Tim Hill

2.4k citations
46 papers · 1.8k · h-index 18

Impact in

Papers in

    • Neural Networks and Applications 7
    • Fuzzy Logic and Control Systems 3
    • Consumer Behavior in Brand Consumption and Identification 6

Tim Hill

41 papers receiving 1.7k citations

Peers

Tim Hill
Comparison fields: 5 of 171
  • Management Science and Operations Research 532
  • Marketing 226
  • Tourism, Leisure and Hospitality Management 29
  • Artificial Intelligence 391
  • Gender Studies 87
Replace Fred Collopy with:
Fred Collopy United States
Gopal K. Kanji United Kingdom
Erjia Yan United States
Emmanuel Sirimal Silva United Kingdom
Jingjing Li China
Julia Neidhardt Austria
Min Song South Korea
Fernanda Strozzi Italy
Huy Quan Vu Australia
Tim Hill relative to Fred Collopy United States Fred Collopy's profile →
Citations per field
00.5×4.7×
Fred Collopy · 1×
Citations per year

Countries citing papers authored by Tim Hill

Since Specialization
Citations

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

Fields of papers citing papers by Tim Hill

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996380
2 1994363
3 1999144
4 1994119
5 2014114
6 202194
7 201587
8 201754
9 201648
10 198846
11 199443
12 200232
13 198831
14 199428
15 199825
16 199225
17 198922
18 200221
19 198917
20 200215

About Tim Hill

Tim Hill is a scholar working on Artificial Intelligence, Marketing, Sociology and Political Science, Management Science and Operations Research and Education, having authored 46 papers that have together received 1.8k indexed citations. Recurring topics across this work include Neural Networks and Applications (7 papers), Consumer Behavior in Brand Consumption and Identification (6 papers), Stock Market Forecasting Methods (4 papers), Forecasting Techniques and Applications (4 papers), Culinary Culture and Tourism (3 papers), Fuzzy Logic and Control Systems (3 papers), Digital Marketing and Social Media (3 papers) and Reservoir Engineering and Simulation Methods (3 papers). The work is most often cited by research in Management Science and Operations Research (532 citations), Marketing (226 citations), Tourism, Leisure and Hospitality Management (29 citations), Artificial Intelligence (391 citations) and Gender Studies (87 citations). Tim Hill has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include William Remus, Marcus O’Connor, Leorey Marquez, Robin Canniford, Sandra Acker, Joeri Mol, Giana M. Eckhardt, Marcus Phipps, Michael G. Luchs and Alton L. Boynton. Their work appears in journals such as SAE technical papers on CD-ROM/SAE technical paper series, Marketing Theory, Journal of Marketing, Sociology and Journal of Marketing Management.

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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