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Purpose: The objective of this study is to examine current business and management research on "Industry 4.0 base technologies" and "business models" to shed light on this vast literature and to point out future research agenda. Design/methodology/approach: The authors conducted a bibliometric analysis of scientific publications based on 482 documents collected from the Scopus database and a co-citation analysis to provide an overview of business model studies related to Industry 4.0 base technologies. After that a qualitative analysis of the articles was also conducted to identify research trends and trajectories. Findings: The results reveal the existence of five research themes: smart products (cluster 1); business model innovation (cluster 2); technological platforms (cluster 3); value creation and appropriation (cluster 4); and digital business models (cluster 5). A qualitative analysis of the articles was also conducted to identify research trends and trajectories. Research limitations/implications: First, the dataset was collected through Scopus. The authors are aware that other databases, such as Web of Science, can be used to deepen the focus of quantitative bibliometric analysis. Second, the authors based this analysis on the Industry 4.0 base technologies identified by Frank et al. (2019). The authors recognize that Industry 4.0 comprises other technologies beyond IoT, cloud computing, big data and analytics. Practical implications: Drawing on these analyses, the authors submit a useful baseline for developing Industry 4.0 base technologies and considering their implications for business models. Originality/value: In this paper, the authors focus their attention on the relationship between technologies underlying the fourth industrial revolution, identified by Frank et al. (2019), and the business model, with a particular focus on the developments that have occurred over the last decade and the authors performed a bibliometric analysis to consider all the burgeoning literature on the topic. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to combine open innovation (OI) and organizational learning (OL) literature in the context of strategic alliances. Design/methodology/approach: The authors develop a conceptual framework that links OI to OL literatures. The authors empirically validate this framework through four representative cases of dyadic strategic alliances in which the allied partners have (mainly) adopted an inbound or outbound OI strategy and (mainly) used an experiential or experimental learning approach to access knowledge in the alliance. Findings: The authors propose and validate a framework that links two well-known OI strategies (inbound and outbound) and two types of OL, namely, experiential and experimental learning. This, in turn, allows us to propose four different typologies of learning opportunities that could be pursued by alliance partners. Research limitations/implications: The research offers a framework that links experiential and experimental learning to inbound and outbound OI strategies. However, the authors focused on inbound and outbound OI. The authors are aware that sometimes coupled innovation could take place in alliances. Practical implications: This study proposes best practices for companies willing to open their innovation processes with alliance partners by bearing in mind the learning outcomes that may be exploited through the alliance. Originality/value: This study highlights four alliance archetypes emerging from the nexus between OI strategies to OL methods. [ABSTRACT FROM AUTHOR]