2019 CSAMSE Conference Call for Papers on Special Issue
Data Science and Scientific Management
Journal of Management Science and Engineering
Special issue on Data Science and Scientific Management
Guest Editors (in alphabetic order)Fangruo Chen, Shanghai Jiaotong University Michael Pinedo, New York University Jeannette Song, Duke University
Data science as well as data analytics, derived from the application of Internet of Things, Cloud Computing, Artificial Intelligence, has a substantial impact on the acquisition of enterprise resources, production/operations, logistics, transaction, product development and financing activities. It can greatly improve the efficiency of commodities production and circulation, and profoundly change the mode of production and consumption of social and economic systems worldwide, which has attracted widespread attention of both industry and academia.
This Special Issue, therefore jointly launched by NSFC and CSAMSE through the platform of 2019 CSAMSE conference, seeks to publish high-quality scholarly papers that focus on original works or comprehensive reviews with relevancy of Data Science and Scientific Management in the fields of management science and engineering. Some topics include, but are not limited to, the following:
How to make a submission
Please submit your paper via the following website: https://mc03.manuscriptcentral.com/jmse
In the process of submission, please select type “Special Issue” and special issue “Special Issue on Data Science and Scientific Management_2019CSAMSE.”
Publication schedule
Manuscript submission deadline: June 30, 2019 Deadline for final decision notification: Oct. 20, 2019 Tentative date for publication: Dec. 2019
About JMSE
Journal of Management Science and Engineering (http://engine.scichina.com/publisher/CSPM/journal/JMSE) is a peer-reviewed open access scholarly journal on all aspects of management science and engineering published quarterly online. JMSE is sponsored by National Natural Science Foundation of China (NSFC), Science Press, Tianjin University and CSAMSE. JMSE collaborates with Elsevier through KeAi. All published papers are available on ScienceDirect.
