Escaping excess inertia by the adoption of transitional technology : implications for the electric vehicle adoption policy과도기 기술 도입을 통한 기술 관성 극복 방안 : 전기차 도입 정책을 중심으로

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We build the network effect model treats the context in which the environmentally clean technology cannot be adopted by consumers due to excess inertia because of incompatibility to the installed complementary infrastructure of the incumbent dirty technology, and analyze the optimal subsidy policy of government on the adoption of a transitional technology to induce the entrant clean technology ultimately until the clean technology escapes from excess inertia. We introduce two extreme Nash equilibria in which the consumers expect the consistency of government electric vehicle policy or not, considering the choices of future consumers, and we also show different decision dynamics for each equilibrium in the model. We prove that if the government intervenes to the market, every consumer believes the consistency of the policy and expects that every future consumer also joins to the entrant technology network in unique subgame-perfect Nash equilibrium. With the subgame-perfect Nash equilibrium, we discuss the warranty of government intervention and optimal choice of the government on the amount of subsidy and duration of transitional technology adoption, considering the net present value life time utility of consumers and environmental damage. Finally, we highlight the role of the transitional technology in excess inertia context.
Advisors
Lee, Chang-Yangresearcher이창양researcher
Description
한국과학기술원 :경영공학부,
Publisher
한국과학기술원
Issue Date
2018
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 경영공학부, 2018.2,[iii, 23 p. :]

Keywords

transitional technology▼aexcess inertia▼atechnology adoption▼anetwork effect▼aenvironmental damage▼aelectric vehicle market; 과도기 기술▼a기술 관성▼a기술 도입▼a네트워크 효과▼a환경 오염▼a전기차 시장

URI
http://hdl.handle.net/10203/265656
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=842568&flag=dissertation
Appears in Collection
MT-Theses_Master(석사논문)
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