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 18
- Big Data and Business Intelligence 8
- Marketing 11
- Customer churn and segmentation 11
- Co-authors
- Başar Öztayşi (10 shared papers)Cengiz Kahraman (2 shared papers)Muhammet Deveci (1 shared paper)Fatih Canıtez (1 shared paper)Carlos Fernández-Llatas (4 shared papers)Sanju Tiwari (2 shared papers)M. A. Jabbar (1 shared paper)Zeki Atıl Bulut (1 shared paper)
In The Last Decade
Onur Doğan
56 papers receiving 559 citations
Peers
Comparison fields: 5 of 98
- Management Information Systems 109
- Management Science and Operations Research 142
- Marketing 85
- Health Informatics 8
- Health Information Management 22
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 58 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 80 | |
| 2 | 2019 | 78 | |
| 3 | 2021 | 54 | |
| 4 | CUSTOMER SEGMENTATION BY USING RFM MODEL AND CLUSTERING METHODS: A CASE STUDY IN RETAIL INDUSTRY | 2018 | 40 |
| 5 | 2019 | 35 | |
| 6 | 2022 | 23 | |
| 7 | 2019 | 21 | |
| 8 | 2013 | 21 | |
| 9 | 2022 | 18 | |
| 10 | 2018 | 17 | |
| 11 | 2019 | 16 | |
| 12 | 2021 | 16 | |
| 13 | 2023 | 12 | |
| 14 | 2019 | 12 | |
| 15 | 2020 | 10 | |
| 16 | 2022 | 10 | |
| 17 | 2017 | 9 | |
| 18 | 2022 | 7 | |
| 19 | 2018 | 6 | |
| 20 | 2018 | 6 |
About Onur Doğan
Onur Doğan is a scholar working on Management Information Systems, Marketing, Management Science and Operations Research, Information Systems and Artificial Intelligence, having authored 58 papers that have together received 576 indexed citations. Recurring topics across this work include Business Process Modeling and Analysis (18 papers), Customer churn and segmentation (11 papers), Big Data and Business Intelligence (8 papers), Multi-Criteria Decision Making (7 papers), Data Mining Algorithms and Applications (4 papers), Digital Transformation in Industry (4 papers), Service-Oriented Architecture and Web Services (3 papers) and Customer Service Quality and Loyalty (3 papers). The work is most often cited by research in Management Information Systems (109 citations), Management Science and Operations Research (142 citations), Marketing (85 citations), Health Informatics (8 citations) and Health Information Management (22 citations). Onur Doğan has collaborated with scholars based in Türkiye, Italy and Spain. Frequent co-authors include Başar Öztayşi, Cengiz Kahraman, Muhammet Deveci, Fatih Canıtez, Carlos Fernández-Llatas, Sanju Tiwari, M. A. Jabbar, Zeki Atıl Bulut, Ejder Ayçın and Ömer Faruk Beyca. Their work appears in journals such as Applied Sciences, Journal of theoretical and applied electronic commerce research, Expert Systems with Applications, Complex & Intelligent Systems 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.