A sales strategy optimization model on online group buying in a fuzzy dual channel supply chain using a game theoretic approach

Several factors affect customers' decisions regarding service selection. Two of the essential factors are the price and the service quality. The seller's credibility is also among the influential factors in selecting a service that is reinforced by advertising. The emergence of the Internet has led to increasing attention by sellers to advertising through online group buying (OGB) platforms. Sellers aim to attract new customers by offering discounts on OGB platforms. In this paper, the seller can sell its service through offline and online channels during two current and future courses. The aim is to determine the optimal strategy for the seller when deciding to join the OGB platform. All parameters of the problem are determined as fuzzy variables. Accordingly, this paper develops a fuzzy mathematical model to simultaneously determine price, service quality, and advertising level in a dual channel supply chain. A cooperative game between the seller and the OGB platform is developed under different refunding and revenue sharing scenarios for the centralized model. The optimal solutions of the problem are then defined using the game and fuzzy sets theories for each scenario. A numerical example is presented to indicate the effectiveness of the theoretical results of the models and developing management insights. In addition, sensitivity analyses also provide the effect of changes in essential parameters on the seller’s decisions.