A Model for Integrating Digital Technology into Hazard Analysis and Critical Control Points (HACCP) Systems to Improve Food Safety in Small-Scale Industries
Keywords:
Digital HACCP, Food Safety, Small-Scale Industry, Food Safety CultureAbstract
This study aims to develop a model for integrating digital technology into Hazard Analysis and Critical Control Points (HACCP) systems to improve food safety in small-scale food industries. The issue addressed in this study concerns the gap between existing food safety practices and the limited capacity of small enterprises to conduct systematic documentation, monitoring, and traceability. This research employed a qualitative case study approach involving business owners, production supervisors, food processing workers, quality control personnel, food safety consultants, and relevant institutional stakeholders. Data were collected through semi-structured interviews, field observations, and document analysis, then analyzed using thematic analysis. The findings reveal five main themes: informal food safety practices, documentation constraints, limited digital readiness, the importance of leadership and food safety culture, and the need for a gradual digital integration model. The study shows that digital HACCP can improve food safety when supported by simple tools, worker training, managerial commitment, and routine evaluation. The proposed model contributes to food safety management literature by framing digital HACCP as a socio-technical process rather than a purely technological intervention. Practically, the findings provide guidance for small-scale food industries and policymakers in designing affordable, usable, and scalable digital food safety systems. Further research should test the model in different food sectors and examine its measurable impact on food safety performance.
References
Allam, M., et al. (2023). Assistance needed for increasing knowledge of HACCP food safety principles for organic sector in selected EU countries. Sustainability, 15(8), 6605. https://doi.org/10.3390/su15086605
Balamurugan, S., Ayyasamy, A., & Joseph, K. S. (2022). IoT-blockchain driven traceability techniques for improved safety measures in food supply chain. International Journal of Information Technology, 14, 1087–1098. https://doi.org/10.1007/s41870-020-00581-y
Braun, V., & Clarke, V. (2021). To saturate or not to saturate? Qualitative Research in Sport, Exercise and Health, 13(2), 201–216. https://doi.org/10.1080/2159676X.2019.1704846
Byrne, D. (2022). A worked example of Braun and Clarke’s approach to reflexive thematic analysis. Quality & Quantity, 56, 1391–1412. https://doi.org/10.1007/s11135-021-01182-y
Campbell, S., et al. (2020). Purposive sampling: Complex or simple? Journal of Research in Nursing, 25(8), 652–661. https://doi.org/10.1177/1744987120927206
Cao, S., et al. (2023). Blockchain traceability for sustainability communication in food supply chains. Sustainability, 15(18), 13486. https://doi.org/10.3390/su151813486
Dasaklis, T. K., et al. (2022). Blockchain-enabled supply chain traceability implementations. Sustainability, 14(4), 2439. https://doi.org/10.3390/su14042439
de Andrade, M. L., et al. (2020). Food safety culture in food services. Food Control, 112, 107152. https://doi.org/10.1016/j.foodcont.2020.107152
Hassoun, A., et al. (2024). The fourth industrial revolution in the food industry. Critical Reviews in Food Science and Nutrition, 64(2), 407–437. https://doi.org/10.1080/10408398.2022.2106472
Hennink, M., & Kaiser, B. N. (2022). Sample sizes for saturation in qualitative research. Social Science & Medicine, 292, 114523. https://doi.org/10.1016/j.socscimed.2021.114523
Iftekhar, A., & Cui, X. (2021). Blockchain-based traceability system. Foods, 10(6), 1289. https://doi.org/10.3390/foods10061289
Johnson, J. L., Adkins, D., & Chauvin, S. (2020). Quality indicators of rigor in qualitative research. American Journal of Pharmaceutical Education, 84(1), 7120. https://doi.org/10.5688/ajpe7120
Lee, J. C., Neonaki, M., Alexopoulos, A., & Varzakas, T. (2023). Food safety management systems in SMEs. Foods, 12(17), 3218. https://doi.org/10.3390/foods12173218
Lobe, B., Morgan, D., & Hoffman, K. A. (2020). Qualitative data collection in an era of social distancing. International Journal of Qualitative Methods, 19, 1–8. https://doi.org/10.1177/1609406920937875
Lu, Y., Li, P., & Xu, H. (2022). Blockchain and IoT food traceability system. Procedia Computer Science, 199, 629–636. https://doi.org/10.1016/j.procs.2022.01.077
Nair, S. S., et al. (2023). Assessing food safety compliance in a small-scale food company. Applied Sciences, 13(22), 12190. https://doi.org/10.3390/app132212190
Pai, A. S., Jaiswal, S., & Jaiswal, A. K. (2024). Food safety culture in the food industry. Foods, 13(24), 4078. https://doi.org/10.3390/foods13244078
Patel, A. S., et al. (2023). Blockchain technology in food safety and traceability. Heliyon, 9(6), e16526. https://doi.org/10.1016/j.heliyon.2023.e16526
Radu, E., et al. (2023). Global trends and research hotspots on HACCP. Heliyon, 9(7), e18232. https://doi.org/10.1016/j.heliyon.2023.e18232
Revelou, P. K., Giaouris, E., & Skandamis, P. N. (2025). Machine learning applications in food safety. Foods, 14(6), 922. https://doi.org/10.3390/foods14060922
Sartoni, M., Semercioz Oduncuoglu, A. S., Guidi, A., Annosi, M. C., & Luning, P. A. (2025). Towards digitalisation of food safety management systems. Food Control, 168, 110952. https://doi.org/10.1016/j.foodcont.2024.110952
Singh, A., Gutub, A., Nayyar, A., & Khan, M. K. (2023). Redefining food safety traceability through blockchain. Multimedia Tools and Applications, 82, 21243–21277. https://doi.org/10.1007/s11042-022-14006-4
Zarid, M. (2025). The green HACCP approach: Advancing food safety and sustainability. Sustainability, 17(17), 7834. https://doi.org/10.3390/su17177834
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
