Data-driven Decision Making – Theory, Methods, and Applications

Data-driven decision making approaches have been widely used in emergency response, medicine, manufacturing, renewable energy, and so on. Businesses generally use a wide range of tools to get useful information from big data, and to present it in ways that back up decisions. They form a hot research topic owing to their importance and effectiveness in addressing aspects of uncertainty and incompleteness of data. Moreover, in some cases the incomplete information about the consequences of the alternatives can be tackled by means of the theory of Soft Computing (SC), Data Mining (DM) and Artificial Intelligence (AI). Now and in the future, data-driven decision making under uncertainty and incompleteness would be a quite promising research line representing a high quality breakthrough in this topic.

The objective of this special issue is to explore latest up-to-date methods of SC, DM and AI, and their applications in data-driven decision making under uncertainty and incompleteness environment. Both theoretical and applied results with applications are sought for. It offers a concentrative venue for researchers to make rapid exchange of ideas and original research findings in data-driven decision making problems. In particular, new interdisciplinary approaches in SC, DM and AI for decision making theories and applications, or strong conceptual foundation in newly evolving topics are especially welcome.

TOPICS OF INTEREST FOR THE SPECIAL ISSUE

We invite researchers and experts worldwide to submit high-quality original research papers and critical survey articles on the following potential topics and their applications, but are not limited to:

• Big (small) data analysis for decision making
• Soft Computing and its applications in decision making
• Nature-inspired optimization for decision making
• Fuzzy Multiple Criteria/Objective Decision Making
• Consensus and cooperation for decision making
• Rough Sets and its applications
• Fuzzy set qualitative comparative analysis
• Decision making with incomplete / uncertain systems
• Other DM, AI for decision support/making

SUBMISION GUIDELINES:

Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by, other journal.

All papers will be reviewed following standard reviewing procedures for the Journal.

Prospective authors must prepare their submission in accordance with the guideline specified in the \”instructions for Authors\” of the Journal.

IMPORTANT: Please choose \”VSI: Data-driven DM\” when specifying the Article Type.

IMPORTANT DATES:

Virtual Special Issue Start: March 15, 2019

Final Deadline for Submissions: August 15, 2019

Review notification about 10 weeks after submission.

Up to 2 rounds of revisions.

Publication immediately after receipt of accepted final in 2019.

GUEST EDITORS

Ching-Ter Chang. Chang Gung University, Tao-Yuan, Taiwan, R.O.C. chingter@mail.cgu.edu.tw

Tzu-Liang (Bill) Tseng, University of Texas at El Paso, El Paso, U.S.A.

btseng@utep.edu

Chun-Che Huang. National Chi Nan University, Pu-Li, Taiwan, R.O.C.

cchuang@ncnu.edu.tw