Matching Items (3)
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- All Subjects: Analysis of variance
- All Subjects: Health facilities
- Creators: Lines, Brian
- Creators: Borror, Connie
Description
Owner organizations in the architecture, engineering, and construction (AEC) industry are presented with a wide variety of project delivery approaches. Implementation of these approaches, while enticing due to their potential to save money, reduce schedule delays, or improve quality, is extremely difficult to accomplish and requires a concerted change management effort. Research in the field of organizational behavior cautions that perhaps more than half of all organizational change efforts fail to accomplish their intended objectives. This study utilizes an action research approach to analyze change message delivery within owner organizations, model owner project team readiness and adoption of change, and identify the most frequently encountered types of resistance from lead project members. The analysis methodology included Spearman's rank order correlation, variable selection testing via three methods of hierarchical linear regression, relative weight analysis, and one-way ANOVA. Key findings from this study include recommendations for communicating the change message within owner organizations, empirical validation of critical predictors for change readiness and change adoption among project teams, and identification of the most frequently encountered resistive behaviors within change implementation in the AEC industry. A key contribution of this research is the recommendation of change management strategies for use by change practitioners.
ContributorsLines, Brian (Author) / Sullivan, Kenneth (Thesis advisor) / Wiezel, Avi (Committee member) / Badger, William (Committee member) / Arizona State University (Publisher)
Created2014
Description
The purpose of this paper is to present a case study on the application of the Lean Six Sigma (LSS) quality improvement methodology and tools to study the analysis and improvement of facilities management (FM) services at a healthcare organization. Research literature was reviewed concerning whether or not LSS has been applied in healthcare-based FM, but no such studies have been published. This paper aims to address the lack of an applicable methodology for LSS intervention within the context of healthcare-based FM. The Define, Measure, Analyze, Improve, and Control (DMAIC) framework was followed to test the hypothesis that LSS can improve the service provided by an FM department responsible for the maintenance and repair of furniture and finishes at a large healthcare organization in the southwest United States of America. Quality improvement curricula and resources offered by the case study organization equipped the FM department to apply LSS over the course of a five-month period. Qualitative data were gathered from pre- and post-intervention surveys while quantitative data were gathered with the Organization’s computerized maintenance management system (CMMS) software. Overall, LSS application proved to be useful for the intended purpose. The author proposes that application of LSS by other FM departments to improve their services could also be successful, which is noteworthy and deserving of continued research.
ContributorsShirey, William T (Author) / Sullivan, Kenneth (Thesis advisor) / Smithwick, Jake (Committee member) / Lines, Brian (Committee member) / Arizona State University (Publisher)
Created2017
Description
The Partition of Variance (POV) method is a simplistic way to identify large sources of variation in manufacturing systems. This method identifies the variance by estimating the variance of the means (between variance) and the means of the variance (within variance). The project shows that the method correctly identifies the variance source when compared to the ANOVA method. Although the variance estimators deteriorate when varying degrees of non-normality is introduced through simulation; however, the POV method is shown to be a more stable measure of variance in the aggregate. The POV method also provides non-negative, stable estimates for interaction when compared to the ANOVA method. The POV method is shown to be more stable, particularly in low sample size situations. Based on these findings, it is suggested that the POV is not a replacement for more complex analysis methods, but rather, a supplement to them. POV is ideal for preliminary analysis due to the ease of implementation, the simplicity of interpretation, and the lack of dependency on statistical analysis packages or statistical knowledge.
ContributorsLittle, David John (Author) / Borror, Connie (Thesis advisor) / Montgomery, Douglas C. (Committee member) / Broatch, Jennifer (Committee member) / Arizona State University (Publisher)
Created2015