Reselling or agency selling? Sales mode selection for a manufacturer in private label competition under information asymmetry - Min Yang; Anqi Li; Yang Yang (PLoS ONE, 2026)
Big data systems enhance retailers’ predictive capabilities, providing them with a significant advantage in understanding end-market demand, increasing the competitiveness of retailers’ private labels, and significantly impacting manufacturers’ sales strategies. This paper applies dynamic game-theoretic models to explore the interaction between the retailer’s information-sharing strategies and the manufacturer’s sales mode selections when the retailer introduces a private label. Through backward induction, the equilibrium strategies of both parties can be derived. The results show that the manufacturer consistently benefits from information-sharing under both sales modes, potentially achieving a win-win outcome under the agency selling mode. Improving the retailer’s information forecast accuracy encourages a shift from reselling to agency selling mode. The retailer’s lower information forecast accuracy or the smaller demand variance offers no first-mover advantage to either the manufacturer or the retailer. Additionally, an Information Compensation Mechanism (ICM) for revenue-sharing is proposed, and contract conditions across different sales modes are discussed.