To maintain thermal performance of the Ondol system, elements of the system must be optimally designed so that the thermal performance and hot water flow can be efficiently transmitted from the Ondol system in apartment units. The purpose of this study is to propose the optimal design data and applicable design process of the Ondol system. The design process should incorporate the energy-efficient system as well as a comfortable indoor thermal environment in the early design stage.

This study aims to evaluate the heat transfer characteristics and energy consumption in the wet and dry ondol systems. Conditions of the continued heating mode set the room temperature at 20℃ and hot water supply temperature at 60℃ and 70℃ for 3 days. The scheduled heating mode operates heating at 6～9am (room temperature at 20℃), suspends heating at 9～18pm (leaving mode), and runs heating at 1 8～24am (room temperature at 20℃) and 24～6am (room temperature at 17℃) for 2 days. The results from the continued heating mode in the dry/wet ondol systems confirmed that the dry and wet systems had the same average indoor temperature (18.9℃) and similar energy consumption. In addition, the results from the scheduled heating mode in the dry/wet ondol systems confirmed that the dry ondol system had lower energy consumption than the wet ondol system. Therefore, the scheduled heating mode in the dry ondol system is expected to reduce energy consumption.

Purpose: In Korea, win-win growth policy has been successfully implemented in supply chain and logistics management. In the policy, it is recommended to support supply chain partners with various mechanisms including financial and technical aids. This study attempts to scientifically analyze the effects of direct and indirect win-win growth policy factors on supply chain and logistics management performance through partnership factors. Research design, data and methodology: This study builds a structural equation model reflecting the relationship between the win-win growth policy, partnership and performance factors. The proposed model is verified with the PLS (Partial Least Squares regression) methodology. Data from shipper and logistics companies were collected and analyzed by the PLS model. Results: The analysis showed that both direct and indirect policy factors are meaningful to improve supply chain and logistics performance. Indirect support factors including R&D, management innovation, human resources development and educational supports have positive impacts on partnership factors. Direct support factors including financial aids and fairness also have positive impacts on the performance. Conclusions: This study is meaningful in that it suggests a turning point in which supply chain Win-win growth and partnership efforts are perceived as new value-creating mechanism rather than unilateral cost reduction for logistics industry.