Uday Kulkarni

3.4k total citations · 1 hit paper
43 papers, 2.3k citations indexed

About

Uday Kulkarni is a scholar working on Strategy and Management, Management Information Systems and Computer Networks and Communications. According to data from OpenAlex, Uday Kulkarni has authored 43 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Strategy and Management, 14 papers in Management Information Systems and 10 papers in Computer Networks and Communications. Recurrent topics in Uday Kulkarni's work include Big Data and Business Intelligence (10 papers), Knowledge Management and Sharing (9 papers) and Competitive and Knowledge Intelligence (8 papers). Uday Kulkarni is often cited by papers focused on Big Data and Business Intelligence (10 papers), Knowledge Management and Sharing (9 papers) and Competitive and Knowledge Intelligence (8 papers). Uday Kulkarni collaborates with scholars based in United States, India and Peru. Uday Kulkarni's co-authors include Ronald Freeze, Sury Ravindran, Michael Rosemann, Tonia de Bruin, Thilini Ariyachandra, Gloria Phillips‐Wren, Melody Y. Kiang, Lakshmi Iyer, Marcus A. Rothenberger and Robert D. St. Louis and has published in prestigious journals such as Physical Review Letters, European Journal of Operational Research and Journal of the Operational Research Society.

In The Last Decade

Uday Kulkarni

37 papers receiving 2.0k citations

Hit Papers

Understanding the Main Ph... 2005 2026 2012 2019 2005 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Uday Kulkarni United States 16 840 609 607 525 385 43 2.3k
Walter Brenner Switzerland 27 1.1k 1.3× 229 0.4× 783 1.3× 393 0.7× 578 1.5× 223 3.2k
Mohan Tanniru United States 23 664 0.8× 223 0.4× 607 1.0× 339 0.6× 584 1.5× 108 2.6k
Claudia Loebbecke Germany 20 830 1.0× 205 0.3× 923 1.5× 372 0.7× 335 0.9× 138 2.5k
Chyan Yang Taiwan 24 505 0.6× 269 0.4× 606 1.0× 471 0.9× 179 0.5× 97 2.4k
Irma Becerra‐Fernandez United States 18 491 0.6× 765 1.3× 811 1.3× 307 0.6× 349 0.9× 54 2.2k
Bill C. Hardgrave United States 26 677 0.8× 219 0.4× 262 0.4× 415 0.8× 660 1.7× 64 2.4k
Ray Hackney United Kingdom 27 1.1k 1.3× 217 0.4× 761 1.3× 500 1.0× 260 0.7× 116 2.2k
Frederick J. Riggins United States 22 926 1.1× 177 0.3× 819 1.3× 557 1.1× 409 1.1× 48 2.8k
J. Alberto Espinosa United States 21 758 0.9× 758 1.2× 553 0.9× 262 0.5× 1.0k 2.6× 41 2.8k
Judy E. Scott United States 21 900 1.1× 352 0.6× 463 0.8× 632 1.2× 239 0.6× 55 2.0k

Countries citing papers authored by Uday Kulkarni

Since Specialization
Citations

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

Fields of papers citing papers by Uday Kulkarni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Uday Kulkarni

This figure shows the co-authorship network connecting the top 25 collaborators of Uday Kulkarni. A scholar is included among the top collaborators of Uday Kulkarni 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 Uday Kulkarni. Uday Kulkarni 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
1.
Kulkarni, Uday, et al.. (2024). Knowledge Distillation Using Deep Learning Techniques: A Survey. 1–10.
2.
Kulkarni, Uday, et al.. (2019). Data Analytics to Improve Citizen-Centric Smart City Services. Journal of the Association for Information Systems. 2 indexed citations
3.
Kulkarni, Uday, Amit V. Deokar, & Haya Ajjan. (2019). Mining online reviews to uncover consumer brand engagement. Journal of the Association for Information Systems. 3 indexed citations
4.
Wixom, Barbara H., Thilini Ariyachandra, David Douglas, et al.. (2014). The Current State of Business Intelligence in Academia: The Arrival of Big Data. Communications of the Association for Information Systems. 34. 116 indexed citations
5.
Kulkarni, Uday, et al.. (2013). Development and Validation of a BI Success Model. Journal of the Association for Information Systems. 15 indexed citations
6.
Wixom, Barbara H., et al.. (2011). The Current State of Business Intelligence in Academia. Journal of the Association for Information Systems. 29(1). 1. 1 indexed citations
7.
Lee, Gunwoong & Uday Kulkarni. (2011). Business Intelligence in Corporate Risk Management. Journal of the Association for Information Systems. 3720–3730. 2 indexed citations
8.
Islam, Nazrul, et al.. (2007). Knowledge Management Practices in Thai SMEs:Influence of SME Characteristics on Knowledge Management Processes. Journal of the Association for Information Systems. 243. 2 indexed citations
9.
Kulkarni, Uday, et al.. (2007). Impact of Knowledge Management Systems on Knowledge Intensive Business Processes. Journal of the Association for Information Systems. 278. 6 indexed citations
10.
Kulkarni, Uday, Daniel Power, & Ramesh Sharda. (2006). Decision Support for Global Enterprises (Annals of Information Systems). Springer eBooks. 1 indexed citations
11.
Kulkarni, Uday, Sury Ravindran, & Ronald Freeze. (2006). A Knowledge Management Success Model: Theoretical Development and Empirical Validation. Journal of Management Information Systems. 23(3). 309–347. 404 indexed citations
12.
Kulkarni, Uday, et al.. (2005). Knowledge Management Systems: A Business Value Model. Journal of the Association for Information Systems. 27. 2 indexed citations
13.
Bruin, Tonia de, et al.. (2005). Understanding the Main Phases of Developing a Maturity Assessment Model. Journal of the Association for Information Systems. 549 indexed citations breakdown →
14.
Freeze, Ronald & Uday Kulkarni. (2005). Knowledge Management Capability Assessment: Validating a Knowledge Assets Measurement Instrument. 251a–251a. 32 indexed citations
15.
Kulkarni, Uday & Ronald Freeze. (2004). Development and Validation of a Knowledge Management Capability Assessment Model. Journal of the Association for Information Systems. 657–670. 55 indexed citations
16.
Kulkarni, Uday & Robert D. St. Louis. (2003). Organizational Self Assessment of Knowledge Management Maturity. Journal of the Association for Information Systems. 332. 45 indexed citations
17.
Rothenberger, Marcus A., et al.. (2003). Strategies for software reuse: a principal component analysis of reuse practices. IEEE Transactions on Software Engineering. 29(9). 825–837. 79 indexed citations
18.
Gregg, Dawn G., Uday Kulkarni, & Ajay Vinzé. (2001). Understanding the Philosophical Underpinnings of Software Engineering Research in Information Systems. Information Systems Frontiers. 3(2). 169–183. 59 indexed citations
19.
Rothenberger, Marcus A., Uday Kulkarni, & Kevin Dooley. (1998). Critical success factors for software projects. International Conference on Information Systems. 331–335. 4 indexed citations
20.
Kulkarni, Uday, et al.. (1997). Independently updated views. IEEE Transactions on Knowledge and Data Engineering. 9(5). 798–812. 8 indexed citations

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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