Multi-Criteria Decision Support System for Green Commercial Space Design

Abstract

Commercial space features essential characteristics of attracting clients and creating profits; thus, the exterior and interior designs of conventional commercial space were often made to look grandiose and overdecorated. Over time, according to commercial attributes, operator preferences, and style of the designer, commercial spaces have constantly undergone renovation into varied styles. However, the physical renovation processhas caused multiple and composite types of environmental pollution, such as waste and noise pollution caused by breaking of walls or partitions, anddecorative paint pollution, as well as the use of high-energy-consuming lighting equipment, air-conditioning systems, and decorative materials. Global pollution has caused climate change, endangering living organismsand human life. Furthermore, no effective method exists to control the problem of high greenhouse gas emissions. Therefore, this study used energy-saving design concerns of a garden-type commercial space to propose an energy-saving evaluation model. The study combined three methodologies, the Delphi method, analytic hierarchy process, and fuzzy logic theory, to construct a multi-criteria decision support system for designing green commercial spaces, and used the green spatial design of a garden café as an example to illustrate the high objectivity and adaptability of the proposed model in practical application. The study also used an international award-winning case to validate that the proposed model had practical value as a reference to support key design decisions.