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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM68175
Volume:
10 |
10 |
Oct 2026
Pages:
1-20
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Bachelor of Business Administration (BBA)
Anil Surendra Modi School of Commerce (ASMSOC), SVKM's NMIMS, Mumbai
Bachelor of Business Administration (BBA)
Anil Surendra Modi School of Commerce (ASMSOC), SVKM's NMIMS, Mumbai
Bachelor of Business Administration (BBA)
Anil Surendra Modi School of Commerce (ASMSOC), SVKM's NMIMS, Mumbai
Bachelor of Business Administration (BBA)
Anil Surendra Modi School of Commerce (ASMSOC), SVKM's NMIMS, Mumbai
Bachelor of Business Administration (BBA)
Anil Surendra Modi School of Commerce (ASMSOC), SVKM's NMIMS, Mumbai
Bachelor of Business Administration (BBA)
Anil Surendra Modi School of Commerce (ASMSOC), SVKM's NMIMS, Mumbai
Analytics now shapes how hospitals treat patients, how medicines reach the right cells, and how parcels, power and online courses reach their users. This study maps the research that links delivery and analytics. We searched the Scopus database with the query "Delivery AND Analytics" and, after screening, kept 2,802 journal documents (2,195 articles and 607 reviews) published between 2014 and 2027. Biblioshiny (Bibliometrix) and VOSviewer were used to study publication and citation trends, leading authors, sources and countries, and the keyword structure of the field. Output grew from 52 papers in 2014 to 544 in 2026, about 21.6 per cent a year, and 2025 and 2026 together hold 38.4 per cent of all documents. Health care dominates: about six in ten documents deal with patients, hospitals or clinical care, and "health care delivery" is the most frequent subject term once generic indexing labels are set aside. The keyword maps show four groups: health-care delivery and management, analytics methods and digital technology, clinical study terms, and drug delivery with precision medicine. Logistics and last-mile delivery form a smaller strand that is growing quickly. The paper also reports the limits of the data. The export has no cited references, so co-citation and bibliographic coupling could not be run, and the word "delivery" covers very different subjects, such as parcel routing and nanoparticle drug carriers.
KEYWORDS
The analysis covers 2,802 documents retrieved from Scopus with the query "Delivery AND Analytics" and published between 2014 and 2027. For RQ1, output rose from 52 documents in 2014 to 544 in 2026, an average growth of 21.6 per cent a year. The path was uneven: output dipped in 2022 and 2023, then more than doubled in 2025. The years 2025 and 2026 hold 38.4 per cent of the set, and 2026 is incomplete. Mean citations fall from 87.4 per paper for 2014 to 1.1 for 2026, because recent papers have had less time to be cited. The median is 7 citations, 549 papers have none, and the top 10 per cent of papers hold 63.3 per cent of all citations, so impact is concentrated in a small set of mostly older work. For RQ2, the field is large and spread out, with 12,328 authors and 1,634 sources. Papers have 4.99 authors on average and only 9.1 per cent are single-authored. The United States accounts for 28.6 per cent of author appearances, India for 11.4 per cent and China for 7.4 per cent. The most productive author labels (Wang Y, Kumar A, Zhang Y) each combine many different people, so author rankings should be read with care. Multi-country papers (30.8 per cent) average 36.3 citations against 22.3 for single-country papers. The gap is statistically significant, though reviews account for part of it. For RQ3, the keyword maps at thresholds of 30, 35 and 40 give the same four clusters: health-care delivery and management, analytics methods and digital technology, clinical and population study terms, and drug delivery with precision medicine. Health care is the core of the field and appears in about six of every ten documents, but its share is falling as logistics and education studies grow. Methods have moved from big data towards machine learning, artificial intelligence and, since 2024, large language models (Bates et al., 2014; Jiang et al., 2017; Liu et al., 2021; Gencer & Gencer, 2025). For RQ4, the main limits come from the export and the search. All cited-reference fields are empty, so co-citation analysis and bibliographic coupling cannot be done. Index keywords are missing for 30.2 per cent of records, and generic indexer labels such as "human" and "article" dominate the maps. The query joins fields that share a word but little else, such as nanoparticle drug carriers and parcel routing, so citation totals and clusters describe the retrieved set rather than one research community. The two 2027 records were kept to match the screening flow, which makes Biblioshiny report a negative growth rate. Recent papers have had less time to gather citations, so their lower counts do not by themselves show lower quality. Within these limits, the counts and maps show how research on delivery and analytics has grown, where it comes from and how its themes have shifted. Later studies would gain from narrower queries for each field of delivery, an export that includes cited references, and conclusions that stay within what the chosen data can support.
1. Ahmad, T., Madonski, R., Zhang, D., Huang, C., & Mujeeb, A. (2022). Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the context of smart grid paradigm. Renewable and Sustainable Energy Reviews, 160, 112128. https://doi.org/10.1016/j.rser.2022.112128 2. Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007 3. Arji, G., Ahmadi, H., Avazpoor, P., & Hemmat, M. (2023). Identifying resilience strategies for disruption management in the healthcare supply chain during COVID-19 by digital innovations: A systematic literature review. Informatics in Medicine Unlocked, 38, 101199. https://doi.org/10.1016/j.imu.2023.101199 4. Bag, S., Dhamija, P., Singh, R. K., Rahman, M. S., & Sreedharan, V. R. (2023). Big data analytics and artificial intelligence technologies based collaborative platform empowering absorptive capacity in health care supply chain: An empirical study. Journal of Business Research, 154, 113315. https://doi.org/10.1016/j.jbusres.2022.113315 5. Bates, D. W., Saria, S., Ohno-Machado, L., Shah, A., & Escobar, G. (2014). Big data in health care: Using analytics to identify and manage high-risk and high-cost patients. Health Affairs, 33(7), 1123-1131. https://doi.org/10.1377/hlthaff.2014.0041 6. Belle, A., Thiagarajan, R., Soroushmehr, S. M. R., Navidi, F., Beard, D. A., & Najarian, K. (2015). Big data analytics in healthcare. BioMed Research International, 2015, 370194. https://doi.org/10.1155/2015/370194 7. Bibri, S. E. (2018). The IoT for smart sustainable cities of the future: An analytical framework for sensor-based big data applications for environmental sustainability. Sustainable Cities and Society, 38, 230-253. https://doi.org/10.1016/j.scs.2017.12.034 8. Cavalcante, I. M., Frazzon, E. M., Forcellini, F. A., & Ivanov, D. (2019). A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing. International Journal of Information Management, 49, 86-97. https://doi.org/10.1016/j.ijinfomgt.2019.03.004 9. Chae, B. (2015). Insights from hashtag and Twitter analytics: Considering Twitter and Twitter data for supply chain practice and research. International Journal of Production Economics, 165, 247-259. https://doi.org/10.1016/j.ijpe.2014.12.037 10. Chatfield, A. T., & Reddick, C. G. (2018). Customer agility and responsiveness through big data analytics for public value creation: A case study of Houston 311 on-demand services. Government Information Quarterly, 35(2), 336-347. https://doi.org/10.1016/j.giq.2017.11.002
Publication Date
10/22/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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