Human-centred and BIM-integrated automated value analysis of buildings

Abstract

This paper presents a study on automated value analysis of buildings for supporting value-adding and human-centred decision making in building planning and design. The analysis was conducted using a proposed system for automatically analyzing the value of a building based on its properties and multidimensional stakeholder values. The system is integrated with building information modelling (BIM) and is composed of three modules: a stakeholder input capturing module, a building information extraction module, and a value analysis module. The value analysis relies on valuation models that are theoretically grounded in axiology (value theory) and integration theory. A set of experiments were conducted, using the proposed system, to analyze the impacts of alternative planning and design decisions on the value of buildings to the stakeholders. The results indicate that it is important that decision makers not only enhance a design’s ability in fulfilling individual stakeholder values, but also account for the stakeholders’ systems of value priorities and seek to create a high level of synergy between the value that the design fulfils and the personal value systems of the stakeholders. The research contributes to the body of knowledge by integrating the human element of value – the human values – into value analysis. It could promote improved information for making more value-adding and human-centred decisions, and it could provide a foundation for planning and designing buildings in a way that is synergistically aligned with human values. Since the current study is limited in scope, in the future, the authors will expand the analysis by studying different types and scales of buildings and considering additional stakeholder values.

Keywords:

• Automation
• building information modelling
• human values
• value analysis

Acknowledgements

The authors would like to thank the National Science Foundation (NSF). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of NSF.

Disclosure statement

No potential conflict of interest was reported by the authors.

Human participants statement

An exemption was obtained from the Institutional Review Board (IRB) of the University of Illinois at Urbana-Champaign. The IRB Protocol Number is 13327. All the participants in this study have provided informed consent prior to their participation.

Additional information

Funding

This paper is based upon work supported by NSF under Grant No.1254679.