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Development of a Cost Prediction Mod...

Nankar, Bhushan Rajendra.

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Development of a Cost Prediction Model for Mass Timber Gravity Frame Construction.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Development of a Cost Prediction Model for Mass Timber Gravity Frame Construction./
Author:	Nankar, Bhushan Rajendra.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	156 p.
Notes:	Source: Masters Abstracts International, Volume: 81-11.
Contained By:	Masters Abstracts International81-11.
Subject:	Architectural engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27959224
ISBN:	9798643180685

Development of a Cost Prediction Model for Mass Timber Gravity Frame Construction.
Nankar, Bhushan Rajendra.

Development of a Cost Prediction Model for Mass Timber Gravity Frame Construction. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 156 p.

Source: Masters Abstracts International, Volume: 81-11.

Thesis (M.S.)--Michigan State University, 2020.

This item must not be sold to any third party vendors.

Construction materials like concrete and steel have been a primary choice for designers. As a result, the construction industry has become one of the biggest sources of greenhouse gas emissions. With increasing global population and climate change, resource scarcity and a need for healthy habitat is a likelihood. Therefore, to address these issues, green building movement escalated, and mass timber was looked upon as an alternative to offer a family of engineered wood products with comparable strength characteristics and desirable environmental benefits. Despite its benefits, designers are hesitant to adopt mass timber as a reliable alternative due to their lack of familiarity with the material which leads to uncertainty about costs and acts a barrier for adoption. This study attempts to break this link by investigating the cost implications of using mass timber gravity frame through the development of a cost prediction tool. This tool is envisioned to deliver costs to refer to compare mass timber as an alternative, thereby helping designers to make informed decisions for construction material at a conceptual stage of a project. This study initially developed regression equations using Principal Component Regression (PCR) and improvised to Partial Least Squares Regression (PLSR) to understand cost implications of selected variables and to develop a prediction tool to address the cost barrier. The researcher also believes that greater adoption will ultimately lead to sustainable forest management, reduced wildfires, and an economic base for rural regions.

ISBN: 9798643180685Subjects--Topical Terms:

3174102
Architectural engineering.
Subjects--Index Terms:

Cost prediction tool

Development of a Cost Prediction Model for Mass Timber Gravity Frame Construction.
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300 $a 156 p.
500 $a Source: Masters Abstracts International, Volume: 81-11.
500 $a Advisor: Berghorn, Dr George.
502 $a Thesis (M.S.)--Michigan State University, 2020.
506 $a This item must not be sold to any third party vendors.
520 $a Construction materials like concrete and steel have been a primary choice for designers. As a result, the construction industry has become one of the biggest sources of greenhouse gas emissions. With increasing global population and climate change, resource scarcity and a need for healthy habitat is a likelihood. Therefore, to address these issues, green building movement escalated, and mass timber was looked upon as an alternative to offer a family of engineered wood products with comparable strength characteristics and desirable environmental benefits. Despite its benefits, designers are hesitant to adopt mass timber as a reliable alternative due to their lack of familiarity with the material which leads to uncertainty about costs and acts a barrier for adoption. This study attempts to break this link by investigating the cost implications of using mass timber gravity frame through the development of a cost prediction tool. This tool is envisioned to deliver costs to refer to compare mass timber as an alternative, thereby helping designers to make informed decisions for construction material at a conceptual stage of a project. This study initially developed regression equations using Principal Component Regression (PCR) and improvised to Partial Least Squares Regression (PLSR) to understand cost implications of selected variables and to develop a prediction tool to address the cost barrier. The researcher also believes that greater adoption will ultimately lead to sustainable forest management, reduced wildfires, and an economic base for rural regions.
590 $a School code: 0128.
650 4 $a Architectural engineering. $3 3174102
650 4 $a Sustainability. $3 1029978
650 4 $a Civil engineering. $3 860360
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653 $a Cross-laminated timber
653 $a Glulam
653 $a Mass timber construction
653 $a Regression analysis
653 $a Sustainability
690 $a 0462
690 $a 0640
690 $a 0543
710 2 $a Michigan State University. $b Construction Management - Master of Science. $3 2095061
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