The concepts of proximity have been utilized for exploring both psychological and geographical incentives for users within social networks to collaborate with others for mutual goals. The massive information does not facilitate quality decision support. In this chapter, we focus on discovering the proximal social intelligence for quality decision support. The utilization of investigating both the context and the content of the application domain from social network relationships would highly improve the information quality for better decisions. Discovering proximal social intelligence from user's personal context they encountered enable the improvement of decision-making quality. We illustrate a case of leisure recommendatory e-service for bicycle exercise entertainment in Taiwan. We introduce the proximity e-service as well as its theoretical support. The most recent personalized experience according to its context provides remarkable perceptual data from unique information sources. Moreover, the social network relationships extend the power of the unique perceptual information to converge as the collective social network intelligence.
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