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http://dx.doi.org/10.3745/KTSDE.2021.10.12.329

A Study on The Effect of Perceived Value and Innovation Resistance Factors on Adoption Intention of Artificial Intelligence Platform: Focused on Drug Discovery Fields  

Kim, Yeongdae (숭실대학교 IT정책경영학과)
Kim, Ji-Young (숭실대학교 IT정책경영학과)
Jeong, Wonkyung (숭실대학교 IT정책경영학과)
Shin, Yongtae (숭실대학교 컴퓨터공학부)
Publication Information
KIPS Transactions on Computer and Communication Systems / v.10, no.12, 2021 , pp. 329-342 More about this Journal
Abstract
The pharmaceutical industry is experiencing a productivity crisis with a low probability of success despite a long period of time and enormous cost. As a strategy to solve the productivity crisis, the use cases of Artificial Intelligence(AI) and Bigdata are increasing worldwide and tangible results are coming out. However, domestic pharmaceutical companies are taking a wait-and-see attitude to adopt AI platform for drug research. This study proposed a research model that combines the Value-based Adoption Model and the Innovation Resistance Model to empirically study the effect of value perception and resistance factors on adopting AI Platform. As a result of empirical verification, usefulness, knowledge richness, complexity, and algorithmic opacity were found to have a significant effect on perceived values. And, usefulness, knowledge richness, algorithmic opacity, trialability, technology support infrastructure were found to have a significant effect on the innovation resistance.
Keywords
Artificial Intelligence; Drug Discovery; Perceived Value; Innovation Resistance; Value Based Adoption Model;
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