Block chain-based shopping mall supply chain management method and system

Abstract

The invention discloses a shopping mall supply chain management method and system based on a block chain, and relates to the field of supply chain management, and the method comprises the steps: obtaining the type data and behavior data of a supply chain participant, carrying out the authority distribution according to the type data, and generating the authority data of the supply chain participant; constructing a three-dimensional permission model based on the behavior data, and calculating a reputation score of the supply chain participant; adjusting the permission data based on the reputation score, and performing permission verification on the business operation by using a block chain to obtain a verification result; and recording the permission data, the permission adjustment result and the verification result on the block chain, and evaluating the permission adjustment result to realize block chain-based mall supply chain management. According to the invention, the authority management and the block chain technology are organically combined, so that the security and reliability of the data are guaranteed, and the transparency and efficiency of supply chain management are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of supply chain management, and in particular to a mall supply chain management method and system based on blockchain. Background Art

[0002] With the in-depth development of the global economy and the rapid evolution of information technology, supply chain management, as a key element of an enterprise's core competitiveness, has become increasingly prominent in terms of its complexity and importance; traditional supply chain management models have gradually revealed many chronic problems such as data islands, lack of trust mechanisms, and information asymmetry in the wave of digital transformation; in recent years, blockchain technology, with its characteristics of decentralization, immutability, and traceability, has brought a revolutionary change to the field of supply chain management; blockchain technology records transaction data through a distributed ledger, and smart contracts automatically execute business rules, creating a transparent, efficient, and trustworthy collaboration environment for supply chain participants; however, existing blockchain-based supply chain management methods still have defects such as rigid permission management, single reputation evaluation mechanism, and lack of dynamics in permission adjustment; existing technologies usually adopt a static permission allocation mechanism and cannot be dynamically adjusted according to the actual performance of supply chain participants; reputation evaluation is mostly based on single-dimensional indicators and it is difficult to comprehensively reflect the comprehensive performance of participants in the supply chain; the coupling degree between permission verification and business logic is low, resulting in a disconnection between the effectiveness of permission management and the compliance of business operations; in addition, existing technologies lack a systematic design for the blockchain storage of permission data, and the evaluation mechanism for the results of permission adjustment is not perfect enough to achieve the closed-loop optimization of permission management.

[0003] The current application of blockchain technology in mall supply chain management has not fully exerted its potential. Among them, existing technologies mostly adopt a simple two-dimensional permission model, which cannot comprehensively capture the multi-dimensional behavioral characteristics of supply chain participants in resource use, operation execution, and role fulfillment, resulting in a mismatch between permission allocation and actual needs; the reputation scoring calculation method lacks the support of a mathematical model, and the objectivity and accuracy of the scoring results need to be improved; the permission adjustment mechanism usually relies on manual intervention, with insufficient automation, low efficiency, and being easily affected by subjective factors; at the same time, the existing technology is not deeply integrated with the blockchain in the permission verification link, and fails to make full use of the smart contract function of the blockchain to achieve automated permission verification, and the security and reliability of permission data are not guaranteed enough; in addition, there is a lack of a systematic evaluation mechanism for the results of permission adjustment, making it difficult to judge the rationality and effectiveness of permission adjustment and unable to form a continuous optimization closed-loop of permission management. These problems seriously restrict the application effect and value of blockchain technology in supply chain management. Summary of the Invention

[0004] The purpose of this section is to outline some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section, as well as in the abstract and title of the present application, to avoid obscuring the purpose of this section, the abstract, and the title. However, such simplifications or omissions shall not be used to limit the scope of the present invention.

[0005] In view of the above problems, the present invention is proposed.

[0006] Therefore, the present invention provides a blockchain-based mall supply chain management method, which can solve the problems mentioned in the background art.

[0007] To solve the above technical problems, the present invention provides the following technical solutions: In a first aspect, an embodiment of the present invention provides a blockchain-based mall supply chain management method, which includes obtaining type data and behavior data of supply chain participants, and performing permission allocation according to the type data to generate permission data of supply chain participants; constructing a three-dimensional permission model based on the behavior data, and calculating the credit score of supply chain participants; adjusting the permission data based on the credit score, and using the blockchain to perform permission verification on business operations to obtain a verification result; recording the permission data, permission adjustment result, and verification result on the blockchain, and evaluating the permission adjustment result to achieve blockchain-based mall supply chain management.

[0008] As a preferred solution of the blockchain-based mall supply chain management method of the present invention, wherein: the type data of the supply chain participants includes role type data and credit score data; the role type data includes suppliers, manufacturers, logistics providers, and retailers; the behavior data includes transaction data, contract performance, and product quality; the permission data includes resource dimension permissions, operation dimension permissions, and role dimension permissions.

[0009] As a preferred solution of the blockchain-based mall supply chain management method of the present invention, wherein: constructing a three-dimensional permission model based on the behavior data means obtaining the behavior data of supply chain participants, including transaction data, contract performance, and product quality, and performing comprehensive analysis to construct a three-dimensional permission model, and then obtaining the credit score of supply chain participants; constructing a three-dimensional permission model based on the behavior data includes the following steps: obtaining the transaction data, contract performance, and product quality of supply chain participants; formulating resource dimension indicators based on the transaction data, and introducing a decay coefficient for optimization to obtain the final resource dimension indicators. The specific formula of the resource dimension indicators is as follows: , where f1(T) is the resource dimension indicator; T is the transaction data; γ1 is the decay coefficient; α1 is the exponential decay coefficient; By formulating and adjusting operation dimension indicators based on the contract performance, the final operation dimension indicators are obtained. The specific formula for the operation dimension indicators is as follows: , where f2(C) is the operation dimension indicator; C is the contract performance; β2 is the attenuation coefficient; α2 is the exponential attenuation coefficient; γ2 is the attenuation coefficient; Formulate role dimension indicators based on the product quality, and adjust the initial role dimension indicators by using the quality feedback attenuation coefficient to obtain the final role dimension indicators. The specific formula for the role dimension indicators is as follows: , where f3(Q) is the role dimension indicator; Q is the product quality; γ3 is the attenuation coefficient; Based on the resource dimension indicator, the operation dimension indicator, and the role dimension indicator, a comprehensive analysis is performed to obtain a three-dimensional permission model.

[0010] As a preferred embodiment of the blockchain-based mall supply chain management method of the present invention, wherein: the specific formula for the three-dimensional permission model is as follows: , where S cred is the credit score of the supply chain participant; T is the transaction data; γ1 is the attenuation coefficient; α1 is the exponential attenuation coefficient; C is the contract performance; β2 is the attenuation coefficient; α2 is the exponential attenuation coefficient; γ2 is the attenuation coefficient; Q is the product quality; γ3 is the attenuation coefficient.

[0011] As a preferred embodiment of the blockchain-based mall supply chain management method of the present invention, wherein: adjusting the permission data based on the credit score includes the following steps: calculating the credit score by using the three-dimensional permission model to obtain the credit score of the supply chain participant, and updating the credit score data to the corresponding credit score of the supply chain participant; judging the credit score data according to the set permission adjustment trigger condition. If the credit score data is greater than the credit increase threshold, perform the permission upgrade evaluation step; if the credit score data is less than the credit decrease threshold, perform the permission downgrade evaluation step; if the credit score data is greater than or equal to the credit decrease threshold and less than or equal to the credit increase threshold, no permission adjustment is performed.

[0012] As a preferred solution of the blockchain-based mall supply chain management method of the present invention, the following steps are included: The execution permission elevation assessment step includes: When performing permission elevation assessment, it is judged based on the transaction data, contract performance status, and product quality of the corresponding supply chain participant. If the transaction data is greater than the transaction standard threshold, the resource dimension permission of the corresponding supply chain participant is elevated; if the contract performance status is greater than the performance standard threshold, the operation dimension permission of the corresponding supply chain participant is elevated; if the product quality is greater than the quality standard threshold, the role dimension permission of the corresponding supply chain participant is elevated; if the transaction data is less than or equal to the transaction standard threshold, the contract performance status is less than or equal to the performance standard threshold, or the product quality is less than or equal to the quality standard threshold, the resource dimension permission, operation dimension permission, or role dimension permission of the corresponding supply chain participant is not elevated. The execution permission reduction assessment step includes: When performing permission reduction assessment, it is judged based on the transaction data, contract performance status, and product quality of the corresponding supply chain participant. If the transaction data is less than the transaction standard threshold, the resource dimension permission of the corresponding supply chain participant is reduced; if the contract performance status is less than the performance standard threshold, the operation dimension permission of the corresponding supply chain participant is reduced; if the product quality is less than the quality standard threshold, the role dimension permission of the corresponding supply chain participant is reduced; if the transaction data is greater than or equal to the transaction standard threshold, the contract performance status is greater than or equal to the performance standard threshold, or the product quality is greater than or equal to the quality standard threshold, the resource dimension permission, operation dimension permission, or role dimension permission of the corresponding supply chain participant is not reduced.

[0013] As a preferred solution of the blockchain-based mall supply chain management method of the present invention, the following steps are included: Permission allocation is performed according to the type data to generate the permission data of the supply chain participant, including the following steps: Obtain the basic information and role type application submitted by the supply chain participant; Verify the identity credentials submitted by the supply chain participant; Generate a unique blockchain address and private key pair for the supply chain participant according to the role type data; Perform permission data allocation for the supply chain participant to obtain the corresponding permission data, and create a unique permission identifier and associate it with the permission data; Write the permission data into the blockchain through a smart contract, activate the permission data of the supply chain participant, and record the permission effective status on the blockchain.

[0014] Second aspect: To further solve the security problems existing in supply chain management, an embodiment of the present invention provides a mall supply chain management system based on blockchain, which includes: a data acquisition module, configured to obtain the type data and behavior data of supply chain participants, and perform permission allocation according to the type data to generate permission data of supply chain participants; a reputation scoring module, configured to construct a three-dimensional permission model based on the behavior data and calculate the reputation score of supply chain participants; a permission adjustment module, configured to adjust the permission data based on the reputation score, and perform permission verification on business operations using blockchain to obtain a verification result; an adjustment evaluation module, configured to record the permission data, permission adjustment result, and verification result on the blockchain, and evaluate the permission adjustment result to implement mall supply chain management based on blockchain.

[0015] Third aspect: An embodiment of the present invention provides a computer device, including a memory and a processor, where the memory stores a computer program, and: when the computer program is executed by the processor, any step of the method for mall supply chain management based on blockchain as described in the first aspect of the present invention is implemented.

[0016] Fourth aspect: An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, and: when the computer program is executed by the processor, any step of the method for mall supply chain management based on blockchain as described in the first aspect of the present invention is implemented.

[0017] Advantages of the present invention: By using the permission allocation mechanism based on type data, the system can assign differentiated access permissions for different roles, laying a foundation for subsequent refined management; by comprehensively considering three key dimensions of transaction data, contract performance, and product quality, and using a scientific mathematical model to calculate the reputation score, it can comprehensively reflect the true credit status of supply chain participants, avoiding the one-sidedness of traditional single-dimensional evaluation; by establishing an association mechanism between the reputation score and the permission level, when the reputation score of a participant changes to a specific threshold, the system will automatically trigger permission adjustment and perform permission verification through blockchain technology to ensure the compliance of business operations, establishing a positive feedback loop between the behavior and permissions of supply chain participants, effectively motivating good behaviors, suppressing bad behaviors, optimizing the supply chain ecological environment, and improving the overall operation efficiency; by organically combining permission management with blockchain technology, it not only ensures the security and reliability of data, but also significantly improves the transparency and efficiency of supply chain management. Description of the Drawings

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings. Among them: Figure 1 It is the overall flowchart of the blockchain-based mall supply chain management method in Embodiment 1; Figure 2 It is the construction flowchart of the three-dimensional permission model in Embodiment 1; Figure 3 It is the permission improvement evaluation flowchart in Embodiment 1; Figure 4 It is the permission reduction evaluation flowchart in Embodiment 1; Figure 5 It is the structural schematic diagram of the computer device in Embodiment 3. Detailed implementation manners

[0019] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will make a detailed description of the specific implementation manners of the present invention in conjunction with the drawings of the specification.

[0020] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can also be implemented in other ways different from those described herein. Those skilled in the art can make similar extensions without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0021] Secondly, the so-called "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that can be included in at least one implementation manner of the present invention. The "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selectively exclusive embodiment from other embodiments.

[0022] Embodiment 1, referring to Figures 1 to 4 , is the first embodiment of the present invention. This embodiment provides a blockchain-based mall supply chain management method.

[0023] The existing mall supply chain management methods mainly have the following problems: Most of the existing technologies adopt a simple two-dimensional permission model, which cannot comprehensively capture the multi-dimensional behavioral characteristics of supply chain participants in resource use, operation execution, role fulfillment, etc., resulting in a mismatch between permission allocation and actual needs; The reputation scoring calculation method lacks the support of a mathematical model, and the objectivity and accuracy of the scoring results need to be improved; The permission adjustment mechanism usually relies on manual intervention, with insufficient automation, low efficiency and being easily affected by subjective factors; At the same time, the existing technologies are not deeply integrated with the blockchain in the permission verification link, and the intelligent contract function of the blockchain cannot be fully utilized to achieve automated verification of permissions, and the security and reliability of permission data are insufficiently guaranteed; In addition, there is a lack of a systematic evaluation mechanism for the results of permission adjustment, making it difficult to judge the rationality and effectiveness of permission adjustment and unable to form a continuous optimization closed loop for permission management. These problems seriously restrict the application effect and value of blockchain technology in supply chain management.

[0024] This application provides a solution that can effectively solve the above-mentioned problems. Next, multiple embodiments will be combined to elaborate in detail on how to implement this blockchain-based mall supply chain management method.

[0025] Figure 1 The overall flowchart of the blockchain-based mall supply chain management method is shown, including: S1: Obtain the type data and behavioral data of supply chain participants, and perform permission allocation according to the type data to generate the permission data of supply chain participants.

[0026] In the embodiments of this application, the type data of supply chain participants includes role type data and reputation scoring data.

[0027] Furthermore, the role type data includes suppliers, manufacturers, logistics providers, and retailers.

[0028] In the embodiments of this application, the behavioral data includes transaction data, contract fulfillment status, and product quality.

[0029] In the embodiments of this application, the permission data includes resource dimension permissions, operation dimension permissions, and role dimension permissions.

[0030] In the embodiments of this application, performing permission allocation according to the type data to generate the permission data of supply chain participants includes the following steps: Obtain the basic information and role type application submitted by supply chain participants.

[0031] Verify the identity credentials submitted by supply chain participants.

[0032] Generate a unique blockchain address and private key pair for supply chain participants according to the role type data.

[0033] Allocate permission data to supply chain participants to obtain corresponding permission data, and create a unique permission identifier and associate it with the permission data.

[0034] Write the permission data into the blockchain through a smart contract, activate the permission data of supply chain participants, and record the permission effective status on the blockchain.

[0035] S2: Build a three-dimensional permission model based on behavior data and calculate the credit score of supply chain participants.

[0036] In the embodiment of the present application, building a three-dimensional permission model based on behavior data means obtaining the behavior data of supply chain participants, including transaction data, contract performance, and product quality, and conducting comprehensive analysis to build a three-dimensional permission model, and then obtaining the credit score of supply chain participants.

[0037] Further, as Figure 2 shown in the flowchart for building a three-dimensional permission model, building a three-dimensional permission model based on behavior data includes the following steps: Obtain the transaction data, contract performance, and product quality of supply chain participants.

[0038] Formulate resource dimension indicators based on transaction data, representing the impact of transaction data on the credit score, and introduce a decay coefficient for optimization, thereby dealing with the phenomenon that the increase in the credit score gradually slows down as the number of transactions or the amount increases, and obtain the final resource dimension indicators. The specific formula for the resource dimension indicators is as follows: , where f1(T) is the resource dimension indicator, representing the impact of transaction data on the credit score; T is the transaction data, representing the number of transactions or the transaction amount of supply chain participants; γ1 is the decay coefficient, used to control the impact intensity of transaction data on the credit score; α1 is the exponential decay coefficient, used to control the decay speed of the influence of transaction data.

[0039] Contract performance reflects the performance ability and compliance of supply chain participants. The higher the performance rate, the higher the credit score of the participant. However, there is a gradual process for quality improvement. Therefore, by formulating operation dimension indicators using contract performance and making adjustments, ensure that the impact of contract performance gradually decreases as the performance rate increases, and obtain the final operation dimension indicators. The specific formula for the operation dimension indicators is as follows: , where f2(C) is the operation dimension indicator, representing the impact of contract performance on the credit score; C is the contract performance, representing the performance rate or contract completion rate; β2 is the decay coefficient, used to control the improvement amplitude of contract performance on the credit score; α2 is the exponential decay coefficient, used to adjust the influence speed of contract performance on the credit score; γ2 is the decay coefficient, used to control the impact of performance on the credit score.

[0040] Since the evaluation of product quality usually grows non-linearly, especially when the quality is poor, its impact on the reputation score is more significant. By using product quality to formulate role dimension indicators, processing the product quality, avoiding the excessive impact of low-quality products on the reputation score, and adjusting the initial role dimension indicators by using the quality feedback attenuation coefficient to avoid the overly significant impact on the reputation when the quality score is too high, the final role dimension indicators are obtained. The specific formula for the role dimension indicators is as follows: , where f3(Q) is the role dimension indicator, representing the impact of product quality on the reputation score; Q is the product quality, reflecting the product quality assessment of supply chain participants or customer feedback; γ3 is the attenuation coefficient, used to control the degree of impact of product quality on the reputation score.

[0041] Based on the resource dimension indicator, operation dimension indicator, and role dimension indicator for comprehensive analysis, a three-dimensional permission model is obtained.

[0042] It should be noted that the above attenuation coefficient γ1 is used to control the impact intensity of transaction data on the reputation score, which is set by using regression analysis or historical data analysis in this embodiment and adjusted according to different industries, platform scales, and transaction modes, and its value is usually between 0.1 and 1.0; the exponential attenuation coefficient α1 is used to control the attenuation speed of the influence of transaction data, which is determined by fitting the transaction growth trend of historical data in this embodiment or selected empirically according to the model, so as to control the attenuation degree of the influence, and its value is usually between 0.1 and 1.0; the attenuation coefficient β2 is used to control the impact intensity of performance on the reputation score, which can be obtained by analyzing the relationship between performance and reputation score in historical contract data or adjusted through experimental settings, and its value is between 0.1 and 2.0; the exponential attenuation coefficient α2 is used to control the attenuation speed of the influence of performance, which is set by historical data regression analysis or according to experience. Usually, the model needs to adjust the exponential attenuation coefficient α2 to observe the non-linear impact of contract performance on the score, and its value is usually between 0.1 and 1.0; the attenuation coefficient γ3 is used to control the impact intensity of quality feedback on the reputation score, which can be determined by analyzing the relationship between quality feedback and score, or can be fitted through a regression model. Generally speaking, the impact of quality feedback on the score is usually more significant, so the attenuation coefficient γ3 may be larger, and its value is usually between 0.1 and 1.5.

[0043] In the embodiment of this application, the specific formula for the three-dimensional permission model is as follows: , where S credR represents the credit score of supply chain participants, which is the output of the three-dimensional permission model and takes values in the range of [0, 1]; T represents transaction data, which can be the number of transactions or the transaction amount of supply chain participants; γ1 is the decay coefficient, used to control the influence intensity of transaction data on the credit score; α1 is the exponential decay coefficient, used to control the decay speed of the influence of transaction data; C represents the contract fulfillment situation, which can be the fulfillment rate or the contract completion degree; β2 is the decay coefficient, used to control the improvement amplitude of the contract fulfillment situation on the credit score; α2 is the exponential decay coefficient, used to adjust the influence speed of the contract fulfillment situation on the credit score; γ2 is the decay coefficient, used to control the influence intensity of the fulfillment situation on the credit score; Q represents product quality, which reflects the product quality evaluation or customer feedback of supply chain participants; γ3 is the decay coefficient, used to control the influence degree of product quality on the credit score.

[0044] In an alternative embodiment, various strategies can also be adopted to construct the three-dimensional permission model based on behavioral data to capture the credit performance and potential risk characteristics of supply chain participants in different dimensions. For example, a neural network model can be used to perform deep learning on transaction data, contract fulfillment situation, and product quality, and the influence factors of each dimension index can be automatically adjusted through the weights between hidden layers to achieve more accurate credit evaluation. Time series analysis methods can also be introduced. The historical behavioral data of participants can be divided into multiple time windows according to time, and the dimension index values within each time window are calculated respectively, and the influence degree of recent behaviors on the credit score is strengthened through time-weighted averaging. Fuzzy logic theory can also be combined to convert quantitative indicators such as transaction data, contract fulfillment situation, and product quality into linguistic variables, and a fuzzy rule-based inference system is constructed to handle the situation of fuzzy index boundaries in real business. No matter which strategy is adopted, it is necessary to ensure that the constructed three-dimensional permission model can fully reflect the credit status and behavioral characteristics of supply chain participants on the basis of maintaining the fairness of the score, and provide support for the accurate operation of the subsequent permission adjustment mechanism. This embodiment does not make specific limitations on this.

[0045] It should be noted that the reputation evaluation of participants in traditional supply chain management often relies on data from a single dimension and is difficult to comprehensively reflect their actual performance. In addition, existing technologies usually adopt linear models when quantifying behavioral data and cannot accurately capture the non-linear impact of data growth on reputation scores. In this embodiment, by introducing a three-dimensional permission model and combining indicators from the resource dimension, operation dimension, and role dimension, a multi-dimensional comprehensive evaluation of the behavioral data of supply chain participants is achieved, effectively solving the problem of over-inflated scores in the traditional linear model in scenarios with high transaction volumes or high fulfillment rates. For example, when the transaction amount is large, the growth of the reputation score tends to flatten, avoiding score imbalance caused by excessively high single-dimensional data. This design not only improves the scientificity and fairness of the reputation score but also provides a reliable basis for subsequent dynamic permission adjustment. Compared with existing technologies, this method of multi-dimensional modeling combined with non-linear optimization can more accurately reflect the actual performance of supply chain participants and significantly improve the rationality of permission allocation.

[0046] S3: Adjust the permission data based on the reputation score, and use the blockchain to verify the permissions for business operations to obtain the verification result.

[0047] In the embodiment of the present application, adjusting the permission data based on the reputation score includes the following steps: calculating the reputation score using the three-dimensional permission model to obtain the reputation score of the supply chain participant, and updating the reputation score data to the corresponding reputation score of the supply chain participant.

[0048] Judge the reputation score data according to the set permission adjustment trigger condition. If the reputation score data is greater than the reputation increase threshold, then execute the permission promotion evaluation step.

[0049] If the reputation score data is less than the reputation decrease threshold, then execute the permission reduction evaluation step.

[0050] If the reputation score data is greater than or equal to the reputation decrease threshold and less than or equal to the reputation increase threshold, then no permission adjustment is performed.

[0051] In the embodiment of the present application, as Figure 3 shown in the permission promotion evaluation flow chart, executing the permission promotion evaluation step includes: when performing the permission promotion evaluation, judge based on the transaction data, contract fulfillment situation, and product quality of the corresponding supply chain participant. If the transaction data is greater than the transaction standard threshold, then promote the resource dimension permission of the corresponding supply chain participant. For example, if a manufacturer has a good procurement record for a certain type of raw material, its procurement quota permission for this type of raw material can be promoted.

[0052] If the contract fulfillment situation is greater than the fulfillment standard threshold, then promote the operation dimension permission of the corresponding supply chain participant. For example, if a logistics provider has a high on-time delivery rate, its permission to independently adjust the delivery route can be promoted.

[0053] If the product quality is greater than the quality standard threshold, the role dimension permissions of the corresponding supply chain participant are increased. For example, when a certain supplier has a high raw material quality score, its raw material information management permissions can be increased.

[0054] If the transaction data is less than or equal to the transaction standard threshold, the contract performance is less than or equal to the performance standard threshold, or the product quality is less than or equal to the quality standard threshold, then the resource dimension permissions, operation dimension permissions, or role dimension permissions of the corresponding supply chain participant are not increased.

[0055] In the embodiment of the present application, as Figure 4 shown is the flowchart of the permission reduction assessment. The steps for performing the permission reduction assessment include: when performing the permission reduction assessment, based on the transaction data, contract performance, and product quality of the corresponding supply chain participant for judgment. If the transaction data is less than the transaction standard threshold, then the resource dimension permissions of the corresponding supply chain participant are reduced. For example, if a certain manufacturer has multiple waste records of high-value raw materials, the upper limit of the procurement quantity of its high-value raw materials is reduced.

[0056] If the contract performance is less than the performance standard threshold, then the operation dimension permissions of the corresponding supply chain participant are reduced. For example, if a certain retailer has made false price tags multiple times or the price fluctuates abnormally frequently, its independent pricing permission is reduced, and it is changed to that price changes need to be reviewed and confirmed by the system.

[0057] If the product quality is less than the quality standard threshold, then the role dimension permissions of the corresponding supply chain participant are reduced. For example, if the raw material quality of a certain supplier is unqualified three times in a row, its raw material independent entry permission is reduced, and it is changed to that new raw material information needs to be reviewed before uploading.

[0058] If the transaction data is greater than or equal to the transaction standard threshold, the contract performance is greater than or equal to the performance standard threshold, or the product quality is greater than or equal to the quality standard threshold, then the resource dimension permissions, operation dimension permissions, or role dimension permissions of the corresponding supply chain participant are not reduced.

[0059] It should be noted that the permission allocation in the existing supply chain management system is usually static, lacking a dynamic adjustment mechanism, which easily leads to the lag of permission allocation behind the actual business needs, and may even cause risks due to the abuse of permissions. In this embodiment, by setting the trigger conditions for permission adjustment and combining specific behavior data, the dynamic adjustment of permissions is realized. For example, when a certain manufacturer has a good procurement record for a certain type of raw material, the system will automatically increase its procurement quota permission; while when the raw material quality of a certain supplier is unqualified continuously, the system will reduce its information entry permission. This dynamic adjustment mechanism can not only respond to the behavior changes of supply chain participants in a timely manner, but also effectively reduce the risks caused by the abuse of permissions. Compared with the existing technology, the present invention realizes the intelligent and refined management of permissions by linking the permission adjustment with specific behavior data.

[0060] Exemplarily, for the relevant steps of the above-mentioned permission adjustment, assuming that a certain supplier, as a supply chain participant, has calculated its credit score through a three-dimensional permission model, the following situation will occur during the permission adjustment process: First, the system calculates the credit score of the supplier based on the three-dimensional permission model and updates its credit score data; then, the system judges the credit score data of the supplier according to the set permission adjustment trigger conditions. Among them, the credit score data of the supplier is greater than the credit increase threshold, and the system automatically triggers a permission upgrade assessment; during the permission upgrade assessment, the transaction data, contract performance, and product quality of the supplier are specifically analyzed. It is found that the transaction data of the supplier is greater than the transaction standard threshold, so its resource dimension permission is upgraded, enabling it to obtain more supply chain resources and information; at the same time, the contract performance of the supplier is also greater than the performance standard threshold, and the system correspondingly upgrades its operation dimension permission, allowing it to perform more types of supply chain operations; in addition, the product quality of the supplier is also greater than the quality standard threshold, so the system upgrades its role dimension permission, enabling it to obtain higher role permissions in the supply chain; these permission adjustment results and verification results are recorded on the blockchain, ensuring the transparency and immutability of the adjustment process, and at the same time providing a reliable basis for subsequent permission adjustment assessments.

[0061] It should be noted that various thresholds involved in the present invention, such as the credit increase threshold, credit decrease threshold, transaction standard threshold, performance standard threshold, and quality standard threshold, can be scientifically determined by using a variety of data analysis methods; in this embodiment, a multi-stage hybrid analysis method is used to determine these thresholds. First, historical behavior data of supply chain participants is collected, and outliers and incomplete records are removed through preprocessing; then, quantile analysis is applied to the three dimensions of transaction data, contract performance, and product quality respectively to obtain the credit increase threshold and credit decrease threshold; for the specific transaction standard threshold, performance standard threshold, and quality standard threshold, an adaptive clustering algorithm is used. First, the DBSCAN algorithm is used to identify and remove outliers, and then the K-means algorithm is used to perform clustering analysis on the data, and the silhouette coefficient is combined to evaluate the clustering quality; finally, the seasonal fluctuation characteristics of each index are analyzed through time series decomposition technology, and the initially determined thresholds are seasonally adjusted to make the thresholds more in line with the business cycle change law; this method comprehensively considers the data distribution characteristics, the influence of outliers, and the time series characteristics, so that the setting of each threshold has both mathematical theoretical support and meets the actual business needs, and can trigger the permission adjustment mechanism more accurately, improving the efficiency and security of supply chain management.

[0062] In an alternative embodiment, various strategies can also be adopted to adjust the permission data based on the reputation score to achieve precise and dynamic management of the permissions of supply chain participants. For example, a hierarchical incremental adjustment mechanism can be introduced to determine the amplitude of permission adjustment according to the gap between the reputation score and the threshold, rather than simple binary adjustment, making the permission changes smoother and more gradual. Reinforcement learning algorithms can also be combined to continuously optimize the adjustment strategy by continuously observing the operation status of the supply chain after permission adjustment, enabling the system to autonomously learn the optimal permission adjustment plan. Situation awareness technology can also be introduced to dynamically adjust the reputation score threshold according to the current overall operation status of the supply chain, making the permission adjustment more in line with the actual business needs. In addition, a multi-party consensus mechanism can be established. When significant adjustments are required for the permissions of a certain participant, multiple relevant participants are required to vote and confirm through smart contracts to enhance the fairness and acceptability of the adjustment results.

[0063] In an alternative embodiment, various methods can also be used to adjust the permission data based on the reputation score, especially more fine-grained control can be achieved in the processing of three core indicators: transaction data, contract performance, and product quality. For example, different priority weights can be set for the three types of data. According to the specific business characteristics of the supply chain, product quality indicators may be more emphasized for manufacturing supply chains, and transaction data indicators may be more emphasized for fast-moving consumer goods supply chains. By dynamically adjusting the weight ratio of the three types of data, the permission adjustment can better meet the needs of specific industries. A hybrid judgment strategy can also be adopted, using an accumulative judgment method for transaction data, an extreme value judgment method for contract performance, and an average judgment method for product quality, so as to more comprehensively evaluate the behavior of participants. The time sensitivity difference can also be introduced to make the permission reduction caused by product quality problems take effect immediately, while the permission increase brought about by the improvement of transaction data requires confirmation through an observation period. In addition, a cross-threshold mechanism can be designed. When a certain indicator performs extremely well, it can make up for the deficiency of another indicator to a certain extent. For example, when the product quality is particularly excellent, even if the contract performance is slightly lower than the threshold, the existing permissions can be maintained unchanged. No matter which strategy is adopted, it is necessary to ensure that the judgment mechanism can accurately reflect the comprehensive behavior characteristics of supply chain participants and avoid excessive influence on permission adjustment caused by fluctuations in a single indicator. This embodiment does not make specific limitations in this regard.

[0064] In the embodiment of the present application, the permission verification of business operations using blockchain and obtaining the verification result include the following steps: after receiving a business operation request, call the permission verification smart contract on the blockchain to verify the identity signature of the participant.

[0065] Retrieve the current permission data of the supply chain participant from the blockchain ledger and compare the role, resource, and operation dimension permission levels required for the operation.

[0066] Analyze the deviation degree of the current operation based on the historical behavior recorded on the blockchain to identify potential risks.

[0067] Write the verification result into the blockchain to form an immutable verification record, and control the execution of business operations accordingly.

[0068] S4: Record the permission data, permission adjustment result, and verification result on the blockchain, and evaluate the permission adjustment result to achieve blockchain-based mall supply chain management.

[0069] In the embodiment of the present application, evaluating the permission adjustment result includes the following steps: Obtain the permission adjustment result and the corresponding behavior data from the blockchain, and calculate the permission adjustment impact index based on the behavior data before and after the permission adjustment.

[0070] Evaluate the permission adjustment result according to the permission adjustment impact index.

[0071] Verify the evaluation result of the permission adjustment result based on the blockchain consensus mechanism to confirm whether the evaluation result is valid, and record the verification process and verification result on the blockchain through a smart contract to achieve blockchain-based mall supply chain management.

[0072] It should be noted that the traditional permission verification method has problems such as easy data tampering, opaque verification process, and lack of comprehensive analysis ability for historical behavior data, making it difficult to identify potential risks; in this embodiment, the blockchain consensus mechanism is used to evaluate and verify the permission adjustment result, constructing a self-optimizing closed-loop system, enabling the entire supply chain management system to continuously adjust and improve according to the actual operation situation; at the same time, the present invention solves the data security and transparency problems in permission verification through blockchain technology, and enhances the risk identification ability through historical behavior analysis, which are advantages not possessed by the traditional permission verification method.

[0073] In summary, by utilizing the permission allocation mechanism based on type data, the present invention enables the system to assign differentiated access permissions to different roles, laying a foundation for subsequent refined management. By comprehensively considering three key dimensions of transaction data, contract performance, and product quality and using a scientific mathematical model to calculate the credit score, it can comprehensively reflect the true credit status of supply chain participants, avoiding the one-sidedness of traditional single-dimensional evaluations. By establishing an association mechanism between the credit score and the permission level, when the credit score of a participant changes to a specific threshold, the system automatically triggers permission adjustment and uses blockchain technology for permission verification to ensure the compliance of business operations, establishing a positive feedback loop between the behaviors and permissions of supply chain participants, effectively motivating good behaviors, suppressing bad behaviors, optimizing the supply chain ecological environment, and improving the overall operation efficiency. The organic combination of permission management and blockchain technology not only ensures the security and reliability of data but also significantly improves the transparency and efficiency of supply chain management.

[0074] Embodiment 2 is an embodiment of the present invention, which provides a blockchain-based mall supply chain management system, including: a data acquisition module for acquiring the type data and behavior data of supply chain participants, and allocating permissions according to the type data to generate the permission data of supply chain participants; a credit score module for constructing a three-dimensional permission model based on the behavior data and calculating the credit score of supply chain participants; a permission adjustment module for adjusting the permission data based on the credit score and using blockchain to verify the permissions of business operations to obtain a verification result; an adjustment evaluation module for recording the permission data, permission adjustment result, and verification result on the blockchain and evaluating the permission adjustment result to implement blockchain-based mall supply chain management.

[0075] Embodiment 3 is an embodiment of the present invention, which is different from the previous embodiment in that: As Figure 5 shown, if the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0076] The logic and / or steps represented in the flowchart or otherwise described herein can, for example, be considered as a definitional sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in conjunction with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0077] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection portion having one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or other suitable processing as necessary, and then stored in a computer memory.

[0078] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), and the like.

[0079] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A blockchain-based mall supply chain management method, characterized by: include: Acquire type data and behavior data of supply chain participants, and assign permissions based on the type data to generate permission data of supply chain participants; Building a three-dimensional authority model based on the behavior data and calculating the reputation scores of supply chain participants; The permission data is adjusted based on the reputation score, and the permission of the business operation is verified using the blockchain to obtain a verification result; The authority data, authority adjustment results and verification results are recorded on the blockchain, and the authority adjustment results are evaluated to realize the blockchain-based mall supply chain management.

2. The blockchain-based mall supply chain management method according to claim 1, characterized in that: The type data of the supply chain participants includes role type data and reputation score data; The role type data includes suppliers, manufacturers, logistics providers and retailers; The behavioral data includes transaction data, contract performance and product quality; The permission data includes resource dimension permissions, operation dimension permissions and role dimension permissions.

3. The blockchain-based mall supply chain management method according to claim 2, characterized in that: Building a three-dimensional authority model based on the behavior data refers to obtaining the behavior data of supply chain participants, including transaction data, contract performance and product quality, and conducting a comprehensive analysis to build a three-dimensional authority model, thereby obtaining the credit score of the supply chain participants; Building a three-dimensional permission model based on the behavior data includes the following steps: Obtain transaction data, contract performance and product quality of supply chain participants; Based on the transaction data, resource dimension indicators are formulated, and the attenuation coefficient is introduced for optimization to obtain the final resource dimension indicators. The specific formula of the resource dimension indicators is as follows: , where f1(T) is the resource dimension indicator; T is the transaction data; γ1 is the decay coefficient; α1 is the exponential decay coefficient; By using the contract performance to formulate and adjust the operation dimension indicators, the final operation dimension indicators are obtained. The specific formula of the operation dimension indicators is as follows: , where f2(C) is the operation dimension indicator; C is the contract performance; β2 is the attenuation coefficient; α2 is the exponential attenuation coefficient; γ2 is the attenuation coefficient; The product quality is used to formulate a role dimension index, and the initial role dimension index is adjusted by using the quality feedback attenuation coefficient to obtain the final role dimension index. The specific formula of the role dimension index is as follows: , where f3( Q) is the role dimension indicator; Q is product quality; γ3 is the attenuation coefficient; A three-dimensional permission model is obtained by performing a comprehensive analysis based on the resource dimension index, the operation dimension index and the role dimension index.

4. The blockchain-based mall supply chain management method according to claim 3, characterized in that: The specific formula of the three-dimensional permission model is as follows: , where S cred is the reputation score of the supply chain participant; T is the transaction data; γ1 is the attenuation coefficient; α1 is the exponential attenuation coefficient; C is the contract performance; β2 is the attenuation coefficient; α2 is the exponential attenuation coefficient; γ2 is the attenuation coefficient; Q is the product quality; γ3 is the attenuation coefficient.

5. The blockchain-based mall supply chain management method according to claim 4, characterized in that: Adjusting the authority data based on the reputation score comprises the following steps: Calculating reputation scores using the three-dimensional authority model to obtain reputation scores of supply chain participants, and updating the reputation score data to the reputation scores of corresponding supply chain participants; The reputation score data is judged according to the set permission adjustment trigger condition, and if the reputation score data is greater than the reputation increase threshold, the permission escalation evaluation step is executed; If the reputation score data is less than the reputation reduction threshold, executing the authority reduction evaluation step; If the credit score data is greater than or equal to the credit decline threshold and less than or equal to the credit increase threshold, no permission adjustment is performed.

6. The blockchain-based mall supply chain management method according to claim 5, characterized in that: The steps of performing privilege escalation assessment include: When evaluating the authority escalation, the judgment is made based on the transaction data, contract performance and product quality of the corresponding supply chain participants. If the transaction data is greater than the transaction standard threshold, the resource dimension authority of the corresponding supply chain participant is enhanced; If the contract performance is greater than the performance standard threshold, the operation dimension authority of the corresponding supply chain participant will be enhanced; If the product quality is greater than the quality standard threshold, the role dimension permissions of the corresponding supply chain participants will be increased; If the transaction data is less than or equal to the transaction standard threshold, the contract performance is less than or equal to the performance standard threshold, or the product quality is less than or equal to the quality standard threshold, the resource dimension permissions, operation dimension permissions, or role dimension permissions of the corresponding supply chain participant will not be increased; The execution privilege reduction assessment step comprises: When evaluating authority reduction, the judgment is made based on the transaction data, contract performance and product quality of the corresponding supply chain participants. If the transaction data is less than the transaction standard threshold, the resource dimension authority of the corresponding supply chain participant is reduced; If the contract performance is less than the performance standard threshold, the operation dimension authority of the corresponding supply chain participant will be reduced; If the product quality is lower than the quality standard threshold, the role dimension authority of the corresponding supply chain participant will be reduced; If the transaction data is greater than or equal to the transaction standard threshold, the contract performance is greater than or equal to the performance standard threshold, or the product quality is greater than or equal to the quality standard threshold, the resource dimension permissions, operation dimension permissions, or role dimension permissions of the corresponding supply chain participant will not be reduced.

7. The blockchain-based mall supply chain management method according to claim 6, characterized in that: Allocating authority according to the type data to generate authority data for supply chain participants includes the following steps: Obtain basic information and role type applications submitted by supply chain participants; Verify the identity credentials submitted by supply chain participants; Generate unique blockchain addresses and private key pairs for supply chain participants based on role type data; Allocate permission data to supply chain participants, obtain corresponding permission data, and create a unique permission identifier to associate it with the permission data; The permission data is written into the blockchain through a smart contract, and the permission data of the supply chain participants is activated, and the permission effectiveness status is recorded on the blockchain.

8. A blockchain-based shopping mall supply chain management system, based on the blockchain-based shopping mall supply chain management method according to any one of claims 1 to 7, characterized in that: include, The data acquisition module is used for the type data and behavior data of the supply chain participants, and allocates permissions based on the type data to generate the permission data of the supply chain participants; The reputation scoring module is used to build a three-dimensional permission model based on behavioral data and calculate the reputation scores of supply chain participants; The permission adjustment module is used to adjust the permission data based on the reputation score and use the blockchain to verify the permission of business operations and obtain the verification results; The adjustment and evaluation module is used to record the permission data, permission adjustment results and verification results on the blockchain, and evaluate the permission adjustment results to realize the blockchain-based mall supply chain management.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the blockchain-based mall supply chain management method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the blockchain-based mall supply chain management method described in any one of claims 1 to 7 are implemented.

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