Leveraging Online Retail Platforms' Information Acquisition for Manufacturers' New Product Development: A Game‐Theoretic Analysis

ABSTRACT A new business model has arisen in recent years where online retail platforms acquire consumer preference information from their big data and pass this information to manufacturers to guide their design decisions. This represents a platform‐led approach in new product development and is known as the consumer‐to‐manufacturer (C2M) model. This paper analyzes a platform's incentive to launch the C2M project and a manufacturer's incentive to participate. We formulate a game‐theoretical model where the platform determines the information acquisition level and the manufacturer determines the R&D effort for new product development. After the development is complete, the new product is sold through the platform using the wholesale model. We find that as the manufacturer's R&D effectiveness increases, the platform engages in a higher level of information acquisition due to the complementary relationship between R&D effort and information acquisition. Also, as the R&D effectiveness increases, the C2M project generates greater benefits for both the platform and the manufacturer, which increases the likelihood of C2M project implementation. Moreover, our analysis shows that the C2M project becomes less beneficial to both parties under ex‐post pricing (where prices are set after consumer valuation is realized) than under ex‐ante pricing (where prices are set before consumer valuation is realized). This suggests that the project is less likely to be implemented as pricing flexibility increases. Finally, analyzing the impact of selling formats, we show that the C2M project yields a greater benefit to the platform under the agency model than under the wholesale model.