CN114202451A - Evolution analysis method, device, equipment and storage medium of service ecosystem - Google Patents

Evolution analysis method, device, equipment and storage medium of service ecosystem Download PDF

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CN114202451A
CN114202451A CN202111544868.4A CN202111544868A CN114202451A CN 114202451 A CN114202451 A CN 114202451A CN 202111544868 A CN202111544868 A CN 202111544868A CN 114202451 A CN114202451 A CN 114202451A
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何霆
孙凤娇
朱文龙
李海波
廖永新
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Abstract

The embodiment of the invention provides an evolution analysis method, a device, equipment and a storage medium of a service ecosystem, and relates to the technical field of service ecosystem simulation. The evolution analysis method comprises steps S1 to S4. And S1, acquiring initial information of the service ecosystem. And S2, constructing a symbiotic evolution model of interaction of the value co-creation units based on the extended Logistic differential equation according to the initial information. S3, calculating and analyzing the progressive stability of the symbiotic evolution model by adopting a Lyapunov first method based on the Jacobian matrix. And S4, acquiring an evolution process in the calculation process and the scale of each value co-creation unit when the system reaches a stable state. The evolution analysis method is used for exploring the symbiotic mode and symbiotic conditions of different objects of different types for keeping stable states in the service ecosystem, and can accurately obtain required information.

Description

Evolution analysis method, device, equipment and storage medium of service ecosystem
Technical Field
The invention relates to the technical field of service ecosystem simulation, in particular to an evolution analysis method, a device, equipment and a storage medium of a service ecosystem.
Background
Under the new service internet environment, enterprises/organizations need to realize cross-border and agile aggregation and mutual cooperation through services, so that new value is created, and new requirements are met. In order to meet the requirements of more and more complex and personalized users, a complex service network system is formed among various organizations through division of labor, cooperation and advantage complementation. In the service network system, a plurality of cross-network, cross-domain and cross-boundary service providers, service platforms and service consumers participate in creating service value together, so that a network collaborative service ecosystem (namely, a service value network), namely a service ecosystem is formed.
For example, an intelligent mobile service internet system formed by taking platforms such as Taobao, Jingdong, Mei Tuo and the like as cores, and the like, wherein the well-known platform systems have obvious ecosystem and value chain/network characteristics.
How does the size of the value-sharing unit within the system evolve for such a complex service ecosystem? And how large are their worth of co-creation units when the system tends to or reaches stability? The existing analysis methods are all researched aiming at the service ecology with a chain structure, cannot be suitable for a service ecosystem with a network relation, and cannot accurately simulate the scale and the evolution path. This is an important issue that needs to be addressed during the symbiotic evolution of the service ecosystem.
Disclosure of Invention
The invention provides an evolution analysis method, a device, equipment and a storage medium of a service ecosystem, which aim to improve the problems.
The first aspect,
The embodiment of the invention provides an evolution analysis method of a service ecosystem, which comprises a step S1 to a step S4.
And S1, acquiring initial information of the service ecosystem. The service ecosystem comprises a service provider value co-creation unit, a service consumer value co-creation unit and a service platform value co-creation unit, and the initial information comprises the symbiotic action coefficient, the initial scale, the market scale capacity and the natural growth rate of each value co-creation unit.
And S2, constructing a symbiotic evolution model of interaction of the value co-creation units based on the extended Logistic differential equation according to the initial information. The symbiotic evolution model comprises a service provider value co-creation unit symbiotic evolution model, a service consumer value co-creation unit symbiotic evolution model and a service platform value co-creation unit symbiotic evolution model.
S3, calculating and analyzing the progressive stability of the symbiotic evolution model by adopting a Lyapunov first method based on the Jacobian matrix.
And S4, acquiring an evolution process in the calculation process and the scale of each value co-creation unit when the system reaches a stable state.
The second aspect,
The embodiment of the invention provides an evolution analysis device of a service ecosystem, which comprises:
and the acquisition module is used for acquiring initial information of the service ecosystem. The service ecosystem comprises a service provider value co-creation unit, a service consumer value co-creation unit and a service platform value co-creation unit, and the initial information comprises the symbiotic action coefficient, the initial scale, the market scale capacity and the natural growth rate of each value co-creation unit.
And the construction module is used for constructing a symbiotic evolution model of the interaction of the value co-creation units based on the extended Logistic differential equation according to the initial information. The symbiotic evolution model comprises a service provider value co-creation unit symbiotic evolution model, a service consumer value co-creation unit symbiotic evolution model and a service platform value co-creation unit symbiotic evolution model.
And the calculation module is used for calculating and analyzing the progressive stability of the symbiotic evolution model by adopting a Lyapunov first method based on the Jacobian matrix.
And the result module is used for acquiring the evolution process in the calculation process and the scale of each value co-creation unit when the system reaches a stable state.
The third aspect,
An embodiment of the present invention provides an evolution analysis device for a service ecosystem, which includes a processor, a memory, and a computer program stored in the memory. The computer program is executable by a processor to implement a method of evolution analysis of a service ecosystem as in any of the paragraphs of the first aspect.
The fourth aspect,
An embodiment of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program, where when the computer program runs, a device in which the computer-readable storage medium is located is controlled to execute the method for evolution analysis of a service ecosystem according to any section of the first aspect.
By adopting the technical scheme, the invention can obtain the following technical effects:
the embodiment of the invention fully considers a mesh structure consisting of a plurality of service platforms, service providers and service consumers, and explores the symbiotic mode and symbiotic conditions for different objects of different types to keep stable states in a service ecosystem by constructing the symbiotic evolution model of the objects based on the extended Logistic model, thereby accurately obtaining the required information.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flow chart of an evolution analysis method of a service ecosystem.
Fig. 2 is a schematic structural diagram of a health maintenance service ecosystem.
Fig. 3 is a graph of the evolution trajectory in the independent symbiotic mode.
Fig. 4 is a graph of the evolution trajectory in the normal contention mode.
Fig. 5 is a graph of the evolution trajectory in the malignant competition mode.
Fig. 6 is a graph of the evolution trajectory in the spurious mode.
Fig. 7 is a graph of the evolution trajectory in the belief co-occurrence mode.
FIG. 8 is a graph of the evolution trajectory in the reciprocal mode.
FIG. 9 is a graph of the evolution trajectory of the reciprocal pattern at different natural growth rates.
FIG. 10 is a plot of the evolution trajectory of the reciprocal mode at different initial scales.
FIG. 11 is a graph of the evolution trajectory of the reciprocal mode at different maximum scales.
Fig. 12 is a schematic structural diagram of an evolution analysis apparatus of a service ecosystem.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
For better understanding of the technical solutions of the present invention, the following detailed descriptions of the embodiments of the present invention are provided with reference to the accompanying drawings.
The first embodiment is as follows:
referring to fig. 1, a method for evolution analysis of a service ecosystem according to a first embodiment of the present invention can be executed by an evolution analysis apparatus of the service ecosystem. In particular, execution by one or more processors in the evolution analysis device to implement steps S1-S4.
And S1, acquiring initial information of the service ecosystem. The service ecosystem comprises a service provider value co-creation unit, a service consumer value co-creation unit and a service platform value co-creation unit, and the initial information comprises the symbiotic action coefficient of each value co-creation unit, the initial scale, the market scale capacity and the natural growth rate.
It is understood that the evolution analysis device may be an electronic device with computing capabilities, such as a portable computer, a desktop computer, a server, a smart phone, or a tablet computer.
It should be noted that the action coefficient, the initial scale, the scale capacity and the natural growth rate may be calculated according to statistical data or estimated values estimated by human, which is not specifically limited in the present invention. It is not limited to how one skilled in the art obtains more accurate values.
The service ecosystem is shown in fig. 2, and specifically, the service ecosystem is an internet-based dynamically-evolving complex ecosystem composed of a large number of services, and is composed of a value co-creation unit, a co-creation mode, and a co-creation environment.
The service ecosystem comprises three types of main bodies, namely a service consumer, a service provider and a service platform. The service provider provides different mass services to meet the requirements of service consumers, the service platform searches and mines the services, uniformly describes and labels the services, and clusters the services with similar functions to form a service function field, so that a service market is formed. The service consumer selects the service suitable for the consumer according to the specific requirement
Value co-creation units refer to a collection of co-creation units having the same or similar functionality. Symbiotic units refer to the basic energy production and units that make up the symbiotic relationship. Each enterprise (i.e. service provider) providing services is a symbiotic unit, the symbiotic units providing the same or similar functional services form a value co-creation unit, and different value co-creation units and third-party service platforms are combined to provide corresponding requirements for consumers.
The symbiotic mode, i.e. symbiotic relationship, refers to the action mode among symbiotic units, which includes four symbiotic modes of competition, parasitism, partial interest symbiosis and mutual benefit reciprocity among service populations. The competition symbiosis mode means that in the environment of value co-creation, different symbiotic units have no symbiotic effect and are mutually exclusive; the parasitic mode means that in the environment of value co-creation, one type of parasitic value co-creation unit is damaged in development, and the other type of parasitic value co-creation unit is benefited in development; the bias mutualism means that in the environment of value co-creation, one type of value co-creation unit develops without damage and without benefit, and the other type of value co-creation unit develops with benefit; mutual profit and mutual benefit represent the symbiotic relationship of two types of value co-creation units in the value co-creation environment, wherein the two types of value co-creation units mutually benefit and mutually win.
The symbiotic environment refers to the sum of all elements except the symbiotic unit, and generally comprises government policy environment, economic environment, cultural environment and the like which can affect the operation of a service ecosystem.
The market environment capacity scale refers to the maximum scale capacity that can be achieved when the scale growth and change of the value co-creation unit are limited by a plurality of factors in the evolution process of the service ecosystem. The balance point refers to the scale of various value co-creation units when the service ecosystem evolves to a certain period to enable the system to reach a stable state. The natural growth rate refers to the growth quantity of the size of the service ecosystem value co-creation unit group in a certain time.
It can be understood that the service ecosystem comprises N types of service provider value co-creation units (for example, in an automobile production and sales service system, a whole automobile product provider, an insurance type service provider, a financial type service provider, a vehicle maintenance type service provider and the like), M types of service consumer value co-creation units and X types of cloud service platform value co-creation units (including a third party service platform value co-creation unit providing only search and a third party service platform value co-creation unit providing search, mining and service combination). The negative symbiotic coefficient represents that the development of the value co-creation unit is damaged, and the positive symbiotic coefficient represents that the development of the value co-creation unit is benefited. In the competitive mode, consider competition between value co-creation units that provide homogeneous functional services.
And S2, constructing a symbiotic evolution model of interaction of each value co-creation unit based on the extended Logistic basic model differential model according to the initial information. The symbiotic evolution model comprises a service provider value co-creation unit symbiotic evolution model, a service consumer value co-creation unit symbiotic evolution model and a service platform value co-creation unit symbiotic evolution model.
It is understood that the service ecosystem is a complex system consisting of a plurality of third party service platforms, a plurality of service providers and a plurality of service consumers, wherein the third party service platforms/service providers/service consumers comprise a plurality of different types of value co-creation units, and each type of value co-creation unit comprises a plurality of variable-scale/number co-creation units.
In a service ecosystem, when the interaction of the value co-creation units is considered, the growth rate of each type of value co-creation unit is influenced by the population scale of the value co-creation unit and the population scale of the value co-creation unit of the other side. Therefore, the symbiotic evolution model of the interaction of the N-type service providers, the M-type service consumers and the X-type third-party service platform value co-creation units can be described through the differential equation of the extended Logistic basic model.
Specifically, the differential model of the extended Logistic basic model is as follows:
Figure BDA0003415569910000061
N(t0)＝N0
wherein N (t) represents the population size of the study subject in the t-th period, a represents the natural growth rate of the study subject population,
Figure BDA0003415569910000062
representing the hindering effect of limited resources on the growth of the research subject's own scale, N*Represents the maximum environmental capacity, N, of the study subject due to resource density constraints0Is the initial population size.
The symbiotic evolution model of the service provider value co-creation units comprises the following steps:
Figure BDA0003415569910000071
where N is the number of service provider categories, piNatural growth rate, sp, for class i service providersiFor the initial size of the class i service provider,
Figure BDA0003415569910000072
for the largest size of class i service providers,
Figure BDA0003415569910000073
size sp representing the size of various types of service consumers versus the size of the i-th type of service provideriThe effect of growth, M is the number of categories of service consumers,
Figure BDA0003415569910000074
size u for class j service consumerjSize sp for class i service provideriCoefficient of action of ujFor the initial size of class j service consumers,
Figure BDA0003415569910000075
for the largest size of class j service consumers,
Figure BDA0003415569910000076
size sp of class i service provider for other class service providersiThe influence of (c).
Figure BDA0003415569910000077
Scale sp for class s service providersSize sp for class i service provideriCoefficient of action of, spsThe initial size of the class s service provider,
Figure BDA0003415569910000078
maximum size of class s service providers.
The symbiotic evolution model of the service consumer value co-creation units comprises the following steps:
Figure BDA0003415569910000079
wherein M is the number of service consumers' categories, qjNatural growth rate for class j service consumers, ujFor the initial size of class j service consumers,
Figure BDA00034155699100000710
for the largest size of class j service consumers,
Figure BDA00034155699100000711
representing the size of each type of service provider versus the size u of the jth service consumerjThe effect of the growth, N is the number of service provider categories,
Figure BDA00034155699100000712
scale sp for class i service provideriSize u for class j service consumerjCoefficient of action of, spiFor the initial size of the class i service provider,
Figure BDA00034155699100000713
the maximum size of the class i service provider.
The service platform value co-creation unit symbiotic evolution model comprises the following steps:
Figure BDA0003415569910000081
wherein X is the number of kinds of service platforms, mzNatural growth rate for class z service platforms, cdzFor the initial size of the class z service platform,
Figure BDA0003415569910000082
for the maximum size of class z service platforms,
Figure BDA0003415569910000083
scale cd representing scales of various types of service consumers versus class z service platformszThe effect of growth of. M is the number of categories of service consumers,
Figure BDA0003415569910000084
size u for class j service consumerjScale cd for class z service platformszCoefficient of action of ujFor the initial size of class j service consumers,
Figure BDA0003415569910000085
for the largest size of class j service consumers,
Figure BDA0003415569910000086
scale cd representing scale of various types of service providers versus class z service platformszThe effect of growth of. N is the number of categories of service providers,
Figure BDA0003415569910000087
scale sp for class i service provideriScale cd for class z service platformszCoefficient of action of, spiFor the initial size of the class i service provider,
Figure BDA0003415569910000088
for the largest size of class i service providers,
Figure BDA0003415569910000089
scale cd for class z service platforms for other classes of service platformszThe influence of (a) on the performance of the device,
Figure BDA00034155699100000810
scale cd for class y service platformsyScale cd for class z service platformszCoefficient of action of, cdyFor the initial size of the class y service platform,
Figure BDA00034155699100000811
the maximum size of the y-th service platform.
S3, calculating and analyzing the progressive stability of the symbiotic evolution model by adopting a Lyapunov first method based on the Jacobian matrix.
Specifically, on the basis of the above embodiment, in an alternative embodiment of the present invention, the step S3 specifically includes the step S31 and the step S32.
And S31, carrying out progressive stability analysis on the symbiotic evolution model, and calculating to obtain an equilibrium point. Wherein the balance point of the symbiotic evolution model comprises E1、E2、E3、E4、E5、E6、E7And E8。
E1(0,0,0)
Figure BDA0003415569910000091
Figure BDA0003415569910000092
Figure BDA0003415569910000093
Figure BDA0003415569910000094
Figure BDA0003415569910000095
Figure BDA0003415569910000096
E8(sp1 *,sp2 *,u*)
Figure BDA0003415569910000097
Figure BDA0003415569910000098
Figure BDA0003415569910000099
Wherein sp1For the initial size of class 1 service providers, sp2For the initial size of class 2 service provider, u1The size of the class 1 service consumer. p is a radical of1Natural growth rate, p, for class 1 service providers2Natural growth rate, q, for class 2 service providers1For the natural growth rate of class 1 service consumers,
Figure BDA00034155699100000910
for the largest size of class 1 service consumers,
Figure BDA00034155699100000911
for the maximum size of a class 2 service provider,
Figure BDA00034155699100000912
for the maximum size of a class 2 service provider,
Figure BDA00034155699100000913
scale sp for class 1 service providers1Size u for class 1 service consumer1The coefficient of action of (a) is,
Figure BDA00034155699100000914
scale sp for class 2 service providers2Size u for class 1 service consumer1The coefficient of action of (a) is,
Figure BDA00034155699100000915
size u for class 1 service consumer1Scale sp for class 1 service providers1The coefficient of action of (a) is,
Figure BDA00034155699100000916
size u for class 1 service consumer1Scale sp for class 2 service providers2The coefficient of action of (a) is,
Figure BDA00034155699100000917
scale sp for class 2 service providers2Scale sp for class 1 service providers1The coefficient of action of (a) is,
Figure BDA00034155699100001011
scale sp for class 1 service providers1Scale sp for class 2 service providers2The coefficient of action of (c).
And S32, calculating the stability of each equilibrium point by adopting a Lyapunov first method based on the Jacobian matrix. If all the eigenvalues of the matrix J are negative, the balance point is stable; if at least one of the eigenvalues of matrix J is positive, it is unstable. Wherein, the Jacobian matrix is specifically as follows:
Figure BDA0003415569910000101
wherein the content of the first and second substances,
Figure BDA0003415569910000102
Figure BDA0003415569910000103
Figure BDA0003415569910000104
Figure BDA0003415569910000105
Figure BDA0003415569910000106
Figure BDA0003415569910000107
Figure BDA0003415569910000108
Figure BDA0003415569910000109
Figure BDA00034155699100001010
the stability at each equilibrium point is: e1Not a stable point, E2Is a balance point between the extinction of two types of service providers and the survival of service consumers, E3And E4Is a balance point where one of the two service providers is alive and the other of the service providers and the service consumer are extinct, E5Is a balance point where both service providers survive and service consumers die, E6And E7Is a balance point where one of the two service providers and the service consumer survive, while the other service provider goes out of service, E8(sp1 *,sp2 *,u*) Is a balance point where two types of service providers and service consumers coexist.
And S4, obtaining an evolution path in the calculation process and the scale of each value co-creation unit when the system reaches a stable state.
The embodiment of the invention fully considers a mesh structure consisting of a plurality of service platforms, service providers and service consumers, explores symbiotic modes and symbiotic conditions of different types of different objects in a service ecosystem by constructing symbiotic evolution models of the plurality of objects based on the extended Logistic model, and can more accurately simulate the service ecosystem so as to accurately obtain required information, such as the evolution process of a value co-creation unit and the scale when the value co-creation unit is stable.
In order to facilitate further understanding of the evolution analysis method of the invention, an example explanation is given below by using a three-class value co-creation unit symbiotic evolution model. For the service ecosystem, when the types of the value co-creation units reach 4, the model calculation amount is huge. To simplify the process without loss of representativeness, the following example simplifies the kinds of value co-creation units involved in the system model as follows. Here, consider that there are only two types of value co-creation units in the service provider: a class A value co-creation unit and a class B value co-creation unit; only one type of value co-creation unit (service consumer with common consumption capability) is considered in the service consumer, and only one value co-creation unit is arranged in the third-party platform.
Specifically, when the types of the service provider value co-creation units are two, the types of the service consumer value co-creation units are one, and the types of the service platform value co-creation units are one, the symbiotic evolution model of each service provider and each service consumer value co-creation unit is as follows:
Figure BDA0003415569910000111
Figure BDA0003415569910000112
Figure BDA0003415569910000113
the symbiotic pattern is shown in table 1:
TABLE 1 value Co-creation Unit Co-occurrence model
Figure BDA0003415569910000114
Figure BDA0003415569910000121
Progressive stability analysis was then performed on the model. First, an equalization point is calculated
E1(0,0,0)
Figure BDA0003415569910000122
Figure BDA0003415569910000123
Figure BDA0003415569910000124
Figure BDA0003415569910000125
Figure BDA0003415569910000126
Figure BDA0003415569910000127
E8(sp1 *,sp2 *,u*)
Figure BDA0003415569910000128
Figure BDA0003415569910000129
Figure BDA00034155699100001210
Next, model stability was analyzed using the leiapunov first method using the jacobian matrix. Seven equilibrium points and their stability analysis are shown in table 2:
TABLE 2 seven equilibrium points and stability analysis thereof
Figure BDA0003415569910000131
For the equalization point E8(sp1*,sp2U), transforming the formula symbiotic evolution model into a formula:
Figure BDA0003415569910000132
Figure BDA0003415569910000133
Figure BDA0003415569910000134
it can be derived that:
Figure BDA0003415569910000135
when | A |<0 and sp1*>0,sp2*>0,u*>At 0, it is stable. From this, E can be derived8The stable conditions were:
Figure BDA0003415569910000136
on the basis of the above embodiments, in an optional embodiment of the present invention, the evolution analysis method further includes step S5.
S5, obtaining evolution processes among various value co-creation units corresponding to different co-occurrence coefficients based on Runge-Kutta algorithm, and scales of the value co-creation units when systems corresponding to different market scale capacities reach a stable state.
Specifically, parameters affecting the evolution process and the final scale of each value co-creation unit can be obtained through the step S5. Therefore, the method makes reference to the marketing strategy made by each symbiotic unit and has good practical significance.
More specifically:
a famous automobile brand has a nationwide large market, and an Internet of vehicles service ecosystem comprising a service provider, a service consumer and a third-party service platform is developed on the basis of services such as traditional 4S shop sales, maintenance and the like. In the system, the service providers comprise equivalent value co-creation units of an automobile sales service provider, an automobile owner traffic and life service provider, an automobile insurance service provider and a vehicle maintenance service provider, the service consumers comprise equivalent value co-creation units of common consumers, advanced service consumers and VIP service consumers, and the third-party service platform comprises a value co-creation unit of the Internet of vehicles service platform.
In the symbiotic evolution process of all types of value co-creation units of the service ecosystem, only two types of service providers (each comprising service provider individuals with different scale quantities), one type of service consumers (each comprising service consumer individuals with different scale quantities) and a third-party service platform are considered in the numerical simulation experiment later. Service providers include two types of value co-creation units: insurance type service provider and vehicle maintenance service provider, the service consumer includes a type of value co-creation unit: the common service consumer only has one value co-creation unit of the third-party service platform, namely the Internet of vehicles service platform.
Under different symbiotic modes and symbiotic action coefficients, the symbiotic evolution track and rule of the value co-creation unit can be more intuitively reflected through numerical simulation and visual display, so that a relevant conclusion is obtained. The natural growth rates of the insurance type value co-creation units, the vehicle maintenance type value co-creation units and the common service consumer value co-creation units are respectively assumed as follows: 0.1, 0.15, 0.2; the initial scale was 100. Under a certain resource environment, the three-party development scale is 1000, and the evolution period is 800. By exploring the relationship between symbiotic effect coefficients, the evolution process, the path and the influence factors of the service ecosystem are obtained.
In the following, how the value co-creation units act and co-evolution under different values of the co-creation coefficients, and the influence of factors such as market scale capacity on the scale stability point are discussed.
Firstly, symbiotic mode analysis is carried out, and the influence of factors such as how value co-creation units act and symbiotic evolution under different values of symbiotic action coefficients and the influence of factors such as market scale capacity on scale stability points are discussed
In the present specific case, it is preferred that,
Figure BDA0003415569910000151
representing the symbiotic coefficient influence of common service consumers on the insurance value co-creation unit,
Figure BDA0003415569910000152
shows the influence of the symbiotic coefficient of the vehicle maintenance value co-creation unit on the insurance value co-creation unit,
Figure BDA0003415569910000153
representing the symbiotic coefficient influence of common service consumers on the vehicle maintenance value co-creation unit,
Figure BDA0003415569910000154
shows the influence of the symbiotic coefficient of the insurance value co-creation unit on the vehicle maintenance value co-creation unit,
Figure BDA0003415569910000155
representing the sharing of insurance-like value co-creation units to common service consumersThe generation coefficient is generated by the generator and the generator,
Figure BDA0003415569910000156
and the symbiotic coefficient of the vehicle maintenance type value co-creation unit to the common service consumer is represented.
As shown in fig. 3, when the service ecosystem is in the independent symbiotic mode, the symbiotic coefficient between the value co-creation units is zero, i.e.,
Figure BDA0003415569910000157
Figure BDA0003415569910000158
as shown in FIG. 3, three types of value co-creation units are independently increased from the initial scale to the maximum scale.
As shown in fig. 4, when the service ecosystem is in the normal competitive symbiosis mode and the symbiotic coefficient range is (-1, 0), the evolution paths of the value co-creation units are basically consistent, and the final scale stable points of the three value co-creation units are consistent. In the competitive symbiosis mode, the larger the absolute value of the symbiotic action coefficient is, the smaller the final scale stable equilibrium point is, the slower the evolution speed is, and the longer the final scale stable evolution time is.
As shown in fig. 5, when the service ecosystem is in the malignant competition symbiotic mode, the symbiotic coefficient is in the (-1- ∞) interval, which is the evolution of the malignant competition symbiotic mode. In the value co-creation units, at least one value co-creation unit evolves to gradually increase and finally reaches the trend of a stable state, and the final stable value is the maximum scale; at least one value co-creation unit is greatly inhibited from evolving, and tends to grow and weaken, and finally dies up.
As shown in fig. 6, when the service ecosystem is in the parasitic symbiotic mode, the symbiotic coefficients between any two kinds of the value co-creation units are opposite numbers, the parasitic value co-creation unit resources are consumed, the final stable scale is smaller than the maximum scale, the parasitic value co-creation unit benefits from the parasitic value co-creation unit, and the final stable scale is higher than the maximum scale under independent symbiosis. In the mode, more resources are needed among the value co-creation units, and the value sharing further promotes the symbiotic evolution, so that the system benefit maximization is realized. In the parasitic mode, the larger the absolute value of the co-occurrence coefficient, the larger the final stable value of the parasitic value co-creation unit.
As shown in fig. 7, when the service ecosystem is in the partial interest symbiosis mode, the symbiosis coefficients between any two types of value co-creation units are one zero and the other is greater than zero. Under the partial interest symbiosis mode, along with the increase of the symbiotic action coefficient, the evolution paths of the value co-creation units are basically consistent (gradually increased firstly, and are kept stable after reaching the maximum value), but the respective reached stable values are different; the larger the symbiotic effect coefficient is, the faster the symbiotic evolution speed is, and the larger the scale value to reach a stable state is.
As shown in fig. 8, when the service ecosystem is in the mutual-benefit mode, the mutual-benefit coefficient between any two populations is positive, and the final stable state of the population is larger than the maximum independent development scale. The symbiotic coefficient of the interaction of the three value co-creation units is larger than zero, the scale growth of any one part benefits from the other two main bodies, the stable value of the main body scale exceeds the maximum scale value of independent development, and the final stable point is E8(sp1 *,sp2 *,u*). Under the mutual-benefit mutual-generation symbiosis mode, the larger the symbiosis coefficient is, the larger the final scale stable equilibrium point is. According to simulation results in different symbiotic modes, symbiotic evolution of the service ecosystem value co-creation units is related to the symbiotic action coefficient. Under the mutual-benefit and mutual-benefit symbiosis mode, the final stable scale of the co-creation unit is the largest, and the co-creation unit is the best direction for symbiotic evolution of the service ecosystem.
And then carrying out simulation analysis on the relevant factors. Based on a reciprocal and mutual benefit symbiotic mode, the influence of the natural growth rate of the value co-creation unit, the initial scale of the value co-creation unit and the market capacity scale of the value co-creation unit on symbiotic evolution is explored.
As shown in fig. 9, in the mutualistic symbiotic mode, when the natural growth rate increases, the final stable scale does not change. This can result in: the symbiotic evolution stable point of the value co-creation unit is irrelevant to the natural growth rate of the value co-creation unit.
As shown in fig. 10, in the mutualistic symbiotic mode, when the initial scale is increased, the final stable scale is not changed, and it can be seen from the figure that the larger the initial scale is, the faster the evolution rate is. This can result in: the symbiotic evolution stable point of the value co-creation unit is independent of the initial scale of the value co-creation unit, and the larger the initial scale is, the faster the symbiotic evolution speed is.
As shown in fig. 11, the symbiotic evolution stability point of the value co-creation units is related to the market-scale capacity thereof, and the larger the market-scale capacity of each type of value co-creation unit is, the larger the stability-scale value is.
Aiming at a service ecosystem consisting of a plurality of third-party service platforms, a plurality of service providers and a plurality of service consumers, the embodiment of the invention adopts an expanded Logistic model to establish a symbiotic evolution model of different-value co-creation units, adopts a Jacobian matrix to analyze the equilibrium point and the stable condition of the symbiotic evolution model reaching balance, and analyzes the influence of relevant factors such as symbiotic coefficient, market scale capacity and the like on symbiotic evolution through numerical simulation. Therefore, an accurate and effective data basis is provided for enterprises to formulate business strategies, pricing strategies and the like, and the method has good practical significance.
Example II,
As shown in fig. 12, an evolution analysis apparatus for a service ecosystem according to an embodiment of the present invention includes:
the acquisition module 1 is used for acquiring initial information of the service ecosystem. The service ecosystem comprises a service provider, a service consumer and a service platform, and the initial information comprises an action coefficient of the service ecosystem and initial scale, scale capacity and natural growth rate of the service provider, the service consumer and the service platform.
And the construction module 2 is used for constructing a symbiotic evolution model based on the differential model of the Logistic basic model according to the initial information. The symbiotic evolution model comprises a service provider symbiotic evolution model, a service consumer symbiotic evolution model and a service platform symbiotic evolution model.
And the calculating module 3 is used for calculating the stability of the symbiotic evolution model by adopting a Lyapunov first method based on the Jacobian matrix.
And the result module 4 is used for acquiring an evolution path in the calculation process and the final scale of the service ecosystem in the stable process.
Example III,
An embodiment of the present invention provides an evolution analysis device for a service ecosystem, which includes a processor, a memory, and a computer program stored in the memory. The computer program is executable by a processor to implement a method of evolution analysis of a service ecosystem as in any of the paragraphs of the first aspect.
Example four,
An embodiment of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program, where when the computer program runs, a device in which the computer-readable storage medium is located is controlled to execute the method for evolution analysis of a service ecosystem according to any section of the first aspect.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. An evolution analysis method of a service ecosystem, comprising:
acquiring initial information of a service ecosystem; the service ecosystem comprises a service provider value co-creation unit, a service consumer value co-creation unit and a service platform value co-creation unit, wherein the initial information comprises a symbiotic action coefficient, an initial scale, market scale capacity and a natural growth rate of each value co-creation unit;
constructing a symbiotic evolution model of interaction of all value co-creation units based on a differential equation of the extended Logistic basic model according to the initial information; the symbiotic evolution model comprises a service provider value co-creation unit symbiotic evolution model, a service consumer value co-creation unit symbiotic evolution model and a service platform value co-creation unit symbiotic evolution model;
calculating and analyzing the progressive stability of the symbiotic evolution model by adopting a Lyapunov first method based on a Jacobian matrix;
and acquiring an evolution process in the calculation process and the scale of each value co-creation unit when the system reaches a stable state.
2. The evolution analysis method of a service ecosystem according to claim 1, further comprising:
based on Runge-Kutta algorithm, obtaining the evolution process between various value co-creation units corresponding to different co-creation coefficients and the scale of each value co-creation unit when the system corresponding to different market scale capacities reaches a stable state.
3. The evolution analysis method of the service ecosystem according to claim 1, wherein the differential equation of the extended Logistic basic model is:
Figure FDA0003415569900000011
N(t0)＝N0
wherein N (t) represents the population size of the study subject in the t-th period, a represents the natural growth rate of the study subject population,
Figure FDA0003415569900000021
representing the hindering effect of limited resources on the growth of the research subject's own scale, N*Represents the maximum environmental capacity, N, of the study subject due to resource density constraints0Is the initial population scale;
the symbiotic evolution model of the service provider value co-creation units comprises the following steps:
Figure FDA0003415569900000022
wherein N is the number of types of service provider type value co-creation units, piNatural growth rate, sp, for class i service providersiFor the initial size of the class i service provider,
Figure FDA0003415569900000023
for the largest size of class i service providers,
Figure FDA0003415569900000024
size sp representing the size of various types of service consumers versus the size of the i-th type of service provideriThe effect of growth, M is the number of categories of service consumers,
Figure FDA0003415569900000025
size u for class j service consumerjSize sp for class i service provideriCoefficient of action of ujFor the initial size of class j service consumers,
Figure FDA00034155699000000210
for the largest size of class j service consumers,
Figure FDA0003415569900000026
size sp of class i service provider for other class service providersiThe influence of (a);
Figure FDA0003415569900000027
scale sp for class s service providersSize sp for class i service provideriCoefficient of action of, spsThe initial size of the class s service provider,
Figure FDA0003415569900000028
maximum size of class s service providers.
4. The evolution analysis method of the service ecosystem according to claim 3, wherein the service consumer value co-creation unit symbiotic evolution model is:
Figure FDA0003415569900000029
wherein M is the number of service consumers' categories, qjNatural growth rate for class j service consumers, ujFor the initial size of class j service consumers,
Figure FDA0003415569900000031
for the largest size of class j service consumers,
Figure FDA0003415569900000032
representing the size of each type of service provider versus the size u of the jth service consumerjThe effect of the growth, N is the number of service provider categories,
Figure FDA0003415569900000033
scale sp for class i service provideriSize u for class j service consumerjCoefficient of action of, spiFor the initial size of the class i service provider,
Figure FDA0003415569900000034
the maximum size of the class i service provider.
5. The evolution analysis method of the service ecosystem according to claim 3, wherein the service platform value co-creation unit symbiotic evolution model is:
Figure FDA0003415569900000035
wherein X is the number of kinds of service platforms, mzNatural growth rate for class z service platforms, cdzFor the initial size of the class z service platform,
Figure FDA0003415569900000036
for the maximum size of class z service platforms,
Figure FDA0003415569900000037
scale cd representing scales of various types of service consumers versus class z service platformszThe effect of growth of; m is the number of categories of service consumers,
Figure FDA0003415569900000038
size u for class j service consumerjScale cd for class z service platformszCoefficient of action of ujFor the initial size of class j service consumers,
Figure FDA0003415569900000039
for the largest size of class j service consumers,
Figure FDA00034155699000000310
scale cd representing scale of various types of service providers versus class z service platformszThe effect of growth of; n is the number of categories of service providers,
Figure FDA00034155699000000311
scale sp for class i service provideriScale cd for class z service platformszCoefficient of action of, spiFor the initial size of the class i service provider,
Figure FDA00034155699000000312
for class i service providersThe maximum size of the (c) is,
Figure FDA00034155699000000313
scale cd for class z service platforms for other classes of service platformszThe influence of (a) on the performance of the device,
Figure FDA00034155699000000314
scale cd for class y service platformsyScale cd for class z service platformszCoefficient of action of, cdyFor the initial size of the class y service platform,
Figure FDA0003415569900000041
the maximum size of the y-th service platform.
6. The evolution analysis method of the service ecosystem according to any one of claims 1 to 5, wherein when the service provider value co-creation units are of two kinds, the service consumer value co-creation units are of one kind, and the service platform value co-creation units are of one kind, the symbiotic evolution model of each service provider and service consumer value co-creation unit is as follows:
Figure FDA0003415569900000042
Figure FDA0003415569900000043
Figure FDA0003415569900000044
the method comprises the following steps of calculating and analyzing the gradual stability of the symbiotic evolution model by adopting a Lyapunov first method based on a Jacobian matrix, and specifically comprises the following steps:
carrying out progressive stability analysis on the model and calculating to obtainTo the equilibrium point; wherein the equilibrium point of the symbiotic evolution model comprises E1、E2、E3、E4、E5、E6、E7And E8；
E1(0,0,0)
Figure FDA0003415569900000045
Figure FDA0003415569900000046
Figure FDA0003415569900000047
Figure FDA0003415569900000048
Figure FDA0003415569900000049
Figure FDA00034155699000000410
E8(sp1 *,sp2 *,u*)
Figure FDA0003415569900000051
Figure FDA0003415569900000052
Figure FDA0003415569900000053
Wherein sp1For the initial size of class 1 service providers, sp2For the initial size of class 2 service provider, u1Initial size for category 1 service consumer; p is a radical of1Natural growth rate, p, for class 1 service providers2Natural growth rate, q, for class 2 service providers1For the natural growth rate of class 1 service consumers,
Figure FDA0003415569900000054
for the largest size of class 1 service consumers,
Figure FDA0003415569900000055
for the maximum size of a class 2 service provider,
Figure FDA0003415569900000056
for the maximum size of a class 2 service provider,
Figure FDA0003415569900000057
scale sp for class 1 service providers1Size u for class 1 service consumer1The coefficient of action of (a) is,
Figure FDA0003415569900000058
scale sp for class 2 service providers2Size u for class 1 service consumer1The coefficient of action of (a) is,
Figure FDA0003415569900000059
size u for class 1 service consumer1Scale sp for class 1 service providers1The coefficient of action of (a) is,
Figure FDA00034155699000000510
size u for class 1 service consumer1Scale sp for class 2 service providers2The coefficient of action of (a) is,
Figure FDA00034155699000000511
scale sp for class 2 service providers2Scale sp for class 1 service providers1The coefficient of action of (a) is,
Figure FDA00034155699000000512
scale sp for class 1 service providers1Scale sp for class 2 service providers2The coefficient of action of (c).
7. The evolution analysis method of the service ecosystem according to claim 6, wherein the gradual stability of the symbiotic evolution model is calculated and analyzed by using a Lyapunov first method based on the Jacobian matrix, further comprising:
calculating the stability of each balance point by adopting a Lyapunov first method based on a Jacobian matrix; wherein the jacobian matrix specifically is:
Figure FDA0003415569900000061
wherein the content of the first and second substances,
Figure FDA0003415569900000062
Figure FDA0003415569900000063
Figure FDA0003415569900000064
Figure FDA0003415569900000065
Figure FDA0003415569900000066
Figure FDA0003415569900000067
Figure FDA0003415569900000068
Figure FDA0003415569900000069
Figure FDA00034155699000000610
the stability at each equilibrium point is: e1Not a stable point, E2Is a balance point between the extinction of two types of service providers and the survival of service consumers, E3And E4Is a balance point where one of the two service providers is alive and the other of the service providers and the service consumer are extinct, E5Is a balance point where both service providers survive and service consumers die, E6And E7Is a balance point where one of the two service providers and the service consumer survive, while the other service provider goes out of service, E8(sp1 *,sp2 *,u*) Is a balance point where two types of service providers and service consumers coexist.
8. An evolution analysis apparatus of a service ecosystem, comprising:
the acquisition module is used for acquiring initial information of the service ecosystem; the service ecosystem comprises a service provider value co-creation unit, a service consumer value co-creation unit and a service platform value co-creation unit, wherein the initial information comprises a symbiotic action coefficient, an initial scale, market scale capacity and a natural growth rate of each value co-creation unit;
the construction module is used for constructing a symbiotic evolution model of interaction of all the value co-creation units based on a differential equation of the extended Logistic basic model according to the initial information; the symbiotic evolution model comprises a service provider value co-creation unit symbiotic evolution model, a service consumer value co-creation unit symbiotic evolution model and a service platform value co-creation unit symbiotic evolution model;
the calculation module is used for calculating and analyzing the gradual stability of the symbiotic evolution model by adopting a Lyapunov first method based on a Jacobian matrix;
and the result module is used for acquiring the evolution process in the calculation process and the scale of each value co-creation unit when the system reaches a stable state.
9. An evolution analysis device of a service ecosystem, comprising a processor, a memory, and a computer program stored in the memory; the computer program is executable by the processor to implement the evolution analysis method of the service ecosystem as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, comprising a stored computer program, wherein the computer program, when executed, controls an apparatus in which the computer-readable storage medium is located to perform the evolution analysis method of the service ecosystem according to any one of claims 1 to 7.
CN202111544868.4A 2021-12-16 2021-12-16 Evolution analysis method, device, equipment and storage medium of service ecosystem Pending CN114202451A (en)

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