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

Xuefeng Wang, Rongrong Li, Yuqin Liu, Ming Lei
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Abstract

Abstract 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.
测量技术互补性的形态学驱动方法:阿尔茨海默病的实证研究
摘要目的衡量不同机构之间的确切技术互补性是获得研发合作互补技术资源的必要条件。设计/方法论/方法本研究以医学领域为例,构建了一种形态学驱动的技术互补性测量方法。首先,我们基于元词库计算主体(S和S)和动作对象(AO和AO)之间的语义相似性,基于语义相似性矩阵形成S和AO的聚类。第二,基于S和AO聚类识别关键技术问题和方法。第三,利用形态学分析构建了一个多维度的技术形态矩阵,并根据不同机构对应的关键技术问题与方法,在矩阵中填充主体-行动对象(SAO)结构。最后,利用技术形态矩阵来衡量基于SAO的不同机构之间的技术互补性。研究结果基于SAO的改进技术互补方法是对传统IPC方法的补充和细化。研究局限性在未来的研究中,我们将重新处理和识别不在技术形态矩阵中的SAO结构,并找到其他方法来表征关键技术问题和方法。此外,我们还将添加所提出的方法与传统的、最常用的基于产业链和行业代码的互补性测量方法的比较。实际意义本研究以医学领域为例。测量技术互补性的形态学驱动方法可以迁移并应用于任何给定的领域。原创性/价值从技术资源互补的角度,本研究开发并测试了一种更准确的形态学驱动的技术互补性测量方法。
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