CN120338914A - Inquiry method based on supply and demand transactions - Google Patents

Abstract

The present invention provides an inquiry method based on supply and demand transactions, comprising obtaining an inquiry list published by a buyer on a pre-created supply and demand transaction platform; matching the inquiry list according to evaluation indicators of suppliers registered on the supply and demand transaction platform 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 buyers on 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 status of the order, and feeding back the progress status to the buyer and the final supplier; when the completion information of the order is obtained, providing the buyer with an evaluation list; obtaining the evaluation result of the evaluation list, and feeding back to the final supplier, which can effectively and accurately match the buyer's needs with the supplier, improve the transaction efficiency, and reduce the transaction cost.

Description

Price inquiring method based on supply and demand transaction

Technical Field

The invention relates to the technical field of electronic commerce, in particular to a price inquiring method based on supply and demand transaction.

Background

Under the current surge of global economy integration, the market environment in which enterprises are located is increasingly competitive, and efficient operation of a supply chain becomes a key element for enterprises to acquire competitive advantages. However, the conventional source-seeking price-inquiring mode has various defects in efficiency, information symmetry, user experience and the like.

Specifically, for example, the conventional price inquiry method mainly relies on manual screening and matching, and it is difficult to accurately find the supplier which meets the requirements, so that the purchasing efficiency is low, and the quality supplier is easy to miss. Meanwhile, the purchasing flow is complicated, a buyer needs to fill in a large amount of information manually, and effective tool support is lacking in evaluating the quotation of the supplier, so that the operation difficulty and the time cost are increased. In addition, the information of the buyer and the seller is asymmetric, the buyer is difficult to acquire the detailed information of the provider, the provider is difficult to accurately grasp the requirement of the buyer, the purchasing decision is lack of basis, and the purchasing risk is increased.

Disclosure of Invention

The invention provides a price inquiring method based on supply and demand transaction, which is used for solving the technical problem that corresponding suppliers cannot be matched for buyers efficiently and accurately in the prior art.

In one aspect, the present invention provides a price inquiring method based on supply and demand transactions, including:

Acquiring a price inquiry list issued by a buyer on a pre-established supply and demand transaction platform, wherein the price inquiry list comprises product specifications, quantity, price range, delivery date and quality standard;

Matching the price inquiry list according to the evaluation indexes of the suppliers registered by the supply and demand transaction platform to obtain a target supplier, and sending the price inquiry list to the target supplier, wherein the evaluation indexes comprise historical performance, product quality, price competitiveness and delivery capacity;

Acquiring a quotation submitted by the target provider at the supply-demand trading platform, and pushing the quotation to a buyer of the supply-demand trading platform, wherein the quotation comprises price, quantity and expected delivery date;

Acquiring a final provider selected by a buyer from the target providers, and forming an order between the buyer and the final provider based on the supply-demand transaction platform;

tracking the progress status of the order and feeding back the progress status to the buyer and the final supplier;

providing an evaluation list to a buyer when the completion information of the order is acquired;

and obtaining an evaluation result of the evaluation list and feeding back the evaluation result to the final supplier.

According to the price inquiring method based on the supply and demand transaction, according to the evaluation indexes of the suppliers registered by the supply and demand transaction platform, the price inquiring list is matched to obtain the target suppliers, the price inquiring list is sent to the target suppliers, the quotation list submitted by the target suppliers at the supply and demand transaction platform is obtained, the quotation list is pushed to the buyers of the supply and demand transaction platform, the final suppliers selected by the buyers from the target suppliers are obtained, and orders between the buyers and the final suppliers are formed based on the supply and demand transaction platform. Through realizing the whole process management from acquisition of price inquiring lists to order formation and order progress tracking on a supply and demand trading platform, the method can efficiently and accurately match the demands of buyers with suppliers, quickly screen out proper target suppliers and push the price inquiring lists, enable the suppliers to respond and submit quotation lists in time, and enable buyers to select final suppliers and form orders based on the quotation lists. In addition, the method can track the progress of the order and feed back the state, and can provide an evaluation mechanism after the order is completed, so that the transaction efficiency is improved, the transaction cost is reduced, the transaction experience of both supply and demand parties is enhanced, and the smooth proceeding of the supply and demand transaction is promoted.

Drawings

In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a price inquiring method based on supply and demand transactions according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of a price inquiring device based on supply and demand transactions according to an embodiment of the present invention;

fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Fig. 1 is a flow chart of a price inquiring method based on supply and demand transactions according to an embodiment of the present invention. The execution subject of the method can be a computer, a tablet computer, intelligent wearable equipment and the like.

Referring to fig. 1, the price inquiring method based on the supply-demand transaction may include the following steps.

Step 101, acquiring a price inquiry list issued by a buyer on a pre-established supply and demand transaction platform, wherein the price inquiry list comprises product specifications, quantity, price range, delivery date and quality standard.

In this step, the product specifications may include model number, size, performance parameters, and the like. The quality standards can include ISO 9001 standard, ISO 22000:2018, and the like, and can be defined according to the demands of buyers, and the quality standards are not listed. An example of the price inquiry list is that 1000 electronic products with the model number of XJ-2023 are purchased, the unit price expectation is between 50 and 70 yuan, the delivery period is 30 days, and the quality standard is required to be in accordance with ISO 9001. The second example of the price inquiry list is to purchase a product, namely a mobile phone, 256GB blue, 1000 price, 5000-6000 price range, a delivery date of 2025, 3 months and 15 days ago, and a quality standard of genuine products of original factories, which are brand new and not unpacked. The listing of queries may also include other information such as customized packaging and specific after-market services, etc., which are not listed here.

And 102, matching the price inquiry list according to the evaluation indexes of the suppliers registered by the supply and demand transaction platform to obtain a target supplier, and sending the price inquiry list to the target supplier, wherein the evaluation indexes comprise historical performance, product quality, price competitiveness and delivery capacity.

In this step, the historical performance may refer to a supply schedule rate (e.g., 90%), a good rate (e.g., 95%), etc. over a period of time (e.g., one year, one quarter, or one month). Product quality may refer to product yield (e.g., 95%), free exchange time, etc. Price competitiveness may refer to the result of a provider's offer compared to the average price of the market, e.g., the offer is 10% below the average price of the market. Delivery capacity may refer to a yield per unit time, such as 5000 units of monthly production. The evaluation index may also comprise other information, which is not listed here.

Step 103, acquiring a quotation submitted by a target provider at a supply-demand trading platform, and pushing the quotation to a buyer of the supply-demand trading platform, wherein the quotation comprises price, quantity and expected delivery date.

Examples of the bill of quotes in this step are "product: cell phone, specification: 256GB, blue, quantity: 1000, quotes: 5500 yuan each, estimated date of delivery: 2025, 3 months, 10 days. The bill of quote may also include other information, which is not listed here.

Step 104, 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-demand transaction platform.

In this step, examples of orders are order number 20250301-001, purchase product, cell phone, specification 256GB, blue color, number 1000, unit price 5500 Yuan, total price 550 ten thousand Yuan, delivery date 2025, 3 months and 10 days. The order may also include other information, which is not listed here. It will be appreciated that the order is generated based on the price inquiry list and the price quotation list, or may be filled in according to an order template after the negotiation between the buyer and the provider.

Step 105, track the progress status of the order and feed back the progress status to the buyer and the final supplier.

In this step, the progress status of the order may include the progress of the production, for example 80% completed, and may also include the status of the logistics, for example, the goods have been shipped, and are expected to arrive after 3 days.

And 106, providing an evaluation list for the buyer when the completion information of the order is acquired.

In this step, the evaluation list may contain the following items of product quality evaluation, delivery date evaluation, service attitude evaluation, price rationality evaluation, and the like.

And 107, acquiring an evaluation result of the evaluation list and feeding back the evaluation result to a final provider.

In this embodiment, according to the evaluation index of the supplier registered by the supply and demand transaction platform, the price inquiry list is matched to obtain the target supplier, the price inquiry list is sent to the target supplier, the price quotation submitted by the target supplier on the supply and demand transaction platform is obtained, the price quotation is pushed to the buyer of the supply and demand transaction platform, the final supplier selected by the buyer in the target supplier is obtained, and an order between the buyer and the final supplier is formed based on the supply and demand transaction platform. According to the method, the full-flow management from acquisition of the price inquiry list to order formation and order progress tracking is achieved on the supply and demand trading platform, the demands of buyers and suppliers can be accurately matched, suitable target suppliers can be rapidly screened out, the price inquiry list is pushed, the suppliers can timely respond and submit the price inquiry list, and the buyers select final suppliers and form orders based on the price inquiry list. In addition, the method can track the progress of the order and feed back the state, and can provide an evaluation mechanism after the order is completed, so that the transaction efficiency is improved, the transaction cost is reduced, the transaction experience of both supply and demand parties is enhanced, and the smooth proceeding of the supply and demand transaction is promoted.

A specific example is shown below, assuming that an electronic manufacturing enterprise (buyer) needs to purchase a batch of electronic components. It issues a price inquiry list on the supply and demand trade platform, and the list details the specification (such as model, size and performance parameter), quantity (1000 pieces), price range (50-70 yuan each), delivery period (within 30 days) and quality standard (meeting ISO 9001 standard) of the required electronic components. The platform matches according to the evaluation indexes (such as historical supply performance, product quality qualification rate, price competitiveness and delivery timing rate) of registered suppliers, screens out several target suppliers meeting the conditions, and sends the price inquiry list to the suppliers. The suppliers A, B, C submit a list of offers, including prices (60, 65, 58, respectively), and estimated delivery dates (25 days each). After the buyer views these listings through the platform, provider C is selected as the final provider and an order is generated through the platform. The platform then tracks the production progress and logistics transportation status of the order and feeds this information back to the buyer and supplier C in real time. After the order is completed, the platform provides an evaluation list for the buyer, the buyer evaluates the product quality, delivery date, service attitude and the like of the provider C, and the evaluation result is fed back to the provider C for improvement.

In an embodiment of the present disclosure, matching a price inquiry list according to an evaluation index of a supplier registered by a supply and demand transaction platform to obtain a target supplier, and sending the price inquiry list to the target supplier, including:

the first step is to collect various data of suppliers based on the data collection and preprocessing subsystem of the supply and demand transaction platform, and to carry out data cleaning and standardization processing on the various data to obtain target data.

And secondly, converting target data into feature vectors based on a feature extraction and model training subsystem of the supply and demand transaction platform, and carrying out model training based on the feature vectors to obtain an evaluation model of the supplier.

Thirdly, based on a real-time matching and recommending subsystem of the supply and demand trading platform, converting the price inquiring list into a demand vector, matching the demand vector with an evaluation model by using a similarity matching algorithm to obtain a supplier group matched with the demand vector, sequencing suppliers in the supplier group according to the sequence of comprehensive scores from high to low, screening out N suppliers with the top ranking as target suppliers, and sending the price inquiring list to the target suppliers, wherein N is an integer greater than 1.

In this embodiment, in the first step, on one hand, the provider needs to submit detailed basic information of the enterprise, such as enterprise scale, production capacity, operation range, qualification certificate, etc., product catalog information including product name, model number, specification, detailed parameters, picture display, price system, etc., and historical transaction records (i.e. historical performance data), such as transaction time, transaction amount, product quantity, customer information, delivery time, quality feedback, etc., of the past orders when the provider is on the platform. On the other hand, the platform acquires market data such as credit rating, financial status, legal dispute records and the like of the suppliers from the third party authority credit institution, and simultaneously collects information such as industry standards, technical development trends, market supply and demand dynamics and the like from industry associations and professional research institutions so as to enrich data dimension. After entering the platform, the original data firstly goes through a strict data cleaning flow, and the repeated, invalid, erroneous or incomplete data records, such as deleting product parameters with wrong format, correcting obviously unreasonable price data and the like, are removed by using a data filtering algorithm. And then, data in different formats and units are uniformly converted into a standard format through data standardization processing, for example, all date formats are uniformly converted into YYYY-MM-DD, currency units are uniformly converted into RMB (RMB) and the like, so that the consistency and the usability of the data are ensured, and a foundation is laid for subsequent analysis processing.

In the second step, historical performance data of the suppliers are quantified into specific characteristic values by calculating indexes such as on-time delivery rate (ratio of on-time delivery order quantity to total order quantity), product quality qualification rate (ratio of qualified product quantity to total delivery product quantity), customer repeat purchase rate (ratio of repeat purchase customer quantity to total customer quantity), customer complaint rate (ratio of complaint order quantity to total order quantity), etc., key technical indexes (such as chip process of electronic products, machining precision of mechanical products, etc.) in the production process, key elements (such as whether the quality management system authentication of ISO9001, sampling proportion and frequency of internal quality detection, etc.), various authentication quantity and grade obtained by the products, etc., and characteristics such as deviation rate of the price of the suppliers and average price of the market, price fluctuation range, cost rate, etc., and characteristics such as capacity, average turnover rate of stock, average time of the stock, average delivery and accuracy vector of the quality control system are calculated for the relevant data of the products, so that comprehensive performance parameters such as accuracy and accuracy vector are comprehensively reflected. Based on the feature vectors, model training is performed by adopting a plurality of machine learning algorithms, such as a classification algorithm based on decision trees is used for primarily screening suppliers meeting basic conditions, a regression algorithm based on a neural network is used for accurately predicting comprehensive scores of the suppliers, repeated training and verification are performed by continuously adjusting parameters and structures of the models and utilizing a large amount of historical data, performance and accuracy of the models are optimized, and finally an efficient and accurate comprehensive evaluation model and a demand matching model of the suppliers are constructed.

In the third step, natural language processing technology and semantic analysis algorithm are used for analyzing the price inquiring list of the buyer, and the key product characteristics, quantity, price range, delivery date and other demand information are extracted and converted into standardized demand vectors with the same dimensionality as the characteristic vectors of the suppliers. And then, comparing and calculating the demand vector with a trained comprehensive supplier assessment model, and finding out a supplier group which is most matched with the demand by using a similarity matching algorithm. During the matching process, the performance of the suppliers in each dimension is weighted and scored according to preset feature weights (which can be dynamically adjusted and optimized according to the big data accumulated by the platform and the experience of industry experts), for example, the weight of the delivery capacity feature is correspondingly increased for a purchase demand with strict requirements on delivery period. And finally, sorting suppliers according to the order of the comprehensive scores from high to low, screening a top-ranked high-quality supplier list, recommending detailed information (including enterprise basic information, product information, quotation information, comprehensive scores, each dimension score condition and the like) to the buyer, and simultaneously providing a detailed analysis report of the matching degree of each supplier and the requirement for the buyer so as to help the buyer to deeply understand the advantages and characteristics of the recommended suppliers and make a more intelligent decision.

In the process of matching the target suppliers, various data of the suppliers are cleaned and standardized through the data acquisition and preprocessing subsystem, accuracy and consistency of the data are guaranteed, the feature extraction and model training subsystem is used for converting the data into feature vectors and training an evaluation model, comprehensive strength of the suppliers can be evaluated more accurately, and finally the real-time matching and recommending subsystem is used for combining the evaluation model through a similarity matching algorithm, and the N-ranked target suppliers are selected according to comprehensive score sorting.

In an embodiment of the present disclosure, obtaining a bid list submitted by a target provider at a supply and demand transaction platform, and pushing the bid list to a buyer of the supply and demand transaction platform includes:

The method comprises the steps of acquiring a quotation link of a supply and demand trading platform clicked by a target provider, and displaying a quotation submitting page, wherein the quotation submitting page comprises a quotation template provided by the supply and demand trading platform for the target provider, and the quotation template is pre-filled with partial information and provides a reference cost price interval, an average market price in a preset period and a suggested profit space range;

Acquiring a quotation list submitted by a target provider, wherein the quotation list comprises prices filled by the target provider according to a quotation template and predicted delivery dates;

and verifying the quotation submitted by the target provider based on the supply and demand transaction platform, and pushing the verified quotation to the buyer of the supply and demand transaction platform.

In the embodiment, the quotation template with the pre-filling information and the reference data is provided for the provider, so that the provider can be helped to fill in the quotation list more quickly and accurately, errors and uncertainty in the quotation process are reduced, meanwhile, the platform checks the submitted quotation list and pushes the submitted quotation list to the buyer, the quality and compliance of the quotation list are ensured, invalid or wrong quotation is prevented from interfering with the decision of the buyer, the efficiency and accuracy of a quotation link are improved, and the transaction process is accelerated.

Specifically, for example, the target provider clicks on the offer link of the supply-demand transaction platform, and presents an offer submission page. The page displays a quotation template provided by the platform for the provider, and partial information such as basic information of product specifications, quantity and the like in a price inquiry list is pre-filled in the template. At the same time, the platform also provides reference information, such as reference cost price interval of 100-120 elements per element according to market analysis, average market price of 130 elements per element in the past 3 months within preset period, and recommended profit margin range of 10-20% of the profit margin range recommended by the platform. The contents of the bill of quote may be shown as price 135 element/piece (price determined by the supplier based on cost, average market price and suggested profit margin taken into account), estimated date of delivery, 2025, 3 months 15 days (estimated date of delivery by the supplier based on its own capacity and current order conditions).

In one embodiment of the present disclosure, obtaining a final supplier selected by a buyer from target suppliers, and forming an order between the buyer and the final supplier based on a supply and demand transaction platform, includes:

Based on the supply-demand transaction platform, displaying an evaluation and selection page to a buyer, wherein the evaluation and selection page comprises a quotation summary list and provider information;

acquiring the weight of each evaluation standard set by a buyer through a supply-demand transaction platform, wherein the evaluation standards comprise product quality, price, delivery date, after-sales service and supplier credit;

Based on the supply-demand transaction platform, determining the comprehensive score of each target provider according to the weight set by the buyer and the actual performance of the provider, and generating an evaluation report and a comparison chart;

the final provider selected by the buyer based on the assessment report and the comparison chart is obtained and an order is formed.

In this embodiment, by providing the buyer with the evaluation and selection page, displaying the bid summary list and the supplier information, setting the evaluation standard weight for the buyer, and generating the evaluation report and the comparison chart according to the weight and the actual performance of the suppliers, the buyer is helped to evaluate each target supplier more intuitively and comprehensively, so that the final supplier which best meets the needs of the buyer can be selected more scientifically and an order can be formed. The decision support mode based on multidimensional evaluation and visual display enhances the decision basis of buyers, improves the accuracy and satisfaction of decisions, and is beneficial to establishing a better supply and demand cooperation relationship.

In particular, product quality may refer to the performance of a product provided by a provider in terms of quality standards, performance, durability, consistency, product yield, and the like. Lead time refers to the speed and punctuality at which a provider completes an order and delivers a product. After-market services refer to support and services provided by suppliers after delivery of products, including response time, problem solving capability, service attitude, warranty terms, and the like. Vendor reputation refers to the reputation and praise of the vendor in the market, including customer ratings, credit ratings, historical transaction records, and the like. Customer rating may refer to a comprehensive rating of the provider by the past customer. The credit rating may refer to a rating of the provider by a third party credit rating agency. The historical transaction record may refer to completion of past orders by the provider, customer satisfaction, etc.

The actual performance refers to the actual situation and history of the provider in terms of past transactions, production operations, customer services, etc. These performances are measured by specific data and facts, e.g. product quality, whether the provider's product meets quality criteria, frequency and severity of historical quality problems. Price-the price level offered by the provider, and the stability and competitiveness of the price. Delivery period-whether delivery time promised by the supplier is on time or not, and coping capability when an emergency is encountered. After-sales services-response time of the provider after delivery of the product, problem solving capability, and customer satisfaction. Vendor reputation-vendor's public praise in the marketplace, credit rating, and historical transaction records. The quality control method comprises the steps of providing a supplier A, performing quality control, namely, passing ISO 9001 control, performing quality control, wherein the quality control comprises the steps of enabling a quality problem feedback rate to be lower than 2% in the past year, and enabling a product with a quality qualification rate of 98% to pass quality detection. The quality certification of the supplier B is that the supplier B fails to pass the ISO 9001 certification, the historical quality problem is that the feedback rate of the quality problem is 5% in the past year, and the product with the quality qualification rate of 95% passes the quality detection.

In one embodiment of the present description, tracking the progress status of an order and feeding back the progress status to a buyer and a final supplier includes:

acquiring the production progress information and logistics transportation state information of a final supplier based on a pre-established data interaction mechanism of a supply and demand transaction platform, a production management system and a logistics distribution system of the supplier;

Based on a supply-demand trading platform, the production progress information and the logistics transportation state information are updated to a state page of an order in real time, and are presented to buyers and final suppliers in a visual mode;

when the production progress information and the logistics transportation state information are monitored to be abnormal, starting an early warning mechanism based on the supply and demand transaction platform, sending an abnormal notification to buyers and final suppliers, and providing a solution.

In the embodiment, based on the data interaction mechanism of the supply-demand transaction platform, the production management system of the suppliers and the logistics distribution system, the production progress and logistics transportation state information can be obtained in real time and presented to the buyers and the suppliers in a visual mode, so that both parties can know the order progress in time, when abnormality is monitored, an early warning mechanism can be started, a solution is provided, the real-time tracking and early warning function is realized, transparency and controllability of order management are enhanced, risks caused by information asymmetry are reduced, success rate of order on-time delivery is improved, and smooth proceeding of transactions is ensured.

Specifically, for example, suppose a buyer purchases a batch of electronic products from a supplier via a supply-demand trading platform, with an order number of 20250211-001. The platform operation comprises that the supply and demand transaction platform establishes a data interaction mechanism with a production management system (such as ERP) and a logistics distribution system (such as TMS) of a supplier to acquire the production progress and the logistics state of an order in real time. The platform obtains production progress information from the ERP system of the supplier, e.g., raw material procurement progress: 80% completed. The production process was completed by 50%. The completion time was expected to be 3 days later. The platform obtains logistics information from the logistics system, such as shipping time, i.e., shipping on day 2 after the completion of the intended production. And the goods are delivered at the in-transit position temporarily. The expected arrival time is 5 days after shipment. The platform updates the production progress and logistics state information to an order state page in real time and presents the order state page to buyers and suppliers in a visual mode. There are various visual display modes, for example, a progress bar, which displays 50% of production progress and 80% of raw material purchasing progress. Map tracking, displaying that the goods have not been shipped, the estimated shipment time and the arrival time.

The platform monitors the production progress and the logistics state in real time, and when abnormality is found, an early warning mechanism is started. For example, production delays, where the platform detects a delay in the provider's production progress, it is expected that this cannot be done on time. And (3) the logistics are abnormal, namely the platform detects that goods are detained in the logistics transportation process. The platform sends short messages to buyers and suppliers, wherein the short messages include the production schedule delay of orders 20250211-001, and the estimated delivery time delay of 3 days. The platform pops up prompt boxes on login interfaces of buyers and suppliers to display detailed abnormal information and solution suggestions, such as suggesting the suppliers to increase the production progress by hand or negotiating with the buyers to adjust delivery period.

In an embodiment of the present disclosure, the method further comprises:

Based on a supply-demand trading platform, cleaning, preprocessing and analyzing purchasing behavior data of buyers, sales data of suppliers and market price data, and generating a market trend analysis report and a purchasing strategy optimization suggestion;

market trend analysis reports and purchasing strategy optimization suggestions are provided to buyers and suppliers based on the supply-demand trading platform.

In this embodiment, through cleaning, preprocessing and analyzing buyer purchase behavior data, vendor sales data and market price data, a market trend analysis report and a purchase strategy optimization suggestion are generated, and provided to the buyer and the vendor, both parties can be helped to better understand market dynamics and self-transaction conditions, reasonable purchase and sales strategies are formulated in advance, resource allocation is optimized, purchase cost and inventory risk are reduced, market competitiveness is improved, and thus the efficiency and benefit of the whole supply and demand transaction ecology are improved.

In an embodiment of the present disclosure, cleaning, preprocessing and analyzing purchasing behavior data of a buyer, sales data of a provider and market price data based on a supply and demand transaction platform to generate a market trend analysis report and a purchasing strategy optimization suggestion, including:

The system comprises a data acquisition module based on a supply-demand transaction platform, a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module acquires purchasing behavior data of a buyer, sales data of a provider and market price data, wherein the purchasing behavior data comprises purchasing time, product types, quantity, amount, purchasing frequency, purchasing source place and using place distribution, and the sales data comprises sales quantity, sales amount, sales price trend, sales area distribution, customer type and distribution;

The data cleaning module based on the supply-demand transaction platform performs denoising, duplication removing, missing value filling, error value correcting and format standardization on purchasing behavior data, sales data of suppliers and market price data;

Classifying buyers and suppliers according to purchasing behavior data, sales data of the suppliers and market price data by using a clustering analysis algorithm based on a data analysis module of a supply-demand transaction platform, wherein the data analysis module comprises the steps of classifying the buyers into high-frequency high values, high-frequency low values, low-frequency high values and low-frequency low values according to purchasing frequencies and purchasing amounts, and analyzing purchasing preference, demand trend and price sensitivity of different types of buyer groups;

the data analysis module based on the supply-demand transaction platform detects the association relation in the data set by using an association rule mining algorithm, wherein the association relation between raw material price fluctuation and finished product price fluctuation is detected, and other related products which can be purchased in a matched manner after a buyer purchases the products are detected;

The data analysis module based on the supply and demand trading platform predicts market price trend, demand change trend and seasonal fluctuation law by using a time sequence analysis model, and comprises the steps of predicting the price change trend of various products in a preset time period in the future by modeling and analyzing historical data, and informing buyers and suppliers of possible trend of market price in advance.

In the embodiment, the specific method and content of data acquisition, cleaning and analysis are further refined, through acquiring comprehensive purchasing behavior and sales data, cleaning operations such as denoising, deduplication and the like are performed, and then various data analysis algorithms such as clustering analysis, association rule mining and time sequence analysis are used for classifying buyers and suppliers, mining association relations and predicting market trends, so that data values can be further mined, more powerful support is provided for generating accurate market trend analysis reports and purchasing strategy optimization suggestions, and the reports and suggestions are more targeted and practical and better serve decision requirements of the buyers and the suppliers.

Specifically, for example, the purchase time is the specific date and time the buyer made the purchase. The product category is the product category purchased by the buyer. Quantity is the quantity of products purchased each time. The sum is the total sum of each purchase. The purchasing frequency is the number of times the buyer makes purchases in a certain time. Purchasing sources and usage locations are distributed, namely, the geographical locations of the delivery locations and usage locations where the buyers purchase the products. Sales quantity: the number of products sold by the supplier. Sales amount-the total amount the provider obtains through sales. Sales price trend-the trend of the price of the provider product over time. Distribution of sales areas-distribution of vendor products. Customer type and distribution, i.e. industry, scale, registration address, etc. to which the customer purchasing the supplier product belongs.

Market price data refers to price information of similar products or services on the market, and the data reflects market supply and demand relations and price fluctuation conditions. For example, raw material price required for producing a product. And the price of the finished product is the market price of the final product. Price fluctuation trend, which is the trend of price change with time. Industry dynamic information, new technology development, policy and regulation change, competitor market share and the like.

The market trend analysis report may refer to a report generated regarding market dynamics, demand changes, price trends, etc., through analysis of purchasing behavior data, sales data, and market price data. For example, price trend, prediction of future market prices. Demand trend, the prediction of future market demand. Regional analysis, namely sales and demand conditions of markets in different areas. Industry dynamics-new technology, influence of policy and regulation changes on markets. For example, electronic product prices have increased over the past year, and prices are expected to remain between 110-120 elements/item for the next three months, with demand peaking in the third quarter of the year, suggesting that buyers stock in advance.

The purchasing strategy optimization suggestions can refer to suggestions provided for buyers on how to optimize purchasing flows, reduce cost and improve efficiency based on market trend analysis results. For example, cost optimization, how to reduce costs by reasonable arrangement of purchase time, quantity, etc. The suppliers select how to select the suppliers with high cost performance and good reputation. Inventory management, namely, how to reasonably arrange the inventory according to the demand trend. Risk management how market price fluctuations and supply risks are handled. For example, buyer A is recommended to increase the purchase amount when the price is low (e.g., the first quarter) to reduce the cost. Buyer a is recommended to consider establishing a long-term partnership with provider B because of its strong price competitiveness and high matching of sales areas to buyer needs.

The error values may include format errors, unreasonable values, duplicate data, missing values, logical errors, and the like. Denoising, namely removing abnormal values or noise in the data. Deduplication, deleting duplicate data records. Filling the missing value, namely filling the missing data according to historical data or a statistical method. Correcting error values, i.e., correcting erroneous or unreasonable data. And (5) format standardization, namely unifying the data format into a standard format. The high frequency high value means that the frequency of purchase is high and the amount of purchase is large, the high frequency low value means that the frequency of purchase is high and the amount of purchase is small, the low frequency high value means that the frequency of purchase is low and the amount of purchase is large, and the low frequency low value means that the frequency of purchase is low and the amount of purchase is small.

The platform is used for carrying out the function module of deep analysis to the data after washing to extract valuable information. For example, cluster analysis, grouping data with similar characteristics. And (5) association rule mining, namely discovering association relations in the data. And (5) time sequence analysis, namely predicting the change trend of the data along with time. And (3) visually displaying, namely displaying the analysis result in the forms of charts, reports and the like.

In an embodiment of the present disclosure, further includes:

After the buyer issues the price inquiring list, other products or services related to the current price inquiring list are automatically recommended based on the supply and demand trading platform by analyzing the historical purchasing behavior and preference of the buyer;

Based on the supply and demand transaction platform, the production capacity and inventory level of the suppliers are analyzed, and suggestions for optimizing the purchasing plan are provided for buyers.

In the embodiment, after the buyer issues the price inquiry list, related products or services are automatically recommended based on the platform analysis of the historical purchasing behavior and preference of the buyer, so that the buyer can be helped to expand the purchasing field, find potential purchasing demands and improve the completeness and the synergy of purchasing.

Specifically, for example, historical purchasing behavior may refer to records that a buyer left when conducting purchasing activities through a platform in the past. For example, the time of purchase is the specific date of each purchase, the type of purchased product is the type of product purchased in the past, the number of purchases is the number of products purchased each time, and the amount of purchase is the total amount of each purchase. The purchasing frequency is the number of times of purchasing in a certain time, and the purchasing source place and the using place are distributed. Purchasing preferences may refer to preferences and habits that a buyer exhibits during purchasing. For example, product preferences such as the type or brand of product that the buyer is inclined to purchase, price preferences such as the sensitivity and range of expectations of the buyer to price, lead time preferences such as the buyer's desire to lead time, quality preferences such as the buyer's desire for product quality, and service preferences such as the buyer's desire for after-market services.

Related products or services may refer to other products or services that have a direct association with the products or services in the buyer's current listing of queries. For example, the product used with the main product, such as charger, data line, etc., the substitute product, such as product with similar functions but different brands or specifications, and the value added service, such as installation service, after-sales service, customized service, etc.

Throughput may refer to the amount of product a provider can produce over a period of time. For example, the equipment utilization rate, the use efficiency of the production equipment. And (5) production progress, namely, the completion condition of the current production task. The upper limit of the productivity is the maximum production capacity of the equipment in full load operation. For example, the utilization rate of the production equipment of the supplier B is about 80%, the current production progress is normal, and the upper limit of the productivity is 1000 electronic products produced per month. Inventory levels may refer to the number of product inventory currently held by a provider. For example, the existing inventory, the number of products actually stored in the current warehouse. And (5) predicting the replenishment time, namely, predicting the arrival time of the next batch of goods. Inventory turnover rate, the turnover speed of inventory, reflecting the mobility and sales conditions of inventory.

The advice for optimizing the procurement plan may refer to advice provided to the buyer regarding how to optimize the procurement plan based on the production capacity and inventory levels of the suppliers. For example, purchase time advice, suggesting when the buyer places an order to ensure delivery on time. Purchasing quantity advice the specific quantity purchased by the buyer is advised to avoid stock backlog or backorder. Batch purchase advice, advice whether the buyer needs batch purchase, and the purchase time and quantity of each batch. Risk cues alert buyers of supply risks that may be faced, such as production delays or under-stocking.

In one embodiment of the present disclosure, obtaining a query list issued by a buyer on a pre-created supply and demand transaction platform includes:

Acquiring a login instruction of a buyer on a supply and demand transaction platform, and displaying a page of a price inquiring list;

When receiving a completion instruction of the price inquiring list of the buyer, verifying the information in the price inquiring list based on a verification system of the supply-demand trading platform;

when receiving the identity confidentiality requirement of the price inquiring list of the buyer, generating a unique anonymous identifier for the identity of the buyer;

when receiving the request of the identification disclosure of the inquiring list of the buyer, generating a name used by registration for the identification of the buyer.

In the embodiment, when acquiring the price inquiring list of the buyer, the platform not only can verify the information and ensure the accuracy and the integrity of the price inquiring list, but also can generate an anonymous identifier or a public name for the identity according to the requirement of the buyer, thereby meeting the privacy protection and information disclosure requirements of the buyer under different conditions, enhancing the flexibility and the user friendliness of the platform, enabling the buyer to release the price inquiring list more reliablely and improving the attraction and the utilization rate of the platform.

In an embodiment of the present disclosure, after forming an order between a buyer and a final provider based on a supply and demand transaction platform, the method further includes:

After the buyer confirms the order, the supply and demand trading platform automatically triggers an electronic contract generation flow, and generates an electronic contract based on the standard compound same template and the orders of both parties;

providing electronic signature functions for buyers and final suppliers based on a supply-demand transaction platform, and performing real-name authentication and encryption backup on the signing process;

storing the signed electronic contract in a storage library of a platform to generate a unique number and a two-dimensional code for review and downloading;

Automatically detecting legal risks in the contract based on a contract clause auditing module of the supply-demand transaction platform;

based on the supply and demand transaction platform, contract performance is tracked in real time, and both parties are reminded to fulfill obligations at preset nodes.

In this embodiment, after an order is formed, the platform automatically triggers an electronic contract generation flow, generates an electronic contract based on a standardized template and the order, provides functions such as electronic signature, real-name authentication, encryption backup and the like, and contract term auditing and performance tracking reminding services, and the electronic contract management mode of the whole flow not only improves the efficiency and convenience of contract signing, reduces the complexity and errors of manual operation, but also enhances the legal effectiveness and safety of the contract, reduces the contract dispute risk, ensures the smooth execution of the contract by tracking the contract performance in real time, maintains the legal rights and interests of both supply and demand parties, and provides powerful guarantee for the smooth completion of transactions.

Specifically, for example, the electronic contract generation process may refer to a contract generation process that the platform automatically triggers after the buyer confirms the order. For example, standard compound and template, a contract template preset by the platform, covers common purchasing terms and legal requirements. And data filling, namely automatically filling contract contents according to the details agreed by buyers and suppliers in the price inquiry, quotation and negotiation processes. After buyer A confirms the order with provider B, the platform automatically triggers the electronic contract generation flow. The contract template is automatically filled with detailed information such as product specification, quantity, price, delivery date and the like, and a complete electronic contract is generated.

The electronic signature function may refer to a function provided by the platform for signing an electronic contract, and supports various electronic signature modes. For example, digital certificate signing, a digital certificate based signature scheme. The handwritten signature is electronic, namely the handwritten signature is converted into an electronic form. And (3) signature of the short message verification code, namely confirming the signature through the short message verification code. The platform provides electronic signature functionality for buyer a and provider B. Buyer A selects the handwritten signature to be electronic, and provider B selects the short message verification code signature. After the two parties complete the signature, the contract takes effect formally. Real name authentication may refer to the process by which a platform verifies the identity of both parties signing an electronic contract. For example, identity information verification, which verifies the identity information of the signer, ensures the authenticity of the signing action. Legal effectiveness-ensuring that electronic signatures have legal effectiveness. When signing the electronic combination, the platform requires the buyer A and the provider B to provide the ID card number and the mobile phone number for real-name authentication. After verification, the electronic signatures of both parties are legal.

The contract term review module may refer to a functional module of the platform for automatically detecting legal risks in an electronic contract. For example, clause auditing checks that the contract clauses meet legal regulations and industry standards. And (5) prompting the potential legal risks existing in the contracts of the two parties. The contract term auditing module of the platform detects that the contract lacks default responsibility terms and automatically prompts the buyer A and the provider B to supplement relevant content so as to avoid potential legal risks. Contract performance tracking may refer to real-time monitoring of contract performance by a platform. For example, the preset node alerts that both parties are being obligated at the key node for contract performance. Fulfillment records, recording detailed processes of contract fulfillment, including delivery, payment, etc. The platform sets a plurality of preset nodes, such as delivery date, payment date, etc., during contract fulfillment. 3 days before the delivery date, the platform reminds the provider B to deliver on time, and 3 days before the payment date, the platform reminds the buyer A to pay on time. Meanwhile, the platform records the specific conditions of each delivery and payment, and ensures that the contract is smoothly fulfilled.

In some other embodiments of the present disclosure, the acquiring the query list issued by the buyer on the pre-created supply and demand transaction platform further includes:

The platform provides a virtual reality or augmented reality tool, so that a buyer can display and experience the actual application scene of a product in a virtual environment, the buyer can display the product requirement more intuitively through VR/AR technology, the product requirement can be accurately understood by a provider through the installation position, the use environment, the cooperation with other equipment and the like of the product, and the accuracy of quotation is improved.

The intelligent voice interaction price inquiry comprises the steps that a platform supports voice input and voice interaction functions, buyers can issue price inquiry lists through voice instructions, the platform automatically converts voice contents into texts through a voice recognition technology, and intelligent verification and supplement are carried out. Meanwhile, the platform can feed back verification results and suggestions of the price inquiring list to the buyer through a voice synthesis technology, and more convenient interaction experience is provided.

The platform allows buyers to adjust price inquiring contents, such as product specification, quantity, price range and the like, according to market change or own demand after the price inquiring list is issued. The platform pushes the adjusted price list to the matched target suppliers in real time, and records feedback information of the suppliers, so that both sides can respond to the change of the demand in time, and the flexibility and adaptability of the transaction are improved.

The inquiring list is stored based on the blockchain, wherein the platform stores the inquiring list issued by the buyer by utilizing the blockchain technology, so that the non-tampering and traceability of the inquiring list are ensured. The blockchain certification provides legal basis for subsequent transactions, enhances the safety and the trust degree of the transactions, and provides reliable data support for solving potential disputes.

In some other embodiments of the present description, detecting the association between raw material price fluctuations and finished product price fluctuations, and other related products that a buyer will complete with a purchase after purchasing the product, includes:

Association rule mining:

A data set is constructed containing raw material price fluctuations and finished product price fluctuations, each data point including a raw material price, a finished product price, and a corresponding timestamp.

And calculating the correlation between the price fluctuation of the raw materials and the price fluctuation of the finished products by using a statistical method, and determining the causal relationship of the price fluctuation of the raw materials to the price fluctuation of the finished products by using a time sequence analysis method.

An association rule mining algorithm (such as an Apriori algorithm or an FP-Growth algorithm) is used for mining association rules between raw material price fluctuation and finished product price fluctuation, a minimum support degree and a confidence threshold are set, and the association rules with statistical significance are screened out.

For example, by calculating the correlation, the price fluctuation of the raw material A and the price fluctuation of the finished product B have strong positive correlation, and the correlation coefficient is 0.85, which exceeds the preset correlation threshold. Using the gland causal test, it was determined that price fluctuations of raw material a had a significant causal relationship to price fluctuations of finished product B, i.e. an increase in raw material a price would typically result in an increase in finished product B price within one month. The algorithm digs out the association rule that if the price of the raw material A rises by 10%, the probability that the price of the finished product B rises by 8% in the next month is 70%, and the preset probability threshold is exceeded, and then the association exists.

And (5) matched purchase analysis:

And extracting purchasing records from purchasing behavior data of the buyers, wherein the purchasing records comprise information such as the types of the purchased products, purchasing time, purchasing quantity and the like.

And carrying out preprocessing operations such as denoising, deduplication, missing value filling and the like on the purchasing behavior data, and grouping according to buyers.

And analyzing purchasing behavior data of the buyer by using an association rule mining algorithm, mining out other products which are commonly purchased in a matched mode after the buyer purchases a certain product, setting a minimum support degree and a confidence degree threshold, and screening out matched purchasing rules with statistical significance.

For example, the purchasing behavior is analyzed by analyzing the purchasing records of the buyer, and the buyer is found to purchase finished product C or finished product D in a matched manner after purchasing finished product B. The matched purchasing rules are mined, namely if the buyer purchases the finished product B, the probability of purchasing the finished product C in the next month is 60%, the probability of purchasing the finished product D is 40%, and all the probabilities exceed a preset probability threshold, and then the correlation exists.

Results presentation and application:

the association rules between the mined raw material price fluctuation and the finished product price fluctuation and the matched purchasing rules are presented to a user in an intuitive manner, for example, a correlation curve and a matched purchasing association network diagram are displayed through a visual chart.

Decision support is provided for suppliers and buyers according to the association rules and the matched purchasing rules, for example, the suppliers predict the price trend of the finished product according to the price fluctuation of the raw materials, adjust the production plan and the pricing strategy, and the buyers optimize the purchasing plan according to the matched purchasing rules so as to reduce the cost.

In some other embodiments of the present description, predicting the price trend of each type of product within a predetermined period of time in the future by modeling and analyzing historical data, the possible trend of market prices of buyers and suppliers is informed in advance, including:

Data acquisition and pretreatment:

Historical market price data is collected, and the historical market price data comprises information such as prices, time stamps, sales quantity, market supply and demand conditions and the like of various products. And cleaning the acquired data, removing repeated, wrong or missing data records, and carrying out format standardization to ensure the consistency and usability of the data.

Characteristic engineering:

features associated with price changes are extracted, including time features (e.g., season, month, week), market supply and demand features (e.g., stock level, sales growth rate), macro-economic features (e.g., currency expansion rate, interest rate), etc. Statistical features of the historical prices, such as mean, variance, volatility, etc., are calculated as input features of the model.

Model selection and training:

Models suitable for time series prediction are selected, such as ARIMA (autoregressive integral moving average model), LSTM (long term memory network), prophet, etc. The model is trained using historical market price data, and model parameters are adjusted to optimize predictive performance. And the accuracy and generalization capability of the model are evaluated by methods such as cross verification and the like, so that the prediction effect of the model in different time periods is ensured.

Price prediction:

And predicting the prices of various products in a preset time period in the future by using the trained model, and generating a price prediction curve. And the prediction result is adjusted by combining with market dynamic factors (such as raw material price fluctuation, policy change and the like), so that the prediction accuracy is improved.

Results presentation and notification:

And displaying the prediction result to buyers and suppliers in the form of visual charts (such as line charts and bar charts), and intuitively presenting the change trend of the future price. The possible trend of the market price of buyers and suppliers is informed in advance, and the possible trend comprises information such as the rising or falling amplitude of the price, the duration of the trend and the like, so that the buyers and the suppliers can be assisted in making purchasing or selling strategies in advance.

Dynamic update and feedback:

the model is updated periodically, and the model is retrained in combination with the latest market price data to adapt to market changes. And feedback of buyers and suppliers to the prediction results is collected, a model and a prediction flow are further optimized, and the practicability and accuracy of prediction are improved.

By way of example, suppose that the platform collects price data for an electronic product over the past year, including information on average monthly price, sales quantity, inventory level, etc. Price prediction is achieved by the following steps.

Data acquisition and pretreatment:

The collected data comprise 500 price units for 1 month in 2024, 1000 sales, 2000 stock levels, 520 price units for 2 months, 1200 sales, 1800 stock levels, etc. Cleaning data, removing abnormal values (such as data points with abnormally large price fluctuation), and unifying data formats.

Characteristic engineering:

extracting time characteristics, namely month and season. And extracting market supply and demand characteristics, namely the sales growth rate and the stock level change rate of each month. And calculating statistical characteristics such as price fluctuation rate.

Model selection and training:

and selecting an ARIMA model for time sequence prediction. The model is trained using data from the past 12 months, and predictive performance is optimized by adjusting model parameters (e.g., autoregressive terms, differential terms, running average terms). And the accuracy of the model is evaluated through cross verification, so that the prediction errors of the model in different time periods are ensured to be in a reasonable range.

Price prediction:

and predicting price change trend of 3 months in the future by using the trained ARIMA model to generate a prediction curve. And the prediction result is adjusted by combining the price fluctuation of the raw materials (such as 5 percent of the price rise of the raw materials), and the prices of 3 months in the future are predicted to rise by 3 percent, 4 percent and 5 percent respectively.

Results presentation and notification:

And displaying a price prediction curve of 3 months in the future in the form of a line graph, and clearly showing the rising trend of the price. The buyers and the suppliers are informed in advance, the buyers are recommended to increase the purchase quantity before the price rises, and the suppliers are recommended to adjust the production plan and the pricing strategy according to the price trend.

Dynamic update and feedback:

And updating the model every month, and retraining the model by combining the latest market price data to ensure the timeliness and accuracy of the prediction result. Feedback from buyers and suppliers, such as assessment of accuracy and practicality of the predictions, is collected, further optimizing the model and prediction process.

Based on the same general inventive concept, the present invention also protects a price inquiring device based on supply and demand transactions, as shown in fig. 2, fig. 2 is a schematic structural diagram of the price inquiring device based on supply and demand transactions according to the embodiment of the present invention. The price inquiring device based on the supply and demand transaction provided by the invention is described below, and the price inquiring device based on the supply and demand transaction described below and the price inquiring method based on the supply and demand transaction described above can be correspondingly referred to each other.

The price inquiring device based on the supply and demand transaction comprises a price inquiring 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.

The price inquiring list module 201 obtains a price inquiring list issued by a buyer on a pre-created supply and demand transaction platform, wherein the price inquiring list comprises product specifications, quantity, price range, delivery date and quality standard;

the matching module 202 matches the price inquiry list according to the evaluation indexes of the suppliers registered by the supply and demand transaction platform to obtain a target supplier, and sends the price inquiry list to the target supplier, wherein the evaluation indexes comprise historical performance, product quality, price competitiveness and delivery capacity;

The bill of price quotation module 203 obtains the bill of price quotation submitted by the target supplier on the supply-demand transaction platform and pushes the bill of price quotation to the buyer of the supply-demand transaction platform, wherein the bill of price quotation comprises price, quantity and expected delivery date;

The order module 204 obtains the final supplier selected by the buyer from the target suppliers and forms an order between the buyer and the final supplier based on the supply-demand transaction platform;

The tracking module 205 tracks the status of progress of the order and feeds the status of progress back to the buyer and the final supplier;

the evaluation module 206 provides an evaluation list to the buyer when the completion information of the order is acquired;

the feedback module 207 obtains the evaluation result of the evaluation list and feeds back to the final provider.

Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. As shown in FIG. 3, the electronic device may include a processor (processor) 310, a communication interface (Communications Interface) 320, a memory (memory) 330, and a communication bus 340, where the processor 310, the communication interface 320, and the memory 330 communicate with each other via the communication bus 340. The processor 310 may invoke logic instructions in the memory 330 to perform a price-polling method based on the supply-demand transaction.

Further, the logic instructions in the memory 330 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. The storage medium includes a U disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, an optical disk, or other various media capable of storing program codes.

In another aspect, the present invention also provides a computer program product comprising a computer program, the computer program being storable on a non-transitory computer readable storage medium, the computer program, when executed by a processor, being capable of executing the price-polling method based on supply-demand transactions provided by the methods described above.

In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the method of providing a supply and demand transaction based pricing method as provided above.

The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.

It should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention, and not for limiting the same, and although the present invention has been described in detail with reference to the above-mentioned embodiments, it should be understood by those skilled in the art that the technical solution described in the above-mentioned embodiments may be modified or some technical features may be equivalently replaced, and these modifications or substitutions do not make the essence of the corresponding technical solution deviate from the spirit and scope of the technical solution of the embodiments of the present invention.

Claims (10)

1. A method of price polling based on supply and demand transactions, comprising:

Acquiring a price inquiry list issued by a buyer on a pre-established supply and demand transaction platform, wherein the price inquiry list comprises product specifications, quantity, price range, delivery date and quality standard;

Matching the price inquiry list according to the evaluation indexes of the suppliers registered by the supply and demand transaction platform to obtain a target supplier, and sending the price inquiry list to the target supplier, wherein the evaluation indexes comprise historical performance, product quality, price competitiveness and delivery capacity;

Acquiring a quotation submitted by the target provider at the supply-demand trading platform, and pushing the quotation to a buyer of the supply-demand trading platform, wherein the quotation comprises price, quantity and expected delivery date;

Acquiring a final provider selected by a buyer from the target providers, and forming an order between the buyer and the final provider based on the supply-demand transaction platform;

tracking the progress status of the order and feeding back the progress status to the buyer and the final supplier;

providing an evaluation list to a buyer when the completion information of the order is acquired;

and obtaining an evaluation result of the evaluation list and feeding back the evaluation result to the final supplier.

2. The price inquiring method based on supply and demand transaction according to claim 1, wherein the matching the price inquiring list according to the evaluation index of the registered suppliers of the supply and demand transaction platform to obtain a target supplier, and transmitting the price inquiring list to the target supplier comprises:

based on the data acquisition and preprocessing subsystem of the supply and demand transaction platform, collecting various data of suppliers, and performing data cleaning and standardization processing on the various data to obtain target data;

Converting the target data into feature vectors based on a feature extraction and model training subsystem of the supply and demand transaction platform, and carrying out model training based on the feature vectors to obtain an evaluation model of a supplier;

Based on the real-time matching and recommending subsystem of the supply and demand trading platform, the price inquiring list is converted into a demand vector, the demand vector is matched with the evaluating model by using a similarity matching algorithm, a provider group matched with the demand vector is obtained, the providers in the provider group are ordered according to the order of comprehensive scores from high to low, the top-ranked N provider is selected as a target provider, the price inquiring list is sent to the target provider, and N is an integer greater than 1.

3. The method of claim 1, wherein the obtaining a bid list submitted by the target provider at the supply-demand transaction platform and pushing the bid list to a buyer of the supply-demand transaction platform comprises:

The method comprises the steps of acquiring a quotation link of a supply and demand trading platform clicked by a target provider, and displaying a quotation submitting page, wherein the quotation submitting page comprises a quotation template provided by the supply and demand trading platform for the target provider, and the quotation template is pre-filled with partial information and provides a reference cost price interval, an average market price within a preset period and a suggested profit space range;

Acquiring a quotation list submitted by the target provider, wherein the quotation list comprises prices filled by the target provider according to the quotation template and predicted delivery dates;

And verifying the quotation submitted by the target provider based on the supply and demand transaction platform, and pushing the verified quotation to a buyer of the supply and demand transaction platform.

4. The method of claim 1, wherein the acquiring a final provider selected by a buyer from the target providers and forming an order between the buyer and the final provider based on the supply-demand transaction platform comprises:

displaying an evaluation and selection page to a buyer based on the supply and demand transaction platform, wherein the evaluation and selection page comprises a quotation summary list and provider information;

The weight of each evaluation standard set by the buyer through the supply-demand transaction platform is obtained, wherein the evaluation standard comprises product quality, price, delivery date, after-sales service and supplier credit;

Based on the supply and demand transaction platform, determining the comprehensive score of each target provider according to the weight set by the buyer and the actual performance of the provider, and generating an evaluation report and a comparison chart;

And acquiring a final provider selected by the buyer according to the evaluation report and the comparison chart, and forming an order.

5. The supply and demand transaction based price-polling method of claim 1, wherein said tracking the progress status of said order and feeding back said progress status to the buyer and said final supplier comprises:

Acquiring the production progress information and the logistics transportation state information of the final supplier based on a pre-established data interaction mechanism of the supply-demand transaction platform, a production management system and a logistics distribution system of the supplier;

Based on the supply and demand trading platform, the production progress information and the logistics transportation state information are updated to a state page of an order in real time, and are presented to buyers and final suppliers in a visual mode;

When the production progress information and the logistics transportation state information are monitored to be abnormal, starting an early warning mechanism based on the supply and demand transaction platform, sending an abnormal notification to buyers and final suppliers, and providing a solution.

6. The supply and demand transaction-based price-polling method of claim 1, further comprising:

Based on the supply and demand transaction platform, cleaning, preprocessing and analyzing purchasing behavior data of buyers, sales data of suppliers and market price data, and generating a market trend analysis report and a purchasing strategy optimization suggestion;

providing the market trend analysis report and purchase strategy optimization advice to buyers and suppliers based on the supply-demand trading platform.

7. The supply-demand transaction-based price-polling method of claim 6, wherein said generating a market trend analysis report and a purchase strategy optimization suggestion based on said supply-demand transaction platform cleans, pre-processes, and analyzes buyer's purchasing behavior data, vendor's sales data, and market price data, comprises:

collecting purchasing behavior data of a buyer, sales data of a provider and market price data based on a data collecting module of the supply and demand transaction platform, wherein the purchasing behavior data comprises purchasing time, product types, quantity, amount, purchasing frequency, purchasing source place and using place distribution, and the sales data comprises sales quantity, sales amount, sales price trend, sales area distribution, customer types and distribution;

based on the data cleaning module of the supply and demand transaction platform, denoising, deduplicating, filling missing values, correcting error values and format standardization are carried out on purchasing behavior data, sales data of suppliers and market price data;

Classifying buyers and suppliers according to purchasing behavior data, sales data of the suppliers and market price data by using a clustering analysis algorithm based on the data analysis module of the supply and demand transaction platform, wherein the data analysis module comprises the steps of classifying the buyers into high-frequency high values, high-frequency low values, low-frequency high values and low-frequency low values according to purchasing frequencies and purchasing amounts, and analyzing purchasing preference, demand trend and price sensitivity of different types of buyer groups;

based on the data analysis module of the supply-demand transaction platform, an association rule mining algorithm is applied to detect the association relation in the data set, wherein the association relation between raw material price fluctuation and finished product price fluctuation is detected, and other related products which can be purchased in a matched manner after a buyer purchases the products are detected;

Based on the data analysis module of the supply and demand trading platform, the time sequence analysis model is used for predicting market price trend, demand change trend and seasonal fluctuation law, and the method comprises the steps of predicting the price change trend of various products in a preset time period in the future through modeling and analysis of historical data, and informing buyers and suppliers of possible trend of market price in advance.

8. The supply and demand transaction-based price-polling method of claim 1, further comprising:

After the buyer issues the price inquiring list, other products or services related to the current price inquiring list are automatically recommended based on the supply and demand transaction platform by analyzing the historical purchasing behavior and preference of the buyer;

based on the supply and demand transaction platform, the production capacity and the inventory level of the suppliers are analyzed, and suggestions for optimizing the purchasing plan are provided for buyers.

9. The method for inquiring price based on supply and demand transaction according to claim 1, wherein the acquiring the inquiring price list issued by the buyer on the pre-created supply and demand transaction platform comprises:

Acquiring a login instruction of a buyer on the supply and demand transaction platform, and displaying a page of a price inquiring list;

When receiving a completion instruction of a price inquiring list of a buyer, checking information in the price inquiring list based on a checking system of the supply and demand trading platform;

when receiving the identity confidentiality requirement of the price inquiring list of the buyer, generating a unique anonymous identifier for the identity of the buyer;

when receiving the request of the identification disclosure of the inquiring list of the buyer, generating a name used by registration for the identification of the buyer.

10. The supply-demand transaction-based price inquiring method according to claim 1, further comprising, after forming an order between a buyer and the final provider based on the supply-demand transaction platform:

after the buyer confirms the order, the supply and demand transaction platform automatically triggers an electronic contract generation flow, and generates an electronic contract based on the standard compound same template and the orders of the two parties;

Providing electronic signature functions for buyers and the final suppliers based on the supply and demand transaction platform, and performing real-name authentication and encryption backup on the signing process;

storing the signed electronic contract in a storage library of a platform to generate a unique number and a two-dimensional code for review and downloading;

Automatically detecting legal risks in the contract based on a contract clause auditing module of the supply-demand transaction platform;

based on the supply and demand transaction platform, contract performance is tracked in real time, and both parties are reminded to fulfill obligations at preset nodes.