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Information Risks and Supply Chain Resilience: A Global Bibliometric Review with Agricultural Perspectives

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This study conducts a bibliometric analysis of research on information risks and supply chain risk management, focusing on insights relevant to the cattle supply chain in Malaysia. Data were collected from Scopus for 2020–2025, resulting in 451 documents analyzed using bibliometric mapping tools. The results show a rising trend in publication output, peaking in 2024, which reflects the growing academic and industry attention to supply chain resilience. The research field is interdisciplinary, with the most substantial contributions from business, engineering, and computer science, while agriculture and veterinary sciences remain less represented, signaling a notable gap. Journal articles dominate the publication types, complemented by conference papers and book chapters, emphasizing peer-reviewed knowledge dissemination. Keyword analysis highlights resilience, sustainability, and digital transformation as central themes, with emerging technologies such as blockchain, artificial intelligence, and big data analytics as key approaches for mitigating risks. Regarding geographic distribution, China, India, and the United States are leading contributors, while Malaysia shows modest but increasing participation through regional collaborations. Overall, the analysis maps global research trends and underlines the need for a stronger focus on agriculture and livestock sectors to enhance food security and supply chain sustainability.
Aizat Md Sin, M., Shabudin Ariffin, A., Farzuha Nor, N., & Fairuz Ramli, M. (2024). The Contribution of Supply Chain Risk Management Towards the Performance of the Cattle Industry in the Northern Region, Malaysia. In T. null, W. null, N. Rahmawati, S. null, R. Wulandari, F. R. Fivintari, M. Senge, A. A. Aziz, M. M. Tjale, A. B. Robani, P. Saiyut, bin K. M. F, J. Sharifuddin, H. Basha, Z. Pengfei, Y. Witono, J. H. Mulyo, & B. Krisnamurthi (Eds.), E3S Web of Conferences (Vol. 595). EDP Sciences. https://doi.org/10.1051/e3sconf/202459501035
Azadegan, A., Mellat Parast, M., Lucianetti, L., Nishant, R., & Blackhurst, J. (2020). Supply Chain Disruptions and Business Continuity: An Empirical Assessment. Decision Sciences, 51(1), 38–73. https://doi.org/10.1111/deci.12395
Bahrami, M., & Shokouhyar, S. (2022). The role of big data analytics capabilities in bolstering supply chain resilience and firm performance: a dynamic capability view. Information Technology and People, 35(5), 1621–1651. https://doi.org/10.1108/ITP-01-2021-0048
Birkel, H. S., & Hartmann, E. (2020). Internet of Things – the future of managing supply chain risks. Supply Chain Management, 25(5), 535–548. https://doi.org/10.1108/SCM-09-2019-0356
Cárdenas-Arias, C. G., Zuza-Hernández, E., Quiroga-Méndez, J. E., Lengerke-Perez, O., & Acosta-Cárdenas, O. A. (2023). Lactic acid production: a bibliometric study. Periodicals of Engineering and Natural Sciences, 11(6), 27–35. https://doi.org/10.21533/pen.v11i6.3892.g1345
Chen, Y. (2009). Research on information risk prevention in supply chain. Proceedings - International Conference on Management and Service Science, MASS 2009. https://doi.org/10.1109/ICMSS.2009.5301203
Costas, R., Van Leeuwen, T. N., & Bordons, M. (2009). A bibliometric methodology for supporting research assessment at individual level: A classification approach. 12th International Conference on Scientometrics and Informetrics, ISSI 2009, 817–828. https://www.scopus.com/inward/record.uri?eid=2-s2.0-79951947422&partnerID=40&md5=f7c3cd67e6ef3628cac79516fcb0f65a
Costas, R., Van Leeuwen, T. N., & Bordons, M. (2010). A bibliometric classificatory approach for the study and assessment of research performance at the individual level: The effects of age on productivity and impact. Journal of the American Society for Information Science and Technology, 61(8), 1564–1581. https://doi.org/10.1002/asi.21348
El Ouarrak, Y., & Hmioui, A. (2024). Communication Between Supply Chain Actors: A Risk Reduction Factor in Supply Chains. In Y. X.-S., R. S. Sherratt, N. Dey, & A. Joshi (Eds.), Lecture Notes in Networks and Systems: Vol. 695 LNNS (pp. 695–703). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-99-3043-2_56
Fallahieh, M. S., Mohezar, S., & Kanapathy, K. (2025). Data Analytics Capability Transforms Risk Management and Firm Performance. Global Business and Organizational Excellence, 44(3), 50–65. https://doi.org/10.1002/joe.22274
Foudah, A., Tarek, M., Essam, S., El Hawary, M., Adel, K., & Marzouk, M. (2024). Digital twin publications in construction (2017–2023): a bibliometrics-based visualization analysis. Construction Innovation. https://doi.org/10.1108/CI-09-2023-0229
Hallinger, P., & Kova?evi?, J. (2022). Applying bibliometric review methods in education: rationale, definitions, analytical techniques, and illustrations. In International Encyclopedia of Education: Fourth Edition (pp. 546–556). Elsevier. https://doi.org/10.1016/B978-0-12-818630-5.05070-3
Hasan, F., Setia Budi, H., Yuliana, L. T., & Sujarwadi, M. (2024). Trends of machine learning for dental caries research in Southeast Asia: insights from a bibliometric analysis. F1000Research, 13. https://doi.org/10.12688/f1000research.154704.3
Hashom, H., Ariffin, A. S., Md Sin, M. A., & Ahmad, A. (2023). Challenges in Cattle-Beef Product Supply: KLPKas Value Creation Strategic Plan. In W. null, T. null, S. null, N. Rahmawati, Z. Rozaki, R. Wulandari, M. Senge, M. F. Kamarudin, M. M. Tjale, Y. Witono, & J. H. Mulyo (Eds.), E3S Web of Conferences (Vol. 444). EDP Sciences. https://doi.org/10.1051/e3sconf/202344402009
Khan, W., Khan, S., Dhamija, A., Haseeb, M., & Ansari, S. A. (2023). Risk assessment in livestock supply chain using the MCDM method: a case of emerging economy. Environmental Science and Pollution Research, 30(8), 20688–20703. https://doi.org/10.1007/s11356-022-23640-2
Koo, M., & Lin, S.-C. (2023). An analysis of reporting practices in the top 100 cited health and medicine-related bibliometric studies from 2019 to 2021 based on a proposed guidelines. Heliyon, 9(6). https://doi.org/10.1016/j.heliyon.2023.e16780
Li, J., & Wei, R. (2022). VOSviewer Application Status and Its Knowledge Base. Journal of Library and Information Science in Agriculture, 34(6), 61–71. https://doi.org/10.13998/j.cnki.issn1002-1248.21-0843
Li, Z., Guo, H., Barenji, A. V, Wang, W. M., Guan, Y., & Huang, G. Q. (2020). A sustainable production capability evaluation mechanism based on blockchain, LSTM, analytic hierarchy process for supply chain network. International Journal of Production Research, 58(24), 7399–7419. https://doi.org/10.1080/00207543.2020.1740342
Lim, W. M., Kumar, S., & Donthu, N. (2024). How to combine and clean bibliometric data and use bibliometric tools synergistically: Guidelines using metaverse research. Journal of Business Research, 182. https://doi.org/10.1016/j.jbusres.2024.114760
Malmqvist, J., Machado, T., Meikleham, A., & Hugo, R. (2019). BIBLIOGRAPHIC DATA ANALYSIS OF CDIO CONFERENCE PAPERS FROM 2005-2018. In J. Bennedsen, A. B. Lauritsen, K. Edstrom, N. Kuptasthien, J. Roslof, & R. Songer (Eds.), Proceedings of the International CDIO Conference (pp. 816–833). Chalmers University of Technology. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145886066&partnerID=40&md5=552d45e3b93fc1678c65b3b395d16218
Marvi, R., & Foroudi, M. M. (2023). Bibliometric analysis: Main procedure and guidelines. In Researching and Analysing Business: Research Methods in Practice (pp. 43–54). Taylor and Francis. https://doi.org/10.4324/9781003107774-4
Mezquita, B., Alfonso-Arias, C., Martínez-Jaimez, P., & Borrego, Á. (2024). The use of bibliometrics in nursing science: Topics, data sources and contributions to research and practice. Nursing Open, 11(9). https://doi.org/10.1002/nop2.70036
Munir, M., Jajja, M. S. S., Chatha, K. A., & Farooq, S. (2020). Supply chain risk management and operational performance: The enabling role of supply chain integration. International Journal of Production Economics, 227. https://doi.org/10.1016/j.ijpe.2020.107667
Öztürk, O., Kocaman, R., & Kanbach, D. K. (2024). How to design bibliometric research: an overview and a framework proposal. Review of Managerial Science, 18(11), 3333–3361. https://doi.org/10.1007/s11846-024-00738-0
Sahu, K., & Chakma, S. (2024). Recent trends on hydrogel development and sustainable applications: a bibliometric analysis and concise review. Polymer Bulletin, 81(9), 7687–7711. https://doi.org/10.1007/s00289-023-05080-1
Santagata, R., Ripa, M., Genovese, A., & Ulgiati, S. (2021). Food waste recovery pathways: Challenges and opportunities for an emerging bio-based circular economy. A systematic review and an assessment. Journal of Cleaner Production, 286. https://doi.org/10.1016/j.jclepro.2020.125490
Shishodia, A., Sharma, R., Rajesh, R., & Munim, Z. H. (2023). Supply chain resilience: A review, conceptual framework and future research. International Journal of Logistics Management, 34(4), 879–908. https://doi.org/10.1108/IJLM-03-2021-0169
Siu, W. H. S., Lim, A. Y., Liu, J.-R., Chang, S.-H., Chen, W.-M., Li, P.-R., & See, L.-C. (2025). Cancer publications using real-world data from the Taiwan National Health Insurance Research Database: Conceptual framework and bibliometric analysis. Journal of the Chinese Medical Association, 88(5), 398–409. https://doi.org/10.1097/JCMA.0000000000001227
Su, L., & Zhang, X. (2011). Diagnosis and treatment of information risks in supply chain. 2011 International Conference on Computer Science and Service System, CSSS 2011 - Proceedings, 1227–1230. https://doi.org/10.1109/CSSS.2011.5974801
Tomé, P. (2024). Information Systems Field: An Analysis Through a Bibliometric Methodology. In A. Iglesias, J. Shin, B. Patel, & A. Joshi (Eds.), Lecture Notes in Networks and Systems (Vol. 834, pp. 1–8). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-99-8349-0_1
Van Eck, N. J., & Waltman, L. (2009). VOSviewer: A computer program for bibliometric mapping. 12th International Conference on Scientometrics and Informetrics, ISSI 2009, 886–897. https://www.scopus.com/inward/record.uri?eid=2-s2.0-84901992309&partnerID=40&md5=2b19eafa3759e96b197c3ec7535a731f
van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3
Vilko, J., Rumpu, A., & Koivuniemi, J. (2011). Risk management in supply chains: Information exchange, systemic motives and cognitive barriers. PICMET: Portland International Center for Management of Engineering and Technology, Proceedings. https://www.scopus.com/inward/record.uri?eid=2-s2.0-80053357961&partnerID=40&md5=6c7ae4be7135f285a300dbe92d3a5743
Wong, C. W. Y., Lirn, T.-C., Yang, C.-C., & Shang, K.-C. (2020). Supply chain and external conditions under which supply chain resilience pays: An organizational information processing theorization. International Journal of Production Economics, 226. https://doi.org/10.1016/j.ijpe.2019.107610
Xu, M., Yang, X., & Sun, Z. (2025). Risk Identification and Prevention of Supply Chain Operation in Small and Medium-Sized Livestock Farms. Systems, 13(5). https://doi.org/10.3390/systems13050308
Xu, S., Zhang, X., Feng, L., & Yang, W. (2020). Disruption risks in supply chain management: a literature review based on bibliometric analysis. International Journal of Production Research, 58(11), 3508–3526. https://doi.org/10.1080/00207543.2020.1717011
Yang-Ngam, C., Chankoson, T., & Aodton, P. (2019). Influence of internal and external factors on supply chain information system risk management implementation. International Journal of Supply Chain Management, 8(2), 612–623. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064973733&partnerID=40&md5=728d9557814c704ca805a97b6e0c8812
Zhang, Y., Wang, X., Zhang, G., & Lu, J. (2018). Predicting the dynamics of scientific activities: A diffusion-based network analytic methodology. Proceedings of the Association for Information Science and Technology, 55(1), 598–607. https://doi.org/10.1002/pra2.2018.14505501065
Sin, M. A. M., & Ariffin, A. S. (2025). Information Risks and Supply Chain Resilience: A Global Bibliometric Review with Agricultural Perspectives. International Journal of Academic Research in Business and Social Sciences, 15(9), 618–638.