1. For several decades now, social scientists have been increasingly interested in understanding social processes at the individual level, which aligns with the broader themes in complexity science...

This study is aimed to compare the strengths and weaknesses of three approaches—analytic hierarchy process analysis, sentiment analysis, and floating population analysis—in estimating the social demands for local forest ecosystem services (ES) in South Korea: Gariwangsan and Yeoninsan. The results were as follows: First, the survey respondents of Gariwangsan and Yeoninsan believed that the cultural ES category was the most fundamental one that should be maintained, whereas they thought the supporting ES category needed the least maintenance. Second, both forests had a high frequency of sentiment words related to the cultural ES category, followed by the regulating ES category, such as air and water quality improvement. Third, the spatiotemporal distribution of the floating populations in both forests was concentrated in their valleys and mountainous areas, indicating the finer-scale demands for the cultural and regulating ES category. Fourth, the research shows the areas that are high in demand and those that are not; this result helps forest management. In conclusion, none of the three methodologies was superior to the other two, as they each captured distinct ES demands. To investigate ES demands in a multifaceted way, we suggest applying the three approaches in tandem.

Most of the existing studies on relieving bottlenecks have aimed to develop route-finding algorithms that consider structural factors such as passages and stairs, as well as human factors such as density and speed. However, the methods in providing evacuation routes are as important as the route-making algorithms because a secondary bottleneck could occur continuously during evacuations. Even if an evacuation system provides the same routes to all evacuees regardless of their locations, secondary bottlenecks could happen following the initial bottlenecks due to people rushing toward uncrowded exits all together. To address this issue, we developed a location-based service (LBS) evacuation system prototype that provides optimized-alternative routes to evacuees in real time considering their locations in indoor space. The system was designed to relieve continuous bottlenecks, which relies on installed IoT sensors and beacon machines which detect bottlenecks and provide updated routes, separately. Next, we conducted agent-based simulations to measure the system’s effectiveness (evacuation time reduction and dispersion of evacuees) by changing the system parameters. Simulation results show the evacuation time decreased from 100 to 65 s, and the number of people who took a detour to avoid bottlenecks increased by 28.66% out of the total evacuees with this system. Since this system provides the theoretical solution for distributing evacuees, it can be flexibly employed to a disaster situation in a large and complex indoor environment by applying to other evacuation systems. Moreover, by adjusting parameters, we can derive maximum evacuation effectiveness in other indoor spaces. Future work will consider demographic features of population and multilayer building structure to draw a more accurate pedestrian flow.