Special Issue "Future Intelligent Systems and Networks 2019"

A special issue of Future Internet (ISSN 1999-5903).

Deadline for manuscript submissions: closed (20 February 2019)

Special Issue Editor

Guest Editor
Dr. Carmen de Pablos Heredero

Research Groups Open Innova and Strategor, Department of Business Organization, Head of the Master Degree and Doctoral Program in Business Organization and Master of Management of Strategic Logistic Processes, SAP ERP Faculty of Social Sciences, Universidad Rey Juan Carlos, Office 15, Department Building, 28032 Madrid, Spain
Website | E-Mail
Interests: open innovation; impact of IT and IS over firm’s final performance; relational coordination

Special Issue Information

Dear Colleagues,

The evolution of Internet Systems in the Experience Society has made possible the co-creation of value that can be measured in terms of economic, organizational and social impacts. Firms and Public Institutions have put into action new business models according to new technology options and changed management efforts. Smart cities, smart farms, smart hospitals, smart production and smart education turn into higher levels of quality of life and promote the social and economic sustainability of our society.

Due to the increasing interests of governments, institutions and firms in evolving business models to “smarter environments”, this Special Issue intends to collect the current developments and future directions of “Future Intelligent Systems and Networks”. Hence, we encourage authors to submit original papers related to these fields.

Potential topics include, but are not limited to:

  • Smart cities
  • Smart governments
  • Smarts Institutions
  • Data reuse of information
  • Innovative organizational models
  • The Internet of Things
  • Open innovation practices
  • Business intelligence
  • Social implications of collaborative networks
  • Mobile computing innovative models
  • Co-creation of value with Intelligent Systems and Networks
  • Environmental and social sustainable applications

Prof. Dr. Carmen de Pablos Heredero
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Business intelligence
  • Blockchain technologies
  • Internet of things
  • Reuse of data
  • Smart cities
  • Smart industries
  • Open collaborative models
  • Value co-creation
  • Open innovation
  • Social interaction
  • Environmental sustainability
  • Experience economy
  • Intelligent systems and networks

Published Papers (5 papers)

View options order results:
result details:
Displaying articles 1-5
Export citation of selected articles as:

Research

Jump to: Review

Open AccessArticle
Analysis of the Structure and Use of Digital Resources on the Websites of the Main Football Clubs in Europe
Future Internet 2019, 11(5), 104; https://doi.org/10.3390/fi11050104
Received: 24 January 2019 / Revised: 24 February 2019 / Accepted: 10 April 2019 / Published: 29 April 2019
PDF Full-text (565 KB) | HTML Full-text | XML Full-text
Abstract
Football clubs can be considered global brands, and exactly as any other brand, they need to face the challenge of adapting to digital communications. Nevertheless, communication sciences research in this field is scarce, so the main purpose of this work is to analyze [...] Read more.
Football clubs can be considered global brands, and exactly as any other brand, they need to face the challenge of adapting to digital communications. Nevertheless, communication sciences research in this field is scarce, so the main purpose of this work is to analyze digital communication of the main football clubs in Europe to identify and describe what strategies they follow to make themselves known on the internet and to interact with their users. Specifically, the article studies the characteristics of web pages—considered as the main showcase of a brand/team in the digital environment—of the fifteen best teams in the UEFA ranking to establish what type of structure and what online communication resources they use. Through a descriptive and comparative analysis, the study concludes, among other aspects, that the management of communication is effective, but also warns that none of the analyzed team takes full advantage of the possibilities of interaction with the user offered by the digital scenario. Full article
(This article belongs to the Special Issue Future Intelligent Systems and Networks 2019)
Figures

Figure 1

Open AccessArticle
Tax Fraud Detection through Neural Networks: An Application Using a Sample of Personal Income Taxpayers
Future Internet 2019, 11(4), 86; https://doi.org/10.3390/fi11040086
Received: 27 February 2019 / Revised: 21 March 2019 / Accepted: 26 March 2019 / Published: 30 March 2019
PDF Full-text (1868 KB) | HTML Full-text | XML Full-text
Abstract
The goal of the present research is to contribute to the detection of tax fraud concerning personal income tax returns (IRPF, in Spanish) filed in Spain, through the use of Machine Learning advanced predictive tools, by applying Multilayer Perceptron neural network (MLP) models. [...] Read more.
The goal of the present research is to contribute to the detection of tax fraud concerning personal income tax returns (IRPF, in Spanish) filed in Spain, through the use of Machine Learning advanced predictive tools, by applying Multilayer Perceptron neural network (MLP) models. The possibilities springing from these techniques have been applied to a broad range of personal income return data supplied by the Institute of Fiscal Studies (IEF). The use of the neural networks enabled taxpayer segmentation as well as calculation of the probability concerning an individual taxpayer’s propensity to attempt to evade taxes. The results showed that the selected model has an efficiency rate of 84.3%, implying an improvement in relation to other models utilized in tax fraud detection. The proposal can be generalized to quantify an individual’s propensity to commit fraud with regards to other kinds of taxes. These models will support tax offices to help them arrive at the best decisions regarding action plans to combat tax fraud. Full article
(This article belongs to the Special Issue Future Intelligent Systems and Networks 2019)
Figures

Graphical abstract

Open AccessArticle
Sentiment Analysis Based Requirement Evolution Prediction
Future Internet 2019, 11(2), 52; https://doi.org/10.3390/fi11020052
Received: 12 January 2019 / Revised: 2 February 2019 / Accepted: 11 February 2019 / Published: 21 February 2019
PDF Full-text (796 KB) | HTML Full-text | XML Full-text
Abstract
To facilitate product developers capturing the varying requirements from users to support their feature evolution process, requirements evolution prediction from massive review texts is in fact of great importance. The proposed framework combines a supervised deep learning neural network with an unsupervised hierarchical [...] Read more.
To facilitate product developers capturing the varying requirements from users to support their feature evolution process, requirements evolution prediction from massive review texts is in fact of great importance. The proposed framework combines a supervised deep learning neural network with an unsupervised hierarchical topic model to analyze user reviews automatically for product feature requirements evolution prediction. The approach is to discover hierarchical product feature requirements from the hierarchical topic model and to identify their sentiment by the Long Short-term Memory (LSTM) with word embedding, which not only models hierarchical product requirement features from general to specific, but also identifies sentiment orientation to better correspond to the different hierarchies of product features. The evaluation and experimental results show that the proposed approach is effective and feasible. Full article
(This article belongs to the Special Issue Future Intelligent Systems and Networks 2019)
Figures

Figure 1

Open AccessArticle
Audio-Visual Genres and Polymediation in Successful Spanish YouTubers
Future Internet 2019, 11(2), 40; https://doi.org/10.3390/fi11020040
Received: 8 January 2019 / Revised: 1 February 2019 / Accepted: 2 February 2019 / Published: 11 February 2019
PDF Full-text (11664 KB) | HTML Full-text | XML Full-text
Abstract
This paper is part of broader research entitled “Analysis of the YouTuber Phenomenon in Spain: An Exploration to Identify the Vectors of Change in the Audio-Visual Market”. My main objective was to determine the predominant audio-visual genres among the 10 most influential Spanish [...] Read more.
This paper is part of broader research entitled “Analysis of the YouTuber Phenomenon in Spain: An Exploration to Identify the Vectors of Change in the Audio-Visual Market”. My main objective was to determine the predominant audio-visual genres among the 10 most influential Spanish YouTubers in 2018. Using a quantitative extrapolation method, I extracted these data from SocialBlade, an independent website, whose main objective is to track YouTube statistics. Other secondary objectives in this research were to analyze: (1) Gender visualization, (2) the originality of these YouTube audio-visual genres with respect to others, and (3) to answer the question as to whether YouTube channels form a new audio-visual genre. I quantitatively analyzed these data to determine how these genres are influenced by the presence of polymediation as an integrated communicative environment working in relational terms with other media. My conclusion is that we can talk about a new audio-visual genre. When connected with polymediation, this may present an opportunity that has not yet been fully exploited by successful Spanish YouTubers. Full article
(This article belongs to the Special Issue Future Intelligent Systems and Networks 2019)
Figures

Figure 1

Review

Jump to: Research

Open AccessFeature PaperReview
Open Data for Open Innovation: An Analysis of Literature Characteristics
Future Internet 2019, 11(3), 77; https://doi.org/10.3390/fi11030077
Received: 19 February 2019 / Revised: 14 March 2019 / Accepted: 20 March 2019 / Published: 24 March 2019
Cited by 1 | PDF Full-text (982 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we review some characteristics of the literature that studies the uses and applications of open data for open innovation. Three research questions are proposed about both topics: (1) What journals, conferences and authors have published papers about the use of [...] Read more.
In this paper, we review some characteristics of the literature that studies the uses and applications of open data for open innovation. Three research questions are proposed about both topics: (1) What journals, conferences and authors have published papers about the use of open data for open innovation? (2) What knowledge areas have been analysed in research on open data for open innovation? and (3) What are the methodological characteristics of the papers on open data for open innovation? To answer the first question, we use a descriptive analysis to identify the relevant journals and authors. To address the second question, we identify the knowledge areas of the studies about open data for open innovation. Finally, we analyse the methodological characteristics of the literature (type of study, analytical techniques, sources of information and geographical area). Our results show that the applications of open data for open innovation are interesting but their multidisciplinary nature makes the context complex and diverse, opening up many future avenues for research. To develop a future research agenda, we propose a theoretical model and some research questions to analyse the open data impact process for open innovation. Full article
(This article belongs to the Special Issue Future Intelligent Systems and Networks 2019)
Figures

Figure 1

Future Internet EISSN 1999-5903 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top