Mona Ashok

1.2k total citations · 2 hit papers
9 papers, 684 citations indexed

About

Mona Ashok is a scholar working on Strategy and Management, Communication and Sociology and Political Science. According to data from OpenAlex, Mona Ashok has authored 9 papers receiving a total of 684 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Strategy and Management, 3 papers in Communication and 2 papers in Sociology and Political Science. Recurrent topics in Mona Ashok's work include Knowledge Management and Sharing (3 papers), Innovation and Knowledge Management (3 papers) and Organizational and Employee Performance (2 papers). Mona Ashok is often cited by papers focused on Knowledge Management and Sharing (3 papers), Innovation and Knowledge Management (3 papers) and Organizational and Employee Performance (2 papers). Mona Ashok collaborates with scholars based in United Kingdom, China and Spain. Mona Ashok's co-authors include Uthayasankar Sivarajah, Anton Joha, Rajneesh Narula, Andrea Martínez‐Noya, Michael D. Dzandu, Marc Day and Kui Yin and has published in prestigious journals such as International Journal of Information Management, Industrial Marketing Management and Journal of Knowledge Management.

In The Last Decade

Mona Ashok

9 papers receiving 642 citations

Hit Papers

Ethical framework for Artificial Intelligence and Digital... 2021 2026 2022 2024 2021 2022 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mona Ashok United Kingdom 8 177 127 126 125 112 9 684
Donald Heath United States 7 116 0.7× 110 0.9× 111 0.9× 150 1.2× 81 0.7× 14 705
Shiko M. Ben‐Menahem Switzerland 7 202 1.1× 87 0.7× 95 0.8× 91 0.7× 41 0.4× 13 672
Eleni Trichina Cyprus 8 145 0.8× 61 0.5× 174 1.4× 130 1.0× 72 0.6× 9 902
Hind Benbya United States 14 202 1.1× 104 0.8× 172 1.4× 227 1.8× 55 0.5× 42 977
Benjamin Mueller Germany 11 152 0.9× 64 0.5× 94 0.7× 247 2.0× 120 1.1× 58 726
Stella Pachidi United Kingdom 9 144 0.8× 249 2.0× 181 1.4× 296 2.4× 56 0.5× 17 960
Alex Murray United States 8 133 0.8× 87 0.7× 59 0.5× 152 1.2× 82 0.7× 17 662
Jacob M. Rose United States 19 274 1.5× 103 0.8× 59 0.5× 128 1.0× 52 0.5× 58 1.2k
Alessandro Pagano Italy 14 292 1.6× 27 0.2× 99 0.8× 84 0.7× 132 1.2× 54 802
Anton Joha Netherlands 11 106 0.6× 76 0.6× 61 0.5× 86 0.7× 111 1.0× 18 616

Countries citing papers authored by Mona Ashok

Since Specialization
Citations

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

Fields of papers citing papers by Mona Ashok

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mona Ashok

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

All Works

9 of 9 papers shown
1.
Ashok, Mona, et al.. (2024). Making Sense of AI Benefits: A Mixed-method Study in Canadian Public Administration. Information Systems Frontiers. 27(3). 889–923. 7 indexed citations
2.
Yin, Kui, et al.. (2023). A meta-analysis of horizontal leadership and knowledge sharing. Current Psychology. 43(17). 15507–15521. 3 indexed citations
3.
Ashok, Mona, et al.. (2022). AI adoption and diffusion in public administration: A systematic literature review and future research agenda. Government Information Quarterly. 40(1). 101774–101774. 176 indexed citations breakdown →
4.
Ashok, Mona, et al.. (2021). Value co-creation in the B2B context: a conceptual framework and its implications. Service Industries Journal. 42(3-4). 178–205. 25 indexed citations
5.
Ashok, Mona, et al.. (2021). Ethical framework for Artificial Intelligence and Digital technologies. International Journal of Information Management. 62. 102433–102433. 219 indexed citations breakdown →
6.
Ashok, Mona, et al.. (2021). How to counter organisational inertia to enable knowledge management practices adoption in public sector organisations. Journal of Knowledge Management. 25(9). 2245–2273. 61 indexed citations
7.
Ashok, Mona, et al.. (2020). Value co-destruction: Exploring the role of actors’ opportunism in the B2B context. International Journal of Information Management. 52. 102093–102093. 69 indexed citations
8.
Ashok, Mona, Marc Day, & Rajneesh Narula. (2017). Buyer (dis)satisfaction and process innovation: The case of information technology services provision. Industrial Marketing Management. 68. 132–144. 31 indexed citations
9.
Ashok, Mona, Rajneesh Narula, & Andrea Martínez‐Noya. (2016). How do collaboration and investments in knowledge management affect process innovation in services?. Journal of Knowledge Management. 20(5). 1004–1024. 93 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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