ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- Creators: Shen, Wei
Description
The theme for this work is the development of fast numerical algorithms for sparse optimization as well as their applications in medical imaging and source localization using sensor array processing. Due to the recently proposed theory of Compressive Sensing (CS), the $\ell_1$ minimization problem attracts more attention for its ability to exploit sparsity. Traditional interior point methods encounter difficulties in computation for solving the CS applications. In the first part of this work, a fast algorithm based on the augmented Lagrangian method for solving the large-scale TV-$\ell_1$ regularized inverse problem is proposed. Specifically, by taking advantage of the separable structure, the original problem can be approximated via the sum of a series of simple functions with closed form solutions. A preconditioner for solving the block Toeplitz with Toeplitz block (BTTB) linear system is proposed to accelerate the computation. An in-depth discussion on the rate of convergence and the optimal parameter selection criteria is given. Numerical experiments are used to test the performance and the robustness of the proposed algorithm to a wide range of parameter values. Applications of the algorithm in magnetic resonance (MR) imaging and a comparison with other existing methods are included. The second part of this work is the application of the TV-$\ell_1$ model in source localization using sensor arrays. The array output is reformulated into a sparse waveform via an over-complete basis and study the $\ell_p$-norm properties in detecting the sparsity. An algorithm is proposed for minimizing a non-convex problem. According to the results of numerical experiments, the proposed algorithm with the aid of the $\ell_p$-norm can resolve closely distributed sources with higher accuracy than other existing methods.
ContributorsShen, Wei (Author) / Mittlemann, Hans D (Thesis advisor) / Renaut, Rosemary A. (Committee member) / Jackiewicz, Zdzislaw (Committee member) / Gelb, Anne (Committee member) / Ringhofer, Christian (Committee member) / Arizona State University (Publisher)
Created2011
Description
Informal finance in this paper refers to the financing activities of individuals or households to borrow money through channels other than formal financial institutions such as commercial banks. Using data from China Household Finance Survey (CHFS) conducted by Southwestern University of Finance and Economics (SWUFE) and the People's Bank of China, this paper employs Probit model to analyze the factors that may influence the financing needs of Chinese households and factors that influence their likelihood of obtaining loans from formal financial institutions versus from informal channels. Results show that household wealth, family structure, and household head’s characteristics are the major factors that influence their financing needs. Moreover, the results suggest that (a) richer families are more likely to obtain loans from formal financial channels while poorer families are more likely to do so from informal channels; (b) families with stronger social ties are more likely to obtain loans from formal financial channels, but this relationship is weaker in regions where the financial market is more competitive;and (c) the increase of formal financial services is positively related to the probability of households obtaining formal finance, but has no relationship with the probability of households obtaining informal finance. These findings have important implications for finance policy making.
ContributorsZhang, Linchao (Author) / Shen, Wei (Thesis advisor) / Chen, Xiaoping (Thesis advisor) / Liu, Jun (Committee member) / Arizona State University (Publisher)
Created2016
Description
This thesis investigates whether mergers and acquisitions (M&As) help increase the competitive advantage and core competency of Chinese securities companies. Although M&As among Chinese securities companies were almost exclusively guided by the Chinese government in the earlier years, they have increasingly become more market-driven in recent years. Many large Chinese securities companies have engaged in horizontal mergers, cross-industry mergers, and cross-border mergers to increase their market positions. However, there is little up-to-date evidence about how these market-driven M&As influence the competitive advantage and core competency of securities companies in China. I seek to fill this gap by conducting a systematic analysis about whether M&As increase the core competency of the acquiring companies using data collected over a five-year window from 2010 to 2014.
On the basis of prior research findings and the current situation of the Chinese securities industry, I first develop a theoretical model about the sources of competitive advantage for Chinese securities companies, and then compile a comprehensive list of observable indicators that can be used to assess a Chinese securities company’s core competency. Next, I conduct a quantitative analysis to assess the core competency and relative market positions of the leading Chinese securities companies using data from 2010 to 2014. Overall, the results suggest that market-driven M&As increases the core competency of the acquiring securities companies. I then conduct four in-depth case analyses to better understand the mechanisms through which M&As can help increase the acquiring firms' core competency. I conclude with a discussion of the findings and their implications for Chinese securities companies and the overseeing governmental agencies.
On the basis of prior research findings and the current situation of the Chinese securities industry, I first develop a theoretical model about the sources of competitive advantage for Chinese securities companies, and then compile a comprehensive list of observable indicators that can be used to assess a Chinese securities company’s core competency. Next, I conduct a quantitative analysis to assess the core competency and relative market positions of the leading Chinese securities companies using data from 2010 to 2014. Overall, the results suggest that market-driven M&As increases the core competency of the acquiring securities companies. I then conduct four in-depth case analyses to better understand the mechanisms through which M&As can help increase the acquiring firms' core competency. I conclude with a discussion of the findings and their implications for Chinese securities companies and the overseeing governmental agencies.
ContributorsWang, Lijuan (Author) / Shen, Wei (Thesis advisor) / Qian, Jun (Thesis advisor) / Liu, Jun (Committee member) / Arizona State University (Publisher)
Created2016
Description
In this study I investigate the organizational strategies that Chinese power generation companies may use to reduce the impact of coal price increases on their profits. Organizations are open systems in that no organization possesses all the resources that it needs and all organizations must obtain resources from their external environments in order to survive. Resource dependent theory suggests that the most important goal of an organization is to find effective mechanisms to cope with its dependence on the external environments for resources that are critical to its survival. Chinese power generation companies traditionally rely heavily on coal as their raw materials, and an increase in coal price can have a significant negative impact on their profits. To address this issue, I first provide a systematic review of the resource dependence theory and research, with a focus on the strategies such as vertical integration, diversification, and hedging that organizations can undertake to reduce their dependence on the external environment as well as their respective benefits and costs. Next, I conduct a qualitative case analysis of the primary strategies the largest Chinese power generation companies have used to reduce their dependence on coal. I then explore a new approach that Chinese power generation companies may use to cope with increases in coal price, namely, by investing in an index of coal companies in the stock market. My regression analysis shows that coal price has a strong positive relation with the price of the coal company index. This finding suggests that it is possible for firms to reduce the negative impact of raw material price increase on their profits by investing in a stock market index of the companies that supply the raw materials that they depend on.
ContributorsSun, Min (Author) / Shen, Wei (Thesis advisor) / Liu, Jun (Committee member) / Pei, Ker-Wei (Committee member) / Arizona State University (Publisher)
Created2015