A bibliographic study on big data: concepts, trends and challenges
Abstract
Purpose: The purpose of paper is twofold. First, it provides a consolidated overview of the existing literature on “big data” and second, it presents the current trends and opens up various future directions for researchers who wish to explore and contribute in this rapidly evolving field. Design/methodology/approach: To achieve the objective of this study, the bibliographic and network techniques of citation and co-citation analysis was adopted. This analysis involved an assessment of 57 articles published over a period of five years (2011-2015) in ten selected journals. Findings: The findings reveal that the number of articles devoted to the study of “big data” has increased rapidly in recent years. Moreover, the study identifies some of the most influential articles of this area. Finally, the paper highlights the new trends and discusses the challenges associated with big data. Research limitations/implications: This study focusses only on big data concepts, trends, and challenges and excludes research on its analytics. Thus, researchers may explore and extend this area of research. Originality/value: To the knowledge of the authors, this is the first study to review the literature on big data by using citation and co-citation analysis.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Cites
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Flagged first, then by citations
Cited by
Sorted by citations
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- Authors
- Mishra, D., Luo, Z., Jiang, S., Papadopoulos, T., & Dubey, R.
- Affiliations
- Indian Institute of Technology Kanpur (IN)
- Southern University of Science and Technology (CN)
- Symbiosis International University (IN)
- Venue
- Business Process Management Journal
- Publisher
- Emerald
- Published
- 2017-06-05
- Volume
- 23
- Issue
- 3
- Pages
- 555-573
- ISSN
- 1463-7154 (ISSN-L)
- OpenAlex
- W2607615935
- Cited by
- 84
- References
- 88
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 5 · 2023: 9 · 2022: 13 · 2021: 7 · 2020: 14 · 2019: 15 · 2018: 6 · 2017: 1
- FWCI
- 15.83
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Business Process Management Journal (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
- Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
- Keywords
- big data, research trends, research challenges, citation analysis, co-citation analysis, influential papers
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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