Discovering heterogeneous consumer journeys in online platforms: implications for networking investment

JOURNAL OF THE ACADEMY OF MARKETING SCIENCE(2020)

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摘要
We model consumer journeys for user-created programs published in an online programming platform (OPP) and uncover factors that predict their occurrence. We build our model on a theoretical framework where consumer journeys involve three latent stages (Learn, Feel, Do), in which users gather information about, express fondness toward, and try the published items, respectively. Using a dataset from an OPP where users publish multimedia items and follow other users, we find that there is no one dominant consumer journey; instead, the sequences of stages in a journey (e.g., Learn → Feel → Do) vary across published items. Furthermore, we find that the social capital (i.e., social network) of a publisher influences the occurrence of spillover effects between latent stages (the phenomenon that one stage in a period triggers another stage in the next period) for the items posted by the publisher. We also find that a publisher’s social capital has only a transient impact on the consumer journeys for the publisher’s projects, underlining the importance of consistently making new network connections in order to promote the growth of user activities surrounding the publisher’s projects. We apply our findings to the publishers’ networking investment decisions to show that publishers’ networking investment would be severely suboptimal if journey heterogeneity is not considered.
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关键词
Consumer journey, Online platform, User activity metrics, Social influence, Spillover effect, Sequential Monte Carlo methods, Dynamic latent instrumental variable, Networking investment
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