Analyzing Technological Spillover Effects Between Technology Classes: the Case of Korea Technology Finance Corporation
Author(s) -
Sungchul Choi,
Maeng Seok Noh,
Janghyeok Yoon,
Hyunseok Park,
Wonchul Seo
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2017.2788918
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
A technology evaluation system is mandatory to successfully implement a technology-based financial support system. Technology evaluation has generally been relied on the experts' manual work. Various quantitative indicators have been presented to improve the efficiency of this manual work. Among these indicators, the spillover effect is perceived as useful for the disposal of patents of a firm, which received credit guarantee but lost its ability to service its debt. A model for measuring the spillover effects has already been proposed, but it has low reliability. Therefore, this paper presents a systematic approach for measuring technological spillover effects between technology classes. The approach mainly relies on patent data due to its features of the latest reliable sources of technological intelligence. We first extract co-classification information from patent data and generate association rules between technology classes. The relationships represented by the rules, however, can only depict the direct effects. Therefore, we first derive the indirect effects from the direct ones and then integrate both the effects to measure the technological spillover effects. We conduct an empirical study to show the applicability of the presented approach using patents granted in the Korean Intellectual Property Office. We expect that this paper can contribute to establish a quantitative evaluation model to help assess technologies for successful technology-based credit guarantee system. It will improve the reliability of the technology assessment by reducing the variance of the qualitative evaluation results due to the individual differences of the evaluator. Furthermore, it will also enhance the efficiency of evaluation work.
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