Modeling and Analysis of Complex Technology Adoption Decisions: An Investigation in the Domain of Mobile ICT

Mobile information and communication technologies (ICT) promise to significantly transform enterprises, their business processes and services, improve employee productivity, effectiveness, and efficiency, and create new competitive advantages and business agility. Despite the plethora of potential benefits, however, widespread enterprise adoption of mobile ICT has not been as extensive as initially anticipated. Drawing on the extant information systems, technology management, and organizational innovation literature, this dissertation investigates the salient drivers and inhibitors of emerging ICT adoption, in general, and mobile ICT in particular, and develops an integrative ICT adoption decision framework. From this synthesis we identify four broad elements that influence an enterprise s decision to adopt mobile ICT: (1) business value, (2) costs and economics, (3) strategic alignment, and (4) enterprise readiness. The latter decision element has received only little theoretical and practical attention. In order to fill this gap, this dissertation explored the concept of enterprise readiness in further detail and identified eight key dimensions and their associated assessment indicators. Using a two-stage expert study and experimental design approach, we empirically validated these dimensions and determined their relative importance. Results indicated that leadership readiness followed by technology, data and information, and resource readiness, contributed the most to enterprise readiness for mobile ICT. The results are implemented into a web-based readiness diagnostic tool (RDT) that enables decision makers to assess an enterprise s readiness for mobile ICT. The benefits of the RDT are multifold: first, it navigates the decision maker through the complex readiness assessment space; second, it identifies potential organizational deficiencies and provides a means to assess potential sources of risks associated with the adoption and implementation of mobile ICT; and third, it enables decision makers to benchmark their level of readiness against other organizations. The dissertation concludes by highlighting both theoretical and practical implications for emerging and mobile ICT adoption management and suggesting directions for future research.Ph.D.Committee Chair: Rouse, William; Committee Member: Cross, Steve; Committee Member: Cummins, Michael; Committee Member: DeMillo, Richard; Committee Member: Vengazhiyil, Rosha

Structural Analysis and Visualization of Ecosystems: A Study of Mobile Device Platforms

Platforms enable and drive the creation of new products and services; they also shape and transform industries in fundamental ways. Consequently, platforms have become a core feature of many emerging business models. The success of a platform is inextricably linked to its network, or ecosystem, of enablers and complementors. Drawing on models and theories of complex systems, innovation, and network analysis, this study analyzes the evolving structure of interfirm relations in the mobile device platform ecosystem. This domain is of particular interest due to the emergence of promising new platforms and competition for platform leadership between open and closed business models. The visual approach presented in this study provides insights to the complexity of interfirm relations in the mobile device platform ecosystem, determines a platform’s competitive position, and identifies structural configurations that characterize various types of business strategies. Both theoretical and practical implications are discussed

Segue: Overviewing Evolution Patterns of Egocentric Networks by Interactive Construction of Spatial Layouts

Getting the overall picture of how a large number of ego-networks evolve is a common yet challenging task. Existing techniques often require analysts to inspect the evolution patterns of ego-networks one after another. In this study, we explore an approach that allows analysts to interactively create spatial layouts in which each dot is a dynamic ego-network. These spatial layouts provide overviews of the evolution patterns of ego-networks, thereby revealing different global patterns such as trends, clusters and outliers in evolution patterns. To let analysts interactively construct interpretable spatial layouts, we propose a data transformation pipeline, with which analysts can adjust the spatial layouts and convert dynamic egonetworks into event sequences to aid interpretations of the spatial positions. Based on this transformation pipeline, we developed Segue, a visual analysis system that supports thorough exploration of the evolution patterns of ego-networks. Through two usage scenarios, we demonstrate how analysts can gain insights into the overall evolution patterns of a large collection of ego-networks by interactively creating different spatial layouts.Comment: Published at IEEE Conference on Visual Analytics Science and Technology (IEEE VAST 2018

Visual analytics for supply network management: system design and evaluation

We propose a visual analytic system to augment and enhance decision-making processes of supply chain managers. Several design requirements drive the development of our integrated architecture and lead to three primary capabilities of our system prototype. First, a visual analytic system must integrate various relevant views and perspectives that highlight different structural aspects of a supply network. Second, the system must deliver required information on-demand and update the visual representation via user-initiated interactions. Third, the system must provide both descriptive and predictive analytic functions for managers to gain contingency intelligence. Based on these capabilities we implement an interactive web-based visual analytic system. Our system enables managers to interactively apply visual encodings based on different node and edge attributes to facilitate mental map matching between abstract attributes and visual elements. Grounded in cognitive fit theory, we demonstrate that an interactive visual system that dynamically adjusts visual representations to the decision environment can significantly enhance decision-making processes in a supply network setting. We conduct multi-stage evaluation sessions with prototypical users that collectively confirm the value of our system. Our results indicate a positive reaction to our system. We conclude with implications and future research opportunities.The authors would like to thank the participants of the 2015 Businessvis Workshop at IEEE VIS, Prof. Benoit Montreuil, and Dr. Driss Hakimi for their valuable feedback on an earlier version of the software; Prof. Manpreet Hora for assisting with and Georgia Tech graduate students for participating in the evaluation sessions; and the two anonymous reviewers for their detailed comments and suggestions. The study was in part supported by the Tennenbaum Institute at Georgia Tech Award # K9305. (K9305 - Tennenbaum Institute at Georgia Tech Award)Accepted manuscrip

On the Evolution of Mobile Platform Ecosystem Structure and Strategy

Platforms have become a core fundament of many technology industries. Platforms not only enable new products and services but have also been shown to influence strategies, shape businessmodels, and even transform entire industries. Platforms play a particularly important role in the mobile ecosystem. The success of smartphones has led to an intense battle of mobile platforms, each looking for ways to become the system of choice for mobile device manufacturers, mobile network operators, and mobile application developers. Drawing on theories of platform markets, strategic networks, and business ecosystems, this paper uses a visualization approach to study the evolving global interfirm structure and examines strategies used in the mobile platform ecosystem over the past five years. We identify important differences between mobile platform strategies and discuss their implications for both mobile ecosystem participants and the future of the app economy

Enterprise Readiness for IT Innovation: A Study of Mobile Computing in Healthcare

This research posits that enterprise-wide information technology (IT) innovation initiatives in uncertain economic times amplify the need and importance for decision makers to systemically evaluate their organization’s capabilities, competencies, and potential risk areas that could either accelerate or impede adoption and implementation. The purpose of this research is to develop a theoretically-grounded, conceptual framework of healthcare enterprise readiness for IT innovation that will aid health IT decision makers with this complex task. We study this in the context of mobile computing which is poised to fundamentally transform healthcare delivery by improving patient care and lowering costs. Preliminary findings of our multi-phase exploratory empirical study with healthcare CIOs reveal the relative importance of several key assessment dimensions and indicators. Our research has important implications for both adopters and providers of health IT and contributes to our broader understanding of IT-enabled transformation of healthcare

Competition between platform ecosystems: a longitudinal study of MOOC platforms

The last decade has seen a rise in software-based platforms that engender entirely new ecosystems. In newly emerging platform markets, platforms compete for partners and customers in a rapidly changing environment. Yet, extant research mostly studies platforms\u27 supply-side and demand-side strategies in relatively established platform markets. By combining a market-level and platform-level perspective, our research aims to develop a holistic understanding about the interdependencies between business model decisions, market evolution, and performance outcomes of platforms in emerging markets. We focus on the novel context of Massive Open Online Course (MOOC) platforms, analyzing longitudinal data for 35 MOOC platforms and their ecosystems. To account for the multi-level perspective, our research applies an innovative mixed-methods approach that combines qualitative methods with quan-titative measures and visualizations derived from network analysis. Our findings suggest that platforms in new markets converge towards common business models as market leaders imitate the business model innovations of its smaller competitors to manifest their market position. Based on these analyses, we derive four propositions on how the dynamics of a platform’s business model and ecosystem posi-tion affect each other and the platform’s market performance

Повышение эффективности подготовки нефти на нефтегазовом месторождении "К" (Красноярский край)

Объектом исследования является параметры работы установка подготовки нефти (УПН) на нефтегазовом месторождении (НГМ) "К", а предметом исследования УПН НГМ "К". Целью данной дипломной работы является определение критериев, характеризующих процесс работы УПН. Повышение эффективности сбора и подготовки продукции скважин в условиях нефтегазового месторождения "К". Объектом исследования является УПН на нефтегазовом месторождении "К", а предметом исследования является параметры работы УПН на нефтегазовом месторождении "К". Актуальность данной работы обоснована экономической целесообразностью увеличения выхода товарной нефти и уменьшению потерь нефтепродуктов.The object of the study is the operating parameters of an oil treatment unit (OTP) at an oil and gas field (NGM) "K", and the subject of research is the UPN NGM "K". The purpose of this thesis is to determine the criteria that characterize the process of the UPN work. Improving the efficiency of collection and preparation of well production in the conditions of the oil and gas field "K". The object of the study is the OTP at the oil and gas field "K", and the subject of the study is the parameters of the OTP at the oil and gas field "K". The relevance of this work is justified by the economic feasibility of increasing the yield of marketable oil and reducing the loss of oil

UNDERSTANDING MOBILE ECOSYSTEM DYNAMICS: A DATA-DRIVEN APPROACH

The mobile ecosystem consists of a heterogeneous and continuously evolving set of firms that are interconnected through a complex, global network of relationships. However, there is very little theoretical understanding how these networks emerge and evolve and no well-established methodology to study these phenomena. Traditional approaches have primarily utilized alliance data of relatively established firms; however, these approaches ignore the vast number of relevant ecosystem activities that occur at the personal, entrepreneurial, and university level. We argue and empirically illustrate that a data-driven approach, using both alliance and socially-curated datasets, can provide important complementary explanatory insights into the dynamics of the mobile ecosystem. We present our approach through two recently formed mobile ecosystem relationships – the strategic partnership between Nokia and Microsoft and Google’s acquisition of Motorola Mobility. Our analysis is complemented using network visualization techniques. The paper concludes with implications and future research opportunities