David Chan
- Statistics and Probability top 2%
- Statistical Methods and Inference 5
- Finance top 5%
- Financial Risk and Volatility Modeling 3
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- Hospitality and Tourism Education 3
- Marketing top 10%
- Consumer Market Behavior and Pricing 3
- Artificial Intelligence top 10%
- Bayesian Methods and Mixture Models 5
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- International Student and Expatriate Challenges 3
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- Monetary Policy and Economic Impact 2
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- Human Resource and Talent Management 2
David Chan
14 papers receiving 416 citations
Peers
Comparison fields: 5 of 80
- Statistics and Probability 204
- Finance 94
- Tourism, Leisure and Hospitality Management 13
- Marketing 59
- Artificial Intelligence 153
Countries citing papers authored by David Chan
This map shows the geographic impact of David Chan'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 David Chan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Chan more than expected).
Fields of papers citing papers by David Chan
This network shows the impact of papers produced by David Chan. 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 David Chan. The network helps show where David Chan may publish in the future.
Co-authorship network
The 13 scholars most cited alongside David Chan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 10 | |
| 2 | 2018 | 3 | |
| 3 | Bayesian Methods for Media Mix Modeling with Carryover and Shape Effects | 2017 | 6 |
| 4 | Geo-level Bayesian Hierarchical Media Mix Modeling | 2017 | 1 |
| 5 | Challenges and Opportunities in Media Mix Modeling | 2017 | 8 |
| 6 | A Hierarchical Bayesian Approach to Improve Media Mix Models Using Category Data | 2017 | 2 |
| 7 | 2016 | 10 | |
| 8 | 2016 | 2 | |
| 9 | 2011 | 21 | |
| 10 | 2010 | 54 | |
| 11 | 2006 | 22 | |
| 12 | 2006 | 3 | |
| 13 | 2006 | 161 | |
| 14 | 2006 | 21 | |
| 15 | 2005 | 2 | |
| 16 | 2001 | 129 |
About David Chan
David Chan is a scholar working on Tourism, Leisure and Hospitality Management, Statistics and Probability, Communication, Marketing and General Social Sciences, having authored 16 papers that have together received 455 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (5 papers), Statistical Methods and Inference (5 papers), Financial Risk and Volatility Modeling (3 papers), Hospitality and Tourism Education (3 papers), Consumer Market Behavior and Pricing (3 papers), International Student and Expatriate Challenges (3 papers), Monetary Policy and Economic Impact (2 papers) and Human Resource and Talent Management (2 papers). The work is most often cited by research in Statistics and Probability (204 citations), Finance (94 citations), Tourism, Leisure and Hospitality Management (13 citations), Marketing (59 citations) and Artificial Intelligence (153 citations). David Chan has collaborated with scholars based in United States, Australia and China. Frequent co-authors include Robert Kohn, M. Pitt, Michael S. Smith, Chris Kirby, Rong Ge, Diane Lambert, Tim Hesterberg, Jim Koehler, Honggang Xu and David J. Nott. Their work appears in journals such as Journal of China Tourism Research, Journal of Advertising Research, Biometrika, Statistics and Computing and International Journal of Hospitality 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.