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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

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
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The difficulty of demonstrating a significant return on investment from the use of advanced data analytics has led to a lack of utilization of this tool. The most likely explanation for this phenomenon is the difficulty of incorporating non-financial metrics in the higher levels of analysis that are fully salient

The difficulty of demonstrating a significant return on investment from the use of advanced data analytics has led to a lack of utilization of this tool. The most likely explanation for this phenomenon is the difficulty of incorporating non-financial metrics in the higher levels of analysis that are fully salient and derived in a manner that can be understood and trusted by organizational leaders. Another challenge that has confounded the use of advanced analytics by the leadership of organizations is the widely accepted belief that models are oftentimes developed with an insufficient number of variables that are expected to have an impact, which inhibits extrapolation of results for use in real-world decision making. This research identifies factors that contribute to the underutilization of analytics models in managerial decisions by leadership of the produce industry, and explores a variety of potential tools including descriptive analytics and dashboards that are able to provide predictive, prescriptive, and more advanced cognitive methods of decision making for use by organizational leadership. By understanding the disconnect between availability of the advanced data analysis tools and use of such tools by organizational leadership, this research assists in identifying the programs and resources that should be developed and presented as opportunities for support in the industrial decision-making process. This dissertation explores why managers within the produce industry underutilize higher levels of data analytics and whether it is possible to increase their levels of cognitive comfort. It shows that by providing leadership with digestible and rudimentary business experiments, they become more comfortable with more complex data analytics and then are better able to utilize dashboards and other tools within their decision-making models. As experiments are explained to managers, they become as comfortable with conducting experiments as they are with dashboards, thus becoming comfortable with evaluating their benefits.
ContributorsGlassman, Jeremy Britz (Author) / St. Louis, Robert (Thesis advisor) / Shao, Benjamin (Committee member) / Manfredo, Mark (Committee member) / Arizona State University (Publisher)
Created2020
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The impacts of information technology (IT) on total factor productivity (TFP) are assessed through an integrative framework of IT-induced externalities and IT-leveraged innovations. Based on network externalities and endogenous growth theory, our study aims to reconcile the seeming discrepancy between the recent observed evidence and the prediction by neoclassical growth

The impacts of information technology (IT) on total factor productivity (TFP) are assessed through an integrative framework of IT-induced externalities and IT-leveraged innovations. Based on network externalities and endogenous growth theory, our study aims to reconcile the seeming discrepancy between the recent observed evidence and the prediction by neoclassical growth theory. We argue that computerization has reshaped the competitive landscape into a network economy with IT-induced externalities that benefit not only IT purchasers but also other stakeholders. Moreover, IT is a platform technology that can leverage innovations to enhance the technological level of production process. Consequently, these two factors of IT-induced externalities and IT-leveraged innovations exert positive impacts on TFP, suggesting IT plays a more pivotal role than input consumption and accumulation that neoclassical growth theory assumes for IT. We use panel data from 30 Organization of Economic Cooperation and Development (OECD) countries over the period of 2000–2009 to empirically test hypotheses on this IT-TFP link. Implications are drawn from our findings for future research to measure IT׳s contributions at the macro level more accurately, and policymakers are urged to cultivate IT׳s positive impacts on TFP to help sustain long-term economic growth.

ContributorsChou, Yen-Chun (Author) / Chuang, Howard Hao-Chun (Author) / Shao, Benjamin (Author) / W.P. Carey School of Business (Contributor)
Created2014-12-01