Anu Sayal

32 papers receiving 151 citations

Peers

Anu Sayal
Comparison fields: 5 of 51
  • Human-Computer Interaction 20
  • Health Informatics 3
  • Management Information Systems 19
  • Health Information Management 7
  • Management Science and Operations Research 17
Replace Yunifa Miftachul Arif with:
Yunifa Miftachul Arif Indonesia
Usman Wajid United Kingdom
Stefano Tranquillini Italy
Remya George Saudi Arabia
Kati Kuusinen Denmark
Michael Xieyang Liu United States
Xiaochong Lan China
Rashadul Islam Sumon South Korea
Azadeh Imani Rad Iran
Samedi Heng Belgium
Anu Sayal relative to Yunifa Miftachul Arif Indonesia Yunifa Miftachul Arif's profile →
Citations per field
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Yunifa Miftachul Arif · 1×
Citations per year

Countries citing papers authored by Anu Sayal

Since Specialization
Citations

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

Fields of papers citing papers by Anu Sayal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Anu Sayal, 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 Anu Sayal Line = papers co-authored together Anu Sayal links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202430
2 202315
3 202313
4 20249
5 20238
6 20237
7 20237
8 20256
9 20236
10 20216
11 20235
12 20224
13 20224
14 20194
15 20243
16 20253
17 20253
18 20223
19 20252
20 20252

About Anu Sayal

Anu Sayal is a scholar working on Management Information Systems, Information Systems, Management Science and Operations Research, Marketing and Artificial Intelligence, having authored 36 papers that have together received 157 indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (5 papers), Impact of AI and Big Data on Business and Society (5 papers), Environmental Sustainability in Business (4 papers), Supply Chain and Inventory Management (4 papers), Scheduling and Optimization Algorithms (4 papers), Big Data and Business Intelligence (3 papers), Consumer Behavior in Brand Consumption and Identification (3 papers) and Artificial Intelligence in Healthcare (2 papers). The work is most often cited by research in Human-Computer Interaction (20 citations), Health Informatics (3 citations), Management Information Systems (19 citations), Health Information Management (7 citations) and Management Science and Operations Research (17 citations). Anu Sayal has collaborated with scholars based in India, Malaysia and Saudi Arabia. Frequent co-authors include Ashulekha Gupta, Minakshi Memoria, Amar Johri, Anand Chauhan, Neeraj Dhiman, Rajiv Kumar, Varun Dogra, M. C. Pant, T R Mahesh and Mohammad Wasiq. Their work appears in journals such as Cleaner Engineering and Technology, Results in Engineering, International Journal of Asian Business and Information Management, Journal of Open Innovation Technology Market and Complexity and International Journal of Information Management Data Insights.

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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