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Conceptual paper | Open Access

Crowd science and engineering: concept and research framework

Yueting Chai1( ), Chunyan Miao2, Baowen Sun3, Yongqing Zheng4, Qingzhong Li4
National Engineering Laboratory for E-commerce Technology, Tsinghua University, Beijing, China
Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly, Nanyang Technological University, Singapore, Singapore and School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
Central University of Finance and Economics, Beijing, China
Shangdong University, Jinan, China
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Abstract

Purpose

The synthetic application and interaction of/between the internet, Internet of Things, cloud computing, big data, Industry 4.0 and other new patterns and new technologies shall breed future Web-based industrial operation system and social operation management patterns, manifesting as a crowd cyber eco-system composed of multiple interconnected intelligent agents (enterprises, individuals and governmental agencies) and its dynamic behaviors. This paper aims to explore the basic principles and laws of such a system and its behavior.

Design/methodology/approach

The authors propose the concepts of crowd science and engineering (CSE) and expound its main content, thus forming a research framework of theories and methodologies of crowd science.

Findings

CSE is expected to substantially promote the formation and development of crowd science and thus lay a foundation for the advancement of Web-based industrial operation system and social operation management patterns.

Originality/value

This paper is the first one to propose the concepts of CSE, which lights the beacon for the future research in this area.

Keywords

TransactionIntelligenceCrowd scienceStabilityEcology and evolutionModelling and simulation
International Journal of Crowd Science
Volume 1 Issue 1,
March 2017
Pages 2-8
DOI: 10.1108/IJCS-01-2017-0004
Cite this article:
Chai Y, Miao C, Sun B, et al. Crowd science and engineering: concept and research framework. International Journal of Crowd Science, 2017, 1(1): 2-8. https://doi.org/10.1108/IJCS-01-2017-0004

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Received: 06 December 2016
Revised: 10 January 2017
Accepted: 13 January 2017
Published: 06 March 2017
© The author(s)

Yueting Chai, Chunyan Miao, Baowen Sun, Yongqing Zheng and Qingzhong Li. Published in International Journal of Crowd Science. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
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