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- All Subjects: construction
- Creators: Stone, Brian
Description
Within the vast area of study in Organizational Change lays the industrial application of Change Management, which includes the understanding of both resisters and facilitators to organizational change. This dissertation presents an approach of gauging levels of change as it relates to both external and internal organization factors. The arena of such a test is given through the introduction of the same initiative change model, which attempts to improve transparency and accountability, across six different organizations where the varying results of change are measured. The change model itself consists of an interdisciplinary approach which emphasizes education of advanced organizational measurement techniques as fundamental drivers of converging change. The observations are documented in the real-time observed cased studies of six organizations as they progressed through the change process. This research also introduces a scaled metric for determining preliminary levels of change and endeavors to test both internal and external, or environmental, factors of change. A key contribution to the work is the analysis between both observed and surveyed data where a grounded theory analysis is used to help answer the question of what are factors of change in organizations. This work is considered to be foundational in real-time observational studies but has a promise for future additional contributions which would further elaborate on the phenomenon of prescribed organizational change.
ContributorsStone, Brian (Author) / Sullivan, Kenneth T. (Thesis advisor) / Verdini, William (Committee member) / Badger, William (Committee member) / Arizona State University (Publisher)
Created2012
Description
Modern computer systems are complex engineered systems involving a large collection of individual parts, each with many parameters, or factors, affecting system performance. One way to understand these complex systems and their performance is through experimentation. However, most modern computer systems involve such a large number of factors that thorough experimentation on all of them is impossible. An initial screening step is thus necessary to determine which factors are relevant to the system's performance and which factors can be eliminated from experimentation.
Factors may impact system performance in different ways. A factor at a specific level may significantly affect performance as a main effect, or in combination with other main effects as an interaction. For screening, it is necessary both to identify the presence of these effects and to locate the factors responsible for them. A locating array is a relatively new experimental design that causes every main effect and interaction to occur and distinguishes all sets of d main effects and interactions from each other in the tests where they occur. This design is therefore helpful in screening complex systems.
The process of screening using locating arrays involves multiple steps. First, a locating array is constructed for all possibly significant factors. Next, the system is executed for all tests indicated by the locating array and a response is observed. Finally, the response is analyzed to identify the significant system factors for future experimentation. However, simply constructing a reasonably sized locating array for a large system is no easy task and analyzing the response of the tests presents additional difficulties due to the large number of possible predictors and the inherent imbalance in the experimental design itself. Further complications can arise from noise in the system or errors in testing.
This thesis has three contributions. First, it provides an algorithm to construct locating arrays using the Lovász Local Lemma with Moser-Tardos resampling. Second, it gives an algorithm to analyze the system response efficiently. Finally, it studies the robustness of the analysis to the heavy-hitters assumption underlying the approach as well as to varying amounts of system noise.
Factors may impact system performance in different ways. A factor at a specific level may significantly affect performance as a main effect, or in combination with other main effects as an interaction. For screening, it is necessary both to identify the presence of these effects and to locate the factors responsible for them. A locating array is a relatively new experimental design that causes every main effect and interaction to occur and distinguishes all sets of d main effects and interactions from each other in the tests where they occur. This design is therefore helpful in screening complex systems.
The process of screening using locating arrays involves multiple steps. First, a locating array is constructed for all possibly significant factors. Next, the system is executed for all tests indicated by the locating array and a response is observed. Finally, the response is analyzed to identify the significant system factors for future experimentation. However, simply constructing a reasonably sized locating array for a large system is no easy task and analyzing the response of the tests presents additional difficulties due to the large number of possible predictors and the inherent imbalance in the experimental design itself. Further complications can arise from noise in the system or errors in testing.
This thesis has three contributions. First, it provides an algorithm to construct locating arrays using the Lovász Local Lemma with Moser-Tardos resampling. Second, it gives an algorithm to analyze the system response efficiently. Finally, it studies the robustness of the analysis to the heavy-hitters assumption underlying the approach as well as to varying amounts of system noise.
ContributorsSeidel, Stephen (Author) / Syrotiuk, Violet R. (Thesis advisor) / Colbourn, Charles J (Committee member) / Montgomery, Douglas C. (Committee member) / Arizona State University (Publisher)
Created2018
Description
This thesis draws on industry experience and academic literature to highlight several problems facing the construction and facility management industries. These problems include issues with product delivery performance and financial failures that often lead firms to spend much more than anticipated, while obtaining much less of a product. Transaction-cost economics theory and literature are presented as a model for understanding, predicting, and preventing these problems. Transaction-cost economics suggests that specificity and uncertainty, two key characteristics of industry transactions, are improperly aligned with governance structures, leading to preventable failures. This thesis highlights several case studies in which these failures occur and argues that the correct application of this theory can mitigate many of these problems. A final case study illustrates how this alignment can make a difference in outcome without a compromise of quality.
ContributorsRice, Michael L., M.S (Author) / Sullivan, Kenneth (Thesis advisor) / Stone, Brian (Committee member) / Smithwick, Jake (Committee member) / Arizona State University (Publisher)
Created2019
Description
The intent of this study was to identify the most viable among a proposive sample of emerging sustainable construction technologies with respect to the Twin Cities Metropolitan Geographic Area. With space heating and space cooling accounting for such a significant portion of energy consumption in Twin Cities homes, a representative sample of homes was analyzed for annual heating and cooling loads. For each home a series of heating, ventilation, air conditioning (HVAC) and envelope equipment was modeled in order to provide data for various sustainable home construction technologies. The result was a specific amount of energy savings from baseline construction methods for each sustainable technology. The study found that integrated geothermal heat pump and radiant conditioning systems have a far greater impact on energy savings than the construction methods evaluated. Nevertheless, insulated concrete forms provided the greatest energy savings within the proposive set of construction methods. The greatest amount of space conditioning energy savings of all configurations tested was 73.48% using an integrated geothermal heat pump and radiant conditioning system, structural insulated panel wall construction, aerosol air infiltration prevention, and insulated concrete form basement construction. The results of the study were used to determine areas for further research and to provide awareness within the Twin Cities construction enterprise to determine the most viable technologies that contractors, municipalities, and citizens should prioritize moving forward.
ContributorsMcKilligan, Ryan (Author) / Sullivan, Kenneth (Thesis advisor) / Stone, Brian (Committee member) / Smithwick, Jake (Committee member) / Arizona State University (Publisher)
Created2019
Description
The applications of Building Information Modelling (BIM) technology extend beyond performing clash detection and avoiding installation issues among subcontractors. When properly budgeted and fully integrated into the pre-construction work-flow, BIM technology can improve the accuracy of estimates and reduce material as well as labor costs. The purpose of this paper is to analyze BIM-related budgeting practices and explore options for optimizing BIM budgeting strategy as well as integrating BIM technology into an estimating strategy. The methodology chosen was a case study. A study of an electrical contractor was conducted using BIM budgeting data based on actual and estimated figures for 245 jobs completed in the years 2015-2019. A review of literature was conducted for the purpose of researching current options with regard to the implementation of BIM as part of estimation, its associated financial cost, and the challenges faced in adapting existing frameworks to meet new demands. It was observed that the current resources allocated for BIM are under-utilized on an aggregate basis. It was also observed that the budget for these resources is sometimes exceeded for larger projects and frequently, grossly under-utilized for smaller projects. There is a strong correlation between contract value and project type, suggesting that contract value is a primary predictor of BIM requirements. The review of literature suggests what employee skills are most necessary for integrating BIM with estimating: the ability to perform accurate takeoffs from BIM models, evaluate the cost of materials that are typically not modeled or appear poorly in the model, the ability to work with a variety of BIM software, the ability to know if a model is accurate, and an understanding of how the model interacts with other aspects of the construction process. It also discusses the challenges faced when adopting BIM in estimation. This paper contributes to the field of construction management by expanding the body of research for the BIM budgeting strategy in electrical contracting; an area of research which is not well developed. The data analyzed from this single electrical contractor provides the basis for an exploratory case study that contributes to the development of a conceptual framework for accurate BIM budgeting, where no such framework had previously existed.
ContributorsBalmer, Steven Thomas (Author) / Sullivan, Kenneth (Thesis advisor) / Smithwick, Jake (Committee member) / Stone, Brian (Committee member) / Arizona State University (Publisher)
Created2020