93,263 research outputs found

    Designing Scalable Business Models

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    Digital business models are often designed for rapid growth, and some relatively young companies have indeed achieved global scale. However despite the visibility and importance of this phenomenon, analysis of scale and scalability remains underdeveloped in management literature. When it is addressed, analysis of this phenomenon is often over-influenced by arguments about economies of scale in production and distribution. To redress this omission, this paper draws on economic, organization and technology management literature to provide a detailed examination of the sources of scaling in digital businesses. We propose three mechanisms by which digital business models attempt to gain scale: engaging both non- paying users and paying customers; organizing customer engagement to allow self- customization; and orchestrating networked value chains, such as platforms or multi-sided business models. Scaling conditions are discussed, and propositions developed and illustrated with examples of big data entrepreneurial firms

    On the intertwining between capacity scaling and TCP congestion control

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    Recent works advocate the possibility of improving energy efficiency of network devices by modulating switching and transmission capacity according to traffic load. However, addressing the trade-off between energy saving and Quality of Service (QoS) under these approaches is not a trivial task, specially because most of the traffic in the Internet of today is carried by TCP, and is hence adaptive to the available resources. In this paper we present a preliminary investigation of the possible intertwining between capacity scaling approaches and TCP congestion control, and we show how this interaction can affect performance in terms of both energy saving and QoS

    BlogForever D2.4: Weblog spider prototype and associated methodology

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    The purpose of this document is to present the evaluation of different solutions for capturing blogs, established methodology and to describe the developed blog spider prototype

    Domain Objects and Microservices for Systems Development: a roadmap

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    This paper discusses a roadmap to investigate Domain Objects being an adequate formalism to capture the peculiarity of microservice architecture, and to support Software development since the early stages. It provides a survey of both Microservices and Domain Objects, and it discusses plans and reflections on how to investigate whether a modeling approach suited to adaptable service-based components can also be applied with success to the microservice scenario

    How Much is the Whole Really More than the Sum of its Parts? 1 + 1 = 2.5: Superlinear Productivity in Collective Group Actions

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    In a variety of open source software projects, we document a superlinear growth of production (R∼cβR \sim c^\beta) as a function of the number of active developers cc, with β≃4/3\beta \simeq 4/3 with large dispersions. For a typical project in this class, doubling of the group size multiplies typically the output by a factor 2β=2.52^\beta=2.5, explaining the title. This superlinear law is found to hold for group sizes ranging from 5 to a few hundred developers. We propose two classes of mechanisms, {\it interaction-based} and {\it large deviation}, along with a cascade model of productive activity, which unifies them. In this common framework, superlinear productivity requires that the involved social groups function at or close to criticality, in the sense of a subtle balance between order and disorder. We report the first empirical test of the renormalization of the exponent of the distribution of the sizes of first generation events into the renormalized exponent of the distribution of clusters resulting from the cascade of triggering over all generation in a critical branching process in the non-meanfield regime. Finally, we document a size effect in the strength and variability of the superlinear effect, with smaller groups exhibiting widely distributed superlinear exponents, some of them characterizing highly productive teams. In contrast, large groups tend to have a smaller superlinearity and less variability.Comment: 29 pages, 8 figure
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