Digital Economy. Emerging Technologies and Business Innovation : Second International Conference, ICDEc 2017, Sidi Bou Said, Tunisia, May 4-6, 2017, Proceedings /
Corporate Author: | |
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Other Authors: | , , , , |
Format: | eBook |
Language: | English |
Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2017.
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Edition: | 1st ed. 2017. |
Series: | Lecture Notes in Business Information Processing,
290 |
Subjects: |
Table of Contents:
- Digital Marketing
- Online Celebrities' Endorsement and Consumers' Adoption and Dissemination of Information
- What "Uses and Gratifications' Theory can tell us about using Professional Networking Sites (e.g LinkedIn, Viadeo, Xing, SkilledAfricans, Plaxo...)
- Intention of Adoption of Mobile Commerce from Consumer Perspective
- Not Always a Co-Creation: Exploratory Study of Causes, Emotions and Practices of the Value Co-Destruction in Virtual Communities
- Empirical Study of Algerian Web Users' Behavior. The case of Ouedkniss.com
- Capturing Leading Factors Contributing To Consumer Engagement In Online Co-Design Platform Of Olive Oil Packaging: A Focus Group Study And A Research Model Proposal
- Digital Economy and e-Learning
- Knowledge Transfer Through e-Learning: Case of Tunisian Post
- Modeling of a Collaborative Learning Process with Business Process Model Notation
- Intermediation and Decision Support System for the Management of Unemployment: the Simulator of Duration
- Online Project Management and PHP7 Application: a real case study
- Data Science and Security
- Data Stream Mining Based-Outlier Prediction for Cloud Computing
- Overlapping Community Detection for Social Networks
- New Overlap Measure for the Validation of Non-Disjoint Partitioning
- Uniformly Spread Embedding based Steganography
- Uncertainty in Web Data
- First steps towards an electronic meta-journal platform based on crowdsourcing
- Skyline Operator over Combined Reviews of Tripadvisor Travelers under the Belief Functions Theory
- An adaptive approach of label aggregation using a belief function framework
- Assessing Items Reliability for Collaborative Filtering within the Belief Function Framework.