Unlocking the secrets of Spain’s R&D subsidies: An advanced analysis of applicant companies

Innovation is crucial for companies to stay competitive, provide value to customers, and generate profits. Likewise, research and development (R&D) is critical for companies to sustain productivity growth. Spain has lagged behind other countries in terms of R&D investment, with only 1.4% of its GDP allocated to R&D, well below the European average. To improve this situation, the government offers subsidies to stimulate R&D in Spanish companies. This study examines the profile of subsidized companies in Spain. The aim is to provide insight into the support for companies that apply for innovation subsidies by analyzing the profile of subsidized companies and identifying key variables influencing the success of obtaining innovation grants. The study is based on advanced estimation methods. Natural language processing (NLP), artificial neural network (ANN) techniques, and clustering are used to perform rigorous and robust analysis of the profile of subsidized companies in Spain. The study thus contributes to knowledge in the field of innovation subsidies

Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction

The paper reviews product data technology initiatives in the construction sector and provides a synthesis of related ICT industry needs. A comparison between (a) the data centric characteristics of Product Data Technology (PDT) and (b) ontology with a focus on semantics, is given, highlighting the pros and cons of each approach. The paper advocates the migration from data-centric application integration to ontology-based business process support, and proposes inter-enterprise collaboration architectures and frameworks based on semantic services, underpinned by ontology-based knowledge structures. The paper discusses the main reasons behind the low industry take up of product data technology, and proposes a preliminary roadmap for the wide industry diffusion of the proposed approach. In this respect, the paper stresses the value of adopting alliance-based modes of operation

G-DaM: A Distributed Data Storage with Blockchain Framework for Management of Groundwater Quality Data

Groundwater overuse in different domains will eventually lead to global freshwater scarcity. To meet the anticipated demands, many governments worldwide are employing innovative and traditional techniques for forecasting groundwater availability by conducting research and studies. One challenging step for this type of study is collecting groundwater data from different sites and securely sending it to the nearby edges without exposure to hacking and data tampering. In the current paper, we send raw data formats from the Internet of Things to the Distributed Data Storage (DDS) and Blockchain (BC) edges. We use a distributed and decentralized architecture to store the statistics, perform double hashing, and implement access control through smart contracts. This work demonstrates a modern and innovative approach combining DDS and BC technologies to overcome traditional data sharing, and centralized storage, while addressing blockchain limitations. We have shown performance improvements with increased data quality and integrity

Global Employer Forum 2017: FutureWorks - Connecting Leaders & Fresh Thinking

We recently held our FutureWorks Global Employer Forum in London to discuss the megatrends that will impact global businesses and the future of work. Together with HR and employment leaders from some of the most innovative companies in the world, as well as leading academics and thinkers, we looked at how global employers can embrace the opportunities and manage the coming shocks. Here we share highlights from our two days together

Democracy, Ideology and Process Re-Engineering: Realising the Benefits of e-Government in Singapore

The re-engineering of governmental processes is a necessary condition for the realisation of the benefits of e-government. Several obstacles to such re-engineering exist. These include: (1) information processing thrives on transparency and amalgamation of data, whilst governments are constrained by principles of privacy and data separation; (2) top-down re-engineering may be resisted effectively from the bottom up. This paper analyses these obstacles in the way of re-engineering in Singapore – a democratic one-party state where legislative and executive power lies with the People’s Action Party – and considers how that hegemony has aided the development of e-government

A Novel Framework for Big Data Security Infrastructure Components

Big data encompasses enormous data and management of huge data collected from various sources like online social media contents, log files, sensor records, surveys and online transactions. It is essential to provide new security models, concerns and efficient security designs and approaches for confronting security and privacy aspects of the same. This paper intends to provide initial analysis of the security challenges in Big Data. The paper introduces the basic concepts of Big Data and its enormous growth rate in terms of pita and zettabytes. A model framework for Big Data Infrastructure Security Components Framework (BDAF) is proposed that includes components like Security Life Cycle, Fine-grained data-centric access control policies, the Dynamic Infrastructure Trust Bootstrap Protocol (DITBP). The framework allows deploying trusted remote virtualised data processing environment and federated access control and identity management

Knowledge Management in the Fourth Industrial Revolution: Mapping the Literature and Scoping Future Avenues

Due to increased competitive pressure, modern organizations tend to rely on knowledge and its exploitation to sustain a long-term advantage. This calls for a precise understanding of knowledge management (KM) processes and, specifically, how knowledge is created, shared/transferred, acquired, stored/retrieved, and applied throughout an organizational system. However, since the beginning of the new millennium, such KM processes have been deeply affected and molded by the advent of the fourth industrial revolution, also called Industry 4.0, which involves the interconnectedness of machines and their ability to learn and share data autonomously. For this reason, the present study investigates the intellectual structure and trends of KM in Industry 4.0. Bibliometric analysis and a systematic literature review are conducted on a total of 90 relevant articles. The results reveal 6 clusters of keywords, subsequently explored via a systematic literature review to identify potential stream of this emergent field and future research avenues capable of producing meaningful advances in managerial knowledge of Industry 4.0 and its consequences