Willingness-to-pay experimental model for Stackelberg dual channel pricing decision

Abstract

PurposeThis study proposes and demonstrates a novel approach to analyzing customer channel preferences and willingness-to-pay (WTP) in the dual sales channel (DSC) system involving direct online channels and conventional offline retailers, and to how the pricing decisions are made under specific game competition.Design/methodology/approachQuestionnaire survey based on central composite experiment design was utilized to obtain primary data. The model for customer channel preferences and WTP was then built by using multinomial logistic regression. The propensity of a customer to make purchases in either channel estimated by using the logit model was inserted in the bilevel programming model to formulate and solve for the Stackelberg competition where the conventional retailer acted as a leader.FindingsThe study found that channel prices have nonlinear impacts on WTP and channel preference. The empirical results complement the mathematical formulation well where high-order own-price and cross-price effects on channel selection are generally not analytical tractable. Under the Stackelberg competition, the traditional retailer (as the leader) still achieves higher profits than the online facility.Practical implicationsThe proposed framework provides an empirical approach that can easily address the competition model in the sales channel when complicated own-price or cross-price effects are present.Originality/valueThe present work provides a novel approach to analyze customer preference and WTP of the DSC systems. This alternative method simplifies the procedure for investigating and estimating price sensitivity, especially when the online and offline prices affect customer WTP and channel preferences nonlinearly. This model is also utilized in the game competition to facilitate data-driven price decision making to better formulate and understand real-world DSC problems.