Alan J. King

50 papers receiving 1.4k citations

Peers

Alan J. King
Comparison fields: 5 of 107
  • Management Science and Operations Research 674
  • Management Information Systems 261
  • Finance 263
  • Numerical Analysis 139
  • Statistics and Probability 152
Replace Julia L. Higle with:
Julia L. Higle United States
Rüdiger Schultz Germany
Miguel A. Lejeune United States
Jitka Dupačová Czechia
A. Hadi‐Vencheh Iran
Dessislava A. Pachamanova United States
Pankaj Gupta India
Mehrdad Tamiz United Kingdom
Aurélie Thiele United States
Alan J. King relative to Julia L. Higle United States Julia L. Higle's profile →
Citations per field
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Citations per year

Countries citing papers authored by Alan J. King

Since Specialization
Citations

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

Fields of papers citing papers by Alan J. King

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alan J. King. 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 Alan J. King. The network helps show where Alan J. King may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003238
2 2012189
3 1993137
4 1993133
5 199199
6 199280
7
A Standard Input Format for Multiperiod Stochastic Linear Programs
198771
8 200268
9 200263
10 199543
11 199843
12 199343
13 199530
14 198927
15 198926
16 199223
17 199222
18 200819
19 200417
20
On Their Own?: Making the Transition from School to Work in the Information Age
199915

About Alan J. King

Alan J. King is a scholar working on Management Science and Operations Research, Finance, Economics and Econometrics, Computational Theory and Mathematics and Statistics and Probability, having authored 53 papers that have together received 1.5k indexed citations. Recurring topics across this work include Risk and Portfolio Optimization (14 papers), Economic theories and models (6 papers), Fuzzy Systems and Optimization (6 papers), Stochastic processes and financial applications (5 papers), Optimization and Variational Analysis (5 papers), Optimization and Mathematical Programming (4 papers), Financial Markets and Investment Strategies (3 papers) and Supply Chain and Inventory Management (3 papers). The work is most often cited by research in Management Science and Operations Research (674 citations), Management Information Systems (261 citations), Finance (263 citations), Numerical Analysis (139 citations) and Statistics and Probability (152 citations). Alan J. King has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include R. T. Rockafellar, Stein W. Wallace, Roger J.‐B. Wets, Gyana R. Parija, Shabbir Ahmed, Pasumarti V. Kamesam, Laureano F. Escudero, Yuri M. Kaniovski, Matthew King and William Pickett. Their work appears in journals such as The Medical Journal of Australia, Annals of Operations Research, IBM Systems Journal, Mathematical Programming and Mathematics of Operations 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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