Tim Hill

2.3k citations
40 papers · 1.6k · 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

35 papers receiving 1.5k citations

Peers

Tim Hill
Comparison fields: 5 of 173
  • Management Science and Operations Research 467
  • Marketing 210
  • Tourism, Leisure and Hospitality Management 27
  • Artificial Intelligence 345
  • Gender Studies 80
Replace Gopal K. Kanji with:
Gopal K. Kanji United Kingdom
Fred Collopy United States
Erjia Yan United States
Jingjing Li China
Emmanuel Sirimal Silva United Kingdom
Fernanda Strozzi Italy
J Courtial France
Julia Neidhardt Austria
Concepción S. Wilson Australia
B. Chandra India
Tim Hill relative to Gopal K. Kanji United Kingdom Gopal K. Kanji's profile →
Citations per field
00.5×4.7×
Gopal K. Kanji · 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 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996344
2 1994330
3 1999124
4 1994108
5 2014105
6 202186
7 201577
8 201746
9 198844
10 199442
11 201641
12 200231
13 198830
14 199425
15 199822
16 198920
17 200220
18 198917
19 199217
20 199414

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 40 papers that have together received 1.6k 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), Digital Marketing and Social Media (3 papers), Reservoir Engineering and Simulation Methods (3 papers), Fuzzy Logic and Control Systems (3 papers) and Transportation Safety and Impact Analysis (2 papers). The work is most often cited by research in Management Science and Operations Research (467 citations), Marketing (210 citations), Tourism, Leisure and Hospitality Management (27 citations), Artificial Intelligence (345 citations) and Gender Studies (80 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, Giana M. Eckhardt, Michael G. Luchs, Marcus Phipps, Alton L. Boynton and Henrik Kindmark. Their work appears in journals such as Marketing Theory, SAE technical papers on CD-ROM/SAE technical paper series, Journal of Marketing Management, Journal of Marketing and Sociology.

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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