Abstract

While technology acceptance models (TAM) are widely used, questions remain concerning practical utility. Recent research suggests TAM applicability requires model predictors to exhibit heterogeneity across products and contexts. This study explored TAM's application for comparative analysis of handheld gaming consoles by examining heterogeneity in the effect sizes of Perceived Usefulness and Ease of Use coefficients across different console products. User reviews were collected from Amazon.com for four major consoles and annotated using NLP-LLM system to obtain numerical scores for TAM variables. Separate TAM regressions were fitted for each console, and models were compared using coefficient difference tests and ANOVA. Results supported the heterogeneity hypotheses, revealing significant differences in TAM coefficients across consoles. The observed heterogeneity enables utilizing TAM for practical applications such as product comparison and design improvement. Companies can identify product strengths, weaknesses, and user priorities by jointly examining model coefficients and mean user sentiment scores on TAM variables.

Recommended Citation

Smolinski, P.R., Januszewicz, J. & Winiarski, J. (2024). Heterogeneous Technology Acceptance Models as a Tool for Product Analysis: Example from Comparison of Handheld Gaming Consoles. In B. Marcinkowski, A. Przybylek, A. Jarzębowicz, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Harnessing Opportunities: Reshaping ISD in the post-COVID-19 and Generative AI Era (ISD2024 Proceedings). Gdańsk, Poland: University of Gdańsk. ISBN: 978-83-972632-0-8. https://doi.org/10.62036/ISD.2024.58

Paper Type

Full Paper

DOI

10.62036/ISD.2024.58

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Heterogeneous Technology Acceptance Models as a Tool for Product Analysis: Example from Comparison of Handheld Gaming Consoles

While technology acceptance models (TAM) are widely used, questions remain concerning practical utility. Recent research suggests TAM applicability requires model predictors to exhibit heterogeneity across products and contexts. This study explored TAM's application for comparative analysis of handheld gaming consoles by examining heterogeneity in the effect sizes of Perceived Usefulness and Ease of Use coefficients across different console products. User reviews were collected from Amazon.com for four major consoles and annotated using NLP-LLM system to obtain numerical scores for TAM variables. Separate TAM regressions were fitted for each console, and models were compared using coefficient difference tests and ANOVA. Results supported the heterogeneity hypotheses, revealing significant differences in TAM coefficients across consoles. The observed heterogeneity enables utilizing TAM for practical applications such as product comparison and design improvement. Companies can identify product strengths, weaknesses, and user priorities by jointly examining model coefficients and mean user sentiment scores on TAM variables.