Giancarlo Manzi

511 total citations
36 papers, 294 citations indexed

About

Giancarlo Manzi is a scholar working on Statistics and Probability, Economics and Econometrics and Epidemiology. According to data from OpenAlex, Giancarlo Manzi has authored 36 papers receiving a total of 294 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Statistics and Probability, 10 papers in Economics and Econometrics and 8 papers in Epidemiology. Recurrent topics in Giancarlo Manzi's work include Data-Driven Disease Surveillance (8 papers), Statistical Methods and Bayesian Inference (8 papers) and COVID-19 epidemiological studies (6 papers). Giancarlo Manzi is often cited by papers focused on Data-Driven Disease Surveillance (8 papers), Statistical Methods and Bayesian Inference (8 papers) and COVID-19 epidemiological studies (6 papers). Giancarlo Manzi collaborates with scholars based in Italy, United Kingdom and Malaysia. Giancarlo Manzi's co-authors include Pier Alda Ferrari, Alessandro Barbiero, Massimo Florio, Chiara Del Bo, Cinzia Colapinto, Silvia Salini, Paola Annoni, Claudio Giachetti, Siok Kun Sek and Zaidi Isa and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and International Journal of Environmental Research and Public Health.

In The Last Decade

Giancarlo Manzi

31 papers receiving 276 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Giancarlo Manzi Italy 11 84 45 36 34 28 36 294
Simon Peters United Kingdom 9 132 1.6× 28 0.6× 11 0.3× 9 0.3× 31 1.1× 23 388
Consuelo Rubina Nava Italy 13 116 1.4× 15 0.3× 23 0.6× 8 0.2× 84 3.0× 34 390
Sherzod B. Akhundjanov United States 12 192 2.3× 48 1.1× 8 0.2× 22 0.6× 31 1.1× 30 403
Marcello Basili Italy 13 148 1.8× 10 0.2× 13 0.4× 7 0.2× 71 2.5× 48 446
Matheus Pereira Libório Brazil 11 101 1.2× 16 0.4× 37 1.0× 17 0.5× 94 3.4× 79 380
Alessandro Romano Italy 11 120 1.4× 5 0.1× 13 0.4× 32 0.9× 37 1.3× 33 292
Prana Ugiana Gio Indonesia 12 107 1.3× 3 0.1× 18 0.5× 25 0.7× 126 4.5× 46 451
Vita Ratnasari Indonesia 10 80 1.0× 84 1.9× 15 0.4× 2 0.1× 27 1.0× 91 359
Seth Benzell United States 7 96 1.1× 4 0.1× 46 1.3× 137 4.0× 83 3.0× 20 302

Countries citing papers authored by Giancarlo Manzi

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Ferrari, Luisa, et al.. (2024). Correction: Pandemic data quality modelling: a Bayesian approach in the Italian case. Quality & Quantity. 59(1). 989–991. 1 indexed citations
2.
Ferrari, Luisa, et al.. (2024). Pandemic data quality modelling: a Bayesian approach in the Italian case. Quality & Quantity. 59(1). 87–109. 1 indexed citations
3.
Ismail, Mohd Tahir, et al.. (2024). Enhancing Model Selection by Obtaining Optimal Tuning Parameters in Elastic-Net Quantile Regression, Application to Crude Oil Prices. Journal of risk and financial management. 17(8). 323–323. 1 indexed citations
4.
Manzi, Giancarlo, et al.. (2023). Regional economic convergence in federation contexts: a comparative analysis of Brazil and the European Union. Regional Studies. 57(11). 2269–2284. 5 indexed citations
5.
Manzi, Giancarlo, et al.. (2022). Most Favoured Nation Clauses in Tax Treaties: Comparative Analysis and Main Issues. World Tax Journal. 14(1). 2 indexed citations
6.
Micheletti, Alessandra, Matteo Zignani, Alessandro Comunian, et al.. (2021). CoViD-19, learning from the past: A wavelet and cross-correlation analysis of the epidemic dynamics looking to emergency calls and Twitter trends in Italian Lombardy region. PLoS ONE. 16(2). e0247854–e0247854. 13 indexed citations
7.
Castaldi, Silvana, Patrizia Boracchi, Giuseppe Marano, et al.. (2021). Are Epidemiological Estimates Able to Describe the Ability of Health Systems to Cope with COVID-19 Epidemic?. Risk Management and Healthcare Policy. Volume 14. 2221–2229. 2 indexed citations
8.
Ferrari, Luisa, et al.. (2021). Modeling Provincial Covid-19 Epidemic Data Using an Adjusted Time-Dependent SIRD Model. International Journal of Environmental Research and Public Health. 18(12). 6563–6563. 15 indexed citations
9.
Manzi, Giancarlo, et al.. (2020). Analysis of Sustainability Propensity of Bike-Sharing Customers Using Partially Ordered Sets Methodology. Social Indicators Research. 157(1). 123–138. 9 indexed citations
10.
Ferrari, Luisa, et al.. (2020). COVID-19 in Italy: An app for a province-based analysis. Europe PMC (PubMed Central). 2 indexed citations
11.
Castaldi, Silvana, Matteo Zignani, Giancarlo Manzi, et al.. (2020). Monitoring emergency calls and social networks for COVID-19 surveillance. To learn for the future: The outbreak experience of the Lombardia region in Italy.. PubMed. 91(9-S). 29–33. 11 indexed citations
12.
Tanda, Alessandra & Giancarlo Manzi. (2019). Underpricing of venture backed IPOs: a meta-analysis approach. Economics of Innovation and New Technology. 29(4). 331–348. 5 indexed citations
13.
Isa, Zaidi, et al.. (2019). Quantile Regression to Tackle the Heterogeneity on the Relationship Between Economic Growth, Energy Consumption, and CO2 Emissions. Environmental Modeling & Assessment. 25(2). 251–258. 19 indexed citations
14.
Manzi, Giancarlo, et al.. (2017). Are they telling the truth? Revealing hidden traits of satisfaction with a public bike-sharing service. International Journal of Sustainable Transportation. 12(4). 253–270. 35 indexed citations
15.
Ferrari, Pier Alda & Giancarlo Manzi. (2014). Citizens evaluate public services: a critical overview of statistical methods for analysing user satisfaction. Journal of Economic Policy Reform. 17(3). 236–252. 13 indexed citations
16.
Barbiero, Alessandro & Giancarlo Manzi. (2014). SunterSampling : Sunter's sampling design. IRIS Research product catalog (Sapienza University of Rome).
17.
Barbiero, Alessandro, et al.. (2013). Bootstrapping probability-proportional-to-size samples via calibrated empirical population. Journal of Statistical Computation and Simulation. 85(3). 608–620. 8 indexed citations
18.
Manzi, Giancarlo, et al.. (2009). Criticalities In applying the Neyman's optimality in business surveys: a comparison of selected allocation methods. BOA (University of Milano-Bicocca). 37–7. 1 indexed citations
19.
Ferrari, Pier Alda, Paola Annoni, & Giancarlo Manzi. (2009). Evaluation and comparison of European countries: public opinion on services. Quality & Quantity. 44(6). 1191–1205. 8 indexed citations
20.
Manzi, Giancarlo, et al.. (2008). Bootstrap Algorithms for Risk Models with Auxiliary Variable and Complex Samples. Methodology And Computing In Applied Probability. 11(1). 21–27. 2 indexed citations

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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