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The growing interest on ecosystems on both managerial and academic side reflects a vibrant field of study, nevertheless, the subject is very heterogeneous and in particular concerning a particular form of ecosystems: collaborative ecosystems, the purpose of this study is to shed light on these.

The definition gap existent and the multiplicity of fields and composite studies on collaborative ecosystems have made it necessary to conduct a systematic literature review of the phenomenon, a bibliometric analysis and content analysis.

The research offers an overview of the phenomenon, three main cluster categories emerged: ecosystem, competition and open innovation; this cluster offers a comprehensive schematization of the research topics.

Limitations of this research are that the investigation has been confined to specific keywords related to collaborative ecosystems that led to a strict selection of papers to be analyzed and in having confined the investigation to publications in the managerial area. Further research will be able to expand the selection of keywords or use more strings and proceed to a comparative analysis of results. Another limitation is the small number of databases assessed (only Scopus and Web of Science) and have confined the analysis to specific clusters that emerged from the quantitative analysis of papers.

By proposing a taxonomy of collaborative ecosystems, the paper highlights what solutions and architectures an ecosystem manager must consider when developing collaborative ecosystems, what factors he or she must pay attention to in order to ensure their development and survival, and what elements determine the development of an ecosystem, in particular, the management of innovation and knowledge and the scarcity of resources in a hyper-competitive environment.

A combination of research methods was used to identify the intellectual structure of collaborative ecosystems. In addition, we propose a taxonomy for collaborative ecosystems, opening the study to new lines of investigation and providing a new research agenda.

This study, a theoretical article, aims to introduce new institutionalism as a framework through which business and management researchers can explore the significance of artificial intelligence (AI) in organizations. Although the new institutional theory is a fully established research program, the neo-institutional literature on AI is almost non-existent. There is, therefore, a need to develop a deeper understanding of AI as both the product of institutional forces and as an institutional force in its own right.

The authors follow the top-down approach. Accordingly, the authors first briefly describe the new institutionalism, trace its historical development and introduce its fundamental concepts: institutional legitimacy, environment and isomorphism. Then, the authors use those as the basis for the queries to perform a scoping review on the institutional role of AI in organizations.

The findings reveal that a comprehensive theory on AI is largely absent from business and management literature. The new institutionalism is only one of many possible theoretical perspectives (both contextually novel and insightful) from which researchers can study AI in organizational settings.

The authors use the insights from new institutionalism to illustrate how a particular social theory can fit into the larger theoretical framework for AI in organizations. The authors also formulate four broad research questions to guide researchers interested in studying the institutional significance of AI. Finally, the authors include a section providing concrete examples of how to study AI-related institutional dynamics in business and management.