The effect of social proximity on degree distribution of Scale-free network

With limited resources in knowledge seeking, firms are more likely to connect with influential firms in adjacent areas according to preferential attachment mechanism of BA model, and thus geographical proximity plays an important role in shaping typology of a scale-free network. However, prior researches, adopting BA model, cannot explain why there are more and more nonlocal ties constructed via social relationships of local firms in industrial clusters. This paper proposed a new model by changing the rule of preferential attachment to detect the effect of social proximity on the typology of scale-free network through simulation. The results indicate that the distance of in-degree between core and peripheral nodes would decrease with the expanding of searching range and number of connections affecting by social proximity. Though the degree distribution still follows power-laws, peripheral nodes are less depended on core actors in accessing to external knowledge in case that social proximity rather than geographical proximity becomes the main factor in actors' knowledge seeking strategy.