1,310 research outputs found

    The effect of competition among brokers on the quality and price of differentiated internet services

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    Price war, as an important factor in undercutting competitors and attracting customers, has spurred considerable work that analyzes such conflict situation. However, in most of these studies, quality of service (QoS), as an important decision-making criterion, has been neglected. Furthermore, with the rise of service-oriented architectures, where players may offer different levels of QoS for different prices, more studies are needed to examine the interaction among players within the service hierarchy. In this paper, we present a new approach to modeling price competition in (virtualized) service-oriented architectures, where there are multiple service levels. In our model, brokers, as the intermediaries between end-users and service providers, offer different QoS by adapting the service that they obtain from lower-level providers so as to match the demands of their clients to the services of providers. To maximize profit, players, i.e. providers and brokers, at each level compete in a Bertrand game while they offer different QoS. To maintain an oligopoly market, we then describe underlying dynamics which lead to a Bertrand game with price constraints at the providers' level. Numerical simulations demonstrate the behavior of brokers and providers and the effect of price competition on their market shares.This work has been partly supported by National Science Foundation awards: CNS-0963974, CNS-1346688, CNS-1536090 and CNS-1647084

    Cloud Market Maker: An automated dynamic pricing marketplace for cloud users

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    © 2015 Elsevier B.V. Abstract Cloud providers commonly incur heavy upfront set up costs which remain almost constant whether they serve a single or many customers. In order to generate a return on this investment, a suitable pricing strategy is required by providers. Established industries such as the airlines employ dynamic pricing to maximize their revenues. In order to increase their resource utilization rates, cloud providers could also use dynamic pricing for their services. At present however most providers use static schemes for pricing their resources. This work presents a new dynamic pricing mechanism for cloud providers. Furthermore, at present no platform exists that provides a dynamic unified view of the different cloud offerings in real-time. Due to a rapidly changing landscape and a limited knowledge of the cloud marketplace, consumers can often end up choosing a cloud provider that is more expensive or does not give them what they really need. This is because some providers spend significantly on advertising their services online. In order to assist cloud customers in the selection of a suitable resource and cloud providers in implementing dynamic pricing, this work describes an automated dynamic pricing marketplace and a decision support system for cloud users. We present a multi-agent multi-auction based system through which such services are delivered. An evaluation has been carried out to determine how effectively the Cloud Market Maker selects the resource, dynamically adjusts the price for the cloud users and the suitability of dynamic pricing for the cloud environment

    Internet Startups’ Profit Dilemma. A Theoretical Paper on Using Two-Sided Markets Theory as a Framework in a Valuation Setting.

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    A Theoretical Paper on Using Two-Sided Markets Theory as a Framework in a Valuation Setting

    Automation and Adaptation: Information Technology, Work Practices, and Labor Demand at Three Firms

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    The use of information and communication technology to automate routine tasks involves two types of innovation: technological and organizational. Together, improvements in technological capabilities and complementary changes made by firms in the way they organize work and implement work practices constitute the conditions under which machines substitute for or complement human workers. Building on the prevailing model of routine-biased technical change and recent insights into organizational complementarities, I conduct three qualitative case studies in health care and real estate to assess the relationship between technology and firm-level labor demand. Unique combinations of technological innovation, organizational complementarity, and decision-making at each firm produce differential impacts for labor demand, with even similar technologies exhibiting quite different patterns of substitution for workers of all skill types. In addition, studying firm-level complementarities illuminates how and why the scope of the routine task may be growing, with particularly important implications for relatively higher skill workers

    Measuring the Business Value of Cloud Computing

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    The importance of demonstrating the value achieved from IT investments is long established in the Computer Science (CS) and Information Systems (IS) literature. However, emerging technologies such as the ever-changing complex area of cloud computing present new challenges and opportunities for demonstrating how IT investments lead to business value. Recent reviews of extant literature highlights the need for multi-disciplinary research. This research should explore and further develops the conceptualization of value in cloud computing research. In addition, there is a need for research which investigates how IT value manifests itself across the chain of service provision and in inter-organizational scenarios. This open access book will review the state of the art from an IS, Computer Science and Accounting perspective, will introduce and discuss the main techniques for measuring business value for cloud computing in a variety of scenarios, and illustrate these with mini-case studies

    Equilibrium and Learning in Queues with Advance Reservations

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    Consider a multi-class preemptive-resume M/D/1M/D/1 queueing system that supports advance reservations (AR). In this system, strategic customers must decide whether to reserve a server in advance (thereby gaining higher priority) or avoid AR. Reserving a server in advance bears a cost. In this paper, we conduct a game-theoretic analysis of this system, characterizing the equilibrium strategies. Specifically, we show that the game has two types of equilibria. In one type, none of the customers makes reservation. In the other type, only customers that realize early enough that they will need service make reservations. We show that the types and number of equilibria depend on the parameters of the queue and on the reservation cost. Specifically, we prove that the equilibrium is unique if the server utilization is below 1/2. Otherwise, there may be multiple equilibria depending on the reservation cost. Next, we assume that the reservation cost is a fee set by the provider. In that case, we show that the revenue maximizing fee leads to a unique equilibrium if the utilization is below 2/3, but multiple equilibria if the utilization exceeds 2/3. Finally, we study a dynamic version of the game, where users learn and adapt their strategies based on observations of past actions or strategies of other users. Depending on the type of learning (i.e., action learning vs.\ strategy learning), we show that the game converges to an equilibrium in some cases, while it cycles in other cases

    Multi-attribute demand characterization and layered service pricing

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    As cloud computing gains popularity, understanding the pattern and structure of its workload is increasingly important in order to drive effective resource allocation and pricing decisions. In the cloud model, virtual machines (VMs), each consisting of a bundle of computing resources, are presented to users for purchase. Thus, the cloud context requires multi-attribute models of demand. While most of the available studies have focused on one specific attribute of a virtual request such as CPU or memory, to the best of our knowledge there is no work on the joint distribution of resource usage. In the first part of this dissertation, we develop a joint distribution model that captures the relationship among multiple resources by fitting the marginal distribution of each resource type as well as the non-linear structure of their correlation via a copula distribution. We validate our models using a public data set of Google data center usage. Constructing the demand model is essential for provisioning revenue-optimal configuration for VMs or quality of service (QoS) offered by a provider. In the second part of the dissertation, we turn to the service pricing problem in a multi-provider setting: given service configurations (qualities) offered by different providers, choose a proper price for each offered service to undercut competitors and attract customers. With the rise of layered service-oriented architectures there is a need for more advanced solutions that manage the interactions among service providers at multiple levels. Brokers, as the intermediaries between customers and lower-level providers, play a key role in improving the efficiency of service-oriented structures by matching the demands of customers to the services of providers. We analyze a layered market in which service brokers and service providers compete in a Bertrand game at different levels in an oligopoly market while they offer different QoS. We examine the interaction among players and the effect of price competition on their market shares. We also study the market with partial cooperation, where a subset of players optimizes their total revenue instead of maximizing their own profit independently. We analyze the impact of this cooperation on the market and customers' social welfare

    Measuring the Business Value of Cloud Computing

    Get PDF
    The importance of demonstrating the value achieved from IT investments is long established in the Computer Science (CS) and Information Systems (IS) literature. However, emerging technologies such as the ever-changing complex area of cloud computing present new challenges and opportunities for demonstrating how IT investments lead to business value. Recent reviews of extant literature highlights the need for multi-disciplinary research. This research should explore and further develops the conceptualization of value in cloud computing research. In addition, there is a need for research which investigates how IT value manifests itself across the chain of service provision and in inter-organizational scenarios. This open access book will review the state of the art from an IS, Computer Science and Accounting perspective, will introduce and discuss the main techniques for measuring business value for cloud computing in a variety of scenarios, and illustrate these with mini-case studies
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