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Research on product-service systems: topic landscape and future trends

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jats:sec<jats:title content-type="abstract-subheading">Purpose</jats:title>jats:pThe paper attempts to address the following research questions (RQs): RQ1: What are the main research topics within PSS research? RQ2: What are future trends for PSS research?</jats:p></jats:sec>jats:sec<jats:title content-type="abstract-subheading">Design/methodology/approach</jats:title>jats:pTwenty years of research (1999–2018) on product-service systems (PSS) produced a significant amount of scientific literature on the topic. As the PSS field is relatively new and fragmented across different disciplines, a review of the prior and relevant literature is important in order to provide the necessary framework for understanding current developments and future perspectives. This paper aims to review and organize research contributions regarding PSS. A machine-learning algorithm, namely Latent Dirichlet Allocation, has been applied to the whole literature corpus on PSS in order to understand its structure.</jats:p></jats:sec>jats:sec<jats:title content-type="abstract-subheading">Findings</jats:title>jats:pThe adopted approach resulted in the definition of eight distinct and representative topics able to deal adequately with the multidisciplinarity of the PSS. Furthermore, a systematic review of the literature is proposed to summarize the state-of-the-art and limitations in the identified PSS research topics. Based on this critical analysis, major gaps and future research challenges are presented and discussed.</jats:p></jats:sec>jats:sec<jats:title content-type="abstract-subheading">Originality/value</jats:title>jats:pOn the basis of the results of the topic landscape, the paper presents some potential research opportunities on PSSs. In particular, challenges, transversal to the eight research topics and related to recent technology trends and digital transformation, have been discussed.</jats:p></jats:sec>



Product-service systems, Text mining, Latent dirichlet allocation, Topic landscape, Literature review

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Journal of Manufacturing Technology Management

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