Abstracts – Browse Results
Click on the titles below to expand the information about each abstract.
Viewing 21 results ...
Abdollahipour, S (2013) Multi-parameter bidding in highway construction and rehabilitation projects, Unpublished PhD Thesis, , Oklahoma State University.
- Type: Thesis
- Keywords: competition; competitiveness; contracting methods; construction project; highway; pavement; bidding; capital investment; collaboration; cost analysis; investment; project delivery; rehabilitation; data mining
- ISBN/ISSN:
- URL: https://www.proquest.com/docview/1427860239
- Abstract:
According to the 2013 ASCE infrastructure report card, roads have been given a grade of D. In addition, the level of federal, state, and local capital investment is insufficient and projected to result in a farther decline in conditions and performance in the long term. Poor highway conditions have caused transportation agencies to shift their focus from expanding road networks to rehabilitation of their existing infrastructures. In response to increasing road user costs caused by rehabilitation or reconstruction projects and limited resources due to insufficient capital investments, State Highway Agencies (SHAs) have started to utilize innovative contracting methods by incorporating construction time and life-cycle cost into the bidding process. In multi-parameter bidding method, a combination of price, construction time, and life-cycle cost is considered the decisive factor in awarding a contract to the successful bidder. The purpose of these bidding methods is to obtain accelerated construction at the lowest possible cost in order to minimize inconvenience to the public. However, unlike conventional bidding, SHAs are required to determine the Unit Time Value (incentive/disincentive rate) and life-cycle cost parameters before the bid process. This study focuses on the impact of different Unit Time Values on the competitiveness of contractors in the A+B bidding process. A new criterion is introduced to assist SHAs to determine an optimal Unit Time Value to maximize the competition during the bid process. To assist SHAs in determining the value of the life-cycle cost factor, an association analysis method in data mining is applied to historical pavement treatment datasets in order to identify the sequential patterns of various maintenance and rehabilitation activities. Since the newly developed life-cycle cost analysis models are based on the actual treatment strategies, it is expected that the life-cycle cost factor determined by this model is more realistic and closer to actual costs than that of the traditional approach suggested by the Federal Highway Administration. The results of this research will facilitate collaboration among different parties in highway construction contracts. It will advance Integrated Project Delivery (IPD) methods which are a collaborative alliance between SHAs and contractors.
Alroomi, A S (2013) Integrative framework for sustainable development of the cost estimating profession, Unpublished PhD Thesis, , Oklahoma State University.
Brown, B H J (1974) An econometric forecasting model for a segment of the construction market, Unpublished PhD Thesis, , Oklahoma State University.
Duffy, G A (2009) Linear scheduling of pipeline construction projects with varying production rates, Unpublished PhD Thesis, , Oklahoma State University.
Eldin, N N (1987) Methodology for project management control in the construction industry, Unpublished PhD Thesis, , Oklahoma State University.
Ghulman, B A (2000) Predicting construction cost growth in ODOT's paving projects using information available at the bidding time, Unpublished PhD Thesis, , Oklahoma State University.
Hajji, A M (2013) Development of a productivity-based economic, energy, environmental model for heavy duty diesel construction equipment, Unpublished PhD Thesis, , Oklahoma State University.
Johnson, L R (1969) A competitive strategy model for highway construction proposals, Unpublished PhD Thesis, , Oklahoma State University.
Karimi, B (2018) Evaluation of emissions reduction strategies for heavy duty diesel construction equipment, Unpublished PhD Thesis, , Oklahoma State University.
Kim, J (2022) A multimodal approach to improve fire safety on construction sites, Unpublished PhD Thesis, , Oklahoma State University.
King-Lewis, A (2020) Diversity and inclusion of women in the construction industry, Unpublished PhD Thesis, , Oklahoma State University.
Lee, B-H (2011) Forecasting wheat yield and quality conditional on weather information and estimating construction costs of agricultural facilities, Unpublished PhD Thesis, , Oklahoma State University.
Lusby, A K (2003) The effect of increased public investment in transportation infrastructure on oklahoma's economic development, Unpublished PhD Thesis, , Oklahoma State University.
Miller, R H (1973) Life cycle system model for estimating construction equipment ownership costs, Unpublished PhD Thesis, , Oklahoma State University.
Rainer, R K (1968) Predicting productivity of one or two elevators for construction of high-rise buildings, Unpublished PhD Thesis, , Oklahoma State University.
Shararah, H H (1981) Evaluation of wall construction techniques based upon economical factors influencing labor and materials, Unpublished PhD Thesis, , Oklahoma State University.
Spencer, G R (1987) Integration of cost estimating with critical path scheduling, Unpublished PhD Thesis, , Oklahoma State University.
Syachrani, S (2010) Advanced sewer asset management using dynamic deterioration models, Unpublished PhD Thesis, , Oklahoma State University.
Tamimi, M F (2022) Reliability and sensitivity analysis of civil and marine structures using machine-learning-assisted simulation, Unpublished PhD Thesis, , Oklahoma State University.
Trost, S M (1998) A quantitative model for predicting the accuracy of early cost estimates for construction projects in the process industry, Unpublished PhD Thesis, , Oklahoma State University.
Zeitoun, A A (1992) Evaluation of cost and schedule growth trends during construction, Unpublished PhD Thesis, , Oklahoma State University.