Research on the Niche Evolution Game of Ecological ...downloads.hindawi.com/journals/complexity/2020/6327218.pdf · 4/17/2020 · ResearchArticle Research on the Niche Evolution

Research ArticleResearch on the Niche Evolution Game of Ecological CommunityInnovation of Corporate Venture Capital Based on LogisticExtended Complexity Model

FanglinMeng 12 ZengruiTian 2 BeiquanChang 3HongxinYu 4 andShuaiZhang5

1Business School Sanda University Shanghai 201209 China2Glorious Sun School of Business and Management Donghua University Shanghai 200051 China3School of Public Policy amp Management Tsinghua University Beijing 100084 China4Business Economics College Shanghai Business School Shanghai 200235 China5University of Greenwich London SE10 9LS UK

Correspondence should be addressed to Zengrui Tian flmengsandaueducn

Received 17 April 2020 Revised 26 May 2020 Accepted 3 June 2020 Published 28 August 2020

Guest Editor Zhihan Lv

Copyright copy 2020 FanglinMeng et al+is is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

With the gestation and development of new technologies new products new formats and new models venture capital in-vestment as one of the most important forms of open innovation in large companies plays an increasingly important role in theinnovation of mature large companies and entrepreneurial enterprises To deal with the complex and dynamic environment theniche of Corporate Venture Capital (CVC) ecological community is investigated from the perspective of the innovation eco-system By analyzing the innovation of CVC ecological community with the use of the logistic expansion model this paperanalyzes the stability of evolution game through the replicator dynamic equation and discusses ten parameters of niche state Inthe end we conclude that there are four optimization strategies in the coevolution of major corporations and entrepreneurialfirms namely niche separation niche expansion niche K-R and niche alliance

1 Introduction

Innovation has become the endogenous driving force andcore competitive advantage of a countrys economic growthIn the complex and dynamic digital economy era it isdifficult for enterprises to maintain traditional competitionbarriers To keep growing continuously enterprises mustdeal with issues such as the increasingly uncertain envi-ronment challenging value creation and oversupply choicesfor customers +e traditional value chain creation model ischanging to the shared destiny community with a symbiosiscreation model +erefore large companies are constantlyseeking the path of open empowerment Corporate VentureCapital (CVC) has become an important model and tool foropen innovation access to external technology sources andvalue creation +e global venture capital funding in 2018reached 254 billion US dollars and the financing amount in

2017 was 174 billion RMB of which the global companystotal venture capital investment was 312 billion US dollarsInvestment activities increased by 19 over 2016 and totalinvestment increased by 18 [1] Companies in countrieslike Britain China and India have hit record highs in theirventure capital +e global CVC investment industry hasstrong interests in areas with high technological innovationand fierce competitions such as Internet healthcare andmobile technology

+e companyrsquos venture capital originated in the UnitedStates in the 1960s It is now one of the main ways for maturelarge companies to develop outwards It has a strategicappeal because it provides multiple choice platforms forlarge companies to innovate Corporate innovation requiresventure capital as a mechanism and driving force CorporateVenture Capital aims to achieve open innovation obtain thelatest technology in related fields and overcome the soft

HindawiComplexityVolume 2020 Article ID 6327218 13 pageshttpsdoiorg10115520206327218

constraints of the companyrsquos internal RampD budget so thatthey can improve technology innovation efficiency It couldalso reduce the risk of investment in independent RampD andimprove organizational capabilities to foster an innovationculture It benefits the corporate by realizing the value ofstrategic mergers and acquisitions and initiating entrepre-neurial investment in strategic innovation projects Ascompanyrsquos venture capital has a high degree of risk toleranceand a long investment cycle it can invest in the startups thatare struggling to obtain traditional independent venturecapital (IVC) It promotes and optimizes mutual regener-ation and achieves a better evolutionary cycle for bothparties While mature companies deeply cultivate the RedSea they must also actively explore in the Blue Ocean CVCis a hybrid model that stimulates innovation It expandsindustrial boundaries rebuilds market boundaries explorescutting-edge technologies encourages open innovation andexpands organizational structures for large companies It isregarded as an effective paradigm to promote the evolutionof the industry ecosystem It is also an important way forlarge companies to acquire innovative technologies andindustrial integration [2] CVC activities are a ldquodual andtwo-wayrdquo value creation process that includes both strategicand financial values while creating value for mature largecompanies and startups With the advent of the digitaleconomy 20 era ecological collaborative innovation modelshave gradually taken shape Typical digital economy com-panies in China such as Alibaba Tencent Xiaomi andBaidu as well as traditional enterprises such as Haier andFosun are actively building open innovation enterpriseecosystems +ey integrate the companyrsquos own technologycapital and market advantages with external resources todevelop new technologies new products and new modelsfor new markets

2 Related Work

Hannah and Eisenhardt proposed that in addition to therelationship between competition and cooperation enter-prises also need to continuously meet customer needsthrough innovation [3] Enterprises have evolved from therole of an individual player in the industry into part of theindustrial ecosystem Luo and Ratchford took Apple IBMFord and Wal-Mart as examples to study focal companieswhich develop service technology and value networkplatforms to build their own unique business ecosystems andobtain value returns [4] Yao and Zhou used the theory ofnatural ecosystem evolution to study the innovation path ofhigh-tech enterprises and found that the dependence ofenterprise innovation paths has ecological genetic andvariability characteristics [5] Daniela et al in ldquoEvolutionary+eory of Economic Changerdquo explain economic changesfrom a perspective of dynamic evolution Evolutionary gametheory pays attention to the change of population structureand uses evolutionary stable strategy (ESS) to represent astable state that can resist the invasion of mutation strategy[6] Levinthal proposed that corporate adaptation and en-vironmental selection are the main paths of populationevolution [7] Zaman et al believe that internal and external

resources of an enterprise are equally important Enterprisesuse external resources and external channels to help com-mercialize their new technological achievements +ey alsoemphasize that enterprises should quickly implement in-novation reduce innovation costs and work with profes-sional venture capital institutions to jointly improveinnovation performance [8]

One of the most challenging 125 scientific issues in the21st century in science is ldquohow does cooperative behaviorevolverdquo +e innovation ecosystem has the same charac-teristics of natural evolution integration self-organizationperiodicity and openness as natural ecosystems and sharesthe same characteristics in power genetics evolution andfeedback Important scholars in the CVC field Jog andMcconomy creatively proposed that mature large compa-nies have regarded CVC not only as the window for tech-nology discovery but also as an ecosystem around largecompanies [9]+is conclusion is based on previous researchon CVC enterprise value creation CVC investment enter-prise entrepreneurial performance investment conditionsand cross-organizational knowledge acquisitionBased onthe analysis of nearly 300 CVCs Jog and Mcconomy pro-posed that the increasing number of CVCs would contributein better short-term and long-term performance of theecosystem which extends a previous view shared by scholarsthat the CVC is only an incubator-level participant Insteadas an ecosystem strategy CVC intends to ldquobuild a con-stellationrdquo [10] +erefore from the perspective of theecosystem and the niche theory it is proposed that the CVCecological community formed by mature large companiesand startups in the form of CVC projects achieves syn-chronization through interactions between CVC functionsbehavioral processes and the external environment In thesymbiotic mode a symbiotic evolution can be developedwith the growth of large companies and entrepreneurialenterprises

3 CVC Niche for Major Corporations andEntrepreneurial Firms

In 1838 the Dutch mathematical biologist Verhulst pro-posed a logistic equation to study the growth of biologicalpopulations It was found that the population grew fastest atthe beginning When it grew to a certain value the speedbegan to slow down until it finally decreased to zero (iestop growing) In 1900 Italian mathematician Volterraproposed the predator and prey populations model In 1925Lotka proposed mathematical ecology in chemical reactions+en in 1926 Volterra used the LotkandashVolterra model todemonstrate the rule of fish population in the port of FiumeLotkandashVolterra model which evolved from the logisticextended model can better explain the relationship betweenlarge companies and startups in the CVC ecological com-munity +is model as an evolutionary game for species orpopulation formation provides a new perspective to un-derstand community structure optimization and nicheevolution [11]

+e growth of the corporate ecological community in-volved in CVC also generally conforms to the mechanism of

2 Complexity

the logistic development that is the development of theCVC ecological community is relatively immature thescale is not large the growth space is large and the de-velopment speed is fast at S1 However at this stage forlarge enterprises and startups the initial capital investmenthuman investment and technical investment are relativelylarge +e symbiotic subjects of the CVC ecologicalcommunity are still in the running-in period with highrisks At node P1 either CVC is offside to enhance theniche occupying a favorable position in the innovation andentrepreneurship ecosystem or it may gradually declineCVCs that operate smoothly realize technological inno-vation and have shared and coordinated development cansuccessfully enter the second stage of the ecological nichebeyond P1 In the second stage of S2 the ecological niche ofCVC continued to expand the benefits continued to in-crease innovation results and innovative technologies wererapidly transformed large companies achieved their stra-tegic goals and financial goals and startup companies alsoachieved growth At the second branch point P2 with greatinnovation potential the CVC ecological communityformed by large companies with startups integrates moreresources and continues to develop +e symbiotic systemwill rise to a higher stage while the ecological shrinkagemay also occur Figure 1 is the trend of CVC ecologicalcommunity evolution

+erefore the evolution of the niche also reflects thecharacteristics of repeated games between large companiesand startups in the CVC ecological community CVC ac-tivities are also innovative activities Large companies formCVC ecological communities with startups through venturecapital for technological innovation +ey aim to realizevalue cultivation and value innovation and continuouslydevelop new competitive advantages in the industry com-petition By improving their own niche they can achievetheir strategic goals and financial goals

From the perspective of biology and evolutionarygames the development of the CVC ecological communityis constrained by various factors such as talent technologycapital and services in specific time and space dimensions+e ecological factor domain Ci f(z1 z2 z3 middot middot middot zn) isused to represent the various factors z1 z2 z3 middot middot middot zn thatindicate the constraints for the development of the CVCecological community +ere is a range value Ni of theniche width Wi of ecological community i which repre-sents the competition coefficient αi of the CVC ecologicalcommunity β represents the niche overlap value of theCVC ecological community and χi indicates the impact ofCVC investment strategies such as combination strategiescapital injection strategies exit methods and space pref-erences on the innovation of the CVC ecologicalcommunitySt represents the niche status (i) of the CVCecological community at time of t and dS(t)dt representsthe rate of change in the niche width for large enterprisesand entrepreneurial enterprises in the CVC ecologycommunity Adjusted from the LotkandashVolterra model theniche evolution equations of the major corporations (MC)and entrepreneurial firms (EF) in the CVC ecosystem areset as follows

dS1(t)

dt r1S1 ρ1 + χ1 minus α1 minus S1 minus βS2( 1113857

dS2(t)


⎧⎪⎪⎪⎨

⎪⎪⎪⎩

(1)

Here S1 and S2 represent the niche width limit of MCand EF ρ1 and ρ2 represent niche saturation coefficient ofMC and EF in the CVC ecological community α1 and α2represent competition coefficients α1 is the competitiveeffect of EF on MC while α2 is the competitive effect of MCon EF and β represents niche overlap betweenMC and EF inthe CVC ecological community

When β 1 there is a complete niche overlap betweenMC and EFWhen β 0 there is a complete niche separationfor MC and EF If the value of β is between 0 and 1 there ispartial overlap between MC and EF +e β is proportional toα1 and α2 which means the bigger the overlap between MCand EF the more the fierce competition

According to the above differences in β the evolution ofthe niche of large companies and startups in the CVCecological community is discussed as follows [12]

(1) When β 1 there is a complete niche overlap be-tween MC and EF

If dS1(t)dt 0dS2(t)dt 01113896 the balanced position includes

H1(ρ1 + χ1 minus α1 0) H2(ρ2 + χ2 minus α2 0)H3(0 ρ1+χ1 minus α1) H4(0 ρ2 + χ2 minus α2) O(0 0)+e equation for MC in the CVC ecological com-munity is ρ1 + χ1 minus α1 minus S1 minus S2 0+e equation for EF in the CVC ecological com-munity is ρ2 + χ2 minus α2 minus S2 minus S1 0As there is an equal slope the position of the twoparallel straight lines L1 L2 depends on the values ofparameters ρ1 + χ1 minus α1 and ρ2 + χ2 minus α2When ρ1 + χ1 minus α1 gt ρ2 + χ2 minus α2 we can obtainFigure 2 in the following+e niche width of the MC in the CVC ecologicalcommunity is larger than the niche width of the EF

P1

P2

Logistic curveS1 S2 S3

t

CVC

nich

e

Figure 1 +e trend of CVC ecological community evolution

Complexity 3

MC completely includes the EF indicating that theMC occupies the entire niche spaceWhen ρ2 + χ2 minus α2 gt ρ1 + χ1 minus α1 we can get Figure 3in the followingEntrepreneurial firmrsquos niche width (L2) in the CVCecological community is larger than that of majorcorporation (L1) EF completely includes MC +isindicates that EF occupies the entire niche space+eresult of evolution will also approach EF +ereforewhen the MC and EF in the CVC ecological com-munity completely overlap the direction of the nicheevolution depends on the technologies capital hu-man resources and innovation resources used by theMC and EF +e one occupying the resource ad-vantage will eventually control the evolution

(2) When β 0 there is a complete niche separation forMC and EF


H1(ρ1 + χ1 minus α1 ρ2 + χ2 minus α2)

H2(ρ1 + χ1 minus α1 0)H3(0 ρ2 + χ2 minus α2) O(0 0)+e equation for MC in the CVC ecological com-munity is L1 S1 ρ1 + χ1 minus α1+e equation for EF in the CVC ecological com-munity is L2 S2 ρ2 + χ2 minus α2We can obtain a separation as shown in Figure 4L1 andL2 divide four areas in the quadrant In theareas below L1 (dS1(t)dtlt 0) the evolution direc-tion rises while in the areas above L1 (dS1(t)dtgt 0)the evolution direction goes downward In the areason the left of L2 (dS2(t)dtlt 0) the evolution di-rection goes right while in the areas on the right ofL2(dS2(t)dtgt 0) the evolution direction goes leftIn quadrant 1 dS1(t)dtgt 0 and dS2(t)dt lt 0In quadrant 2 dS1(t)dtgt 0 and dS2(t)dt gt 0In quadrant 3 dS1(t)dtlt 0 and dS2(t)dt lt 0In quadrant 4 dS1(t)dtlt 0 and dS2(t)dt gt 0+erefore we can conclude that the result of evo-lution tends to equilibrium H1(ρ1 + χ1 minus α1 ρ2+

χ2 minus α2) where the large companies and startups inthe CVC ecological community occupy their re-spective niche Its niche size is related to the nichesaturation coefficients ρi of both parties the com-petition coefficient αi of large enterprises andstartups in the CVC ecosystem and the impactcoefficient χi of CVC ecological community inno-vation CVC investment strategy (CVC portfoliostrategy CVC investment stage strategy CVC exitmethod CVC investment space preference)

(3) When 0lt βlt 1 MC and EF niche partially overlap+e evolution path depends on the ecological do-main space of their respective resources


O(0 0) H1(ρ1 + χ1 minus α1 0)

H2(0 ρ1 + χ1 minus α1β)H3(ρ2 + χ2 minus α2β 0) andH4(0 ρ2 + χ2 minus α2)

Gρ1 + χ1 minus α1 minus β ρ2 + χ2 minus α2( 1113857

1 minus β2ρ2 + χ2 minus α2 minus β ρ1 + χ1 minus α1( 1113857

1 minus β21113888 1113889

(2)

As the values of the parameters are different the ana-lytical expressions have different evolution trends +ere arefour competition situations between the two populations

Situation 1 When (ρ1 + χ1 minus α1β)gt ρ2 + χ2 minus α2 and(ρ2 + χ2 minus α2β)lt ρ1 + χ1 minus α1

In the area surrounded by the quads H1 H2 H3 H4(Figure 5) where dS1(t)dtlt 0cedil dS2(t)dt gt 0 large com-panies have not reached the maximum capacity for growthie there is still room for growth and development Whilestartups have reached the maximum capacity ie there islittle room for continued growth Large companies havemastered related technological innovations +e corre-sponding evolution is shown in Figure 5

Situation 2 When (ρ1 + χ1 minus α1β)lt ρ2 + χ2 minus α2 and(ρ2 + χ2 minus α2β)gt ρ1 + χ1 minus α1

In the area surrounded by the quads H1 H2 H3 H4(Figure 6) where dS1(t)dtgt 0 dS2(t)dtgt 0

Majorcorporations

Entrepreneurialfirms

L2

L1

Figure 2 Evolution of niche overlap when MC contains EF

4 Complexity

H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0

Figure 5 Large companies occupy part of the startuprsquos niche


Majorcorporations

L1

L2

Figure 3 Evolution of niche overlap when EF contains MC


Majorcorporations

L2

L1

Figure 4 Niche separation of CVC

H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0

Figure 6 Startups occupy the ecological domain of large companies

Complexity 5

entrepreneurial enterprises in the CVC ecosystem cancontinue to develop but large companies have reached theirlimits +erefore entrepreneurial enterprises can invadesome ecological domains for large companies as shown inFigure 6

Situation 3 When (ρ2 + χ2 minus α2β)gt ρ1 + χ1 minus α1 and(ρ1 + χ1 minus α1β)gt ρ2 + χ2 minus α2

L1and L2 come across at point G as shown in Figure 7



1 minus β21113888 1113889

(3)

In the area of H2GH4 there is still room for growth ofstartups while large companies have developed to themaximum capacity approaching G In the GH1H3 regionlarge companies continue to grow while the growth ofstartups has reached the upper limit +e movement trendsof both parties will gradually approach point G where G isthe equilibrium point for the coexistence of large enterprisesand entrepreneurial enterprises in the CVC ecologicalcommunity

Situation 4 When (ρ2 + χ2 minus α2β)lt ρ1 + χ1 minus α1 and(ρ1 + χ1 minus α1β)lt ρ2 + χ2 minus α2

L1 andL2 come across at point P as shown in Figure 8In the H2PH4 andH1PH3 areas both large companies and

startups have room for continued innovation and growth Bothsides may have the opportunity to win in the competitionprocess so they have not reached an equilibrium state +eniche occupation depends on what the two parties have in theinitial ecological domain +e larger the initial ecological do-main is the more resources it possesses and the easier it is towin in the CVC ecological community +is also makes CVCultimately achieve the strategic goals and financial goals of largecompanies by IPO mergers and acquisitions While startupsget mature big companies can quit

In the above analysis situations (1) (2) and (4) are allunbalanced and stable In the balanced state (3) large en-terprises and startups in the CVC ecosystem can coexist andmaximize their own added value

4 Construction of the Evolutionary GameModel for the CVC EcologicalCommunity Innovation

Evolutionary game theory exists in Darwinrsquos idea of naturalselection Based on the dual theory of game theory andbiological evolution this section analyzes the formationmechanism of interaction between populations in ecologicalcommunities and studies population growth evolution andstability [13]

41 Evolutionary Game Analysis +e symbiotic evolutionbetween large companies and startups in the CVC ecologicalcommunity will increase the adaptability of both parties andthus their respective niche +e evolutionary game theoryhas been used to analyze the operating mechanism of large

companies and startups Here we use evolution stabilitystrategy to analyze the evolution path of CVC ecologicalcommunity +e strategy adjustment process trends andstability of large players and startups in priority game playersare considered ESS evolutionary stability strategy andTaylor and Jonkerrsquos replicator dynamic equations are used aswell [14] +e niche evolution process of CVC ecologicalcommunity innovation also requires mutation and selectionmechanisms [15] +e formation and development of theCVC eco-community is the game behavior between largecompanies startups and other related entities Its formationand development are also the result of the dynamic evolutionof multiparty games When there is a two-way causal re-lationship between a large company and a startup companyunder a certain feedback mechanism the adaptive change ofthe large company will change the adaptability of the startupcompany while the change of the startup company willfurther affect the change of the large company By assessingtheir participation in CVC investment activities the twoparties will promote the continuous evolution of the CVCecological community when the results of multiple rounds ofgame play with other entities are greater than theirnonparticipation

42 Research Hypothesis and Model Building

421 Research Hypothesis +e changes in the niche of largecompanies and startups in the CVC ecosystem are affectedby a variety of ecological factors in the symbiotic envi-ronment of venture capital At the same time the strategyobtained by the opponent based on the irrational selection isan important factor Entrepreneurial enterprises will playdynamic games First assuming that the strategy set of MC isniche maintenance and niche expansion the strategy set ofan entrepreneurial company can be participation in com-petition and acceptance In this case there is a two-stagegame in the CVC investment activity process +is can beregarded as an evolutionary game of dual population anddual strategy [16] Second assuming that both large com-panies and startups are bounded in rationality they choosethe best strategy based on their own situation and envi-ronment +ird in the CVC ecological community largecompanies and startups make strategic adjustments basedon their strategy and the external environment A repeatedgame would happen as the adjustment also depends on thechoices and the performance of these companies

422 Construction of Fitness Function Matrix Assumingthat the niche separation of large companies and startupsdoes not affect them the two types of corporate populationsin their own ecological space and time have the benefits ofindependent innovation R1 and R2 When the MC pop-ulation chooses to expand its niche through CVC activitiesit can realize innovation benefits including the benefitscreated by knowledge sharing as a result of sharing variousresources and technology spillovers It can be represented byλ(a + b)Δr where λ is the absorptive capacity coefficient ofthe large company population a and b are the knowledge

6 Complexity

sharing coefficient and the technology spillover coefficientrespectively and Δr is unit excesses benefit If the MC ex-pands the EF also carries out the niche expansion which canachieve excess returns Both parties need to pay a certain costduring the niche expansion process +e cost paid by thelarge company can be expressed as C1 and the cost paid bystartup company is represented by C2 +ere are also largecompanies that expand their niche and startups choose tokeep the same niche In this case they can get a profit e +eprobability that a large company will expand its niche is pand the probability of maintaining it is 1 minus p +e probabilityof participating in competition based on feedback fromstartups is q and the probability of maintaining the originalecology is 1 minus q +e game fitness payment matrix isestablished in Table 1

43 Evolution Path Analysis

431 Replicator Dynamic Equation Solving According tothe game fitness function matrix above it can be concludedthat for theMC which chooses to expand the niche that is tocarry out CVC investment activities the expected return is

U11 q R1 + λ(a + b)Δr minus C1( 1113857 +(1 minus q) R1 minus C1( 1113857

R1 + qλ(a + b)Δr minus C1

U12 q R1 + e( 1113857 +(1 minus q)R1 qe + R1

U1 pU11 +(1 minus p)U12

p qλ(a + b)Δr minus qe minus C1( 1113857 + qe + R1

(4)

In the same way for the EF the expected income andexpansion of the niche expansion are U21 and U22 while theaverage expectation of the startup enterprise is U2

U21 p R2 +[1 minus λ(a + b)]Δr minus C21113858 1113859 +(1 minus p) R2 minus C2( 1113857

R2 + p[1 minus λ(a + b)]Δr minus C2

U22 p R2 + e( 1113857 +(1 minus p)R2 e + R2

U2 qU21 +(1 minus q)U22

q R2 + p[1 minus λ(a + b)]Δr minus C21113858 1113859 +(1 minus q) pe + R21113858 1113859

q p[1 minus λ(a + b)]Δr minus pe minus C21113858 1113859 + pe + R2

(5)

According to the replicator dynamic formula of theevolutionary game the replicator dynamic equations of largecompanies and startups in the CVC ecosystem can be ob-tained as follows

H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0G

Figure 7 Ecological stability of large companies and startups

H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0P

Figure 8 Large companies and startups continue to grow and cannot reach balance

Table 1 Niche game fitness function matrix

Subject nichein CVC

EFExpanding

nicheMaintaining

niche

MCExpanding R1 + λ(a + b)Δr minus C1 R1 minus C1

R2 + [1 minus λ(a + b)]Δr minus C2 R2 + e

Maintaining R1 + e R1R2 minus C2 R2

Complexity 7

F(p) dp

dt p U11 minus U1( 1113857

p(1 minus p) q(λ(a + b)Δr minus e) minus C11113858 1113859

F(q) dq

dt q U22 minus U2( 1113857

q(1 minus q) p[[1 minus λ(a + b)]Δr minus e] minus C21113864 1113865

(6)

432 Evolutionary Stability Strategies for MC According tothe dynamic equations for MC we have

F(p) dp

dt p U11 minus U1( 1113857


(7)

+ree stable points of the equation can be obtainednamely plowast1 0 plowast2 1 and plowast3 C1λ(a + b)Δr minus e If anevolutionary stable strategy is required the derivative dy-namic equation needs to be derived and satisfy d2pd2tlt 0We will obtain

d2p

d2t (1 minus 2p) q(λ(a + b)Δr minus e) minus C11113858 1113859 (8)

When qgtC1λ(a + b)Δr minus e we get plowast2 1 an evolu-tionary expansion strategy which means MC will chooseniche expansion strategy When qltC1λ(a + b)Δr minus e weget plowast1 0 an evolutionary stability strategy which meansMC will choose strategies to maintain their original nicheWhen q C1λ(a + b)Δr minus e dpdt equals zero which isalways a stable status

433 Evolutionary Stability Strategies for EF According todynamic equations for EF we have

F(q) dq

dt q U22 minus U2( 1113857


(9)

+ree stable points of the equation can be obtainednamely qlowast1 0 qlowast2 1 and qlowast3 C2[1 minus λ(a + b)]Δr minus e

When p C2[1 minus λ(a + b)]Δr minus e we get dqdt 0with q being in stable status When pgtC2[1 minus λ(a+

b)]Δr minus e we get dqdtlt 0 which is an evolutionary ex-pansion strategy EF also chooses to expand its niche to enterMCrsquos related industries When pltC2[1 minus λ(a + b)]Δr minus ewe get qlowast1 0 which is an evolutionary stable strategy EFmaintains its original niche

+e above discussion does not consider the relationshipand size of the parameters When the combination of pa-rameters changes the game strategy of large enterprises andentrepreneurial enterprises in the CVC ecological com-munity changes

434 Impact of Parameter Changes on Evolutionary GameStrategies +e first topic is about the effect of parameterchanges on the evolutionary stability strategy of MC

(1) For 0ltC1λ(a + b)Δr minus elt 1 evolutionary stableequilibrium is determined by two situations of qWhen qgtC1λ(a + b)Δr minus e we get plowast2 1 anevolutionary expansion strategy (EES) while whenqltC1λ(a + b)Δr minus e we get plowast1 0 an evolution-ary stable strategy (ESS)

(2) For C1λ(a + b)Δr minus ege 1 we always getqltC1λ(a + b)Δr minus e and plowast1 0 which is ESS+atis the cost of niche expansion is high and largecompanies maintain their original niche

+e second topic is about the impact of changes inparameters on the evolutionary stability strategy of EF

(1) For 0ltC21 minus λ(a + b)Δr minus elt 1 there are twopossibilities When pgtC21 minus λ(a + b)Δr minus e we getqlowast2 1 an EES When pltC21 minus λ(a + b)Δr minus e weget qlowast1 0 an ESS

(2) For C21 minus λ(a + b)Δr minus ege 1 we always get pltC21 minus λ(a + b)Δr minus e qlowast1 0 which is an ESS

By a comprehensive analysis of the stability strategies ofthe two sides of the game analyzed above we get five balancepoints namely O(0 0) P(1 0) Q(0 1) R(1 1) E(C1λ(a + b)Δr minus e C2[1 minus λ(a + b)]Δr minus e)

44 Game Process with Niche Parameters

441 Evolution Strategy of MC in the CVC EcologicalCommunity When considering the status and momentumof large companies and startups in the CVC ecosystem thatis the growth of large companiesrsquo innovation efforts andpotential innovation capabilities the fitness function needsto consider the status value of the large company population(T1) and potential value (S1) +e game playerrsquos entrepre-neurial state value is T2 and the potential value is S2 +ehigher the values of T1 S1 T2 and S2 the stronger theability to obtain innovative resources and the stronger theability to expand the niche+ematrix above can be adjustedto Table 2

+e corresponding income formula is as followsU11 q R1 + λ(a + b))Δr minus C1( 1113857 +(1 minus q) R1 minus C1( 1113857

U12 q R1 + e + T1S1( 1113857 +(1 minus q)R1 q e + T1S1( 1113857 + R1


p qλ(a + b)Δr minus q e + T1S1( 1113857 minus C1( 1113857 + q e + T1S1( 1113857 + R1

(10)

+e dynamic equation is as follows

F(p) dp

dt p U11 minus U1( 1113857

p(1 minus p) q λ(a + b)Δr minus e + T1S1( 1113857 minus C11113858 1113859

(11)

8 Complexity

For F(p) 0 the stable points are qlowast1 0 qlowast2 1 andqlowast3 C2[1 minus λ(a + b)]Δr minus (e + T1S1)

(1) When q C1λ(a + b)Δr minus (e + T1S1) dpdt equalszero and the value of p is stable

(2) When qgtC1λ(a + b)Δr minus (e + T1S1) d2pd2tlt 0we obtain plowast2 1 an EES

(3) When qltC1λ(a + b)Δr minus (e + T1S1) d2pd2tgt 0we obtain plowast1 0 an ESS

442 Evolutionary Strategies of EF +e correspondingincome formula is as follows



U22 p R2 + e + T2S2( 1113857 +(1 minus p)R2 p e + T2S2( 1113857 + R2


q R2 + p[1 minus λ(a + b)]Δr minus C21113858 1113859

+(1 minus q) p e + T2S2( 1113857 + R21113858 1113859

q p[1 minus λ(a + b)]Δr minus p e + T2S2( 1113857 minus C21113858 1113859

+ p e + T2S2( 1113857 + R2

(12)


F(q) dq

dt q U22 minus U2( 1113857

q(1 minus q) p [1 minus λ(a + b)]Δr minus e + T2S2( 11138571113858 1113859 minus C21113864 1113865

(13)

For F(q) 0 the stable points are qlowast1 0 qlowast2 1 andqlowast3 C2[1 minus λ(a + b)]Δr minus (e + T2S2)

(1) When p C2[1 minus λ(a + b)]Δr minus (e + T2S2) anyvalue of q is an ESS

(2) When pgtC2[1 minus λ(a + b)]Δr minus (e + T2S2) we getqlowast2 1 an ESS

(3) When pltC2[1 minus λ(a + b)]Δr minus (e + T2S2) we getqlowast1 0 an ESS

443 Coevolution Strategy of MC and EF in the CVC Eco-logical Community By unifying the above various gameresults into a coordinate quadrant we get comprehensive

game process of large companies and startups in CVCecological community in Figure 9

It can be seen from the figure that in the regional QOPEthe evolutionary stability strategy of large companies andstartups is (00) that is neither party adopts the strategy ofniche expansion in CVC activities +e evolutionary andstable strategies of both enterprises and startups are (11)which means that both large companies and startups areactively expanding their niche However the strategic ac-tions of large enterprises and startups depend on the po-sition of E +rough discussing the position of E the factorsthat affect the strategic actions of large and startups can beidentified

SQOPE 12

times 1 times Ex +12

times 1 times Ey 12

Ex + Ey1113872 1113873

12

C1

λ(a + b)Δr minus e + T1S1( 1113857+

C2

[1 minus λ(a + b)]Δr minus e + T2S2( 11138571113890 1113891

(14)

As long as the probability of more actions taken by largecompanies and startups on both sides of the game is withinSQOPE both parties choose not to expand the niche At thistime the evolution direction depends on SQOPE and SQRPEWhen SQOPEgt SQRPE the evolution converges to point OWhen SQOPElt SQRPE the evolution converges to point BWhen SQOPE SQRPE the probability of the two sidesconverging toward O or R is equal

45 Evolution Strategy of CVC Ecological Community+rough the above analysis 10 parameters that influence thedirection of evolution are obtained +e common evolutionpath is discussed separately for each parameter by seekingpartial derivatives

(1) Impact of C1 andC2 on SQOPE

zS

zC112

times1

λ(a + b)Δr minus e + T1S1( 1113857gt 0

zS

zC212

times1

[1 minus λ(a + b)]Δr e + T2S2( 1113857gt 0

(15)

+is shows that SQOPE is a monotonically increasingfunction for C1 C2 For MC and EF the higher thecost of forming a CVC ecological community is themore it tends to maintain the original niche

(2) Impact of (a+ b) on SQOPE

zS

za12

C2


⎡⎣

minusC1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(16)

Since a is not monotonic for SQOPE a second-orderderivative is performed

Table 2 Population fitness function matrix in CVC ecologicalcommunity

Subject nichein CVC

EF

Expanding niche Maintainingniche


R2 + [1 minus λ(a + b)]Δr minus C2 R2 + e + T2S2

Maintaining R1 + e + T1S1 R1R2 minus C2 R2

Complexity 9

z2S

z2a

C2Δr2


minusC1Δr3

λ(a + b)Δr minus e + T1S1( 11138571113858 11138593 gt 0

(17)

+erefore there is a minimum value for SQOPEWhen

z2S

z2a

C2Δr2


minusC1Δr3

λ(a + b)Δr minus e + T1S1( 11138571113858 11138593 0

(18)

we obtainC2


C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592

(19)

At this time the stable strategy of MC and EF is (11)Both of them implement niche expansion strategies+e parameter b is derived from the above a

(3) Impact of T1 S1T2 and S2 on SQOPEzS

zT112

C1


zS

zS112

C1


zS

zT212

C1

[1 minus λ(a + b)]Δr minus e + T2S2( 11138571113858 11138592 gt 0

zS

zS212

C1


(20)

SQOPE is a monotonically increasing function of T1S1T2 and S2 indicating that the larger the state andpotential of the niche of large companies andstartups in the CVC ecosystem (that is the tech-nology talents capital and social resources of largecompanies and startups) the better the foundationand the greater the real dominance and influencethat large companies and startups have on the in-novation environment It is more likely that twosides tend to maintain their original niche

(4) +e impact of e on SQOPE

zS

ze12

C2


⎡⎣

+C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦gt 0

(21)

It shows that SAECO is a monotonically increasingfunction of e which means that the greater the in-novation income from maintaining the originalniche is the more likely the large enterprises andstartups tend to maintain the original niche

(5) +e impact of Δr on SQOPE

zS

zΔ r minus

12

(1 minus λ(a + b))C2


⎡⎣

+λ(a + b)C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦lt 0

(22)

SQOPE is a monotonic reduction function for Δr thatis the larger the excess returns the larger the resultof the game between the large enterprise and theentrepreneurial enterprise Both parties choose toexpand the niche strategy

Time (t)Growth Development Mature Extension period

CVC

nich

e evo

lutio

n

CVC niche expansion ofecological community

Cooperation

Competition balance

Evolution andtransformation

St

S3

S2

S1

Figure 9 Comprehensive game process of large companies and startups in CVC ecological community after comprehensive situationalfactors

10 Complexity

(6) +e impact of λ on SQOPE

zS

zλ minus

12



⎡⎣

+λ(a + b)C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(23)

SQOPE is a monotonic reduction function for Δr that isthe larger the excess returns the larger the result of the gamebetween the MC and the EF Both parties choose to expandniche strategy

5 Optimization Strategy for CVC NicheEvolution in Ecological Community

+e evolution of the ecological niche of the CVC ecologicalcommunity is subject to the combined effects of multiplemechanisms and competition and symbiosis are affected byinterest-driven and ecological balance +e benefit-drivenmechanism is the inherent growth mechanism of the CVCecological community under a certain environment of in-novation and entrepreneurship +e source of motivation isthe maximum pursuit of individual interests by large en-terprises and entrepreneurial enterprises Large enterprisepopulations and entrepreneurial enterprise populationsintegrate related resources through horizontal symbiosisvertical symbiosis or dynamic alliances to eliminate orreduce resource bottlenecks and promote the smooth de-velopment of large enterprises and individual entrepre-neurial enterprises +erefore the CVC ecologicalcommunity as a core part of the innovation and entre-preneurship ecosystem presents a nonlinear and expo-nential growth trend As a self-protection mechanism of theecological niche of the CVC ecological community theecological balance mechanism can ensure the self-sustain-ment and steady evolution of the CVC niche In addition tothe innovation entrepreneurship and ecological resourcesthe growth of the population is affected by material energyand information accumulation but is also balanced andstabilized by self-organization and self-regulation because ofenvironmental factors

+e CVC ecological niche represents the status of theCVC ecological community with large companies andstartups as the core to own and control human resourcestechnical resources capital and other social resources aswell as the adaptability to the innovative ecological envi-ronment and the comprehensive use of various resources+e healthy growth of CVC ecological communities requiresspecific analysis of internal and external environmentalecological factors including limiting factors and interestfactors +e limiting factor is the bottleneck that restricts thedevelopment of the CVC ecological community Both thelarge enterprise population and the entrepreneurial enter-prise population focus on easing the constraint of thelimiting factor to enhance the evolution capacity of theentire CVC ecological community At the same time theCVC ecological community also has benefit factors as its

driving force for development+e enhanced interest factorsof core populations can enable their respective niche evo-lution to achieve sustainable competitiveness and become anirreproducible and far-reaching advantage through theformation of core competitiveness +e large enterprisepopulation and entrepreneurial enterprise population in theCVC ecological community are usually in different positionsin the value chain +erefore the CVC ecological com-munity should make full use of the symbiotic resources onthe value chain unblock the symbiotic channels or formstrategic alliances or virtual industries to achieve coevolutionfor the niche +e large enterprise population and the en-trepreneurial enterprise population within the CVC eco-logical community implement corresponding nicheseparation strategies niche expansion strategies niche K-Rstrategies and niche alliance strategies

51 CVC Niche Separation Strategy If the niche overlapbetween large enterprises and startups in the CVC eco-logical community indicates that there is a certain in-dustry correlation between large companies and startupsthe competition is fierce when the niche overlaps betweenthe two In order to obtain more living space the two sidescan implement niche separation strategy Large enter-prises and startups can find the most suitable position fortheir own development through CVC activities +e coreof niche separation is to (a) use and integrate innovationand entrepreneurial resources (b) choose a combinationof ecological factors that are different from those ofcompetitors (c) have a stronger advantage at a certainposition of talent technology capital and social resourcegradients and (d) achieve heterogeneity and symmetryWhether it is a mature large enterprise or a startup en-terprise it can choose two different niche separationstrategies specialization strategy and generalizationstrategy +e specialization strategy is for narrow-nicheenterprises which can provide a small range of productsand services with characteristics to form an agglomerationstrategy to concentrate the various resources of species ina limited ecological space that is to focus on a certain stepin the value chain so that the niche overlap with otherspecies is reduced +e generalized strategy is similar tothe no-difference strategy for relatively wide nichecompanies and the risks are relatively small

In the CVC ecological community whether largecompanies and startups choose specialization or general-ization strategies is related to the richness of resources theycan use Generalization strategies can provide more survivalfor large companies with strong competitiveness Howeverearly stage startups which have limted resources while stillimplementing generalisation strategies would easily fail orbe acquired by large companies +erefore for startupcompanies specialization strategies are more conducive tomaintaining their own niche and reducing the ecologyoverlap with large enterprises to reduce competitionStartups in the CVC eco-community can also consideradopting a niche separation strategy from the time spaceand target market dimensions

Complexity 11

52 CVC Niche Expansion Strategy +e investment ofmature large enterprises in startup enterprises through CVCactivities is a niche expansion strategy It uses open-endedinnovation through venture capital to open up new resourcespaces acquire innovative technologies and thus achieve thepurpose of expanding the niche +ey aim to alleviate thecompetitive pressure brought by overlapping niche Forlarge enterprises the introduction of new and efficientecological elements is their original intention when choosingCVC It is also an effective means of exploring and devel-oping suitable options for their own development so thatthey can acquire financial benefits +e introduction of newecological elements can improve the utilization of variousresources in the innovation and entrepreneurship ecosys-tem Due to the obvious industry attributes of CVC and thehigh degree of innovation in the high-tech industry thetechnology has a high rate of change ie products andtechnologies will be updated faster +e uncertainty of in-dependent research and development is high so large en-terprises need to expand their niche through CVC For largeenterprises and startups with weak innovation ability weakinterorganizational learning ability and low absorptivecapacity and involvement especially for large companies itis worthwhile to raise the basic niche or explore potentialniche through CVC activities [17]

53 CVCNicheK-R Strategy Ray proposed a niche selectionstrategy +e K strategy indicates that by increasing com-petitiveness improving resource utilization efficiency andincreasing the environmental capacity of species in a stableenvironment a higher saturation density can be achieved+e R strategy means that by breeding in large numbersnew offspring can be adapted to the unstable environmentthereby identifying its own niche [18]

+e choice of K strategy will be limited by the envi-ronment When the niche develops to a certain degree it willreach the limit of affordability In the CVC ecologicalcommunity the development of large enterprise populationsalso follows the KR strategy +e large enterprise populationof the K strategy is characterized by a low reproduction rateand slow growth but it can achieve strategic goals throughCVC and continuously adapt to new environmentalchanges It has unique core competitiveness in related in-dustries Its products and services are not easily copied andimitated When large enterprises become the leadingcompanies in an industry environmental resources will bethe biggest obstacle to their development [19] +e startupsof R strategy are usually small in size are not constrained bythe environment and have a fast reproduction capacityWhen they grow to a certain degree the growth rate alsostarts to decline

+e CVC ecological community uses the R strategy andthe K strategy respectively +e abscissa indicates the size ofniche space occupied by the large enterprises and startups inthe ecological community at time t while the ordinaterepresents the size of the niche space occupied by species attime t+ 1 +e dotted line indicates that the size of the nichespace has not changed (Nt+1Nt 1) +e part above the

dotted line indicates that the ecology of large enterprises orstartups has become larger that is Nt+1 gtNt +e curvebelow the dotted line indicates that the niche space hasbecome smaller that is Nt+1 ltNt (Figure 10)

+ere are two intersections between the growth curveand the dotted line for K strategy X is an unstable equi-librium point [20] +ere may be two situations for largeenterprises or startups at point X First when the CVCecological community survives there are large niche spacesthat have not been occupied yet Companies using K strategyto grow rapidly Second the overall space of the CVCecological community has continued to shrink during therecession period until the K strategy companies die outWhen it is at a stable point it indicates the maximum ca-pacity of the ecosystem space and the maximum marketcapacity of technology talent capital social resources etcWhen the K strategy prevents the individual from fallingbelow stability the scale is expanded to achieve stabilityWhen the K strategy enterprise is above the stability pointits downsizing resumes [21]+e sustainable development ofthe CVC eco-community can be achieved if the large en-terprise population and the entrepreneurial enterprisepopulation in the CVC eco-community can adjust the nichecountermeasures in a timely and accurate manner at dif-ferent stages in the development process

54 CVC Niche Alliance Strategy In the CVC ecologicalcommunity large companies and startups can expand theirniche by establishing a mutually beneficial symbioticrelationship +is strategy is called the niche alliancestrategy When the weaker startups and the stronger largecompanies can improve their respective competitivenessthrough symbiotic relationships symbiotic parties in theCVC ecosystem can either choose their own appropriateniche or expand the boundaries of the entire ecologicalcommunity from the perspective of enhancing the sym-biotic system promoting the metabolism of the entireCVC ecological community based on innovation If theimplementation of the niche alliance strategy requires theevaluation of their respective niche the niche overlap andmarket crossover of both sides should be minimized toavoid parasitic or favorable symbiosis and form conflictsof interest [22] Large enterprises and startups can seekintersections that is new requirements between the twosides +ey can use the positive feedback effect of theinnovation and entrepreneurship environment to createhigher-level niche that is beneficial to both sides and canrealize the coevolution of the niche +e main motivationof CVC activities is that large enterprises need to seektechnological progress Entrepreneurs in small and me-dium habitats in the industry can obtain more coopera-tion resources through the form of CVC so that they canexpand their survival through cooperative technologicalinnovation management innovation and differentiatedservice innovation In this case they can expand the widthof the niche and then penetrate or embed other industries+e formation and evolution of large enterprises andentrepreneurial enterprises in the CVC ecological

12 Complexity

community will also generate greater benefits in their ownor other fields

Data Availability

+e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is study was sponsored by the National Social ScienceFund of China (Grant no 18CGL015)

References

[1] T Tykvova ldquoLegal framework quality and success of (differenttypes of) venture capital investmentsrdquo Journal of Banking ampFinance vol 87 no 2 pp 333ndash350 2018

[2] C H Dyer G P Hammond C I Jones and R C McKennaldquoEnabling technologies for industrial energy demand man-agementrdquo Energy Policy vol 36 no 12 pp 4434ndash4443 2008

[3] D P Hannah and K M Eisenhardt ldquoBottlenecks coopera-tion and competition in nascent ecosystemsrdquo StrategicManagement Journal vol 40 no 9 pp 1333ndash1335 2019

[4] L Luo P K Kannan and B T Ratchford ldquoNew productdevelopment under channel acceptancerdquo Marketing Sciencevol 26 no 2 pp 149ndash163 2007

[5] Y Yao and H Zhou ldquo+e dynamic equilibrium and simu-lation of mobile internet platform innovation ecosystemrdquoKybernetes vol 45 no 9 pp 1406ndash1420 2016

[6] D Firoiu and A G Croitoru ldquoTourism and tourism infra-structure from the perspective of technological changesrdquoRomanian Economic Business Review vol 8 no 8 pp 93ndash1032013

[7] D A Levinthal ldquoOrganizational adaptation and environ-mental selection-interrelated processes of changerdquo Organi-zation Science vol 2 no 1 pp 140ndash145 1991

[8] M Zaman Mir and A Shiraz Rahaman ldquo+e role of ac-counting in the enterprise bargaining process of an Australianuniversityrdquo Accounting Auditing amp Accountability Journalvol 16 no 2 pp 298ndash315 2003

[9] V Jog and B J Mcconomy ldquoVoluntary disclosure of man-agement earnings forecasts in IPO prospectuses[J]rdquo Journal ofBusiness Finance amp Accounting vol 30 no 2 pp 125ndash1682003

[10] Z Jing and L Xiong-Jian ldquoBusiness ecosystem strategies ofmobile network operators in the 3G era the case of ChinaMobilerdquo Telecommunications Policy vol 35 no 2 pp 156ndash171 2011

[11] T Wei Z Zhu Y Li and N Yao ldquo+e evolution of com-petition in innovation resource a theoretical study based onLotkandashVolterra modelrdquo Technology Analysis amp StrategicManagement vol 30 no 3 pp 295ndash310 2018

[12] S K Wilson R Fisher M S Pratchett et al ldquoHabitat deg-radation and fishing effects on the size structure of coral reeffish communitiesrdquo Ecological Applications vol 20 no 2pp 442ndash451 2010

[13] O Honnay B Bossuyt K Verheyen J Butaye H Jacquemynand M Hermy ldquoEcological perspectives for the restoration ofplant communities in European temperate forestsrdquo Biodi-versity and Conservation vol 11 no 2 pp 213ndash242 2002

[14] T L Vincent M V Van and B S Goh ldquoEcological stabilityevolutionary stability and the ESS maximum principlerdquoEvolutionary Ecology vol 10 no 6 pp 567ndash591 1996

[15] I Loera V Sosa and S M Ickert-Bond ldquoDiversification inNorth American arid lands niche conservatism divergenceand expansion of habitat explain speciation in the genusEphedrardquo Molecular Phylogenetics and Evolution vol 65no 2 pp 437ndash450 2012

[16] J Li Y Huang and X Niu ldquoA branch population geneticalgorithm for dual-resource constrained job shop schedulingproblemrdquo Computers amp Industrial Engineering vol 102no 12 pp 113ndash131 2016

[17] B Herault ldquoReconciling niche and neutrality through theEmergent Group approachrdquo Perspectives in Plant EcologyEvolution and Systematics vol 9 no 2 pp 71ndash78 2007

[18] S K Ray ldquoEffect of phosphorus on carbon activity carbideprecipitation and coarsening in ferritic Feminus Cminus P alloysrdquoMetallurgical Transactions A vol 22 no 1 pp 35ndash43 1991

[19] B Lavm and E Nevo ldquoGenetic diversity in marine molluscs atest of the niche-width variation hypothesisrdquoMarine Ecologyvol 2 no 4 pp 335ndash342 1981

[20] C Xu ldquoA novel recommendation method based on socialnetwork using matrix factorization techniquerdquo InformationProcessing amp Management vol 54 no 3 pp 463ndash474 2018

[21] Z Chen Y Zhang C Wu and B Ran ldquoUnderstandingindividualization driving states via latent dirichlet allocationmodelrdquo IEEE Intelligent Transportation Systems Magazinevol 11 no 2 pp 41ndash53 2019

[22] Z Xie R Lin J Wang W Hu and L Miao ldquoVicariouslearning how entrepreneurs enhance a Firmrsquos internationalcompetitiveness through learning from interlocking directornetwork partnersrdquo Frontiers in Psychology vol 11 p 6892020

E

QR

PO

Figure 10 Coevolution of niche-cooperation relationships in CVCecological communities

Complexity 13

constraints of the companyrsquos internal RampD budget so thatthey can improve technology innovation efficiency It couldalso reduce the risk of investment in independent RampD andimprove organizational capabilities to foster an innovationculture It benefits the corporate by realizing the value ofstrategic mergers and acquisitions and initiating entrepre-neurial investment in strategic innovation projects Ascompanyrsquos venture capital has a high degree of risk toleranceand a long investment cycle it can invest in the startups thatare struggling to obtain traditional independent venturecapital (IVC) It promotes and optimizes mutual regener-ation and achieves a better evolutionary cycle for bothparties While mature companies deeply cultivate the RedSea they must also actively explore in the Blue Ocean CVCis a hybrid model that stimulates innovation It expandsindustrial boundaries rebuilds market boundaries explorescutting-edge technologies encourages open innovation andexpands organizational structures for large companies It isregarded as an effective paradigm to promote the evolutionof the industry ecosystem It is also an important way forlarge companies to acquire innovative technologies andindustrial integration [2] CVC activities are a ldquodual andtwo-wayrdquo value creation process that includes both strategicand financial values while creating value for mature largecompanies and startups With the advent of the digitaleconomy 20 era ecological collaborative innovation modelshave gradually taken shape Typical digital economy com-panies in China such as Alibaba Tencent Xiaomi andBaidu as well as traditional enterprises such as Haier andFosun are actively building open innovation enterpriseecosystems +ey integrate the companyrsquos own technologycapital and market advantages with external resources todevelop new technologies new products and new modelsfor new markets

2 Related Work

Hannah and Eisenhardt proposed that in addition to therelationship between competition and cooperation enter-prises also need to continuously meet customer needsthrough innovation [3] Enterprises have evolved from therole of an individual player in the industry into part of theindustrial ecosystem Luo and Ratchford took Apple IBMFord and Wal-Mart as examples to study focal companieswhich develop service technology and value networkplatforms to build their own unique business ecosystems andobtain value returns [4] Yao and Zhou used the theory ofnatural ecosystem evolution to study the innovation path ofhigh-tech enterprises and found that the dependence ofenterprise innovation paths has ecological genetic andvariability characteristics [5] Daniela et al in ldquoEvolutionary+eory of Economic Changerdquo explain economic changesfrom a perspective of dynamic evolution Evolutionary gametheory pays attention to the change of population structureand uses evolutionary stable strategy (ESS) to represent astable state that can resist the invasion of mutation strategy[6] Levinthal proposed that corporate adaptation and en-vironmental selection are the main paths of populationevolution [7] Zaman et al believe that internal and external

resources of an enterprise are equally important Enterprisesuse external resources and external channels to help com-mercialize their new technological achievements +ey alsoemphasize that enterprises should quickly implement in-novation reduce innovation costs and work with profes-sional venture capital institutions to jointly improveinnovation performance [8]

One of the most challenging 125 scientific issues in the21st century in science is ldquohow does cooperative behaviorevolverdquo +e innovation ecosystem has the same charac-teristics of natural evolution integration self-organizationperiodicity and openness as natural ecosystems and sharesthe same characteristics in power genetics evolution andfeedback Important scholars in the CVC field Jog andMcconomy creatively proposed that mature large compa-nies have regarded CVC not only as the window for tech-nology discovery but also as an ecosystem around largecompanies [9]+is conclusion is based on previous researchon CVC enterprise value creation CVC investment enter-prise entrepreneurial performance investment conditionsand cross-organizational knowledge acquisitionBased onthe analysis of nearly 300 CVCs Jog and Mcconomy pro-posed that the increasing number of CVCs would contributein better short-term and long-term performance of theecosystem which extends a previous view shared by scholarsthat the CVC is only an incubator-level participant Insteadas an ecosystem strategy CVC intends to ldquobuild a con-stellationrdquo [10] +erefore from the perspective of theecosystem and the niche theory it is proposed that the CVCecological community formed by mature large companiesand startups in the form of CVC projects achieves syn-chronization through interactions between CVC functionsbehavioral processes and the external environment In thesymbiotic mode a symbiotic evolution can be developedwith the growth of large companies and entrepreneurialenterprises

3 CVC Niche for Major Corporations andEntrepreneurial Firms

In 1838 the Dutch mathematical biologist Verhulst pro-posed a logistic equation to study the growth of biologicalpopulations It was found that the population grew fastest atthe beginning When it grew to a certain value the speedbegan to slow down until it finally decreased to zero (iestop growing) In 1900 Italian mathematician Volterraproposed the predator and prey populations model In 1925Lotka proposed mathematical ecology in chemical reactions+en in 1926 Volterra used the LotkandashVolterra model todemonstrate the rule of fish population in the port of FiumeLotkandashVolterra model which evolved from the logisticextended model can better explain the relationship betweenlarge companies and startups in the CVC ecological com-munity +is model as an evolutionary game for species orpopulation formation provides a new perspective to un-derstand community structure optimization and nicheevolution [11]

+e growth of the corporate ecological community in-volved in CVC also generally conforms to the mechanism of

2 Complexity




dS1(t)


dS2(t)


⎧⎪⎪⎪⎨

⎪⎪⎪⎩

(1)







P1

P2


t

CVC

nich

e


Complexity 3









O(0 0) H1(ρ1 + χ1 minus α1 0)




1 minus β21113888 1113889

(2)






Majorcorporations


L2

L1


4 Complexity

H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0



Majorcorporations

L1

L2



Majorcorporations

L2

L1


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0


Complexity 5






1 minus β21113888 1113889

(3)













6 Complexity






U12 q R1 + e( 1113857 +(1 minus q)R1 qe + R1



(4)




U22 p R2 + e( 1113857 +(1 minus p)R2 e + R2




(5)


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0G


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0P



Subject nichein CVC

EFExpanding

nicheMaintaining

niche




Complexity 7

F(p) dp

dt p U11 minus U1( 1113857


F(q) dq

dt q U22 minus U2( 1113857


(6)


F(p) dp

dt p U11 minus U1( 1113857


(7)


d2p




F(q) dq

dt q U22 minus U2( 1113857


(9)


















(10)


F(p) dp

dt p U11 minus U1( 1113857


(11)

8 Complexity











+(1 minus q) p e + T2S2( 1113857 + R21113858 1113859


+ p e + T2S2( 1113857 + R2

(12)


F(q) dq

dt q U22 minus U2( 1113857


(13)








SQOPE 12


times 1 times Ey 12

Ex + Ey1113872 1113873

12

C1

λ(a + b)Δr minus e + T1S1( 1113857+

C2


(14)




zS

zC112

times1


zS

zC212

times1


(15)



zS

za12

C2


⎡⎣

minusC1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(16)



Subject nichein CVC

EF





Complexity 9

z2S

z2a

C2Δr2


minusC1Δr3


(17)


z2S

z2a

C2Δr2


minusC1Δr3

λ(a + b)Δr minus e + T1S1( 11138571113858 11138593 0

(18)

we obtainC2


C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592

(19)



zT112

C1


zS

zS112

C1


zS

zT212

C1


zS

zS212

C1


(20)



zS

ze12

C2


⎡⎣

+C1


(21)



zS

zΔ r minus

12



⎡⎣

+λ(a + b)C1


(22)



CVC

nich

e evo

lutio

n


Cooperation

Competition balance


St

S3

S2

S1


10 Complexity


zS

zλ minus

12



⎡⎣

+λ(a + b)C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(23)








Complexity 11








12 Complexity


Data Availability




Acknowledgments


References























E

QR

PO


Complexity 13




dS1(t)


dS2(t)


⎧⎪⎪⎪⎨

⎪⎪⎪⎩

(1)







P1

P2


t

CVC

nich

e


Complexity 3









O(0 0) H1(ρ1 + χ1 minus α1 0)




1 minus β21113888 1113889

(2)






Majorcorporations


L2

L1


4 Complexity

H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0



Majorcorporations

L1

L2



Majorcorporations

L2

L1


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0


Complexity 5






1 minus β21113888 1113889

(3)













6 Complexity






U12 q R1 + e( 1113857 +(1 minus q)R1 qe + R1



(4)




U22 p R2 + e( 1113857 +(1 minus p)R2 e + R2




(5)


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0G


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0P



Subject nichein CVC

EFExpanding

nicheMaintaining

niche




Complexity 7

F(p) dp

dt p U11 minus U1( 1113857


F(q) dq

dt q U22 minus U2( 1113857


(6)


F(p) dp

dt p U11 minus U1( 1113857


(7)


d2p




F(q) dq

dt q U22 minus U2( 1113857


(9)


















(10)


F(p) dp

dt p U11 minus U1( 1113857


(11)

8 Complexity











+(1 minus q) p e + T2S2( 1113857 + R21113858 1113859


+ p e + T2S2( 1113857 + R2

(12)


F(q) dq

dt q U22 minus U2( 1113857


(13)








SQOPE 12


times 1 times Ey 12

Ex + Ey1113872 1113873

12

C1

λ(a + b)Δr minus e + T1S1( 1113857+

C2


(14)




zS

zC112

times1


zS

zC212

times1


(15)



zS

za12

C2


⎡⎣

minusC1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(16)



Subject nichein CVC

EF





Complexity 9

z2S

z2a

C2Δr2


minusC1Δr3


(17)


z2S

z2a

C2Δr2


minusC1Δr3

λ(a + b)Δr minus e + T1S1( 11138571113858 11138593 0

(18)

we obtainC2


C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592

(19)



zT112

C1


zS

zS112

C1


zS

zT212

C1


zS

zS212

C1


(20)



zS

ze12

C2


⎡⎣

+C1


(21)



zS

zΔ r minus

12



⎡⎣

+λ(a + b)C1


(22)



CVC

nich

e evo

lutio

n


Cooperation

Competition balance


St

S3

S2

S1


10 Complexity


zS

zλ minus

12



⎡⎣

+λ(a + b)C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(23)








Complexity 11








12 Complexity


Data Availability




Acknowledgments


References























E

QR

PO


Complexity 13









O(0 0) H1(ρ1 + χ1 minus α1 0)




1 minus β21113888 1113889

(2)






Majorcorporations


L2

L1


4 Complexity

H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0



Majorcorporations

L1

L2



Majorcorporations

L2

L1


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0


Complexity 5






1 minus β21113888 1113889

(3)













6 Complexity






U12 q R1 + e( 1113857 +(1 minus q)R1 qe + R1



(4)




U22 p R2 + e( 1113857 +(1 minus p)R2 e + R2




(5)


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0G


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0P



Subject nichein CVC

EFExpanding

nicheMaintaining

niche




Complexity 7

F(p) dp

dt p U11 minus U1( 1113857


F(q) dq

dt q U22 minus U2( 1113857


(6)


F(p) dp

dt p U11 minus U1( 1113857


(7)


d2p




F(q) dq

dt q U22 minus U2( 1113857


(9)


















(10)


F(p) dp

dt p U11 minus U1( 1113857


(11)

8 Complexity











+(1 minus q) p e + T2S2( 1113857 + R21113858 1113859


+ p e + T2S2( 1113857 + R2

(12)


F(q) dq

dt q U22 minus U2( 1113857


(13)








SQOPE 12


times 1 times Ey 12

Ex + Ey1113872 1113873

12

C1

λ(a + b)Δr minus e + T1S1( 1113857+

C2


(14)




zS

zC112

times1


zS

zC212

times1


(15)



zS

za12

C2


⎡⎣

minusC1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(16)



Subject nichein CVC

EF





Complexity 9

z2S

z2a

C2Δr2


minusC1Δr3


(17)


z2S

z2a

C2Δr2


minusC1Δr3

λ(a + b)Δr minus e + T1S1( 11138571113858 11138593 0

(18)

we obtainC2


C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592

(19)



zT112

C1


zS

zS112

C1


zS

zT212

C1


zS

zS212

C1


(20)



zS

ze12

C2


⎡⎣

+C1


(21)



zS

zΔ r minus

12



⎡⎣

+λ(a + b)C1


(22)



CVC

nich

e evo

lutio

n


Cooperation

Competition balance


St

S3

S2

S1


10 Complexity


zS

zλ minus

12



⎡⎣

+λ(a + b)C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(23)








Complexity 11








12 Complexity


Data Availability




Acknowledgments


References























E

QR

PO


Complexity 13

H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0



Majorcorporations

L1

L2



Majorcorporations

L2

L1


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0


Complexity 5






1 minus β21113888 1113889

(3)













6 Complexity






U12 q R1 + e( 1113857 +(1 minus q)R1 qe + R1



(4)




U22 p R2 + e( 1113857 +(1 minus p)R2 e + R2




(5)


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0G


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0P



Subject nichein CVC

EFExpanding

nicheMaintaining

niche




Complexity 7

F(p) dp

dt p U11 minus U1( 1113857


F(q) dq

dt q U22 minus U2( 1113857


(6)


F(p) dp

dt p U11 minus U1( 1113857


(7)


d2p




F(q) dq

dt q U22 minus U2( 1113857


(9)


















(10)


F(p) dp

dt p U11 minus U1( 1113857


(11)

8 Complexity











+(1 minus q) p e + T2S2( 1113857 + R21113858 1113859


+ p e + T2S2( 1113857 + R2

(12)


F(q) dq

dt q U22 minus U2( 1113857


(13)








SQOPE 12


times 1 times Ey 12

Ex + Ey1113872 1113873

12

C1

λ(a + b)Δr minus e + T1S1( 1113857+

C2


(14)




zS

zC112

times1


zS

zC212

times1


(15)



zS

za12

C2


⎡⎣

minusC1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(16)



Subject nichein CVC

EF





Complexity 9

z2S

z2a

C2Δr2


minusC1Δr3


(17)


z2S

z2a

C2Δr2


minusC1Δr3

λ(a + b)Δr minus e + T1S1( 11138571113858 11138593 0

(18)

we obtainC2


C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592

(19)



zT112

C1


zS

zS112

C1


zS

zT212

C1


zS

zS212

C1


(20)



zS

ze12

C2


⎡⎣

+C1


(21)



zS

zΔ r minus

12



⎡⎣

+λ(a + b)C1


(22)



CVC

nich

e evo

lutio

n


Cooperation

Competition balance


St

S3

S2

S1


10 Complexity


zS

zλ minus

12



⎡⎣

+λ(a + b)C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(23)








Complexity 11








12 Complexity


Data Availability




Acknowledgments


References























E

QR

PO


Complexity 13






1 minus β21113888 1113889

(3)













6 Complexity






U12 q R1 + e( 1113857 +(1 minus q)R1 qe + R1



(4)




U22 p R2 + e( 1113857 +(1 minus p)R2 e + R2




(5)


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0G


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0P



Subject nichein CVC

EFExpanding

nicheMaintaining

niche




Complexity 7

F(p) dp

dt p U11 minus U1( 1113857


F(q) dq

dt q U22 minus U2( 1113857


(6)


F(p) dp

dt p U11 minus U1( 1113857


(7)


d2p




F(q) dq

dt q U22 minus U2( 1113857


(9)


















(10)


F(p) dp

dt p U11 minus U1( 1113857


(11)

8 Complexity











+(1 minus q) p e + T2S2( 1113857 + R21113858 1113859


+ p e + T2S2( 1113857 + R2

(12)


F(q) dq

dt q U22 minus U2( 1113857


(13)








SQOPE 12


times 1 times Ey 12

Ex + Ey1113872 1113873

12

C1

λ(a + b)Δr minus e + T1S1( 1113857+

C2


(14)




zS

zC112

times1


zS

zC212

times1


(15)



zS

za12

C2


⎡⎣

minusC1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(16)



Subject nichein CVC

EF





Complexity 9

z2S

z2a

C2Δr2


minusC1Δr3


(17)


z2S

z2a

C2Δr2


minusC1Δr3

λ(a + b)Δr minus e + T1S1( 11138571113858 11138593 0

(18)

we obtainC2


C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592

(19)



zT112

C1


zS

zS112

C1


zS

zT212

C1


zS

zS212

C1


(20)



zS

ze12

C2


⎡⎣

+C1


(21)



zS

zΔ r minus

12



⎡⎣

+λ(a + b)C1


(22)



CVC

nich

e evo

lutio

n


Cooperation

Competition balance


St

S3

S2

S1


10 Complexity


zS

zλ minus

12



⎡⎣

+λ(a + b)C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(23)








Complexity 11








12 Complexity


Data Availability




Acknowledgments


References























E

QR

PO


Complexity 13






U12 q R1 + e( 1113857 +(1 minus q)R1 qe + R1



(4)




U22 p R2 + e( 1113857 +(1 minus p)R2 e + R2




(5)


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0G


H1

H2

H4

H3


Majorcorporations

L1

L2

dS1 (t)dt = 0

dS2 (t)dt = 0P



Subject nichein CVC

EFExpanding

nicheMaintaining

niche




Complexity 7

F(p) dp

dt p U11 minus U1( 1113857


F(q) dq

dt q U22 minus U2( 1113857


(6)


F(p) dp

dt p U11 minus U1( 1113857


(7)


d2p




F(q) dq

dt q U22 minus U2( 1113857


(9)


















(10)


F(p) dp

dt p U11 minus U1( 1113857


(11)

8 Complexity











+(1 minus q) p e + T2S2( 1113857 + R21113858 1113859


+ p e + T2S2( 1113857 + R2

(12)


F(q) dq

dt q U22 minus U2( 1113857


(13)








SQOPE 12


times 1 times Ey 12

Ex + Ey1113872 1113873

12

C1

λ(a + b)Δr minus e + T1S1( 1113857+

C2


(14)




zS

zC112

times1


zS

zC212

times1


(15)



zS

za12

C2


⎡⎣

minusC1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(16)



Subject nichein CVC

EF





Complexity 9

z2S

z2a

C2Δr2


minusC1Δr3


(17)


z2S

z2a

C2Δr2


minusC1Δr3

λ(a + b)Δr minus e + T1S1( 11138571113858 11138593 0

(18)

we obtainC2


C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592

(19)



zT112

C1


zS

zS112

C1


zS

zT212

C1


zS

zS212

C1


(20)



zS

ze12

C2


⎡⎣

+C1


(21)



zS

zΔ r minus

12



⎡⎣

+λ(a + b)C1


(22)



CVC

nich

e evo

lutio

n


Cooperation

Competition balance


St

S3

S2

S1


10 Complexity


zS

zλ minus

12



⎡⎣

+λ(a + b)C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(23)








Complexity 11








12 Complexity


Data Availability




Acknowledgments


References























E

QR

PO


Complexity 13

F(p) dp

dt p U11 minus U1( 1113857


F(q) dq

dt q U22 minus U2( 1113857


(6)


F(p) dp

dt p U11 minus U1( 1113857


(7)


d2p




F(q) dq

dt q U22 minus U2( 1113857


(9)


















(10)


F(p) dp

dt p U11 minus U1( 1113857


(11)

8 Complexity











+(1 minus q) p e + T2S2( 1113857 + R21113858 1113859


+ p e + T2S2( 1113857 + R2

(12)


F(q) dq

dt q U22 minus U2( 1113857


(13)








SQOPE 12


times 1 times Ey 12

Ex + Ey1113872 1113873

12

C1

λ(a + b)Δr minus e + T1S1( 1113857+

C2


(14)




zS

zC112

times1


zS

zC212

times1


(15)



zS

za12

C2


⎡⎣

minusC1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(16)



Subject nichein CVC

EF





Complexity 9

z2S

z2a

C2Δr2


minusC1Δr3


(17)


z2S

z2a

C2Δr2


minusC1Δr3

λ(a + b)Δr minus e + T1S1( 11138571113858 11138593 0

(18)

we obtainC2


C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592

(19)



zT112

C1


zS

zS112

C1


zS

zT212

C1


zS

zS212

C1


(20)



zS

ze12

C2


⎡⎣

+C1


(21)



zS

zΔ r minus

12



⎡⎣

+λ(a + b)C1


(22)



CVC

nich

e evo

lutio

n


Cooperation

Competition balance


St

S3

S2

S1


10 Complexity


zS

zλ minus

12



⎡⎣

+λ(a + b)C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(23)








Complexity 11








12 Complexity


Data Availability




Acknowledgments


References























E

QR

PO


Complexity 13











+(1 minus q) p e + T2S2( 1113857 + R21113858 1113859


+ p e + T2S2( 1113857 + R2

(12)


F(q) dq

dt q U22 minus U2( 1113857


(13)








SQOPE 12


times 1 times Ey 12

Ex + Ey1113872 1113873

12

C1

λ(a + b)Δr minus e + T1S1( 1113857+

C2


(14)




zS

zC112

times1


zS

zC212

times1


(15)



zS

za12

C2


⎡⎣

minusC1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(16)



Subject nichein CVC

EF





Complexity 9

z2S

z2a

C2Δr2


minusC1Δr3


(17)


z2S

z2a

C2Δr2


minusC1Δr3

λ(a + b)Δr minus e + T1S1( 11138571113858 11138593 0

(18)

we obtainC2


C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592

(19)



zT112

C1


zS

zS112

C1


zS

zT212

C1


zS

zS212

C1


(20)



zS

ze12

C2


⎡⎣

+C1


(21)



zS

zΔ r minus

12



⎡⎣

+λ(a + b)C1


(22)



CVC

nich

e evo

lutio

n


Cooperation

Competition balance


St

S3

S2

S1


10 Complexity


zS

zλ minus

12



⎡⎣

+λ(a + b)C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(23)








Complexity 11








12 Complexity


Data Availability




Acknowledgments


References























E

QR

PO


Complexity 13

z2S

z2a

C2Δr2


minusC1Δr3


(17)


z2S

z2a

C2Δr2


minusC1Δr3

λ(a + b)Δr minus e + T1S1( 11138571113858 11138593 0

(18)

we obtainC2


C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592

(19)



zT112

C1


zS

zS112

C1


zS

zT212

C1


zS

zS212

C1


(20)



zS

ze12

C2


⎡⎣

+C1


(21)



zS

zΔ r minus

12



⎡⎣

+λ(a + b)C1


(22)



CVC

nich

e evo

lutio

n


Cooperation

Competition balance


St

S3

S2

S1


10 Complexity


zS

zλ minus

12



⎡⎣

+λ(a + b)C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(23)








Complexity 11








12 Complexity


Data Availability




Acknowledgments


References























E

QR

PO


Complexity 13


zS

zλ minus

12



⎡⎣

+λ(a + b)C1

λ(a + b)Δr minus e + T1S1( 11138571113858 11138592⎤⎦

(23)








Complexity 11








12 Complexity


Data Availability




Acknowledgments


References























E

QR

PO


Complexity 13








12 Complexity


Data Availability




Acknowledgments


References























E

QR

PO


Complexity 13


Data Availability




Acknowledgments


References























E

QR

PO


Complexity 13

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Research on the Niche Evolution Game of Ecological ...downloads.hindawi.com/journals/complexity/2020/6327218.pdf · 4/17/2020 · ResearchArticle Research on the Niche Evolution