Journal of Data and Information Science ›› 2022, Vol. 7 ›› Issue (3): 20-48.doi: 10.2478/jdis-2022-0017

• Research Paper • Previous Articles     Next Articles

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

Xuefeng Wang(), Rongrong Li2,(), Yuqin Liu3, Ming Lei1   

  1. 1School of Management & Economics, Beijing Institute of Technology, Haidian District, Beijing 100081, China
    2School of Economics and Management, China University of Petroleum (East China), Qingdao, Shandong 266580, China
    3School of Journalism and Publication, Beijing Institute of Graphic Communication, Daxing District,Beijing 102600, China
  • Received:2022-02-18 Revised:2022-06-01 Accepted:2022-06-02 Online:2022-07-20 Published:2022-07-29
  • Contact: Xuefeng Wang,Rongrong Li;


Purpose: Measuring the exact technology complementarity between different institutions is necessary to obtain complementary technology resources for R&D cooperation.
Design/methodology/approach: This study constructs a morphology-driven method for measuring technology complementarity, taking medical field as an example. First, we calculate semantic similarities between subjects (S and S) and action-objects (AO and AO) based on the Metathesaurus, forming clusters of S and AO based on a semantic similarity matrix. Second, we identify key technology issues and methods based on clusters of S and AO. Third, a technology morphology matrix of several dimensions is constructed using morphology analysis, and the matrix is filled with subjects -action-objects (SAO) structures according to corresponding key technology issues and methods for different institutions. Finally, the technology morphology matrix is used to measure the technology complementarity between different institutions based on SAO.
Findings: The improved technology complementarity method based on SAO is more of a supplementary and refined framework for the traditional IPC method.
Research limitations: In future studies we will reprocess and identify the SAO structures which were not in the technology morphology matrix, and find other methods to characterize key technical issues and methods. Furthermore, we will add the comparison between proposed method and traditional and mostly used complementarity measurement method based on industry chain and industry code.
Practical implications: This study takes medical field as an example. The morphology-driven method for measuring technology complementarity can be migrated and applied for any given field.
Originality/value: From the perspective of complementary technology resources, this study develops and tests a more accurate morphology-driven method for technology complementarity measurement.

Key words: Technology complementarity, SAO structure, Technology morphology analysis, Alzheimer's disease