Open Innovation Research in Marketing: A Review Using Latent Dirichlet Allocation

Open innovation is an increasingly important paradigm in a highly competitive technological landscape which demands collaboration and co-creation. And yet, a comprehensive review of open innovation research in the context of marketing is absent. To fill this void, we offer a synthesis of existing research on open innovation within the marketing domain. We utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol to identify 176 representative articles published during 2009–23. The abstracts of the sampled articles are then subjected to topic modelling using the latent Dirichlet allocation (LDA) algorithm. The topic modelling output suggests existence of two underlying themes in extant open innovation literature within the marketing domain: strategic innovation management, and digital and social innovation ecosystems. The study also brings to the fore open innovation research output over the years, representative studies for the topics unearthed, top-30 most relevant terms for each of the two topics, and top-30 most salient terms in the corpus. The findings are of significance to academicians as well as practitioners intending to expand the horizons of knowledge on open innovation or leverage it for enhancing competitiveness, respectively.