Multivariate data analysis (4th ed.): with readings
Multivariate data analysis (4th ed.): with readings
Measuring system usage: implications for IS theory testing
Management Science
Empirical evaluation of the revised technology acceptance model
Management Science
The psychological origins of perceived usefulness and ease-of-use
Information and Management
An assessment of the prototyping approach to information systems development
Communications of the ACM
Why do people use information technology?: a critical review of the technology acceptance model
Information and Management
Antecedents of B2C Channel Satisfaction and Preference: Validating e-Commerce Metrics
Information Systems Research
Assessing the Validity of IS Success Models: An Empirical Testand Theoretical Analysis
Information Systems Research
Understanding it adoption decisions in small business: integrating current theories
Information and Management
Examining the technology acceptance model using physician acceptance of telemedicine technology
Journal of Management Information Systems - Special section: Strategic and competitive information systems
An empirical assessment of a modified technology acceptance model
Journal of Management Information Systems - Special section: Strategic and competitive information systems
Testing the determinants of microcomputer usage via a structural equation model
Journal of Management Information Systems - Special section: Navigation in information-intensive environments
Journal of Management Information Systems
A meta-analysis of the technology acceptance model
Information and Management
Designing usable online stores: A landscape preference perspective
Information and Management
Journal of Biomedical Informatics
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Selecting the appropriate mix of functional and/or interface characteristics to achieve user acceptance has proven to be a more challenging and difficult decision than expected. While numerous studies have shown that the technology acceptance model (TAM) is useful for predicting acceptance, estimates of its structural weights are not consistent across studies. Using initial exposure data from 742 users of office suite applications (i.e., spreadsheet, database, word processing, and graphics), our research illustrated the use of multi-group analysis of structural invariance (MASI) to test differences in structural weights across population subgroups for latent variables in TAM. We argue that, for large sample studies containing latent variables, MASI may be a more appropriate test of differences for structural weights/regression coefficients than analysis of covariance. The managerial implications of the results in setting functionality and interface goals and allocating resources to continued development efforts are discussed.