CN114004656A - Method and device for determining product consumption mode, electronic equipment and storage medium - Google Patents

Method and device for determining product consumption mode, electronic equipment and storage medium Download PDF

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CN114004656A
CN114004656A CN202111302914.XA CN202111302914A CN114004656A CN 114004656 A CN114004656 A CN 114004656A CN 202111302914 A CN202111302914 A CN 202111302914A CN 114004656 A CN114004656 A CN 114004656A
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product
mode
consumption
rental
pattern
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张鑫
余玉刚
郭晓龙
余伟图
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University of Science and Technology of China USTC
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Abstract

The embodiment of the disclosure provides a method and a device for determining a product consumption mode. The method comprises the following steps: in response to the consumption pattern determination request, obtaining historical data for each consumption pattern of a plurality of consumption patterns corresponding to the first product, wherein the historical data comprises the number of consumers and the usage amount; establishing a product utility function corresponding to the consumption mode according to the historical data of each consumption mode in a plurality of consumption modes corresponding to the first product; generating consumption information of a second product corresponding to the consumption mode according to the product utility function corresponding to the consumption mode, wherein the consumption information comprises the number of consumers; determining a profit function corresponding to the consumption pattern according to consumption information of the second product corresponding to the consumption pattern based on production information of the second product; and determining a target consumption pattern for the second product from the plurality of consumption patterns according to a profit function corresponding to each of the plurality of consumption patterns.

Description

Method and device for determining product consumption mode, electronic equipment and storage medium
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method and an apparatus for determining a product consumption mode performed by an electronic device, and a storage medium.
Background
After the enterprise releases a new product, a plurality of consumption modes can be selected to face the consumer, so that the consumer obtains the product through different consumption modes, wherein profits obtained by selecting different consumption modes by the enterprise may be different.
In implementing the disclosed concept, the inventors found that there are at least the following problems in the related art: the selection mode of the consumption mode is not accurate enough, and the maximum profit is further influenced.
Disclosure of Invention
In view of this, the disclosed embodiments provide a method and an apparatus for determining a product consumption pattern performed by an electronic device, the electronic device, and a storage medium.
An aspect of an embodiment of the present disclosure provides a method for determining a product consumption mode, including:
in response to a consumption pattern determination request, obtaining historical data of each consumption pattern in a plurality of consumption patterns corresponding to a first product, wherein the historical data comprises the number and the usage amount of consumers;
establishing a product utility function corresponding to the consumption mode according to historical data of each consumption mode in a plurality of consumption modes corresponding to the first product;
generating consumption information of a second product corresponding to the consumption mode according to a product utility function corresponding to the consumption mode, wherein the consumption information comprises the number of consumers;
determining a profit function corresponding to the consumption pattern according to consumption information of a second product corresponding to the consumption pattern based on production information of the second product; and
and determining a target consumption pattern of the second product from the plurality of consumption patterns according to a profit function corresponding to each of the plurality of consumption patterns.
According to an embodiment of the present disclosure, the obtaining of the history data of each consumption mode of the plurality of consumption modes corresponding to the first product includes:
calling a data interface of the Internet of things platform; and
and acquiring historical data of each consumption mode in a plurality of consumption modes corresponding to the first product by using the platform data interface of the internet of things.
According to an embodiment of the present disclosure, the determining the target consumption pattern of the second product from the plurality of consumption patterns according to the profit function corresponding to each of the plurality of consumption patterns includes:
predicting pre-sale information of a second product corresponding to each consumption mode according to a profit function corresponding to each consumption mode; and
and determining a target consumption mode of the second product from the plurality of consumption modes according to the plurality of pre-sale information.
According to an embodiment of the present disclosure, the pre-sale information includes pre-sale profits;
wherein the determining a target consumption pattern of the second product from the plurality of consumption patterns based on the plurality of pre-sale information comprises:
determining the pre-sale profit with the largest value in the plurality of pre-sale profits as the target pre-sale profit; and
and determining the consumption pattern corresponding to the target pre-sale profit as the target consumption pattern of the second product.
According to the embodiment of the disclosure, the pre-sale information further comprises pre-sale pricing; wherein the determining a target consumption pattern of the second product from the plurality of consumption patterns based on the plurality of pre-sale information comprises:
and determining a target consumption pattern of the second product from the plurality of consumption patterns according to the pre-sale pricing and the pre-sale profit.
According to an embodiment of the present disclosure, the plurality of consumption modes include at least one of: the system comprises a sale mode, a lease mode and a mixed mode, wherein the mixed mode represents a mode with the sale mode and the lease mode simultaneously;
the historical data further comprises the price, the usage amount, the unit usage value and the product upgrading capacity of the first product, wherein the historical data corresponding to the rental mode further comprises the rental duration and the rental unit price;
the production information includes a production cost and a product upgrade capability of the second product.
According to an embodiment of the present disclosure, the utility function of the sales pattern is determined according to a unit usage value, a usage amount, and a price of the first product of the sales pattern;
said pre-sale quantity of said sales pattern is determined based on said utility function of said sales pattern according to a price of said first product;
the utility function of the rental model is determined based on a unit use value of the first product, a usage amount of the first product, a rental unit price of the first product, the product upgradability, and a number of the consumers who selected the first product in the rental model;
the pre-sale quantity of the rental model is determined according to the rental unit price of the first product in the rental model based on the utility function of the rental model;
the utility function of the sales model in the mixed mode is determined based on a unit usage value of the first product in the sales model in the mixed mode, a number of consumers who selected the first product in the mixed mode, a usage amount of the first product in the sales model in the mixed mode, and a price of the first product in the sales model in the mixed mode;
the pre-sale quantity of the sale mode in the mixed mode is determined according to the price of the first product in the sale mode in the mixed mode, the lease price of the first product in the lease mode in the mixed mode, and the upgrade capability of the product based on the utility function of the sale mode in the mixed mode;
the utility function of the rental mode in the mixed mode is determined according to a unit usage value of the first product in the rental mode in the mixed mode, a usage amount of the first product in the sales mode in the mixed mode, a number of consumers selecting the first product in the mixed mode, and a price of the first product in the sales mode in the mixed mode;
the pre-sale quantity of the rental model in the mixed model is determined according to the price of the first product in the sale model in the mixed model and the rental unit price of the first product in the rental model in the mixed model based on the utility function of the rental model in the mixed model.
According to an embodiment of the present disclosure, the utility function u of the sales patternpThe pre-sale quantity D of the sales pattern is as followspThe utility function u of the rental model is shown belowsThe pre-sale quantity D of the rental model is shown belowsThe utility function U of the sales mode in the mixed mode is shown belowphAnd the above-mentioned pre-sale quantity DphThe utility function U of the rental mode in the hybrid mode is shown belowshAnd the above-mentioned pre-sale quantity DshRespectively as follows;
Figure BDA0003336927580000041
Figure BDA0003336927580000042
Figure BDA0003336927580000043
Figure BDA0003336927580000044
Figure BDA0003336927580000045
Figure BDA0003336927580000046
Figure BDA0003336927580000047
Figure BDA0003336927580000048
wherein theta represents the unit use value and theta is subject to uniform distribution, i.e.
Figure BDA0003336927580000049
dpCharacterizing the amount of use of the first product in sales mode, dsCharacterizing the amount of use of the first product in rental mode, dphAnd dshCharacterizing the usage of the first product in sales mode and rental mode, p, respectively, in the Mixed modepCharacterizing the price of a first product in sales mode, psCharacterizing a rental price, p, of a first product in rental modephAnd pshRespectively characterizing the price of the first product in the sale mode in the mixed mode and the rental price of the first product in the rental mode in the mixed mode, DpCharacterizing the number of consumers that buy the first product in a sales Pattern, DsCharacterizing the number of consumers who select the first product in rental mode, DphAnd DshCharacterizing the number of consumers selecting the first product in sales mode and rental mode, N, respectively, in mixed modehCharacterization DphAnd DshAnd the sum, lambda, represents the coefficient of the upgrading capability of the product.
According to an embodiment of the present disclosure, the profit function pi of the sales patternpAs shown below, the profit function pi for the rental modelsThe profit function of the hybrid mode described above, pi, is shown belowhAs follows;
πp＝(pp-c)Dp
πs＝psΦs-cDs
πh＝pphDph+pshΦsh-cNh
wherein c represents the production cost of the second product, pipCharacterizing the pre-sale profit, π, of a second product in a sales modesCharacterizing the pre-sale profit, π, of the second product in rental modehCharacterizing the pre-sale profit, Φ, of the second product in the Mixed modesCharacterizing usage in rental mode, phishThe usage of the selected rental mode in the hybrid mode is characterized.
According to an embodiment of the present disclosure, the product properties of the first product are the same or different from the product properties of the second product.
Another aspect of an embodiment of the present disclosure provides an apparatus for determining a consumption mode of a product, including:
the acquisition module is used for responding to the consumption mode determination request and acquiring historical data of each consumption mode in a plurality of consumption modes corresponding to the first product, wherein the historical data comprises the number and the usage amount of consumers;
the establishing module is used for establishing a product utility function corresponding to the consumption mode according to the historical data of each consumption mode in a plurality of consumption modes corresponding to the first product;
the generating module is used for generating consumption information of a second product corresponding to the consumption mode according to a product utility function corresponding to the consumption mode, wherein the consumption information comprises the number of consumers;
a first determining module for determining a profit function corresponding to the consumption pattern according to consumption information of a second product corresponding to the consumption pattern based on production information of the second product; and
a second determining module for determining a target consumption pattern of the second product from the plurality of consumption patterns according to a profit function corresponding to each of the plurality of consumption patterns.
According to the embodiment of the disclosure, the number of consumers in different consumption modes of the second product can be predicted by the utility functions of different consumption modes established by historical data such as the number of consumers of the first product, the usage amount and the like, so that the profit functions corresponding to the consumption modes can be established according to the number of consumers of the second product and the production information, a target consumption mode can be determined from multiple consumption modes according to profits obtained by the profit functions, and the maximum profit can be obtained. The technical means at least partially solves the technical problem that the selection mode of the consumption mode is not accurate enough, so that the acquisition of the maximum profit is influenced, the accuracy of selecting the consumption mode is improved, and the technical effect of acquiring the maximum profit is realized.
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The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments of the present disclosure with reference to the accompanying drawings, in which:
FIG. 1 schematically illustrates an exemplary system architecture to which a method of determining product consumption patterns may be applied, according to an embodiment of the disclosure;
FIG. 2 schematically illustrates a flow chart of a method of determining a consumption pattern of a product according to an embodiment of the present disclosure;
FIG. 3 schematically shows a flow chart of a method of determining a consumption pattern of a product according to an embodiment of the present disclosure; and
fig. 4 schematically shows a block diagram of an electronic device implementing a method of determining a consumption pattern of a product according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.
Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B and C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).
After a business releases a new product, consumers typically acquire the product through a variety of consumption modes. However, different consumption patterns bring different profits to the enterprise.
For example, a business sells a product to a consumer through a sales model, the business sells ownership of the product to the consumer at a fixed price higher than the cost, the business can quickly recover the production cost of the product, and the business belongs to light asset operation in the sales model.
In the rental mode, the enterprise retains ownership of the product and only charges according to the usage duration of the consumer, and since the usage durations of different consumers may be different, the overall profit and profit level of the enterprise also has high uncertainty.
In the mixed mode, an enterprise rents and sells products by adopting two business modes, namely a selling mode and a leasing mode, a consumer selects the two modes according to own preference, and the two modes possibly compete with each other, so that the product service mode which can bring more profits to the enterprise is not clear.
In view of the above, the inventors have found that utility functions in different consumption modes can be established by the number and usage of consumers in the historical data of the first product related to the second product, the number of consumers of the second product in different consumption modes can be derived by using the utility functions, so as to establish profit functions corresponding to the second product in different consumption modes, and finally an optimal target consumption mode for the second product can be determined from multiple consumption modes according to the maximum profit of the different consumption modes.
Specifically, the embodiment of the disclosure provides a method and a device for determining a product consumption mode, an electronic device and a storage medium. The method comprises the following steps: in response to the consumption pattern determination request, obtaining historical data for each consumption pattern of a plurality of consumption patterns corresponding to the first product, wherein the historical data comprises the number of consumers and the usage amount; establishing a product utility function corresponding to the consumption mode according to the historical data of each consumption mode in a plurality of consumption modes corresponding to the first product; generating consumption information of a second product corresponding to the consumption mode according to the product utility function corresponding to the consumption mode, wherein the consumption information comprises the number of consumers; determining a profit function corresponding to the consumption pattern according to consumption information of the second product corresponding to the consumption pattern based on production information of the second product; and determining a target consumption pattern for the second product from the plurality of consumption patterns according to a profit function corresponding to each of the plurality of consumption patterns.
Fig. 1 schematically illustrates an exemplary system architecture 100 to which a method of determining product consumption patterns may be applied, according to an embodiment of the present disclosure. It should be noted that fig. 1 is only an example of a system architecture to which the embodiments of the present disclosure may be applied to help those skilled in the art understand the technical content of the present disclosure, and does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments or scenarios.
As shown in fig. 1, the system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired and/or wireless communication links, and so forth.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. Various client applications may be installed on the terminal devices 101, 102, 103, such as a consumption pattern determination class application, a web browser application, a search class application, an instant messaging tool, a mailbox client, and/or social platform software, etc. (by way of example only).
The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server (for example only) providing support for websites browsed by users using the terminal devices 101, 102, 103. The background management server may analyze and otherwise process the received data such as the consumption pattern determination request, and feed back a processing result (e.g., a web page, information, or data obtained or generated according to a user request) to the terminal device.
It should be noted that the method for determining the product consumption mode provided by the embodiment of the present disclosure may be generally executed by the server 105. Accordingly, the determining device of the product consumption mode provided by the embodiment of the present disclosure can be generally disposed in the server 105. The determination method of the product consumption pattern provided by the embodiment of the present disclosure may also be executed by a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Accordingly, the device for determining the product consumption pattern provided by the embodiment of the present disclosure may also be disposed in a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Alternatively, the method for determining the product consumption mode provided by the embodiment of the present disclosure may also be executed by the terminal device 101, 102, or 103, or may also be executed by another terminal device different from the terminal device 101, 102, or 103. Accordingly, the device for determining the product consumption mode provided by the embodiment of the present disclosure may also be disposed in the terminal device 101, 102, or 103, or in another terminal device different from the terminal device 101, 102, or 103.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Fig. 2 schematically shows a flow chart of a method of determining a consumption pattern of a product according to an embodiment of the present disclosure.
As shown in fig. 2, the method may include operations S210 to S250.
In operation S210, in response to a consumption pattern determination request, history data of each of a plurality of consumption patterns corresponding to a first product is acquired, wherein the history data includes the number of consumers and the usage amount.
In operation S220, a product utility function corresponding to the consumption pattern is established according to the historical data of each of the plurality of consumption patterns corresponding to the first product.
In operation S230, consumption information of the second product corresponding to the consumption pattern is generated according to the product utility function corresponding to the consumption pattern, wherein the consumption information includes the number of consumers.
In operation S240, a profit function corresponding to the consumption pattern is determined according to consumption information of the second product corresponding to the consumption pattern based on production information of the second product.
In operation S250, a target consumption pattern of the second product is determined from the plurality of consumption patterns according to a profit function corresponding to each of the plurality of consumption patterns.
According to embodiments of the present disclosure, a consumption pattern may refer to a manner in which a consumer obtains a product, such as a manner in which a product is obtained for purchase, lease, and the like.
In accordance with embodiments of the present disclosure, a product utility function may represent a function of the quantitative relationship between the value obtained by a consumer in consumption and the product combinations consumed to measure the degree to which the consumer is satisfied from consuming a given product combination.
According to an embodiment of the present disclosure, the production information may refer to information associated with the product during production of the product, such as production cost and the like.
According to an embodiment of the present disclosure, the consumption information may refer to information of the number, usage amount, and the like of consumers in a rental or sale process of a product.
For a specified price, it is equal to the maximum value of that price on the production set.
According to the embodiment of the disclosure, when the consumption mode of the product needs to be determined, the enterprise may send a consumption mode determination request to the electronic device, and the electronic device collects historical data of the first product in different consumption modes, such as the number and usage of the consumers, of the consumers in response to the consumption mode determination request. The enterprise respectively establishes utility functions of the first products in the corresponding consumption modes based on the collected historical data in the multiple consumption modes, and analyzes and predicts the number of consumers in the multiple consumption modes. The enterprise constructs profit functions under different consumption modes according to the production information of the second product and in combination with the consumption information of the second product, aims at maximizing profits, solves the optimal profits under various consumption modes, compares and analyzes the three modes, and selects the optimal target consumption mode.
According to the embodiment of the disclosure, the number of consumers in different consumption modes of the second product can be predicted by the utility functions of different consumption modes established by historical data such as the number of consumers of the first product, the usage amount and the like, so that the profit functions corresponding to the consumption modes can be established according to the number of consumers of the second product and the production information, a target consumption mode can be determined from multiple consumption modes according to profits obtained by the profit functions, and the maximum profit can be obtained. Therefore, the technical problem that the acquisition of the maximum profit is influenced due to the fact that the selection mode of the consumption mode is not accurate is at least partially solved, the accuracy of selecting the consumption mode is improved, and the acquisition of the maximum profit is realized.
According to an embodiment of the present disclosure, the obtaining of the historical data of each consumption pattern of the plurality of consumption patterns corresponding to the first product may include the following operations.
And calling a platform data interface of the Internet of things. And acquiring historical data of each consumption mode in a plurality of consumption modes corresponding to the first product by utilizing the platform data interface of the internet of things.
According to the embodiment of the disclosure, with the rapid development of information technologies such as the internet of things and cloud computing, many enterprises begin to embed sensors and software modules in hardware products, and the intelligent components can help the enterprises collect the use data of consumers, analyze the personalized demands of the consumers, and update and upgrade the existing products.
According to the embodiment of the disclosure, in order to acquire more and richer historical data, historical data under different consumption modes can be acquired from the internet of things by using the data acquisition equipment, so that a target consumption mode can be determined according to the acquired historical data.
According to an embodiment of the present disclosure, determining a target consumption pattern of the second product from the plurality of consumption patterns according to the profit function corresponding to each of the plurality of consumption patterns may include the following operations.
And predicting the pre-sale information of the second product corresponding to each consumption mode according to the profit function corresponding to each consumption mode. A target consumption pattern for the second product is determined from the plurality of consumption patterns based on the plurality of pre-sale information.
According to embodiments of the present disclosure, the pre-sale information may refer to predicted quantities of sale and/or lease of the product, product price, expected profit, and the like, under different consumption patterns.
According to the embodiment of the disclosure, the pre-sale information of the second product in different consumption modes can be calculated according to the constructed profit functions in different consumption modes, so that the optimal consumption mode is selected from the plurality of consumption modes as the target consumption mode according to the plurality of pre-sale information, an enterprise can apply the target consumption mode to the second product conveniently, and the enterprise can obtain larger profits.
According to an embodiment of the present disclosure, the pre-sale information includes pre-sale profits.
Wherein determining the target consumption pattern of the second product from the plurality of consumption patterns according to the plurality of pre-sale information may include the following operations.
Determining the pre-sale profit with the largest value in the plurality of pre-sale profits as the target pre-sale profit; and determining a consumption pattern corresponding to the target pre-sale profit as a target consumption pattern of the second product.
According to the embodiment of the disclosure, since the production and the operation of the enterprise require certain cost, the enterprise can select the consumption mode with the maximum profit as the operation mode of the second product.
According to embodiments of the present disclosure, the pre-sale information also includes pre-sale pricing.
Wherein determining the target consumption pattern of the second product from the plurality of consumption patterns according to the plurality of pre-sale information may include the following operations.
A target consumption pattern for the second product is determined from the plurality of consumption patterns based on the pre-sale pricing and the pre-sale profit.
According to the embodiment of the disclosure, the pricing of the second product directly affects the number of consumers, and further affects profit gain of an enterprise, for example, the pricing of the second product is within a certain range, and the pricing and the profit are in a positive correlation relationship, but as the pricing continues to rise, the number of consumers may decrease by a large margin, so that the profit gained by the enterprise rapidly slips down, therefore, when selecting a consumption mode, the relationship between the pre-sale pricing and the pre-sale profit of the second product can be comprehensively considered, so that the pre-sale pricing is within an expected range of the consumers while obtaining a large profit, and thus the number of consumers is large, and the popularization and the promotion of the second product are facilitated.
According to an embodiment of the present disclosure, the plurality of consumption patterns may include at least one of: a sales mode, a rental mode, and a mixed mode, the mixed mode characterizing a mode having both a sales mode and a rental mode.
The historical data can also comprise the price, the usage amount, the unit usage value and the product upgrading capacity of the first product, wherein the historical data corresponding to the rental mode further comprises the rental duration and the rental unit price;
the production information may include a production cost and a product upgrade capability of the second product.
According to an embodiment of the present disclosure, the historical data further includes preference information of the consumer, evaluation information of the first product by the consumer.
According to embodiments of the present disclosure, a unit use value may refer to a relationship between a value obtained by a consumer using a product and a price of the product.
According to an embodiment of the present disclosure, the product upgrade capability may refer to the capability of an enterprise to upgrade and update a product, for example, a mobile phone system. Wherein, the upgrading capability of the product is related to the usage amount and the unit usage value.
According to embodiments of the present disclosure, the sales patterns may be directed to patterns in which the consumer sells products, such as purchasing a cell phone or the like. The rental mode may refer to a mode of renting a product to a consumer in units of days or hours, such as a sharing bicycle or the like. Mixed mode may refer to a mode in which products are offered to consumers in a combination of sales mode and rental mode, such as a portion of a business offering a purchase and rental of a car to a consumer at the same time.
According to the embodiment of the disclosure, under the support of the digital technologies such as the internet of things and big data, the value of the product is not only reflected on the hardware product, but also develops towards the combination of the hardware product and the software service. As consumers begin to pay more attention to the services and experiences brought by products, enterprises need to analyze the personalized needs of consumers in order to update and upgrade products.
According to an embodiment of the present disclosure, a utility function of a sales pattern is determined according to a unit usage value, a usage amount, and a price of a first product in the sales pattern.
The pre-sale amount of the sales pattern is determined based on a utility function of the sales pattern based on the price of the first product.
The utility function of the rental model is determined based on a unit use value of the first product in the rental model, an amount of the first product used, a rental unit price of the first product, a product upgradeability, and a number of consumers selecting the first product.
The pre-sale quantity of the rental mode is determined according to the rental unit price of the first product in the rental mode based on the utility function of the rental mode.
The utility function of the sales mode in the mixed mode is determined based on the unit usage value of the first product in the sales mode in the mixed mode, the number of consumers selecting the first product in the mixed mode, the usage amount of the first product in the sales mode in the mixed mode, and the price of the first product in the sales mode in the mixed mode.
The pre-sale quantity of the sale modes in the mixed mode is determined according to the price of the first product in the sale mode in the mixed mode, the lease unit price of the first product in the lease mode in the mixed mode and the upgrading capacity of the product based on the utility function of the sale modes in the mixed mode.
The utility function for the rental mode in the mixed mode is determined based on a unit use value of the first product in the rental mode in the mixed mode, an amount of the first product in the sales mode in the mixed mode, a number of consumers selecting the first product in the mixed mode, and a price of the first product in the sales mode in the mixed mode.
The pre-sale quantity of the leasing mode in the mixed mode is determined according to the price of the first product in the sale mode in the mixed mode and the leasing unit price of the first product in the leasing mode in the mixed mode based on the utility function of the leasing mode in the mixed mode.
According to an embodiment of the present disclosure, utility function u of sales patternspThe pre-sale quantity D of the sale mode as shown in the formula (1)pAs shown in equation (2), utility function u of rental modesThe pre-sale quantity D of the rental mode as shown in the formula (3)sThe utility function U of the sales model in the hybrid model, as shown in equation (4)phAnd a pre-sale quantity DphUtility function U of rental mode in blending mode, as shown in equations (5) and (6), respectivelyshAnd a pre-sale quantity DshAs shown in equation (7) and equation (8), respectively.
Figure BDA0003336927580000131
Figure BDA0003336927580000132
Figure BDA0003336927580000133
Figure BDA0003336927580000134
Figure BDA0003336927580000135
Figure BDA0003336927580000136
Figure BDA0003336927580000137
Figure BDA0003336927580000141
Wherein theta represents the unit use value and theta is subject to uniform distribution, i.e.
Figure BDA0003336927580000142
dpCharacterizing the amount of use of the first product in sales mode, dsCharacterizing the amount of use of the first product in rental mode, dphAnd dshCharacterizing the usage of the first product in sales mode and rental mode, p, respectively, in the Mixed modepCharacterizing the price of a first product in sales mode, psCharacterizing a rental price, p, of a first product in rental modephAnd pshRespectively characterizing the price of the first product in the sale mode in the mixed mode and the rental price of the first product in the rental mode in the mixed mode, DpCharacterizing the number of consumers that buy the first product in a sales Pattern, DsCharacterizing the number of consumers who select the first product in rental mode, DphAnd DshCharacterizing the number of consumers selecting the first product in sales mode and rental mode, N, respectively, in mixed modehCharacterization DphAnd DshAnd the sum, lambda, represents the coefficient of the upgrading capability of the product.
According to the embodiment of the disclosure, no matter the consumer obtains the product in the sales mode or the rental mode, the consumer can obtain a certain unit use value, the unit use value influences the willingness of the consumer to obtain the product, and the unit use value may vary from person to person due to different value concepts of different consumers, so that the distribution of the consumer use value can be approximately fitted through market research and later data analysis.
According to an embodiment of the disclosure, in the rental mode, the unit use value can follow the usage amount d of the consumersIncreasing with increasing, and of decreasing marginal utility. The marginal effect may refer to the utility of increasing (or decreasing) the revenue of a corresponding product or service per new unit of product or service.
According to an embodiment of the present disclosure, in the sales mode, according to
Figure BDA0003336927580000143
Deducing the optimal usage amount of the consumer as
Figure BDA0003336927580000144
Will be provided with
Figure BDA0003336927580000145
Substituting the utility function in the sales mode to obtain the maximum utility of the consumer
Figure BDA0003336927580000146
In that
Figure BDA0003336927580000147
In the case of (1), i.e.
Figure BDA0003336927580000148
The consumer selects a sales model to obtain the product, and therefore the interval
Figure BDA0003336927580000149
The consumers in the system can obtain the products in a sales mode, so that the number of the consumers in the sales mode can be deduced to be
Figure BDA00033369275800001410
According to an embodiment of the present disclosure, in the rental mode, according to
Figure BDA00033369275800001411
Figure BDA00033369275800001412
Deducing the optimal usage amount of the consumer
Figure BDA00033369275800001413
The maximum utility of the consumer can be obtained after the utility function in the rental mode is substituted
Figure BDA0003336927580000151
In that
Figure BDA00033369275800001516
In the case ofI.e. by
Figure BDA0003336927580000152
The consumer chooses to obtain the product in rental mode, so the interval
Figure BDA00033369275800001517
The consumer in the system will obtain the product in the mode of rent, so as to deduce the number of consumers in the mode of rent as
Figure BDA0003336927580000153
According to an embodiment of the present disclosure, in a hybrid mode, according to
Figure BDA0003336927580000154
Figure BDA0003336927580000155
And
Figure BDA0003336927580000156
deducing the optimal usage amount of the product acquired by the consumer in the sales mode as
Figure BDA0003336927580000157
Substitution of uphThe maximum utility obtained by the consumer for obtaining the product in the sales mode can be obtained
Figure BDA0003336927580000158
Similarly, the optimal usage of a product in rental mode by a consumer can be deduced
Figure BDA0003336927580000159
Substitution of ushThe maximum utility obtained by the consumer for obtaining the product in the rental mode can be obtained
Figure BDA00033369275800001510
In that
Figure BDA00033369275800001511
In which case the consumer would choose to obtain the product in a sales mode
Figure BDA00033369275800001515
The consumer may choose to obtain the product in rental mode. It is therefore possible to deduce the number of consumers in the mixed mode
Figure BDA00033369275800001513
Figure BDA00033369275800001514
According to an embodiment of the present disclosure, profit function of sales patterns pipAs shown in equation (9), the profit function of the rental model pisAs shown in equation (10), the Mixed mode profit function πhAs shown in equation (11).
πp＝(pp-c)Dp 9)
πs＝psΦs-cDs (10)
πh＝pphDph+pshΦsh-cNh (11)
Wherein c represents the production cost of the second product, pipCharacterizing the pre-sale profit, π, of a second product in a sales modesCharacterizing the pre-sale profit, π, of the second product in rental modehCharacterizing the pre-sale profit, Φ, of the second product in the Mixed modesCharacterizing usage in rental mode, phishThe usage of the selected rental mode in the hybrid mode is characterized.
According to the embodiment of the disclosure, the enterprise, by evaluating the production cost and the product upgrade capability of the second product, combines one of the following: the method comprises the steps of calculating the profit functions of the consumer under different consumption modes, calculating the maximum profit and the pre-sale pricing under different consumption modes, carrying out comparative analysis on the maximum profit and the pre-sale pricing under different consumption modes, and selecting the optimal consumption mode to provide a mode for obtaining a second product for the consumer.
According to embodiments of the present disclosure, the product properties of the first product are the same or different from the product properties of the second product.
According to an embodiment of the present disclosure, for example, the first product is a brand a automobile and the second product is a brand B automobile, both of which belong to a new energy automobile. For another example, the first product is an electric vehicle with a replaceable battery, the second product is a battery, and although the two products have different properties, the demand of the battery vehicle is related to the demand of the battery.
Fig. 3 schematically shows a flow chart of a method of determining a consumption pattern of a product according to an embodiment of the present disclosure.
As shown in fig. 3, the product consumption pattern determining apparatus 300 may include an obtaining module 310, an establishing module 320, a generating module 330, a first determining module 340, and a second determining module 350.
The obtaining module 310 is configured to obtain historical data of each consumption pattern of a plurality of consumption patterns corresponding to the first product in response to the consumption pattern determination request, wherein the historical data includes the number of consumers and the usage amount.
The establishing module 320 is configured to establish a product utility function corresponding to the consumption pattern according to the historical data of each consumption pattern of the plurality of consumption patterns corresponding to the first product.
The generating module 330 is configured to generate consumption information of the second product corresponding to the consumption pattern according to the product utility function corresponding to the consumption pattern, where the consumption information includes the number of consumers.
The first determining module 340 is configured to determine a profit function corresponding to the consumption pattern according to the consumption information of the second product corresponding to the consumption pattern based on the production information of the second product.
The second determining module 350 is for determining a target consumption pattern of the second product from the plurality of consumption patterns according to a profit function corresponding to each of the plurality of consumption patterns.
According to the embodiment of the disclosure, the number of consumers in different consumption modes of the second product can be predicted by the utility functions of different consumption modes established by historical data such as the number of consumers of the first product, the usage amount and the like, so that the profit functions corresponding to the consumption modes can be established according to the number of consumers of the second product and the production information, a target consumption mode can be determined from multiple consumption modes according to profits obtained by the profit functions, and the maximum profit can be obtained. Therefore, the technical problem that the acquisition of the maximum profit is influenced due to the fact that the selection mode of the consumption mode is not accurate is at least partially solved, the accuracy of selecting the consumption mode is improved, and the acquisition of the maximum profit is realized.
According to the embodiment of the disclosure, historical data of multiple consumption modes of the first product is acquired from an internet of things environment by using a data acquisition device.
According to an embodiment of the present disclosure, the second determination module 350 may include a prediction unit and a first determination unit.
The prediction unit is used for predicting the pre-sale information of the second product corresponding to each consumption mode according to the profit function corresponding to each consumption mode.
The first determining unit is used for determining a target consumption mode of the second product from a plurality of consumption modes according to the plurality of pre-sale information.
According to an embodiment of the present disclosure, the first determination unit may include a first determination subunit and a second determination subunit.
The first determining subunit is configured to determine the pre-sale profit with the largest value among the plurality of pre-sale profits as the target pre-sale profit.
The second determining subunit is configured to determine a consumption pattern corresponding to the target pre-sale profit as a target consumption pattern of the second product.
According to embodiments of the present disclosure, the pre-sale information may also include pre-sale pricing.
According to an embodiment of the present disclosure, the first determination unit may include a third determination subunit.
And a third determining subunit, configured to determine a target consumption pattern of the second product from the plurality of consumption patterns according to the pre-sale pricing and the pre-sale profit.
According to an embodiment of the present disclosure, the plurality of consumption patterns may include at least one of: a sales mode, a rental mode, and a mixed mode, the mixed mode characterizing a mode having both a sales mode and a rental mode.
The historical data can also comprise the price, the usage amount, the unit usage value and the product upgrading capacity of the first product, wherein the historical data corresponding to the rental mode further comprises the rental duration and the rental unit price.
The production information may include a production cost and a product upgrade capability of the second product.
According to an embodiment of the present disclosure, a utility function of a sales pattern is determined according to a unit usage value, a usage amount, and a price of a first product in the sales pattern.
The pre-sale amount of the sales pattern is determined based on a utility function of the sales pattern based on the price of the first product.
The utility function of the rental model is determined based on a unit use value of the first product in the rental model, an amount of the first product used, a rental unit price of the first product, a product upgradeability, and a number of consumers selecting the first product.
The pre-sale quantity of the rental mode is determined according to the rental unit price of the first product in the rental mode based on the utility function of the rental mode.
The utility function of the sales mode in the mixed mode is determined based on the unit usage value of the first product in the sales mode in the mixed mode, the number of consumers selecting the first product in the mixed mode, the usage amount of the first product in the sales mode in the mixed mode, and the price of the first product in the sales mode in the mixed mode.
The pre-sale quantity of the sale modes in the mixed mode is determined according to the price of the first product in the sale mode in the mixed mode, the lease unit price of the first product in the lease mode in the mixed mode and the upgrading capacity of the product based on the utility function of the sale modes in the mixed mode.
The utility function for the rental mode in the mixed mode is determined based on a unit use value of the first product in the rental mode in the mixed mode, an amount of the first product in the sales mode in the mixed mode, a number of consumers selecting the first product in the mixed mode, and a price of the first product in the sales mode in the mixed mode.
The pre-sale quantity of the leasing mode in the mixed mode is determined according to the price of the first product in the sale mode in the mixed mode and the leasing unit price of the first product in the leasing mode in the mixed mode based on the utility function of the leasing mode in the mixed mode.
According to embodiments of the present disclosure, the product properties of the first product are the same or different from the product properties of the second product.
Any of the modules, units, sub-units, or at least part of the functionality of any of them according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, units and sub-units according to the embodiments of the present disclosure may be implemented by being split into a plurality of modules. Any one or more of the modules, units, and sub-units according to the embodiments of the present disclosure may be implemented at least partially as a hardware Circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented by hardware or firmware in any other reasonable manner of integrating or packaging a Circuit, or implemented by any one of or a suitable combination of software, hardware, and firmware. Alternatively, one or more of the modules, units, sub-units according to embodiments of the disclosure may be at least partially implemented as computer program modules, which, when executed, may perform the corresponding functions.
For example, any plurality of the obtaining module 310, the establishing module 320, the generating module 330, the first determining module 340 and the second determining module 350 may be combined and implemented in one module/unit/sub-unit, or any one of the modules/units/sub-units may be split into a plurality of modules/units/sub-units. Alternatively, at least part of the functionality of one or more of these modules/units/sub-units may be combined with at least part of the functionality of other modules/units/sub-units and implemented in one module/unit/sub-unit. According to an embodiment of the present disclosure, at least one of the obtaining module 310, the establishing module 320, the generating module 330, the first determining module 340 and the second determining module 350 may be at least partially implemented as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented by hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or implemented by any one of three implementations of software, hardware and firmware, or any suitable combination of any of them. Alternatively, at least one of the obtaining module 310, the establishing module 320, the generating module 330, the first determining module 340 and the second determining module 350 may be at least partially implemented as a computer program module, which when executed may perform a corresponding function.
It should be noted that, the determining device portion of the consumption pattern in the embodiment of the present disclosure corresponds to the determining method portion of the consumption pattern in the embodiment of the present disclosure, and the description of the determining device portion of the consumption pattern specifically refers to the determining method portion of the consumption pattern, and is not repeated herein.
Fig. 4 schematically shows a block diagram of an electronic device adapted to implement the above described method according to an embodiment of the present disclosure. The electronic device shown in fig. 4 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 4, an electronic device 400 according to an embodiment of the present disclosure includes a processor 401 that can perform various appropriate actions and processes according to a program stored in a Read-Only Memory (ROM) 402 or a program loaded from a storage section 408 into a Random Access Memory (RAM) 403. Processor 401 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), among others. The processor 401 may also include onboard memory for caching purposes. Processor 401 may include a single processing unit or multiple processing units for performing the different actions of the method flows in accordance with embodiments of the present disclosure.
In the RAM403, various programs and data necessary for the operation of the electronic apparatus 400 are stored. The processor 401, ROM402 and RAM403 are connected to each other by a bus 404. The processor 401 performs various operations of the method flows according to the embodiments of the present disclosure by executing programs in the ROM402 and/or the RAM 403. Note that the programs may also be stored in one or more memories other than the ROM402 and RAM 403. The processor 401 may also perform various operations of the method flows according to embodiments of the present disclosure by executing programs stored in the one or more memories.
According to an embodiment of the present disclosure, electronic device 400 may also include an input/output (I/O) interface 405, input/output (I/O) interface 405 also being connected to bus 404. The system 400 may also include one or more of the following components connected to the I/O interface 405: an input section 406 including a keyboard, a mouse, and the like; an output section 407 including a Display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 408 including a hard disk and the like; and a communication section 409 including a network interface card such as a LAN card, a modem, or the like. The communication section 409 performs communication processing via a network such as the internet. A driver 410 is also connected to the I/O interface 405 as needed. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 410 as necessary, so that a computer program read out therefrom is mounted into the storage section 408 as necessary.
According to embodiments of the present disclosure, method flows according to embodiments of the present disclosure may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable storage medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 409, and/or installed from the removable medium 411. The computer program, when executed by the processor 401, performs the above-described functions defined in the system of the embodiments of the present disclosure. The systems, devices, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.
The present disclosure also provides a computer-readable storage medium, which may be contained in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer-readable storage medium carries one or more programs which, when executed, implement the method according to an embodiment of the disclosure.
According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. Examples may include, but are not limited to: a portable Computer diskette, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM) or flash Memory), a portable compact Disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the preceding. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
For example, according to embodiments of the present disclosure, a computer-readable storage medium may include ROM402 and/or RAM403 and/or one or more memories other than ROM402 and RAM403 described above.
Embodiments of the present disclosure also include a computer program product comprising a computer program containing program code for performing the method provided by the embodiments of the present disclosure, when the computer program product is run on an electronic device, the program code being adapted to cause the electronic device to carry out the method for determining a consumption pattern provided by the embodiments of the present disclosure.
The computer program, when executed by the processor 401, performs the above-described functions defined in the system/apparatus of the embodiments of the present disclosure. The systems, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.
In one embodiment, the computer program may be hosted on a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. In another embodiment, the computer program may also be transmitted, distributed in the form of a signal on a network medium, downloaded and installed through the communication section 409, and/or installed from the removable medium 411. The computer program containing program code may be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
In accordance with embodiments of the present disclosure, program code for executing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, these computer programs may be implemented using high level procedural and/or object oriented programming languages, and/or assembly/machine languages. The programming language includes, but is not limited to, programming languages such as Java, C + +, python, the "C" language, or the like. The program code may execute entirely on the user computing device, partly on the user device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments and/or claims of the present disclosure may be made without departing from the spirit or teaching of the present disclosure. All such combinations and/or associations are within the scope of the present disclosure.
The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.

Claims (13)

1. A method of determining a consumption pattern of a product performed by an electronic device, comprising:
in response to a consumption pattern determination request, obtaining historical data for each consumption pattern of a plurality of consumption patterns corresponding to a first product, wherein the historical data includes a number of consumers and a usage amount;
establishing a product utility function corresponding to the consumption mode according to historical data of each consumption mode in a plurality of consumption modes corresponding to the first product;
generating consumption information of a second product corresponding to the consumption mode according to a product utility function corresponding to the consumption mode, wherein the consumption information comprises the number of consumers;
determining a profit function corresponding to the consumption pattern according to consumption information of a second product corresponding to the consumption pattern based on production information of the second product; and
determining a target consumption pattern for the second product from the plurality of consumption patterns according to a profit function corresponding to each of the plurality of consumption patterns.
2. The method of claim 1, wherein said obtaining historical data for each consumption pattern of a plurality of consumption patterns corresponding to a first product comprises:
calling a data interface of the Internet of things platform; and
and acquiring historical data of each consumption mode in a plurality of consumption modes corresponding to the first product by utilizing the platform data interface of the internet of things.
3. The method of claim 1, wherein said determining a target consumption pattern for the second product from the plurality of consumption patterns according to a profit function corresponding to each of the plurality of consumption patterns comprises:
predicting pre-sale information of a second product corresponding to each consumption mode according to a profit function corresponding to each consumption mode; and
and determining a target consumption mode of the second product from the plurality of consumption modes according to a plurality of the pre-sale information.
4. The method of claim 3, the pre-sale information comprising pre-sale profits;
wherein said determining a target consumption pattern for said second product from said plurality of consumption patterns based on said plurality of pre-sale information comprises:
determining the pre-sale profit with the largest value in the plurality of pre-sale profits as the target pre-sale profit; and
determining a consumption pattern corresponding to the target pre-sale profit as a target consumption pattern of the second product.
5. The method of claim 4, the pre-sale information further comprising pre-sale pricing;
wherein said determining a target consumption pattern for said second product from said plurality of consumption patterns based on said plurality of pre-sale information comprises:
determining a target consumption pattern for the second product from the plurality of consumption patterns based on the pre-sale pricing and the pre-sale profit.
6. The method of claim 3, wherein: the plurality of consumption patterns comprises at least one of: a sales mode, a rental mode, and a mixed mode, the mixed mode characterizing a mode having both a sales mode and a rental mode;
the historical data further comprises the price, the usage amount, the unit usage value and the product upgrading capacity of the first product, wherein the historical data corresponding to the rental mode further comprises the rental duration and the rental unit price;
the production information includes a production cost and a product upgrade capability of the second product.
7. The method of claim 6, wherein the utility function of the sales pattern is determined from a unit usage value, an amount of usage, and a price of the first product for the first product in the sales pattern;
the pre-sale quantity of the sales pattern is determined from a price of the first product based on the utility function of the sales pattern;
the utility function of the rental model is determined based on a unit use value of the first product, an amount of the first product used, a rental unit price of the first product, the product upgradeability, and the number of the consumers who selected the first product in the rental model;
the pre-sale quantity of the rental mode is determined according to the rental unit price of the first product in the rental mode based on the utility function of the rental mode;
the utility function of a sales pattern in the mixed mode is determined according to a unit usage value of the first product of the sales pattern in the mixed mode, a number of consumers selecting the first product in the mixed mode, an amount of usage of the first product in the sales pattern in the mixed mode, and a price of the first product in the sales pattern in the mixed mode;
the pre-sale quantity of the sales pattern in the mixed mode is determined according to the price of the first product in the sales pattern in the mixed mode, the rental unit price of the first product in the rental mode in the mixed mode, and the product upgrading capability based on the utility function of the sales pattern in the mixed mode;
the utility function of a rental mode in the mixed mode is determined according to a unit usage value of the first product in the rental mode in the mixed mode, a usage amount of the first product in a sales mode in the mixed mode, a number of consumers selecting the first product in the mixed mode, and a price of the first product in the sales mode in the mixed mode;
the pre-sale quantity of the rental mode in the mixed mode is determined according to the price of the first product in the sales mode in the mixed mode and the rental unit price of the first product in the rental mode in the mixed mode based on the utility function of the rental mode in the mixed mode.
8. The method of claim 7, wherein the utility function u of the sales patternpThe pre-sale quantity D of the sale mode is as followspThe utility function u of the rental pattern is shown belowsThe pre-sale quantity D of the rental mode is shown belowsThe utility function U of the sales patterns in the hybrid pattern is shown belowphAnd said pre-sale quantity DphThe utility function U of the rental mode in the hybrid mode is shown belowshAnd said pre-sale quantity DshRespectively as follows;
Figure FDA0003336927570000031
Figure FDA0003336927570000032
Figure FDA0003336927570000033
Figure FDA0003336927570000034
Figure FDA0003336927570000035
Figure FDA0003336927570000036
Figure FDA0003336927570000037
Figure FDA0003336927570000041
wherein theta represents the unit use value and theta is subject to uniform distribution, i.e.
Figure FDA0003336927570000042
dpCharacterizing the amount of use of the first product in sales mode, dsCharacterizing the amount of use of the first product in rental mode, dphAnd dshCharacterizing the usage of the first product in sales mode and rental mode, p, respectively, in the Mixed modepCharacterizing the price of a first product in sales mode, psCharacterizing a rental price, p, of a first product in rental modephAnd pshRespectively characterizing the price of the first product in the sale mode in the mixed mode and the rental price of the first product in the rental mode in the mixed mode, DpCharacterizing the number of consumers that buy the first product in a sales Pattern, DsCharacterizing the number of consumers who select the first product in rental mode, DphAnd DshCharacterizing the number of consumers selecting the first product in sales mode and rental mode, N, respectively, in mixed modehCharacterization DphAnd DshAnd the sum, lambda, represents the coefficient of the upgrading capability of the product.
9. The method of claim 8, wherein the profit function of the sales pattern is pipThe profit function pi of the rental model is shown belowsThe profit function of the mixed mode, pi, is shown belowhAs follows;
πp＝(pp-c)Dp
πs＝psΦs-cDs
πh＝pphDph+pshΦsh-cNh
wherein c represents the production cost of the second product, pipCharacterizing the pre-sale profit, π, of a second product in a sales modesCharacterizing the pre-sale profit, π, of the second product in rental modehCharacterizing the pre-sale profit, Φ, of the second product in the Mixed modesCharacterizing usage in rental mode, phishThe usage of the selected rental mode in the hybrid mode is characterized.
10. An apparatus for determining a consumption pattern of a product, comprising:
an acquisition module, configured to acquire, in response to a consumption pattern determination request, historical data of each consumption pattern of a plurality of consumption patterns corresponding to a first product, where the historical data includes a number of consumers and a usage amount;
the establishing module is used for establishing a product utility function corresponding to the consumption mode according to the historical data of each consumption mode in a plurality of consumption modes corresponding to the first product;
the generating module is used for generating consumption information of a second product corresponding to the consumption mode according to a product utility function corresponding to the consumption mode, wherein the consumption information comprises the number of consumers;
a first determining module for determining a profit function corresponding to the consumption pattern according to consumption information of a second product corresponding to the consumption pattern based on production information of the second product; and
a second determination module to determine a target consumption pattern for the second product from the plurality of consumption patterns according to a profit function corresponding to each of the plurality of consumption patterns.
11. An electronic device, comprising:
one or more processors;
a memory for storing one or more programs,
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-9.
12. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to carry out the method of any one of claims 1 to 9.
13. A computer program product comprising a computer program which, when executed by a processor, is adapted to carry out the method of any one of claims 1 to 9.
CN202111302914.XA 2021-11-04 2021-11-04 Method and device for determining product consumption mode, electronic equipment and storage medium Pending CN114004656A (en)

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