Giancarlo Manzi
- Economics and Econometrics top 10%
- Statistics and Probability top 10%
- Transportation top 10%
- Modeling and Simulation top 10%
- Sociology and Political Science
- Co-authors
- Pier Alda FerrariAlessandro BarbieroMassimo FlorioChiara Del BoCinzia ColapintoSilvia SaliniPaola AnnoniClaudio Giachetti
- Topics
- Data-Driven Disease Surveillance (8 papers)Statistical Methods and Bayesian Inference (8 papers)COVID-19 epidemiological studies (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEInternational Journal of Environmental Research and Public Health
- Partner nations
- ItalyUnited KingdomMalaysia
In The Last Decade
Giancarlo Manzi
31 papers receiving 276 citations
Peers
Comparison fields: 5 of 102
- Economics and Econometrics 84
- Statistics and Probability 45
- Transportation 36
- Modeling and Simulation 34
- Sociology and Political Science 28
Countries citing papers authored by Giancarlo Manzi
This map shows the geographic impact of Giancarlo Manzi'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 Giancarlo Manzi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giancarlo Manzi more than expected).
Fields of papers citing papers by Giancarlo Manzi
This network shows the impact of papers produced by Giancarlo Manzi. 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 Giancarlo Manzi. The network helps show where Giancarlo Manzi may publish in the future.
Co-authorship network of co-authors of Giancarlo Manzi
This figure shows the co-authorship network connecting the top 25 collaborators of Giancarlo Manzi. A scholar is included among the top collaborators of Giancarlo Manzi 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 Giancarlo Manzi. Giancarlo Manzi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 13 | |
| 8 | 2 | |
| 9 | 15 | |
| 10 | 9 | |
| 11 | 11 | |
| 12 | COVID-19 in Italy: An app for a province-based analysis | 2 |
| 13 | 5 | |
| 14 | 19 | |
| 15 | 35 | |
| 16 | GenForImp: The Forward Imputation: A Sequential Distance-Based Approach for Imputing Missing Data. R package version 1.0. | 3 |
| 17 | 13 | |
| 18 | 8 | |
| 19 | 30 | |
| 20 | Criticalities In applying the Neyman's optimality in business surveys: a comparison of selected allocation methods | 1 |
About Giancarlo Manzi
Giancarlo Manzi is a scholar working on Statistics and Probability, Modeling and Simulation and Management Science and Operations Research, having authored 36 papers that have together received 294 indexed citations. Recurring topics across this work include Data-Driven Disease Surveillance (8 papers), Statistical Methods and Bayesian Inference (8 papers) and COVID-19 epidemiological studies (6 papers). The work is most often cited by research in Modeling and Simulation (34 citations), Statistics and Probability (45 citations) and Transportation (36 citations). Giancarlo Manzi has collaborated with scholars based in Italy, United Kingdom and Malaysia. Frequent co-authors include Pier Alda Ferrari, Alessandro Barbiero, Massimo Florio, Chiara Del Bo, Cinzia Colapinto, Silvia Salini, Paola Annoni, Claudio Giachetti, Alessandra Micheletti and Siok Kun Sek. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and International Journal of Environmental Research and Public Health.
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.