Abstracts – Browse Results
Click on the titles below to expand the information about each abstract.
Viewing 9 results ...
Fathi, M (2020) Public-private partnership contract framework development and project performance analysis compared to design-build in the US highway projects, Unpublished PhD Thesis, , University of Nevada, Las Vegas.
Maharjan, R (2017) Effects of contract procurement factors on performance of transportation projects, Unpublished PhD Thesis, , University of Nevada, Las Vegas.
Motaharikarein, S (2019) Development of natural perlite based concrete for sustainable construction, Unpublished PhD Thesis, , University of Nevada, Las Vegas.
Nikkhah Manesh, S (2020) Temporal and spatial analysis of the wage gap for women and underrepresented minorities in the architecture, engineering, and construction (AEC) workforce, Unpublished PhD Thesis, , University of Nevada, Las Vegas.
Sakhakarmi, S (2022) Automated approach for the enhancement of scaffolding structure monitoring with strain sensor data, Unpublished PhD Thesis, , University of Nevada, Las Vegas.
Shrestha, B K (2021) Relationship between standardization critical success factors (CSFs) and project performance, Unpublished PhD Thesis, , University of Nevada, Las Vegas.
Shrestha, K (2016) Framework of performance-based contracting for chip seal and striping maintenance activities, Unpublished PhD Thesis, , University of Nevada, Las Vegas.
Shrestha, K K (2016) Causes of change orders and its impact on road maintenance contracts, Unpublished PhD Thesis, , University of Nevada, Las Vegas.
- Type: Thesis
- Keywords: failure; optimization; contingency; specifications; artificial neural network; maintenance contract; neural network; quantification
- ISBN/ISSN:
- URL: https://www.proquest.com/docview/1830472270
- Abstract:
Change orders (CO) commonly generate cost-growth, schedule-growth or both, in construction as well as in maintenance contracts. Literature reviews revealed that the causes and impact of CO on new construction contracts had been comprehensively studied, but the causes and impact of CO in maintenance contracts remained neglected. This study collected CO data on road maintenance contracts to determine the amount of CO and the most frequent and high-risk road maintenance activities that had CO. A Delphi study was conducted with 33 maintenance engineers from the state Department of Transportations (DOTs) to identify causes of CO and its impact on cost and schedule of road maintenance contracts. The results showed that the three important reasons of CO on the maintenance contracts were: changes in work scope, errors in the estimate, and failure to verify work site conditions before signing a contract. To reduce these CO, three most important preventive measures agreed by participants were: reviewing specifications, preparing accurate estimates, and reviewing the design drawing before bid solicitation. In this study, the CO contingency estimation tool was prepared using an artificial neural network (ANN) and a linear regression method. Historical CO data was used to predict the contingency cost for maintenance contracts. In order to reduce the negative impact on the schedule-growth, a schedule-crashing optimization tool was also developed. Hence, the primary contributions of this research to the body of knowledge are the quantification of the CO, the identification of the causes and preventive measures of CO, and the development of the tools to manage cost and schedule growth in road maintenance contracts.
Tafazzoli, M (2017) Dynamic risk analysis of construction delays using fuzzy-failure mode effects analysis, Unpublished PhD Thesis, , University of Nevada, Las Vegas.