3.2 Model setting
（1）regional enterprise innovation population relationship model
According to the relevant hypotheses，the internal relationship model of enterprise innovation population（population 1）is constructed.According to the Logistic model，we can get：
g1（t） indicates population growth rate of phase t.N1（t） indicates the number of individuals of population in phase t.
represents the amount of resources occupied by populations of phase t.Within a population of an innovation ecosystem，each unit occupies resources as 
.
ΔN1（t） is the number of individuals in a population during the T period.Usually α1＞0，Indicating synergistic effects within populations.
，Usually β2＜0，Represents the internal competition effect of the population.The coefficient of internal competition or population density is called the inhibitory factor.
If｛β1＋β2N1（t-1｝）＞1，thenΔN1（t）＞0.The synergistic effects were dominant in the population.Resources within an innovative ecosystem can support an increase in the number of individuals in an innovation population.Growth can be sustained.
If｛β1＋β2N1（t-1｝）＜1，thenΔN1（t）＜0.The competition effect is dominant in the population.Innovative resources are difficult to support the increase in the number of individuals in the innovation population.Growth is unsustainable.
（2）influence of adjacent area on innovation population
Considering the adjacent region，the enterprise innovation population（population 2）affects the enterprise innovation population（population 1）.According to the Logistic model，we can get：
g1（t）indicates population growth rate of phase t.N1（t） indicates the number of individuals in phase t population.
represents the amount of resources occupied by populations of phase t.Within a population of an innovation ecosystem，each unit occupies resources as 
.
ΔN1（t）is the number of individuals in a population during the T period.Usually α1＞0，Indicating synergistic effects within populations.
，Usually β2＜0，Represents the internal competition effect of the population.The coefficient of internal competition or population density is called the inhibitory factor.
If 
，then ΔN1（t）＞0.The effect of neighborhood population is mainly synergistic effect.Resources in an innovative ecosystem of adjacent areas can support an increase in the number of individuals in an innovation population.Growth can be sustained.
If 
，then ΔN1（t）＜0.The influence of adjacent populations is dominated by competition.Resources in an innovative ecosystem of adjacent areas are difficult to support an increase in the number of individuals in an innovation population.Growth is unsustainable.
（3）the influence of innovative population on adjacent regional innovation population
The regression models（4），（8）and（9）are constructed by formula（10），（11）and（12）
Judge by the result of the regression model.Each model may have three conclusions：“not significant”，“competition is greater than synergy”and“synergy is greater than competition”.According to the results of the three models，each enterprise innovation population has its own population relationship vector.According to the results of the three models，each enterprise innovation population has its own population relationship vector.
The vector of population relations is R（r1，r2，r3）.
r1 is the analysis results for model（10）.
r2 is the analysis results for model（11）.
r3 is the analysis results for model（12）.
This population relationship vector is a three dimensional row vector，and there are 27 combinations.Among them，there are three special cases：R1（collaboration，collaboration，collaboration），R2（competition，competition，competition），R3（not significant，not significant，not significant）.
The area of enterprise innovation population relationship shows that the region of R1is the core of innovation in the whole region.Not only does the enterprise relationship in this region show greater synergy than competition，but also the neighborhood and adjacent area show synergistic relationship.Innovation core area is the leading force of promoting collaborative innovation in the whole region.
The most competitive area for enterprise innovation in the whole region is the region with the relationship between enterprise innovation and population shows R2.Innovative enterprises in the region are facing dual pressures of competition between regional and contiguous regions.
Isolated areas of innovation throughout the region is that the region with the relationship between enterprise innovation and population shows R3.There is no significant relationship between the endogenous population relationship in the innovation region and the innovation population in the adjacent region.