Optimal advertising and pricing strategies for luxury fashion brands with social influences

Abstract

In the fashion industry, it is well-known that social needs play an important role in the purchase of conspicuous products such as high-end fashion labels. In this thesis, motivated by various industrial cases, we analytically study the optimal advertising and pricing decisions for fashion brands in a market consisting of two groups of consumers with opposite social needs for fashion products, namely the Leader Group (LG) and the Follower Group (FG). We consider the situation when the LG consumers have a desire to distinguish themselves from the FG consumers whereas the FG consumers would like to assimilate themselves with the LG consumers. Thus, social influences exist between the two groups of consumers. Based on this market feature, we first develop an optimization model which is original and has not been proposed in the literature before for this problem and we call it the basic model. We explore the solution scheme for identifying the optimal strategy by investigating different tactics. We conduct extensive sensitivity analysis and reveal that the optimal strategies follow different scenarios and it can be optimal for a brand of conspicuous product to (1) advertise to only one group while sell to the whole market, (2) advertise and sell to FG only, or (3) advertise and sell to LG only, depending on the situation. We also derive the analytical conditions for the existence of the Veblen effect, which refers to the phenomenon that a higher selling price can lead to a higher demand for a specific consumer group. After that, we extend the model to the case when there are linear-loss penalties owing to insufficient resource allocation to each consumer group. This extension leads to a much more complicated model with a lot more possible scenarios. Similar to the basic model, we derive the detailed mechanism to solve this extended model and conduct in-depth analysis. Important new insights are then generated. This thesis contributes to the literature not only by developing innovative optimization models for the research problem, but also deriving significant findings and managerial insights with real world relevance.