基于复杂网络的新产品赠样目标优化策略

Strategies of Optimizing Sampling Targets for New Product Based on Complex Networks

提出把采用网络中起Hub作用的主体做为赠样目标的Hub赠样策略,并运用复杂网络方法研究了该策略的效果和实施环境对效果的影响.结果表明,与随机选取赠样目标相比,运用Hub策略选取赠样目标明显提高了新产品市场份额.Hub赠样策略实施环境对该策略的效果有较大影响,具体表现为:替代市场比创新市场更适合运用该策略;采用网络异构程度中等时运用该策略效果最好;赠样比例较低时运用Hub赠样策略效果更好.

Sampling is one of the most common promotion tools and which can increase short-term sales and longterm market share. It is necessary to optimize targets because sampling of new products is very expensive. In this paper, we present an approach-Hub Sampling Strategy to choose sampling targets. The proposed strategy means that we should target hub nodes in adoption networks. Then we have studied the effects of Hub Sampling Strategy and how the implementation contexts affect the improvement effects by applying the method of complex networks. Our results show that applying Hub Sampling Strategy can improve the market share evidently compared with sampling randomly. Furthermore, the implementation contexts of that strategy have moderated the improvement effects. Specifically, the Replacing Market is more fitting to apply the strategy than Original Market; the improvement effects maximize when the adoption network is in middling heterogeneity; and the improvement effects are better when the rate of sampling is lower. Our research results are helpful for mangers to develop more effective sampling strategy for the diffusion of a new product.