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Using Davis's Perceived Usefulness and Ease‐of‐use Instruments for Decision Making: A Confirmatory and Multigroup Invariance Analysis
Author(s) -
Doll William J.,
Hendrickson Anthony,
Deng Xiaodong
Publication year - 1998
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1998.tb00879.x
Subject(s) - confirmatory factor analysis , equivalence (formal languages) , usability , technology acceptance model , measurement invariance , psychology , computer science , reliability (semiconductor) , sample (material) , structural equation modeling , machine learning , mathematics , human–computer interaction , power (physics) , chemistry , physics , discrete mathematics , quantum mechanics , chromatography
As key components of Davis's technology acceptance model (TAM), the perceived usefulness and perceived ease‐of‐use instruments are widely accepted among the MIS research community as tools for evaluating information system applications and predicting usage. Despite this wide acceptance, a series of incremental cross‐validation studies have produced conflicting and equivocal results that do not provide guidance for researchers or practitioners who might use the TAM for decision making. Using a sample of 902 “initial exposure” responses, this research conducts: (1) a confirmatory factor analysis to assess the validity and reliability of the original instruments proposed by Davis, and (2) a multigroup invariance analysis to assess the equivalence of these instruments across subgroups based on type of application, experience with computing, and gender. In contrast to the mixed results of prior cross‐validation efforts, the results of this confirmatory study provide strong support for the validity and reliability of Davis's sixitem perceived usefulness and six‐item ease‐of‐use instruments. The multigroup invariance analysis suggests the usefulness and ease‐of‐use instruments have invariant true scores across most, but not all, subgroups. With notable exemptions for word processing applications and users with no prior computing experience, this research provides evidence that the item‐factor loadings (true scores) are invariant across spread sheet, database, and graphic applications. The implications of the results for managerial decision making are discussed.