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A Morphology-Driven Method for Measuring Technology Complementarity: Empirical Study Involving Alzheimer's Disease Cover

A Morphology-Driven Method for Measuring Technology Complementarity: Empirical Study Involving Alzheimer's Disease

Journal of Data and Information Science
Volume 7 (2022): Issue 3 (August 2022)
By: Xuefeng Wang,  Rongrong Li,  Yuqin Liu and  Ming Lei  
Open Access
|Aug 2022

Authors

Xuefeng Wang

wxf5122@bit.edu.cn

School of Management & Economics, Beijing Institute of Technology, Beijing, China

Rongrong Li

lirr@upc.edu.cn

School of Economics and Management, China University of Petroleum (East China), Qingdao, China
School of Management & Economics, Beijing Institute of Technology, Beijing, China

Yuqin Liu

School of Journalism and Publication, Beijing Institute of Graphic Communication, Daxing District, China

Ming Lei

School of Management & Economics, Beijing Institute of Technology, Beijing, China
DOI: https://doi.org/10.2478/jdis-2022-0017 | Journal eISSN: 2543-683X | Journal ISSN: 2096-157X
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Language: English
Page range: 20 - 48
Submitted on: Feb 18, 2022
Accepted on: Jun 2, 2022
Published on: Aug 12, 2022
Published by: Chinese Academy of Sciences, National Science Library
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Technology complementarity,
SAO structure,
Technology morphology analysis,
Alzheimer's disease
Related subjects:
Computer sciences,
Information technology,
Project management,
Databases and data mining

© 2022 Xuefeng Wang, Rongrong Li, Yuqin Liu, Ming Lei, published by Chinese Academy of Sciences, National Science Library
This work is licensed under the Creative Commons Attribution 4.0 License.

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