CASRO, the Council of American Survey Research Organizations communicated their preliminary program for the CASRO Technology Conference this week. For 16 years this event has been broadly acclaimed for featuring the latest, most effective technologies in the market research industry. And great news, our paper on online research communities has been accepted. Prof. Dr. Niels Schillewaert (co-founder of InSites Consulting) will be presenting the research results in June in New York City.
Together with Stephan Ludwig (PhD Candidate at the University of Maastricht) and Moritz Mann (Master Student at the University of Maastricht) our ForwaR&D Lab team tested the optimal level of contributions per discussion in online research communities.
In identifying innovative trends, solving marketing problems and researching differentiation opportunities, firms collaborate more directly with consumers than before. Online Research Communities have proven to be a viable environment to stimulate co-creation and consumer insighting. Research communities mostly rely on ‘crowdsourcing‘ and have yielded surprisingly creative and differentiated consumer insights.
The term ‘Crowdsourcing’ was coined by Jeff Howe as a neologistic compound of the words Crowd and Outsourcing. Crowdsourcing is “the act of taking a job traditionally performed by a designated employee and outsourcing it to an undefined, generally large group of people in the form of an open call”. The strength of crowdsourcing is the extent of social interaction, namely the combination and exchange of knowledge – taking place in the online communities. Many studies have looked at and pointed to the effectiveness of crowd sourcing. However, whilst focusing on the quantity of opinions gathered, past research thus far neglected a potential pitfall of crowd sourcing methods. Drawing from group norm theory we posit that consensus norms and social confirmation seeking are dysfunctional for online research communities. In fact, groups with salient consensus norms have been found to make poorer decisions than groups with critical norms.
(Sources: Prahalad and Ramaswamy 2004; Sawhney, Verona et al. 2005; Nambissan et al. 2009; De Ruyck et al. 2010; Howe 2006; Howe 2008; Nahapiet and Ghoshal 1998; Nambisan 2002; Algesheimer, Dholakia et al. 2005; Postmes, Spears et al. 2001)