CN110298726B - Commodity information updating method and system for e-commerce platform and storage medium - Google Patents

Commodity information updating method and system for e-commerce platform and storage medium Download PDF

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CN110298726B
CN110298726B CN201910451800.8A CN201910451800A CN110298726B CN 110298726 B CN110298726 B CN 110298726B CN 201910451800 A CN201910451800 A CN 201910451800A CN 110298726 B CN110298726 B CN 110298726B
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何建民
张苗苗
张红
贾艳
吴琦超
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Hefei University of Technology
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Abstract

The embodiment of the invention provides a commodity information updating method for an e-commerce platform, and belongs to the technical field of platform management of e-commerce. The commodity information updating method comprises the following steps: determining an online sales linear model and an offline sales linear model of the commodity; determining a profit function according to the online sales linear model and the offline sales linear model; determining the optimal wholesale price, the online sale price and the offline sale price of the commodity according to the income function based on the Stainberg game theory; and updating the commodity information according to the calculated optimal wholesale price, the online sale price and the offline sale price. The commodity information updating method, system and storage medium can update commodity information in real time based on data in a database.

Description

Commodity information updating method and system for e-commerce platform and storage medium
Technical Field
The invention relates to the technical field of platform management of electronic commerce, in particular to a commodity information updating method, a commodity information updating system and a storage medium for an e-commerce platform.
Background
The popularization of the internet and the development of electronic commerce change the consumption mode of consumers and the sales mode of products, and a mixed sales mode with the coexistence of an online mode and an offline mode becomes a development trend of enterprises. In this case, how to determine the market retail price and wholesale price for maximizing the profit among the product transaction parties becomes a key issue for achieving online and offline transactions. Meanwhile, due to uncertainty of consumer behaviors and market demands, decisions of all members can be influenced.
The current common pricing methods mainly comprise:
the method comprises the steps that firstly, through analyzing a value law decision theory and a supply and demand law decision theory of a product, a demand, supply and value are used as influence factors of price, the relation of the demand, the supply and the value can obey a multiplication principle, and a pricing method comprises a cost-oriented pricing method, a demand-oriented pricing method and a competition-oriented pricing method;
secondly, on the premise of the market random demand of the product, the influence factors of the time, the quantity and the quality of the product are considered, a production plan is made, the production capacity is determined, and the price of the product is predicted by designing a solving algorithm.
And thirdly, constructing different decision objective functions according to different product demands of the lead-in period, the growth period, the maturity period and the attenuator based on the life cycle of the product, analyzing the supply chain pricing strategies in different periods, and giving the optimal retail price, wholesale price and operation efficiency of a decision maker.
With the development of internet and e-commerce technology, the barrier of asymmetric product information is weakened continuously, the phenomenon of coexistence of offline distribution and online direct sale is increased day by day, the method researches the pricing of products from different perspectives, and the influence of time and consumer effectiveness on production and retail price decision under the e-commerce environment is not comprehensively considered.
Disclosure of Invention
The invention aims to provide a commodity information updating method, a commodity information updating system and a storage medium for an e-commerce platform.
In order to achieve the above object, an embodiment of the present invention provides a commodity information updating method for an e-commerce platform, including:
determining an online sales linear model and an offline sales linear model of the goods;
determining a profit function according to the online sales linear model and the offline sales linear model;
determining the optimal wholesale price, the online sale price and the offline sale price of the commodity according to the income function based on the Stainberg game theory;
and updating the commodity information according to the calculated optimal wholesale price, the online sale price and the offline sale price.
Optionally, the goods information updating method further includes:
randomly selecting an unselected commodity from a database of the e-commerce platform;
judging whether the unselected commodities exist in the database or not;
under the condition that the unselected commodities exist in the database, randomly selecting an unselected commodity from the database of the E-commerce platform again;
and under the condition that the unselected commodities do not exist in the database, ending the commodity information updating method.
Optionally, the determining the online sales linear model and the offline sales linear model of the goods comprises:
determining a quality decay function θ (t) of the commodity with respect to time using equation (1):
Figure GDA0003567466660000021
and T is the life cycle of the commodity, T is the transportation time of the commodity, and eta is the sensitivity coefficient of the commodity to time.
Optionally, the determining the online sales linear model and the offline sales linear model of the goods comprises:
determining the time-varying utility d of the consumer for purchasing the commodity through the online path and the offline path according to the formula (2) and the formula (3) respectively1(p,t)、d2(p,t)，
d1(p,t)＝λa-p1+αp2+βθ(t)，(2)
d2(p,t)＝(1-λ)a-p2+αp1+βθ(t)，(3)
Wherein λ is the market share occupied by the sales through the offline route of the commodity, a is the market size of the commodity, α is the cross-price elastic coefficient of online and offline sales, β is the sensitivity coefficient of the consumer to the mass attenuation function, p1、p2Respectively the current off-line and on-line selling prices of said goods.
Optionally, the determining the online sales linear model and the offline sales linear model of the goods comprises:
determining the on-line sales linear model and the off-line sales linear model according to formula (4) and formula (5) based on a consumer utility theory,
Figure GDA0003567466660000031
Figure GDA0003567466660000032
wherein q is1For said on-line sales linear model, q2And mu is a market potential size of the commodity at any moment in time, which is a linear model of the offline sales volume.
Optionally, the determining a revenue function according to the online sales linear model and the offline sales linear model includes:
determining a revenue function pi for the manufacturer of the good according to equation (6)m(pi,ω)，
πm(pi,ω)＝(p2-c0)q2+(ω-c0)q1，(6)
Where ω is the current wholesale price at which the manufacturer sells the product to the retailer, c0The unit production cost for the manufacturer;
determining a revenue function pi for the retailer of the good according to equation (7)r(pi,ω)，
πr(pi,ω)＝(p1-ω)q1，(7)
Wherein p is1>ω。
Optionally, the determining the optimal wholesale price and the on-line sale price of the commodity according to the revenue function includes:
determining a reaction function p for the retailer's off-line price using equation (8)1(p2,ω)，
Figure GDA0003567466660000041
Determining a wholesale price omega and an online sale price p for the manufacturer to sell the commodity to the retailer using equation (9)2，
Figure GDA0003567466660000042
Figure GDA0003567466660000043
Wherein, the formula (9) and the formula (10) satisfy the hessian matrix negative definite.
Optionally, the determining the optimal wholesale price and the on-line sale price of the commodity according to the revenue function includes:
determining the optimal wholesale price omega according to formula (11)*Selling price p on line1 *Off-line selling price p2 *，
Figure GDA0003567466660000044
Figure GDA0003567466660000045
Figure GDA0003567466660000046
In another aspect, the present invention further provides a merchandise information updating system for an e-commerce platform, where the merchandise information updating system includes a processor configured to execute any one of the above merchandise information updating methods.
Yet another aspect of the present invention further provides a storage medium storing instructions for being read by a machine to cause the machine to execute any one of the above-mentioned goods information updating methods.
Through the technical scheme, the commodity information updating method, the commodity information updating system and the storage medium for the e-commerce platform provided by the invention calculate the price of each commodity in the e-commerce platform in real time based on the database pre-stored in the server, so that the commodity information is updated, and the automatic updating of the commodity information of the e-commerce platform is realized without considering operation.
Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.
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The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the embodiments of the invention and do not limit the embodiments. In the drawings:
fig. 1 is a flowchart of a goods information updating method for an e-commerce platform according to an embodiment of the present invention;
fig. 2 is a flowchart of a goods information updating method for an e-commerce platform according to an embodiment of the present invention.
Detailed Description
The following describes embodiments of the present invention in detail with reference to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration and explanation only, not limitation.
In the embodiments of the present invention, unless otherwise specified, the use of directional terms such as "upper, lower, top, and bottom" is generally used with respect to the orientation shown in the drawings or the positional relationship of the components with respect to each other in the vertical, or gravitational direction.
In addition, if there is a description of "first", "second", etc. in the embodiments of the present invention, the description of "first", "second", etc. is for descriptive purposes only and is not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between the respective embodiments may be combined with each other, but it is necessary to be based on the realization of the technical solutions by those skilled in the art, and when the technical solutions are contradictory to each other or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present invention.
Fig. 1 is a flowchart illustrating a commodity information updating method for an e-commerce platform according to an embodiment of the present invention. In fig. 1, the goods information updating method may include:
in step S20, an online sales linear model and an offline sales linear model of the goods are determined.
Specifically, the step S20 may include:
1. due to the realizable nature of the good, its quality tends to be inversely related to time. Then, the quality decay function θ (t) of the good with respect to time can be determined using equation (1):
Figure GDA0003567466660000061
wherein T is the life cycle of the commodity, T is the transportation time of the commodity, and eta is the sensitivity coefficient of the commodity to time. Further, since the quality of an arbitrary commodity gradually decreases with time in the production cycle of the commodity, there is a negative correlation between the two. Based on the negative correlation, the quality of the product gradually decreases from 1, and therefore, the quality number decay function θ (t) has a characteristic of 0< θ (t) < 1.
2. Determining the time-varying utility d of the consumer purchasing the commodity through the online path and the offline path according to the formula (2) and the formula (3) respectively1(p,t)、d2(p,t)，
d1(p,t)＝λa-p1+αp2+βθ(t)，(2)
d2(p,t)＝(1-λ)a-p2+αp1+βθ(t)，(3)
Wherein, lambda is the market share occupied by the sale amount through the offline way of the commodity, a is the market scale of the commodity, alpha is the cross price elastic coefficient of the online sale and the offline sale, beta is the sensitive coefficient of the consumer to the quality attenuation function, and p1、p2Respectively, the current offline and online sales prices for the goods. In this embodiment, since there are problems such as double marginalization and channel conflict between the online sales mode and the offline sales mode, the time-varying usage is affected by the channel price, the channel cross price, and the time.
3. Determining an online sales linear model and an offline sales linear model according to formula (4) and formula (5) based on a consumer utility theory,
Figure GDA0003567466660000071
Figure GDA0003567466660000072
wherein q is1For an online sales linear model, q2And mu is a linear model of the offline sales volume, and is the market potential size of the commodity at any moment. In this embodiment, taking the functions of the time-varying utility shown in the formula (2) and the formula (3) as examples, the time-varying utility d of the commodity is obtained at any time ti(p, t) is greater than 0 before the consumer chooses to purchase. Thus, the consumer's purchase probability P (d)1(p,t)>0)，P(d2(p,t)>0). Accordingly, during the life cycle of a commodity, its online sales linear model q1And offline sales linear model q2The following conditions need to be met to ensure that the purchase is of practical significance,
q1＝μP[(λa-p1+αp2+βθ(t))>0]，
q2＝μP[((1-λ)a-p2+αp1+βθ(t))>0]。
in step S30, a revenue function is determined from the online sales linear model and the offline sales linear model. In this embodiment, the manufacturer opens up both online and offline sales modes under conditions and technologies, i.e., the product can be sold to the retailer online and can be sold directly to the consumer via online sales. Thus, the revenue function π for the manufacturer of the good may be determined according to equation (6)m(pi,ω)，
πm(pi,ω)＝(p2-c0)q2+(ω-c0)q1，(6)
Where ω is the wholesale price of the product sold to the retailer by the current manufacturer, c0Is the unit production cost of the manufacturer;
determining a retailer's revenue function pi for a commodity according to equation (7)r(pi,ω)，
πr(pi,ω)＝(p1-ω)q1，(7)
Wherein, since in p1<In the case of omega, the number of,indicating that the actual price sold by the retailer via the offline route is higher than the wholesale price itself purchased from the producer, which obviously may not constitute a transaction. Thus, p1>ω。
In step S40, based on the steinberg game theory, the optimal wholesale price, online sale price and offline sale price of the merchandise are determined according to the profit function. Since in the steinberg theory, the manufacturer needs to first determine the wholesale price and the online sale price for the retailer's reaction function before the goods enter the market, the retailer will accordingly determine the actual offline sale price according to the manufacturer's wholesale price. Therefore, in this embodiment, the step S40 may include:
1. determining a reaction function p for an offline price of a retailer using equation (8)1(p2,ω)，
Figure GDA0003567466660000081
2. Determining a wholesale price omega and an online sale price p for the manufacturer to sell the goods to the retailer using equation (9)2，
Figure GDA0003567466660000082
Figure GDA0003567466660000083
Wherein, the formula (9) and the formula (10) satisfy the hessian matrix negative definite. PimWith respect to p2And Hessian Matrix of ω (Hessian Matrix):
Figure GDA0003567466660000091
the hessian matrix negative definite can also be expressed as | H |1|>0, thereby ensuring scientific reasonability of the price;
3. determining an optimal wholesale price omega according to formula (11)*Selling price p on line1 *Selling price p under line2 *，
Figure GDA0003567466660000092
Figure GDA0003567466660000093
Figure GDA0003567466660000094
In step S50, the goods information is updated according to the calculated optimal wholesale price, online sales price, and offline sales price.
Fig. 2 is a flowchart illustrating a method for updating commodity information for an e-commerce platform according to an embodiment of the present invention. The difference from the product information updating method shown in fig. 1 is that the product information updating method shown in fig. 2 further includes:
in step S10, randomly selecting an unselected product from the database of the e-commerce platform;
in step S60, it is determined whether or not an unselected product exists in the database;
under the condition that the unselected commodity exists in the database, randomly selecting an unselected commodity from the database of the E-commerce platform again;
and under the condition that the commodity which is not selected does not exist in the judgment database, ending the commodity information updating method.
Another aspect of the present invention also provides a goods information updating system for an e-commerce platform, which may include a processor, and the processor may be configured to perform any one of the above goods information updating methods. For the processor, a general purpose processor, a special purpose processor, a conventional processor, a Digital Signal Processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) circuits, any other type of Integrated Circuit (IC), a state machine, a system on a chip (SOC), and the like may be included, without limitation.
Yet another aspect of the present invention also provides a storage medium that may store instructions that may be used to be read by a machine to cause the machine to perform any one of the above-described merchandise information updating methods.
Through the technical scheme, the commodity information updating method, the commodity information updating system and the storage medium for the E-commerce platform provided by the invention calculate the price of each commodity in the E-commerce platform in real time based on the database pre-stored in the server, so that the commodity information is updated, and the automatic updating of the commodity information of the E-commerce platform is realized under the condition that the E-commerce platform does not need to think of operation.
Although the embodiments of the present invention have been described in detail with reference to the accompanying drawings, the embodiments of the present invention are not limited to the details of the above embodiments, and various simple modifications can be made to the technical solution of the embodiments of the present invention within the technical idea of the embodiments of the present invention, and the simple modifications all belong to the protection scope of the embodiments of the present invention.
It should be noted that the various features described in the above embodiments may be combined in any suitable manner without departing from the scope of the invention. In order to avoid unnecessary repetition, the embodiments of the present invention will not be described separately for the various possible combinations.
Those skilled in the art can understand that all or part of the steps in the method for implementing the above embodiments may be implemented by a program to instruct related hardware, where the program is stored in a storage medium and includes several instructions to enable a (may be a single chip, a chip, etc.) or a processor (processor) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk, and various media capable of storing program codes.
In addition, various different embodiments of the present invention may be arbitrarily combined with each other, and the embodiments of the present invention should be considered as disclosed in the disclosure of the embodiments of the present invention as long as the embodiments do not depart from the spirit of the embodiments of the present invention.

Claims (6)

1. A commodity information updating method for an E-commerce platform is characterized by comprising the following steps:
determining an online sales linear model and an offline sales linear model of the commodity;
determining a profit function according to the online sales linear model and the offline sales linear model;
based on the Steinberg game theory, determining the optimal wholesale price, the online sale price and the offline sale price of the commodity according to the income function;
updating the commodity information according to the calculated optimal wholesale price, the online sale price and the offline sale price;
the commodity information updating method further includes:
randomly selecting an unselected commodity from a database of the e-commerce platform;
judging whether the unselected commodities exist in the database or not;
under the condition that the unselected commodities exist in the database, randomly selecting an unselected commodity from the database of the E-commerce platform again;
under the condition that the unselected commodities do not exist in the database, ending the commodity information updating method;
the linear model for determining the online sales volume and the offline sales volume of the goods comprises the following steps:
determining a quality decay function θ (t) of the commodity with respect to time using equation (1):
Figure FDA0003567466650000011
wherein T is the life cycle of the commodity, T is the transportation time of the commodity, and eta is the sensitivity coefficient of the commodity to time;
the linear model for determining the online sales and the offline sales of the goods comprises:
determining the time-varying utility d of the consumer for purchasing the commodity through the online path and the offline path according to the formula (2) and the formula (3) respectively1(p,t)、d2(p,t)，
d1(p,t)＝λa-p1+αp2+βθ(t)， (2)
d2(p,t)＝(1-λ)a-p2+αp1+βθ(t)， (3)
Wherein λ is the market share occupied by the sales through the offline route of the commodity, a is the market size of the commodity, α is the cross-price elastic coefficient of online and offline sales, β is the sensitivity coefficient of the consumer to the mass attenuation function, p1、p2Respectively the current offline and online selling prices of the commodity;
the linear model for determining the online sales and the offline sales of the goods comprises:
determining the online sales linear model and the offline sales linear model according to formula (4) and formula (5) based on a consumer utility theory,
Figure FDA0003567466650000021
Figure FDA0003567466650000022
wherein q is1For said on-line sales linear model, q2And mu is a market potential size of the commodity at any moment in time, which is a linear model of the offline sales volume.
2. The merchandise information updating method of claim 1, wherein determining the revenue function from the online sales linear model and the offline sales linear model comprises:
determining a revenue function pi for the manufacturer of the good according to equation (6)m(pi,ω)，
πm(pi,ω)＝(p2-c0)q2+(ω-c0)q1， (6)
Where ω is the current wholesale price at which the manufacturer sells the product to the retailer, c0The unit production cost for the manufacturer;
determining a revenue function π for said retailer of said good according to equation (7)r(pi,ω)，
πr(pi,ω)＝(p1-ω)q1， (7)
Wherein p is1>ω。
3. The merchandise information updating method of claim 2, wherein the determining the optimal wholesale price and the on-line sale price of the merchandise according to the revenue function comprises:
determining a reaction function p for the retailer's off-line price using equation (8)1(p2,ω)，
Figure FDA0003567466650000031
Determining a wholesale price omega and an online sale price p for the manufacturer to sell the commodity to the retailer using equation (9)2，
Figure FDA0003567466650000032
Figure FDA0003567466650000033
Wherein, the formula (9) and the formula (10) satisfy the hessian matrix negative definite.
4. The merchandise information updating method of claim 3, wherein the determining the optimal wholesale price and the on-line sale price of the merchandise according to the revenue function comprises:
determining the optimal wholesale price omega according to formulas (11) to (13)*Selling price p on line1 *Selling price p under line2 *，
Figure FDA0003567466650000034
Figure FDA0003567466650000035
Figure FDA0003567466650000036
5. A merchandise information updating system for an e-commerce platform, the merchandise information updating system comprising a processor configured to perform the merchandise information updating method of any one of claims 1 to 4.
6. A storage medium storing instructions to be read by a machine to cause the machine to execute the merchandise information updating method according to any one of claims 1 to 4.
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