IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v131y2021icp374-390.html
   My bibliography  Save this article

A bibliometric review of a decade of research: Big data in business research – Setting a research agenda

Author

Listed:
  • Zhang, Yucheng
  • Zhang, Meng
  • Li, Jing
  • Liu, Guangjian
  • Yang, Miles M.
  • Liu, Siqi

Abstract

The last several years have witnessed a surge of interest in artificial intelligence (AI). As the foundation of AI technologies, big data has attracted attention of researchers. Big data and data science have been recognized as new tools and methodologies for developing theories in business research (George, 2014). While several qualitative reviews have been conducted, there is still a lack of a quantitative and systematic review of big data in business research. Our review study fills this gap by depicting the development of big data in business research using bibliometric methods, such as publication counts and trends analysis, co-citation analysis, co-authorship analysis and keywords co-occurrence analysis. Based on the sample of 1366 primary focal articles and 55,718 secondary references, we visualize the landscape and evolution of big-data business research and capture the developmental trajectory and trends over time (between 2008 and 2018). Furthermore, based on our analyses, we provide several promising directions for future research. In doing so, we provide scholars with a systematic understanding of the development and panoramic roadmap of big data research in business.

Suggested Citation

  • Zhang, Yucheng & Zhang, Meng & Li, Jing & Liu, Guangjian & Yang, Miles M. & Liu, Siqi, 2021. "A bibliometric review of a decade of research: Big data in business research – Setting a research agenda," Journal of Business Research, Elsevier, vol. 131(C), pages 374-390.
    • Handle: RePEc:eee:jbrese:v:131:y:2021:i:c:p:374-390
    DOI: 10.1016/j.jbusres.2020.11.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296320307475
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2020.11.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Loet Leydesdorff, 2005. "Similarity measures, author cocitation analysis, and information theory," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 56(7), pages 769-772, May.
    2. Ebadi, Ashkan & Schiffauerova, Andrea, 2015. "How to become an important player in scientific collaboration networks?," Journal of Informetrics, Elsevier, vol. 9(4), pages 809-825.
    3. Li, Huajiao & An, Haizhong & Wang, Yue & Huang, Jiachen & Gao, Xiangyun, 2016. "Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 657-669.
    4. Huchang Liao & Ming Tang & Li Luo & Chunyang Li & Francisco Chiclana & Xiao-Jun Zeng, 2018. "A Bibliometric Analysis and Visualization of Medical Big Data Research," Sustainability, MDPI, vol. 10(1), pages 1-18, January.
    5. Sridhar P. Nerur & Abdul A. Rasheed & Vivek Natarajan, 2008. "The intellectual structure of the strategic management field: an author co‐citation analysis," Strategic Management Journal, Wiley Blackwell, vol. 29(3), pages 319-336, March.
    6. Rampersad, Giselle, 2020. "Robot will take your job: Innovation for an era of artificial intelligence," Journal of Business Research, Elsevier, vol. 116(C), pages 68-74.
    7. Holmes, R. Michael & Hoskisson, Robert E. & Kim, Hicheon & Wan, William P. & Holcomb, Tim R., 2018. "International strategy and business groups: A review and future research agenda," Journal of World Business, Elsevier, vol. 53(2), pages 134-150.
    8. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    9. Ritu Agarwal & Vasant Dhar, 2014. "Editorial —Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research," Information Systems Research, INFORMS, vol. 25(3), pages 443-448, September.
    10. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    11. Robinson, Stacey & Orsingher, Chiara & Alkire, Linda & De Keyser, Arne & Giebelhausen, Michael & Papamichail, K. Nadia & Shams, Poja & Temerak, Mohamed Sobhy, 2020. "Frontline encounters of the AI kind: An evolved service encounter framework," Journal of Business Research, Elsevier, vol. 116(C), pages 366-376.
    12. Merendino, Alessandro & Dibb, Sally & Meadows, Maureen & Quinn, Lee & Wilson, David & Simkin, Lyndon & Canhoto, Ana, 2018. "Big data, big decisions: The impact of big data on board level decision-making," Journal of Business Research, Elsevier, vol. 93(C), pages 67-78.
    13. Nikolay Archak & Anindya Ghose & Panagiotis G. Ipeirotis, 2011. "Deriving the Pricing Power of Product Features by Mining Consumer Reviews," Management Science, INFORMS, vol. 57(8), pages 1485-1509, August.
    14. O'Reilly, Tim, 2007. "What Is Web 2.0: Design Patterns and Business Models for the Next Generation of Software," MPRA Paper 4578, University Library of Munich, Germany.
    15. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    16. Howard D. White & Belver C. Griffith, 1981. "Author cocitation: A literature measure of intellectual structure," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 32(3), pages 163-171, May.
    17. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2012. "Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content," Marketing Science, INFORMS, vol. 31(3), pages 493-520, May.
    18. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    19. G. Scott Erickson & Helen N. Rothberg, 2013. "A strategic approach to knowledge development and protection," The Service Industries Journal, Taylor & Francis Journals, vol. 33(13-14), pages 1402-1416, October.
    20. Giada Di Stefano & Alfonso Gambardella & Gianmario Verona, 2012. "Technology Push and Demand Pull Perspectives in Innovation Studies: Current Findings and Future Research Directions," Post-Print hal-00696607, HAL.
    21. Michael Haenlein & Andreas Kaplan & Chee-Wee Tan & Pengzhu Zhang, 2019. "Artificial intelligence (AI) and management analytics," Journal of Management Analytics, Taylor & Francis Journals, vol. 6(4), pages 341-343, October.
    22. Di Stefano, Giada & Gambardella, Alfonso & Verona, Gianmario, 2012. "Technology push and demand pull perspectives in innovation studies: Current findings and future research directions," Research Policy, Elsevier, vol. 41(8), pages 1283-1295.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yong Qin & Zeshui Xu & Xinxin Wang & Marinko Skare, 2024. "Artificial Intelligence and Economic Development: An Evolutionary Investigation and Systematic Review," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 1736-1770, March.
    2. Jianmin Song & Senmao Xia & Demetris Vrontis & Arun Sukumar & Bing Liao & Qi Li & Kun Tian & Nengzhi Yao, 2022. "The Source of SMEs’ Competitive Performance in COVID-19: Matching Big Data Analytics Capability to Business Models," Information Systems Frontiers, Springer, vol. 24(4), pages 1167-1187, August.
    3. Kim, Hyunsu & Li, Jing & So, Kevin Kam Fung, 2024. "Psychological ownership research in business: A bibliometric overview and future research directions," Journal of Business Research, Elsevier, vol. 174(C).
    4. Qin, Yong & Xu, Zeshui & Wang, Xinxin & Škare, Marinko, 2022. "Green energy adoption and its determinants: A bibliometric analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Maximilian Scheffler & Johannes Brunzel, 2020. "Destructive leadership in organizational research: a bibliometric approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 755-775, October.
    2. Kim, Juran & Kang, Seungmook & Lee, Ki Hoon, 2021. "Evolution of digital marketing communication: Bibliometric analysis and network visualization from key articles," Journal of Business Research, Elsevier, vol. 130(C), pages 552-563.
    3. Hötte, Kerstin, 2023. "Demand-pull, technology-push, and the direction of technological change," Research Policy, Elsevier, vol. 52(5).
    4. Osman Issah & Lúcia Lima Rodrigues, 2021. "Corporate Social Responsibility and Corporate Tax Aggressiveness: A Scientometric Analysis of the Existing Literature to Map the Future," Sustainability, MDPI, vol. 13(11), pages 1-23, June.
    5. Hélène Dernis & Mariagrazia Squicciarini & Roberto Pinho, 2016. "Detecting the emergence of technologies and the evolution and co-development trajectories in science (DETECTS): a ‘burst’ analysis-based approach," The Journal of Technology Transfer, Springer, vol. 41(5), pages 930-960, October.
    6. Maria Glinyanova & Ricarda B. Bouncken & Victor Tiberius & Antonio C. Cuenca Ballester, 2021. "Five decades of corporate entrepreneurship research: measuring and mapping the field," International Entrepreneurship and Management Journal, Springer, vol. 17(4), pages 1731-1757, December.
    7. Ren, Yi-Shuai & Ma, Chao-Qun & Chen, Xun-Qi & Lei, Yu-Tian & Wang, Yi-Ran, 2023. "Sustainable finance and blockchain: A systematic review and research agenda," Research in International Business and Finance, Elsevier, vol. 64(C).
    8. Yi Zhang & Patrick Sik-Wah Fong & Daniel Yamoah Agyemang, 2021. "What Should Be Focused on When Digital Transformation Hits Industries? Literature Review of Business Management Adaptability," Sustainability, MDPI, vol. 13(23), pages 1-30, December.
    9. Mochen Yang & Gediminas Adomavicius & Gordon Burtch & Yuqing Rena, 2018. "Mind the Gap: Accounting for Measurement Error and Misclassification in Variables Generated via Data Mining," Information Systems Research, INFORMS, vol. 29(1), pages 4-24, March.
    10. Manuel Castriotta & Michela Loi & Elona Marku & Ludovica Moi, 2021. "Disentangling the corporate entrepreneurship construct: conceptualizing through co-words," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2821-2863, April.
    11. Jorge Mejia & Shawn Mankad & Anandasivam Gopal, 2019. "A for Effort? Using the Crowd to Identify Moral Hazard in New York City Restaurant Hygiene Inspections," Information Systems Research, INFORMS, vol. 30(4), pages 1363-1386, December.
    12. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.
    13. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2019. "Technology in the 21st century: New challenges and opportunities," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 321-335.
    14. Gaviria-Marin, Magaly & Merigó, José M. & Baier-Fuentes, Hugo, 2019. "Knowledge management: A global examination based on bibliometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 194-220.
    15. Christoph P. Kiefer & Pablo Del Río González & Javier Carrillo‐Hermosilla, 2019. "Drivers and barriers of eco‐innovation types for sustainable transitions: A quantitative perspective," Business Strategy and the Environment, Wiley Blackwell, vol. 28(1), pages 155-172, January.
    16. Gao, Qiang & Liang, Zhentao & Wang, Ping & Hou, Jingrui & Chen, Xiuxiu & Liu, Manman, 2021. "Potential index: Revealing the future impact of research topics based on current knowledge networks," Journal of Informetrics, Elsevier, vol. 15(3).
    17. Paolo E. Giordani & Francesco Rullani, 2020. "The Digital Revolution and COVID-19," Working Papers 06, Department of Management, Università Ca' Foscari Venezia.
    18. Anke Joubert & Matthias Murawski & Markus Bick, 2023. "Measuring the Big Data Readiness of Developing Countries – Index Development and its Application to Africa," Information Systems Frontiers, Springer, vol. 25(1), pages 327-350, February.
    19. Souzanchi Kashani, Ebrahim & Roshani, Saeed, 2019. "Evolution of innovation system literature: Intellectual bases and emerging trends," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 68-80.
    20. Gallego-Losada, María-Jesús & Montero-Navarro, Antonio & García-Abajo, Elisa & Gallego-Losada, Rocío, 2023. "Digital financial inclusion. Visualizing the academic literature," Research in International Business and Finance, Elsevier, vol. 64(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbrese:v:131:y:2021:i:c:p:374-390. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.