Estimating Network Effects in Two-Sided Markets

• 成果类型: Article
• 署名作者: Hinz, Oliver; Otter, Thomas; Skiera, Bernd
• 署名单位: Goethe University Frankfurt; Deakin University
• 刊物名称: JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
• ISSN/ISSBN: 0742-1222
• DOI: 10.1080/07421222.2019.1705509
• 发表日期: 2020
• 页码: 12-38
• 关键词: EMPIRICAL-ANALYSIS; externalities; platform; DESIGN; IMPACT; COMPETITION; DYNAMICS; adoption; LESSONS; MODEL

摘要

The proliferation of the Internet has enabled platform intermediaries to create two-sided markets in many industries. Time-series data on the number of customers on both sides of the markets allow platform intermediaries for estimating the direction and magnitude of network effects, which can then support growth predictions and subsequent information technology (IT) or marketing investment decisions. This article investigates the conditions under which this estimation of same-side and cross-side network effects should distinguish between its impact on the number of new customers (i.e., acquisition) and existing customers (i.e., their activity). The authors propose an influx-outflow model for doing so and conduct a simulation study to benchmark the new model against the traditional model. Further they compare the models in an illustrative empirical study in which they study the growth of an Internet auction platform. The results show that this separation of effects is beneficial because the existing customers on both sides of the market can influence the acquisition and dropout of other customers asymmetrically. The paper thus makes an important contribution that should impact the way how researchers and business practitioners measure network effects in two-sided markets.