Digitally forecasting new music product success via active crowdsourcing

Publication date: September 2019Source: Technological Forecasting and Social Change, Volume 146Author(s): Dennis M. Steininger, Simon GatzemeierAbstractDeciding which artist or song to sign and promote has always been a challenge for recording companies, especially when it comes to innovative newcomer singers without any chart history. However, the specifics of a creative industry such as the hedonic nature of music, socio-network effects, and ever fastening fashion cycles in combination with digitalization have made the recording industry even more competitive and these initial decisions even more crucial. With respect to the ongoing digital transformation and shift in power from organizations to consumers, we leverage digitally mediated wisdom of the crowd to build a forecasting model for better understanding chart success. Therefore, we draw on the literature of hedonic and experiential goods to investigate the relationship between crowd evaluations based on listening experience and popular music chart success. We track 150 song positions in reported music charts and also evaluate these songs via the crowd. Our model indicates that the wisdom of the crowd can improve forecasting chart success by almost 30% relatively to factors that have been earlier identified in the literature. However, this forecasting relevance is bound to certain conditions, namely the composition of the crowd, the underlying chart and market mechanisms, and the novelty of the musical material. In sum...
Source: Technological Forecasting and Social Change - Category: Science Source Type: research