Jay E. Aronson

71 papers receiving 4.2k citations

Jay E. Aronson's Hit Papers

Business Intelligence 2007 · 688 citations
6880+9+19Years since publication50010001.5k

Peers

Jay E. Aronson
Comparison fields: 5 of 152
  • Management Information Systems 1.6k
  • Communication 514
  • Information Systems and Management 498
  • Strategy and Management 1.0k
  • Management Science and Operations Research 718
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Ramesh Sharda United States
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Citations per year

Countries citing papers authored by Jay E. Aronson

Since Specialization
Citations

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

Fields of papers citing papers by Jay E. Aronson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay E. Aronson. 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 Jay E. Aronson. The network helps show where Jay E. Aronson may publish in the future.

Co-authors

The 25 scholars most cited alongside Jay E. Aronson, 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 Jay E. Aronson Line = papers co-authored together Jay E. Aronson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Decision support systems and intelligent systems
Hit paper breakdown →
19971782
2
Business Intelligence
Hit paper breakdown →
2007688
3 2000368
4 1989213
5 2008192
6
Resource-Based View of Knowledge Management for Competitive Advantage
2005183
7 1998160
8
Decision Support Systems and Intelligent Systems (7th Edition)
2004159
9
Decision Support and Business Intelligence Systems (8th Edition)
2006114
10 2006108
11 1985102
12 199990
13 200485
14 199769
15 199159
16 199851
17 198940
18 200435
19 200934
20 199927

About Jay E. Aronson

Jay E. Aronson is a scholar working on Management Information Systems, Communication, Industrial and Manufacturing Engineering, Strategy and Management and Transportation, having authored 72 papers that have together received 5.0k indexed citations. Recurring topics across this work include Knowledge Management and Sharing (14 papers), Transportation Planning and Optimization (9 papers), Team Dynamics and Performance (7 papers), Big Data and Business Intelligence (6 papers), Technology Adoption and User Behaviour (6 papers), Vehicle Routing Optimization Methods (6 papers), Innovation and Knowledge Management (5 papers) and Scheduling and Optimization Algorithms (5 papers). The work is most often cited by research in Management Information Systems (1.6k citations), Communication (514 citations), Information Systems and Management (498 citations), Strategy and Management (1.0k citations) and Management Science and Operations Research (718 citations). Jay E. Aronson has collaborated with scholars based in United States, Austria and Latvia. Frequent co-authors include Efraim Turban, Richard V. McCarthy, Leila Halawi, Ramesh Sharda, David R. King, Dursun Delen, Lakshmi Iyer, Babita Gupta, Ting‐Peng Liang and Kathryn E. Stecke. Their work appears in journals such as Journal of the Association for Information Systems, European Journal of Operational Research, Management Science, Annals of Operations Research and Information Systems Research.

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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