Matching Items (42)
Description
Forrest Research estimated that revenues derived from mobile devices will grow at an annual rate of 39% to reach $31 billion by 2016. With the tremendous market growth, mobile banking, mobile marketing, and mobile retailing have been recently introduced to satisfy customer needs. Academic and practical articles have widely discussed unique features of m-commerce. For instance, hardware constraints such as small screens have led to the discussion of tradeoff between usability and mobility. Needs for personalization and entertainment foster the development of new mobile data services. Given distinct features of mobile data services, existing empirical literature on m-commerce is mostly from the consumer side and focuses on consumer perceptions toward these features and their adoption intentions. From the supply side, limited data availability in early years explains the lack of firm-level studies on m-commerce. Prior studies have shown that unclear market demand is a major reason that hinders firms' adoption of m-commerce. Given the advances of smart phones, especially the introduction of the iPhone in 2007, firms recently have started to incorporate various mobile information systems in their business operations. The study uses mobile retailing as the context and empirically assesses firms' migration to this new sales venue with a unique cross-sectional dataset. Despite the distinct features of m-commerce, m-Retailing is essentially an extended arm of e-Retailing. Thus, a dependency perspective is used to explore the link between a firm's e-Retail characteristics and the migration to m-Retailing. Rooted in the innovation diffusion theory, the first stage of my study assesses the decision of adoption that indicates whether a firm moves to m-Retailing and the extent of adoption that shows a firm's commitment to m-Retailing in terms of system implementation choices. In this first stage, I take a dependency perspective to examine the impacts of e-Retail characteristics on m-Retailing adoption. The second stage of my study analyzes conditions that affect business value of the m-Retail channel. I examine the association between system implementation choices and m-Retail performance while analyzing the effects of e-Retail characteristics on value realization. The two-stage analysis provides an exploratory assessment of firm's migration from e-Retailing to m-Retailing.
ContributorsChou, Yen-Chun (Author) / Shao, Benjamin (Thesis advisor) / St. Louis, Robert (Committee member) / Goul, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
Information technology (IT) outsourcing, including foreign or offshore outsourcing, has been steadily growing over the last two decades. This growth in IT outsourcing has led to the development of different hubs of services across nations, and has resulted in increased competition among service providers. Firms have been using IT outsourcing to not only leverage advanced technologies and services at lower costs, but also to maintain their competitive edge and grow. Furthermore, as prior studies have shown, there are systematic differences among industries in terms of the degree and impact of IT outsourcing. This dissertation uses a three-study approach to investigate issues related to IT outsourcing at the macro and micro levels, and provides different perspectives for understanding the issues associated with IT outsourcing at a firm and industry level. The first study evaluates the diffusion patterns of IT outsourcing across industries at aggregate level and within industries at a firm level. In addition, it analyzes the factors that influence the diffusion of IT outsourcing and tests models that help us understand the rate and patterns of diffusion at the industry level. This study establishes the presence of hierarchical contagion effects in the diffusion of IT outsourcing. The second study explores the role of location and proximity of industries to understand the diffusion patterns of IT outsourcing within clusters using the spatial analysis technique of space-time clustering. It establishes the presence of simultaneous space and time interactions at the global level in the diffusion of IT outsourcing. The third study examines the development of specialized hubs for IT outsourcing services in four developing economies: Brazil, Russia, India, and China (BRIC). In this study, I adopt a theory-building approach involving the identification of explanatory anomalies, and propose a new hybrid theory called- knowledge network theory. The proposed theory suggests that the growth and development of the IT and related services sector is a result of close interactions among adaptive institutions. It is also based on new knowledge that is created, and which flows through a country's national diaspora of expatriate entrepreneurs, technologists and business leaders. In addition, relevant economic history and regional geography factors are important. This view diverges from the traditional view, wherein effective institutions are considered to be the key determinants of long-term economic growth.
ContributorsMann, Arti (Author) / Kauffman, Robert J. (Thesis advisor) / Santanam, Raghu (Thesis advisor) / St. Louis, Robert (Committee member) / Anselin, Luc (Committee member) / Nault, Barrie R (Committee member) / Arizona State University (Publisher)
Created2012
Description
Ample evidence exists to support the conclusion that enterprise search is failing its users. This failure is costing corporate America billions of dollars every year. Most enterprise search engines are built using web search engines as their foundations. These search engines are optimized for web use and are inadequate when used inside the firewall. Without the ability to use popularity-based measures for ranking documents returned to the searcher, these search engines must rely on full-text search technologies. The Information Science literature explains why full-text search, by itself, fails to adequately discriminate relevant from irrelevant documents. This failure in discrimination results in far too many documents being returned to the searcher, which causes enterprise searchers to abandon their searches in favor of re-creating the documents or information they seek. This dissertation describes and evaluates a potential solution to the problem of failed enterprise search derived from the Information Science literature: subject-aided search. In subject-aided search, full-text search is augmented with a search of subject metadata coded into each document based upon a hierarchically structured subject index. Using the Design Science methodology, this dissertation develops and evaluates three IT artifacts in the search for a solution to the wicked problem of enterprise search failure.
ContributorsSchymik, Gregory (Author) / St. Louis, Robert (Thesis advisor) / Goul, Kenneth M (Committee member) / Santanum, Raghu (Committee member) / Arizona State University (Publisher)
Created2012
Description
This study examines the 3 key questions of media budget allocation, to find our a better invest model. Including spending share of traditional media and digital media, program selection strategy and duration mix optimization to analyse the trend of sample A (a global cosmetic brand) . Based on every test media campaign, we do research of media performance and sales volumn, add youth consumer behavior result, to develop a media investment ROI model for this brand. Create the evaluation system according to past big data and find the learnings of different length TVC usage. Of course all relavant findings and implications will be summarized after every section.
ContributorsXu, Jin (Author) / Gu, Bin (Thesis advisor) / Chen, Xinlei (Thesis advisor) / Shao, Benjamin (Committee member) / Arizona State University (Publisher)
Created2018
Description
The Pearson and likelihood ratio statistics are well-known in goodness-of-fit testing and are commonly used for models applied to multinomial count data. When data are from a table formed by the cross-classification of a large number of variables, these goodness-of-fit statistics may have lower power and inaccurate Type I error rate due to sparseness. Pearson's statistic can be decomposed into orthogonal components associated with the marginal distributions of observed variables, and an omnibus fit statistic can be obtained as a sum of these components. When the statistic is a sum of components for lower-order marginals, it has good performance for Type I error rate and statistical power even when applied to a sparse table. In this dissertation, goodness-of-fit statistics using orthogonal components based on second- third- and fourth-order marginals were examined. If lack-of-fit is present in higher-order marginals, then a test that incorporates the higher-order marginals may have a higher power than a test that incorporates only first- and/or second-order marginals. To this end, two new statistics based on the orthogonal components of Pearson's chi-square that incorporate third- and fourth-order marginals were developed, and the Type I error, empirical power, and asymptotic power under different sparseness conditions were investigated. Individual orthogonal components as test statistics to identify lack-of-fit were also studied. The performance of individual orthogonal components to other popular lack-of-fit statistics were also compared. When the number of manifest variables becomes larger than 20, most of the statistics based on marginal distributions have limitations in terms of computer resources and CPU time. Under this problem, when the number manifest variables is larger than or equal to 20, the performance of a bootstrap based method to obtain p-values for Pearson-Fisher statistic, fit to confirmatory dichotomous variable factor analysis model, and the performance of Tollenaar and Mooijaart (2003) statistic were investigated.
ContributorsDassanayake, Mudiyanselage Maduranga Kasun (Author) / Reiser, Mark R. (Thesis advisor) / Kao, Ming-Hung (Committee member) / Wilson, Jeffrey (Committee member) / St. Louis, Robert (Committee member) / Kamarianakis, Ioannis (Committee member) / Arizona State University (Publisher)
Created2018
Description当前各个城市都在努力推动“互联网+政务”的公共服务新模式，打造政府公共服务平台，提供“一站式”的服务资源，以民众需求为中心，解决民众信息查询、政府办事预约、政策咨询等公共活动的需要。可以看出，政务平台给民众的生活带来极大的便利，是当前各地政府响应中央建立“智慧城市”“数字中国”的重要举措。
本课题发现当前的政务平台逐步引入PPP模式，借助社会资源开发政务平台。但是，PPP模式是否有利于政务平台的建设，受到哪些因素的制约，如何更好地利用PPP模式进行开发工作，这些问题在现前的研究中没有得到很好地探索。带着这些问题，本课题对PPP模式在政务平台建设中的作用进行了深入剖析。主要研究内容如下：
在第一部分中，本课题政府公共服务和政务相关理论进行了全面整理，发现政务平台要想走出一条健康发展之路，需要借助社会资源进行市场化，而PPP模式符合当前政务平台建设的需要。本文对PPP模式在国内外电子政务的应用进行了分析，提出了本文的研究主题。
在第二部分中，本文对华东地区50座城市的政务平台进行了调研，对常见问题进行了整理，发现PPP模式已经广泛应用于政务平台建设中，且主要有四种模式，本文对50座城市的政务平台建设情况进行了数据采集，并进行了深入分析。
在第三部分中，结合调研现状和文献研究成果，提出了PPP模式影响政务平台建设的相关假设，并构建了计量模型。通过短面板分析验证假设，并进行了Robust分析，证实结论的普适性。
在第四部分中，本文分析了研究结果，认为政务平台采用PPP模式能够有效促进政务平台的建设水平，提高用户满意度；并且PPP模式与合作企业的估摸、信息的透明程度和平台的交互能力存在显著的交互作用，共同影响用户对政务平台的评价。政府引入PPP模式，充分对接可利用资源，并加强盈利控制，对当前政务平台的建设是具有积极意义的。
本课题发现当前的政务平台逐步引入PPP模式，借助社会资源开发政务平台。但是，PPP模式是否有利于政务平台的建设，受到哪些因素的制约，如何更好地利用PPP模式进行开发工作，这些问题在现前的研究中没有得到很好地探索。带着这些问题，本课题对PPP模式在政务平台建设中的作用进行了深入剖析。主要研究内容如下：
在第一部分中，本课题政府公共服务和政务相关理论进行了全面整理，发现政务平台要想走出一条健康发展之路，需要借助社会资源进行市场化，而PPP模式符合当前政务平台建设的需要。本文对PPP模式在国内外电子政务的应用进行了分析，提出了本文的研究主题。
在第二部分中，本文对华东地区50座城市的政务平台进行了调研，对常见问题进行了整理，发现PPP模式已经广泛应用于政务平台建设中，且主要有四种模式，本文对50座城市的政务平台建设情况进行了数据采集，并进行了深入分析。
在第三部分中，结合调研现状和文献研究成果，提出了PPP模式影响政务平台建设的相关假设，并构建了计量模型。通过短面板分析验证假设，并进行了Robust分析，证实结论的普适性。
在第四部分中，本文分析了研究结果，认为政务平台采用PPP模式能够有效促进政务平台的建设水平，提高用户满意度；并且PPP模式与合作企业的估摸、信息的透明程度和平台的交互能力存在显著的交互作用，共同影响用户对政务平台的评价。政府引入PPP模式，充分对接可利用资源，并加强盈利控制，对当前政务平台的建设是具有积极意义的。
ContributorsZhao, Liang (Author) / Pei, Ker-Wei (Thesis advisor) / Chen, Xinlei (Thesis advisor) / Shao, Benjamin (Committee member) / Arizona State University (Publisher)
Created2019
Description
Sprouts Farmers Market is a natural grocery retailer that has undertaken a major growth strategy in recent years, and as a result, will soon face the task of managing over 150 stores in 7 states. This rapid expansion has created a need for process improvement and automation for many tasks that have become too time consuming and cumbersome. As an intern working in the purchasing division of this company for over a year now, I have had the opportunity to identify some of these issues, one of which I have addressed through completion of my honors creative project.
ContributorsWeiss, Jesse (Author) / Shao, Benjamin (Thesis director) / Hayes, Collen (Committee member) / Couturier, Stuart (Committee member) / Barrett, The Honors College (Contributor)
Created2011-05
Description
This study explores the impact of feedback and feedforward and personality on computer-mediated behavior change. The impact of the effects were studied using subjects who entered information relevant to their diet and exercise into an online tool. Subjects were divided into four experimental groups: those receiving only feedback, those receiving only feedforward, those receiving both, and those receiving none. Results were analyzed using regression analysis. Results indicate that both feedforward and feedback impact behavior change and that individuals with individuals ranking low in conscientiousness experienced behavior change equivalent to that of individuals with high conscientiousness in the presence of feedforward and/or feedback.
ContributorsMcCreless, Tamuchin (Author) / St. Louis, Robert (Thesis advisor) / St. Louis, Robert D. (Committee member) / Goul, Kenneth M (Committee member) / Shao, Benjamin B (Committee member) / Arizona State University (Publisher)
Created2012
Description随着信息通信技术在金融科技领域中得到广泛应用，传统金融机构依靠互联网技术极大的提升了自己的金融服务能力和金融服务效率。但与此同时，作为一个新兴业态，与互联网金融服务配套的法律制度和保障措施还未完善，特别是互联网借贷业务，贷前的风控系统不完善，同时还缺乏贷后管理机制，造成了网络贷款平台不断出现爆雷现象。仅2018年7月一个月内就有200多家平台出现问题，而到2020年底为止，出现问题的在线借贷平台高达80%。为了更好的保障在线借贷平台和互联网金融行业的健康发展，亟需完善个人征信体系建设，科学评估借款人违约风险。为了解决这一问题，本文首先对现有研究进行了理论梳理，找到可能对违约风险产生影响的因素，并总结为个人特征、社交网络特征、金融特征等三方面的因素。在这之后，从社交网络特征对违约风险进行了深入分析。其次，利用大数据分析方法，构建了随机森林信用评价模型。最后，文章还通过与不同数据集上的相同模型、相同数据集上的不同模型进行对比，对本文构建模型的有效性进行了评估。
研究结论表明：（1）用户的社交网络特征对用户违约风险、欺诈等级具有一定的解释力度，其中用户通话类社交特征对用户欺诈等级的识别效果最好，其次为风险等级，违约标签的识别效果最差，而且用户的地域特征对社交网络特征有显著的调节作用。（2）通过随机森林模型，本文发现年龄、贷款金额是影响客户违约风险和欺诈等级的最重要的因素。（3）比较多元回归模型和随机森林模型，随机森林模型对样本用户特征重要性探索的准确度要高于多元回归模型。
根据上述结论，本文提出了相应了建议：（1）在线借贷平台在判断用户违约风险时，应该在现有的分析框架中考虑用户社交特征来提升用户风险预测精度；（2）信贷公司应该将随机森林等方法纳入到用户是否违约、风险等级和欺诈等级的预测中，这样会显著的提升公司对用户违约、欺诈等级的预测精度。
ContributorsHan, Wei (Author) / Shen, Wei (Thesis advisor) / Hu, Jie (Thesis advisor) / Zheng, Zhiqiang (Committee member) / Arizona State University (Publisher)
Created2022
Description在目前中国资本市场中，风险资本偏好于科创企业，而科创企业的重要创新产出——专利，是衡量其创新程度的重要指标。本文以上市公司和非上市公司样本为研究标的，分别探讨其专利数量、质量对股权融资的影响效应。从理论意义来看，目前关于专利与企业价值关系的研究，大多集中在上市公司。此外，对上市公司的研究层面及内容，大多关注一个维度，专利要素内容相对单一。另外，既有研究对专利与企业绩效之间关系研究较多，对于专利与融资估值之间关系的关注较少。为此，本文从非上市科创企业入手，从专利的数量、质量两个维度对其股权融资进行整体分析、研究。从实践意义来看，本文通过收集非上市公司、科创板上市公司的专利、财务等数据，进行分析，得出专利数量、质量与融资估值之间的关系，从而对预备在科创板上市的公司提供可借鉴的内容。
基于此，本文以综合质性研究和定量实证研究两种研究方法，对专利数量、质量与创新型企业的融资估值关系进行了分析。本文以3家非上市公司和3家上市公司为研究标的，取得初步结论后，以非上市公司和上市公司数据为样本，进行对比分析，得出主要研究结论如下：
1、无论是上市公司还是非上市公司，专利数量与融资估值之间存在着显著的倒U型关系。
2、无论是上市公司还是非上市公司，专利质量与融资估值之间存在着显著的正相关关系。
3、将上市公司与非上市公司进行对比，在专利数量与融资估值的关系方面，上市公司的专利数量的临界值比非上市公司更高，且在跨过临界值之后，专利数量的增减对于非上市公司融资估值的影响会比上市公司的影响更大。
4、从企业IPO前的专利情况与企业IPO后第一年的融资估值之间的关系来看，企业IPO前的专利数量与专利质量与融资估值之间都存在显著的正相关的关系。说明对于科技创新能力较强的企业来说，在企业IPO前的积累阶段，企业的专利数量越多，专利质量越高，对于企业的融资估值的促进作用越显著。
ContributorsWang, Hua (Author) / Shao, Benjamin (Thesis advisor) / Chang, Eric (Thesis advisor) / Zhu, Kevin (Committee member) / Arizona State University (Publisher)
Created2022