Devon K. Barrow

2.0k citations
16 papers · 806 · h-index 13

Impact in

Papers in

Devon K. Barrow

16 papers receiving 787 citations

Peers

Devon K. Barrow
Comparison fields: 5 of 108
  • Management Science and Operations Research 437
  • Management Information Systems 100
  • Statistics, Probability and Uncertainty 50
  • Computer Science Applications 39
  • Signal Processing 63
Replace Hsiao–Cheng Yu with:
Hsiao–Cheng Yu Taiwan
Mariano Luque Spain
Sajid Siraj United Kingdom
Zaiyong Tang United States
Müjgân Sağır Türkiye
Roberta Parreiras Brazil
Hamidreza Eskandari Iran
Seng Hansun Indonesia
Neamat El Gayar Egypt
Ru‐xin Nie China
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Citations per field
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Hsiao–Cheng Yu · 1×
Citations per year

Countries citing papers authored by Devon K. Barrow

Since Specialization
Citations

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

Fields of papers citing papers by Devon K. Barrow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Devon K. Barrow. 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 Devon K. Barrow. The network helps show where Devon K. Barrow may publish in the future.

Co-authors

The 8 scholars most cited alongside Devon K. Barrow, 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 Devon K. Barrow Line = papers co-authored together Devon K. Barrow links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 2014204
2 201881
3 201675
4 201663
5 201959
6 201657
7 201256
8 201742
9 201639
10 202038
11 201031
12 201329
13 201628
14
Dynamic Model Selection and Combination in Forecasting: an Empirical Evaluation of Bagging and Boosting
20112
15 20241
16 20191

About Devon K. Barrow

Devon K. Barrow is a scholar working on Management Science and Operations Research, Artificial Intelligence, Electrical and Electronic Engineering, General Economics, Econometrics and Finance and Statistics, Probability and Uncertainty, having authored 16 papers that have together received 806 indexed citations. Recurring topics across this work include Forecasting Techniques and Applications (13 papers), Stock Market Forecasting Methods (10 papers), Energy Load and Power Forecasting (4 papers), Neural Networks and Applications (3 papers), Intelligent Tutoring Systems and Adaptive Learning (2 papers), Advanced Statistical Process Monitoring (2 papers), Monetary Policy and Economic Impact (2 papers) and Advanced Statistical Methods and Models (1 paper). The work is most often cited by research in Management Science and Operations Research (437 citations), Management Information Systems (100 citations), Statistics, Probability and Uncertainty (50 citations), Computer Science Applications (39 citations) and Signal Processing (63 citations). Devon K. Barrow has collaborated with scholars based in United Kingdom, Sweden and New Zealand. Frequent co-authors include Nikolaos Kourentzes, Sven F. Crone, Fotios Petropoulos, Juan R. Trapero, Stellan Ohlsson, Antonija Mitrović, Bahman Rostami-Tabar and Mohammad Ali. Their work appears in journals such as International Journal of Production Economics, International Journal of Forecasting, Journal of Business Research, Expert Systems with Applications and Computers & Education.

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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