Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61422
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dc.contributor.authorTalukder, Shamimen
dc.contributor.authorChiong, Raymonden
dc.contributor.authorDhakal, Sandeepen
dc.contributor.authorSorwar, Golamen
dc.contributor.authorBao, Yukunen
dc.date.accessioned2024-07-10T01:02:53Z-
dc.date.available2024-07-10T01:02:53Z-
dc.date.issued2019-
dc.identifier.citationJournal of Systems and Information Technology, 21(4), p. 419-438en
dc.identifier.issn1758-8847en
dc.identifier.issn1328-7265en
dc.identifier.urihttps://hdl.handle.net/1959.11/61422-
dc.description.abstract<p>Purpose</p> <p>Despite the widespread use of mobile government (m-government) services in developed countries, the adoption and acceptance of m-government services among citizens in developing countries is relatively low. The purpose of this study is to explore the most critical determinants of acceptance and use of m-government services in a developing country context.</p> <p>Design/methodology/approach</p> <p>The unified theory of acceptance and use of technology (UTAUT) extended with perceived mobility and mobile communication services (MCS) was used as the theoretical framework. Data was collected from 216 m-government users across Bangladesh and analyzed in two stages. First, structural equation modeling (SEM) was used to identify significant determinants affecting users' acceptance of m-government services. In the second stage, a neural network model was used to validate SEM results and determine the relative importance of the determinants of acceptance of m-government services.</p> <p>Findings</p> <p>The results show that facilitating conditions and performance expectancy are the two important precedents of behavioral intention to use m-government services, and performance expectancy mediates the relationship between MCS, mobility and the intention to use m-government services.</p> <p>Research limitations/implications</p> <p>Academically, this study extended and validated the underlying concept of UTAUT to capture the adoption behavior of individuals in a different cultural context. In particular, MCS might be the most critical antecedent towards mobile application studies. From a practical perspective, this study may provide valuable guidelines to government policymakers and system developers towards the development and effective implementation of m-government systems.</p> <p>Originality/value</p> <p>This study has contributed to the existing, but limited, literature on m-government service adoption in the context of a developing country. The predictive modeling approach is an innovative approach in the field of technology adoption.</p>en
dc.languageenen
dc.publisherEmerald Publishing Limiteden
dc.relation.ispartofJournal of Systems and Information Technologyen
dc.titleA two-stage structural equation modeling-neural network approach for understanding and predicting the determinants of m-government service adoptionen
dc.typeJournal Articleen
dc.identifier.doi10.1108/JSIT-10-2017-0096en
local.contributor.firstnameShamimen
local.contributor.firstnameRaymonden
local.contributor.firstnameSandeepen
local.contributor.firstnameGolamen
local.contributor.firstnameYukunen
local.profile.schoolSchool of Science & Technologyen
local.profile.emailrchiong@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeUnited Kingdomen
local.format.startpage419en
local.format.endpage438en
local.peerreviewedYesen
local.identifier.volume21en
local.identifier.issue4en
local.contributor.lastnameTalukderen
local.contributor.lastnameChiongen
local.contributor.lastnameDhakalen
local.contributor.lastnameSorwaren
local.contributor.lastnameBaoen
dc.identifier.staffune-id:rchiongen
local.profile.orcid0000-0002-8285-1903en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/61422en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleA two-stage structural equation modeling-neural network approach for understanding and predicting the determinants of m-government service adoptionen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorTalukder, Shamimen
local.search.authorChiong, Raymonden
local.search.authorDhakal, Sandeepen
local.search.authorSorwar, Golamen
local.search.authorBao, Yukunen
local.uneassociationNoen
dc.date.presented2019-
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.published2019en
local.year.presented2019en
local.fileurl.closedpublishedhttps://rune.une.edu.au/web/retrieve/af6598e1-a640-40c8-b85e-97292b4c436den
local.subject.for20204602 Artificial intelligenceen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.date.moved2024-07-23en
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School of Science and Technology
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