Abstract
This article investigates whether a retailer’s store brand supply source impacts vertical pricing and supply channel profitability. Using chain-level retail scanner data, a random coefficients logit demand model is estimated employing a Bayesian estimation approach. Supply models are specified conditional on demand parameter estimates. Bayesian decision theory is applied to select the best fitting pricing model. Results indicate that a vertically integrated retailer engages in linear pricing for brand manufacturers’ products while competing retailers make nonlinear pricing contracts with brand manufacturers for branded products and store brands. A simulated vertical divestiture based on real world events provides evidence for improved channel efficiency.
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