Effects of visual reference information on solution quality in crowdsourcing contests: A cognitive load perspective

Crowdsourcing contests enable organizations to tap into diverse external contributors, but ensuring high-quality, innovative solutions remains challenging. This study examines the role of visual reference information (VRI) as a critical but underexplored factor influencing solution quality. Drawing on cognitive load theory, we theorize how three forms of VRI—prototypes, exemplars, and guidelines—shape crowdsourcing contest outcomes. Using a dataset of 950 contests from the 99designs platform and applying Beta regression analysis, we test a set of hypotheses. The results present an inverted U-shaped relationship between the number of prototypes and solution quality; a significant linear positive relationship between the number of exemplars and solution quality; and a significant negative relationship between providing guidelines and solution quality. Moreover, our moderating test results show that providing guidelines amplifies the positive prototype-solution quality relationship, while causing the positive exemplars-solution quality link to become negative. These findings advance the literature by identifying novel antecedents of solution quality in crowdsourcing and extending the application of cognitive load theory to digital innovation contexts. For practice, this study provides actionable implications for crowdsourcing contest organizers and platforms on the strategic use of VRI—both in type and quantity—to enhance the likelihood of high-quality outcomes.