Hidden building performance evaluation sources: What can trip advisor and other informal user-generated data tell us?

0Citations
Citations of this article
3Readers
Mendeley users who have this article in their library.
Get full text

Abstract

There are well-known benefits to carry out Building Performance Evaluation (BPE), but also well-known barriers, including lack of support from clients which limits the ability to carry out extensive BPE exercises. Focusing on user feedback evaluation, this paper presents a methodology to expand current approaches by using data that is publically available and requires little resource to analyse: the systematic analysis of reviews from a travel or visitor website (in this case, Trip Advisor). Two case studies are presented (one hotel, one leisure centre). The first used the proposed method alongside more formal BPE methods, which helped to interrogate findings and validate the method in principle. The second uses it as the main BPE method. The analysis draws out which design and operational issues are mentioned most often by users and in what way (i.e. positively or negatively). It can then investigate these issues in more detail and over time, comparing the early stages of occupation with later, more ‘settled’, stages. Both case studies indicate significant potential to generate valuable feedback on building briefing, design, delivery and operations, both in relation to specific buildings and as a way to better understand user needs and expectations and inform future projects. Formal and extensive methods are invaluable, and should not be replaced by less formal ones which have inherent limitations; however, built environment professionals risk missing valuable opportunities to learn and improve building performance by concentrating on formal methods alone, particularly in a world where user-generated content grows in quantity, availability and prominence.

Cite

CITATION STYLE

APA

Godefroy, J. (2020). Hidden building performance evaluation sources: What can trip advisor and other informal user-generated data tell us? In Smart Innovation, Systems and Technologies (Vol. 163, pp. 235–245). Springer. https://doi.org/10.1007/978-981-32-9868-2_20

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free