Information Use Under Quality Uncertainties and Its Impact on the Digital Goods Production

The wide application of digital technologies has created an enriched digitized environment and changed many people's lifestyles. Such a digitized environment also provides a free and open playing field for average people in the public to pursue innovative digital activities such as digital goods production. However, users face severe uncertainty on both general quality and taste-match quality of digital goods, considering the lack of formal training of average people as producers and standards for producing such goods. So far, little is known about how users deal with the severe dual quality uncertainties issue in a digitized environment, which in turn influences producers' successes in digital goods production in both short and long terms. This paper presents a novel theory-based model to address these issues based on the signaling theory. Empirical testing using real-world data provides strategies to users on quality inference, and offers actionable knowledge to average people as producers and the platform on how to design effective signal devices to build their user bases and earn revenue in the short and long runs. This study thus sheds light on such an IT-enabled production by the public in digital goods markets.