在线到移动环境下消费接受行为的演化研究:基于计算实验方法

Abstract

Abstract: Computational experiment platform is built based on empirical data driven multi-Agent to research dynamic evolutionary process of consumer adoption from online to mobile environment. The experimental results show that better fineness are existing between experimental data and classic diffusion equation, which indicates the experimental model can be used to simulate real behavior evolutionary process. Brand have significant effect on consumer adoption at the primacy stage, with the increased of advertising intensity, the effect is not evident. When market is with high level of consumption dormancy, even using high-wake strategy, its mobile services is also low levels of consumer adoption. When dormancy rate is much larger than wake rate, the adoption mobile products/services will decline after the stage of market maturity, but adoption of online products/services will recovery. When wake rate is much larger than dormancy rate, adoption of mobile products/services can reach maximum level, and then remain stability. The provided computational models and results will give some reference for decision-making and technical support to regulators.

Key words: computational experiment, multi-agent, consumption transition behavior, evolution

CLC Number:

C931

JIANG Guo-yin, MA Fei-cheng, LIU Xing-jun. Research on Consumption Acceptance Evolutionary from Online to Mobile Environment: Based on Computational Experiment[J]. Chinese Journal of Management Science, 2014, 22(11): 97-104.

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Research on Consumption Acceptance Evolutionary from Online to Mobile Environment: Based on Computational Experiment

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