Browsing by Subject "failure"

Now showing 1 - 4 of 4
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    Essays on the Role of Stakeholders in Firms’ Learning and Strategic Response to Failures
    (2018-12) Say, Gui Deng
    This dissertation examines how firms strategically respond to failures and the role of stakeholders in these responses. I propose that learning from stakeholder cues results in substantive behavioral changes which not only exceed stakeholders’ immediate expectations but also enable firms to avoid failures. Such failure-learning is contingent on whether failures are experienced directly or indirectly, and the degree of stakeholder involvement. Through two essays, I explore these ideas in novel and increasingly prevalent failure settings. In the first essay, I show that even without active direction by regulators, firms experiencing technological failures in the form of data breaches go beyond mandatory disclosure and strategically renew themselves through divestitures and top management turnover. Drawing on the failure-learning and strategic renewal literatures, I argue that technological failures occur possibly due to dysfunctional organizational and technical routines which stricken firms interpret broadly as problems of organizing. I test my hypotheses on unrelated subsidiary divestitures and Chief Technology Officer turnover undertaken by 6269 U.S. publicly traded firms of which 149 firms experienced data breaches during the period 2005- 2016. I find that firms’ size and diversification increase their vulnerability to failures. While firms respond through divestitures and management turnover, only divestitures reduce the recurrence of failures. Firms’ responses are also independent of regulatory stringency. In the second essay, I invoke resource dependence and institutional arguments and examine how social divestments, which represent a breakdown (failure) in the relationship between a prominent institutional investor and a targeted firm, affect the social responsibility behaviors of the remaining portfolio firms. I argue that social divestments signal the potential for resource withdrawal and delegitimization. Accordingly, remaining portfolio firms incorporate their vicarious learning by improving their ESG practices. I test my hypotheses within the context of social divestments by Norway’s sovereign wealth fund and changes in the ESG ratings of its U.S.-based portfolio firms over the period 1998-2011. I find that while larger equity holdings representing greater resource leverage enhances the positive effect of divestment of peers, complementary voice-based activism that exerts institutional pressures on portfolio firms is more effective in combination with the divestment tactic.
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    Modeling the mechanics and failure of discrete viscoelastic fiber networks
    (2018-10) Dhume, Rohit
    Network problems arise in all aspects of bioengineering, including biomechanics. For decades, the mechanical importance of highly interconnected networks of macromolecular fibers, especially collagen fibers, has been recognized, but models at any scale that explicitly incorporate fiber-fiber interactions into a mechanical description of the tissue have only started to emerge more recently. The mechanical response of networks shows an inherent non-linearity arising from the network architecture, and the non-affine deformations occurring within it. Thus, the overarching goal of this dissertation was to model the steady-state and time-dependent behaviors of discrete fiber networks to understand better how the behavior of an individual fiber differs from that of a network, and to study the effect of a network’s structure on its mechanics. First, viscoelastic relaxation of networks composed of linear viscoelastic fibers was analyzed, throwing light on two different contributions to the network re- laxation process: a material contribution due to the intrinsic viscoelasticity of the fibers, and a kinematic contribution due to the structure of the network. The effect of network composition on its relaxation spectrum was also analyzed revealing a constant evolution of structure-dependent characteristic relaxation times with changing composition. Next, network fatigue behavior was modeled using a fiber-based cumulative damage model to obtain stress-life (SN) curves for the network, and to compare fatigue behaviors of different network structures. Finally, the network model was used in a multiscale finite element approach to model actin-myosin motor-driven cell cytoskeletal contraction. The multiscale model was also used to highlight the importance of the choice of microstructure in predicting tissue pre-failure and failure behaviors.
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    The morphodynamic influence of base-level change and waves on lake sediment
    (2018-10) LaGarde, Michelle
    Lakes continuously accumulate sediment, a process that has been ongoing since their formation. The sediment consists of soil particles and biological remains that runoff from the watershed and into the lake. The sediment may also contain particles from aeolian transported material from the “airshed” and biological and inorganic precipitated minerals. Thus, lake sediment is a continuous environmental archive, containing information about the history of the lake, and its surroundings. Unfortunately, lake sediment is subject to remobilization and mixing due to a variety of sediment transport processes, such as mass wasting. There has been limited research on how base-level change influences mass wasting, in particular, slope failure. Some studies suggest slope failures are correlated with base-level fall and/or base-level rise, while others suggest they don’t correlate at all. To address this controversy, I conducted flume experiments at the Saint Anthony Falls Laboratory (SAFL) to observe slope failure in sediment mixtures containing four different walnut-shell/kaolinite ratios. Three base-level change rates were tested, producing 12 base-level change experiments. Another set of experiments was also designed to investigate what effect, if any, the addition of waves would have on mass flow. Video recordings were taken during each experiment and were analyzed to study the geometry of each profile before and after base-level change had occurred. Results suggest that there is consistent sediment transport when waves are present, aiding in the transportation of walnut-shell downslope. Without waves, transport is limited, and the clinoform is subject to compaction, or slump formation, depending on clay content. This difference depends heavily on a sediment’s composition, where hydraulic conductivity (K) plays an important role in water transmission through the clinoform. My experiments suggest that slope failures in the field would occur in lake sediment with higher clay content. Base-level change itself has no effect on the occurrence of failures, but slope failures should occur during base-level change if clay content is high. With only base-level change, we can expect to see compacted lake sediment with lower clay content (~15-33% clay). Slope failures (slumps) occur in lake sediment with higher clay content (~50%). With the presence of waves, however, wavebase plays an important role in sediment transport. Wave-base greatly influences sediment transport downslope, which is seen in my experimental work. This suggests that waves in the field also transport lake sediment downslope while washing away any finegrained particles (i.e. clay).
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    A Probabilistic Model for Failure of Polycrystaline Silicon MEMS Structures
    (2015-05) Zhu, Zhiren
    Reliable MEMS devices are expected to have a very low failure probability, and thus it is cost-prohibitive to determine design strength values merely based on extensive histogram testings. A theoretical understanding of probabilistic failure in the structure is critical for reliability analysis of MEMS devices. Prediction of failure statistics for MEMS structures are commonly based on the classical Weibull's model for material strength, which has been experimentally proven to be incapable of optimally fitting the failure probability distribution of MEMS structures. A generalized finite weakest-link model is developed to describe the strength statistics of polycrystalline silicon (poly-Si) MEMS structures. Different from the classical Weibull statistics based on extreme value statistics, the present model is applicable for poly-Si structures of all sizes. The overall failure probability of the structure is related to the failure probability of each material element along its sidewalls through a weakest-link statistical model. For each material element, the failure statistics is determined by both the random material strength and stress field induced by random sidewall geometry. The model is shown to agree well with measured strength histograms of poly-Si MEMS specimens of different sizes, and the calibrated mean strength of the material element is in accordance with theoretical strength of silicon. The strength statistics is further related to the effects of structure size on the mean structural strength, and an efficient method to determine the failure statistics of MEMS structures is proposed based on the present model.