Matching Items (3)
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- All Subjects: Project Performance
- Creators: Sullivan, Kenneth T.
- Creators: AL Saber, Salem Samer
Description
Commodity contracts are often awarded on the basis of price. A price-based methodology for making such awards fails to consider the suppliers' ability to minimize the risk of non-performance in terms of cost, schedule, or customer satisfaction. Literature suggests that nearly all risk in the delivery of commodities is in the interfacing of nodes within a supply chain. Therefore, commodity suppliers should be selected on the basis of their past performance, ability to identify and minimize risk, and capacity to preplan the delivery of services. Organizations that select commodity suppliers primarily on the basis of price may experience customer dissatisfaction, delayed services, low product quality, or some combination thereof. One area that is often considered a "commodity" is the delivery of furniture services. Arizona State University, on behalf of the Arizona Tri-University Furniture Consortium, approached the researcher and identified concerns with their current furnishing services contract. These concerns included misaligned customer expectations, minimal furniture supplier upfront involvement on large capital construction projects, and manufacturer design expertise was not being utilized during project preplanning. The Universities implemented a best value selection process and risk management structure. The system has resulted in a 9.3 / 10 customer satisfaction rating (24 percent increase over the previous system), for over 1,100 furniture projects totaling $19.3M.
ContributorsSmithwick, Jake (Author) / Sullivan, Kenneth T. (Thesis advisor) / Kashiwagi, Dean T. (Committee member) / Badger, William W. (Committee member) / Arizona State University (Publisher)
Created2012
Description
The construction industry is the backbone of any country’s economy. It is a primary source of foreign investments, creates new jobs, and maintains the economy flowing in various trades. Accurate cost estimation is a critical aspect for the construction industry, directly impacting project success and profitability. This master's thesis focuses on comprehensively identifying the key factors that influence cost estimation and provides valuable recommendations for constructing an optimized Artificial Neural Network (ANN) model. Through an extensive research methodology encompassing literature review, surveys, and interviews with industry professionals, this study uncovers significant factors that exert a substantial impact on cost estimation practices. The findings emphasize the importance of seamlessly integrating project delivery systems, meticulously considering project duration, and incorporating diverse perspectives from global regions. By incorporating these insights, stakeholders can make informed decisions, enhance project planning, and elevate overall project performance. This study successfully bridges the gap between theory and practice, presenting invaluable insights for stakeholders within the construction industry. Keywords: cost estimation, construction industry, Artificial Neural Network, factors, project delivery systems, project duration, global perspectives, informed decision-making, project planning, project performance
ContributorsAL Saber, Salem Samer (Author) / Sullivan, Kenneth (Thesis advisor) / Hurtado, Kristian (Committee member) / Standage, Richard (Committee member) / Arizona State University (Publisher)
Created2023
Description
The current paradigm to addressing the marginal increases in productivity and quality in the construction industry is to embrace new technologies and new programs designed to increase productivity. While both pursuits are justifiable and worthwhile they overlook a crucial element, the human element. If the individuals and teams operating the new technologies or executing the new programs lack all of the necessary skills the efforts are still doomed for, at best, mediocrity. But over the past two decades researchers and practitioners have been exploring and experimenting with a softer set of skills that are producing hard figures showing real improvements in performance.
ContributorsMischung, Joshua (Author) / Sullivan, Kenneth T. (Thesis advisor) / El Asmar, Mounir (Committee member) / Wiezel, Avi (Committee member) / Arizona State University (Publisher)
Created2014