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| The Diffusion Characteristics of Intelligent Driving Innovation in China in the Post-Epidemic Period: An In-depth Interview Survey Based on Innovative Diffusion Theory |
| Gao Zejin |
| (School of Journalism and Communication, Tsinghua University, Beijing 100083, China) |
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Abstract Nowadays the issue of innovation and diffusion of intelligent driving technology has attracted wide attention of both academia and industry. As the most important theory and application development direction in the field of artificial intelligence technology innovation, intelligent driving can only maximize its economic or social benefitsthrough effective social diffusion. In China, while the intelligent driving technology innovation is widely spreading in the society, it is confronted with many challenges. At the beginning of 2020, China unfortunately became one of the regions most seriously affected by the COVID-19 epidemic in the world, and many industrial innovation diffusion practices, including intelligent driving technology, were hit hard. Under such circumstances, how has the innovation diffusion practice of intelligent driving in China been affected? How should we do to minimize the negative impact of COVID-19 epidemic and continue to maintain its effective diffusion practice? Both questions are worthy of exploration.#br#In view of this,this study starts from Rogers' framework of innovative diffusion theory. From October 2019 to October 2020, the researchers conducted in-depth interviews with 95 people from 10 intelligent driving enterprises, 10 enterprise customers and 5 government agencies. Through the in-depth interview surveys, the different characteristics presented by the diffusion practice of China's intelligent driving innovation before and after the COVID-19 epidemic are summarized.#br#The main conclusions obtained in this study are as follows. (1) From the perspective of innovation diffusion theory, the five attribute characteristics affecting innovation diffusion are comparative advantage, compatibility, testability, complexity and observability, and they have direct impacts on the efficiency process of innovation diffusion of technology. Among them, comparative advantage, compatibility, testability and observability have positive impacts on the diffusion efficiency process of innovation, while complexity has a negative impact on the diffusion efficiency process of innovation. Although the COVID-19 epidemic eliminates the contradiction between the innovative diffusion sources of intelligent driving and the potential customers on the characteristics of innovation attributes, such as relative advantages, compatibility, trial and observability, the new contradictions focus on the education,training and easier operation requirements for non-professionals. (2) Before the COVID-19 epidemic, the government and potential users of limited scenarios had limited cognitive level of L1-L5 intelligent driving innovation, and there was a cognitive gap between the objective development of technical indicators and the actual needs of the industry, which was mainly reflected in the contradiction around the attribute characteristics of intelligent driving innovation. But COVID-19 epidemic has played an important role in dispelling the cognitive gap between the government and potential users. This makes the intelligent driving innovation persuasion and decision-making process gradually easier and even leapfrog its path. The process of innovative diffusion may directly entry into the implementation stage. (3) With the process change of the diffusion stage of intelligent driven innovation, the bell curve distribution of intelligent driving innovation is shifted. People who were originally more inclined to adopt in the later stage or do not adopt the innovation have changed their attitude towards intelligent driving innovation, showing the characteristics of competing for early adoption. (4) Facing the sudden crisis of COVID-19, Chinese intelligent driving innovation diffusion sources actively sought application opportunities under the epidemic and resumption of work scenarios, targeted development and expansion of product lines, and accelerated iteration and upgrading of technology in practice scenarios to continue its effective diffusion practice.#br# The above research conclusions outline the diffusion practice changes and stress the measures of China's intelligent driving innovation before and after COVID-19 epidemic. In future research, further quantitative research based on the above research conclusions can be conducted to obtain more micro changes in adoption rate.#br#
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Received: 21 July 2021
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