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中国水环境行业当前正处在以质量驱动、效率提升为主导的发展阶段，为积极响应国家政策以及环境发展导向，平衡公众日益增长的公共品需求同公共品短缺、低效之间的矛盾，抓住市场发展机遇，提高企业市场竞争中的核心能力，水环境行业必须要明确资本驱动、效率导向、服务标准提高要求下的价值流方向，加快行业发展动力的创新改革。因此，本文立足政府充分授权下的水环境企业战略联盟模式（具体体现为BOT模式）影响因素研究，包括如下几部分内容：
第一，界定政府充分授权下水环境企业战略联盟内涵，分析其形成的理论基础、水环境企业战略联盟的类型、发展差异性及战略联盟动因。通过梳理战略联盟理论国内外研究现状回顾及评述，提出政府充分授权下水环境企业战略联盟模式研究的主要问题。
第二，探索政府充分授权下水环境企业战略联盟模式的影响因素。通过对水环境基础设施战略联盟项目合同关键内容的深入分析，识别出政府充分授权下水环境企业战略联盟模式的关键影响因素。
第三，实证分析各关键因素对政府充分授权下水环境企业战略联盟模式效果的影响。运用回归分析方法对项目规模、政府政策、监督管理、激励机制、风险分配和投资回报对联盟模式效果的影响进行实证检验，验证了各影响因素对政府充分授权下水环境企业战略联盟模式效果的正向作用。
最后，对政府充分授权下水环境企业战略联盟模式影响因素及作用研究的结论进行总结。
第一，界定政府充分授权下水环境企业战略联盟内涵，分析其形成的理论基础、水环境企业战略联盟的类型、发展差异性及战略联盟动因。通过梳理战略联盟理论国内外研究现状回顾及评述，提出政府充分授权下水环境企业战略联盟模式研究的主要问题。
第二，探索政府充分授权下水环境企业战略联盟模式的影响因素。通过对水环境基础设施战略联盟项目合同关键内容的深入分析，识别出政府充分授权下水环境企业战略联盟模式的关键影响因素。
第三，实证分析各关键因素对政府充分授权下水环境企业战略联盟模式效果的影响。运用回归分析方法对项目规模、政府政策、监督管理、激励机制、风险分配和投资回报对联盟模式效果的影响进行实证检验，验证了各影响因素对政府充分授权下水环境企业战略联盟模式效果的正向作用。
最后，对政府充分授权下水环境企业战略联盟模式影响因素及作用研究的结论进行总结。
ContributorsLi, Zhensheng (Author) / Pei, Ker-Wei (Thesis advisor) / Yu, Xiaoyun (Thesis advisor) / Shen, Wei (Committee member) / Arizona State University (Publisher)
Created2019
Description
In this study I investigate the factors that may influence consumer preference and choice in China’s home interior decoration industry. With the fast development of information technology such as the internet in China, it becomes increasingly important to have a more precise understanding of consumer preference and choice in home interior decoration decisions so that companies in this industry can provide better services to meet customer needs. Using survey data from a sample of potential customers and a sample of existing customers of a large home interior decoration company, I find that (1) internet has become the mostly used channel by consumers to gather information about home interior decoration, (2) design style is the most influential factor in consumers’ choice of home interior decoration company, and (3) consumers are more likely to choose home interior decoration companies to provide full services when they are between 35 to 45 years old or above 55 years old, when it is the first time for them to purchase a real estate property, and when they are located in the Eastern region of China. Findings of this study can help home interior decoration companies better understand customer needs and preferences, facilitate changes in their marketing and sales strategies, and consequently strengthen their competitive advantage．
ContributorsYang, Jin (Author) / Shen, Wei (Thesis advisor) / Zhang, Anmin (Committee member) / Gu, Bin (Committee member) / Arizona State University (Publisher)
Created2015
Description汽车行业属于国家支柱型产业，创造了高额的产值，增加了就业岗位。随着汽车生产行业竞争日趋激烈的趋势影响，汽车经销商在未来会出现明显的分化，并且逐步向头部集中。基于这样的行业背景，本项研究开展汽车经销商整体经营和盈利能力等方面的详细深入分析，即系统整合汽车经销商业务运营层面和财务层面数据，结合统计研究方法，对经销商盈利能力进行系统且详实归因分析，从而试别驱动盈利能力的关键业务要素。其研究成果能够完善对行业发展规律和经营模式系统性理解，从而进一步指导该领域的相关业务实践，提高经销商整体经营业绩。本课题通过四个阶段来开展经销商整体经营与盈利归因的相关研究。首先，本课题梳理了中国汽车消费行业发展的历史，同时阐述样本期内（2018-2020年）国内宏观经济和汽车消费市场的特征进行，并介绍X品牌汽车经销商的地理分布、资质和业绩评级体系、自身经营特征以及汽车生产商对经销商扶持政策等方面。在第二阶段，本课题聚焦研究假设、模型与方法，通过对X品牌汽车经销商的业务结构和运营管理开展分析，并逐步识别影响经销商盈利的关键指标变量，并提出研究假设和相关模型（即时间序列模型和面板回归模型）。在第三阶段，本课题首先开展经销商相关信息整体性统计分析，获得关键业务指标在样本期内动态特征，并结合时间序列回归模型探讨各项业务指标对经销商整体盈利能力的影响程度。在第四阶段，本课题采用（个体）固定效应的面板回归模型来研究不同组别（控制）条件下经销商盈利能力的影响因素以及其盈利能力对这些因素的敏感程度，从而更深入和全面地揭示影响经销商盈利能力的潜在因素。
基于上述四阶段的研究结果，本研究进一步就提升经销商盈利能力展开讨论，并提出相应对策。本课题相关结论仅从X品牌汽车经销商经营和财务数据进行定性和定量分析获得，但衷心希望本研究的成果能够对汽车经销商改善经营业务方面能起到实践上的借鉴和指导意义。
ContributorsPan, Guangxiong (Author) / Shen, Wei (Thesis advisor) / Wu, Fei (Thesis advisor) / Zhu, Qigui (Committee member) / Arizona State University (Publisher)
Created2022
Description
Over the past two decades, propelled by urbanization, domestic investment and construction of commercial complexes have rapidly accelerated. This has led to a dramatic expansion of these complexes with swift operational iterations and related data changes. The impact of changing domestic and international financial policies, along with political environments, has seen e-commerce gradually seize the middle and low-end retail markets. Additionally, the global spread of the COVID-19 pandemic in the last three years has resulted in a substantial slowdown in domestic economic growth. Despite this, there is still developmental potential, prompting unprecedented attention to corporate investment and commercial operations.However, acquiring basic operational data in commerce is challenging, with inconsistent measurement standards among enterprises, hindering accurate and systematic judgments of operational performance. The factors influencing the operational performance of commercial complexes in China remain inadequately researched.At this juncture, the scientific measurement of commercial complex operational performance is crucial for their healthy development. This study explores the relationship between enterprise investment behavior, operational management behavior, and commercial complex operational performance. It measures influencing factors using resource configuration theory to control uncontrollable environmental factors, such as urban hierarchy, surrounding population, per capita GDP, surrounding commercial inventory and increment, and location planning support. Dynamic capability theory is then applied to investigate the impact of variables like the number of leases, area, brands, lease cost income, marketing activity types, activity funds, and activity time on operational performance. A model is established to analyze operational performance, contrasting significant variables before and after the pandemic, identifying factors affecting operational performance in early-stage investment and later-stage management strategies. Post-pandemic adjustments are suggested to adapt to changing environmental conditions.In the empirical research section, this paper validates the theoretical model through data analysis, studying the volatility of operational performance based on factors influencing commercial complexes. Integrating theoretical backgrounds, it analyzes investment and management strategies for enterprises in different situations, emphasizing key indicators. This provides enterprises with better choices for future projects and empowers commercial complex managers for effective future management, enhancing operational performance. The study offers a theoretical basis and guidance for promoting the healthy development of the market.
ContributorsHuang, Ke (Author) / Shen, Wei (Thesis advisor) / Zhu, Qigui (Thesis advisor) / Hu, Yu (Committee member) / Arizona State University (Publisher)
Created2024
Description
With the continuous development of the Chinese capital market over the past thirty years, the securities analyst industry has experienced a process of transformation from a reckless period to a golden time. One of the most important signals is that securities analysts are increasingly conducting research report providing long-term earnings forecasts for the company. However, current research on analysts is limited to their short-term forecasting behavior, and there is little on analysts' long-term earnings forecasts. Therefore, this article takes the research on analysts' long-term forecast reports issued by analysts on A-share listed companies, and conducts an empirical study on the analysts' forecasts accuracy and its influencing factors. First, the author combed the research literature related to analyst forecasts and selected variables from three dimensions, including company characteristics (financial indicators and non-financial indicators), analyst characteristics and affiliated institution characteristics; secondly, considering the high-dimensionality of the influencing factors, this paper uses the method of combining machine learning and traditional regression to conduct empirical research; finally, the research tested the heterogeneity of influencing factors from two perspectives, including time and industry.The results of this article show that the long-term profit forecasts of analysts in China have advantages over traditional statistical models. More than 60% of analysts
provide profit forecasts that are better than statistical models. Afterwards, when examining the factors that affected the accuracy of analysts’ forecasts, it found that although analyst and institutional characteristics affected analysts’ predictions to a certain extent, company characteristics are the most important variables among them all. As the time goes by, the influence of non-financial factors on forecast accuracy gradually decreasing, but analyst characteristics continue to strengthen. In addition, cyclical industries are more difficult to predict than companies in non-cyclical industries, and the difficulty of prediction will not be reduced with the analyst efforts. This research can help analysts optimizing their forecasting behavior and prompts investors to understand analysts' reports more deeply, which makes them using analyst forecast data to make investment decisions in a rationally ways, and it can also help to promote the securities pricing efficiency and development of Chinese capital market.
ContributorsRao, Gang (Author) / Shen, Wei (Thesis advisor) / Yan, Hong (Thesis advisor) / Hu, Jie (Committee member) / Arizona State University (Publisher)
Created2024