Analyzing User Costs In a Hospital: Methodological Implication of Space Syntax to Support Whole-life Target Value Design
2010
Download PDFDOI: https://doi.org/10.60164/a7g7i1d4c
Authors: Youngchul Kim, Hyun Woo Lee
Citation:
Kim, H., Lee, Kim, Y., & Lee, H. (2010). Analyzing User Costs in a Hospital: Methodological Implication of Space Syntax to Support Whole-life Target Value Design Lean Construction. Lean Construction Journal 2010 pp 55-65.
Abstract:
Research Hypothesis:
H1: Space Syntax analysis can be used to simulate a user’s experience and movement for investigating design alternatives in the design of healthcare facilities.
H2: Space Syntax can efficiently be used to support Whole-life Target Value Design (TVD).
Purpose: This paper investigates a methodological implication of Space Syntax to Whole- life TVD in the design of healthcare facilities.
Research Design/Method: Three hypothetical hospital ward design alternatives are selected – shallow-plan, deep-plan, and courtyard-plan type – to analyze user costs in hospital design to determine which alternative is the most cost-efficient. These three hypothetical design alternatives are evaluated using a Space Syntax program, and then the findings are interpreted to determine user costs.
Findings: The study finds that the deep-plan type has four “low” scores, the shallow-plan type has three “high” and one “medium” score, and the courtyard type has two “high” scores and two “medium” scores. Thus, the deep-plan type is determined to be the lowest user cost type, and the shallow-plan type is expected to have the highest user costs.
Limitations: User costs are discussed in qualitative basis such as high, medium, or low with proportion to the simulation due to the lack of empirical evidence in financial value.
Implications: Space Syntax assures valid results of spatial analysis in relation to users’ movement within the built environment.
Value for practitioners: Space Syntax allows designers to visually compare design alternatives relating to space planning during set-based design using spatial analysisapplications.