{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T09:11:24Z","timestamp":1784020284591,"version":"3.55.0"},"reference-count":58,"publisher":"SAGE Publications","issue":"8","license":[{"start":{"date-parts":[[2024,12,25]],"date-time":"2024-12-25T00:00:00Z","timestamp":1735084800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32000753"],"award-info":[{"award-number":["32000753"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Hum Factors"],"published-print":{"date-parts":[[2025,8]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study investigated the effect of reliability on the function allocation (FA) boundary by examining the interaction effect of degree of automation (DOA) and reliability on routine performance, failure performance, and attention allocation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>According to the lumberjack effect, an increase in DOA will typically improve routine performance, while failure performance may remain undeteriorated until a specific, high DOA threshold is reached. This threshold can be regarded as the FA boundary. Considering that both DOA and reliability can influence failure performance through attention allocation, it is crucial to investigate how reliability affects the FA boundary.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>Participants performed three MATB tasks, one of which, the system monitoring task, was supported by four types of automation: information acquisition (IAc), information analysis (IAn), action selection (AS), and action implementation (AI). From IAc to AI, the DOA incrementally increased. Additionally, automation reliability was set to three levels, namely, 87.50%, 68.75%, and 56.25%.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>For routine performance, participants assisted by AS reacted more rapidly to gauge malfunctions than those supported by IAc or IAn. For failure performance, participants aided by AI corrected gauge malfunctions less frequently than other participants. Correspondingly, participants supported by AI exhibited fewer fixation counts on the system monitoring task than did others.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>It appears that the FA boundary lies between AS and AI. However, there is insufficient evidence to support the effect of reliability on the FA boundary.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Application<\/jats:title>\n                    <jats:p>These findings can provide useful insights for improving the design of automated systems in complex working environments.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/00187208241311808","type":"journal-article","created":{"date-parts":[[2024,12,25]],"date-time":"2024-12-25T21:28:01Z","timestamp":1735162081000},"page":"757-775","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Where Is the Function Allocation Boundary? 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