Iñaki Bildosola

Design and Implementation of a Cloud Computing Adoption Decision Tool: Generating a Cloud Road

Migrating to cloud computing is one of the current enterprise challenges. This technology provides a new paradigm based on “on-demand payment” for information and communication technologies. In this sense, the small and medium enterprise is supposed to be the most interested, since initial investments are avoided and the technology allows gradual implementation. However, even if the characteristics and capacities have been widely discussed, entry into the cloud is still lacking in terms of practical, real frameworks. This paper aims at filling this gap, presenting a real tool already implemented and tested, which can be used as a cloud computing adoption decision tool. This tool uses diagnosis based on specific questions to gather the required information and subsequently provide the user with valuable information to deploy the business within the cloud, specifically in the form of Software as a Service (SaaS) solutions. This information allows the decision makers to generate their particular Cloud Road. A pilot study has been carried out with enterprises at a local level with a two-fold objective: to ascertain the degree of knowledge on cloud computing and to identify the most interesting business areas and their related tools for this technology. As expected, the results show high interest and low knowledge on this subject and the tool presented aims to readdress this mismatch, insofar as possible.

Effects of innovation management system standardization on firms: evidence from text mining annual reports

Using a management formula to standardize innovation management can be thought of as deeply contradictory, however, several successful firms in Spain have been certified under the pioneer innovation management standard UNE 166002. This paper analyzes the effects that standardization has in the attitudes and values as regard to innovation for a sample of firms by text-mining their corporate disclosures. Changes in the relevance of the concepts, co-word networks and emotion analysis have been employed to conclude that the effects of certification on the corporate behavior about innovation are coincident with the open innovation and transversalization concepts that UNE 166002 promotes.

Forecasting the Big Services Era: Novel Approach Combining Statistical Methods, Expertise and Technology Roadmapping

This paper aims at proposing a novel approach to gathering and structuring information concerning an emerging technology, generating a relevant profile, identifying its past evolution, forecasting the short and medium-term evolution and integrating all of the elements graphically into a hybrid roadmap. The approach combines four families of technological forecasting methods, namely: Statistical Methods in terms of Bibliometrics and Data Mining; Trend Analysis; Descriptive Methods in terms of Technological Roadmapping; and Expertise. Its future application to forecast the evolution of emerging IT trends in current entities, which are creating the Big Services era, is proposed as future work.

Adaptive scalable SVD unit for fast processing of large LSE problems

Singular Value Decomposition (SVD) is a key linear algebraic operation in many scientific and engineering applications. In particular, many computational intelligence systems rely on machine learning methods involving high dimensionality datasets that have to be fast processed for real-time adaptability. In this paper we describe a practical FPGA (Field Programmable Gate Array) implementation of a SVD processor for accelerating the solution of large LSE problems. The design approach has been comprehensive, from the algorithmic refinement to the numerical analysis to the customization for an efficient hardware realization. The processing scheme rests on an adaptive vector rotation evaluator for error regularization that enhances convergence speed with no penalty on the solution accuracy. The proposed architecture, which follows a data transfer scheme, is scalable and based on the interconnection of simple rotations units, which allows for a trade-off between occupied area and processing acceleration in the final implementation. This permits the SVD processor to be implemented both on low-cost and highend FPGAs, according to the final application requirements.

Forecasting Cloud Computing: Producing a Technological Profile

Migrating to cloud computing is one of the current enterprise challenges. In this sense, the small and medium enterprise should be the most interested, given that initial investments are avoided and the technology offers gradual implementation. However, 54.9 % of SMEs confess that they have no knowledge of cloud technology. Accordingly, this paper aims at generating a relevant profile of cloud computing technology, as the first part of a novel approach based on four families of technological forecasting methods to gather and structure information concerning an emerging technology, generating a relevant profile, identifying its past development, forecasting the short and medium-term evolution and integrating all of the elements graphically into a hybrid roadmap. The outcome of the approach will raise the awareness of such technology as well as facilitate its implementation.

Laser Additive Manufacturing: A Patent Overview

Additive manufacturing technologies have the potential to change the paradigm of manufacturing. In this scenario, the main objective of this research work is to gain, through a patent study, an overall view of the trends of laser-based additive manufacturing technologies. The database used in order to retrieve patent information is Patseer and the data have been analyzed through the text mining and analytics package called VantagePoint. From the data obtained it can be concluded that, Laser-based additive manufacturing is an emerging technology with huge market potential. Undoubtedly, China is the prime mover of basic research in this technology development. However, Germany and the United States are the ones who are developing the market applications.

An Innovation Model for EPC/Turnkey Sector: The Case of Abengoa Solar New Technologies

Abengoa Solar New Technologies (ASNT) is a relevant R&D actor in solar energy EPC/Turnkey sector, its innovation strategy being characterized by the aggressive patenting strategy they have deployed since year 2008. On that same year ASNT got its innovation management system certified under UNE 166002 standard, combining two divergent issues such as standardization and innovation. This paper presents the main features of the innovation model put into practice at ASNT, detailing its implications for knowledge management and R&D employee incentive system.

Depicting Big Data: Producing a Technological Profile

Emerging Technologies are having a huge impact in the income statement of current enterprises and therefore they must be adopted as soon as possible. Thus, any attempt to introduce the characteristics and evolution of this kind of technologies is helpful for decision makers. In this sense, this paper aims at depicting Big Data, one of these cutting edge technologies, by obtaining a complete profile of it and generating the bases for a valid forecast. The approach is made within the Information Structuring and Technological Forecasting fields, with the application of several methods, namely: Text Mining and Natural Language Processing, Visualization Techniques and Trend Analysis.

An approach for modelling and forecasting research activity related to an emerging technology

The understanding of emerging technologies and the analysis of their development pose a great challenge for decision makers, as being able to assess and forecast technological change enables them to make the most of it. There is a whole field of research focused on this area, called technology forecasting, in which bibliometrics plays an important role. Within that framework, this paper presents a forecasting approach focused on a specific field of technology forecasting: research activity related to an emerging technology. This approach is based on four research fields—bibliometrics, text mining, time series modelling and time series forecasting—and is structured in five interlinked steps that generate a continuous flow of information. The main milestone is the generation of time series that measure the level of research activity and can be used for forecasting. The usefulness of this approach is shown by applying it to an emerging technology: cloud computing. The results enable the technology to be structured into five main sub-technologies which are characterised through five time series. Time series analysis of the trends related to each sub-technology shows that Privacy and Security has been the most active sub-technology to date in this area and is expected to maintain its level of interest in the near future.