Bilevel Game-Theoretic Optimization for Product Adoption Maximization Incorporating Social Network Effects

Viral product design involves sophisticated interactions between product portfolio planning and viral marketing. However, social network effects are mainly considered in marketing-related activities, and there is still limited investigation of the interplay between product design and viral marketing. In the context of social networks, it is important to jointly leverage both viral product attributes and viral influence attributes for product adoption maximization and product line performance optimization. In order to deal with the joint optimization problem, this paper presents a systematic formulation of a bilevel decision-making strategy for viral product design based on the Stackelberg game theory. The product adoption maximization problem with viral influence and product attributes is modeled as the leader and the product portfolio optimization problem with product attributes is modeled as the follower. The interaction and coupling of these two optimization problems are addressed with a coordinate-wise optimization strategy, in which adoption maximization is tackled with an improved greedy algorithm and a hybrid Taguchi genetic algorithm. A case study of Kindle Fire HD tablets demonstrates the feasibility and potential of the bilevel decision-making strategy for viral product design, which is advantageous over the existing viral marketing methods that only consider viral influence attributes.