The DOI matches its Crossref record; 100 of the 100 references it cites were found in a registry or an index.
A Review of Research Relevant to the Emerging Industry Trends: Industry 4.0, IoT, Blockchain, and Business Analytics
Abstract
Industry 4.0, Internet of Things, Blockchain, and Business Analytics are the hot research topics and have attracted much attention from scholars and practitioners in recent years. In order to identify the forces driving their development and to promote their development, this paper reviews the extant studies on these topics. The review provides a comprehensive overview of state-of-the-art researches on Industry 4.0, Internet of Things, Blockchain, and Business Analytics. The results assist scholars to figure out the directions of future studies on these topics.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Internet of Things in industries: A survey
Xu, L. D., He, W., & Li, S. (2014) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2014.2300753 · Cited by 5,172
Industry 4.0: state of the art and future trends
Xu, L. D., Xu, E. L., & Li, L. (2018) · International Journal of Production Research · doi:10.1080/00207543.2018.1444806 · Cited by 3,221
Industry 4.0: A survey on technologies, applications and open research issues
Lu, Y. (2017) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2017.04.005 · Cited by 3,012
Casino, F., Dasaklis, T. K., & Patsakis, C. (2019) · Telematics and Informatics · doi:10.1016/j.tele.2018.11.006 · Cited by 2,557
The internet of things: a survey
Li, S., Xu, L. D., & Zhao, S. (2015) · Information Systems Frontiers · doi:10.1007/s10796-014-9492-7 · Cited by 2,297
The Internet of Things—A survey of topics and trends
Whitmore, A., Agarwal, A., & Da Xu, L. (2015) · Information Systems Frontiers · doi:10.1007/s10796-014-9489-2 · Cited by 1,568
Deep Learning for IoT Big Data and Streaming Analytics: A Survey
Mohammadi, M., Al-Fuqaha, A., Sorour, S., & Guizani, M. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2844341 · Cited by 1,471
Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges
Wang, Y., Chen, Q., Hong, T., & Kang, C. (2019) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2018.2818167 · Cited by 1,369
5G Internet of Things: A survey
Li, S., Xu, L. D., & Zhao, S. (2018) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2018.01.005 · Cited by 1,293
Horváth, D., & Szabó, R. Z. (2019) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2019.05.021 · Cited by 1,281
Cited by
Industry 5.0: A survey on enabling technologies and potential applications
Maddikunta, P. K. R., Pham, Q.-V., B, P., Deepa, N., Dev, K., Gadekallu, T. R., Ruby, R., & Liyanage, M. (2022) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2021.100257 · Cited by 1,890
Critical Components of Industry 5.0 Towards a Successful Adoption in the Field of Manufacturing
Javaid, M., & Haleem, A. (2020) · Journal of Industrial Integration and Management · doi:10.1142/s2424862220500141 · Cited by 292
Industry 4.0 in the port and maritime industry: A literature review
de la Peña Zarzuelo, I., Freire Soeane, M. J., & López Bermúdez, B. (2020) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2020.100173 · Cited by 269
Industry’s 4.0 transformation process: How to start, where to aim, what to be aware of
Calabrese, A., Dora, M., Levialdi Ghiron, N., & Tiburzi, L. (2022) · Production Planning & Control · doi:10.1080/09537287.2020.1830315 · Cited by 109
Modelling procurement problems in the environment of blockchain technology
Yadav, S., & Prakash Singh, S. (2022) · Computers & Industrial Engineering · doi:10.1016/j.cie.2022.108546 · Cited by 33
Metadata
- Authors
- Zhang, C., & Chen, Y.
- Venue
- Journal of Industrial Integration and Management
- Publisher
- World Scientific Pub Co Pte Lt
- Published
- 2020-02-19
- Volume
- 05
- Issue
- 01
- Pages
- 165-180
- ISSN
- 2424-8622 (ISSN-L)
- 2424-8630
- OpenAlex
- W2995286220
- Cited by
- 313
- References
- 100
- FWCI
- 31.22
- Type
- journal article
- Language
- en
- Open access
- closed
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A Review of Research Relevant to the Emerging Industry Trends: Industry 4.0, IoT, Blockchain, and Business Analytics. https://app.cochat.ai/papers/10.1142/s2424862219500192
- The paper
- Zhang, C., & Chen, Y. (2020). A Review of Research Relevant to the Emerging Industry Trends: Industry 4.0, IoT, Blockchain, and Business Analytics. Journal of Industrial Integration and Management. https://doi.org/10.1142/s2424862219500192
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.