{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T21:07:08Z","timestamp":1774040828773,"version":"3.50.1"},"reference-count":60,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100012456","name":"National Social Science Fund of China","doi-asserted-by":"publisher","award":["25CZZ020"],"award-info":[{"award-number":["25CZZ020"]}],"id":[{"id":"10.13039\/501100012456","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002701","name":"Ministry of Education","doi-asserted-by":"publisher","award":["24YJC850012"],"award-info":[{"award-number":["24YJC850012"]}],"id":[{"id":"10.13039\/501100002701","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013139","name":"Humanities and Social Science Fund of Ministry of Education of China","doi-asserted-by":"publisher","award":["22JJD630001"],"award-info":[{"award-number":["22JJD630001"]}],"id":[{"id":"10.13039\/501100013139","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers in Human Behavior"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1016\/j.chb.2026.108967","type":"journal-article","created":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T00:17:13Z","timestamp":1772583433000},"page":"108967","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Can AI reflect public opinion? Evidence from replicating Hainmueller and Hopkins\u2019 immigration experiment with LLMs"],"prefix":"10.1016","volume":"181","author":[{"given":"Yajing","family":"Chen","sequence":"first","affiliation":[]},{"given":"Ming","family":"Lei","sequence":"additional","affiliation":[]},{"given":"Zhanyu","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Man","family":"Tang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9475-0536","authenticated-orcid":false,"given":"Jie","family":"She","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.chb.2026.108967_bib1","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1017\/pan.2023.2","article-title":"Out of one, many: Using language models to simulate human samples","volume":"31","author":"Argyle","year":"2023","journal-title":"Political Analysis"},{"key":"10.1016\/j.chb.2026.108967_bib2","first-page":"1","article-title":"Synthetic replacements for human survey data? The perils of large language models","author":"Bisbee","year":"2023","journal-title":"Political Analysis"},{"key":"10.1016\/j.chb.2026.108967_bib3","first-page":"23","article-title":"Using GPT for market research","author":"Brand","year":"2023","journal-title":"Harvard Bus. Sch. Mark. Unit Work. Pap"},{"key":"10.1016\/j.chb.2026.108967_bib4","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1017\/S0143814X18000491","article-title":"Policy feedback in the local context: Analysing fairness perceptions of public childcare fees in a German town","volume":"40","author":"Busemeyer","year":"2020","journal-title":"Journal of Public Policy"},{"key":"10.1016\/j.chb.2026.108967_bib5","doi-asserted-by":"crossref","DOI":"10.1016\/j.giq.2024.101988","article-title":"Exploiting GPT for synthetic data generation: An empirical study","volume":"42","author":"Busker","year":"2025","journal-title":"Government Information Quarterly"},{"key":"10.1016\/j.chb.2026.108967_bib6","first-page":"1","article-title":"A manager and an AI walk into a bar: Does ChatGPT make biased decisions like we do?","author":"Chen","year":"2025","journal-title":"Manufacturing & Service Operations Management"},{"key":"10.1016\/j.chb.2026.108967_bib7","doi-asserted-by":"crossref","DOI":"10.1073\/pnas.2316205120","article-title":"The emergence of economic rationality of GPT","volume":"120","author":"Chen","year":"2023","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"10.1016\/j.chb.2026.108967_bib8","article-title":"Marked personas: Using natural language prompts to measure stereotypes in language models","author":"Cheng","year":"2023","journal-title":"arXiv Prepr. arXiv:2305.18189"},{"key":"10.1016\/j.chb.2026.108967_bib9","first-page":"1","article-title":"Large language models show amplified cognitive biases in moral","volume":"122","author":"Cheung","year":"2025","journal-title":"Proceedings of the National Academy of Sciences of the United States of America"},{"key":"10.1016\/j.chb.2026.108967_bib10","article-title":"Inducing anxiety in large language models increases exploration and bias","author":"Coda-Forno","year":"2023","journal-title":"arXiv Prepr. arXiv2304.11111"},{"key":"10.1016\/j.chb.2026.108967_bib11","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1016\/j.tics.2023.04.008","article-title":"Can AI language models replace human participants?","volume":"27","author":"Dillion","year":"2023","journal-title":"Trends in Cognitive Sciences"},{"key":"10.1016\/j.chb.2026.108967_bib12","article-title":"Strong model collapse","author":"Dohmatob","year":"2024","journal-title":"arXiv Prepr. arXiv:2410.04840"},{"key":"10.1016\/j.chb.2026.108967_bib13","first-page":"1","article-title":"Take caution in using LLMs as human surrogates","volume":"122","author":"Gao","year":"2025","journal-title":"Proceedings of the National Academy of Sciences of the United States of America"},{"key":"10.1016\/j.chb.2026.108967_bib14","doi-asserted-by":"crossref","DOI":"10.1126\/sciadv.adz2924","article-title":"Source framing triggers systematic bias in large language models","volume":"11","author":"Germani","year":"2025","journal-title":"Science Advances"},{"key":"10.1016\/j.chb.2026.108967_bib15","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1038\/d41586-024-02420-7","article-title":"AI models fed AI-generated data quickly spew nonsense","volume":"632","author":"Gibney","year":"2024","journal-title":"Nature"},{"key":"10.1016\/j.chb.2026.108967_bib16","article-title":"Frontiers: Can large language models capture human preferences? Mark","volume":"43","author":"Goli","year":"2024","journal-title":"Science"},{"key":"10.1016\/j.chb.2026.108967_bib17","article-title":"Bias runs deep: Implicit reasoning biases in persona-assigned LLMs","author":"Gupta","year":"2023","journal-title":"arXiv Prepr. arXiv:2311.04892"},{"key":"10.1016\/j.chb.2026.108967_bib18","article-title":"Language models represent space and time","author":"Gurnee","year":"2023","journal-title":"arXiv Prepr. arXiv:2310.02207"},{"key":"10.1016\/j.chb.2026.108967_bib19","series-title":"Replication data for: The hidden American immigration consensus: A conjoint analysis of attitudes toward immigrants","author":"Hainmueller","year":"2014"},{"key":"10.1016\/j.chb.2026.108967_bib20","first-page":"529","article-title":"The hidden American immigration consensus: A conjoint analysis of attitudes toward immigrants","volume":"59","author":"Hainmueller","year":"2015","journal-title":"American Journal of Polymer Science"},{"key":"10.1016\/j.chb.2026.108967_bib21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/pan\/mpt024","article-title":"Causal inference in conjoint analysis: Understanding multidimensional choices via stated preference experiments","volume":"22","author":"Hainmueller","year":"2014","journal-title":"Political Analysis"},{"key":"10.1016\/j.chb.2026.108967_bib22","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1111\/coep.12511","article-title":"Attribute nonattendance and citizen preferences for ecosystem-based fisheries management: The case of Atlantic menhaden","volume":"39","author":"Harrison","year":"2021","journal-title":"Contemporary Economic Policy"},{"key":"10.1016\/j.chb.2026.108967_bib23","article-title":"The political ideology of conversational AI: Converging evidence on ChatGPT's pro-environmental, left-libertarian orientation","author":"Hartmann","year":"2021","journal-title":"arXiv Prepr. arXiv:2301.01768"},{"key":"10.1016\/j.chb.2026.108967_bib24","author":"Horton"},{"key":"10.1016\/j.chb.2026.108967_bib25","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1177\/14651165211006838","article-title":"What asylum and refugee policies do Europeans want? Evidence from a cross-national conjoint experiment","volume":"22","author":"Jeannet","year":"2021","journal-title":"European Union Politics"},{"key":"10.1016\/j.chb.2026.108967_bib26","series-title":"Decisions with multiple objectives: Preferences and value trade-offs","author":"Keeney","year":"1993"},{"key":"10.1016\/j.chb.2026.108967_bib27","doi-asserted-by":"crossref","first-page":"916","DOI":"10.1080\/14693062.2017.1389688","article-title":"Smallholder farmers' participation in climate change adaptation programmes: Understanding preferences in Nepal","volume":"18","author":"Khanal","year":"2018","journal-title":"Climate Policy"},{"key":"10.1016\/j.chb.2026.108967_bib28","article-title":"Humans in humans out: On GPT converging toward common sense in both success and failure","author":"Koralus","year":"2023","journal-title":"arXiv Prepr. arXiv:2303.17276"},{"key":"10.1016\/j.chb.2026.108967_bib29","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1080\/13501763.2019.1701529","article-title":"Preferences for European unemployment insurance: A question of economic ideology or EU support?","volume":"27","author":"Kuhn","year":"2020","journal-title":"Journal of European Public Policy"},{"key":"10.1016\/j.chb.2026.108967_bib30","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1017\/pan.2019.30","article-title":"Measuring subgroup preferences in conjoint experiments","volume":"28","author":"Leeper","year":"2020","journal-title":"Political Analysis"},{"key":"10.1016\/j.chb.2026.108967_bib31","article-title":"Emergent world representations: Exploring a sequence model trained on a synthetic task","author":"Li","year":"2022","journal-title":"arXiv Prepr. arXiv:2210.13382"},{"key":"10.1016\/j.chb.2026.108967_bib32","article-title":"Political-LLM: Large language models in political science","author":"Li","year":"2024","journal-title":"arXiv Prepr. arXiv:2412.06864"},{"key":"10.1016\/j.chb.2026.108967_bib33","article-title":"Dissecting human and LLM preferences","author":"Li","year":"2024","journal-title":"arXiv Prepr. arXiv:2402.11296"},{"key":"10.1016\/j.chb.2026.108967_bib34","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2025.104099","article-title":"Towards realistic evaluation of cultural value alignment in large language models: Diversity enhancement for survey response simulation","volume":"62","author":"Liu","year":"2025","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.chb.2026.108967_bib35","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1177\/1094428109341992","article-title":"Conjoint analysis in entrepreneurship research: A review and research agenda","volume":"13","author":"Lohrke","year":"2010","journal-title":"Organizational Research Methods"},{"key":"10.1016\/j.chb.2026.108967_bib36","article-title":"Fantastically ordered prompts and where to find them: Overcoming few-shot prompt order sensitivity","author":"Lu","year":"2021","journal-title":"arXiv Prepr. arXiv:2104.08786"},{"key":"10.1016\/j.chb.2026.108967_bib37","article-title":"Prompt architecture can induce methodological artifacts in large language models","author":"Melanie Brucks","year":"2023","journal-title":"SSRN 4484416"},{"key":"10.1016\/j.chb.2026.108967_bib38","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s11127-023-01097-2","article-title":"More human than human: Measuring ChatGPT political bias","volume":"198","author":"Motoki","year":"2024","journal-title":"Public Choice"},{"key":"10.1016\/j.chb.2026.108967_bib39","article-title":"GPT-4 technical report","year":"2023","journal-title":"arXiv Prepr. arXiv:2303.08774"},{"key":"10.1016\/j.chb.2026.108967_bib40","first-page":"27730","article-title":"Training language models to follow instructions with human feedback","volume":"35","author":"Ouyang","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.chb.2026.108967_bib41","series-title":"The adaptive decision maker","author":"Payne","year":"1993"},{"key":"10.1016\/j.chb.2026.108967_bib42","series-title":"Prompt engineering for generative AI: Future-proof inputs for reliable AI outputs","author":"Phoenix","year":"2024"},{"key":"10.1016\/j.chb.2026.108967_bib43","article-title":"AgentSociety: Large-scale simulation of LLM-driven generative agents advances understanding of human behaviors and society","author":"Piao","year":"2025","journal-title":"arXiv Prepr. arXiv:2502.08691v1"},{"key":"10.1016\/j.chb.2026.108967_bib44","doi-asserted-by":"crossref","DOI":"10.2139\/ssrn.4526072","article-title":"Consumer risk preferences elicitation from large language models","author":"Qiu","year":"2023","journal-title":"SSRN 4526072"},{"key":"10.1016\/j.chb.2026.108967_bib45","series-title":"Qwen2 technical report. arXiv Prepr. arXiv:2407.10671","year":"2024"},{"key":"10.1016\/j.chb.2026.108967_bib46","article-title":"Qwen2.5 technical report","year":"2024","journal-title":"arXiv Prepr. arXiv:2412.15115"},{"key":"10.1016\/j.chb.2026.108967_bib47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pone.0306621","article-title":"The political preferences of LLMs","volume":"19","author":"Rozado","year":"2024","journal-title":"PLoS One"},{"key":"10.1016\/j.chb.2026.108967_bib48","doi-asserted-by":"crossref","DOI":"10.1016\/j.giq.2024.101953","article-title":"Automation bias in public administration \u2013 An interdisciplinary perspective from law and psychology","volume":"41","author":"Ruschemeier","year":"2024","journal-title":"Government Information Quarterly"},{"key":"10.1016\/j.chb.2026.108967_bib49","article-title":"In-context impersonation reveals large language models' strengths and biases","volume":"36","author":"Salewski","year":"2024","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.chb.2026.108967_bib50","series-title":"International conference on machine learning","first-page":"29971","article-title":"Whose opinions do language models reflect?","author":"Santurkar","year":"2023"},{"key":"10.1016\/j.chb.2026.108967_bib51","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1038\/s42256-022-00458-8","article-title":"Large pre-trained language models contain human-like biases of what is right and wrong to do","volume":"4","author":"Schramowski","year":"2022","journal-title":"Nature Machine Intelligence"},{"key":"10.1016\/j.chb.2026.108967_bib52","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1038\/s41586-023-06647-8","article-title":"Role play with large language models","volume":"623","author":"Shanahan","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.chb.2026.108967_bib53","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1038\/s41586-024-07566-y","article-title":"AI models collapse when trained on recursively generated data","volume":"631","author":"Shumailov","year":"2024","journal-title":"Nature"},{"key":"10.1016\/j.chb.2026.108967_bib54","first-page":"5861","article-title":"Process for adapting language models to society (PALMS) with values-targeted datasets","volume":"34","author":"Solaiman","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.chb.2026.108967_bib55","doi-asserted-by":"crossref","DOI":"10.1098\/rsos.231393","article-title":"The moral machine experiment on large language models","volume":"11","author":"Takemoto","year":"2024","journal-title":"Royal Society Open Science"},{"key":"10.1016\/j.chb.2026.108967_bib56","first-page":"6000","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.chb.2026.108967_bib57","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1006\/obhd.1994.1087","article-title":"SMARTS and SMARTER: Improved simple methods for multiattribute utility measurement","volume":"60","author":"Ward","year":"1994","journal-title":"Organizational Behavior and Human Decision Processes"},{"key":"10.1016\/j.chb.2026.108967_bib58","article-title":"Expertprompting: Instructing large language models to be distinguished experts","author":"Xu","year":"2023","journal-title":"arXiv Prepr"},{"key":"10.1016\/j.chb.2026.108967_bib59","article-title":"LLM-RankFusion: Mitigating intrinsic inconsistency in LLM-based ranking","author":"Zeng","year":"2024","journal-title":"arXiv Prepr. arXiv: 2406.00231"},{"key":"10.1016\/j.chb.2026.108967_bib60","article-title":"ElectionSim: Massive population election simulation powered by large language model driven agents","author":"Zhang","year":"2024","journal-title":"arXiv Prepr. arXiv:2410.20746v3"}],"container-title":["Computers in Human Behavior"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0747563226000646?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0747563226000646?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T19:19:21Z","timestamp":1774034361000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0747563226000646"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":60,"alternative-id":["S0747563226000646"],"URL":"https:\/\/doi.org\/10.1016\/j.chb.2026.108967","relation":{},"ISSN":["0747-5632"],"issn-type":[{"value":"0747-5632","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Can AI reflect public opinion? Evidence from replicating Hainmueller and Hopkins\u2019 immigration experiment with LLMs","name":"articletitle","label":"Article Title"},{"value":"Computers in Human Behavior","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.chb.2026.108967","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"108967"}}