Apurva Jain

1.1k total citations
24 papers, 670 citations indexed

About

Apurva Jain is a scholar working on Management Information Systems, Marketing and Information Systems. According to data from OpenAlex, Apurva Jain has authored 24 papers receiving a total of 670 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Management Information Systems, 7 papers in Marketing and 6 papers in Information Systems. Recurrent topics in Apurva Jain's work include Supply Chain and Inventory Management (9 papers), Advanced Queuing Theory Analysis (5 papers) and Consumer Market Behavior and Pricing (5 papers). Apurva Jain is often cited by papers focused on Supply Chain and Inventory Management (9 papers), Advanced Queuing Theory Analysis (5 papers) and Consumer Market Behavior and Pricing (5 papers). Apurva Jain collaborates with scholars based in United States, India and Hong Kong. Apurva Jain's co-authors include Kamran Moinzadeh, Aussadavut Dumrongsiri, Ming Fan, Barry Boehm, Ananth V. Iyer, Raymond Madachy, LiGuo Huang, Kunal Shah, Yong‐Pin Zhou and Daniel Port and has published in prestigious journals such as Management Science, European Journal of Operational Research and Operations Research.

In The Last Decade

Apurva Jain

24 papers receiving 631 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Apurva Jain United States 11 470 349 268 104 84 24 670
Debasish N. Mallick United States 11 233 0.5× 365 1.0× 75 0.3× 46 0.4× 104 1.2× 17 647
Jens Poeppelbuss Germany 15 239 0.5× 147 0.4× 120 0.4× 81 0.8× 56 0.7× 33 556
Tal Ben-Zvi United States 10 262 0.6× 134 0.4× 50 0.2× 70 0.7× 77 0.9× 40 444
Edward Sweeney United States 15 404 0.9× 420 1.2× 112 0.4× 20 0.2× 61 0.7× 82 747
Paul Hawking Australia 13 439 0.9× 174 0.5× 35 0.1× 127 1.2× 76 0.9× 42 729
Frederik Möller Germany 15 162 0.3× 150 0.4× 88 0.3× 110 1.1× 80 1.0× 53 625
Shankar Sundaresan United States 11 200 0.4× 194 0.6× 249 0.9× 43 0.4× 97 1.2× 20 518
Donald G. Reinertsen United States 10 207 0.4× 393 1.1× 63 0.2× 138 1.3× 198 2.4× 16 960
Vincenzo Varriale Italy 13 155 0.3× 227 0.7× 69 0.3× 163 1.6× 27 0.3× 27 544
Anna Maria Oberländer Germany 12 108 0.2× 120 0.3× 84 0.3× 66 0.6× 35 0.4× 24 404

Countries citing papers authored by Apurva Jain

Since Specialization
Citations

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

Fields of papers citing papers by Apurva Jain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Apurva Jain

This figure shows the co-authorship network connecting the top 25 collaborators of Apurva Jain. A scholar is included among the top collaborators of Apurva Jain 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 Apurva Jain. Apurva Jain 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.
Christie, Alana, Michael J. Holcomb, Bingqing Xie, et al.. (2025). Iterative refinement and goal articulation to optimize large language models for clinical information extraction. npj Digital Medicine. 8(1). 301–301. 2 indexed citations
2.
Jain, Apurva, et al.. (2025). Impact of social media advertising on consumer behavior: role of credibility, perceived authenticity, and sustainability. Frontiers in Communication. 10. 1 indexed citations
3.
Jain, Apurva, et al.. (2023). Blockchain and the Law – Legality & Legal Applications. International Journal for Research in Applied Science and Engineering Technology. 11(12). 2040–2043. 2 indexed citations
4.
Fan, Ming, et al.. (2023). Content proliferation and narrowcasting in the age of streaming media. Production and Operations Management. 32(10). 3295–3310. 3 indexed citations
5.
Gupta, Himanshu, Chun G. Schiros, Oleg F. Sharifov, Apurva Jain, & Thomas S. Denney. (2016). Impact of clinical input variable uncertainties on ten-year atherosclerotic cardiovascular disease risk using new pooled cohort equations. BMC Cardiovascular Disorders. 16(1). 165–165. 2 indexed citations
6.
Jain, Apurva, Hamed Mamani, & Kamran Moinzadeh. (2016). Impact of Retailers with Knowledge of Supplier's Inventory on Supply Chain Performance. Production and Operations Management. 26(3). 542–556. 10 indexed citations
7.
Jain, Apurva, et al.. (2014). Comparative analysis of open source content management systems. 1–4. 15 indexed citations
8.
Jain, Apurva, Kamran Moinzadeh, & Yong‐Pin Zhou. (2012). A Single-Supplier, Multiple-Retailer Model with Single-Season, Multiple-Ordering Opportunities, and Fixed Ordering Cost. Operations Research. 60(5). 1098–1110. 11 indexed citations
9.
Boehm, Barry & Apurva Jain. (2007). 3.4.3 The Value‐Based Theory of Systems Engineering: Identifying and Explaining Dependencies. INCOSE International Symposium. 17(1). 562–576. 7 indexed citations
10.
Boehm, Barry & Apurva Jain. (2007). Developing a process framework using principles of value‐based software engineering. Software Process Improvement and Practice. 12(5). 377–385. 3 indexed citations
11.
Jain, Apurva & Barry Boehm. (2006). SimVBSE: Developing a Game for Value-Based Software Engineering. 103–114. 45 indexed citations
12.
Jain, Apurva. (2006). Value of capacity pooling in supply chains with heterogeneous customers. European Journal of Operational Research. 177(1). 239–260. 10 indexed citations
13.
Dumrongsiri, Aussadavut, Ming Fan, Apurva Jain, & Kamran Moinzadeh. (2006). A supply chain model with direct and retail channels. European Journal of Operational Research. 187(3). 691–718. 419 indexed citations
14.
Jain, Apurva. (2006). Priority and dynamic scheduling in a make‐to‐stock queue with hyperexponential demand. Naval Research Logistics (NRL). 53(5). 363–382. 4 indexed citations
15.
Jain, Apurva & Barry Boehm. (2005). Developing a theory of value-based software engineering. ACM SIGSOFT Software Engineering Notes. 30(4). 1–5. 4 indexed citations
16.
Jain, Apurva & Kamran Moinzadeh. (2005). A Supply Chain Model with Reverse Information Exchange. Manufacturing & Service Operations Management. 7(4). 360–378. 26 indexed citations
17.
Boehm, Barry, LiGuo Huang, Apurva Jain, & Raymond Madachy. (2004). The ROI of software dependability: the idave model. IEEE Software. 21(3). 54–61. 36 indexed citations
18.
Iyer, Ananth V. & Apurva Jain. (2004). Modeling the Impact of Merging Capacity in Production-Inventory Systems. Management Science. 50(8). 1082–1094. 14 indexed citations
19.
Iyer, Ananth V. & Apurva Jain. (2003). The Logistics Impact of a Mixture of Order-Streams in a Manufacturer-Retailer System. Management Science. 49(7). 890–906. 14 indexed citations
20.
Boehm, Barry, Daniel Port, Apurva Jain, & Victor R. Basili. (2002). Achieving CMMI Level 5 Improvements with MBASE and the CeBASE Method. 14 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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