Abstract
PurposeThis study aims to formulate a user-friendly pre-design model that could be a decision support tool for green wall systems to assist designers in selecting an optimal green wall system aligned with specified performance criteria while concurrently addressing project requirements linked to social and economic parameters. This approach seeks to enhance overall project satisfaction for the designer and the owner.Design/methodology/approachA correlation between the green wall context and design requirements and its performance on the buildings have been defined by considering its social and economic parameters, which represented the owner preferences to ensure the most satisfaction from installation as it achieves the required performance that is defined by the designer such as maximizing thermal insulation, improving indoor air quality, reducing the needed heating and cooling loads, etc. and also to achieve the satisfaction in social and economic requirements defined by the owner such as system installation cost, system maintenance cost, adding beauty value, etc.FindingsThe research developed an easy pre-design model to be a tool for green wall system decision-making for the most suitable system, which contains three main steps: the first one is defining the required performance of the green wall (designer requirements), the second step is limiting the context of the project which is made by designer and the owner requirements and finally the third step is choosing the system components that ensures achieving the requirements of both owners and designer, related to the building and climate context.Originality/valueThe added value lies in developing a green wall decision-making tool, essentially a pre-design model. This model considers the correlation between the project’s context, encompassing climate and building conditions. It provides a structured approach for decision-making in the early stages of green wall design. It offers valuable insights into the optimal choices related to system type, installation methods and plant characteristics. This enhanced decision-making tool contributes to more informed and efficient design processes, considering each project’s specific needs and conditions.