How Search Engine Impacts Market Structure: Empirical Evidence from a Multivendor Darknet Market

• 成果类型: Article; Early Access
• 署名作者: Lu, Ying; Qiao, Dandan; He, Shu; Tan, Bernard C. Y.
• 署名单位: IE University; National University of Singapore; State University System of Florida; University of Florida
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2022.04133
• 发表日期: 2025
• 关键词: search engine; market structure; Market concentration; darknet market; drug transaction

摘要

Despite the public's familiarity with search engines, little existing research empir-ically investigates the impact of such a search-cost-reduction tool on online market struc-ture. Knowledge scarcity of this question can mainly be attributed to the challenge of accessing detailed data from a cross-website search engine. Using data from the online ille-gal transaction platform, the Darknet markets, we manage to empirically evaluate the influ-ence of a cross-website search engine (i.e., GRAMS) on the market structure at the vendor and product category levels. The results show that, although the search engine's entry enhances the overall market performance, the benefit is more significant among leading vendors and popular products, contributing to a more concentrated market. Additional analyses provide empirical evidence that the trustworthiness and the scale-up ability of leading vendors can be the underlying mechanisms for the increased market concentration after the introduction of search engines into Darknet markets. Our study not only contri-butes to the literature on the dynamics of sales distribution in a multiple-vendor e-commerce market but also provides insights into understanding the operating dynamics of the Darknet markets, which can be helpful for law enforcement policymaking.