社交网络情境下基于同侪影响的产品线规划研究

依托社交网络优化产品线是实现“匹配消费者需求带动产品设计-制造-营销全流程协调发展”的重要途径，尽管已经引起实业界的重点关注，相应的学术研究却十分匮乏。鉴于此，本文基于同侪影响理论与前景理论，结合社交网络情境下消费者的产品需求、偏好及决策，构建涵盖产品线营销层面和设计层面的双层规划模型；然后结合智能手机产品线实例，运用嵌套灰狼算法对该双层规划模型进行求解验证。本研究旨在提出社交网络与产品线规划之间耦合作用的联合优化框架，为面向社交网络的产品线规划提供理论依据。

Research on Product Line Planning Considering Peer Influence in Social Network Context

Under the personalized and diversified consumption trend, product line planning is an important way to meet consumer needs. However, in the traditional business environment, manufacturing companies lack appropriate “channels” to grasp the degree of consumer preference for various attributes of products, and they have a vague understanding of consumers’ product needs. With the widespread use of social networks, an opportunity is provided to solve the dilemma that consumers’ needs are difficult to identify. The reason is that it is possible to observe consumer demand for products by mining consumer browsing records, product reviews and other information in social networks. But it is a pity that although it has attracted the attention of the industry, the corresponding academic research is very scarce. In view of this, a master-slave joint optimization model (two-level programming model) covering the marketing and design levels is constructed by using Stackelberg game theory, prospect theory, and peer influence theory in the context of social networks. Among them, maximizing the number of consumers is regarded as the goal of marketing (master) by adjusting product attributes and attribute levels, and minimizing manufacturing costs is regarded as the goal of designing (slave) by adjusting product attributes and design parameter levels. Then, with the help of an example of smart phone product line planning, the nested gray wolf algorithm is used to numerically analyze the two-level planning model. And based on the results of numerical analysis, it is found that, first, the influence of peers in the context of social networks has positive significance on the number of consumers in the product line and its design and manufacturing costs. It not only contributes to the proliferation of products in social networks, but also contributes to the realization of product line design goals. Second, there is a positive correlation between the number of initial consumers and the number of consumers in the product line, and a negative correlation with manufacturing costs, and it has a “critical value” that can satisfy both the marketing level and the design level optimization goals. The value of this research lies in a joint optimization framework that couples social networks and product line planning is proposed. It not only helps to bridge the gap between engineering design and marketing, but also helps to solve the problem that consumer needs are difficult to identify in the traditional business environment. Of course, it provides a theoretical basis for product line planning for social networks.