Exploring artificial intelligence and big data scholarship in information systems: A citation, bibliographic coupling, and co-word analysis
This research explores extant research on artificial intelligence (AI) and big data published in the premier Information Systems (IS) journals over a period of 26 years (1997–2022), and it uses the techniques of citation analysis, bibliographic coupling, and co-word analysis. Citation analysis resul...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-11-01
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| Series: | International Journal of Information Management Data Insights |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667096823000320 |
| _version_ | 1797399048248885248 |
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| author | Rahul Dwivedi Sridhar Nerur Venugopal Balijepally |
| author_facet | Rahul Dwivedi Sridhar Nerur Venugopal Balijepally |
| author_sort | Rahul Dwivedi |
| collection | DOAJ |
| description | This research explores extant research on artificial intelligence (AI) and big data published in the premier Information Systems (IS) journals over a period of 26 years (1997–2022), and it uses the techniques of citation analysis, bibliographic coupling, and co-word analysis. Citation analysis results reveal IS as the most cited reference discipline, followed by general business, organization science, and marketing. Two major topical clusters have been identified — problem domain-specific AI (e.g., predictive analytics, machine learning algorithms, and text mining) and organizational-specific AI (e.g., big data capabilities, firm performance, agility, and strategy). Co-word analysis revealed a gradual shift of scholarly interest from problem-domain-specific AI toward organizational-specific AI. Using the citation data, the most influential (cited) authors, (cited) articles, journals, institutions, and countries are identified. Gaps in extant research and future research paths are discussed. |
| first_indexed | 2024-03-09T01:33:49Z |
| format | Article |
| id | doaj.art-fe356d2b077a40c8920e0a5d12c654f6 |
| institution | Directory Open Access Journal |
| issn | 2667-0968 |
| language | English |
| last_indexed | 2024-03-09T01:33:49Z |
| publishDate | 2023-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Information Management Data Insights |
| spelling | doaj.art-fe356d2b077a40c8920e0a5d12c654f62023-12-09T06:08:36ZengElsevierInternational Journal of Information Management Data Insights2667-09682023-11-0132100185Exploring artificial intelligence and big data scholarship in information systems: A citation, bibliographic coupling, and co-word analysisRahul Dwivedi0Sridhar Nerur1Venugopal Balijepally2Department of Computer Information Systems, Texas A&M University-Central Texas, Killeen, TX 76549, United States; Corresponding author.Department of Information Systems and Operations Management, The University of Texas at Arlington, Arlington, TX 76019, United StatesDepartment of Decision and Information Sciences, Oakland University, Rochester, MI 48309, United StatesThis research explores extant research on artificial intelligence (AI) and big data published in the premier Information Systems (IS) journals over a period of 26 years (1997–2022), and it uses the techniques of citation analysis, bibliographic coupling, and co-word analysis. Citation analysis results reveal IS as the most cited reference discipline, followed by general business, organization science, and marketing. Two major topical clusters have been identified — problem domain-specific AI (e.g., predictive analytics, machine learning algorithms, and text mining) and organizational-specific AI (e.g., big data capabilities, firm performance, agility, and strategy). Co-word analysis revealed a gradual shift of scholarly interest from problem-domain-specific AI toward organizational-specific AI. Using the citation data, the most influential (cited) authors, (cited) articles, journals, institutions, and countries are identified. Gaps in extant research and future research paths are discussed.http://www.sciencedirect.com/science/article/pii/S2667096823000320Information systemsArtificial intelligenceBig data researchIntellectual structureIdentifying reference disciplinesCitation analysis |
| spellingShingle | Rahul Dwivedi Sridhar Nerur Venugopal Balijepally Exploring artificial intelligence and big data scholarship in information systems: A citation, bibliographic coupling, and co-word analysis International Journal of Information Management Data Insights Information systems Artificial intelligence Big data research Intellectual structure Identifying reference disciplines Citation analysis |
| title | Exploring artificial intelligence and big data scholarship in information systems: A citation, bibliographic coupling, and co-word analysis |
| title_full | Exploring artificial intelligence and big data scholarship in information systems: A citation, bibliographic coupling, and co-word analysis |
| title_fullStr | Exploring artificial intelligence and big data scholarship in information systems: A citation, bibliographic coupling, and co-word analysis |
| title_full_unstemmed | Exploring artificial intelligence and big data scholarship in information systems: A citation, bibliographic coupling, and co-word analysis |
| title_short | Exploring artificial intelligence and big data scholarship in information systems: A citation, bibliographic coupling, and co-word analysis |
| title_sort | exploring artificial intelligence and big data scholarship in information systems a citation bibliographic coupling and co word analysis |
| topic | Information systems Artificial intelligence Big data research Intellectual structure Identifying reference disciplines Citation analysis |
| url | http://www.sciencedirect.com/science/article/pii/S2667096823000320 |
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