Information technology (IT) services vendors operate in a highly competitive but also institutional environment that render their service-line offerings mutually observable. This suggests that imitation of rivals' decisions can be an efficient means for IT vendors when reconfiguring their service-line offerings. To explore how such imitation unfolds in this sector, we estimate a series of logistic regression models of 116 IT vendors' service-line choices over three time periods. First, from the strategic imitation literature we identify the key imitation Òreferents,Ó which is a group of firms or a single firm with specific traits, and we test the relative influence of each referent. All of our analysis includes these referents as predictors of service-line choice. Next, we tested more nuanced models using theoretically guided subsamples as follows. One, based on information systems (IS) literature, we consider the IT vendors as embedded in three distinct Òinstitutional spheres,Ó each corresponding to a knowledge domain, namely, technical, functional, and vertical industry domains. We separately examine imitation in each subsample corresponding to the three types of service lines. Two, based on strategy literature, we consider that the influence of the imitation referents differs when the choice under consideration is the addition of a new service line versus a withdrawal. Our results across all of these subsamples uncover a nuanced pattern of imitation that sometimes contrasts the full-sample results. The most prominent result is that although imitation is highly salient, the different imitation referents are not universally influential across all knowledge domains and between development versus withdrawal decisions. Specifically, the imitation of similar firms is widespread, whereas the imitation of largest firms or offering popular service-lines, which indicates bandwagon effects, are at play only selectively. This study contributes to the IS literature by laying a basis for a variety of research directions including resource spillovers and vicarious learning in IT sectors.