报告内容摘要：

We study a firm's manufacturing strategy under two types of flexible production technologies: the traditional flexible technology and 3D printing. Under the traditional flexible technology, capacity becomes more expensive as it handles more product variants; under 3D printing, however, capacity cost is independent of the number of product variants processed. The firm adopts a dedicated technology and one type of flexible technology, either the traditional one or 3D printing. It needs to choose an assortment from a potential set of variants, assigns each chosen variant to a production technology, and finally invests in capacities. We first establish that the optimal assortment must contain a number of the most popular variants from the potential set. Based on the variants' popularity rankings, we find that the optimal technology assignment can follow an unexpected reversed structure under the traditional flexible technology, while the optimal assignment always follows an ordered structure under 3D printing. Surprisingly, we find that adopting the traditional flexible technology in addition to the dedicated one may reduce product variety chosen by the firm. 3D printing, by contrast, always enhances product variety. Furthermore, 3D printing allows the firm to choose a much larger assortment than optimal without significant profit loss. These results demonstrate that the rising 3D printing has significantly different implications for firms' assortment and production strategy than the traditional flexible technology.

报告人简介：

Duo Shi is a Ph.D candidate at Olin Business School, Washington University in St. Louis. Prior to joining Olin, Duo earned an honored bachelor's degree in mathematics and applied mathematics from School of the Gifted Young, University of Science and Technology of China. Duo has a broad research interest in analytical modeling of operations management, including value chain coordination, innovation & technology management, product variety, marketing-operations interface, and social & environmental responsibility in operations. Duo's work is currently under review at Management Science.

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