Tim Hill

2.4k citations
43 papers · 1.8k · h-index 17

Impact in

    • Forecasting Techniques and Applications
    • Stock Market Forecasting Methods
  • Marketing top 2%
    • Consumer Behavior in Brand Consumption and Identification
    • Consumer Retail Behavior Studies
    • Environmental Sustainability in Business

Papers in

Tim Hill

40 papers receiving 1.6k citations

Peers

Tim Hill
Comparison fields: 5 of 156
  • Management Science and Operations Research 498
  • Marketing 250
  • Physiology 39
  • Sensory Systems 34
  • Signal Processing 56
Replace Le Wang with:
Le Wang China
Eric W. Zivot United States
Fernanda Strozzi Italy
Jun Li China
Aman Ullah United States
Anindya Banerjee United Kingdom
Dilek Önkal United Kingdom
Kuan‐Yu Chen Taiwan
Ryuichi Kitamura Japan
Tim Hill relative to Le Wang China Le Wang's profile →
Citations per field
00.5×2×4×6.8×
Le Wang · 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 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996377
2 1994360
3 1999137
4 1994114
5 2014114
6 2021104
7 201594
8 201754
9 201647
10 198846
11 199443
12 200232
13 198830
14 199825
15 198923
16 199223
17 200221
18 198917
19 200215
20 199412

About Tim Hill

Tim Hill is a scholar working on Marketing, Management Science and Operations Research, Sociology and Political Science, Gender Studies and Artificial Intelligence, having authored 43 papers that have together received 1.8k indexed citations. Recurring topics across this work include Consumer Behavior in Brand Consumption and Identification (8 papers), Forecasting Techniques and Applications (6 papers), Neural Networks and Applications (5 papers), Educational Leadership and Practices (4 papers), School Leadership and Teacher Performance (3 papers), Physical Education and Sports Studies (3 papers), Sports, Gender, and Society (3 papers) and Consumer Retail Behavior Studies (3 papers). The work is most often cited by research in Management Science and Operations Research (498 citations), Marketing (250 citations), Physiology (39 citations), Sensory Systems (34 citations) and Signal Processing (56 citations). Tim Hill has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include William Remus, Marcus J. O’Connor, Leorey Marquez, Robin Canniford, Sandra Acker, Joeri M. Mol, Giana M. Eckhardt, Michael Gerhard Luchs, Marcus Phipps and Alton L. Boynton. Their work appears in journals such as Marketing Theory, Sociology, SAE technical papers on CD-ROM/SAE technical paper series, Journal of Marketing and Journal of Forecasting.

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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