{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T03:18:10Z","timestamp":1793762290588,"version":"4.6.1"},"reference-count":79,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T00:00:00Z","timestamp":1787184000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Foods"],"abstract":"<jats:p>The implementation of Hazard Analysis and Critical Control Points (HACCP) systems remains a cornerstone of food safety management. However, their effectiveness is influenced by organizational, human, and technological factors. This study investigates professional perceptions of HACCP implementation and explores the extent to which a large language model (LLM)\u2014ChatGPT 4.1\u2014can approximate human judgments in this domain. A structured questionnaire was administered to 90 professionals operating in food service, hospitality, industry, and consultancy. Responses were compared with outputs generated by ChatGPT 4.1 via a standardized multi-persona prompting protocol simulating five professional roles. To enhance response stability and minimize stochastic variation, each question was submitted in independent zero-shot sessions over multiple iterations. Responses were analysed across three thematic dimensions: barriers to HACCP implementation, perceived benefits, and digital readiness. Spearman correlation analysis of human responses revealed a systemic \u201ctraining\u2013turnover association,\u201d where high staff turnover (r = 0.62, p &lt; 0.01) was significantly associated with difficulties in maintaining continuous training. Statistical benchmarking using one-sample t-tests showed that the tested model generated significantly higher ratings for implementation barriers (p &lt; 0.001) and digital readiness (p &lt; 0.001) than the corresponding human assessments. These findings suggest that while ChatGPT can approximate aggregated professional perceptions in certain areas, notable divergences persist in operational and readiness-related domains. The study contributes methodological insights into human\u2013AI comparative research and highlights opportunities and limitations of AI-supported decision-making in food safety management systems.<\/jats:p>","DOI":"10.3390\/foods15162916","type":"journal-article","created":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T09:48:31Z","timestamp":1787219311000},"page":"2916","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Can ChatGPT Reflect Professional HACCP Judgments? A Comparative Study in Hospitality Food Safety"],"prefix":"10.3390","volume":"15","author":[{"given":"Despoina Maria","family":"Konstantinidi","sequence":"first","affiliation":[{"name":"Laboratory of Hygiene and Environmental Protection, Medical School, Democritus University of Thrace, 68100 Alexandroupolis, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8299-9035","authenticated-orcid":false,"given":"Elisavet","family":"Stavropoulou","sequence":"additional","affiliation":[{"name":"Laboratory of Hygiene and Environmental Protection, Medical School, Democritus University of Thrace, 68100 Alexandroupolis, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0303-0809","authenticated-orcid":false,"given":"Agathangelos","family":"Stavropoulos","sequence":"additional","affiliation":[{"name":"Laboratory of Hygiene and Environmental Protection, Medical School, Democritus University of Thrace, 68100 Alexandroupolis, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8035-1710","authenticated-orcid":false,"given":"Chrysoula (Chrysa)","family":"Voidarou","sequence":"additional","affiliation":[{"name":"Department of Agriculture, School of Agriculture, University of Ioannina, 47100 Arta, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7869-6824","authenticated-orcid":false,"given":"Christina","family":"Tsigalou","sequence":"additional","affiliation":[{"name":"Laboratory of Hygiene and Environmental Protection, Medical School, Democritus University of Thrace, 68100 Alexandroupolis, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1951-8489","authenticated-orcid":false,"given":"Vassiliki","family":"Pitiriga","sequence":"additional","affiliation":[{"name":"Department of Microbiology, Medical School, University of Athens, 11527 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2459-2963","authenticated-orcid":false,"given":"Christos","family":"Stefanis","sequence":"additional","affiliation":[{"name":"Laboratory of Hygiene and Environmental Protection, Medical School, Democritus University of Thrace, 68100 Alexandroupolis, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"851","DOI":"10.71000\/dtdm8185","article-title":"Emerging trends in food safety and quality management","volume":"3","author":"Aslam","year":"2025","journal-title":"Insights J. 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