Loading…
Convenient or risky? Investigating the behavioral intention to use facial recognition payment in smart hospitals
This study investigates the factors influencing users’ behavioral intention to adopt facial recognition payment (FRP) in smart hospitals, considering convenience and potential risks. The unified theory of acceptance and use of technology (UTAUT), the diffusion of innovations theory, and trust theory...
Saved in:
Published in: | Humanities & social sciences communications 2024-11, Vol.11 (1), p.1592-20, Article 1592 |
---|---|
Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | cdi_FETCH-LOGICAL-c266t-b9b8c21b8ee4982155042d6eff9cd77e5d1ad5d247291d2a81971af3465284f43 |
container_end_page | 20 |
container_issue | 1 |
container_start_page | 1592 |
container_title | Humanities & social sciences communications |
container_volume | 11 |
creator | Yu, Teng Teoh, Ai Ping Wang, Chengliang Bian, Qing |
description | This study investigates the factors influencing users’ behavioral intention to adopt facial recognition payment (FRP) in smart hospitals, considering convenience and potential risks. The unified theory of acceptance and use of technology (UTAUT), the diffusion of innovations theory, and trust theory are employed to identify critical factors for promoting FRP adoption. A quantitative cross-sectional survey is conducted among smart hospital users in China, collecting 811 valid questionnaires, and the partial least squares structural equation method (PLS-SEM) is utilized for analysis. The results show that performance expectancy, effort expectancy, social influence, and facilitating conditions positively affect behavioral intention. Privacy concerns and perceived risks negatively impact trust in FRP, while familiarity enhances trust. Trust in FRP and personal innovativeness positively influence behavioral intention, with personal innovativeness moderating the trust-behavioral intention relationship. The findings emphasize the mediating role of trust in FRP and the importance of familiarity and personal innovativeness in driving FRP adoption. Gender (male or female) does not significantly impact the relationships and path coefficients in the model. However, slight discrepancies are observed between the permutation test and Henseler’s MGA in terms of the effect of privacy concerns on trust in FRP. This research contributes to the literature on users’ behavioral intentions, aiding smart hospitals in promoting FRP adoption while considering user concerns. |
doi_str_mv | 10.1057/s41599-024-03910-9 |
format | article |
fullrecord | <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_d43bdcca5e844ffcabd78470bf02a960</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_d43bdcca5e844ffcabd78470bf02a960</doaj_id><sourcerecordid>3132019514</sourcerecordid><originalsourceid>FETCH-LOGICAL-c266t-b9b8c21b8ee4982155042d6eff9cd77e5d1ad5d247291d2a81971af3465284f43</originalsourceid><addsrcrecordid>eNp9UU2L2zAUNMsWNmTzB3oS9Oyu9CzZ1qmU0G0Dgb20ZyHrw1GaSK6kBPLvV4lLt6c9PTFvZt6gqaqPBH8mmHVPiRLGeY2B1rjhBNf8rlpA20LNOYf7_94P1SqlPcYYGAEK_aKa1sGfjXfGZxQiii79vnxBm4Kl7EaZnR9R3hk0mJ08uxDlATmfC9sFj3JAp2SQlcoVPBoVRu9um0lejldL51E6ypjRLqTJZXlIj9UHW4ZZ_Z3L6tfzt5_rH_X25ftm_XVbq5I21wMfegVk6I2hvAfCGKagW2MtV7rrDNNEaqaBdsCJBtkT3hFpG9oy6KmlzbLazL46yL2YoisxLiJIJ25AiKMouZw6GKFpM2ilJDM9pdYqOeiupx0eLAbJW1y8Ps1eUwx_TuVnxD6coi_xRUMawIQzcr0IM0vFkFI09t9VgsW1KDEXJUpR4laU4EXUzKJUyH408c36HdUrDZqX0w</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3132019514</pqid></control><display><type>article</type><title>Convenient or risky? Investigating the behavioral intention to use facial recognition payment in smart hospitals</title><source>Social Science Premium Collection</source><source>ProQuest - Publicly Available Content Database</source><source>Coronavirus Research Database</source><creator>Yu, Teng ; Teoh, Ai Ping ; Wang, Chengliang ; Bian, Qing</creator><creatorcontrib>Yu, Teng ; Teoh, Ai Ping ; Wang, Chengliang ; Bian, Qing</creatorcontrib><description>This study investigates the factors influencing users’ behavioral intention to adopt facial recognition payment (FRP) in smart hospitals, considering convenience and potential risks. The unified theory of acceptance and use of technology (UTAUT), the diffusion of innovations theory, and trust theory are employed to identify critical factors for promoting FRP adoption. A quantitative cross-sectional survey is conducted among smart hospital users in China, collecting 811 valid questionnaires, and the partial least squares structural equation method (PLS-SEM) is utilized for analysis. The results show that performance expectancy, effort expectancy, social influence, and facilitating conditions positively affect behavioral intention. Privacy concerns and perceived risks negatively impact trust in FRP, while familiarity enhances trust. Trust in FRP and personal innovativeness positively influence behavioral intention, with personal innovativeness moderating the trust-behavioral intention relationship. The findings emphasize the mediating role of trust in FRP and the importance of familiarity and personal innovativeness in driving FRP adoption. Gender (male or female) does not significantly impact the relationships and path coefficients in the model. However, slight discrepancies are observed between the permutation test and Henseler’s MGA in terms of the effect of privacy concerns on trust in FRP. This research contributes to the literature on users’ behavioral intentions, aiding smart hospitals in promoting FRP adoption while considering user concerns.</description><identifier>ISSN: 2662-9992</identifier><identifier>EISSN: 2662-9992</identifier><identifier>DOI: 10.1057/s41599-024-03910-9</identifier><language>eng</language><publisher>London: Palgrave Macmillan UK</publisher><subject>4000/4008 ; 4014/4045 ; Airports ; Artificial intelligence ; Bank technology ; Consumers ; Facial recognition technology ; Gender differences ; Health insurance ; Humanities and Social Sciences ; Insurance policies ; Mobile commerce ; multidisciplinary ; Pandemics ; Patient satisfaction ; Privacy ; Restaurants ; Science ; Science (multidisciplinary) ; Technological change ; Technology adoption ; Telemedicine ; User behavior ; Web portals</subject><ispartof>Humanities & social sciences communications, 2024-11, Vol.11 (1), p.1592-20, Article 1592</ispartof><rights>The Author(s) 2024</rights><rights>The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c266t-b9b8c21b8ee4982155042d6eff9cd77e5d1ad5d247291d2a81971af3465284f43</cites><orcidid>0000-0002-9267-9094 ; 0000-0001-5198-7261 ; 0000-0003-2208-3508</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/3132019514/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/3132019514?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,21394,25753,27924,27925,33611,37012,38516,43733,43895,44590,74221,74412,75126</link.rule.ids></links><search><creatorcontrib>Yu, Teng</creatorcontrib><creatorcontrib>Teoh, Ai Ping</creatorcontrib><creatorcontrib>Wang, Chengliang</creatorcontrib><creatorcontrib>Bian, Qing</creatorcontrib><title>Convenient or risky? Investigating the behavioral intention to use facial recognition payment in smart hospitals</title><title>Humanities & social sciences communications</title><addtitle>Humanit Soc Sci Commun</addtitle><description>This study investigates the factors influencing users’ behavioral intention to adopt facial recognition payment (FRP) in smart hospitals, considering convenience and potential risks. The unified theory of acceptance and use of technology (UTAUT), the diffusion of innovations theory, and trust theory are employed to identify critical factors for promoting FRP adoption. A quantitative cross-sectional survey is conducted among smart hospital users in China, collecting 811 valid questionnaires, and the partial least squares structural equation method (PLS-SEM) is utilized for analysis. The results show that performance expectancy, effort expectancy, social influence, and facilitating conditions positively affect behavioral intention. Privacy concerns and perceived risks negatively impact trust in FRP, while familiarity enhances trust. Trust in FRP and personal innovativeness positively influence behavioral intention, with personal innovativeness moderating the trust-behavioral intention relationship. The findings emphasize the mediating role of trust in FRP and the importance of familiarity and personal innovativeness in driving FRP adoption. Gender (male or female) does not significantly impact the relationships and path coefficients in the model. However, slight discrepancies are observed between the permutation test and Henseler’s MGA in terms of the effect of privacy concerns on trust in FRP. This research contributes to the literature on users’ behavioral intentions, aiding smart hospitals in promoting FRP adoption while considering user concerns.</description><subject>4000/4008</subject><subject>4014/4045</subject><subject>Airports</subject><subject>Artificial intelligence</subject><subject>Bank technology</subject><subject>Consumers</subject><subject>Facial recognition technology</subject><subject>Gender differences</subject><subject>Health insurance</subject><subject>Humanities and Social Sciences</subject><subject>Insurance policies</subject><subject>Mobile commerce</subject><subject>multidisciplinary</subject><subject>Pandemics</subject><subject>Patient satisfaction</subject><subject>Privacy</subject><subject>Restaurants</subject><subject>Science</subject><subject>Science (multidisciplinary)</subject><subject>Technological change</subject><subject>Technology adoption</subject><subject>Telemedicine</subject><subject>User behavior</subject><subject>Web portals</subject><issn>2662-9992</issn><issn>2662-9992</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>ALSLI</sourceid><sourceid>COVID</sourceid><sourceid>M2R</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp9UU2L2zAUNMsWNmTzB3oS9Oyu9CzZ1qmU0G0Dgb20ZyHrw1GaSK6kBPLvV4lLt6c9PTFvZt6gqaqPBH8mmHVPiRLGeY2B1rjhBNf8rlpA20LNOYf7_94P1SqlPcYYGAEK_aKa1sGfjXfGZxQiii79vnxBm4Kl7EaZnR9R3hk0mJ08uxDlATmfC9sFj3JAp2SQlcoVPBoVRu9um0lejldL51E6ypjRLqTJZXlIj9UHW4ZZ_Z3L6tfzt5_rH_X25ftm_XVbq5I21wMfegVk6I2hvAfCGKagW2MtV7rrDNNEaqaBdsCJBtkT3hFpG9oy6KmlzbLazL46yL2YoisxLiJIJ25AiKMouZw6GKFpM2ilJDM9pdYqOeiupx0eLAbJW1y8Ps1eUwx_TuVnxD6coi_xRUMawIQzcr0IM0vFkFI09t9VgsW1KDEXJUpR4laU4EXUzKJUyH408c36HdUrDZqX0w</recordid><startdate>20241122</startdate><enddate>20241122</enddate><creator>Yu, Teng</creator><creator>Teoh, Ai Ping</creator><creator>Wang, Chengliang</creator><creator>Bian, Qing</creator><general>Palgrave Macmillan UK</general><general>Palgrave Macmillan</general><general>Springer Nature</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>3V.</scope><scope>7XB</scope><scope>88J</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>M2O</scope><scope>M2R</scope><scope>MBDVC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-9267-9094</orcidid><orcidid>https://orcid.org/0000-0001-5198-7261</orcidid><orcidid>https://orcid.org/0000-0003-2208-3508</orcidid></search><sort><creationdate>20241122</creationdate><title>Convenient or risky? Investigating the behavioral intention to use facial recognition payment in smart hospitals</title><author>Yu, Teng ; Teoh, Ai Ping ; Wang, Chengliang ; Bian, Qing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c266t-b9b8c21b8ee4982155042d6eff9cd77e5d1ad5d247291d2a81971af3465284f43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>4000/4008</topic><topic>4014/4045</topic><topic>Airports</topic><topic>Artificial intelligence</topic><topic>Bank technology</topic><topic>Consumers</topic><topic>Facial recognition technology</topic><topic>Gender differences</topic><topic>Health insurance</topic><topic>Humanities and Social Sciences</topic><topic>Insurance policies</topic><topic>Mobile commerce</topic><topic>multidisciplinary</topic><topic>Pandemics</topic><topic>Patient satisfaction</topic><topic>Privacy</topic><topic>Restaurants</topic><topic>Science</topic><topic>Science (multidisciplinary)</topic><topic>Technological change</topic><topic>Technology adoption</topic><topic>Telemedicine</topic><topic>User behavior</topic><topic>Web portals</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yu, Teng</creatorcontrib><creatorcontrib>Teoh, Ai Ping</creatorcontrib><creatorcontrib>Wang, Chengliang</creatorcontrib><creatorcontrib>Bian, Qing</creatorcontrib><collection>SpringerOpen</collection><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection【Remote access available】</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Social Science Database (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>ProQuest Research Library</collection><collection>Social Science Database (ProQuest)</collection><collection>Research Library (Corporate)</collection><collection>ProQuest - Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>Open Access: DOAJ - Directory of Open Access Journals</collection><jtitle>Humanities & social sciences communications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yu, Teng</au><au>Teoh, Ai Ping</au><au>Wang, Chengliang</au><au>Bian, Qing</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Convenient or risky? Investigating the behavioral intention to use facial recognition payment in smart hospitals</atitle><jtitle>Humanities & social sciences communications</jtitle><stitle>Humanit Soc Sci Commun</stitle><date>2024-11-22</date><risdate>2024</risdate><volume>11</volume><issue>1</issue><spage>1592</spage><epage>20</epage><pages>1592-20</pages><artnum>1592</artnum><issn>2662-9992</issn><eissn>2662-9992</eissn><abstract>This study investigates the factors influencing users’ behavioral intention to adopt facial recognition payment (FRP) in smart hospitals, considering convenience and potential risks. The unified theory of acceptance and use of technology (UTAUT), the diffusion of innovations theory, and trust theory are employed to identify critical factors for promoting FRP adoption. A quantitative cross-sectional survey is conducted among smart hospital users in China, collecting 811 valid questionnaires, and the partial least squares structural equation method (PLS-SEM) is utilized for analysis. The results show that performance expectancy, effort expectancy, social influence, and facilitating conditions positively affect behavioral intention. Privacy concerns and perceived risks negatively impact trust in FRP, while familiarity enhances trust. Trust in FRP and personal innovativeness positively influence behavioral intention, with personal innovativeness moderating the trust-behavioral intention relationship. The findings emphasize the mediating role of trust in FRP and the importance of familiarity and personal innovativeness in driving FRP adoption. Gender (male or female) does not significantly impact the relationships and path coefficients in the model. However, slight discrepancies are observed between the permutation test and Henseler’s MGA in terms of the effect of privacy concerns on trust in FRP. This research contributes to the literature on users’ behavioral intentions, aiding smart hospitals in promoting FRP adoption while considering user concerns.</abstract><cop>London</cop><pub>Palgrave Macmillan UK</pub><doi>10.1057/s41599-024-03910-9</doi><tpages>20</tpages><orcidid>https://orcid.org/0000-0002-9267-9094</orcidid><orcidid>https://orcid.org/0000-0001-5198-7261</orcidid><orcidid>https://orcid.org/0000-0003-2208-3508</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2662-9992 |
ispartof | Humanities & social sciences communications, 2024-11, Vol.11 (1), p.1592-20, Article 1592 |
issn | 2662-9992 2662-9992 |
language | eng |
recordid | cdi_doaj_primary_oai_doaj_org_article_d43bdcca5e844ffcabd78470bf02a960 |
source | Social Science Premium Collection; ProQuest - Publicly Available Content Database; Coronavirus Research Database |
subjects | 4000/4008 4014/4045 Airports Artificial intelligence Bank technology Consumers Facial recognition technology Gender differences Health insurance Humanities and Social Sciences Insurance policies Mobile commerce multidisciplinary Pandemics Patient satisfaction Privacy Restaurants Science Science (multidisciplinary) Technological change Technology adoption Telemedicine User behavior Web portals |
title | Convenient or risky? Investigating the behavioral intention to use facial recognition payment in smart hospitals |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T04%3A57%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Convenient%20or%20risky?%20Investigating%20the%20behavioral%20intention%20to%20use%20facial%20recognition%20payment%20in%20smart%20hospitals&rft.jtitle=Humanities%20&%20social%20sciences%20communications&rft.au=Yu,%20Teng&rft.date=2024-11-22&rft.volume=11&rft.issue=1&rft.spage=1592&rft.epage=20&rft.pages=1592-20&rft.artnum=1592&rft.issn=2662-9992&rft.eissn=2662-9992&rft_id=info:doi/10.1057/s41599-024-03910-9&rft_dat=%3Cproquest_doaj_%3E3132019514%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c266t-b9b8c21b8ee4982155042d6eff9cd77e5d1ad5d247291d2a81971af3465284f43%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=3132019514&rft_id=info:pmid/&rfr_iscdi=true |