Deepa Chandrasekaran
- Marketing top 5%
- Consumer Market Behavior and Pricing 4
- Consumer Behavior in Brand Consumption and Identification 3
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- Innovation Diffusion and Forecasting 9
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- Open Source Software Innovations 4
- Strategy and Management top 10%
- Digital Platforms and Economics 4
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- Firm Innovation and Growth 6
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- Digital Marketing and Social Media 2
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- Customer Service Quality and Loyalty 2
- Co-authors
- Gerard J. TellisSuman BasuroyGaia RuberaAndrea OrdaniniRaji SrinivasanGareth JamesJoep ArtsR.T. Frambach
- Journals
- Journal of Marketing (4 papers)Journal of Business Ethics (1 paper)Journal of the Academy of Marketing Science (2 papers)
- Partner nations
- United StatesCanadaNetherlands
In The Last Decade
Deepa Chandrasekaran
19 papers receiving 495 citations
Peers
Comparison fields: 5 of 76
- Marketing 180
- Management Science and Operations Research 201
- Business and International Management 31
- Computer Science Applications 60
- Strategy and Management 147
Countries citing papers authored by Deepa Chandrasekaran
This map shows the geographic impact of Deepa Chandrasekaran'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 Deepa Chandrasekaran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deepa Chandrasekaran more than expected).
Fields of papers citing papers by Deepa Chandrasekaran
This network shows the impact of papers produced by Deepa Chandrasekaran. 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 Deepa Chandrasekaran. The network helps show where Deepa Chandrasekaran may publish in the future.
Co-authorship network
The 14 scholars most cited alongside Deepa Chandrasekaran, 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 | 2024 | 2 | |
| 2 | 2021 | 4 | |
| 3 | 2020 | 19 | |
| 4 | 2020 | 24 | |
| 5 | 2020 | 2 | |
| 6 | 2018 | 3 | |
| 7 | 2018 | 16 | |
| 8 | 2017 | 48 | |
| 9 | 2017 | 89 | |
| 10 | 2015 | 89 | |
| 11 | 2013 | 16 | |
| 12 | 2012 | 1 | |
| 13 | 2012 | 2 | |
| 14 | 2012 | 0 | |
| 15 | 2011 | 1 | |
| 16 | 2011 | 28 | |
| 17 | Does Culture Matter? Assessing Response Biases in Cross-National Survey Research | 2010 | 9 |
| 18 | 2010 | 53 | |
| 19 | 2008 | 6 | |
| 20 | 2007 | 131 |
About Deepa Chandrasekaran
Deepa Chandrasekaran is a scholar working on Marketing, Computer Science Applications and Management Science and Operations Research, having authored 20 papers that have together received 543 indexed citations. Recurring topics across this work include Innovation Diffusion and Forecasting (9 papers), Firm Innovation and Growth (6 papers), Open Source Software Innovations (4 papers), Consumer Market Behavior and Pricing (4 papers), Digital Platforms and Economics (4 papers), Consumer Behavior in Brand Consumption and Identification (3 papers), Digital Marketing and Social Media (2 papers) and Customer Service Quality and Loyalty (2 papers). The work is most often cited by research in Marketing (180 citations), Management Science and Operations Research (201 citations) and Business and International Management (31 citations). Deepa Chandrasekaran has collaborated with scholars based in United States, Canada and Netherlands. Frequent co-authors include Gerard J. Tellis, Suman Basuroy, Gaia Rubera, Andrea Ordanini, Raji Srinivasan, Gareth James, Joep Arts, R.T. Frambach, Peter R. Monge and Richard T. Gretz. Their work appears in journals such as Journal of Marketing, Journal of Business Ethics and Journal of the Academy of Marketing Science.
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.