nep-ict New Economics Papers
on Information and Communication Technologies
Issue of 2015‒06‒05
three papers chosen by
Walter Frisch
Universität Wien

  1. Digital waves in economics By Ledenyov, Dimitri O.; Ledenyov, Viktor O.
  2. Risk-Benefit-Mediated Impact of Determinants on the Adoption of Cloud Federation By Netsanet Haile; Jorn Altmann
  3. Digital Data Genesis – evolution over time Dynamic Capability and Information Systems By Claudio Vitari; Elisabetta Raguseo

  1. By: Ledenyov, Dimitri O.; Ledenyov, Viktor O.
    Abstract: The recent discovery of the Ledenyov digital waves in the economies of scale and scope led to an origination of considerable scientific interest in the modeling of new types of the discrete-time digital signals generators for the business cycles generation in the macroeconomics. Article aims: 1) to model the discrete-time digital signals generators for the business cycles generation in the macroeconomics, 2) to demonstrate the technical differences between the new model of the discrete-time digital signals generator and the existing models of the continuous-time (continuous wave) signals generators in the macroeconomics; 3) to accurately analyze the spectrum of discrete-time digital signals in the economies of scale and scope, 4) to improve the Ledenyov discrete time digital signals theory to precisely characterize the discrete time digital signals in the macroeconomics, 5) to better develop the complex software program to forecast the business cycles, going from the spectral analysis of the discrete time digital signals and the continuous time signals in the nonlinear dynamic economic system over the selected time period. The developed MicroSA software program intends: 1) to perform the spectrum analysis of the discrete-time digital signals and the continuous-time signals in the macroeconomics; 2) to make the computer modeling and to forecast the business cycles, going from the spectral analysis of the discrete time signals and the continuous time signals in the macroeconomics. The MicroSA can be used by a) the central banks with the purpose to make the strategic decisions on the monetary policies, financial stability policies, and b) the commercial/investment banks with the aim to make the business decisions on the minimum capital allocation, countercyclical capital buffer creation, and capital investments.
    Keywords: discrete-time digital waves, discrete-time digital signals generators, spectrum analysis of discrete-time digital signals, amplitude of discrete-time digital signal, frequency of discrete-time digital signal, wavelength of discrete-time digital signal, period of discrete-time digital signal, phase of discrete-time digital signal, mixing of discrete-time digital signals, harmonics of discrete-time digital signal, nonlinearities of discrete-time digital signal, Juglar fixed investment cycle, Kitchin inventory cycle, Kondratieff long wave cycle, Kuznets infrastructural investment cycle, econophysics, econometrics, nonlinear dynamic economic system, economy of scale and scope, macroeconomics.
    JEL: E0 E00 E10 E17 E20 E22 E27 E30 E32 E37 E40 E44 E47 E50 E58 F0 F40 F41 F44 F47 O31 O33
    Date: 2015–06–02
  2. By: Netsanet Haile (College of Engineering, Seoul National University); Jorn Altmann (College of Engineering, Seoul National University)
    Abstract: As an emerging trend for maximizing IT resource utilization, cloud federation raises various technical, economic, and legal issues. In order to understand the future of its adoption among cloud providers, it is important to identify which factors can be driving or inhibiting the process. This study aims at closing this research gap and find out the strength of their inhibiting or facilitating factors. Factors suggested by relevant studies as determinants of cloud computing are compiled. Among those determinants, the most relevant factors are selected and, then, used to construct a model of hypothesized relationships of the determinants with the perception of risk and benefits of cloud federation, thus with the intention of joining a cloud federation. Data from a total of 300 cloud service providers, consultants, and IT experts were collected through a survey questionnaire. The model is evaluated using structural equation modeling. The findings show that, among the six determinants analyzed by the study, flexibility and competitive pressure showed strong positive impacts. Thus, they are considered the major drivers of cloud federation. Furthermore, interoperability, service quality decline, and legal issues could be linked to be strong inhibitors of cloud federation. However, all these determines are strongly mediated by the perceived risk and perceived benefit of cloud federation. The estimated results for cloud providers showed that large cloud providers are attracted to cloud federation due to the potential of offering flexible services, while small cloud providers are driven by competitive pressure to join a cloud federation.
    Keywords: Cloud Computing, Cloud Federation, Structural Equation Modelling, Strategic Alliance, Survey, Adoption, Cloud Provider.
    JEL: C12 C51 C83 D74 D81 L16 L86 M21
  3. By: Claudio Vitari (MTS - Management Technologique et Strategique - Grenoble École de Management (GEM)); Elisabetta Raguseo (MTS - Management Technologique et Strategique - Grenoble École de Management (GEM))
    Abstract: This report is the output of a research project co-financed by Grenoble Ecole de Management and Rhône Alpes French region. This study was conducted with the aim of understanding how Information Technology (IT) provides new opportunities to firms, specifically focusing on the role that such solutions play in the process and usage of digital data. Digital data are the focus of this project since data can provide new opportunities for firms: they have become a torrent flowing into every area of the global economy. In such a context, companies may have to deal with a high volume of transactional data, capturing trillions of bytes of information about their customers, suppliers, and operations. Millions of sensors are embedded in the physical world in devices such as mobile phones, smart energy meters, cars, and industrial machines that sense, create and communicate data in the “digitalized” age. Therefore, there is the need of understanding whether companies are ready for extracting value from digital data and for figuring out the more favorable conditions under which this happens.
    Date: 2014

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