Dries F. Benoit

1.7k total citations
38 papers, 1.2k citations indexed

About

Dries F. Benoit is a scholar working on Artificial Intelligence, Marketing and Information Systems. According to data from OpenAlex, Dries F. Benoit has authored 38 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 9 papers in Marketing and 7 papers in Information Systems. Recurrent topics in Dries F. Benoit's work include Customer churn and segmentation (8 papers), Consumer Market Behavior and Pricing (6 papers) and Imbalanced Data Classification Techniques (5 papers). Dries F. Benoit is often cited by papers focused on Customer churn and segmentation (8 papers), Consumer Market Behavior and Pricing (6 papers) and Imbalanced Data Classification Techniques (5 papers). Dries F. Benoit collaborates with scholars based in Belgium, France and United Kingdom. Dries F. Benoit's co-authors include Dirk Van den Poel, Kristof Coussement, Rahim Alhamzawi, Keming Yu, Philippe Baecke, Annelies Raes, Chris Develder, Arno De Caigny, Vu Minh Hieu Phan and Nico Van de Weghe and has published in prestigious journals such as Applied Energy, European Journal of Operational Research and Computers in Human Behavior.

In The Last Decade

Dries F. Benoit

38 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dries F. Benoit Belgium 22 321 220 197 133 117 38 1.2k
József Mezei Finland 16 375 1.2× 104 0.5× 93 0.5× 107 0.8× 282 2.4× 59 1.2k
Khai Wah Khaw Malaysia 23 131 0.4× 158 0.7× 141 0.7× 53 0.4× 117 1.0× 85 1.3k
Krishnamurty Muralidhar United States 19 557 1.7× 517 2.4× 81 0.4× 190 1.4× 263 2.2× 56 1.8k
Xin Fu China 19 186 0.6× 86 0.4× 35 0.2× 155 1.2× 110 0.9× 58 982
Junhua Hu China 23 394 1.2× 132 0.6× 249 1.3× 98 0.7× 1.0k 8.9× 71 1.7k
Fang-Mei Tseng Taiwan 21 340 1.1× 119 0.5× 94 0.5× 117 0.9× 790 6.8× 54 1.8k
Salman Nazari-Shirkouhi Iran 20 218 0.7× 105 0.5× 49 0.2× 87 0.7× 600 5.1× 62 1.7k
Guangxu Li China 16 411 1.3× 62 0.3× 92 0.5× 107 0.8× 774 6.6× 27 1.3k
XinYing Chew Malaysia 17 112 0.3× 89 0.4× 98 0.5× 43 0.3× 73 0.6× 77 727
J. Douglas Barrett United States 10 190 0.6× 96 0.4× 150 0.8× 19 0.1× 193 1.6× 24 1.0k

Countries citing papers authored by Dries F. Benoit

Since Specialization
Citations

This map shows the geographic impact of Dries F. Benoit'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 Dries F. Benoit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dries F. Benoit more than expected).

Fields of papers citing papers by Dries F. Benoit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dries F. Benoit. 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 Dries F. Benoit. The network helps show where Dries F. Benoit may publish in the future.

Co-authorship network of co-authors of Dries F. Benoit

This figure shows the co-authorship network connecting the top 25 collaborators of Dries F. Benoit. A scholar is included among the top collaborators of Dries F. Benoit 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 Dries F. Benoit. Dries F. Benoit 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.
Bogaert, Matthias, et al.. (2025). Evaluating the stability of model explanations in instance-dependent cost-sensitive credit scoring. European Journal of Operational Research. 326(3). 630–640. 2 indexed citations
2.
Coussement, Kristof, et al.. (2024). Incorporating usage data for B2B churn prediction modeling. Industrial Marketing Management. 120. 191–205. 3 indexed citations
3.
Benoit, Dries F., et al.. (2023). Explainability through uncertainty: Trustworthy decision-making with neural networks. European Journal of Operational Research. 317(2). 330–340. 13 indexed citations
4.
Benoit, Dries F., et al.. (2023). High-stake student drop-out prediction using hidden Markov models in fully asynchronous subscription-based MOOCs. Technological Forecasting and Social Change. 198. 123009–123009. 4 indexed citations
5.
Benoit, Dries F., et al.. (2021). Embedding navigation patterns for student performance prediction. Ghent University Academic Bibliography (Ghent University). 2 indexed citations
6.
Benoit, Dries F., et al.. (2021). Towards the application of calibrated Transformers to the unsupervised estimation of question difficulty from text. Ghent University Academic Bibliography (Ghent University). 846–855. 1 indexed citations
7.
Coussement, Kristof & Dries F. Benoit. (2021). Interpretable data science for decision making. Decision Support Systems. 150. 113664–113664. 44 indexed citations
8.
Benoit, Dries F., et al.. (2021). Forecasting directional bitcoin price returns using aspect-based sentiment analysis on online text data. Machine Learning. 113(7). 4761–4784. 28 indexed citations
9.
Benoit, Dries F., Stefan Lessmann, & Wouter Verbeke. (2020). On realising the utopian potential of big data analytics for maximising return on marketing investments. Journal of Marketing Management. 36(3-4). 233–247. 21 indexed citations
10.
Sadeghianpourhamami, Nasrin, Dries F. Benoit, Dirk Deschrijver, & Chris Develder. (2018). Modeling Real-World Flexibility of Residential Power Consumption. Ghent University Academic Bibliography (Ghent University). 408–410. 2 indexed citations
11.
12.
Benoit, Dries F., et al.. (2017). Incorporating sequential information in bankruptcy prediction with predictors based on Markov for discrimination. Decision Support Systems. 98. 59–68. 35 indexed citations
13.
Benoit, Dries F. & Dirk Van den Poel. (2017). bayesQR: A Bayesian Approach to Quantile Regression. Journal of Statistical Software. 76(7). 70 indexed citations
14.
Baecke, Philippe, et al.. (2016). Identifying influencers in a social network: The value of real referral data. Decision Support Systems. 91. 25–36. 49 indexed citations
15.
Raes, Annelies, Tammy Schellens, Bram De Wever, & Dries F. Benoit. (2016). Promoting metacognitive regulation through collaborative problem solving on the web: When scripting does not work. Computers in Human Behavior. 58. 325–342. 42 indexed citations
16.
Coussement, Kristof, Paul Harrigan, & Dries F. Benoit. (2015). Improving direct mail targeting through customer response modeling. Expert Systems with Applications. 42(22). 8403–8412. 15 indexed citations
17.
Benoit, Dries F., Rahim Alhamzawi, & Keming Yu. (2013). Bayesian lasso binary quantile regression. Computational Statistics. 28(6). 2861–2873. 34 indexed citations
18.
Alhamzawi, Rahim, Keming Yu, & Dries F. Benoit. (2012). Bayesian adaptive Lasso quantile regression. Statistical Modelling. 12(3). 279–297. 111 indexed citations
19.
Benoit, Dries F., Rahim Alhamzawi, Keming Yu, & Dirk Van den Poel. (2011). bayesQR: Bayesian quantile regression. Ghent University Academic Bibliography (Ghent University). 11 indexed citations
20.
Coussement, Kristof, Dries F. Benoit, & Dirk Van den Poel. (2009). Improved marketing decision making in a customer churn prediction context using generalized additive models. Expert Systems with Applications. 37(3). 2132–2143. 79 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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