Bice Cavallo

38 papers receiving 589 citations

Peers

Bice Cavallo
Comparison fields: 5 of 69
  • Management Science and Operations Research 485
  • Statistics and Probability 125
  • Computational Theory and Mathematics 181
  • Artificial Intelligence 210
  • Management of Technology and Innovation 39
Replace Manish Aggarwal with:
Manish Aggarwal India
Bowen Zhang China
Surajit Borkotokey India
Xiaoxia Xu China
M.J. del Moral Spain
Rodolfo Lourenzutti Brazil
Bonifacio Llamazares Spain
Yating Liu China
Yuzhu Wu China
Jian‐Zhang Wu China
Bice Cavallo relative to Manish Aggarwal India Manish Aggarwal's profile →
Citations per field
00.5×2.6×
Manish Aggarwal · 1×
Citations per year

Countries citing papers authored by Bice Cavallo

Since Specialization
Citations

This map shows the geographic impact of Bice Cavallo'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 Bice Cavallo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bice Cavallo more than expected).

Fields of papers citing papers by Bice Cavallo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bice Cavallo. 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 Bice Cavallo. The network helps show where Bice Cavallo may publish in the future.

Co-authors

The 9 scholars most cited alongside Bice Cavallo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bice Cavallo Line = papers co-authored together Bice Cavallo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200997
2 201061
3 201741
4 201836
5 201933
6 201132
7 201130
8 201030
9 201729
10 201428
11 201526
12 201919
13 201416
14 201516
15 201416
16 201813
17 201911
18 202210
19 20199
20 20096

About Bice Cavallo

Bice Cavallo is a scholar working on Management Science and Operations Research, Computational Theory and Mathematics, Artificial Intelligence, Management of Technology and Innovation and Statistics and Probability, having authored 40 papers that have together received 612 indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (28 papers), Rough Sets and Fuzzy Logic (14 papers), Advanced Algebra and Logic (12 papers), Bayesian Modeling and Causal Inference (12 papers), Data Quality and Management (6 papers), Privacy-Preserving Technologies in Data (6 papers), Quality Function Deployment in Product Design (4 papers) and Cognitive Science and Mapping (4 papers). The work is most often cited by research in Management Science and Operations Research (485 citations), Statistics and Probability (125 citations), Computational Theory and Mathematics (181 citations), Artificial Intelligence (210 citations) and Management of Technology and Innovation (39 citations). Bice Cavallo has collaborated with scholars based in Italy, France and United Kingdom. Frequent co-authors include Livia D’Apuzzo, Matteo Brunelli, Gerardo Canfora, Massimo Squillante, Massimiliano Di Penta, Alessio Ishizaka, Jiří Mazurek, Biagio Simonetti and Jaroslav Ramı́k. Their work appears in journals such as Quality & Quantity, Fuzzy Optimization and Decision Making, International Journal of Intelligent Systems, Fuzzy Sets and Systems and Journal of the Operational Research Society.

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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