Over the past 50 years, a substantial interest has been put to research onhow innovation spreads within social networks over time (see Rogers,1962, 2010). Our initial aim was to examine innovation diffusion inindustrial networks. We operationalized the research through a casestudy of an advertising network by using systematic combining as theapproach (Dubois & Gadde, 2002, 2014). From the initial focus of innovationdiffusion, the rematching of data and theory led us to focus on thebarriers of innovation diffusion. By doing so, we found out that multilevelstrategizing appears to be an important phenomenon in understandingdynamics of innovation diffusion within industrial networks. Specifically,strategizing occurs in two levels: (1) the groups within the network competefor position, and (2) actors within a group compete for position bytrying to differentiate themselves from other group actors. A strategic mismatch between the two levels leads the network to become deceleratedor even static in diffusing new innovations (Abrahamsen, Henneberg, &Naude`, 2012). Uncovering these findings would not have been possiblewithout the use of systematic combining and the constant matchingbetween theoretical and empirical domains.