Matching Items (6)
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- All Subjects: Business
- Genre: Academic theses
- Creators: Wiezel, Avi
- Creators: Babenko, Ilona
- Status: Published
Description
Random Forests is a statistical learning method which has been proposed for propensity score estimation models that involve complex interactions, nonlinear relationships, or both of the covariates. In this dissertation I conducted a simulation study to examine the effects of three Random Forests model specifications in propensity score analysis. The results suggested that, depending on the nature of data, optimal specification of (1) decision rules to select the covariate and its split value in a Classification Tree, (2) the number of covariates randomly sampled for selection, and (3) methods of estimating Random Forests propensity scores could potentially produce an unbiased average treatment effect estimate after propensity scores weighting by the odds adjustment. Compared to the logistic regression estimation model using the true propensity score model, Random Forests had an additional advantage in producing unbiased estimated standard error and correct statistical inference of the average treatment effect. The relationship between the balance on the covariates' means and the bias of average treatment effect estimate was examined both within and between conditions of the simulation. Within conditions, across repeated samples there was no noticeable correlation between the covariates' mean differences and the magnitude of bias of average treatment effect estimate for the covariates that were imbalanced before adjustment. Between conditions, small mean differences of covariates after propensity score adjustment were not sensitive enough to identify the optimal Random Forests model specification for propensity score analysis.
ContributorsCham, Hei Ning (Author) / Tein, Jenn-Yun (Thesis advisor) / Enders, Stephen G (Thesis advisor) / Enders, Craig K. (Committee member) / Mackinnon, David P (Committee member) / Arizona State University (Publisher)
Created2013
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
Qualifications based selection (QBS) of construction services uses a variety of criteria to evaluate proponents and select a contractor for the project. The criteria typically fall into three categories: past performance and technical capability, key personnel, and price, with price often being considered the most important factor in selection. Evaluation and the merits of the key personnel category is not well described or discussed in research. Prior research has investigated the evaluation criteria elements and their ability to differentiate proponents. This case study uses QBS evaluation data from fifty-eight construction projects to show that use of a structured interview process provides the highest level of differentiation of qualifications of proponents, as compared to the proposed price and the technical proposal. The results of the analysis also indicate: 1) the key personnel element (the interview) is statistically more important than price,
2) Contractors who propose on projects using QBS should use their best people in proposal response, and 3) Contractors should educate/prepare their teams for interviews, people count.
2) Contractors who propose on projects using QBS should use their best people in proposal response, and 3) Contractors should educate/prepare their teams for interviews, people count.
ContributorsSawyer, Jeff T (Author) / Sullivan, Kennth S (Thesis advisor) / Wiezel, Avi (Committee member) / Badger, William (Committee member) / Arizona State University (Publisher)
Created2014
Description
This dissertation analyzes the reliability of reported employee stock option (ESO) expense, the determination of expected life of ESOs, motivations to manipulate ESO expense, and the impact of noise in ESO expense on subsequent stock price returns. Based on unique data, this is the first paper to measure average historical ESO life for all employees of a broad set of firms. I find average life has a mean of 4.12 years. Average life is reduced by 0.38 years per 10 percentage point increase in volatility, and industry effects explain an additional 7% of the variation. Reported expected life increases 0.37 years per year of historical life and an additional 0.16 years per year of age of the outstanding options. Deviations of reported volatility and life from benchmarks have positive correlations with deviations from own reporting history. Using stated assumptions rather than benchmark assumptions drops (increases) ESO expense by 8.3% (17.6%) for the 25th (75th) percentile firm. The change in earnings per share decreases (increases) by $0.019 ($0.007) for the 25th (75th) percentile firm. Tests for motivations to manipulate stock option expense downward have mixed results. Absolute values of deviations from benchmarks have a positive relationship with subsequent stock price volatility suggesting noise in reported stock option expense results in stock price noise. Deviations from benchmarks and subsequent cumulative abnormal returns have statistically significant results but are difficult to interpret.
ContributorsYoung, Brian (Author) / Coles, Jeffrey (Thesis advisor) / Hertzel, Michael (Committee member) / Babenko, Ilona (Committee member) / Arizona State University (Publisher)
Created2011
Description
Mutual monitoring in a well-structured authority system can mitigate the agency problem. I empirically examine whether the number 2 executive in a firm, if given authority, incentive, and channels for communication and influence, is able to monitor and constrain the potentially self-interested CEO. I find strong evidence that: (1) measures of the presence and extent of mutual monitoring from the No. 2 executive are positively related to future firm value (Tobin's Q); (2) the beneficial effect is more pronounced for firms with weaker corporate governance or CEO incentive alignment, with stronger incentives for the No. 2 executives to monitor, and with higher information asymmetry between the boards and the CEOs; (3) such mutual monitoring reduces the CEO's ability to pursue the "quiet life" but has no effect on "empire building;" and (4) mutual monitoring is a substitute for other governance mechanisms. The results suggest that mutual monitoring by a No. 2 executive provides checks and balances on CEO power.
ContributorsLi, Zhichuan (Author) / Coles, Jeffrey (Thesis advisor) / Hertzel, Michael (Committee member) / Bharath, Sreedhar (Committee member) / Babenko, Ilona (Committee member) / Arizona State University (Publisher)
Created2012
Description
The workforce demographics are changing as a large portion of the population is approaching retirement and thus leaving vacancies in the construction industry. Succession planning is an aspect of talent management which aims to mitigate instability faced by a company when a new successor fills a vacancy. Research shows that in addition to a diminishing pool of available talent, the industry does not have widespread, empirically tested and implemented models that lead to effective successions. The objective of this research was to create a baseline profile for succession planning in the construction industry by identifying currently implemented best practices. The author interviewed six companies of varying sizes and demographics within the construction industry and compared their succession planning methodologies to identify any common challenges and practices. Little consensus between the companies was found. The results of the interviews were then compared to current research literature, but even here, little consensus was found. In addition, companies lacked quantitative performance metrics demonstrating the effectiveness, or ineffectiveness, of their current succession planning methodologies. The authors recommended that additional research is carried out to focus on empirical evidence and measurement of industry practices surrounding talent identification, development, and transition leading to succession.
ContributorsGunnoe, Jake A (Author) / Sullivan, Kenneth (Thesis advisor) / Wiezel, Avi (Committee member) / Kashiwagi, Dean (Committee member) / Arizona State University (Publisher)
Created2015