Niladri Syam

1.7k total citations · 1 hit paper
26 papers, 1.2k citations indexed

About

Niladri Syam is a scholar working on Marketing, Strategy and Management and Management Information Systems. According to data from OpenAlex, Niladri Syam has authored 26 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Marketing, 8 papers in Strategy and Management and 6 papers in Management Information Systems. Recurrent topics in Niladri Syam's work include Consumer Market Behavior and Pricing (7 papers), Consumer Behavior in Brand Consumption and Identification (5 papers) and Digital Platforms and Economics (5 papers). Niladri Syam is often cited by papers focused on Consumer Market Behavior and Pricing (7 papers), Consumer Behavior in Brand Consumption and Identification (5 papers) and Digital Platforms and Economics (5 papers). Niladri Syam collaborates with scholars based in United States, India and Philippines. Niladri Syam's co-authors include Arun Sharma, James D. Hess, Nanda Kumar, Partha Krishnamurthy, Amit Pazgal, Ryan Mullins, Deva Rangarajan, Bert Paesbrugghe, Ram C. Rao and Raj Echambadi and has published in prestigious journals such as Journal of Marketing, Journal of Marketing Research and Marketing Science.

In The Last Decade

Niladri Syam

24 papers receiving 1.1k citations

Hit Papers

Waiting for a sales renaissance in the fourth industrial ... 2018 2026 2020 2023 2018 100 200 300 400

Peers

Niladri Syam
Comparison fields: 5 of 102
  • Marketing 536
  • Strategy and Management 284
  • Sociology and Political Science 236
  • Organizational Behavior and Human Resource Management 230
  • Management Information Systems 203
Replace Esko Penttinen with:
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Citations per field, relative to Niladri Syam
Niladri Syam · 1×
Citations per year, relative to Niladri Syam
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Countries citing papers authored by Niladri Syam

Since Specialization
Citations

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

Fields of papers citing papers by Niladri Syam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Niladri Syam

This figure shows the co-authorship network connecting the top 25 collaborators of Niladri Syam. A scholar is included among the top collaborators of Niladri Syam based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Niladri Syam. Niladri Syam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 3
3
Machine Learning and Artificial Intelligence in Marketing and Sales: Essential Reference for Practitioners and Data Scientists
0
4 9
5 1
6 3
7 10
8
Waiting for a sales renaissance in the fourth industrial revolution: Machine learning and artificial intelligence in sales research and practice breakdown →
477
9 40
10 39
11 40
12 16
13 37
14
Co-Creation with Production Externalities
1
15 9
16 86
17 36
18 100
19 123
20 6

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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