Alexander Pelaez
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- Technology Adoption and User Behaviour 2
- Marketing top 10%
- Modeling and Simulation top 10%
- COVID-19 epidemiological studies 3
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- Open Source Software Innovations 2
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- Digital Marketing and Social Media 4
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- COVID-19 Pandemic Impacts 3
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- Experimental Behavioral Economics Studies 2
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- Stock Market Forecasting Methods 2
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- Big Data and Business Intelligence 1
- Co-authors
- Jim SamuelChi-Wen ChenYana SamuelG. G. Md. Nawaz AliRajiv KashyapMd. Mokhlesur RahmanPeter Han Joo ChongKarl R. Lang
- Journals
- IEEE Access (1 paper)International Journal of Information Management (1 paper)Decision Support Systems (1 paper)
- Partner nations
- United StatesNetherlandsSingapore
In The Last Decade
Alexander Pelaez
16 papers receiving 299 citations
Peers
Comparison fields: 5 of 66
- Information Systems and Management 85
- Marketing 68
- Modeling and Simulation 29
- Health Informatics 8
- Computer Science Applications 19
Countries citing papers authored by Alexander Pelaez
This map shows the geographic impact of Alexander Pelaez'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 Alexander Pelaez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Pelaez more than expected).
Fields of papers citing papers by Alexander Pelaez
This network shows the impact of papers produced by Alexander Pelaez. 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 Alexander Pelaez. The network helps show where Alexander Pelaez may publish in the future.
Co-authorship network
The 14 scholars most cited alongside Alexander Pelaez, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2022 | 5 | |
| 3 | 2022 | 49 | |
| 4 | 2021 | 6 | |
| 5 | 2021 | 22 | |
| 6 | 2021 | 1 | |
| 7 | 2021 | 8 | |
| 8 | 2020 | 69 | |
| 9 | Feeling Positive About Reopening? New Normal Scenarios From COVID-19 US Reopen Sentiment Analytics | 2020 | 5 |
| 10 | 2020 | 10 | |
| 11 | The Effects Of Technology Driven Information Categories On Performance In Electronic Trading Markets | 2017 | 16 |
| 12 | 2017 | 90 | |
| 13 | THE IMPACT OF IT-ENABLED COORDINATION ON GROUP PERFORMANCE IN AN ELECTRONIC GROUP-BUYING MARKET | 2014 | 2 |
| 14 | 2014 | 8 | |
| 15 | 2014 | 4 | |
| 16 | 2013 | 19 | |
| 17 | 2012 | 2 |
About Alexander Pelaez
Alexander Pelaez is a scholar working on Modeling and Simulation, Computer Science Applications and Information Systems and Management, having authored 17 papers that have together received 316 indexed citations. Recurring topics across this work include Digital Marketing and Social Media (4 papers), COVID-19 epidemiological studies (3 papers), COVID-19 Pandemic Impacts (3 papers), Experimental Behavioral Economics Studies (2 papers), Open Source Software Innovations (2 papers), Stock Market Forecasting Methods (2 papers), Technology Adoption and User Behaviour (2 papers) and Big Data and Business Intelligence (1 paper). The work is most often cited by research in Information Systems and Management (85 citations), Marketing (68 citations) and Modeling and Simulation (29 citations). Alexander Pelaez has collaborated with scholars based in United States, Netherlands and Singapore. Frequent co-authors include Jim Samuel, Chi-Wen Chen, Yana Samuel, G. G. Md. Nawaz Ali, Rajiv Kashyap, Md. Mokhlesur Rahman, Peter Han Joo Chong, Karl R. Lang, Myles D. Garvey and Steven T. Petra. Their work appears in journals such as IEEE Access, International Journal of Information Management and Decision Support Systems.
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.