Jana Prodanova

58 total papers · 829 total citations
32 papers, 567 citations indexed

About

Jana Prodanova is a scholar working on Sociology and Political Science, Marketing and Information Systems and Management. According to data from OpenAlex, Jana Prodanova has authored 32 papers receiving a total of 567 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Sociology and Political Science, 15 papers in Marketing and 12 papers in Information Systems and Management. Recurrent topics in Jana Prodanova's work include Digital Marketing and Social Media (14 papers), Technology Adoption and User Behaviour (12 papers) and Consumer Retail Behavior Studies (11 papers). Jana Prodanova is often cited by papers focused on Digital Marketing and Social Media (14 papers), Technology Adoption and User Behaviour (12 papers) and Consumer Retail Behavior Studies (11 papers). Jana Prodanova collaborates with scholars based in Spain, North Macedonia and India. Jana Prodanova's co-authors include Sonia San Martín Gutiérrez, Nadia Jiménez, Ljupčo Kocarev, Prasanta Kr Chopdar, Justin Paul, Blanca López‐Catalán, Paula Rodríguez–Torrico, Amy Van Looy, Aleksandar Dedinec and Desheng Wu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Business Research and IEEE Access.

In The Last Decade

Jana Prodanova

29 papers receiving 545 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Jana Prodanova	340	241	216	160	48	32	567
T. Sai Vijay	274 0.8×	389 1.6×	218 1.0×	151 0.9×	47 1.0×	50	608
Senthil Arasu Balasubramanian	356 1.0×	244 1.0×	356 1.6×	136 0.8×	62 1.3×	22	644
Madhurima Deb	333 1.0×	328 1.4×	187 0.9×	205 1.3×	42 0.9×	33	632
Esthela Galván-Vela	268 0.8×	165 0.7×	189 0.9×	155 1.0×	50 1.0×	40	589
Ash Narayan Sah	219 0.6×	243 1.0×	266 1.2×	124 0.8×	43 0.9×	23	502
Yung‐Cheng Shen	376 1.1×	308 1.3×	280 1.3×	186 1.2×	24 0.5×	24	679
Ioannis Rizomyliotis	284 0.8×	321 1.3×	142 0.7×	111 0.7×	32 0.7×	41	591
Jamil Bojei	371 1.1×	212 0.9×	137 0.6×	205 1.3×	19 0.4×	34	596
Emma Juaneda Ayensa	312 0.9×	449 1.9×	162 0.8×	196 1.2×	44 0.9×	30	685
Dipendra Singh	308 0.9×	221 0.9×	123 0.6×	107 0.7×	84 1.8×	33	565

Countries citing papers authored by Jana Prodanova

Since Specialization

Citations

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

Fields of papers citing papers by Jana Prodanova

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jana Prodanova

This figure shows the co-authorship network connecting the top 25 collaborators of Jana Prodanova. A scholar is included among the top collaborators of Jana Prodanova 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 Jana Prodanova. Jana Prodanova is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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