This study investigates the ordering behavior of a boundedly rational retailer who purchases a product from a rational supplier under a revenue sharing or buyback contract. We develop a behavioral model considering random error, learning effect and anchoring bias using a logit choice framework which also includes a new behavioral paradigm known as round number bias. Experimental data and theoretical analysis are employed to demonstrate the differences between retailer order quantity and related optimal decisions using the suggested behavioral model. We found that round numbers are enticing anchors in retailer ordering decisions. The findings further reveal that the adaptive learning model better explains and predicts the retailer\\\'s ordering behavior than the time trend learning model. Moreover, the results indicate that the prediction accuracy of the model is higher for revenue sharing compared to buyback contracts.

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