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- Member of: ASU Electronic Theses and Dissertations
- Status: Published
Description
Using experience, observations, data, current research, and writings in the field of volunteer management, it was determined there was a need to study the effects of leadership/management practices on the productivity outcomes of a volunteer construction workforce. A simple wood bench that would be tiled and painted was designed to test the areas of Time, Waste, Quality, Safety, and Satisfaction of different volunteer groups. The challenge was bolstered by giving the teams no power tools and limited available resources. A simple design of experiment model was used to test highs and lows in the three management techniques of Instruction, Help, and Encouragement. Each scenario was tested multiple times. Data was collected, normalized and analyzed using statistical analysis software. A few significant findings were discovered. The first; the research showed that there was no significant correlation between the management practices of the leader and the satisfaction of the volunteers. The second; the research also showed when further analyzed into specific realistic scenarios that the organizations would be better to focus on high amounts of Help and Encouragement in order to maximize the productivity of their volunteer construction workforce. This is significant as it allows NPO's and governments to focus their attention where best suited to produce results. The results were shared and the study was further validated as "significant" by conducting interviews with experts in the construction nonprofit sector.
ContributorsPrigge, Diedrich (Author) / Sullivan, Kenneth (Thesis advisor) / Wiezel, Avi (Committee member) / Badger, William (Committee member) / Arizona State University (Publisher)
Created2013
Description
The construction industry is performing poorly regarding project management and service delivery. On average, global projects are over-budget, delayed, and met with unsatisfactory results according to buyers. To mitigate poor performance, the project management career path has been heavily researched and continually developed over the last century. Despite the published advances in project management approaches and tools, project performance continues to suffer. This research seeks to conduct an exploratory analysis of current project management and other approaches and determine how they affect project performance. Through a detailed literature search, the researcher identified a procurement model that is more heavily documented as high performing than all other approaches. The researcher proposed that this model may be a solution to assist project managers with the delivery of high performing services. The model is called the Best Value Approach (BVA). The BVA focuses on leadership, non-technical communication, quality assurance, and transparent project execution. To test the effectiveness of its practices, the researcher modified and adapted the BVA into a project management approach and tested it on a large-scale government project. During the case study test, the researcher observed that there were two primary project management roles in the supply chain; the buyer’s and vendor’s project managers. The case study resulted in the large government organization receiving more work and increased their satisfaction of the work received by 22 percent from the previous year. To further test the project management adapted BVA, the researcher conducted a classroom case-study in which students learned and implemented the BVA practices on real-time, small-scale industry projects. Results include cost savings of $100,000 for 10 companies over 24 projects, cost avoidance of over $4.5M, and a 9.8/10 customer satisfaction [in terms of the companies’ satisfaction with the deliverables produced on each project]. These results suggest that the BVA practices may effectively improve the performance of project delivery, and may be a viable new project management approach to train future project managers. Out of the two project manager roles, it is proposed that the buyer’s project manager may receive the most benefit. Additional research is needed on the other approaches to compare quantitative project performance, and run repeated testing on the potential new project management approach.
ContributorsRivera, Alfredo Octavio (Author) / Badger, William (Thesis advisor) / Sullivan, Kenneth (Thesis advisor) / Kashiwagi, Jacob S (Committee member) / Arizona State University (Publisher)
Created2017
Description
Construction Management research has not been successful in changing the practices of the construction industry. The method of receiving grants and the peer review paper system that academics rely on to achieve promotion, does not align to academic researchers becoming experts who can bring change to industry practices. Poor construction industry performance has been documented for the past 25 years in the international construction management field. However, after 25 years of billions of dollars of research investment, the solution remains elusive. Research has shown that very few researchers have a hypothesis, run cycles of research tests in the industry, and result in changing industry practices.
The most impactful research identified in this thesis, has led to conclusions that pre-planning is critical, hiring contractors who have expertise will result in better performance, and risk is mitigated when the supply chain partners work together and expertise is utilized at the beginning of projects.
The problems with construction non-performance have persisted. Legal contract issues have become more important. Traditional research approaches have not identified the severity and the source of construction non-performance. The problem seems to be as complex as ever. The construction industry practices and the academic research community remain in silos. This research proposes that the problem may be in the traditional construction management research structure and methodology. The research
has identified a unique non-traditional research program that has documented over 1700 industry tests, which has resulted in a decrease in client management by up to 79%, contractors adding value by up to 38%, increased customer satisfaction by up to 140%, reduced change order rates as low as -0.6%, and decreased cost of services by up to 31%.
The purpose of this thesis is to document the performance of the non-traditional research program around the above identified results. The documentation of such an effort will shed more light on what is required for a sustainable, industry impacting, and academic expert based research program.
The most impactful research identified in this thesis, has led to conclusions that pre-planning is critical, hiring contractors who have expertise will result in better performance, and risk is mitigated when the supply chain partners work together and expertise is utilized at the beginning of projects.
The problems with construction non-performance have persisted. Legal contract issues have become more important. Traditional research approaches have not identified the severity and the source of construction non-performance. The problem seems to be as complex as ever. The construction industry practices and the academic research community remain in silos. This research proposes that the problem may be in the traditional construction management research structure and methodology. The research
has identified a unique non-traditional research program that has documented over 1700 industry tests, which has resulted in a decrease in client management by up to 79%, contractors adding value by up to 38%, increased customer satisfaction by up to 140%, reduced change order rates as low as -0.6%, and decreased cost of services by up to 31%.
The purpose of this thesis is to document the performance of the non-traditional research program around the above identified results. The documentation of such an effort will shed more light on what is required for a sustainable, industry impacting, and academic expert based research program.
ContributorsRivera, Alfredo O (Author) / Kashiwagi, Dean T. (Thesis advisor) / Sullivan, Kenneth (Committee member) / Kashiwagi, Jacob S (Committee member) / Arizona State University (Publisher)
Created2014
Description
By the evolution of technologies and computing power, it is possible to capture and save large amounts of data and then find patterns in large and complex datasets using data science and machine learning. This dissertation introduces machine-learning models and econometric models to use in infrastructure transportation projects. Among transportation infrastructure projects, the airline industry and highways are selected to implement the models.The first topic of this dissertation focuses on using machine-learning models in highway projects. The International Roughness Index (IRI) for asphalt concrete pavement is predicted based on the 12,637 observations in the Long-Term Pavement Performance (LTPP) dataset for 1,390 roads and highways in the 50 states of the United States and the District of Columbia from 1989 to 2018. The results show that XGBoost provides a better model fit in terms of mean absolute error and coefficient of determination than other studied models. Also, the most important factors in predicting the IRI are identified.
The second topic of this dissertation aims to develop machine-learning models to predict customer dissatisfaction in the airline industry. The relationship between measures of service failure (flight delay and mishandled baggage) and customer dissatisfaction is predicted by using longitudinal data from 2003 to 2019 from the U.S. airline industry. Data was obtained from the Air Travel Consumer Report (ATCR) published by the U.S. Department of Transportation. Flight delay is more important in low-cost airlines, while mishandled baggage is more important in legacy airlines. Also, the effect of the train-test split ratio on each machine-learning model is examined by running each model using four train-test splits. Results indicate that the train-test split ratio could influence the selection of the best model.
The third topic in this dissertation uses econometric analysis to investigate the relationship between customer dissatisfaction and two measures of service failure in the U.S. airline industry. Results are: 1) Mishandled baggage has more impact than flight delay on customer complaints. 2) The effect of an airline’s service failures on customer complaints is contingent on the category of the airline. 3) The effect of flight delay on customer complaints is lower for low-cost airlines compared to legacy airlines.
ContributorsDamirchilo, Farshid (Author) / Fini, Elham H (Thesis advisor) / Lamanna, Anthony J (Committee member) / Parast, Mahour M (Committee member) / Sullivan, Kenneth (Committee member) / Arizona State University (Publisher)
Created2021