Salman Bahoo

23 papers receiving 1.1k citations

Salman Bahoo's Hit Papers

Artificial intelligence in Finance: a comprehensive review through bibliometric and content analysis 2024 · 65 citations
650+2+4Years since publication50100150200250

Peers

Salman Bahoo
Comparison fields: 5 of 93
  • Accounting 344
  • Strategy and Management 295
  • Management Information Systems 149
  • Finance 159
  • Economics and Econometrics 345
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K. M. Anwarul Islam Bangladesh
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Özgür Özdemir United States
Ehab K. A. Mohamed Egypt
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Countries citing papers authored by Salman Bahoo

Since Specialization
Citations

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

Fields of papers citing papers by Salman Bahoo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Salman Bahoo, 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 Salman Bahoo Line = papers co-authored together Salman Bahoo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Corruption in international business: A review and research agenda
Hit paper breakdown →
2019261
2
A bibliometric review of sukuk literature
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2019203
3
Artificial intelligence and corporate innovation: A review and research agenda
Hit paper breakdown →
2022199
4 2020134
5 202082
6 201979
7
Artificial intelligence in Finance: a comprehensive review through bibliometric and content analysis
Hit paper breakdown →
202465
8 202038
9 202421
10 201817
11 201915
12 202112
13 202310
14 20217
15 20235
16 20194
17 20253
18 20223
19 20203
20 20172

About Salman Bahoo

Salman Bahoo is a scholar working on Accounting, Economics and Econometrics, Strategy and Management, Sociology and Political Science and Management Science and Operations Research, having authored 24 papers that have together received 1.2k indexed citations. Recurring topics across this work include Islamic Finance and Banking Studies (5 papers), Corruption and Economic Development (4 papers), State Capitalism and Financial Governance (3 papers), Banking stability, regulation, efficiency (3 papers), Economic Growth and Development (3 papers), Stock Market Forecasting Methods (3 papers), Insurance and Financial Risk Management (3 papers) and Environmental Sustainability in Business (2 papers). The work is most often cited by research in Accounting (344 citations), Strategy and Management (295 citations), Management Information Systems (149 citations), Finance (159 citations) and Economics and Econometrics (345 citations). Salman Bahoo has collaborated with scholars based in Italy, Pakistan and Norway. Frequent co-authors include Andrea Paltrinieri, Ilan Alon, M. Kabir Hassan, Ashraf Khan, Marco Cucculelli, Alberto Dreassi, Josanco Floreani, Rizwan Mushtaq, Sohail Saeed and Shahid Nawaz. Their work appears in journals such as Finance research letters, Thunderbird International Business Review, International Review of Economics & Finance, Journal of Economic Surveys and International Business Review.

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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