Amy Igou

423 citations
9 papers · 264 · h-index 7

Impact in

Papers in

Amy Igou

8 papers receiving 251 citations

Peers

Amy Igou
Comparison fields: 5 of 58
  • Medical Laboratory Technology 23
  • Management Information Systems 131
  • Industrial and Manufacturing Engineering 62
  • Management Science and Operations Research 55
  • Information Systems and Management 24
Replace Giancarlo Nota with:
Giancarlo Nota Italy
R.R. Lakhe India
A. G. Lockett United Kingdom
G.A. Bohoris United Kingdom
Jacky Akoka France
Xue-Ming Yuan Singapore
David James Brunner United Kingdom
Philipp Gölzer Germany
Volker Stich Germany
Gerry Coleman Ireland
Amy Igou relative to Giancarlo Nota Italy Giancarlo Nota's profile →
Citations per field
00.5×3.2×
Giancarlo Nota · 1×
Citations per year

Countries citing papers authored by Amy Igou

Since Specialization
Citations

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

Fields of papers citing papers by Amy Igou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 6 scholars most cited alongside Amy Igou, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Amy Igou Line = papers co-authored together Amy Igou links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 201788
2 201775
3 201624
4 201922
5 202021
6 202220
7 201211
8 20223
9 20240

About Amy Igou

Amy Igou is a scholar working on Management Information Systems, Industrial and Manufacturing Engineering, Strategy and Management, Sociology and Political Science and Information Systems, having authored 9 papers that have together received 264 indexed citations. Recurring topics across this work include FinTech, Crowdfunding, Digital Finance (3 papers), Robotic Process Automation Applications (3 papers), Big Data and Business Intelligence (3 papers), Business Process Modeling and Analysis (2 papers), Reliability and Maintenance Optimization (1 paper), Technology Adoption and User Behaviour (1 paper), Digital Marketing and Social Media (1 paper) and Technology Assessment and Management (1 paper). The work is most often cited by research in Medical Laboratory Technology (23 citations), Management Information Systems (131 citations), Industrial and Manufacturing Engineering (62 citations), Management Science and Operations Research (55 citations) and Information Systems and Management (24 citations). Amy Igou has collaborated with scholars based in United States, Austria and Ireland. Frequent co-authors include Daniel Bumblauskas, Johanna Anzengruber, Mary B. Burns, Nishani Edirisinghe Vincent, Daniel Power and Ciara Heavin. Their work appears in journals such as Issues in Accounting Education, Expert Systems with Applications, Business Process Management Journal, Journal of Accounting Education and Journal of Emerging Technologies in Accounting.

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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