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构建实证数据驱动下的多智能体计算实验平台,用于研究从在线到移动环境下消费转移行为的动态演化机理。实验结果表明,所收集的实验数据与经典扩散方程拟合程度高,说明计算模型能反映真实系统的演化过程。广告在产品/服务的市场投放初期效果明显,随着广告强度的增加,消费接受效果并非明显。当市场中出现高消费休眠时,即便采用高唤醒策略,其移动服务消费接受水平也低。当休眠率远大于唤醒率时,市场成熟期后,移动产品/服务接受量下降,而在线产品/服务接受量回升。当唤醒率远大于休眠率时,移动产品/服务接受量水平可达到最大,并维持稳定。该计算模型和实验结果能为管理者提供电子商务行为决策方面的支持。
A multi-agent computing experiment platform driven by empirical data is constructed to study the dynamic evolution mechanism of consumer-transfer behavior from online to mobile environment. The experimental results show that the collected experimental data fit well to the classical diffusion equation, indicating that the calculation model can reflect the evolution of the real system. Advertising products and services in the market early delivery effect is obvious, with the increase in advertising intensity, consumer acceptance effect is not obvious. When high-spending hibernation occurs in the market, the acceptance of mobile services is low even with a high wake-up strategy. When the hibernation rate is far greater than the wake-up rate, mobile product / service acceptance declines while online product / service acceptance picks up after the market matures. When the awakening rate is far greater than the dormancy rate, the mobile product / service acceptance level can reach the maximum and remain stable. This computational model and experimental results support managers in decision-making on e-commerce behavior.