Research on the Symbiotic Model of Supply Chains Based on the Logistic Expansion Model for E-Commerce Platforms

Abstract

With the development of globalization and technology, e-commerce platforms provide a more convenient shopping experience while also increasing the complexity and difficulty of the supply chain. Managers of e-commerce platform operations need to think about and investigate how to optimize the supply chains of e-commerce platforms, reduce costs and improve efficiency. In this paper, we use the logistic population expansion model to explore the symbiotic relationship among the core populations, key populations and supporting populations within the supply chain ecosystem of e-commerce platforms and the conditions that affect the evolution direction of the symbiotic model. The results show the following: (1) The size of the symbiosis between the three types of populations determines the equilibrium state of the symbiotic evolution of the e-commerce platform supply chain ecosystem. (2) The value of the sum of the symbiotic interaction coefficients between subjects in the supply chain ecosystem of an e-commerce platform determines the result of the symbiotic evolution of the system. (3) The reciprocal symbiosis model can maximize the synergy of the three types of subjects and is the best goal direction for ecosystem evolution. This study can provide a theoretical basis and practical support for the development of e-commerce platform-related enterprises.

1. Introduction

By the end of 2022, the total number of Internet users in China reached 1.067 billion, the proportion of online shopping users among all users reached 80%, and the national e-commerce transaction volume reached 43.83 trillion CNY, an increase of 3.5% year-on-year. With the development of modern technology and the popularity of the Internet, e-commerce has become an integral part of people’s daily lives. Large e-commerce companies have not only provided consumers with more convenient ways to shop but also promoted the globalization and digitization of goods and services. However, the rapid growth of the e-commerce industry has also brought unprecedented challenges to supply chain management.

Platform ecosystems are another paradigm revolution of business ecosystem innovation in the era of digital economy, which brings changes in efficiency, governance and innovation to human society and productive life, and platform ecosystems are also accelerating in how they are embedded into society and influence society. With the platform as the support, the whole end of the supply chain is constantly upgraded. The e-commerce platform gradually becomes the typical model of the platform supply chain, and the supply chain is developed to a new stage of gradual integration with the platform economy. According to our data on policy advocacy and transactions on e-commerce platforms, the ongoing development of the e-commerce platform is a future trend. However, there are also issues in the e-commerce platform supply chain. For example, e-commerce platforms for integrating the supply chain of information resources have a certain information leakage potential, a logistics enterprise synergy problem and a synergy problem between diversified platforms, and the relationships among the subjects on the supply chains of e-commerce platforms need to be integrated, optimized, and coordinated to solve these problems. Therefore, the study of what kind of competing relationship exists between various groups within the supply chain ecosystem of e-commerce platforms and what kind of law they will follow to evolve has become a popular topic and focus of current research.

The platform supply chain ecosystem is similar to the natural ecosystem evolution. The evolutionary process of the platform supply chain ecosystem is a dynamic display of the concurrent relationship between different groups of members within the system. This dynamic evolutionary process is similar to the symbiotic evolutionary process of biological populations in nature. According to the concept of symbiotic evolution proposed by Ehrlich and Raven [1] in 1964, although competitive relationships among biological populations are the fundamental driving force for their developmental progress, symbiotic evolution among populations is also prevalent in biology, as a stable growth of population size is maintained through symbiotic cooperation among populations. With the interaction of various group members in the ecosystem of the e-commerce platform supply chain, various group members progressively exhibit the biological “symbiosis”. The symbiosis theory is used mainly to represent the symbiotic relationship between populations and the environment resource in a certain mode [2]. The application scope of symbiosis theory continues to expand, which has a significant meaning in the study of supply chain management. Meanwhile, cooperation and competition among populations is the core driving force for the sustainable development of e-commerce platform supply chain ecosystems. Therefore, the process of the generation, development and evolution of the e-commerce platform supply chain ecosystem can be seen more clearly from the perspective of symbiosis theory. Through a combination of the research on the symbiotic evolution of the supply chain of e-commerce platforms in recent years, it can be found that the current research is mostly focused on the following three aspects.

The first aspect is the green design of the e-commerce platform supply chain. By nature, the ecosystem of the e-commerce platform supply chain is similar to the biological community, which is an organic whole with internal subjects competing and cooperating with each other and interacting with the external environment, so it becomes crucial to clarify the internal and external relations of the ecosystem. A platform supply chain ecosystem was constructed to clarify the internal organizational composition of the system and explore the internal member collaboration mechanism [3,4], multiple platform supply chain ecosystems were analyzed to clarify the important clusters in the system [5], and the internal and external influencing factors of the platform supply chain constituted by the important clusters were analyzed to build an evaluation system [6] and discuss the sustainable development of the supply chain of the platform [7], which provides theoretical support for the study of the e-commerce platform supply chain ecosystem [8].

The second aspect consists of a survey of statistical learning methodologies for the supply chain of e-commerce platforms. An extremely important part of the platform supply chain requires solving the problem of information asymmetry that exists among internal members and using new technologies to solve the information asymmetry between e-commerce platforms [9,10] and cross-border e-commerce platforms [11,12] to provide the best decision for enterprises. After considering the influence of the external environment on the decision-making of the internal subjects of the system [13], the problem of equilibrium can be solved and equilibrium can be reached within the system by applying digital technology [14,15], deep learning neural networks [16,17] and other technologies to improve the efficiency of the supply chain. On the basis of the ecological perspective, the problem of synergistic cooperation between the platform for cross-border e-commerce and the topics of supply and demand [18] and cross-border logistics companies [19] is resolved.

The third aspect is the study of the evolution and value cocreation of the e-commerce platform supply chain ecosystem from a symbiotic perspective. The symbiotic relationship between the different groups in the ecosystem of the e-commerce platform supply chain is studied on the basis of symbiosis theory. Some researchers first empirically analyzed the symbiotic relationship between e-commerce platforms and logistics firms and emphasized the evolutionary path of their development [20]. After the symbiotic relationships among the members within the ecosystem are understood, the main factors affecting the development of the supply chain of e-commerce platforms are identified through multiple case studies to provide a framework for improving the overall efficiency of the supply chain [21]. With the increasing popularity of emerging technologies, people have begun to implement them to improve the efficiency of the supply chain. In the supply chain of agricultural e-commerce platforms, multichain integration needs to be considered, and digital technology needs to be introduced; moreover, a reasonable distribution mechanism needs to be built to achieve the sustainable development of the supply chain [22]. Through the introduction of blockchain technology into the e-commerce supply chain ecosystem, a more transparent and effective information exchange channel is established [23]. With the continuous development of e-commerce platforms and the gradual emergence of cross-border e-commerce platforms, some scholars have explored the influencing factors within the ecosystem of cross-border e-commerce platforms [24]. Then, the competing relationships among subsystems within the cross-border e-commerce ecosystem are considered to clarify the development and evolutionary process of the system [25]. In studies on the mechanism of the symbiotic evolution of the ecosystem, the value created by the synergistic cooperation between the members of the system provides the impulse for the sustainable development of the ecosystem. The nature of cooperation and competition among platforms and their participants is explored in depth, which in turn promotes sustainable value cocreation in supply chains [26]. After analyzing the impact of relationships among internal members, we consider the impact of cross-network externality on e-commerce platforms and cross-border e-commerce platforms [27] on competitive markets to coordinate cooperation among subjects within the system and subsequently create value together [28,29]. The evolutionary models of platform symbiosis may differ under the guidance of different participants’ decisions, providing additional research perspectives on the development of the e-commerce platform ecosystem [30].

As shown in the current research, scholars at home and abroad have performed rich research on the symbiotic evolution of platform supply chains, approaching this issue from different perspectives, covering comprehensive issues and achieving rich theoretical results. Collectively, the existing symbiotic evolution studies on platform supply chains mainly use evolutionary games to make decisive choices of multiple actors in specific situations and explore the influence between platforms and single organizations in the supply chain based on symbiosis theory. However, the current study is to using those two subjects as the research objects. To date, there is less research on the impact of the competing relationships among three subjects, with the e-commerce platform as the core population, on the symbiotic evolution of the system. Only the two-by-two relationship among the three subjects within the ecosystem has been studied, and the stability of the symbiotic evolutionary model has not been further explored. Thus, the current research on the symbiotic evolution among the three subjects of the supply chain ecosystem of the e-commerce platform remains incomplete. To begin to fill that research gap, this study proceeds with three subjects as the research objects.

In extant research, when analyzing the interaction behavior among populations within the supply chain ecosystem of e-commerce platforms, it is found that the structure is similar to that of natural ecosystems, and both populations are characterized by dynamic evolutionary development of organizational forms due to competition and cooperation. Therefore, to explore the mechanism of symbiotic evolution of populations within the supply chain ecosystem of e-commerce platforms, it becomes possible to draw on the theory of ecosystem evolution in nature. From the perspective of symbiosis theory, the change in the population size of each subject within the supply chain ecosystem of an e-commerce platform will be constrained by external environmental factors such as resources, technology and policies, and this evolution law is consistent with the logistic growth law in ecology. Therefore, a logistic population expansion model is used in this paper to study in depth the symbiotic relationship among three populations within the ecosystem of the e-commerce platform supply chain, as well as the conditions that affect the evolution direction of the symbiotic pattern. Finally, through MATLAB simulation analysis, corresponding policy recommendations are proposed to promote the development of the supply chain ecosystem of e-commerce platforms toward a mutually beneficial symbiosis model of three subjects.

2. The Current Situation of Supply Chain of E-Commerce Platform

An e-commerce platform supply chain is a complex ecosystem based on the Internet that coordinates the information flow, logistics and capital flow among business organizations in the supply chain. Currently, the Chinese government continues to introduce financial policies to accelerate the application of e-commerce platforms for small and medium-sized enterprises, while in the online shopping market, enterprises increase the utility of mobile websites and the rapid development of mobile shopping, and continue to promote the overall development of e-commerce platform supply chains.

According to the Ministry of Commerce data between 2011 and 2022, e-commerce transactions in China continued to grow, and by 2022, as shown in Figure 1, national e-commerce transactions reached 43.83 trillion CNY, of which online retail sales reached 13.79 trillion CNY, an increase of 4% year-on-year, and physical goods online retail sales reached 11.96 trillion CNY, an increase of 6.2% year-on-year, accounting for 27.2% of the total retail sales of social consumer goods. Retail sales of the national rural network reached 2.17 trillion CNY, an increase of 3.6% year-on-year. Of these, the online retail sales of physical goods in rural areas reached 1.99 trillion CNY, an increase of 4.9% year-on-year. In addition, the cross-border e-commerce platform in China is developing rapidly, gradually showing the brand effect of e-commerce. According to customs data, in 2022, China’s cross-border e-commerce import and export reached 2.11 trillion CNY, an increase of 9.8% year-on-year. Specifically, with exports of 1.55 trillion CNY, increasing up 11.7% year-on-year, imports of 0.56 trillion CNY, increasing up 4.9% year-on-year, and cross-border e-commerce partners including Japan, the United States, Australia, the Netherlands, Spain, Germany, and the United Kingdom, the e-commerce new business model began to show its vitality.

With the gradual popularization of the Internet in China, the scale of online shopping users is gradually growing. According to data from the China Internet Information Center, the scale of China’s Internet users has been growing rapidly since 2016, and by 2022, China’s online shopping users reached 845 million, accounting for 79.2% of all Internet users, which is the key basis for the development of China’s e-commerce platform supply chain. In terms of China’s e-commerce retail competition, the major e-commerce platforms include JD, Alibaba, Suning, Pinduoduo, Tesco, Vipshop, etc. The annual revenue of 2022 was as follows: JD 745.802 billion CNY, Alibaba 529.894 billion CNY, Suning 252.3 billion CNY, Vipshop 101.9 billion CNY, Pinduoduo 59.492 billion CNY, and Gome 44.119 billion CNY, accounting for 40.84%, 29.02%, 13.82%, 5.58%, 3.26%, and 2.42%, respectively, as shown in Figure 2.

The above data show that the booming economy of e-commerce platforms has promoted the national economy, but the current e-commerce platform is limited by its own economic and technological conditions and is unable to maximize its advantages. If the e-commerce platform developers want to solve its problems, they need to collaborate with other members of the supply chain and utilize its platform effect to attract more members to join the supply chain ecosystem of the e-commerce platform. Therefore, constructing the supply chain ecosystem of the e-commerce platform and analyzing the synergistic symbiosis mechanism among the subjects in the system can provide a certain theoretical basis for the collaborative development of the supply chain of the e-commerce platform, help the e-commerce platform developers to deeply understand the symbiosis mode of the subjects in the ecosystem, solve the conflicts among the subjects in the supply chain of the e-commerce platform, and guarantee the sustainable development of the supply chain of the e-commerce platform.

3. Research Methodology

The logistic growth model is widely used to depict the evolutionary trajectory of agents in symbiotic relationships, and it has good data fit and prediction performance [31]. Based on the theory of ecology, in the ecosystem in the supply chain of the e-commerce platform, all kinds of group changes are subject to the constraints of resources, technology and other factors, which is in line with the logistic growth model in ecology. This model is widely applied to the problem of growth evolution resulting from interactions between system agents within an ecosystem. Therefore, in this paper, we first construct a symbiotic evolution model of two subjects inside the supply chain of e-commerce platforms by drawing on the logistic growth function, analyze the symbiotic pattern between the two subjects. We build a three-subject symbiotic evolution model inside the supply chain ecosystem of e-commerce platforms based on an extension of the logistic growth model as a benchmark model for the later introduction of supply and demand subjects as key populations.

3.1. A Model for the Evolution of Two Subjects in the Supply Chain Ecosystem of E-Commerce Platforms from the Perspective of Symbiosis Theory

The concept of the ecosystem originates from ecology and was first proposed in 1935 by the British scientist Tansley [32], who noted that an ecosystem is a natural system with certain functions and properties characterized by a variety of organisms and the specific environment in which they live in a certain space in nature. Moore [33] later extended this concept to the business arena, introducing the concept of the business ecosystem, which Moore believes consists of seven levels of members: the company itself and its customers, the mall media, the market, suppliers, government, and regulatory agencies. Later, scholars defined the business ecosystem based on interorganizational relationship theory as a dynamic and stable complex system formed by the interaction between organizations and individuals engaged in providing comprehensive and diversified products and services to consumers and between organizations and the business environment within a certain time and space [34], emphasizing the symbiotic evolution of system members on the basis of their competition and cooperation. With the emergence of various new economic forms, such as the platform economy and the digital economy, e-commerce platforms have begun to come to light. The traditional e-commerce platform supply chain is more concerned with the impact of the synergistic relationship between the e-commerce platform and the logistics and finance service companies on the members of the organizations in the supply chain. Many studies have focused on the synergy between companies that provide third-party services and e-commerce platforms. In this study, the members of the e-commerce platform supply chain are divided into different subjects and we explore the symbiotic relationship within the system. Before exploring the multi-subject symbiosis model within the supply chain of the e-commerce platform, the mainstream symbiosis model within the system is analyzed.

3.2. Model Construction

In the initial supply chain of the e-commerce platform, we define the e-commerce platform as the core population and the logistics enterprises as the support population.

Hypothesis 1. 

The growth of the core and support population under the constraints of objective conditions such as resources, technology, and costs is similar to the development and evolution of the natural ecosystem. The size of the two subjects will not increase without limit, and they will experience the process of survival to demise.

Hypothesis 2. 

The change in scale of core and support populations indicates the growth process of both. The scale expansion indicates that the supply chain value creation ability of the e-commerce platform is increasing and the growth is good, while the opposite indicates that its growth is slowing down.

Hypothesis 3. 

The growth process of core and support populations obeys the growth process of logistics. Thus, the logistic model is described as follows.

$$d{x}_1/dt=z_1{x}_1\left(1-x_1/N_1\right),x_1\left(0\right)=x_{10}$$

(1)

$$d{x}_2/dt=z_2{x}_2\left(1-x_2/N_2\right),x_2\left(0\right)=x_{20}$$

(2)

We suppose that x₁ and x₂ are the population sizes of the core and support populations, respectively, and N₁ and N₂ are the maximum values of the population sizes of enterprises within the core and support populations, respectively, under resource constraints. x₁₀ and x₂₀ denote the initial population sizes of the core and support populations, respectively; z₁x₁ and z₂x₂ denote the core population and the supporting population’s development trends, respectively, and 1−x₁/N₁ and 1−x₂/N₂ are logistic coefficients, which represent the retarding effect of the consumption of limited resources by core and supporting populations, respectively, on their population size growth. And the meanings represented by the parameters included in the paper are included in Appendix A.

In real situations, such as natural ecosystems, the growth rate of core and supporting populations in the supply chain of e-commerce platforms is affected not only by the sizes of their populations but also by the sizes of other populations. Therefore, the symbiosis coefficient is introduced to represent the effect of the force of the symbiotic effect of populations on population size. Under symbiotic conditions, the evolutionary dynamics of core and support populations in the supply chain of e-commerce platforms are modeled as follows:

$$d{x}_1/dt=z_1{x}_1\left(1-x_1/N_1+{\alpha }_{12}{x}_2/N_2\right),x_1\left(0\right)=x_{10}$$

(3)

$$d{x}_2/dt=z_2{x}_2\left(1-x_2/N_2+{\alpha }_{21}{x}_1/N_1\right),x_2\left(0\right)=x_{20}$$

(4)

where ${\alpha }_{12}$ and ${\alpha }_{21}$ denote the coefficient of the symbiotic effect of the core population on the supporting population and the coefficient of the symbiotic effect of the supporting population on the core population, respectively. This reflects the change in the direction and intensity of the interaction between the two subjects.

To explore the dynamic evolution law between core and support populations in the supply chain of e-commerce platforms, stability analysis of the set of equations is needed. When $d{x}_1/dt=d{x}_2/dt=0$, four local equilibrium points of the evolution of the two-subject symbiotic model are obtained: E₁(0, 0), E₂(0, N₂), E3(N₁, 0), E4$(\frac{(1+{\alpha }_{12})N_1}{1-{\alpha }_{12}{\alpha }_{21}},\frac{(1+{\alpha }_{12})N_1}{1-{\alpha }_{12}{\alpha }_{21}})$. The Jacobi matrix of its dynamic evolution process is as follows:

$$J_1=\left[\begin{array}{cc}{z}_1(1-\frac{2x_1}{N_1}+{\alpha }_{12}\frac{x_2}{N_2})& \frac{z_1{x}_1{\alpha }_{12}}{N_2}\\ \frac{z_2{x}_2{\alpha }_{21}}{N_1}& z_2(1-\frac{2x_2}{N_2}+{\alpha }_{21}\frac{x_1}{N_1})\end{array}\right]$$

The determinants and traces of the Jacobi matrix are denoted as Det(J) and Tr(J), respectively. When Det(J) > 0 and Tr(J) < 0, the equilibrium point is a stable point [35]. At this point, the system reaches an evolutionary stabilization strategy. The equilibrium condition is shown in

Table 1. Equilibrium point and stability analysis of two-subject symbiotic evolutionary model.

Balancing Point	Det(J)	Tr(J)	Stable Conditions
E1 (0, 0)	$z_1{z}_2$	$z_1+z_2$	Unstable
E2 (0, N2)	$-z_1{z}_2(1+{\alpha }_{12})$	$-z_2+z_1(1+{\alpha }_{12})$	${\alpha }_{12}<-1$
E3 (N1, 0)	$-z_1{z}_2(1+{\alpha }_{21})$	$-z_1+z_2(1+{\alpha }_{21})$	${\alpha }_{21}<-1$
$E_4=(\frac{(1+{\alpha }_{12})N_1}{1-{\alpha }_{12}{\alpha }_{21}},\frac{(1+{\alpha }_{12})N_1}{1-{\alpha }_{12}{\alpha }_{21}})$	$\frac{z_1{z}_2(1+{\alpha }_{12})(1+{\alpha }_{21})}{1-{\alpha }_{12}{\alpha }_{21}}$	$\frac{z_1(-1-{\alpha }_{12})+z_2(-1-{\alpha }_{21})}{1-{\alpha }_{12}{\alpha }_{21}}$	${\alpha }_{12}>-1,{\alpha }_{21}>-1$

.

The evolution of the symbiotic pattern between the core and support populations depends on the combination of the values of ${\alpha }_{12}$ and ${\alpha }_{21}$: when ${\alpha }_{12}={\alpha }_{21}=0$, the two symbiotic subjects coexist independently, and the core and supporting populations develop independently without any influence between them; when ${\alpha }_{12}>0,{\alpha }_{21}=0$ or ${\alpha }_{12}=0,{\alpha }_{21}>0$, the two symbiotic subjects are in a preferential symbiosis model, and the subject with a positive symbiosis coefficient benefits and the subject with a zero symbiosis coefficient is not affected; when ${\alpha }_{12}{\alpha }_{21}<0$, the two subjects are in a parasitic symbiosis model, the subject with a negative symbiosis coefficient suffers and the subject with a positive symbiosis coefficient benefits; and when ${\alpha }_{12}>0,{\alpha }_{21}>0$, the two symbiotic subjects are in a reciprocal symbiosis model.

4. Three-Subject Symbiotic Evolutionary Model of Core, Key and Support Populations

With the emergence of various new economic forms, such as the platform economy and the digital economy, the supply chain of e-commerce platforms has expanded from providing traditional low-end services to providing comprehensive operational services of five value streams (physical flow, information flow, commercial flow, funds flow, knowledge flow). Gradually, a complex ecosystem of multiple industry clusters interacting with the internal and external environment has developed. E-commerce platform companies collaborate with financial companies, logistics companies and other third-party service providers to create value through industry-to-industry collaboration. Therefore, when we explore the symbiotic relationship between organizations within the supply chain of e-commerce platforms, we should not only consider the symbiotic relationship between e-commerce platforms and logistics enterprises but also explore the ecological structure in the supply chain network of e-commerce platforms. In this way, we promote information sharing, resource matching and value cocreation between e-commerce platforms and enterprises at the supply chain end to realize the upgrading and expansion of the supply chain of e-commerce platforms and provide a basis for the development and growth of both supply and demand sides and other supporting enterprises while also promoting continuous innovation of e-commerce platforms. Figure 3 shows the model of the supply chain ecosystem of e-commerce platforms from a symbiotic perspective.

The symbiotic evolution of the supply chain ecosystem of the e-commerce platform involves a process of mutual influence and interdependence among various groups within the system, populations and the external environment within the system in the process of exchange activities, and the formation of various symbiotic relationships to promote the evolutionary development of the system.

The symbiotic environment of the supply chain ecosystem of the e-commerce platform includes the political environment, technical support, economic environment, social and cultural environment, etc. Through the implementation of reasonable policies and regulatory mechanisms to provide a good symbiotic environment for the sustainable development of the supply chains of e-commerce platforms, the promotion of the deep sustainable development of the supply chain of e-commerce platforms can be accelerated, the overall development of the supply chain ecosystem of e-commerce platforms can be coordinated, and information sharing, resource integration and value cocreation in the supply chain can finally be realized.

In the supply chain ecosystem of the e-commerce platform, the e-commerce platform is the core of the e-commerce platform enterprise, linking suppliers and consumers and incorporating support such as logistics and finance to meet the continuous and in-depth development of the e-commerce platform. In the ecosystem, the symbiotic units are platform companies, supply and demand sides and logistics finance companies. Among these, the e-commerce platform enterprises are the core population in the whole supply chain ecosystem. The e-commerce platform enterprises provide channels and services for information exchange and resource integration for the key populations composed of supply and demand sides and the supporting populations composed of other supporting enterprises and promote synergistic development within the ecosystem to drive the evolution of the e-commerce platform supply chain ecosystem. To sum up, within the ecosystem, we define e-commerce platforms as core populations, supply and demand parties as key populations, and logistics, finance, and third-party service providers as supporting populations. The following are the hypotheses for constructing the symbiosis model of the three-subject supply chain ecosystem of the e-commerce platforms.

Hypothesis 4. 

The supply chain ecosystem of e-commerce platforms is composed of three types of symbiotic subjects: core population, key population and support population. The population size of the three types of symbiotic subjects is constrained by complex external environmental factors such as technology and policies. Similar to the evolutionary development of natural ecosystems, the population size will not grow indefinitely but will experience the process of survival to extinction.

Hypothesis 5. 

The change in size of each of the three types of subjects indicates their growth and evolution process. An increase in the size of symbiotic subjects indicates that the symbiotic subjects are developing better and better and have the highest ability to create value. A decrease in the size of symbiotic subjects indicates that the symbiotic subjects are developing worse and worse and have a lower ability to create value.

Hypothesis 6. 

The symbiotic evolutionary processes of the core, support and key populations all obey the logistical law. Since the growth of all three population sizes is limited by system resources and technology, when the population density scale increases to a certain level, this will lead to a decrease in the population growth rate, and when the marginal output of the population is equal to the marginal input, the growth rate will be zero, and then there is a maximum population size.

Hypothesis 7. 

The natural growth rates of core, key and support populations are determined by their own unique attributes under ideal conditions, and the natural growth rate is unchanged in this paper because the effect of population evolution on the growth rate is ignored.

Under symbiotic conditions, the evolutionary dynamics of core, key and support populations in the supply chain ecosystem of e-commerce platforms are modeled as follows:

$$d{y}_1/dt=r_1{y}_1\left(1-y_1/M_1+{\theta }_{21}{y}_2/M_2+{\omega }_{31}{y}_3/M_3\right),y_1\left(0\right)=y_{10}$$

(5)

$$d{y}_2/dt=r_2{y}_2\left(1-y_2/M_2+{\beta }_{12}{y}_1/M_1+{\omega }_{32}{y}_3/M_3\right),y_2\left(0\right)=y_{20}$$

(6)

$$d{y}_3/dt=r_3{y}_3\left(1-y_3/M_3+{\beta }_{13}{y}_1/M_1+{\theta }_{23}{y}_2/M_2\right),y_3\left(0\right)=y_{30}$$

(7)

We suppose that y₁, y₂ and y₃ are the population sizes of the core, key and support populations, respectively; r₁, r₂ and r₃ are the nature growth rates of the core, key and support populations, respectively; β₁₂ and β₁₃ denote the coefficients of symbiotic effects of core populations on key populations and supporting populations, respectively; θ₂₁ and θ₂₃ denote the coefficients of symbiotic effects of key populations on core populations and supporting populations, respectively; ω₃₁ and ω₃₂ denote the coefficients of symbiotic effects of supporting populations on core populations and key populations, respectively; and M₁, M₂ and M₃ are the maximum values of the population sizes of enterprises within the core, key and support populations, respectively.

Then, we study the symbiotic patterns among various populations in the ecosystem. The symbiotic patterns of the three types of populations in the supply chain ecosystem of e-commerce platforms depend on the different ranges of values of β₁₂, β₁₃, θ₂₁, θ₂₃, ω₃₁, and ω₃₂, as shown in

Table 2. Symbiotic model of supply chain ecosystem of e-commerce platform.

Different Combinations of Values	Symbiotic Model
β12, β13, θ21, θ23, ω31, ω32 = 0	Independent symbiosis model, the three units do not affect each other, independent evolutionary development
β12 + ω32 > 0, β13 + θ23 < 0, θ21 + ω31 < 0; β13 + θ23 >0, β12 + ω32 < 0, θ21 + ω31 < 0; θ21 +ω31 >0, β12 +ω32 < 0, β13 +θ23 < 0; or β12 + ω32 < 0, β13 + θ23 > 0, θ21 + ω31 > 0; β13 + θ23 < 0, β12 + ω32 > 0, θ21 + ω31 > 0; θ21 +ω31 < 0, β12 +ω32 > 0, β13 +θ23 > 0	Parasitic symbiosis model in which for any two symbiotic populations, the sum of the symbiotic coefficients is negative and the sum of the other symbiotic coefficients is positive; or for any two other symbiotic populations, the sum of the symbiotic coefficients is positive and the sum of the symbiotic coefficients is negative
β12 +ω32 > 0, β13 + θ23 = 0, θ21 +ω31 = 0; β13 + θ23 > 0, β12 + ω32 = 0, θ21 + ω31 = 0; θ21 +ω31 > 0, β12 + ω32 = 0, β13 +θ23 = 0; or β12 + ω32 = 0, β13 + θ23 > 0, θ21 + ω31 > 0; β13 + θ23 = 0, β12 + ω32 > 0, θ21 + ω31 > 0; θ21 + ω31 = 0, β12 + ω32 >0, β13 +θ23 > 0,	Preferential symbiosis model, where for any two symbiotic populations, the sum of the symbiotic effects of the any two symbiotic populations is zero, and the other symbiotic population benefits from the sum of the symbiotic effects’ coefficients being positive; or for any two symbiotic populations, the sum of the symbiotic coefficients is positive, and for the other symbiotic population, the symbiotic effects’ coefficients are zero
β12 + ω32 > 0, β13 + θ23 > 0, θ21 + ω31 > 0	When the sum of symbiotic coefficients of any two symbiotic populations is positive and the magnitudes are different, the symbiotic pattern is asymmetric reciprocal symbiosis between the three symbiotic populations; if the magnitudes are the same, it is symmetric reciprocal symbiosis.

.

Therefore, it can be seen that the symbiotic evolution result of the supply chain ecosystem of e-commerce platforms is affected by the symbiotic interaction coefficient. In order to explore the results of symbiotic evolution among the three subjects in the ecosystem, the stability of the equilibrium point of Equations (5)–(7) is analyzed.

When $d{y}_1/dt=0,d{y}_2/dt=0,d{y}_3/dt=0$, eight local equilibrium points of the symbiotic evolution of the three subjects in the ecosystem can be obtained as follows:

$$E_1(0,0,0),E_2(M_1,0,0),E_3(0,M_2,0),E_4(0,0,M_3),E_5(0,\frac{(1+{\omega }_{32})M_2}{1-{\omega }_{32}{\theta }_{23}},\frac{(1+{\theta }_{23})M_3}{1-{\theta }_{23}{\omega }_{32}})$$

$$E_6(\frac{(1+{\omega }_{31})M_1}{1-{\omega }_{31}{\beta }_{13}},0,\frac{(1+{\beta }_{13})M_3}{1-{\beta }_{13}{\omega }_{31}}),E_7(\frac{(1+{\theta }_{21})M_1}{1-{\theta }_{21}{\beta }_{12}},\frac{(1+{\beta }_{12})M_2}{1-{\beta }_{12}{\theta }_{21}},0),E_8(P,O,Q)$$

where

$$P=\frac{-M_1(1+{\beta }_{12}+{\omega }_{32}+{\omega }_{31}{\beta }_{12}+{\omega }_{32}{\beta }_{13}-{\omega }_{31}{\beta }_{13})}{{\theta }_{21}{\beta }_{12}+{\omega }_{31}{\beta }_{13}+{\omega }_{32}{\theta }_{23}+{\theta }_{21}{\omega }_{32}{\beta }_{13}+{\omega }_{31}{\beta }_{12}{\theta }_{23}-1},O=\frac{-M_2(1+{\beta }_{12}+{\omega }_{32}+{\omega }_{31}{\beta }_{12}+{\omega }_{32}{\beta }_{13}-{\omega }_{31}{\beta }_{13})}{{\theta }_{21}{\beta }_{12}+{\omega }_{31}{\beta }_{13}+{\omega }_{32}{\theta }_{23}+{\theta }_{21}{\omega }_{32}{\beta }_{13}+{\omega }_{31}{\beta }_{12}{\theta }_{23}-1}$$

$$Q=\frac{-M_3(1+{\beta }_{13}+{\theta }_{23}+{\theta }_{21}{\beta }_{13}+{\beta }_{12}{\theta }_{23}-{\theta }_{21}{\beta }_{12})}{{\theta }_{21}{\beta }_{12}+{\omega }_{31}{\beta }_{13}+{\omega }_{32}{\theta }_{23}+{\theta }_{21}{\omega }_{32}{\beta }_{13}+{\omega }_{31}{\beta }_{12}{\theta }_{23}-1}$$

The Jacobi matrix of its dynamic evolution process is as follows:

$$J_2=\left[\begin{array}{ccc}A& \frac{r_1{y}_1{\theta }_{21}}{M_2}& \frac{r_1{y}_1{\omega }_{31}}{M_3}\\ \frac{r_2{y}_2{\beta }_{12}}{M_1}& B& \frac{r_2{y}_2{\omega }_{32}}{M_3}\\ \frac{r_3{y}_3{\beta }_{13}}{M_1}& \frac{r_3{y}_3{\theta }_{23}}{M_2}& C\end{array}\right]$$

where

$$A=\left(r_1(1-\frac{2y_1}{M_1}+\frac{{\theta }_{21}{y}_2}{M_2}+\frac{{\omega }_{31}{y}_3}{M_3}\right),B=\left(r_2(1-\frac{2y_2}{M_2}+\frac{{\beta }_{12}{y}_1}{M_1}+\frac{{\omega }_{32}{y}_3}{M_3}\right),C=\left(r_3(1-\frac{2y_3}{M_3}+\frac{{\beta }_{13}{y}_1}{M_1}+\frac{{\theta }_{23}{y}_2}{M_2}\right)$$

The determinants and traces of the Jacobi matrix are denoted as Det(J) and Tr(J), respectively. When Det(J) > 0 and Tr(J) < 0, the equilibrium point is a stable point. At this point, the ecosystem reaches an evolutionary stabilization strategy. The equilibrium condition is shown in

Table 3. Equilibrium points and stability analysis of the three-subject symbiotic model.

Balancing Point	Det(J)	Tr(J)	Stable Condition
E1	$r_1{r}_2{r}_3$	$r_1+r_2+r_3$	Unstable
E2	$-r_1{r}_2{r}_3(1+{\beta }_{12})(1+{\beta }_{13})$	$-r_1+r_2(1+{\beta }_{12})+r_3(1+{\beta }_{13})$	$(1+{\beta }_{12})(1+{\beta }_{12})<0$
E3	$-r_1{r}_2{r}_3(1+{\theta }_{21})(1+{\theta }_{23})$	$-r_2+r_1(1+{\theta }_{21})+r_3(1+{\theta }_{23})$	$(1+{\theta }_{21})(1+{\theta }_{23})<0$
E4	$-r_1{r}_2{r}_3(1+{\omega }_{31})(1+{\omega }_{32}$	$-r_3+r_1(1+{\omega }_{31})+r_2(1+{\omega }_{32})$	$(1+{\omega }_{31})(1+{\omega }_{32})<0$
E5	$-r_1{r}_2{r}_3(1+\frac{{\theta }_{21}(1+{\omega }_{32})+{\omega }_{31}(1+{\theta }_{23})}{1-{\omega }_{32}{\theta }_{23}})(\frac{1+{\omega }_{32}}{1-{\omega }_{32}{\theta }_{23}})(\frac{1+{\theta }_{23}}{1-{\omega }_{23}{\theta }_{32}})$	$r_1(1+\frac{{\theta }_{21}(1+{\omega }_{32})+{\omega }_{31}(1+{\theta }_{23})}{1-{\omega }_{32}{\theta }_{23}})-r_2(\frac{1+{\omega }_{32}}{1-{\omega }_{32}{\theta }_{23}})-r_3(\frac{1+{\theta }_{23}}{1-{\theta }_{23}{\omega }_{32}})$	$(1+\frac{{\theta }_{21}(1+{\omega }_{32})+{\omega }_{31}(1+{\theta }_{23})}{1-{\omega }_{32}{\theta }_{23}})(\frac{1+{\omega }_{32}}{1-{\omega }_{32}{\theta }_{23}})(\frac{1+{\theta }_{23}}{1-{\omega }_{32}{\theta }_{23}})<0$
E6	$-r_1{r}_2{r}_3(\frac{1+{\omega }_{31}}{1-{\omega }_{31}{\beta }_{13}})(1+\frac{{\beta }_{12}(1+{\omega }_{31})+{\omega }_{32}(1+{\beta }_{13})}{1-{\omega }_{31}{\beta }_{13}})(\frac{1+{\beta }_{13}}{1-{\omega }_{31}{\beta }_{13}})$	$-r_1(\frac{1+{\omega }_{31}}{1-{\omega }_{31}{\beta }_{13}})+r_2(1+\frac{{\beta }_{12}(1+{\omega }_{31})}{1-{\omega }_{31}{\beta }_{13}}+\frac{{\omega }_{32}(1+{\beta }_{13})}{1-{\omega }_{31}{\beta }_{13}})-r_3(\frac{1+{\beta }_{13}}{1-{\omega }_{31}{\beta }_{13}})$	$(\frac{1+{\omega }_{31}}{1-{\omega }_{31}{\beta }_{13}})(1+\frac{{\beta }_{12}(1+{\omega }_{31})+{\omega }_{32}(1+{\beta }_{13})}{1-{\omega }_{31}{\beta }_{13}})(\frac{1+{\beta }_{13}}{1-{\omega }_{31}{\beta }_{13}})<0$
E7	$-r_1{r}_2{r}_3(\frac{1+{\theta }_{21}}{1-{\theta }_{21}{\beta }_{12}})(\frac{1+{\beta }_{12}}{1-{\beta }_{12}{\theta }_{21}})(1+\frac{{\beta }_{13}(1+{\theta }_{21})+{\theta }_{23}(1+{\beta }_{12})}{1-{\beta }_{12}{\theta }_{21}})$	$-r_1(\frac{1+{\theta }_{21}}{1-{\theta }_{21}{\beta }_{12}})-r_2(\frac{1+{\beta }_{12}}{1-{\beta }_{12}{\theta }_{21}})+r_3(1+\frac{{\beta }_{13}(1+{\theta }_{21})}{1-{\theta }_{21}{\beta }_{12}}+\frac{{\theta }_{23}(1+{\beta }_{12})}{1-{\beta }_{12}{\theta }_{21}})$	$(\frac{1+{\theta }_{21}}{1-{\beta }_{12}{\theta }_{21}})(\frac{1+{\beta }_{12}}{1-{\beta }_{12}{\theta }_{21}})(1+\frac{{\beta }_{13}(1+{\theta }_{21})+{\theta }_{23}(1+{\beta }_{12})}{1-{\beta }_{12}{\theta }_{21}})<0$
E8	H	I	J < 0
$\begin{array}{c}H=\frac{-r_1{r}_2{r}_3(1+{\omega }_{31}+{\theta }_{21}+{\theta }_{21}{\omega }_{32}+{\omega }_{31}{\theta }_{23}-{\omega }_{32}{\theta }_{23})(1+{\omega }_{32}+{\beta }_{12}+{\omega }_{32}{\beta }_{13}+{\omega }_{32}{\beta }_{13}-{\omega }_{31}{\beta }_{13})(1+{\theta }_{23}+{\beta }_{13}+{\theta }_{21}{\beta }_{13}+{\beta }_{12}{\theta }_{23}-{\theta }_{21}{\beta }_{12})}{{\theta }_{21}{\beta }_{12}+{\omega }_{31}{\beta }_{13}+{\omega }_{32}{\theta }_{23}+{\theta }_{21}{\omega }_{32}{\beta }_{13}+{\omega }_{31}{\beta }_{12}{\theta }_{23}-1},\\ I=\frac{r_1(1+{\omega }_{31}+{\theta }_{21}+{\theta }_{21}{\omega }_{32}+{\omega }_{31}{\theta }_{23}-{\omega }_{32}{\theta }_{23})+r_2(1+{\omega }_{32}+{\beta }_{12}+{\omega }_{31}{\beta }_{12}+{\omega }_{32}{\beta }_{13}-{\omega }_{31}{\beta }_{13})+r_3(1+{\theta }_{21}+{\beta }_{13}+{\theta }_{21}{\beta }_{13}+{\theta }_{23}{\beta }_{12}-{\theta }_{21}{\beta }_{12})}{{\theta }_{21}{\beta }_{12}{\omega }_{31}{\beta }_{13}+{\omega }_{32}{\theta }_{23}+{\theta }_{21}{\beta }_{13}{\omega }_{32}+{\omega }_{31}{\beta }_{12}{\theta }_{23}-1},\\ J=(1+{\omega }_{31}+{\theta }_{21}+{\omega }_{31}{\theta }_{23}{\theta }_{21}{\omega }_{31}-{\omega }_{32}{\theta }_{23})(1+{\omega }_{32}+{\beta }_{12}+{\omega }_{31}{\beta }_{12}+{\omega }_{32}{\beta }_{13}-{\omega }_{31}{\beta }_{13})(1+{\theta }_{23}+{\beta }_{13}+{\theta }_{21}{\beta }_{13}+{\theta }_{23}{\beta }_{12}-{\theta }_{21}{\beta }_{12}).\end{array}$

.

5. Simulation Analysis

To explore the three-subject symbiotic evolution model of the supply chain ecosystem of the e-commerce platform, we suppose that the natural population growth rates r₁, r₂ and r₃ are set as 0.05, 0.03 and 0.02 [23,36,37], respectively. The x-axis and y-axis of Figure 4, Figure 5, Figure 6 and Figure 7 represent the evolution cycle and maximum population size of the population in the e-commerce platform supply chain ecosystem, respectively.

Table 4. The value of the symbiosis coefficient.

Symbiotic Relationship	Symbiotic Coefficient
	β12	β13	θ21	θ23	ω31	ω32
Independent symbiosis	0	0	0	0	0	0
Parasitic symbiosis 1	0.15	0.2	0.3	−0.5	0.2	0.2
Parasitic symbiosis 2	−0.2	0.2	−0.15	0.2	−0.15	0.1
Preferential symbiosis 1	0.15	0	0.2	0	0.1	0.1
Preferential symbiosis 2	0	0	0.2	0	0.1	0
Symmetric reciprocal symbiosis	0.2	0.2	0.2	0.2	0.2	0.2
Asymmetric reciprocal symbiosis	0.15	0.1	0.2	0.1	0.2	0.1

shows the results when taking the values of each symbiosis coefficient with the interrelated symbiosis scheme.

(1)

Independent symbiosis model

As shown in Figure 4, the symbiosis coefficients of core, key and support populations are all 0. The three populations do not influence each other in the evolution process and develop their own scales independently. After a period of time, when the three populations are in a stable state, this is when the population size develops to the upper limit, the maximum size when each develops independently; the development rate is only related to its own growth rate, and there is no symbiotic effect between populations.

(2)

Parasitic symbiosis model

In the parasitic model, each type of population in the supply chain ecosystem of the e-commerce platform wants to gain benefits from other populations to achieve the growth of its own population size. As shown in Figure 5, the supporting population is parasitized by the core and key populations, and the population’s own resources are consumed by the other two populations, so the evolution of the size of the supporting population stops after a short period of growth as resources are dissipated and eventually falls below the maximum population size when it coexists independently. The core and key populations benefit from the developmental resources of the supporting populations, and both populations are larger than the maximum size when they coexist independently. The other aspect is that the resources of the parasitized key and core populations are depleted by the supporting populations, and the upper population size of both populations decreases below the maximum size when they coexist independently. The supporting population, on the other hand, benefits from access to development resources from the other two parties, and its population size is higher than the maximum size when it coexists independently.

(3)

Preferential symbiosis model

As shown in Figure 6, the preferential symbiosis model is divided into two scenarios: one in which any two of the three populations—core, key and support—benefit while the other subject is unaffected, and the other in which any two populations are unaffected while the other population benefits. The supporting population has no change in its upper population size because the coexistence coefficient is 0. It is identical to the maximum size when it coexists independently. The core and key populations benefit from access to the resources of the supporting populations, and both grow at a rate that breaks the upper limit of their own size growth. With the continuous development of the supply chain ecosystem of e-commerce platforms, the increase in available resources among populations, and the popularity and application of emerging technologies, e-commerce platforms benefit from them as core populations, and the growth of core population size breaks through the upper limit. However, support and key populations both develop normally with no change in the upper growth limit.

(4)

Reciprocal symbiosis model

The symbiosis mode is an asymmetric reciprocal symbiosis when the sum of the symbiotic relationship between any two of the three subjects in the supply chain ecosystem of the e-commerce platform and the other subject is greater than 0 and the sum of the symbiosis coefficients of any two parties among the three subjects is not equal. The symbiosis mode is a symmetric reciprocal symbiosis when the sum of the symbiosis coefficients of any two parties among the three subjects is positive and equal. As shown in Figure 7, there is mutual synergy between the tri-party subjects in the ecosystem and the mutual use of resources. In the asymmetric reciprocal symbiosis model, all three types of subjects break through the upper limit of their own scale and benefit from each other’s synergy and cooperation, and eventually, the steady state is greater than the maximum scale of the subjects when they develop alone. In the symmetric reciprocal symbiosis model, the three types of subjects not only break through their own population scale but also benefit from mutual synergy because the sum of the coefficients of symbiotic effects of any two subjects is the same, and the maximum scale of the three types of subjects in the steady state is the same.

Based on the above simulation analysis results, it can be seen that the process, law and result of the symbiotic evolution of the supply chain ecosystem of e-commerce platforms mainly depend on the dynamic evolution of the symbiotic relationship between various groups in the ecosystem, and its change is determined by the value of the sum of different coefficients of symbiotic effects. Different symbiotic relationships will form different evolutionary equilibrium results. Among them, the reciprocal symbiosis model is the best evolutionary path for the supply chain ecosystems of e-commerce platforms. Next, we will analyze how the supply chain ecosystem of e-commerce platforms evolves towards a reciprocal symbiosis model through a real case study.

Through years of innovation and development, Alibaba Group has gradually become a leading e-commerce platform. Since it was founded in 1999, new entrepreneurs and businesses have continued to join Alibaba, and the ever-increasing number of users has allowed the company to gain a huge network effect. As of 2022, Alibaba’s annual revenue reached 853.1 billion CNY and its net profit reached 47 billion CNY. With a wide range of businesses, from e-commerce retailing to logistics services to cloud computing services, in addition to digital media and entertainment businesses, Alibaba Group has become the leading company in China’s retail e-commerce industry.

(1)

The structure of the supply chain ecosystem of Alibaba’s e-commerce platform

Alibaba Group’s e-commerce platform business has expanded into all aspects of the e-commerce supply chain. Alibaba Group’s e-commerce platform brings stakeholders such as supply and demand, logistics companies, financial services companies, cloud computing services and other related organizations and individuals. These stakeholders are coordinated and interdependent with each other and, in this way, form a huge supply chain ecosystem for e-commerce platforms.

Based on the ecological categorization, the members of the supply chain of Alibaba’s e-commerce platform are classified into three major populations. The core population is mainly the e-commerce trading platform enterprises under the Ali Group, including Taobao, Tmall, 1688 and other e-commerce trading platforms, which provide a place for value creation and value sharing for other populations, prompting them to gather and develop in the ecosystem. The key population is on the supply and demand sides of transactions on e-commerce platforms, including suppliers, retailers, buyers, etc., who are jointly served by other subjects in the ecosystem. The support population is a service organization that guarantees the successful transaction of e-commerce, including logistics companies, financial payment institutions, cloud computing service providers, etc., and representative organizations and institutions include third-party institutions such as Ant Financial, Alibaba Cloud, and Cainiao Network. These organizations provide services to members of the supply chain ecosystem of Alibaba’s e-commerce platform and are indispensable to the operation of the ecosystem.

(2)

Analysis of the evolution model of “reciprocal symbiosis” in the supply chain ecosystem of Alibaba’s e-commerce platform

The core, key and supporting populations in the supply chain ecosystem of Alibaba’s e-commerce platform create value through resource integration and interaction. Among them, Alibaba Group has always centered on the core of e-commerce business, continuously expanded its network effect, improved the business flow, logistics, capital flow and other links in its own trading activities, and continuously built third-party service institutions including payment and logistics with the help of strong e-commerce platform operation capabilities, so as to open up the e-commerce transaction chain. At the same time, relying on Alibaba Cloud technology, it has established Cainiao logistics, to realize the integration of resources and, at the same time, also promote the efficiency of logistics operations. Not only that, Ali’s Ant Financial Services dig deep into the potential financial needs of enterprises, through the provision of a data credit business and convenient payment and settlement services, to drive the e-commerce platform, supply and demand sides, third-party service providers, and other different symbiotic units, again within the ecosystem of synergistic symbiosis. While pursuing sound and reasonable internal development, Ali Group also pays attention to policy orientation, combining the Group’s internal functions with external environmental resources to provide a favorable symbiotic environment for the ecosystem. For example, in 2018, Alibaba Cloud, Ant Financial and other institutions used big data, cloud computing, payment means and other scientific and technological means to promote a digital “new infrastructure”, actively responded to the national “new infrastructure” development strategy, and continuously optimized the external environment of the e-commerce platform supply chain ecosystem. At present, Alibaba’s e-commerce platform supply chain ecosystem is largely complete, covering a wide range of businesses. This is thanks to its strong e-commerce strength, constant utilization of the e-commerce platform and continuous innovation. In addition, Alibaba has been improving its own development by promoting the ecological evolution of mutual benefit and symbiosis and synergy among various populations in the ecosystem.

6. Conclusions

This study took the supply chain ecosystem of the e-commerce platform as the research object. From the symbiotic theory perspective, a two-body e-commerce platform supply chain symbiotic evolution model was first constructed. Based on this, with an in-depth study of the e-commerce platform supply chain ecosystem, a symbiotic evolution model was constructed, utilizing the logistic expansion equation. The three-body symbiotic evolution model was introduced within the ecosystem, the equilibrium point of the symbiotic evolution model was solved, its stability conditions were analyzed, and MATLAB 2022b was used for simulation analysis. The process of the supply chain ecosystem evolution of e-commerce platforms was explored in depth in both theoretical and empirical dimensions. Three meaningful results and new contributions are presented as follows:

(1)

The supply chain ecosystems of e-commerce platforms are complex systems in which the core population, key populations and supporting populations acquire and share information and resources such as business flow, information flow and logistics in a certain symbiotic environment to create value through synergistic cooperation among various populations, in which different populations take up different responsibilities and jointly drive the e-commerce platform through the integration and sharing of resources and information among them. This involves the operation, evolution and development of supply chain ecosystems. The supply chain ecosystems of e-commerce platforms differ from the traditional business ecological model, and the competing relationship between subjects relies on the synergy and sharing of information. The means of information technology should be strengthened, information docking and sharing among the subjects in the ecosystem should be offered, and the synergy and linkage channels of the populations should be thoroughly opened. At the same time, the reasonable allocation of resources within the ecosystem should be considered, and a reasonable and fair benefit-distribution and risk-sharing mechanism can be established to protect the supporting and key populations within the ecosystem, to realize the synergistic development of the system and improve the sustainability of the synergy.

(2)

The value of the sum of the coefficients of symbiotic interactions between three populations within an ecosystem determines the result of the symbiotic evolution of the ecosystem. The three types of subjects interact with each other to form a mutually beneficial symbiotic evolutionary development path through synergistic cooperation. In the process of developing the subjects within the supply chain ecosystem of the e-commerce platform to a reciprocal symbiosis model, mutual synergy and cooperation among the subjects in the system is needed.

(3)

The symbiotic relationship among various groups in the supply chain ecosystems of e-commerce platforms appears to evolve from independent coexistence, parasitism, and deviated symbiosis to reciprocal symbiosis under different symbiotic action coefficients due to the turnover of competing relationships and the amount of resource utilization. The simulation analysis shows that under the reciprocal symbiosis model, the maximum size of various clusters will change significantly, and all three clusters can benefit from it, so the members of organizations in the supply chain ecosystem of e-commerce platforms should be committed to evolving toward the development of the reciprocal symbiosis model. The development of the system toward a model of mutual symbiosis requires a great deal of effort. First, the symbiotic environment of the e-commerce platform supply chain ecosystem should be optimized. A good economic and market environment, the implementation of supply-side reform, the effective boosting of domestic demand and the provision of a good environment for development are all needed for the development of the supply chain ecosystems of e-commerce platforms. Second, the level of the core population should be increased. As an essential component of the ecosystem, e-commerce platforms provide services and a step for the creation of value for other subjects throughout the ecosystem. Then, the ecosystem should continue to attract more symbiotic subjects to join the system, continuously improve the supply chain ecosystem of the e-commerce platform, and realize the synergy and cooperation of multiple subjects to create more value and evolve the ecosystem towards reciprocal symbiosis.