Empirical evaluation of the revised technology acceptance model
Management Science
Testing the technology acceptance model across cultures: a three country study
Information and Management
On the use of construct reliability in MIS research: a meta-analysis
Information and Management
The effect of user engagement on system success: a meta-analytical integration of research findings
Information and Management
Why do people use information technology?: a critical review of the technology acceptance model
Information and Management
The Use of Meta-Analysis in Validating the Delone and McLean Information Systems Success Model
HICSS '96 Proceedings of the 29th Hawaii International Conference on System Sciences Volume 4: Organizational Systems and Technology
Information Systems Research
Extended technology acceptance model of internet utilization behavior
Information and Management
Technology acceptance model for internet banking: an invariance analysis
Information and Management
What drives mobile commerce? An empirical evaluation of the revised technology acceptance model
Information and Management
The role of moderating factors in user technology acceptance
International Journal of Human-Computer Studies
Examining the technology acceptance model using physician acceptance of telemedicine technology
Journal of Management Information Systems - Special section: Strategic and competitive information systems
Information and Management
A meta-analysis of the technology acceptance model
Information and Management
Information System Success: Individual and Organizational Determinants
Management Science
Moderating Effects of Task Type on Wireless Technology Acceptance
Journal of Management Information Systems
Investigating the Moderators of the Group Support Systems Use with Meta-Analysis
Journal of Management Information Systems
International Journal of Electronic Commerce
Acceptance of electronic tax filing: A study of taxpayer intentions
Information and Management
Validating instruments in MIS research
MIS Quarterly
Re-examining perceived ease of use and usefulness
MIS Quarterly
User acceptance of hedonic information systems
MIS Quarterly
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A reliability generalization study (a meta-analysis of reliability coefficients) was conducted on three widely studied information systems constructs from the technology acceptance model (TAM): perceived ease of use, perceived usefulness, and behavioral intentions. This form of meta-analysis summarizes the reliability coefficients of the scores on a specified scale across studies and identifies the study characteristics that influence the reliability of these scores. Reliability is a critical issue in conducting empirical research as the reliability of the scores on well-established scales can vary with study characteristics, attenuating effect sizes. In conducting this study, an extensive literature search was conducted, with 380 articles reviewed and coded to perform reliability generalization. Study characteristics, including technology, sample, and measurement characteristics, for these articles were recorded along with effect size data for the relationships among these variables. After controlling for number of items, sample size, and sampling error, differences in reliability coefficients were found with several study characteristics for the three technology acceptance constructs. The reliability coefficients of PEOU and PU were lower in hedonic contexts than in utilitarian contexts, and were higher when the originally validated scales were used as compared to when other items were substituted. Only 27 percent of the studies that provided the measurement items used the original PEOU items, while 39 percent used the original PU items. Scales that were administered in English had higher reliability coefficients for PU and BI, with a marginal effect for PEOU. Reliability differences were also found for other study characteristics, including reliability type, subject experience, and gender composition. While average reliability coefficients were high, the results show that, on average, relationships among these constructs are attenuated by 12 percent with maximum attenuation in the range of 35 to 43 percent. Implications for technology acceptance research are discussed and suggestions for addressing variation in reliability coefficients across studies are provided.