DEVELOPMENT OF MANAGENMENT STRATEGY THROUGH ANALYSIS OF ADOPTION INTENTION AND INFLUENCE FACTORS OF AUTONOMOUS VEHICLES CENTERING ON VALUE-BASED ADOPTION MODELS

Abstract

This study was conducted to derive business strategies to help commercialize and
popularize autonomous vehicles by exploring and demonstrating factors that affect the
value and acceptance of autonomous vehicles perceived by potential buyers and future
users of autonomous vehicles, one of the state-of-the-art new technologies of the Fourth
Industrial Revolution. Under the consciousness and goals of these problems, this study
verified the effects of 'perceived benefits', 'perceived sacrifice', 'perceived bias,' and 'the
perceived threat' on 'perceived value' and 'adoption intent' through a survey and statistical
analysis of general users, referring to the 'value-based adoption model', a representative
analytic theory of users' perceived value for new technology, intent of acceptance, and
intent for continued use.
To this end, the study conducted a survey of 602 users interested in autonomous
vehicles, and the collected survey data was conducted using the SPSS States 21.0
package program to analyze the frequency of demographic characteristics, analysis of
technical statistics of sub-factors and detailed metrics that make up independent and
dependent variables, analysis of validity and reliability, and simple and multiple
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regression between independent and dependent variables. The results of the analysis and
verification of this study are summarized as follows.
By demonstrating in various ways that individual users' perceived benefits and
optimistic prejudices against autonomous vehicles have a positive impact on perceived
value and adoption intention, while perceived sacrifices and perceived threats have
negative effects, this study derived and suggested a user-centered business strategy that
can be applied and applied as necessary for the commercialization and popularization of
autonomous vehicles. It is hoped that the results and conclusions of this study will be
used as valid theoretical and practical guidelines and basic references to help the mid- to
long-term development of autonomous vehicles.