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Publications
  • September–October 2018
  • Article
  • Marketing Science

Online MAP Enforcement: Evidence from a Quasi-Experiment

By: Ayelet Israeli
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Abstract

This paper investigates a manufacturer’s ability to influence compliance rates among its authorized online retailers by exploiting changes in the Minimum Advertised Price (MAP) policy and in dealer agreements. MAP is a pricing policy widely used by manufacturers to influence prices set by their downstream partners. A MAP policy imposes a lower bound on advertised prices, subjecting violating retailers to punishments such as termination of distribution agreements. Despite this threat, violations are common. I uncover two key elements to improve compliance: customization to the online environment and credible monitoring and punishments. I analyze the pricing, enforcement, and channel management policies of a manufacturer over several years. During this period, new channel policies take effect, providing a quasi-experiment. The new policies lead to substantially fewer violations. With improved compliance, channel prices increase by 2% without loss in volume. The reduction in violations is particularly stark among authorized retailers with lower sales volume, those that previously operated unapproved websites and those that have received violation notifications for the specific product before. Moreover, low service providers improve their service. At the same time, there is an increase in opportunistic behavior among top retailers, retailers that received notifications for other products, and for less popular products via deep discounting.

Keywords

Pricing Policies; Pricing; Channel Management; Legal Aspects Of Business; Retail; Price; Policy; Governance Compliance; Distribution Channels; Management; Retail Industry

Citation

Israeli, Ayelet. "Online MAP Enforcement: Evidence from a Quasi-Experiment." Marketing Science 37, no. 5 (September–October 2018): 710–732.
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About The Author

Ayelet Israeli

Marketing
→More Publications

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    • April 2022
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    Banorte Móvil: Data-Driven Mobile Growth

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    Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)

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More from the Author
  • Banorte Móvil: Data-Driven Mobile Growth By: Ayelet Israeli and Carla Larangeira
  • Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT) By: Eva Ascarza and Ayelet Israeli
  • AptDeco: Circular Economy Furniture Marketplace By: Ayelet Israeli
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