Mitigating perceived uncertainty and risk is critical for successful exchanges in an online B2B marketplace. However, scant empirical research has been devoted to the topic, and even less to small- and medium-sized enterprises (SMEs). We investigate the use of quality signals and recommendations to foster buyer-supplier matching in an online B2B marketplace of SMEs. Unique proprietary data from a leading B2B e-commerce platform suggest that such a matching is significantly related to signals of SME buyers' quality and credibility embedded in how projects are described. Moreover, appropriately designed recommendation system can increase the matching rate because it helps reduce buyers' information overload. This research highlights the importance of integrating online channel data with traditional offline channel data to accurately assess the drivers of buyer-supplier matching. Our findings provide valuable insights into how to design and manage an online B2B marketplace for SMEs to yield more successful matches.

缓解感知的不确定性和风险对于在线B2B市场中成功进行交易至关重要。但是，很少有实证研究专门针对该主题，而对中小型企业（SME）的研究则更少。我们调查了质量信号和建议的使用，以促进中小企业在线B2B市场中的供方匹配。来自领先的B2B电子商务平台的独特专有数据表明，这种匹配与SME买家的质量和信誉如何嵌入项目描述中的信号显着相关。而且，适当设计的推荐系统可以提高匹配率，因为它有助于减少购买者的信息过载。这项研究强调了将在线渠道数据与传统的离线渠道数据相集成以准确评估购买者-供应商匹配的驱动因素的重要性。我们的发现为如何设计和管理中小型企业在线B2B市场提供了宝贵的见解，从而使成功的交易更加成功。