Danny Segev

1.8k total citations
82 papers, 862 citations indexed

About

Danny Segev is a scholar working on Management Information Systems, Computer Networks and Communications and Computational Theory and Mathematics. According to data from OpenAlex, Danny Segev has authored 82 papers receiving a total of 862 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Management Information Systems, 29 papers in Computer Networks and Communications and 25 papers in Computational Theory and Mathematics. Recurrent topics in Danny Segev's work include Supply Chain and Inventory Management (32 papers), Optimization and Search Problems (28 papers) and Consumer Market Behavior and Pricing (22 papers). Danny Segev is often cited by papers focused on Supply Chain and Inventory Management (32 papers), Optimization and Search Problems (28 papers) and Consumer Market Behavior and Pricing (22 papers). Danny Segev collaborates with scholars based in Israel, United States and United Kingdom. Danny Segev's co-authors include Ali Aouad, Retsef Levi, Vineet Goyal, Antoine Désir, Vivek F. Farias, Chun Ye, Asaf Levin, Jacob Feldman, Refael Hassin and Ojas Parekh and has published in prestigious journals such as Management Science, Operations Research and Journal of Theoretical Biology.

In The Last Decade

Danny Segev

74 papers receiving 822 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Danny Segev Israel 18 343 278 224 192 177 82 862
S. Raghavan United States 18 68 0.2× 86 0.3× 176 0.8× 179 0.9× 141 0.8× 68 952
Shoshana Anily Israel 23 385 1.1× 74 0.3× 229 1.0× 139 0.7× 86 0.5× 50 1.5k
Jon Feldman United States 21 122 0.4× 288 1.0× 1.3k 5.7× 365 1.9× 128 0.7× 47 1.7k
Grégory Zacharewicz France 15 228 0.7× 54 0.2× 83 0.4× 166 0.9× 35 0.2× 77 756
Isabel Méndez‐Díaz Argentina 13 276 0.8× 214 0.8× 141 0.6× 244 1.3× 95 0.5× 28 780
Aranyak Mehta United States 18 193 0.6× 318 1.1× 1.0k 4.6× 1.1k 5.9× 300 1.7× 50 1.8k
José Correa Chile 18 141 0.4× 140 0.5× 367 1.6× 544 2.8× 115 0.6× 87 1.3k
Manu De Backer Belgium 13 513 1.5× 32 0.1× 94 0.4× 75 0.4× 72 0.4× 35 1.0k
Gagan Aggarwal United States 15 49 0.1× 269 1.0× 303 1.4× 437 2.3× 119 0.7× 32 1.2k
Wai Ki Ching Hong Kong 11 312 0.9× 77 0.3× 28 0.1× 62 0.3× 67 0.4× 35 788

Countries citing papers authored by Danny Segev

Since Specialization
Citations

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

Fields of papers citing papers by Danny Segev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Danny Segev. 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 Danny Segev. The network helps show where Danny Segev may publish in the future.

Co-authorship network of co-authors of Danny Segev

This figure shows the co-authorship network connecting the top 25 collaborators of Danny Segev. A scholar is included among the top collaborators of Danny Segev 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 Danny Segev. Danny Segev 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.
Aouad, Ali, Jacob Feldman, Danny Segev, & Dennis Zhang. (2024). The Click-Based MNL Model: A Framework for Modeling Click Data in Assortment Optimization. Management Science. 71(8). 6943–6960. 4 indexed citations
2.
Segev, Danny. (2024). Near-Optimal Adaptive Policies for Serving Stochastically Departing Customers. Operations Research. 73(5). 2744–2760.
3.
Feldman, Jacob, et al.. (2023). Assortment Optimization Under the Multi-Purchase Multinomial Logit Choice Model. Operations Research. 72(6). 2631–2664. 9 indexed citations
4.
Segev, Danny, et al.. (2023). Maximum Load Assortment Optimization: Approximation Algorithms and Adaptivity Gaps. SSRN Electronic Journal.
5.
Aouad, Ali, Jacob Feldman, & Danny Segev. (2022). The Exponomial Choice Model for Assortment Optimization: An Alternative to the MNL Model?. Management Science. 69(5). 2814–2832. 11 indexed citations
6.
Feldman, Jacob & Danny Segev. (2022). Technical Note—The Multinomial Logit Model with Sequential Offerings: Algorithmic Frameworks for Product Recommendation Displays. Operations Research. 70(4). 2162–2184. 14 indexed citations
7.
Aouad, Ali & Danny Segev. (2020). Display Optimization for Vertically Differentiated Locations Under Multinomial Logit Preferences. Management Science. 67(6). 3519–3550. 32 indexed citations
8.
Segev, Danny. (2018). Assortment Planning with Nested Preferences: Dynamic Programming with Distributions as States?. Algorithmica. 81(1). 393–417. 6 indexed citations
9.
Gamzu, Iftah, et al.. (2016). Approximation algorithms for sequential batch‐testing of series systems. Naval Research Logistics (NRL). 63(4). 275–286. 9 indexed citations
10.
Désir, Antoine, Vineet Goyal, Srikanth Jagabathula, & Danny Segev. (2016). Assortment Optimization Under the Mallows model. Neural Information Processing Systems. 29. 4700–4708. 7 indexed citations
11.
Segev, Danny, et al.. (2013). The Approximability of Shortest Path-Based Graph Orientations of Protein–Protein Interaction Networks. Journal of Computational Biology. 20(12). 945–957. 3 indexed citations
12.
Segev, Danny. (2013). An Approximate Dynamic-Programming Approach to the Joint Replenishment Problem. Mathematics of Operations Research. 39(2). 432–444. 7 indexed citations
13.
Nov, Yuval & Danny Segev. (2013). Optimal codon randomization via mathematical programming. Journal of Theoretical Biology. 335. 147–152. 3 indexed citations
14.
Segev, Danny, et al.. (2012). Approximation algorithms for orienting mixed graphs. Theoretical Computer Science. 483. 96–103. 4 indexed citations
15.
Bafna, Vineet, Iftah Gamzu, Danny Segev, et al.. (2011). On the Approximability of Reachability-Preserving Network Orientations. Internet Mathematics. 7(4). 209–232. 4 indexed citations
16.
Epstein, Leah, Asaf Levin, Julián Mestre, & Danny Segev. (2010). Improved Approximation Guarantees for Weighted Matching in the Semi-Streaming Model. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 5. 347–358. 11 indexed citations
17.
Chekuri, Chandra, Guy Even, Anupam Gupta, & Danny Segev. (2008). Set connectivity problems in undirected graphs and the directed Steiner network problem. Symposium on Discrete Algorithms. 532–541. 19 indexed citations
18.
Segev, Danny & Gil Segev. (2008). Approximate k-Steiner Forests via the Lagrangian Relaxation Technique with Internal Preprocessing. Algorithmica. 56(4). 529–549. 3 indexed citations
19.
Segev, Danny, et al.. (2007). Role of Intensive Counseling in Smoking Cessation. A Multicausal Prospective Study in the Primary Care Setting. Redalyc (Universidad Autónoma del Estado de México).
20.
Mory, Y, Danny Segev, Batya Cohen, et al.. (1986). Efficient Constitutive Production of Human IFN-γ in Chinese Hamster Ovary Cells. DNA. 5(3). 181–193. 27 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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