We live in the age of digitalization. Due to technological advances in information technology and mobile communications, more people and organizations have greater access to data and information than ever before (George et al., 2014; Hilbert & López, 2011). Just over a century ago, few people had read more than 100 books in their lifetime (van Knippenberg et al., 2015). But today, almost every person is just a click away from information about the latest stock prices, tests and user ratings of products, patent applications, and the latest news from business and science. Algorithms can help us to structure this amount of data and make decisions based on them. While not universally the better decision maker in every situation, an algorithm can be a useful and effective help in many market decision situations (Leyer & Schneider, 2021). But do people use the algorithms?
With the advent of algorithm-based decision making, new challenges have emerged (Leyer & Schneider, 2021). For example, it has been shown that decision-makers reject superior but imperfect algorithms (Dietvorst et al., 2015;2018). This phenomenon - referred to as human algorithm aversion - can pose major challenges to business, namely when bad decisions are made due to algorithm aversion. Current research therefore seeks to better understand the background and influencing factors of algorithm aversion.
In order to answer the research question above, we developed an experimental research design in which about 1000 participants took part. In our study, participants had to predict the success of crowd-funding campaigns based on several pieces of information.