José G. Dias
- Strategy and Management top 5%
- Marketing top 5%
- Economics and Econometrics top 5%
- Artificial Intelligence top 10%
- Sociology and Political Science top 10%
- Co-authors
- Francesca BassiSofía B. RamosJeroen K. VermuntMário Sérgio TeixeiraSabu S. PadmadasLeonor Pereira da CostaMichel WedelFrans Willekens
- Topics
- Complex Systems and Time Series Analysis (10 papers)Bayesian Methods and Mixture Models (9 papers)Market Dynamics and Volatility (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEClinical Infectious Diseases
- Partner nations
- PortugalNetherlandsItaly
In The Last Decade
José G. Dias
58 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 131
- Strategy and Management 291
- Marketing 200
- Economics and Econometrics 196
- Artificial Intelligence 146
- Sociology and Political Science 121
Countries citing papers authored by José G. Dias
This map shows the geographic impact of José G. Dias'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 José G. Dias with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites José G. Dias more than expected).
Fields of papers citing papers by José G. Dias
This network shows the impact of papers produced by José G. Dias. 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 José G. Dias. The network helps show where José G. Dias may publish in the future.
Co-authorship network of co-authors of José G. Dias
This figure shows the co-authorship network connecting the top 25 collaborators of José G. Dias. A scholar is included among the top collaborators of José G. Dias 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 José G. Dias. José G. Dias is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 8 | |
| 3 | MAINT.Data: Modelling and Analysing Interval Data in R | 1 |
| 4 | 61 | |
| 5 | 4 | |
| 6 | 26 | |
| 7 | 32 | |
| 8 | 22 | |
| 9 | 1 | |
| 10 | 7 | |
| 11 | 8 | |
| 12 | 104 | |
| 13 | 59 | |
| 14 | 8 | |
| 15 | 67 | |
| 16 | 3 | |
| 17 | Modeling demographic and health survey (DHS) data by latent class models: an application | 1 |
| 18 | Mixture hidden Markov models in finance research | 0 |
| 19 | Performance Evaluation of Information Criteria for the Naive-Bayes Modelin the Case of Latent Class Analysis: A Monte Carlo Study | 2 |
| 20 | 41 |
About José G. Dias
José G. Dias is a scholar working on Finance, Marketing and Strategy and Management, having authored 62 papers that have together received 1.2k indexed citations. Recurring topics across this work include Complex Systems and Time Series Analysis (10 papers), Bayesian Methods and Mixture Models (9 papers) and Market Dynamics and Volatility (6 papers). The work is most often cited by research in Business and International Management (62 citations), Marketing (200 citations) and Strategy and Management (291 citations). José G. Dias has collaborated with scholars based in Portugal, Netherlands and Italy. Frequent co-authors include Francesca Bassi, Sofía B. Ramos, Jeroen K. Vermunt, Mário Sérgio Teixeira, Sabu S. Padmadas, Leonor Pereira da Costa, Michel Wedel, Frans Willekens, Luca De Angelis and Ricardo Sousa. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Clinical Infectious Diseases.
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.