Measuring Repurchase Decisions by Accelerating Repurchase Behavior. Issue 3 (August 2022) - Dong, Songting; Zhao, Ping; Zou, Deqiang
Repurchase intention questions are routinely used in marketing research and practices to measure consumers' repurchase decisions. They are easy to use but suffer from a few biases and weak predictive power. This article identifies three biases, namely, projection bias, lack-of-context bias, and hypothetical bias. A new method, repurchase acceleration (RA), is proposed targeting these biases. In RA, researchers buy back respondents' currently owned products to ensure they are in the market, provide them with a representative choice set to mimic the repurchase market context, and attach real-life consequences to mimic the incentives in their real-life repurchases. An empirical study demonstrates that RA predicts significantly better than repurchase intention models and captures more than 3 times as much information as the best repurchase intention model does. We recommend that RA is used for high-value, long purchase-cycle products for a precise measure of consumers' repurchase decisions for high-stake marketing decisions.