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Over the past 50 years, a substantial interest has been put to research on how innovation spreads within social networks over time (see Rogers, 1962, 2010). Our initial aim was to examine innovation diffusion in industrial networks. We operationalized the research through a case study of an advertising network by using systematic combining as the approach (Dubois & Gadde, 2002, 2014). From the initial focus of innovation diffusion, the rematching of data and theory led us to focus on the barriers of innovation diffusion. By doing so, we found out that multilevel strategizing appears to be an important phenomenon in understanding dynamics of innovation diffusion within industrial networks. Specifically, strategizing occurs in two levels: (1) the groups within the network compete for position, and (2) actors within a group compete for position by trying to differentiate themselves from other group actors. A strategic mismatch between the two levels leads the network to become decelerated or even static in diffusing new innovations (Abrahamsen, Henneberg, & Naudè, 2012). Uncovering these findings would not have been possible without the use of systematic combining and the constant matching between theoretical and empirical domains.