Onur Doğan
Impact in
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- Business Process Modeling and Analysis
- Big Data and Business Intelligence
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- Multi-Criteria Decision Making
Papers in
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- Business Process Modeling and Analysis 22
- Big Data and Business Intelligence 11
- Co-authors
- Başar Öztayşi (15 shared papers)Cengiz Kahraman (3 shared papers)Carlos Fernández-Llatas (6 shared papers)Muhammet Deveci (1 shared paper)Fatih Canıtez (1 shared paper)Sanju Tiwari (3 shared papers)M. A. Jabbar (2 shared papers)Ejder Ayçın (1 shared paper)
In The Last Decade
Onur Doğan
80 papers receiving 752 citations
Peers
Comparison fields: 5 of 107
- Management Information Systems 166
- Management Science and Operations Research 186
- Marketing 117
- Health Information Management 30
- Industrial and Manufacturing Engineering 71
Countries citing papers authored by Onur Doğan
This map shows the geographic impact of Onur Doğan'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 Onur Doğan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Onur Doğan more than expected).
Fields of papers citing papers by Onur Doğan
This network shows the impact of papers produced by Onur Doğan. 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 Onur Doğan. The network helps show where Onur Doğan may publish in the future.
Co-authors
The 25 scholars most cited alongside Onur Doğan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 90 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 87 | |
| 2 | 2021 | 85 | |
| 3 | 2021 | 62 | |
| 4 | CUSTOMER SEGMENTATION BY USING RFM MODEL AND CLUSTERING METHODS: A CASE STUDY IN RETAIL INDUSTRY | 2018 | 44 |
| 5 | 2019 | 44 | |
| 6 | 2018 | 27 | |
| 7 | 2022 | 25 | |
| 8 | 2019 | 24 | |
| 9 | 2019 | 23 | |
| 10 | 2021 | 21 | |
| 11 | 2013 | 21 | |
| 12 | 2022 | 19 | |
| 13 | 2019 | 16 | |
| 14 | 2019 | 16 | |
| 15 | 2023 | 14 | |
| 16 | 2022 | 14 | |
| 17 | 2020 | 12 | |
| 18 | 2019 | 11 | |
| 19 | 2022 | 10 | |
| 20 | 2022 | 10 |
About Onur Doğan
Onur Doğan is a scholar working on Management Information Systems, Artificial Intelligence, Information Systems, Industrial and Manufacturing Engineering and Management Science and Operations Research, having authored 90 papers that have together received 777 indexed citations. Recurring topics across this work include Business Process Modeling and Analysis (22 papers), Customer churn and segmentation (12 papers), Big Data and Business Intelligence (11 papers), Multi-Criteria Decision Making (8 papers), Digital Transformation in Industry (8 papers), Service-Oriented Architecture and Web Services (6 papers), IoT and Edge/Fog Computing (5 papers) and Data Mining Algorithms and Applications (5 papers). The work is most often cited by research in Management Information Systems (166 citations), Management Science and Operations Research (186 citations), Marketing (117 citations), Health Information Management (30 citations) and Industrial and Manufacturing Engineering (71 citations). Onur Doğan has collaborated with scholars based in Türkiye, Italy and Spain. Frequent co-authors include Başar Öztayşi, Cengiz Kahraman, Carlos Fernández-Llatas, Muhammet Deveci, Fatih Canıtez, Sanju Tiwari, M. A. Jabbar, Ejder Ayçın, Zeki Atıl Bulut and Ömer Faruk Beyca. Their work appears in journals such as Applied Sciences, Journal of theoretical and applied electronic commerce research, Complex & Intelligent Systems, Expert Systems with Applications and Journal of Intelligent & Fuzzy 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.