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Using a large-scale, product-level dataset collected from a supply chain dyad, we examine the effect of own and substitute products on a focal product's bullwhip effect and estimate the existence and magnitude of the bullwhip effect at the product level. We find that, under substitute products, the bullwhip effect is not only affected by a product's own factors but also by those of its substitute products. An increase in the number of own price changes is associated with a decrease in the bullwhip effect in terms of the direct effect but with an increase in the bullwhip effect in terms of the total effect, and increases in the number of price changes of substitute products and own stockouts are associated with increases in the bullwhip effect. The potential effects for own price changes, price changes of substitute products and own stockouts are as much as 59.51%, 95.06% and 66.11%. We also find that the bullwhip effect is prevalent and very intensive at the product level. We discuss the theoretical and managerial implications of the findings. AbstractUsing a large-scale, product-level dataset collected from a supply chain dyad, we examine the effect of own and substitute products on a focal product's bullwhip effect and estimate the existence and magnitude of the bullwhip effect at the product level. We find that, under substitute products, the bullwhip effect is not only affected by a product's own factors but also by those of its substitute products. An increase in the number of own price changes is associated with a decrease in the bullwhip effect in terms of the direct effect but with an increase in the bullwhip effect in terms of the total effect, and increases in the number of price changes of substitute products and own stockouts are associated with increases in the bullwhip effect. The potential effects for own price changes, price changes of substitute products and own stockouts are as much as 59.51%, 95.06% and 66.11%. We also find that the bullwhip effect is prevalent and very intensive at the product level. We discuss the theoretical and managerial implications of the findings.

In contradistinction to the traditional dual‐channel retail model, the online and offline channels are two business units of a single retailer in an online to offline (O2O) business model. The service‐related effort of the offline channel has a spillover effect on the online channel. This paper establishes three game‐theoretic models to analyze how service spillover and power structures affect supply chain members’ performance in the O2O business model. The main results are as follows. First, a service spillover effect is always beneficial to the manufacturer's profit due to the increasing wholesale price and total demand in all three scenarios. Second, unlike the traditional dual‐channel model, service spillover does not inevitably cause price competition in the O2O dual‐channel model. Under different power structure conditions, the spillover intensity has a significant effect on the retailer's profit and service strategy. When the manufacturer is a Stackelberg leader, the effects of spillover on a retailer's profit depend on online channel acceptance level and service level. A service differentiation strategy can help the retailer increase profit margins under certain situations. When the manufacturer and retailer have the same power, retailer's profit increases with spillover intensity, and a service consistency strategy can be implemented. When the retailer is a Stackelberg leader, the retailer's profit decreases first and then increases, and a service mixed strategy will reduce the loss of retailer's profit. Finally, the switch in dominant power between manufacturer and retailer has no impact on retail prices and demand. The total supply chain profit in two Stackelberg models is also equivalent, but lower than that in the Nash model.

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