Massimo Garbuio

75 total papers · 1.2k total citations
27 papers, 742 citations indexed

About

Massimo Garbuio is a scholar working on Strategy and Management, Management Science and Operations Research and Experimental and Cognitive Psychology. According to data from OpenAlex, Massimo Garbuio has authored 27 papers receiving a total of 742 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Strategy and Management, 7 papers in Management Science and Operations Research and 5 papers in Experimental and Cognitive Psychology. Recurrent topics in Massimo Garbuio's work include Innovation and Knowledge Management (7 papers), Design Education and Practice (5 papers) and Creativity in Education and Neuroscience (5 papers). Massimo Garbuio is often cited by papers focused on Innovation and Knowledge Management (7 papers), Design Education and Practice (5 papers) and Creativity in Education and Neuroscience (5 papers). Massimo Garbuio collaborates with scholars based in Australia, United Kingdom and Denmark. Massimo Garbuio's co-authors include Nidthida Lin, Dan Lovallo, Andy Dong, Adelaide Wilcox King, Bent Flyvbjerg, Ted Tschang, Arne Rønnest, Eric Molin, Søren L. Buhl and Alexander Budzier and has published in prestigious journals such as Journal of Management, Journal of Product Innovation Management and California Management Review.

In The Last Decade

Massimo Garbuio

23 papers receiving 706 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Massimo Garbuio 288 220 130 102 96 27 742
Elspeth McFadzean 186 0.6× 84 0.4× 178 1.4× 96 0.9× 95 1.0× 31 840
Albert L. Johnson 355 1.2× 117 0.5× 182 1.4× 72 0.7× 111 1.2× 26 759
van Je Joan Aken 187 0.6× 150 0.7× 131 1.0× 78 0.8× 174 1.8× 17 741
Arik Sadeh 170 0.6× 309 1.4× 121 0.9× 57 0.6× 109 1.1× 37 684
Sylvain Lenfle 390 1.4× 380 1.7× 143 1.1× 54 0.5× 95 1.0× 29 723
Anja Schulze 555 1.9× 127 0.6× 195 1.5× 44 0.4× 116 1.2× 19 874
Peter A. Koen 527 1.8× 142 0.6× 245 1.9× 72 0.7× 58 0.6× 19 811
Jianlin Wu 126 0.4× 63 0.3× 129 1.0× 79 0.8× 34 0.4× 44 775
Anna Rylander 541 1.9× 65 0.3× 119 0.9× 91 0.9× 90 0.9× 17 884
Matti Kaulio 308 1.1× 106 0.5× 195 1.5× 51 0.5× 163 1.7× 30 738

Countries citing papers authored by Massimo Garbuio

Since Specialization
Citations

This map shows the geographic impact of Massimo Garbuio's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Massimo Garbuio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo Garbuio more than expected).

Fields of papers citing papers by Massimo Garbuio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Massimo Garbuio. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Massimo Garbuio. The network helps show where Massimo Garbuio may publish in the future.

Co-authorship network of co-authors of Massimo Garbuio

This figure shows the co-authorship network connecting the top 25 collaborators of Massimo Garbuio. A scholar is included among the top collaborators of Massimo Garbuio based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Massimo Garbuio. Massimo Garbuio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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