UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item FISSION-FUSION DYNAMICS IN MAMMALS: LINKING ANIMAL MOVEMENT TO GROUP BEHAVIOR(2016) Alvarez, Silvia J.; Fagan, William F; Biology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Mammals living in groups show temporal variation in spatial cohesion and membership of groups, a behavior known as fission-fusion dynamics (FFD). Changes in cohesion depend on the movement behavior of individuals, which is influenced by their social environment, among other factors. I aimed to answer two main questions: 1) how do cognitive abilities and environmental factors explain the variation in social systems of mammals with FFD? and 2) how are FFD related to movement behavior? To answer the first question, I built a dataset on social traits of mammals with FFD from published references and used multivariate analysis to uncover the patterns of variation in social systems. Variation resulted mostly from differences in group and subgroup sizes, and differences in social traits evidenced the presence of discrete categories of social organization that might represent distinct strategies of FFD. To assess the effects of brain size and resource availability on social traits, I used generalized estimating equations as a phylogenetic comparative method. Brain size affected most social traits in marine mammals, supporting predictions of the social brain hypothesis. Resource availability was poorly correlated with social traits in all terrestrial mammals, but it had different effects for herbivores and carnivores, suggesting that environmental constraints acting on FFD differ between trophic levels. To answer the second question, I assessed the predictive power of several movement metrics characterizing tracks of orangutans on FFD, using generalized boosted regressions. Tortuosity, speed, and the number of behaviors were strong predictors of group presence and size, while temporal changes in movement behavior were correlated with changes in cohesion. These findings highlight the potential use of individual movement data to predict aspects of FFD. Lastly, I used an agent-based model to explore the influence of different levels of specificity in recognition on grouping behaviors. Model results suggest that basic social behavioral rules influence FFD, and that more complex group dynamics, such as hierarchical group structures, only emerge in scenarios with high levels of recognition specificity. Overall, the model suggests that recognition abilities, which likely correlate with cognitive skills, may play an important role in the evolution of social systems.Item EXPLORING AND MODELING OF BIDDING BEHAVIOR AND STRATEGIES OF ONLINE AUCTIONS(2013) Guo, Wei; Rand, William; Jank, Wolfgang; Mathematics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Internet auctions, as an exemplar of the recent boom in e-commerce, are grow- ing faster than ever in the last decade. Understanding the reasons why bidders be- have a certain way allows invaluable insight into the auction process. This research focuses on methods for modeling, testing and estimation of bidders' behavior and strategies. I start my discussion with bid shading, which is a common strategy bidders believe obtains the lowest possible price. While almost all bidders shade their bids, at least to some degree, it is impossible to infer the degree and volume of shaded bids directly from observed bidding data. In fact, most bidding data only allows researchers to observe the resulting price process, i.e. whether prices increase fast (due to little shading) or whether they slow down (when all bidders shade their bids). In this work, I propose an agent-based model that simulates bidders with different bidding strategies and their interaction with one another. The model is calibrated (and hence properties about the propensity and degree of shaded bids are estimated) by matching the emerging simulated price process with that of the observed auction data using genetic algorithms. From a statistical point of view, this is challenging because it requires matching functional draws from simulated and real price processes. I propose several competing fitness functions and explore how the choice alters the resulting ABM calibration. The method is applied to the context of eBay auctions for digital cameras and show that a balanced fitness function yields the best results. Furthermore, in light of the discrepancy find from the model in bidders' be- havior and optimal strategies proposed from online auction literature. I extract empirical bidding strategies from auction winners and utilize the agent based model to simulate and test the performance of twenty-four different empirical and theo- retical strategies. The experiment results suggest that some empirical strategies perform robustly when compared to theoretical strategies and taking into account other bidders' ability to learn. In addition, I expended the online auction framework from single auction to multiple auction simulation, which acts as a platform for investigating and test- ing more complicated situations that involves the competition among concurrent auctions. This framework facilitates my investigation of bidders' switching behavior and enables me to answer a series questions. For example, is it beneficial for auction website to promote bidders' switching behavior? Will bidders and even sellers get any advantage from bidders' switching? What is the best auction recommendation strategy for online auction website to obtain higher profit and/or a better customer experience? Through careful experiment design, it has been showed that higher switching frequency leads to higher profit for auction website and reduces the price dispersion, which leads to reduced risk for both bidders and sellers. In addition, the best auction recommendation strategy is providing the five earliest closing auctions so that bidders can choose the lowest price auction.