Ferreira, Kris Johnson →

The Impacts of Increasing Search Frictions on Online Shopping Behavior: Evidence from a Field Experiment

This paper challenges the logic that making it easier for consumers to search across a wide assortment of products is the best strategy for online retailers. Experiments show that adding extra search costs to find discounted items can improve gross margins and sales by increasing the number of items inspected and serving as a self-selecting price discrimination mechanism among customers.

Intermediation in the Supply of Agricultural Products in Developing Economies

This paper develops insights into the structural drivers of farmer and supply chain profitability in emerging market supply chains, then studies the impact of an e-intermediary (i.e., a digitally-enabled new supply channel) on this profitability. Results provide a more balanced perspective on the value of e-intermediation compared to the generally positive view that is advanced by case studies.

Companies Love Big Data But Lack the Strategy To Use It Effectively

Big data is a critical competitive advantage for companies that know how to use it. Harvard Business School faculty share insights that they teach to executives. Open for comment; 0 Comments.

Assortment Rotation and the Value of Concealment

Assortment rotation is the retailing practice of changing the assortment of products offered to customers throughout a selling season. It is used by both brick-and-mortar and online retailers as a strategy for gaining competitive advantage. This paper studies assortment rotation in product categories such as apparel, accessories, and toys, where consumers typically make multiple purchases during a season. The authors identify and explain a new reason for retailers to frequently rotate their assortment: Consumers may purchase more products throughout the selling season if a retailer conceals a portion of its full product catalog from consumers by rotating its assortment. Aside from its scholarly contributions, the paper provides practical insights to retailers to guide their assortment rotation strategy decisions.

Online Network Revenue Management Using Thompson Sampling

Kris Johnson Ferreira and colleagues develop a machine learning algorithm that changes product prices in order to learn consumer demand and maximize total revenue in the presence of limited inventory.