The economic approach of cost-benefit analysis plays an important role in analyzing biodiversity conservation, especially in rapidly urbanizing areas. In the existing Chinese academic literature, cost-benefit analyses have been applied in studies on habitat conservation, ecological land protection, and ecological networks. The present study addresses a gap in the research, by determining the effects of a cost-benefit analysis approach on habitat network optimization. Furthermore, this study uses a cross-disciplinary approach between methodologies in economics and ecology, to examine the impacts of the economic approach and ecological processes on network optimization methodology. As a case study, we focused on the Su-Xi-Chang area of the Yangtze River Delta Region, with the little egret (Egretta garzetta) as a regional representative species. We hypothesized that adding new habitat patches would improve network connectivity, and help with network optimization. The study assessed the size and the land use type of 35 identified habitat patches, which were the prior research results. The cost of avoiding the transfer from the current habitat into other land use types, especially construction land, was treated as the protect-cost, which was derived from local prices for land acquisition. From the perspective of network structure, the benefit of habitat network connectivity improvement was represented as a comprehensive indicator generated from three different indexes. These indexes included the number of newly added corridors, the betweenness, and the node degree. The protect-cost of each habitat patch could be matched to its corresponding benefit value for different purposes. The study design considered five different conditions and six scenarios. Scenario 1 was formed from the perspective of minimum cost accumulation, whereas scenarios 2 to 5 focused on maximum benefit accumulation, best effectiveness accumulation, and two limited effectiveness accumulations, respectively. Scenario 6 was the ideal condition meaning with all 35 habitat patches being added as the ideal result of habitat network optimization. The results indicate that (1) scenario 2 of maximum benefit accumulation resulted in network optimization with a lower total cost compared to scenario 6. Scenario 3 of best effectiveness accumulation resulted in network optimization with the least protected area, and associated cost. (2) The effects of the scenarios of best effectiveness accumulation, as well as the one of minimum cost accumulation (i.e., scenario 3 and scenario 1, respectively) were similar. However, the total cost of scenario 3 was only 74 percent of that of scenario 1. This indicates that scenario 3 of best effectiveness accumulation maximized effectiveness with the least cost, and was suitable for rapidly urbanizing areas with scarce land resources. (3) The effects of the two scenarios of limited effectiveness accumulation, (i.e., scenario 4 and scenario 5) were in between the effects of scenario 1 of minimum cost accumulation and scenario 2 of maximum benefit accumulation. This indicates that all scenarios of limited effectiveness accumulation would realize the aim of better effectiveness with lower cost. Furthermore, it indicated that scenario 3 of best effectiveness accumulation was gained under special circumstances. In economics, this phenomenon is referred to as the marginal benefit. Overall, the combined method detailed here, along with ecological, economic, and social factors, contributes to habitat network optimization, and highlights the methodology of network optimization.