In a dual channel, the manufacturer's low-price guarantee facilitates price discrimination and channel coordination and the manufacturer may choose price-beating, price-matching, or no guarantee.

Marketing Science greatly benefited from the admirable and fastidious efforts of more than 300 different individuals who provided manuscript reviews last year. Beyond those individuals already recognized on the editorial board, the editor-in-chief and senior editors of Marketing Science are indebted to the many guest editors, guest associate editors, and ad hoc reviewers who provided expert counsel and guidance on a voluntary basis. The following list acknowledges the contribution of guest editors, guest associate editors, and ad hoc reviewers who served from January 1, 2020, to December 31, 2020. Finally, our sincere appreciation to the authors, whose outstanding submissions and careful revisions make the journal the go-to resource for leading-edge knowledge in quantitative marketing. K. Sudhir Yale University

Jia et al. study the effects of the General Data Protection Regulation on technology venture investment in the European Union.

Context matters when modeling customer purchases and attrition in noncontractual settings.

To optimize price menus for duration discounts, both randomized field experiments and careful modeling of consumer self-selection are critical.

We empirically study the impact of the HOV-incentive launch and termination on green and non‐green product demand in the U.S. automobile industry.

Understanding how forward-looking consumers respond to price promotions in storable goods markets is an important area of research in empirical marketing and industrial organization. In prior work, researchers have assumed that consumers in these markets are very forward-looking, and calibrated their weekly discount factors to levels around 0.9995. This calibration has been used because earlier research has assumed that a consumer’s storage cost is a continuous function of inventory, which rules out exclusion restrictions that can be used to identify the discount factor. We show that by properly modeling storage cost as a step function of inventory (because storage cost depends on the number of packages stored, instead of the actual amount of inventory), natural exclusion restrictions arise that allow for the discount factor to be point identified. In an application to a storable good category, we find that weekly discount factors are very heterogeneous across consumers, and are on average 0.71. We show through a counterfactual exercise that if one used a model that fixed the discount factor to be consistent with the standard calibrated value, one would overpredict the effect of increased promotional depth for a product on its quantity sold by 18% in the short term, and 15% in the long term.