Digital supply chain transaction platform management system

Abstract

The invention discloses a digital supply chain transaction platform management system, and relates to the technical field of building material supply, and the system comprises a quotation collection module which is used for collecting the sales information of a supplier; the risk management module is used for managing building materials, the demand prediction module is used for predicting building material demands of a demand side and intelligently matching the demand side with a supplier, and the coordination module is used for coordinating material supply of the supplier and the demand side of the building materials on site according to data of the demand prediction module and the risk management module; by dynamically adjusting safe inventory and supply strategies, supply and demand can be better balanced, the risk of inventory overstock or insufficient supply is reduced, the flexibility of a supply chain is enhanced, market changes and external environment factors can be quickly responded, the problem of unbalanced supply and demand can be solved in a long project period, and the service life of the system is prolonged. And instability caused by an external environment is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of building material supply, and more specifically, to a digital supply chain transaction platform management system. Background Art

[0002] The digital supply chain trading platform is a market-oriented platform that can integrate the information resources of service providers, collect quotations from suppliers of building materials, and provide multi-dimensional digital supply chain services including electronic bidding, online transactions, logistics supervision, fund settlement, financing services, inventory management, etc., realizing the digitization of the entire supply chain;

[0003] In actual use, the above trading platform requires a management system to ensure its efficient, stable and secure operation. The main tasks of the management system include: understanding market and user needs, providing direction for platform functions and services; integrating and optimizing supplier resources, collecting and comparing quotations, ensuring the quality and price competitiveness of material supply; realizing the electronic bidding process, improving transparency and efficiency; providing a stable and secure online trading platform, processing orders and contracts; tracking logistics information to ensure timely delivery of materials; processing payments and collections to ensure smooth capital flow; providing financing solutions to help solve capital problems; monitoring inventory levels and optimizing inventory management; analyzing business data and providing decision support, etc.

[0004] However, in actual use, due to the long project cycle in the construction industry, demand is difficult to accurately predict, and market competition is fierce. Supply chain management often faces the problem of imbalance between supply and demand. External environmental factors such as policy changes and weather can also bring uncertainty to supply chain management. Summary of the invention

[0005] In order to solve the above problems, the present invention provides a digital supply chain transaction platform management system.

[0006] The present invention provides a digital supply chain transaction platform management system, including a quotation collection module, wherein the quotation collection module is used to collect sales information of suppliers;

[0007] Demand forecasting module, which is used to forecast the demand for building materials from the demand side and to intelligently match it with the supply side:

[0008] A risk management module, the risk management module includes an environmental information collection unit and an evaluation unit, the environmental information collection unit is used to collect historical data, environmental data and market data of the supplier, and the evaluation unit is used to evaluate the potential impact value on the supplier's supply chain based on the data of the information collection unit, so as to adjust the supplier;

[0009] A coordination module is used to coordinate the material supply of the building material supplier and the demander on site according to the data of the demand forecasting module and the risk management module.

[0010] Preferably, the specific working mode of the demand forecasting module is as follows, specifically:

[0011] The demand forecasting module includes a forecasting unit and a matching unit. The forecasting unit is used to forecast the material demand of the demander based on historical data, specifically:

[0012] Obtain the demander's historical purchasing data, including material type, purchase quantity and purchase date;

[0013] Obtain the project information, expected construction period E and project budget R from the demand side;

[0014] Obtain the predicted demand Q of the demand side;

[0015] Get the historical average delay days T of the supplier;

[0016] Determine which months the expected construction period E falls within, and obtain the corresponding monthly proportion coefficient;

[0017] Divide the demand side's forecast demand Q by E to obtain the forecast demand value for each day, and add up the forecast demand values ​​for each day in a month to obtain the average forecast demand value for each month;

[0018] Multiply the average forecast demand value of each month by the monthly ratio coefficient of the corresponding month to obtain the forecast demand of each month, and add the forecast demand of the first month to the monthly ratio coefficient. Obtain forecast demand for each month within the project cycle;

[0019] Transmitting the forecast demand and project budget R for each month in the project cycle to the matching unit;

[0020] The matching unit is used to evaluate the supplier according to the data of the quotation collection module, and select the supplier that matches the demander according to the forecast data of the demand forecast module and the quotation of the supplier.

[0021] Preferably, the specific method of obtaining the monthly proportional coefficient is as follows:

[0022] Obtain the material demand of the supply chain trading platform every month for more than three years;

[0023] Calculate the average material demand for each month;

[0024] The average demand value for each month is divided by the average material demand value for each month of the supply chain trading platform over three years to obtain the monthly proportion coefficient for that month.

[0025] Preferably, the specific working mode of the matching unit is as follows:

[0026] Obtaining the material quotation and material supply quantity of the supplier in the quotation collection module;

[0027] The final forecast demand is obtained by adding up the forecast demand of each month in the project cycle of the demand side's materials. The final forecast demand is multiplied by the corresponding material quotations of all suppliers to obtain the forecast cost of each supplier. The forecast cost of each supplier is compared with the project budget R, and the supplier whose forecast cost is greater than the project budget R is eliminated.

[0028] Compare the material supply of the remaining suppliers with the final forecast demand P of the demander, and give priority to the supplier whose material supply is greater than the forecast demand of each month in the project cycle of the demander and whose material quotation is the lowest, and mark it as the matching supplier;

[0029] If there is no situation where the material supply is greater than the forecast demand for each month during the project cycle of the demander, the material supplies of multiple suppliers are combined until the material supply is greater than the forecast demand for each month during the project cycle, and the combined suppliers are marked as matching suppliers.

[0030] Preferably, the specific working mode of the environmental information collection unit is as follows:

[0031] First, determine the monitoring indicators, which are market price, supply, environmental weather and market demand;

[0032] Regularly collect data on the external environment based on the determined monitoring indicators;

[0033] Standardize the collected data information.

[0034] Preferably, the specific working mode of the evaluation unit is as follows:

[0035] According to the formula The comprehensive risk assessment value H of the supplier supply chain is obtained by calculation, where n is the number of monitoring indicators, X i represents the standardized value of the i-th monitoring indicator, β i is the weight coefficient of the i-th monitoring indicator;

[0036] The comprehensive risk assessment value H is transmitted to the coordination module.

[0037] Preferably, the standardized value X of the i-th monitoring indicator iThe specific way to obtain is as follows:

[0038] Since the monitoring indicators are market price, supply, environmental weather and market demand, correspondingly, X i The supplier’s price risk X1, the supplier’s shortage risk X2, the supplier’s delay risk X3 and the market demand risk X4;

[0039] The price risk X1 of the supply side is obtained by dividing the change in the demand for building materials in a fixed period of time by the change in the price of building materials in a fixed period of time;

[0040] The supply-side stockout risk X2 is obtained by dividing the actual supply of building materials by the planned supply in a fixed time period;

[0041] The supplier's delay risk X3 is obtained by dividing the supply of building materials under specific weather conditions in a fixed period of time by the supply under normal weather conditions;

[0042] Market demand risk X4 is obtained by dividing the actual supply of building materials by the demand in a fixed time period.

[0043] Preferably, the working method of the optimization module also includes:

[0044] Obtain the expected profit value δ of the demand side;

[0045] The risk adjustment factor φ1 is obtained based on the comprehensive risk assessment value H;

[0046] Obtain the expected loss φ2;

[0047] The risk capital φ3 is obtained based on the predicted loss φ2;

[0048] The risk value K is obtained by subtracting the risk capital φ3 from the expected return value δ;

[0049] Obtain the conditional risk value L;

[0050] According to the formula δ1=δ-(φ1*δ)-L, the risk-adjusted predicted profit value δ1 is obtained.

[0051] The risk-adjusted predicted profit value δ1 is transmitted to the coordination module.

[0052] Preferably, the specific method of obtaining the conditional risk value L is as follows:

[0053] According to the formula The conditional risk value L is calculated, where σ is the probability that the loss does not exceed the risk value K, γ represents the random variable of the loss, and f(γ) is its probability density function.

[0054] Preferably, the specific working mode of the coordination module is as follows:

[0055] Set the corresponding thresholds of the risk assessment value H and the risk-adjusted predicted profit value δ1 in advance;

[0056] If the risk assessment value H is greater than the corresponding threshold, the safety stock is increased to cope with potential supply disruptions;

[0057] If the risk assessment value H is less than the corresponding threshold, the safety stock is reduced to reduce costs;

[0058] If the risk-adjusted predicted profit value δ1 is greater than the corresponding threshold, it means that the expected profit of the demander is met. Otherwise, a signal is generated and transmitted to the demand forecasting module for re-forecasting and matching new developers until the risk-adjusted predicted profit value δ1 is less than or equal to the corresponding threshold.

[0059] Beneficial effects: By comparing the risk-adjusted predicted profit value with the threshold, it can ensure that the expected profit of the demand side is met. If the predicted profit does not meet expectations, the strategy can be adjusted to meet the profit requirements by re-forecasting and matching new developers, which can solve the problem of insufficient prediction and matching accuracy of existing supply chain trading platforms;

[0060] By dynamically adjusting safety stocks and supply strategies, supply and demand can be better balanced and the risk of inventory backlogs or insufficient supply can be reduced. The flexibility of the supply chain is enhanced, and it can respond quickly to market changes and external environmental factors. During long project cycles, the problem of supply and demand imbalance can be resolved and the instability caused by the external environment can be reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a flow chart of the management system of the present invention. DETAILED DESCRIPTION

[0062] Application scenarios: In actual use, due to the long project cycle in the construction industry, demand is difficult to accurately predict, and market competition is fierce. Supply chain management often faces the problem of imbalance between supply and demand. External environmental factors such as policy changes and weather can also bring uncertainty to supply chain management.

[0063] like Figure 1 As shown: A digital supply chain transaction platform management system, including a quotation collection module, a demand forecasting module, a risk management module and a coordination module;

[0064] Through the setting of the above modules, by comparing the risk-adjusted predicted profit value and the threshold, it can be ensured that the expected profit of the demand side is met. If the predicted profit does not meet the expectation, the strategy can be adjusted to meet the profit requirements by re-forecasting and matching new developers, which can solve the problem of insufficient prediction and matching accuracy of existing supply chain trading platforms;

[0065] By dynamically adjusting safety inventory and supply strategies, supply and demand can be better balanced, and the risk of inventory backlog or insufficient supply can be reduced. The flexibility of the supply chain is enhanced, and it can respond quickly to market changes and external environmental factors. In a long project cycle, the problem of supply and demand imbalance can be solved and the instability caused by the external environment can be reduced;

[0066] The quotation collection module is used to collect the sales information of the supplier; it should be noted that, in this embodiment, the sales information includes historical sales data, price change data, seasonal factors, market trends and supplier delivery time, etc.;

[0067] The demand forecasting module is used to forecast the demand for building materials on the demand side and to intelligently match it with the supply side: it should be noted that the problem of imbalance between supply and demand is reduced and the accuracy and timeliness of material supply is improved;

[0068] The risk management module includes an environmental information collection unit and an evaluation unit. The environmental information collection unit is used to collect historical data, environmental data and market data of the supplier. The evaluation unit is used to evaluate the potential impact value on the supplier's supply chain based on the data of the information collection unit, so as to adjust the supplier. It should be noted that in this embodiment, the external environmental factors may be policy changes and weather, etc. By predicting the resilience of the supply chain in advance, the impact of uncertainty on the supply chain can be reduced, ensuring the stable progress of the demand side's project.

[0069] The coordination module is used to coordinate the material supply of the building material supplier and the demander on site according to the data of the demand forecasting module and the risk management module; it should be noted that the on-site operation process is optimized to ensure the timely delivery of materials and improve the coordination efficiency of the construction site;

[0070] It should also be noted that by integrating and optimizing each link of the supply chain, the efficiency and stability of the entire construction industry supply chain can be improved. Through intelligent and automated technologies, human errors can be reduced, the quality of decision-making can be improved, and the competitiveness of the entire supply chain can be enhanced.

[0071] As an optional embodiment: the specific working mode of the demand forecasting module is as follows:

[0072] The demand forecasting module includes a forecasting unit and a matching unit. The forecasting unit is used to forecast the material demand of the demander based on historical data, specifically:

[0073] Obtain the historical purchase data of the demander, including material type, purchase quantity and purchase date; it should be noted that in this embodiment, since it is a trading platform for building materials, the material type is generally concrete or sand;

[0074] The project information, expected construction period E and project budget R of the demander are obtained; it should be noted that in this embodiment, the unit of expected period E is day, and the unit of project budget R is yuan;

[0075] The predicted demand Q of the demander is obtained; it should be noted that the predicted demand Q of the demander is obtained through the demander's accounting, which is the building materials required for the entire project of the demander;

[0076] It should also be noted that by calculating the historical average demand, we can get the stable demand level for materials in the past, which provides a benchmark for forecasting. This value smoothes short-term fluctuations and outliers and reflects the average consumption rate without any seasonality or special events.

[0077] The historical average delay days T of the supplier is obtained; it should be noted that the average delay days T is obtained through the supplier information in the quotation collection module, which is obtained by dividing the delay days of material supply by the number of supplies; by considering the historical average delay days, the buffer stock that needs to be prepared additionally, that is, the safety stock, can be calculated. The safety stock is also included in the demand forecast to reduce the risk of supply interruption. The supply chain may be affected by unforeseen events, such as transportation delays, production interruptions, etc. The safety stock provides a certain degree of protection to ensure the continuous supply of materials during the construction process;

[0078] It should be noted that the final demand that combines these factors provides a more accurate and practical forecast, which can help the demand side better plan material procurement, manage inventory and optimize cash flow. It is suitable for those situations that are sensitive to market changes, have large projects or have long construction periods. Through this method, the demand side can reduce the costs and risks caused by inaccurate demand forecasts;

[0079] Determine which months the expected construction period E falls within, and obtain the corresponding monthly proportion coefficient;

[0080] Divide the demand side's forecast demand Q by E to obtain the forecast demand value for each day, and add up the forecast demand values ​​for each day in a month to obtain the average forecast demand value for each month;

[0081] Multiply the average forecast demand value of each month by the monthly ratio coefficient of the corresponding month to obtain the forecast demand of each month, and add the forecast demand of the first month to the monthly ratio coefficient. Obtain the forecast demand for each month within the project cycle; it should also be noted that due to the long construction period of the project and the large demand for materials, the materials are purchased in batches. is the daily forecast demand value, Multiply by T to get the safety stock;

[0082] Because the construction progress is different in each quarter, the material demand for each month will also be affected. This calculation can get the material demand for each month, purchase materials according to the month, and add the forecast demand of safety stock to the forecast demand of the first month;

[0083] It should also be noted that the month can also be replaced by a quarter or other period, which can be adjusted by the installation demander;

[0084] This forecast demand also takes into account the need to set up safety stock in advance to avoid supplier delays that may cause subsequent material shortages;

[0085] The forecast demand and project budget R for each month in the project cycle are transmitted to the matching unit; it should be noted that, in this embodiment, the final forecast demand P is the forecast demand for a single material, and the forecast demand for each material can be obtained in the same way;

[0086] The matching unit is used to evaluate the supplier according to the data of the quotation collection module, and select the supplier that matches the demander according to the forecast data of the demand forecast module and the quotation of the supplier.

[0087] As an optional embodiment: the specific method of obtaining the monthly proportional coefficient is as follows:

[0088] Obtain the material demand of the supply chain trading platform every month for more than three years;

[0089] Calculate the average material demand for each month;

[0090] The monthly proportion coefficient of the month is obtained by dividing the average demand of each month by the average material demand of the supply chain trading platform for more than three years. It should be noted that in this embodiment, the monthly proportion coefficient φ ranges from 0 to 2, and the monthly proportion coefficient φ calculated in this way can reflect the impact of each month on material demand.

[0091] As an optional embodiment: the specific working mode of the matching unit is as follows:

[0092] Obtaining the material quotation and material supply quantity of the supplier in the quotation collection module; it should be noted that, in this embodiment, the material quotation is the market unit price;

[0093] The final forecast demand is obtained by adding up the forecast demand of each month in the project cycle of the demand side's materials, and the final forecast demand is multiplied by the corresponding material quotations of all suppliers to obtain the forecast cost of each supplier. The forecast cost of each supplier is compared with the project budget R, and the supplier whose forecast cost is greater than the project budget R is eliminated. It should be noted that the supplier whose quotation is higher than the budget is eliminated;

[0094] Compare the material supply of the remaining suppliers with the final forecast demand P of the demander, and give priority to the supplier whose material supply is greater than the forecast demand of each month in the project cycle of the demander and whose material quotation is the lowest, and mark it as the matching supplier;

[0095] If there is no situation where the material supply is greater than the forecast demand of each month in the project cycle of the demander, the material supply of multiple suppliers will be combined until the material supply is greater than the forecast demand of each month in the project cycle, and the combined suppliers will be marked as matching suppliers. It should be noted that in the process of combining the material supply of multiple suppliers, the supplier with the lowest material quotation will be selected first;

[0096] Sort by month and match the demand side with the appropriate supplier according to the above steps at the beginning of each month;

[0097] It should also be noted that, because the final predicted demand P for each material can be calculated in the above manner, the matching supplier for each material can be obtained according to the above scheme.

[0098] As an optional embodiment: the specific working mode of the environmental information collection unit is as follows:

[0099] First, the monitoring indicators are determined, and the monitoring indicators are market price, supply, environmental weather and market demand. It should be noted that in this embodiment, the monitoring indicators can be determined according to the characteristics of the building materials, such as price, supply, supplier credit, policy changes, weather, market demand, exchange rate, etc.;

[0100] The data of the external environment is collected regularly according to the determined monitoring indicators; it should be noted that, in this embodiment, the collection method can use web crawler technology to crawl data from a specified website. For data that cannot be obtained automatically, it is collected regularly by manual means. For ambient temperature or humidity, sensors can be deployed in warehouses or construction sites to obtain data;

[0101] It should also be noted that market prices are updated in real time, or the collection frequency is adjusted according to market fluctuations. Data collection is carried out according to the supplier's reporting cycle, such as weekly or monthly reports. Weather data is updated in real time, especially in seasons with frequent extreme weather. Market demand data can be updated according to the release cycle of industry reports, such as monthly or quarterly;

[0102] It can ensure that the monitoring system of building material supply can collect key data in a timely and accurate manner, thereby providing data support for subsequent evaluation units;

[0103] The collected data information is standardized. It should be noted that the dimensional influence between different indicators is eliminated to facilitate comparison and calculation.

[0104] As an optional embodiment: the specific working mode of the evaluation unit is as follows:

[0105] According to the formula The comprehensive risk assessment value H of the supplier supply chain is obtained by calculation, where n is the number of monitoring indicators, X i represents the standardized value of the i-th monitoring indicator, β i is the weight coefficient of the ith monitoring indicator; it should be noted that, in this embodiment, the monitoring indicators are market price, supply, ambient weather and market demand, and the number n is 4;

[0106] β i is the weight coefficient of the i-th monitoring indicator, which can also be described as the sensitivity of a monitoring indicator to changes in the total cost of the supply chain. If β i A high value means that a small change in this factor may lead to a significant change in the total supply chain cost. The specific method of obtaining it can be Where θ represents the partial derivative, β i Defined as the total supply chain cost for a specific factor B i The partial derivative of i is the i-th monitoring indicator;

[0107] The comprehensive risk assessment value H is transmitted to the coordination module. It should be noted that it can help quantify the potential impact of external environmental factors on the supply chain and provide decision support for subsequent risk management.

[0108] As an optional embodiment: the standardized value X of the i-th monitoring indicator i The specific way to obtain is as follows:

[0109] Since the monitoring indicators are market price, supply, environmental weather and market demand, correspondingly, X i The supplier’s price risk X1, the supplier’s shortage risk X2, the supplier’s delay risk X3 and the market demand risk X4;

[0110] The price risk X1 of the supply side is obtained by dividing the change in the demand for building materials in a fixed period of time by the change in the price of building materials in a fixed period of time;

[0111] The supply-side stockout risk X2 is obtained by dividing the actual supply of building materials by the planned supply in a fixed time period;

[0112] The supplier's delay risk X3 is obtained by dividing the supply of building materials under specific weather conditions in a fixed time period by the supply under normal weather conditions; it should be noted that in this embodiment, specific weather refers to weather with a yellow warning or above in the weather forecast, and the rest is normal weather. The fixed time period can be one week, one month or one quarter;

[0113] The market demand risk X4 is obtained by dividing the actual supply of building materials by the demand in a fixed time period. It should be noted that the above monitoring indicators are the data of the supplier after matching by the demand forecast module;

[0114] It should also be noted that the above risks are the main factors that need to be considered when managing project risks on the demand side. Assessing the above risks can help the demand side evaluate the supplier, which is conducive to subsequent response and reducing the risks on the demand side.

[0115] As an optional embodiment: the working method of the optimization module also includes:

[0116] The expected profit value δ of the demander is obtained; it should be noted that, in this embodiment, the expected profit value δ represents the expected profit of the demander without any risk;

[0117] The risk adjustment factor φ1 is obtained based on the comprehensive risk assessment value H. It should be noted that this factor can be based on historical data, industry standards or expert evaluation to quantify the potential impact of risk on profits;

[0118] The expected loss φ2 is obtained; it should be noted that, in this embodiment, the expected return value δ is multiplied by the risk adjustment factor φ1 to obtain the expected loss;

[0119] The risk capital φ3 is obtained based on the predicted loss φ2;

[0120] The risk value K is obtained by subtracting the risk capital φ3 from the expected return value δ. It should be noted that, in this embodiment, the risk value K is the maximum loss that may be incurred under a given confidence level.

[0121] The conditional risk value L is obtained; it should be noted that the conditional risk value L is the average loss beyond the expected loss φ2, which provides additional information about the potential loss when it exceeds the expected loss φ2 estimate;

[0122] According to the formula δ1=δ-(φ1*δ)-L, the risk-adjusted predicted profit value δ1 is obtained. It should be noted that the risk-adjusted predicted profit takes into account the potential risk factors (such as market price fluctuations, supply disruptions, etc.) that may cause losses to the supply chain. The difference between the two is the risk value, which represents the maximum amount of loss that may occur in the worst case scenario.

[0123] The risk-adjusted predicted profit value δ1 is transmitted to the coordination module. It should be noted that the risk faced by the supply chain can be quantified and the predicted profit can be adjusted accordingly to reflect potential losses and help with subsequent coordination of supply.

[0124] As an optional embodiment: the specific method of obtaining the conditional risk value L is as follows:

[0125] According to the formula The conditional risk value L is obtained by calculation, where σ is the probability that the loss does not exceed the risk value K, γ represents the random variable of the loss, and f(γ) is its probability density function. It should be noted that this formula calculates the average value of the part of the loss value that exceeds the conditional risk value L when the loss exceeds the risk value K, where σ is usually determined by the normal distribution or other appropriate loss distribution model, and the integral What is calculated is the area under the cumulative probability density function of the loss exceeding the risk value K;

[0126] Provides a more comprehensive loss measure than VaR K because it considers not only the probability that a loss will exceed VaR K, but also the average size of the loss once this threshold is exceeded.

[0127] As an optional embodiment: the specific working mode of the coordination module is as follows:

[0128] The corresponding thresholds of the risk assessment value H and the risk-adjusted predicted profit value δ1 are set in advance; it should be noted that, in this embodiment, the thresholds are set by the demand side according to the budget and profit;

[0129] If the risk assessment value H is greater than the corresponding threshold, the safety stock is increased to cope with potential supply disruptions. It should be noted that this indicates that the matching supplier and supply chain face greater risks. Alternative suppliers can also be sought to reduce dependence on a single supplier, and more flexible supply contracts can be negotiated with suppliers to cope with market price fluctuations. Consider increasing insurance coverage for the supply chain.

[0130] If the risk assessment value H is less than the corresponding threshold, the safety stock is reduced to reduce costs; it should be noted that the supply chain is relatively stable and the risk is relatively small. The supply chain process can also be optimized to improve efficiency and consider long-term cooperation to obtain more favorable prices and conditions;

[0131] If the risk-adjusted predicted profit value δ1 is greater than the corresponding threshold, it means that the expected profit of the demander is met. Otherwise, a signal is generated and transmitted to the demand forecasting module for re-forecasting, matching new developers, until the risk-adjusted predicted profit value δ1 is less than or equal to the corresponding threshold. It should be noted that when the risk is high, the risk of supply disruption can be reduced by increasing safety inventory and finding alternative suppliers. When the risk is low, the holding cost can be reduced by reducing safety inventory. The cost can be further reduced by optimizing the supply chain process and establishing long-term cooperative relationships.

[0132] How it works

[0133] By integrating and optimizing each link of the supply chain, the efficiency and stability of the entire construction industry supply chain can be improved. Through intelligent and automated technologies, human errors can be reduced, and the quality of decision-making can be improved, thereby enhancing the competitiveness of the entire supply chain.

[0134] Through the setting of the above modules, by comparing the risk-adjusted predicted profit value and the threshold, it can be ensured that the expected profit of the demand side is met. If the predicted profit does not meet the expectation, the strategy can be adjusted to meet the profit requirements by re-forecasting and matching new developers, which can solve the problem of insufficient prediction and matching accuracy of existing supply chain trading platforms;

[0135] By dynamically adjusting safety stocks and supply strategies, supply and demand can be better balanced and the risk of inventory backlogs or insufficient supply can be reduced. The flexibility of the supply chain is enhanced, and it can respond quickly to market changes and external environmental factors. During long project cycles, the problem of supply and demand imbalance can be resolved and the instability caused by the external environment can be reduced.

[0136] The above are only preferred implementations of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technical staff in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of this template.

Claims

1. A digital supply chain transaction platform management system, characterized in that: It includes a quotation collection module, which is used to collect sales information of suppliers; Demand forecasting module, which is used to forecast the demand for building materials from the demand side and to intelligently match it with the supply side: A risk management module, the risk management module includes an environmental information collection unit and an evaluation unit, the environmental information collection unit is used to collect historical data, environmental data and market data of the supplier, and the evaluation unit is used to evaluate the potential impact value on the supplier's supply chain based on the data of the information collection unit, so as to adjust the supplier; A coordination module is used to coordinate the material supply of the building material supplier and the demander on site according to the data of the demand forecasting module and the risk management module.

2. A digital supply chain transaction platform management system according to claim 1, characterized in that: The specific working mode of the demand forecasting module is as follows: The demand forecasting module includes a forecasting unit and a matching unit. The forecasting unit is used to forecast the material demand of the demander based on historical data, specifically: Obtain the demander's historical purchasing data, including material type, purchase quantity and purchase date; Obtain the project information, expected construction period E and project budget R from the demand side; Obtain the predicted demand Q of the demand side; Get the historical average delay days T of the supplier; Determine which months the expected construction period E falls within, and obtain the corresponding monthly proportion coefficient; Divide the demand side's forecast demand Q by E to obtain the forecast demand value for each day, and add up the forecast demand values ​​for each day in a month to obtain the average forecast demand value for each month; Multiply the average forecast demand value of each month by the monthly ratio coefficient of the corresponding month to obtain the forecast demand of each month, and add the forecast demand of the first month to the monthly ratio coefficient. Obtain forecast demand for each month within the project cycle; Transmitting the forecast demand and project budget R for each month in the project cycle to the matching unit; The matching unit is used to evaluate the supplier according to the data of the quotation collection module, and select the supplier that matches the demander according to the forecast data of the demand forecast module and the quotation of the supplier.

3. A digital supply chain transaction platform management system according to claim 2, characterized in that: The specific method for obtaining the monthly proportional coefficient is as follows: Obtain the material demand of the supply chain trading platform every month for more than three years; Calculate the average material demand for each month; The average demand value for each month is divided by the average material demand value for each month of the supply chain trading platform over three years to obtain the monthly proportion coefficient for that month.

4. A digital supply chain transaction platform management system according to claim 3, characterized in that: The specific working mode of the matching unit is as follows: Obtaining the material quotation and material supply quantity of the supplier in the quotation collection module; The final forecast demand is obtained by adding up the forecast demand of each month in the project cycle of the demand side's materials. The final forecast demand is multiplied by the corresponding material quotations of all suppliers to obtain the forecast cost of each supplier. The forecast cost of each supplier is compared with the project budget R, and the supplier whose forecast cost is greater than the project budget R is eliminated. Compare the material supply of the remaining suppliers with the final forecast demand P of the demander, and give priority to the supplier whose material supply is greater than the forecast demand of each month in the project cycle of the demander and whose material quotation is the lowest, and mark it as the matching supplier; If there is no situation where the material supply is greater than the forecast demand for each month during the project cycle of the demander, the material supplies of multiple suppliers are combined until the material supply is greater than the forecast demand for each month during the project cycle, and the combined suppliers are marked as matching suppliers.

5. A digital supply chain transaction platform management system according to claim 1, characterized in that: The specific working mode of the environmental information collection unit is as follows: First, determine the monitoring indicators, which are market price, supply, environmental weather and market demand; Regularly collect data on the external environment based on the determined monitoring indicators; Standardize the collected data information.

6. A digital supply chain transaction platform management system according to claim 1, characterized in that: The specific working mode of the evaluation unit is as follows: According to the formula The comprehensive risk assessment value H of the supplier supply chain is obtained by calculation, where n is the number of monitoring indicators, X i represents the standardized value of the i-th monitoring indicator, β i is the weight coefficient of the i-th monitoring indicator; The comprehensive risk assessment value H is transmitted to the coordination module.

7. A digital supply chain transaction platform management system according to claim 6, characterized in that: The standardized value X of the i-th monitoring indicator i The specific way to obtain is as follows: Since the monitoring indicators are market price, supply, environmental weather and market demand, correspondingly, X i The supplier’s price risk X1, the supplier’s shortage risk X2, the supplier’s delay risk X3 and the market demand risk X4; The price risk X1 of the supply side is obtained by dividing the change in the demand for building materials in a fixed period of time by the change in the price of building materials in a fixed period of time; The supply-side stockout risk X2 is obtained by dividing the actual supply of building materials by the planned supply in a fixed time period; The supplier's delay risk X3 is obtained by dividing the supply of building materials under specific weather conditions in a fixed period of time by the supply under normal weather conditions; Market demand risk X4 is obtained by dividing the actual supply of building materials by the demand in a fixed time period.

8. A digital supply chain transaction platform management system according to claim 6, characterized in that: The working method of the optimization module also includes: Obtain the expected profit value δ of the demand side; The risk adjustment factor φ1 is obtained based on the comprehensive risk assessment value H; Obtain the expected loss φ2; The risk capital φ3 is obtained based on the predicted loss φ2; The risk value K is obtained by subtracting the risk capital φ3 from the expected return value δ; Obtain the conditional risk value L; According to the formula δ1=δ-(φ1*δ)-L, the risk-adjusted predicted profit value δ1 is obtained. The risk-adjusted predicted profit value δ1 is transmitted to the coordination module.

9. A digital supply chain transaction platform management system according to claim 8, characterized in that: The specific method of obtaining the conditional risk value L is as follows: According to the formula The conditional risk value L is calculated, where σ is the probability that the loss does not exceed the risk value K, γ represents the random variable of the loss, and f(γ) is its probability density function.

10. A digital supply chain transaction platform management system according to claim 8, characterized in that: The specific working mode of the coordination module is as follows: Set the corresponding thresholds of the risk assessment value H and the risk-adjusted predicted profit value δ1 in advance; If the risk assessment value H is greater than the corresponding threshold, the safety stock is increased to cope with potential supply disruptions; If the risk assessment value H is less than the corresponding threshold, the safety stock is reduced to reduce costs; If the risk-adjusted predicted profit value δ1 is greater than the corresponding threshold, it means that the expected profit of the demander is met. Otherwise, a signal is generated and transmitted to the demand forecasting module for re-forecasting and matching new developers until the risk-adjusted predicted profit value δ1 is less than or equal to the corresponding threshold.

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