sales data of the supplier, and the market price data; wherein, the procurement behavior data includes procurement time, product type, quantity, amount, procurement frequency, procurement source and usage distribution, and the sales data includes sales quantity, sales amount, sales price trend, sales area distribution, customer type and distribution; Based on the data cleaning module of the supply and demand trading platform, denoising, de-duplicating, filling in missing values, correcting error values, and standardizing the format of the procurement behavior data, the sales data of the supplier, and the market price data; Based on the data analysis module of the supply and demand trading platform, the clustering analysis algorithm is used to classify buyers and suppliers according to procurement behavior data, suppliers' sales data, and market price data, including: classifying buyers into high-frequency high-value, high-frequency low-value, low-frequency high-value, and low-frequency low-value according to procurement frequency and procurement amount, and analyzing their procurement preferences, demand trends, and price sensitivities for different types of buyer groups; Based on the data analysis module of the supply and demand trading platform, the association rule mining algorithm is used to detect the association relationships in the dataset, including: detecting the association between raw material price fluctuations and finished product price fluctuations, and other related products that buyers will purchase as a package after purchasing products; Based on the data analysis module of the supply and demand trading platform, the time series analysis model is used to predict market price trends, demand change trends, and seasonal fluctuation rules, including: predicting the price change trends of various products within a preset future time period through modeling and analysis of historical data, and informing buyers and suppliers in advance of the possible direction of market prices.

8. The inquiry method based on supply and demand transactions according to claim 1, wherein It also includes: After the buyer issues an inquiry list, based on the supply and demand trading platform, other products or services related to the current inquiry list are automatically recommended by analyzing the buyer's historical procurement behavior and preferences; Based on the supply and demand trading platform, analyze the production capacity and inventory level of suppliers, and provide suggestions for buyers to optimize their procurement plans.

9. The inquiry method based on supply and demand transactions according to claim 1, wherein The obtaining of the inquiry list issued by the buyer on the pre-created supply and demand trading platform includes: Obtain the login instruction of the buyer on the supply and demand trading platform and display the page of the inquiry list; When receiving the completion instruction of the buyer's inquiry list, based on the verification system of the supply and demand trading platform, verify the information in the inquiry list; When receiving the identity confidentiality requirement of the buyer's inquiry list, generate a unique anonymous identifier for the buyer's identity; When receiving the identity disclosure requirement of the buyer's inquiry list, generate a registered name for the buyer's identity.

10. The inquiry method based on supply and demand transactions according to claim 1, wherein, After forming an order between the buyer and the final supplier based on the supply and demand trading platform, it also includes: When the buyer confirms the order, the supply and demand trading platform automatically triggers the electronic contract generation process, and generates an electronic contract based on the standardized contract template and the order of both parties; Based on the supply and demand trading platform, provide an electronic signature function for the buyer and the final supplier, and conduct real-name authentication and encrypted backup for the signing process; Store the signed electronic contract in the storage repository of the platform, generate a unique number and a QR code for viewing and downloading; Based on the contract clause review module of the supply and demand trading platform, automatically detect legal risks in the contract; Based on the supply and demand trading platform, track the contract performance situation in real time, and remind both parties to fulfill their obligations at preset nodes.

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