Browsing by Subject "Platform"
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Item (2016-2017) Joint Resolution 3: In Support of the 2017 Invest in Texas Platform(2017-02-07) Helgren, Kevin; Cavazos, Sergio; Brown, Wills; Henry, Thomas; Przada, Jacob; Villareal, Jaime; Sundaram, SuchiItem Disintermediation and co-opetition in platform ecosystems and modern value chains(2015-05) Li, Zhuoxin; Agarwal, Ashish (Ph. D. in business administration); Gilbert, Stephen M.; Barua, Anitesh; Duan, Jun (Jason); Lai, Guoming; Whinston, Andrew B.This dissertation investigates partial disintermediation and co-opetition in platform-based ecosystems and modern supply chains. Disintermediation has been an intriguing puzzle for managers for the last several decades, but recent development in electronic commerce makes the management of this trade-off even more challenging. The first type of partial disintermediation I study, often referred to as platform envelopment, is widely observed in platform-based businesses. Platform owners often rely on complementary innovations from third-party providers (i.e., third-party contents), while providing their own products/services to consumers (i.e., first-party contents). The second type of partial disintermediation I study is referred to as supplier encroachment. Due to the fast development of electronic commerce, many manufacturers have established their direct-selling channels on the internet (e.g., online stores), instead of completely relying on third-party retailers to reach customers. The widespread observation of disintermediation and the resulting co-opetition behaviors in various industries has motivated me to investigate two important questions: (1) what's the impact of partial disintermediation on consumer demand and firm profits? (2) what strategies can be used to manage the co-opetition relationship? I use both analytical modeling and empirical methods to study the impact of disintermediation on consumer behaviors, firm profits, and social welfare. The findings provide managerial insights into how to manage the co-opetition dilemma due to disintermediation.Item Early-stage strategies in two-sided marketplaces(2016-05) Kyprianou, Christina; Graebner, Melissa E.; Bermiss, Y. Sekou; Harrison, David A; Ranganathan, Ram; Tripsas, MaryThis study explores the early-stage strategies that support the creation and growth of peer-to-peer marketplaces, a particular type of two-sided marketplace. Prior research on two-sided marketplaces has studied well-established firms and has not produced systematic evidence of the origins of two-sided marketplaces when a critical mass of participants has not yet been recruited. Moreover, its focus on formal economic models and price structures provides only a limited understanding of the early stage strategies that create value, recruit initial participants, and induce their interactions. I address limitations of prior research through an inductive multi-case study of ten peer-to-peer marketplaces. Findings suggest host firms create value and recruit initial participants by promoting and monitoring marketplace participants’ conformity with appropriate behaviors. In doing so, they exercise different levels of control (low, average, or high) on two dimensions: a) supply-side heterogeneity and b) cross-side interactions. Considering the interactions of these two dimensions, I propose a typology of nine value-creating activities. Patterns in the sequence in which host firms pursue these activities over time reveal two alternative and “equifinal” paths to promoting participant conformity and ultimately to generating growth. Emergent theory extends literature on resource orchestration to entrepreneurial firms and contributes to research on new forms of organizing.Item Essays on information technology for healthcare and sustainable traffic management(2020-09-02) Liu, Yixuan, Ph. D.; Lai, Guoming; Whinston, Andrew B.; Morrice, Douglas; Stinchcombe, Maxwell BInformation technology has fundamentally changed the world in every aspect. In this collection of research papers, I study some effects of IT in two domains - healthcare and sustainability - that closely related to human wellbeing. Levering the power of IT to redistribute resources, healthcare platforms have emerged to connect patients and physicians timely and economically. I study the strategic decisions of each party (Chapter 1) and the service design problem (Chapter 2) on such a two-sided platform using both theoretical modeling and data analytical tools. In Chapter 3, I study on a sustainable traffic management mechanism to decrease greenhouse gas emissions. In Chapter 1, we consider on-demand healthcare platforms that allow patients to seek care online from distributed doctors. Healthcare costs have been steadily increasing, while patient experience continues to sour with costly (many times unnecessary) commute and waiting. To alleviate the costs, various on-demand healthcare platforms have emerged but have been little investigated in academic research. We develop a strategic queueing model where the platform decides the commission rate upon which potential doctors make their participation, service quality and pricing decisions and potential patients make their service acquisition decisions independently. We find that in equilibrium a higher commission rate always lowers doctor participation as well as service quality, but it may increase the service price if it significantly softens the competition. Moreover, as patient intensity increases, the service quality improves, accompanied largely with a higher price. We further investigate the effect of platform price control. We find that allowing the platform to control the service price in addition to the commission rate may result in more doctor participation, higher service quality and price, higher platform profit, and surprisingly even higher profit for the doctors. This generally occurs when the patient intensity is either low or high, the waiting cost is low, or the doctor heterogeneity is low. Our results are useful to understand the performance of on-demand healthcare platforms. In Chapter 2, we focus on the service design problems of on-demand healthcare platforms. Many platforms offer patient subsidy in the form of a short-duration Q&A service at a meager price to induce user adoptions. Using a rich panel data from an on-demand healthcare platform in China, we investigate the impact of such service on demand for online consultations and offline appointments. We find that the subsidized service increases online service purchases and offline appointments by 4.7% and 8.7% in the subsequent month, respectively. Also, users’ expenditure on the online service in the following month increases by 15% after consuming the subsidized service, which highlights the revenue potential of such a service. Besides, we demonstrate the heterogeneity of spillover effects among different types of medical concerns and providers of different ranks. Our results shed light on the importance of such information-based services, which help manage the patient’s needs. In Chapter 3, we study an innovative routing mechanism to decrease GHG emissions in the era of the Internet of Things (IoT). Climate changes and global warming have become a severe issue that concerns people and governments all over the world. The combustion of fossil fuels, such as gasoline and diesel to transport people and goods, is one of the largest sources of CO2 emissions that heat the atmosphere. In this paper, we propose a combined information design and tolling mechanism to route traffics to decrease emissions. We formulate and characterize the equilibrium of a stochastic congestion game through the technique of potential functions. To evaluate the performance of the proposed mechanism, we define a new metric called Environmental Price of Anarchy that captures the inefficiency in congestions and emissions resulted from vehicles’ selfish behaviors. Our work highlights the advantages of the combined approach that improves both the utilities of vehicles and the welfare of societyItem Modest : Modeling, Debugging, and Testing distributed programs(2016-12) Rosales, David Andrew; Garg, Vijay K. (Vijay Kumar), 1963-Modest (Modeling, Debugging, and Testing) is a graphical modeling and testing environment for simulating the execution of distributed systems. Its objective is to assist as a learning tool but more importantly to aid in the design and implementation of distributed algorithms. It builds the simulation environment which means that only the algorithm is required from the user to perform testing. Logging and message animations help understand what events have occurred. Modest has the ability to replicate real life scenarios by inflicting network latency, network failures, and server failures. With the ability to quickly customize environment configuration and options, custom algorithm simulation can be initiated in minimal amounts of time. The concept of distributed computing can be complicated and Modest helps to simplify it with a modern user interface design.Item Platform rules : a case study of Samsung’s failure in the smartphone platform industry(2019-09-23) Seo, Hogeun; Strover, Sharon; Straubhaar, Joseph; Tyner, Kathleen R.; Treem, JeffreyBy investigating Samsung’s platform strategies, organizational culture and control mechanisms in the Android ecosystem, this research provides a balanced view on the global smartphone platform industry. In addition, this dissertation provides both empirical evidence and critical explanations by exploring the challenges of global leading manufacturer Samsung, especially Samsung’s Media Solution Center (hereinafter, MSC) which was in charge of software and platform services of the company. In the literature review and methodology chapter, this study reviews 1) how successful platform providers actually control other platform participants, 2) how they develop platform ecosystems and extend their businesses, 3) how a fast follower strategy which is considered a typical strategy of Samsung Electronics affects business performance, and 4) how cultural elements of organizations affect the performance of a company, especially an ICT firm. This research poses three research questions: RQ 1: How did Samsung’s platform strategies such as the fast follower strategy affect MSC’s platform services? RQ 2: How did the platform governance and control mechanisms in the global smartphone industry influence Samsung’s platform services? And RQ 3: How did the organizational culture of Samsung and MSC influence Samsung’s platform businesses? The research relies on interviews with 25 platform experts who once designed and worked on platform services such as Samsung Apps or Bada in Samsung’s MSC. This study basically explores business experiences of Samsung’s MSC whose challenges were not successful. Since Samsung’s attempts to control a platform failed, this research is in part a study of failure. In this it deviates from the typical study that pays much attention to the winner’s position or experience rather than that of a loser. Based on the interview data, this research provides significant findings. First, Samsung’s strategy of being the fastest follower generated positive network effects for the Google Play Store instead of Samsung’s platforms. Second, Google tightly controlled its competitors’ platform services in diverse (somewhat unfair) ways in order to maintain its dominance. Lastly, Samsung’s hierarchical and micromanaging organizational culture exerted negative influence on MSC’s platform services.Item Simplified engineering of Acinetobacter baylyi ADP1 and evolutionary strategies for genome minimization(2019-09-24) Suárez, Gabriel Antonio; Barrick, Jeffrey E.; Alper, Hal S; Moran, Nancy A; Miller, Kyle M; Davies, Bryan WOur ability to engineer and domesticate microbes to give them useful properties promises grand rewards in the energy, agriculture, chemical and health industries. Yet, synthetic biologists often struggle to engineer bacterial genomes despite ever-improving genome-scale models of how they function. Often, they are stymied by the sheer complexity of the cell’s underlying systems biology and by how these continue to evolve rapidly after they are engineered. Recent advances in genome stabilization and genome simplification promise to overcome these barriers and profoundly extend our understanding of basic molecular biology and cellular life. Both the natural instability of bacterial genomes and their unexplored complexity (e.g., the presence of many genes with unknown functions) underlie major challenges to be reckoned with that often lead synthetic biologists to rely on extensive experimental trial and error. The construction of cells with minimal genomes to make microbiology more predictable is riddled with difficulties. There are sometimes advantages and sometimes disadvantages for removing more and more genes to simplify a bacterial cell. Similarly, evolution is a process that may both frustrate or enable synthetic biology. It can be slowed down by removing selfish DNA elements from a genome or it can be applied to compensate for suboptimal designs. The work in this thesis explores these interactions between genome design and evolution. It asserts that rational engineering and simplification principles can lay stronger foundations for engineering microbial cells so that more complex and ambitious designs can be successfully built, but that evolution is also a necessary tool to achieve extreme simplification of a living cell to make it robust enough for research and industrial demands to achieve the potential of synthetic biology. Our model organism is Acinetobacter baylyi ADP1, a highly naturally transformable and metabolically versatile soil bacterium. Chapter 1 provides an introduction to A. baylyi genetic engineering and the current state-of-the-art in bacterial genome stabilizing and streamlining projects. Chapter 2 describes our rational engineering efforts to reduce A. baylyi ADP1 genome instability– mainly by deleting all transposable elements from its genome–and the beneficial phenotypes in the ADP1-ISx strain that resulted from this work. Chapter 3 describes improved A. baylyi genome engineering methods and how they were used in the first stage of a genome streamlining project. We also describe a “Golden Transformation” protocol that speeds up and simplifies the steps needed to make precise edits to the A. baylyi genome and also show that the native CRISPR-Cas system is functional and can be reprogrammed using this method. Chapter 4 describes how we begin to test how compensatory evolution of reduced genomes can open new pathways to more extreme genome minimization by restoring fitness that is lost after deleting many dispensable genes from a genome. Chapter 5 discusses future directions for making improvements that further stabilize and streamline the A. baylyi genome. Together, the work presented in this dissertation presents concepts, tools, and insights into strategies that were successful and unsuccessful for building a better and simpler Acinetobacter baylyi ADP1 genome. These approaches can also be applied to other bacterial species to propel the goals of synthetic biology forwardItem Towards a privacy-preserving platform for apps(2014-12) Lee, Sangmin; Dahlin, MichaelOn mobile platforms such as iOS and Android, Web browsers such as Google Chrome, and even smart televisions such as Google TV or Roku, hundreds of thousands of software apps provide services to users. Their functionality often requires access to potentially sensitive user data (e.g., contact lists, passwords, photos), sensor inputs (e.g., camera, microphone, GPS), and/or information about user behavior. Most apps use this data responsibly, but there has also been evidence of privacy violations. As a result, individuals must carefully consider what apps to install and corporations often restrict what apps employees can install on their devices, to prevent an untrusted app—or a cloud provider that an app communicates with—from leaking personal data and proprietary information. There is an inherent trade-off between users’ privacy and apps’ functionality. An app with no access to user data cannot leak anything sensitive, but many apps cannot function without such data. A password management app needs access to passwords, an audio transcription app needs access to the recordings of users’ speech, and a navigation app needs users’ location. In this dissertation, we present two app platform designs, πBox and CleanRoom, that strike a useful balance between users’ privacy and apps’ functional needs, thus shifting much of the responsibility for protecting privacy from the app and its users to the platform itself. πBox is a new app platform that prevents apps from misusing information about their users. To achieve this, πBox deploys (1) a sandbox that spans the user’s device and the cloud, (2) specialized storage and communication channels that enable common app functionality, and (3) an adaptation of recent theoretical algorithms for differential privacy under continual observation. We describe a prototype implementation of πBox and show how it enables a wide range of useful apps with minimal performance overhead and without sacrificing user privacy. In particular, πBox develops the aforementioned three techniques under the assumption of limited sharing of personal data. CleanRoom extends πBox and is designed to protect confidentiality in a "Bring Your Own Apps" (BYOA) world in which employees use their own untrusted third-party apps to create, edit, and share corporate data. CleanRoom’s core guarantee is privacy-preserving collaboration: CleanRoom enables employees to work together on shared documents while ensuring that the documents’ owners—not the app accessing the document—control who can access and collaborate on the document. To achieve this guarantee, CleanRoom partitions an app into three parts, each of which implements a different function of the app (data navigation, data manipulation, and app settings), and controls communication between these parts. We show that CleanRoom accommodates a broad range of apps, preserves the confidentiality of the data that these apps access, and incurs insignificant overhead (e.g., 0.11 ms of overhead per client-server request). Both πBox and CleanRoom use differential privacy for apps to provide feedback to their publisher. This dissertation explores how to adapt differential privacy to be useful for app platforms. In particular, we investigate an adaptation of re- cent theoretical algorithms for differential privacy under continual observation and several techniques to leverage it for useful features in an app environment including advertising, app performance feedback, and error reporting.