Special Issue "Information Management in Information Age"

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Systems".

Deadline for manuscript submissions: 15 January 2019

Special Issue Editors

Guest Editor
Dr. Antonín Pavlicek

Faculty of Informatics and Statistics, University of Economics, Prague, Czech Republic
Website | E-Mail
Interests: social media; information management; information security
Guest Editor
Prof. Petr Doucek

Faculty of Informatics and Statistics, University of Economics, Prague, Czech Republic
Website | E-Mail
Interests: information management; cyber security

Special Issue Information

Dear Colleagues,

Modern approaches to information management include all organizational activities related to information (the acquisition of information, the custodianship and the distribution of that information, and its ultimate disposition through archiving or deletion). Such approaches are closely related to, and often overlap with, the management of data, systems, modern information technologies, social media, and – where the availability of information is critical to organizational success – strategy. This broad view of the realm of information management reflects the broad scope of our Special Issue.

This Special Issue invites papers covering a wide range of topics, ranging from information management to Smart Systems.

We will accept papers for peer review in the following areas of interest:

  • Digital Economy and Industry 4.0
  • Innovation, new business models and strategies
  • Crisis management
  • Social media
  • e-Health
  • Digital single market innovation
  • Cyber security
  • Performance management
  • Smart Systems everywhere—intelligence, autonomy, technology, and society
  • Leadership development, innovation behavior, and creativity

We accept both research papers and case studies based on robust and strict methodology with a substantial proportion of original (not published elsewhere) content.

Dr. Antonín Pavlicek
Prof. Petr Doucek
Guest Editors

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. Information 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 850 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

  • information management
  • digital economy and innovations
  • crisis management
  • social media
  • e-health
  • cyber security
  • Smart Systems—intelligence, autonomy, technology, and society

Published Papers (2 papers)

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Research

Open AccessArticle Big Data Analysis to Observe Check-in Behavior Using Location-Based Social Media Data
Information 2018, 9(10), 257; https://doi.org/10.3390/info9100257
Received: 12 September 2018 / Revised: 10 October 2018 / Accepted: 11 October 2018 / Published: 20 October 2018
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Abstract
With rapid advancement in location-based services (LBS), their acquisition has become a powerful tool to link people with similar interests across long distances, as well as connecting family and friends. To observe human behavior towards using social media, it is essential to understand
[...] Read more.
With rapid advancement in location-based services (LBS), their acquisition has become a powerful tool to link people with similar interests across long distances, as well as connecting family and friends. To observe human behavior towards using social media, it is essential to understand and measure the check-in behavior towards a location-based social network (LBSN). This check-in phenomenon of sharing location, activities, and time by users has encouraged this research on the frequency of using an LBSN. In this paper, we investigate the check-in behavior of several million individuals, for whom we observe the gender and their frequency of using Chinese microblog Sina Weibo (referred as “Weibo”) over a period in Shanghai, China. To produce a smooth density surface of check-ins, we analyze the overall spatial patterns by using the kernel density estimation (KDE) by using ArcGIS. Furthermore, our results reveal that female users are more inclined towards using social media, and a difference in check-in behavior during weekday and weekend is also observed. From the results, LBSN data seems to be a complement to traditional methods (i.e., survey, census) and is used to study gender-based check-in behavior. Full article
(This article belongs to the Special Issue Information Management in Information Age)
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Open AccessArticle Predictors of Chinese Users’ Location Disclosure Behavior: An Empirical Study on WeChat
Information 2018, 9(9), 219; https://doi.org/10.3390/info9090219
Received: 12 August 2018 / Accepted: 28 August 2018 / Published: 30 August 2018
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Abstract
Location disclosure behavior on social network sites (SNS) has developed rapidly. However, the influencing factors have not been adequately studied. Based on social cognitive theory and the concept of face, this study developed a research model to explain the factors with uniquely Chinese
[...] Read more.
Location disclosure behavior on social network sites (SNS) has developed rapidly. However, the influencing factors have not been adequately studied. Based on social cognitive theory and the concept of face, this study developed a research model to explain the factors with uniquely Chinese characteristics that predict WeChat users’ location disclosure. Using survey data collected from WeChat users in China (N = 545), the model is tested by a structural equation modeling (SEM). The results show that a desire to gain face, a fear of losing face, social norms, trust in SNS members and trust in an SNS provider positively influence WeChat users’ intention to disclose location information. Moreover, trust in SNS members can also boost trust in an SNS provider. Finally, both theoretical contributions and practical implications are discussed. Full article
(This article belongs to the Special Issue Information Management in Information Age)
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