David Pardoe

748 citations
20 papers · 436 · h-index 12

Impact in

Papers in

David Pardoe

20 papers receiving 391 citations

Peers

David Pardoe
Comparison fields: 5 of 108
  • Management Science and Operations Research 131
  • Management Information Systems 69
  • Marketing 62
  • Artificial Intelligence 168
  • Industrial and Manufacturing Engineering 41
Replace Sung-Hyuk Park with:
Sung-Hyuk Park South Korea
Will Ma United States
Segev Wasserkrug Israel
Ester Samuel‐Cahn Israel
H.S. Wang Taiwan
Romy Shioda Canada
Ross Anderson United Kingdom
Belén Martín-Barragán United Kingdom
Y. S. Chow Singapore
Chih-Chung Lo Taiwan
David Pardoe relative to Sung-Hyuk Park South Korea Sung-Hyuk Park's profile →
Citations per field
00.5×5.7×
Sung-Hyuk Park · 1×
Citations per year

Countries citing papers authored by David Pardoe

Since Specialization
Citations

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

Fields of papers citing papers by David Pardoe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside David Pardoe, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Pardoe Line = papers co-authored together David Pardoe links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1
Boosting for Regression Transfer
201090
2 199672
3
Learning predictive state representations
200369
4
An Autonomous Agent for Supply Chain Management
200727
5
Predictive planning for supply chain management
200625
6 201621
7 200520
8 200419
9 200615
10
TacTex-05: a champion supply chain management agent
200614
11 200912
12 200512
13 20048
14 20107
15 20077
16
Bidding for Customer Orders in TAC SCM
20045
17 20044
18
TacTex09: Champion of the First Trading Agent Competition on Ad Auctions
20104
19 19963
20 20112

About David Pardoe

David Pardoe is a scholar working on Management Science and Operations Research, Marketing, Artificial Intelligence, Industrial and Manufacturing Engineering and Molecular Biology, having authored 20 papers that have together received 436 indexed citations. Recurring topics across this work include Auction Theory and Applications (12 papers), Consumer Market Behavior and Pricing (8 papers), Multi-Agent Systems and Negotiation (4 papers), Scheduling and Optimization Algorithms (4 papers), Hermeneutics and Narrative Identity (2 papers), Computational Drug Discovery Methods (2 papers), Animal Ecology and Behavior Studies (2 papers) and Health, Medicine and Society (2 papers). The work is most often cited by research in Management Science and Operations Research (131 citations), Management Information Systems (69 citations), Marketing (62 citations), Artificial Intelligence (168 citations) and Industrial and Manufacturing Engineering (41 citations). David Pardoe has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include Peter Stone, Donald B. White, K Bachmann, Nicholas K. Jong, Satinder Singh, Michael L. Littman, Risto Miikkulainen, Michael S. Ryoo, Maytal Saar‐Tsechansky and Haishan Liu. Their work appears in journals such as Environmental Health Perspectives, INFORMS journal on computing, International Conference on Automated Planning and Scheduling, Adaptive Agents and Multi-Agents Systems and ACM SIGecom Exchanges.

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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