Answers are grounded in this paper and cite their sources.
Dynamic game modeling reveals how managerial overconfidence alters pricing and operational mode selection in competing e-commerce platforms, indicating strategic shifts driven by consumer perception.
E-commerce platforms involve interactions among platform governance, manufacturer pricing, consumer perception, and managerial cognition. This study examines how platform overconfidence and consumer product-fit perception accuracy affect pricing, profitability, and operational mode selection. Product-fit perception accuracy denotes the probability that consumers correctly perceive the mismatch between their preferences and product attributes. We develop a two-period dynamic game involving two competing platforms and two manufacturers and compare resale and agency modes under simultaneous and sequential decisions. Equilibrium analysis shows that, under the agency mode, overconfidence increases promotional allowances and manufacturers’ first-period and switching-purchase prices, while its effect on repeat-purchase prices depends on a mismatch-cost threshold. Under the resale mode, overconfidence raises wholesale prices only within an intermediate range, and product-fit perception accuracy can have either a positive or negative effect depending on the level of overconfidence. Sequential decision-making further produces different pricing responses for leader and follower platforms due to differences in commitment and information conditions. Numerical analysis under the specified parameter settings indicates that resale tends to generate higher platform profits when consumers’ perceived product-quality level is high. When this level is low, the relative profitability of the two modes becomes more sensitive to overconfidence, product-fit perception accuracy, and decision position, with agency becoming more profitable in some parameter regions. These results characterize how governance mode and decision timing shape the economic consequences of managerial overconfidence and product-fit information within the modeled platform setting.
No takes yet. Share an insight, caveat, or question.
Xie et al. (2026) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: