No abstract

In order to study retailers’ ordering behavior deviating from the standard theoretical optimal decision, which is caused by retailers’ information asymmetry, cognitive ability, insufficient computing ability, and other factors, we construct a bounded-rationality choice model with quantal response equilibrium. First, the existence and uniqueness of quantal response equilibrium of transshipment game have been proved with the transshipment price satisfying certain conditions. Then, the numerical example demonstrates that with the increase of bounded-rationality parameters, retailers’ quantal response equilibrium will converge to Nash equilibrium due to the learning effect, and their profits will converge to the profits predicted by standard theory. Finally, the results show that retailers are more averse to the explicit loss of shortage than to the implicit loss of inventory surplus caused by the increase of order quantity. Hence, retailers tend to overorder to avoid loss of shortage.

Despite the benefits of inventory transshipment, numerous behavioral experiments have revealed that retailers often deviate from the Nash-equilibrium ordering quantities, which in turn impacts the potential advantages. Motivated by this issue, we developed a behavioral model to analyze the deviation of ordering quantities among two independent retailers who engage in inventory transshipment from the perspective of analytical modeling. In our model, we incorporated bounded rationality with the quantal response equilibrium. Firstly, we established the existence of such a quantal response equilibrium and provided the conditions for its uniqueness. Secondly, we compared the quantal response equilibrium with the Nash equilibrium within a certain range of transshipment prices and observed that the limiting quantal response equilibrium is equivalent to the Nash equilibrium. Lastly, we design an iterative algorithm that incorporates the learning effects of the retailers to determine the quantal response equilibrium for the ordering quantity. The results indicate that the optimal ordering quantity and the nearby ordering quantities should be chosen with higher probabilities. Additionally, the retailer should gradually enhance their cognitive or computational abilities through repeated transshipment games to improve their decision-making process. Furthermore, to ensure a balanced inventory-sharing system, the evaluation of inventory strategies should consistently prioritize avoiding surplus instead of shortage.