Title:
Benchmarking building energy in the multifamily industry: A data envelopment analysis (DEA) model

dc.contributor.advisor Ashuri, Baabak
dc.contributor.author Wang, Jun
dc.contributor.committeeMember Tien, Iris
dc.contributor.committeeMember Song, Xinyi
dc.contributor.committeeMember Marks, Eric
dc.contributor.committeeMember Shahandashti, Mohsen
dc.contributor.department Civil and Environmental Engineering
dc.date.accessioned 2017-06-07T17:38:33Z
dc.date.available 2017-06-07T17:38:33Z
dc.date.created 2017-05
dc.date.issued 2017-03-28
dc.date.submitted May 2017
dc.date.updated 2017-06-07T17:38:33Z
dc.description.abstract A new data envelopment analysis (DEA) based approach for benchmarking energy efficiency in buildings in the multifamily sector was proposed in this dissertation. It addressed major limitations of existing DEA model. It provides a method that remediates missing or incorrect values for instances in the dataset, establishes a mechanism that accurately and effectively detects outliers in the dataset, selects appropriate variables to be included in the DEA model and provides justifications for the selection, creates a DEA model that differently handles controllable and non-controllable variables, and quantitatively measures the stability of efficiency scores of each decision making units across the entire period. Data was provided by a third utility management and energy service company in the multifamily housing industry. Research deliverables are expected to provide decision makers and facility managers with the crucial information for building energy improvement. The limitations of future work are also discussed at the end of this dissertation.
dc.description.degree Ph.D.
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/58200
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject Building energy benchmarking
dc.subject Data envelopment analysis
dc.title Benchmarking building energy in the multifamily industry: A data envelopment analysis (DEA) model
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Ashuri, Baabak
local.contributor.corporatename School of Civil and Environmental Engineering
local.contributor.corporatename College of Engineering
relation.isAdvisorOfPublication 61494ab3-3f45-44e8-abe2-b57df371eada
relation.isOrgUnitOfPublication 88639fad-d3ae-4867-9e7a-7c9e6d2ecc7c
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level Doctoral
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