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Management article
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Reference no. SMR4522
Published by: MIT Sloan School of Management
Published in: "MIT Sloan Management Review", 2004
Length: 7 pages

Abstract

Managers know more about customers and their preferences than ever, but putting this knowledge into practice dramatically effects both pricing and supply-chain decisions. In this article, the authors present relevant research linking pricing decisions with operational thinking and highlighting different drivers for dynamic pricing strategies. For example, research on revenue management is concerned with pricing a perishable resource in accordance with demand from multiple customer segments, and the authors say that management practice and software solutions have improved this field dramatically. Other research investigates attempts to maximize revenue from leftover goods, suggesting that static pricing strategies often are easier to implement and less likely to lose revenue than one might expect. In addition, researchers have also found that people stockpile goods more when retailers do fewer promotions. However, while the authors claim there is a dearth of research explicitly linking pricing and lead time or capacity, their own observations suggest that many are pursuing sophisticated pricing and operations decisions, often on parallel tracks. The authors suggest that both marketing and operations managers need to be willing to explore the interactions among dynamic pricing, inventory, production planning and capacity-management decisions. They also recognize, however, that researchers are already actively pursuing more sophisticated models and that software developers have begun building the best insights into their existing offerings. This review includes a comprehensive sidebar of all referenced research.

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Abstract

Managers know more about customers and their preferences than ever, but putting this knowledge into practice dramatically effects both pricing and supply-chain decisions. In this article, the authors present relevant research linking pricing decisions with operational thinking and highlighting different drivers for dynamic pricing strategies. For example, research on revenue management is concerned with pricing a perishable resource in accordance with demand from multiple customer segments, and the authors say that management practice and software solutions have improved this field dramatically. Other research investigates attempts to maximize revenue from leftover goods, suggesting that static pricing strategies often are easier to implement and less likely to lose revenue than one might expect. In addition, researchers have also found that people stockpile goods more when retailers do fewer promotions. However, while the authors claim there is a dearth of research explicitly linking pricing and lead time or capacity, their own observations suggest that many are pursuing sophisticated pricing and operations decisions, often on parallel tracks. The authors suggest that both marketing and operations managers need to be willing to explore the interactions among dynamic pricing, inventory, production planning and capacity-management decisions. They also recognize, however, that researchers are already actively pursuing more sophisticated models and that software developers have begun building the best insights into their existing offerings. This review includes a comprehensive sidebar of all referenced research.

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