CN119359201B - Supply chain tracking and managing method and system - Google Patents
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Abstract
The invention provides a supply chain tracking and managing method and system, which belong to the technical field of data processing, and specifically comprise the steps of determining the liveness types of different associated users according to shopping data of the different associated users on a shopping platform, determining the commodity association coefficient of a target commodity by combining the user association coefficients of the different associated users, determining the commodity loss data of the target commodity in the transportation process according to the supply chain data of the target commodity when the supply chain tracking and managing is not required to be carried out by adopting a preset strategy by utilizing the commodity matching coefficient of the target commodity, and determining the supply chain tracking and managing strategy of the target commodity according to the transportation data, the commodity loss data and the target commodity matching coefficient of the target commodity in the transportation process when the supply chain tracking and managing is not required to be carried out by adopting the preset strategy by utilizing the commodity loss data, so that the reliability of the supply chain tracking and managing is ensured.
Description
Technical Field
The invention belongs to the technical field of data management, and particularly relates to a supply chain tracking and managing method and system.
Background
In order to realize tracking and management processing of a supply chain, in the invention patent application CN202410247241.X, an LOA-LSTM model is adopted to predict the time required for cargo transportation and the occurrence probability of emergency, and real-time data monitoring and historical data are combined to analyze, so that the transportation efficiency of logistics and the reaction speed of the supply chain are improved, the influence of emergency and complex conditions on cargo transportation is reduced, but the following technical problems exist:
in the prior art, when the supply chain management is performed, as the sales data of different types of target commodities have larger deviation, when the supply chain problem occurs to the different types of target commodities, the probability of occurrence of shortage risk of related target commodities in the platform also has a certain degree of difference, so that if the supply chain tracking management strategy cannot be determined according to the shortage risk, the reliability of supply of the supply chain cannot be ensured.
The present invention provides a supply chain tracking and managing method and system for solving the above-mentioned problems.
Disclosure of Invention
In order to achieve the purpose of the invention, the invention adopts the following technical scheme:
According to one aspect of the present invention, a supply chain tracking and management method is provided.
A supply chain tracking and managing method specifically comprises:
S1, determining purchasing users of target commodities and associated commodities according to sales data of a shopping platform on the target commodities and the associated commodities, and determining associated users of the target commodities and user association coefficients of the associated users based on purchasing data and browsing data of the purchasing users on the target commodities and the associated commodities;
S2, determining the liveness types of different associated users according to shopping data of the different associated users on the shopping platform, determining commodity association coefficients of target commodities by combining the user association coefficients of the different associated users, and entering the next step when the commodity matching coefficients of the target commodities are used for determining that supply chain tracking and management do not need to be performed by adopting a preset strategy;
And S3, determining the goods loss data of the target goods in the transportation process according to the supply chain data of the target goods, and determining the supply chain tracking and management strategy of the target goods according to the transportation data and the goods loss data of the target goods in the transportation process and the target goods matching coefficient of the target goods when the goods loss data is used for determining that the supply chain tracking and management is not required to be performed by adopting a preset strategy.
The invention has the beneficial effects that:
1. The supply chain tracking and management method has the advantages that whether the supply chain tracking and management is needed to be carried out is determined by utilizing the commodity matching coefficient of the target commodity, so that the supply chain tracking and management strategy is determined from the perspective of historical shopping data of the target commodity on the shopping platform, the active condition of the associated users on the shopping platform is considered, the number of the associated users on the shopping platform is considered, and accidents such as shortage of the target commodity caused by insufficient reliability of the supply chain tracking and management are avoided.
2. The supply chain tracking and management strategy of the target commodity is determined according to the transportation data and the goods loss data of the target commodity in the transportation process and the target commodity matching coefficient of the target commodity, so that the technical problem that the goods loss of the target commodity due to the fact that the goods loss is serious in the transportation process is not met due to unreliable supply chain tracking and management is avoided, meanwhile, the unexpected situations that the number of related users of the target commodity on a shopping platform is different, the shortage of the target commodity is caused and the like are also considered, and the supply chain tracking and management strategy of the target commodity is determined from multiple angles.
The further technical scheme is that the related commodity is determined according to the target commodity type of the target commodity and the target customer group.
The further technical scheme is that the sales data is determined according to the analysis result of the historical sales record of the target commodity.
The further technical scheme is that the method for determining the associated user of the target commodity comprises the following steps:
determining the commodity with the purchasing times larger than the preset purchasing times according to the purchasing data of the purchasing user on the target commodity and the related commodity, and taking the commodity as a screening purchasing commodity;
determining commodities with browsing times greater than preset browsing times according to browsing data of the purchasing user on the target commodity and related commodities, and taking the commodities as screening browsing commodities;
And determining a user association coefficient of the purchasing user and the target commodity according to the quantity of the selected purchasing commodity and the selected browsing commodity, and determining whether the purchasing user is an associated user of the target commodity or not by utilizing the user association coefficient.
The further technical scheme is that the user association coefficient is determined according to the average value of the quantity ratio of the screening purchased goods in the associated goods and the quantity ratio of the screening browsed goods in the associated goods.
The further technical scheme is that the value range of the user association coefficient is between 0 and 1, wherein when the user association coefficient of the purchasing user is larger than a preset association coefficient, the purchasing user is determined to be the association user of the target commodity.
The further technical scheme is that the supply chain tracking and management strategy of the target commodity is determined based on the management demand coefficient, and specifically comprises the following steps:
And determining a supply chain tracking and management strategy of the target commodity by using a matching strategy corresponding to the demand coefficient interval based on the demand coefficient interval in which the management demand coefficient is positioned.
The further technical scheme is that the preset strategy is to set an internet of things monitoring device on the target commodity and the transport vehicle for supply chain tracking and management.
The supply chain tracking and management strategy of the target commodity comprises the steps of setting an internet of things monitoring device on the target commodity and the transport vehicle for supply chain tracking and management, setting the internet of things monitoring device on the transport vehicle for supply chain tracking and management, and setting the internet of things monitoring device for supply chain tracking and management.
In a second aspect, the present invention provides a computer system comprising a memory and a processor communicatively coupled, and a computer program stored on the memory and capable of running on the processor, the processor executing a supply chain tracking and management method as described above when running the computer program.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the invention as set forth hereinafter.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.
FIG. 1 is a flow chart of a supply chain tracking and management method;
FIG. 2 is a flow chart of a method of determining an associated user of a target commodity;
FIG. 3 is a flow chart of a method of determining an activity type of an associated user;
FIG. 4 is a flow chart of a method of determining target commodity correlation coefficients for a target commodity;
FIG. 5 is a block diagram of a computer system.
Detailed Description
In order to make the technical solutions in the present specification better understood by those skilled in the art, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present specification, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present disclosure.
When the supply chain management is performed, as the sales data of different types of target commodities on the designated platform are different from the sales data of the target commodities on the designated platform, the supply chain tracking and management strategy of the target commodities is determined according to the sales data, the transportation risk condition and the goods loss condition of the target commodities, so that the reliability of the supply chain management is ensured, and the cost of the supply chain management is reduced.
And the user association coefficient is that different commodity purchasing times and browsing times are carried out according to purchasing data and browsing data of the target commodity and the associated commodity of the purchasing user, commodities with purchasing times more than 3 times or browsing times more than 10 times are used as screening commodities, and the duty ratio of the screening commodities to the target commodity and the associated commodity is used as the user association coefficient.
And the related users are purchasing users with the user related coefficient more than 0.6.
Liveness type, namely determining liveness type of the associated user according to the purchase times of the associated user on the shopping platform, wherein the specific liveness type comprises an active user and a general user.
Commodity correlation coefficient of target commodity: and determining commodity association coefficients of the target commodity according to the products of the association coefficients of different liveness types and preset weight coefficients by using the weights of the user association coefficients of the associated users of different liveness types and determining the association coefficients of different liveness types, wherein the preset weight coefficient is 0.6,0.3.
And determining that the supply chain tracking and management do not need to be performed by using a preset strategy by using the commodity matching coefficient of the target commodity, wherein when the commodity correlation coefficient of the target commodity is smaller than 0.3, the supply chain tracking and management do not need to be performed by using the preset strategy, and when the commodity correlation coefficient of the target commodity is not smaller than 0.3, the supply chain tracking and management do not need to be performed by using the preset strategy.
And determining that the supply chain tracking and management do not need to be performed by adopting a preset strategy by utilizing the goods loss data, namely determining the average goods loss rate of the goods loss data of the target goods in the transportation process, and determining that the supply chain tracking and management do not need to be performed by adopting the preset strategy when the average goods loss rate is smaller than 0.05.
And determining a management demand coefficient of the target commodity according to the average goods loss rate, the ratio of the transportation mileage to the preset transportation mileage and the average value of target commodity matching coefficients of the target commodity, and determining the supply chain tracking and management strategy of the target commodity based on the management demand coefficient.
The supply chain tracking and management strategy of the target commodity comprises the steps of setting an internet of things monitoring device on the target commodity and the transport vehicle to track and manage the supply chain, and setting the internet of things monitoring device on the transport vehicle only to track and manage the supply chain without setting the internet of things monitoring device to track and manage the supply chain.
In order to solve the above problems, according to an aspect of the present invention, as shown in fig. 1, there is provided a supply chain tracking and management method, which specifically includes:
S1, determining purchasing users of target commodities and associated commodities according to sales data of a shopping platform on the target commodities and the associated commodities, and determining associated users of the target commodities and user association coefficients of the associated users based on purchasing data and browsing data of the purchasing users on the target commodities and the associated commodities;
S2, determining the liveness types of different associated users according to shopping data of the different associated users on the shopping platform, determining commodity association coefficients of target commodities by combining the user association coefficients of the different associated users, and entering the next step when the commodity matching coefficients of the target commodities are used for determining that supply chain tracking and management do not need to be performed by adopting a preset strategy;
And S3, determining the goods loss data of the target goods in the transportation process according to the supply chain data of the target goods, and determining the supply chain tracking and management strategy of the target goods according to the transportation data and the goods loss data of the target goods in the transportation process and the target goods matching coefficient of the target goods when the goods loss data is used for determining that the supply chain tracking and management is not required to be performed by adopting a preset strategy.
Further, the associated commodity is determined according to the target commodity type of the target commodity and the target customer group.
Specifically, the sales data is determined according to the analysis result of the historical sales record of the target commodity.
As shown in fig. 2, the method for determining the associated user of the target commodity includes:
determining the commodity with the purchasing times larger than the preset purchasing times according to the purchasing data of the purchasing user on the target commodity and the related commodity, and taking the commodity as a screening purchasing commodity;
determining commodities with browsing times greater than preset browsing times according to browsing data of the purchasing user on the target commodity and related commodities, and taking the commodities as screening browsing commodities;
And determining a user association coefficient of the purchasing user and the target commodity according to the quantity of the selected purchasing commodity and the selected browsing commodity, and determining whether the purchasing user is an associated user of the target commodity or not by utilizing the user association coefficient.
It can be appreciated that the user association coefficient is determined according to the average value of the number proportion of the screening purchased goods in the associated goods and the number proportion of the screening browsed goods in the associated goods.
Further, the value range of the user association coefficient is between 0 and 1, wherein when the user association coefficient of the purchasing user is larger than a preset association coefficient, the purchasing user is determined to be the associated user of the target commodity.
Optionally, the method for determining the associated user of the target commodity comprises the following steps:
Determining the total times of purchase of the target commodity and the related commodity by the purchasing user according to the purchasing data of the target commodity and the related commodity, and taking the total times of purchase of the target commodity and the related commodity as the total times of commodity purchase;
Determining the total browsing times of the purchasing user on the target commodity and the related commodity according to the browsing data of the purchasing user on the target commodity and the related commodity, and taking the total browsing times as the total browsing times of the commodity;
And determining the user association coefficient of the purchasing user and the target commodity according to the commodity purchasing total times and the commodity browsing total times, and determining whether the purchasing user is an associated user of the target commodity or not by utilizing the user association coefficient.
In another embodiment, the method for determining the associated user of the target commodity is as follows:
s11, determining the total times of purchase of the target commodity and the related commodity by the purchasing user according to the purchase data of the target commodity and the related commodity by the purchasing user, determining the total times of browsing of the target commodity and the related commodity by the purchasing user according to the browsing data of the target commodity and the related commodity by the purchasing user, and determining a basic related coefficient according to the total times of purchase and the total browsing times;
optionally, the step S11 includes the following:
S111, determining the total times of purchase of the target commodity and the related commodity by the purchasing user according to the purchase data of the target commodity and the related commodity, determining that the purchasing user does not belong to the related user of the target commodity when the total times of purchase are smaller than a preset purchase time threshold, and turning to step S112 when the total times of purchase are not smaller than the preset purchase time threshold;
S112, when the total times of the purchase of the target commodity and the related commodity by the purchasing user are within a preset purchase time interval, turning to step S113, and when the total times of the purchase of the target commodity and the related commodity by the purchasing user are not within the preset purchase time interval, turning to step S114;
S113, determining the total browsing times of the purchasing user in the target commodity and the related commodity according to the browsing data of the purchasing user in the target commodity and the related commodity, determining that the purchasing user does not belong to the related user of the target commodity when the total browsing times are in a preset browsing time interval, and switching to the step S114 when the total browsing times are not in the preset browsing time interval;
s114, determining basic association coefficients according to the total purchase times and the total browsing times, and turning to step S12.
S12, determining browsing times of different commodities according to browsing data of the purchasing user on the target commodity and related commodities, and determining commodity association coefficients of different commodities according to the purchasing times of different commodities;
Optionally, the step S12 includes the following:
s121, when the basic association coefficient is smaller than a preset association coefficient threshold value, turning to step S122, and when the basic association coefficient is not smaller than the preset association coefficient threshold value, turning to step S124;
S122, when the purchasing user determines that the commodity with the purchasing frequency larger than the preset purchasing frequency does not exist according to the purchasing frequency of different commodities, the step S123 is carried out, and when the commodity with the purchasing frequency larger than the preset purchasing frequency exists, the step S124 is carried out;
s123, determining browsing times of different commodities according to browsing data of the purchasing user on the target commodity and related commodities, determining that the purchasing user does not belong to the related user of the target commodity when no commodity with browsing times larger than a preset browsing times exists, and switching to step S124 when commodity with browsing times not larger than the preset browsing times exists;
s124, determining commodity association coefficients of different commodities according to browsing times and purchasing times of the different commodities, determining that the purchasing user does not belong to the associated user of the target commodity when the commodities with the commodity association coefficients larger than the preset commodity coefficient threshold value do not exist, and switching to the step S13 when the commodities with the commodity association coefficients larger than the preset commodity coefficient threshold value exist.
S13, determining user association coefficients of the purchasing user and the target commodity according to commodity association coefficients of different commodities and basic association coefficients, and determining whether the purchasing user is an associated user of the target commodity or not by utilizing the user association coefficients.
It should be noted that, as shown in fig. 3, the method for determining the activity type of the associated user is as follows:
Determining the purchase times of the associated user on the shopping platform according to the shopping data of the associated user on the shopping platform;
and determining the liveness type of the associated user according to the purchase times of the associated user on the shopping platform.
Further, determining the activity type of the associated user according to the purchase times of the associated user on the shopping platform specifically includes:
And determining a preset liveness type corresponding to the purchase times through the purchase times of the shopping platform, and determining the liveness type of the associated user by utilizing the preset liveness type.
It may be understood that, as shown in fig. 4, the method for determining the target commodity correlation coefficient of the target commodity is as follows:
determining the liveness weight coefficients of different associated users according to liveness types of the different associated users;
determining correction association coefficients of different associated users according to the liveness weight coefficients of the different associated users and the commodity association coefficients;
and determining the target commodity correlation coefficient of the target commodity through the sum of the corrected correlation coefficients of different correlation users.
Further, the target commodity association coefficient of the target commodity has a value ranging from 0 to 1, and when the target commodity association coefficient of the target commodity is greater than a preset association threshold, it is determined that the supply chain tracking and management needs to be performed by adopting a preset strategy.
Optionally, the method for determining the target commodity association coefficient of the target commodity comprises the following steps:
Determining the number of the associated users in different liveness types according to the liveness types of the different associated users, and presetting the number of the associated users in the liveness types by using the number of the associated users in the different liveness types;
Determining the sum of association coefficients of the preset liveness type according to the number of associated users in the preset liveness type and commodity association coefficients of different associated users, and taking the sum as the association coefficient weight sum;
And determining the target commodity correlation coefficient of the target commodity through the correlation coefficient weight.
In another embodiment, the method for determining the target commodity correlation coefficient of the target commodity is as follows:
S21, acquiring commodity association coefficients of different associated users, and determining the number of the associated users in different activity types according to the activity types of the different associated users;
Optionally, the step S21 includes the following:
S211, acquiring the number of associated users of the target commodity, determining that the target commodity needs to be subjected to supply chain tracking and management by adopting a preset strategy when the number of associated users of the target commodity is larger than the preset number of associated users, and switching to step S212 when the number of associated users of the target commodity is not larger than the preset number of associated users;
S212, determining the associated users with the commodity association coefficients larger than a preset commodity association coefficient threshold value as screening associated users according to commodity association coefficients of different associated users, determining that the target commodity needs to be subjected to supply chain tracking and management by adopting a preset strategy when the number of the screening associated users does not meet the requirement, and switching to step S213 when the number of the screening associated users meets the requirement;
S213, determining the number of the associated users in different liveness types according to the liveness types of the different associated users, when the number of the associated users in the preset liveness type is larger than a preset user number threshold, determining that the target commodity needs to be subjected to supply chain tracking and management by adopting a preset strategy, and when the number of the associated users in the preset liveness type is not larger than the preset user number threshold, turning to step S22.
S22, determining comprehensive association coefficients of different liveness types according to the number of associated users in the different liveness types and the association coefficients, and determining preset liveness coefficients of the different liveness types;
optionally, the step S22 includes the following:
S221, determining comprehensive association coefficients of different liveness types according to the number of associated users in the different liveness types and the association coefficients, determining that the target commodity needs to be subjected to supply chain tracking and management by adopting a preset strategy when the comprehensive association coefficient of the preset liveness type is larger than a preset comprehensive coefficient threshold value, and switching to step S222 when the comprehensive association coefficient of the preset liveness type is larger than the preset comprehensive coefficient threshold value;
S222, determining preset liveness coefficients of different liveness types, determining correction association coefficients of different liveness types by combining comprehensive association coefficients of different liveness types, when the liveness types with the correction association coefficients being larger than the preset correction coefficients exist, turning to step S223, and when the liveness types with the correction association coefficients being larger than the preset correction coefficients do not exist, turning to step S23;
S223, when the number of the liveness types of which the correction association coefficient is larger than the preset correction coefficient is larger than the preset number of types, determining that the target commodity needs to be tracked and managed by adopting a preset strategy, and when the number of the liveness types of which the correction association coefficient is larger than the preset correction coefficient is not larger than the preset number of types, turning to S23.
S23, determining target commodity association coefficients of the target commodity according to the comprehensive association coefficients of different liveness types and preset liveness coefficients.
The goods loss data of the target goods in the transportation process comprise goods loss rate and goods loss quantity in different transportation times.
Further, the determining, by using the cargo loss data, that the supply chain tracking and management do not need to be performed by using a preset strategy specifically includes:
Determining the cargo loss rate in different transportation times according to the analysis result of the cargo loss data;
carrying out the transportation times with the goods loss rate larger than the preset goods loss rate by using the goods loss rate, and taking the transportation times as the goods loss transportation times;
and determining whether a preset strategy is needed to be adopted for tracking and managing the supply chain according to the number of the cargo loss transportation times.
It can be appreciated that when the number of damaged shipments is greater than a predetermined number of shipments threshold, then determining that the target commodity requires supply chain tracking and management using a predetermined strategy.
Specifically, the method for determining the supply chain tracking and management strategy of the target commodity comprises the following steps:
determining the transportation mileage of the target commodity by adopting different types of transportation modes according to the transportation data of the target commodity in the transportation process, and determining the transportation risk coefficient of the target commodity according to the transportation mileage of the different types of transportation modes;
Determining the average goods loss rate of the target goods based on the goods loss data of the target goods in the transportation process;
and determining a management demand coefficient of the target commodity according to the average commodity loss rate, the transportation risk coefficient and the target commodity matching coefficient, and determining a supply chain tracking and management strategy of the target commodity based on the management demand coefficient.
Further, determining a supply chain tracking and management strategy of the target commodity based on the management demand coefficient specifically includes:
And determining a supply chain tracking and management strategy of the target commodity by using a matching strategy corresponding to the demand coefficient interval based on the demand coefficient interval in which the management demand coefficient is positioned.
It should be noted that, the preset strategy is to set an internet of things monitoring device on the target commodity and the transport vehicle to track and manage a supply chain.
It can be understood that the supply chain tracking and management strategy of the target commodity includes setting the internet of things monitoring device on the target commodity and the transport vehicle to perform supply chain tracking and management, setting the internet of things monitoring device on the transport vehicle only to perform supply chain tracking and management, and not setting the internet of things monitoring device to perform supply chain tracking and management.
In a second aspect of embodiment 2, as shown in FIG. 5, the present invention provides a computer system comprising a memory and a processor communicatively coupled, and a computer program stored on the memory and capable of running on the processor, the processor executing a supply chain tracking and management method as described above when the computer program is run.
In another embodiment, the determining that the supply chain tracking and management does not need to be performed by adopting a preset strategy by using the cargo loss data specifically includes:
determining the cargo loss rate in different transportation times according to the analysis result of the cargo loss data, determining the average value of the cargo loss rates of different transportation times according to the cargo loss rate in different transportation times, and determining that a preset strategy is required to be adopted for tracking and management of a supply chain when the average value of the cargo loss rates of different transportation times does not meet the requirement;
When the average value of the cargo loss rates of different transportation times meets the requirement:
When the transportation times with the goods loss rate larger than the preset goods loss rate do not exist, determining that a preset strategy is not needed for tracking and managing the supply chain;
when the transportation times with the goods loss rate being larger than the preset goods loss rate exist:
Carrying out the transportation times with the goods loss rate larger than the preset goods loss rate by using the goods loss rate, taking the goods loss rate as the transportation times of the goods loss, and determining that a preset strategy is required for tracking and managing the supply chain when the transportation times of the goods loss do not meet the requirement;
When the number of the cargo damage transportation times meets the requirement:
determining the cargo loss coefficients of different transportation times according to the cargo loss rate and the cargo loss amount of different transportation times, and determining that a preset strategy is needed for tracking and managing the supply chain when the average value of the cargo loss coefficients of different transportation times does not meet the requirement;
when the average value of the cargo loss coefficients of different transportation times meets the requirement:
determining the number of serious goods loss transportation times by the goods loss coefficients of different transportation times, and determining that a preset strategy is required for tracking and managing the supply chain when the number of the serious goods loss transportation times does not meet the requirement;
when the number of serious goods loss transportation times meets the requirement:
And determining comprehensive goods loss coefficients according to the goods loss coefficients of different transportation times, and determining whether a preset strategy is needed to be adopted for tracking and managing the supply chain by utilizing the comprehensive goods loss coefficients.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus, devices, non-volatile computer storage medium embodiments, the description is relatively simple, as it is substantially similar to method embodiments, with reference to the section of the method embodiments being relevant.
The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The foregoing is merely one or more embodiments of the present description and is not intended to limit the present description. Various modifications and alterations to one or more embodiments of this description will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, or the like, which is within the spirit and principles of one or more embodiments of the present description, is intended to be included within the scope of the claims of the present description.
Claims (10)
1. A supply chain tracking and management method, comprising:
Determining purchasing users of target commodities and associated commodities according to sales data of a shopping platform on the target commodities and associated commodities, and determining associated users of the target commodities and user association coefficients of the associated users based on the purchasing data and browsing data of the purchasing users on the target commodities and the associated commodities;
Determining the liveness types of different associated users according to shopping data of the different associated users on the shopping platform, determining commodity association coefficients of target commodities by combining the user association coefficients of the different associated users, and entering the next step when the commodity association coefficients of the target commodities are used for determining that supply chain tracking and management do not need to be performed by adopting a preset strategy;
Determining goods loss data of the target goods in the transportation process according to the supply chain data of the target goods, and determining a supply chain tracking and management strategy of the target goods according to the transportation data of the target goods in the transportation process, the goods loss data and the goods association coefficient of the target goods when the goods loss data is used for determining that the supply chain tracking and management is not required to be performed by adopting a preset strategy;
the purchasing user with the user association coefficient larger than the preset threshold value is the associated user;
When the commodity correlation coefficient of the target commodity is smaller than the set threshold, determining that the supply chain tracking and management do not need to be performed by adopting a preset strategy, and when the commodity correlation coefficient of the target commodity is not smaller than the set threshold, determining that the supply chain tracking and management do not need to be performed by adopting the preset strategy;
determining the commodity with the purchasing times larger than the preset purchasing times according to the purchasing data of the purchasing user on the target commodity and the related commodity, and taking the commodity as a screening purchasing commodity;
determining commodities with browsing times greater than preset browsing times according to browsing data of the purchasing user on the target commodity and related commodities, and taking the commodities as screening browsing commodities;
The user association coefficient is determined according to the average value of the quantity proportion of the screening purchased goods in the associated goods and the quantity proportion of the screening browsed goods in the associated goods;
the method for determining the supply chain tracking and management strategy of the target commodity comprises the following steps:
determining the transportation mileage of the target commodity by adopting different types of transportation modes according to the transportation data of the target commodity in the transportation process, and determining the transportation risk coefficient of the target commodity according to the transportation mileage of the different types of transportation modes;
Determining the average goods loss rate of the target goods based on the goods loss data of the target goods in the transportation process;
Determining a management demand coefficient of the target commodity according to the average commodity loss rate, the transportation risk coefficient and the commodity correlation coefficient, and determining a supply chain tracking and management strategy of the target commodity based on the management demand coefficient;
The supply chain tracking and management strategy of the target commodity comprises the steps of setting an internet of things monitoring device on the target commodity and a transport vehicle to track and manage the supply chain, and setting the internet of things monitoring device on the transport vehicle only to track and manage the supply chain without setting the internet of things monitoring device to track and manage the supply chain.
2. The supply chain tracking and management method of claim 1, wherein the associated commodity is determined based on a target commodity type of the target commodity and a target customer group.
3. The supply chain tracking and management method of claim 1, wherein the sales data is determined based on analysis results of historical sales records of the target commodity.
4. The supply chain tracking and management method of claim 1, wherein the method of determining the associated user of the target commodity is:
determining the commodity with the purchasing times larger than the preset purchasing times according to the purchasing data of the purchasing user on the target commodity and the related commodity, and taking the commodity as a screening purchasing commodity;
determining commodities with browsing times greater than preset browsing times according to browsing data of the purchasing user on the target commodity and related commodities, and taking the commodities as screening browsing commodities;
And determining the user association coefficient of the purchasing user and the target commodity according to the quantity of the selected purchasing commodity and the selected browsing commodity, and determining whether the purchasing user is an associated user of the target commodity or not by utilizing the user association coefficient.
5. The supply chain tracking and management method of claim 4, wherein the user association coefficient is determined based on an average of a quantity ratio of the selected purchased goods in the associated goods and a quantity ratio of the selected browsed goods in the associated goods.
6. The supply chain tracking and management method of claim 1, wherein the user association coefficient has a value ranging from 0 to 1, and wherein when the user association coefficient of the purchasing user is greater than a preset association coefficient, the purchasing user is determined to be an associated user of the target commodity.
7. The supply chain tracking and management method of claim 1, wherein the loss data of the target commodity during transportation includes loss rates and loss amounts in different transportation times.
8. The supply chain tracking and management method of claim 1, wherein the determining using the loss data does not require a predetermined strategy for supply chain tracking and management, comprises:
Determining the cargo loss rate in different transportation times according to the analysis result of the cargo loss data;
carrying out the transportation times with the goods loss rate larger than the preset goods loss rate by using the goods loss rate, and taking the transportation times as the goods loss transportation times;
and determining whether a preset strategy is needed to be adopted for tracking and managing the supply chain according to the number of the cargo loss transportation times.
9. The supply chain tracking and management method according to claim 1, wherein the predetermined strategy is to set an internet of things monitoring device on the target commodity and the transportation vehicle for supply chain tracking and management.
10. A computer system comprising a memory and a processor in communication, and a computer program stored on the memory and capable of running on the processor, wherein the processor executes a supply chain tracking and management method according to any one of claims 1-9 when running the computer program.
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