In high-rise residential buildings (HRBs), elevators run at a high speed, which causes problems such as change of atmospheric pressure, noise, and vibration. Elevator noise and vibration (ENV) of HRBs causes both mental anxiety and a consistently negative effect for promoting a comfortable residential area. Therefore, a solution for alleviating the ENV of HRBs is essential. To date, studies related to ENV have been mostly conducted in the approach of mechanical and electric aspects. There have been few cases conducted from the perspective of construction management (CM), which integrates design and construction. Therefore, the aim of this study is to propose CM solutions to mitigate the ENV of HRB. For this study, the CM solution is presented after identifying the ENV problems of HRBs through documented research and case measurement. By measuring the noise of HRB that the solution was applied to, the noise level, especially in a range of >125 Hz, was extensively reduced. The result of this study will be used as sustainable guidelines that alleviate ENV problems in the process of design and construction of HRB elevators. It is expected that studies for improving ENV problems that occur in high-rise elevators will increase on the basis of the results of this study.

Many factors influence the success of apartment development projects, but it is difficult to quantitatively measure them. In terms of risk control, the five most direct influence factors are sales ratio, unit sale price, financial cost, land cost, and construction cost. These factors will vary during the project, from planning to land purchase to design to sale to construction, and the levels of these factors will also affect project performance. Therefore, it is necessary to dynamically forecast, control and monitor, and manage these factors in order to successfully implement apartment development projects. This study develops a dynamic simulation model to analyze the economic feasibility of apartment development projects. It draws a causal loop diagram of the aforementioned influence factors, develops a simulation model using system dynamics, and verifies the model with a case study of a 1,794-unit apartment development project. Using this simulation model, it is possible to quickly and easily simulate the economic effects of the risk factors that change throughout the project, analyze its economic feasibility, and develop a plan to reduce economic losses, if necessary. The simulation model can also identify the optimal conditions for project feasibility and develop a risk-control model for apartment development projects