Abstract

While Technology Acceptance Models (TAM) are widely used, their practical utility remains under scrutiny. This study investigates the usefulness of TAM for market intelligence by examining the heterogeneity of its predictors across different handheld gaming consoles. We collected user reviews for Nintendo, Steam Deck, Logitech, and Razer consoles from Amazon.com and annotated them using NLP-LLM to obtain scores for TAM variables. Separate TAM regressions were fitted for each console and compared using coefficient tests and ANOVA. Results supported the heterogeneity hypotheses, revealing significant differences in TAM coefficients across consoles. Steam Deck emerged as a market leader, while Nintendo lagged behind competitors. Logitech and Razer demonstrated comparative advantages in Perceived Usefulness over Ease of Use. We demonstrated that he model heterogeneity enables utilizing TAM for practical applications such as product comparison and design improvement prioritization. Companies can identify strengths, weaknesses, and user priorities for their products by jointly examining model coefficients and mean user sentiment scores.

Recommended Citation

Smolinski, P.R., Januszewicz, J. & Winiarski, J. (2024). From Information Systems Theory to Market Intelligence: Heterogeneous Technology Acceptance Models as a Tool for Product Analysis. 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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From Information Systems Theory to Market Intelligence: Heterogeneous Technology Acceptance Models as a Tool for Product Analysis

While Technology Acceptance Models (TAM) are widely used, their practical utility remains under scrutiny. This study investigates the usefulness of TAM for market intelligence by examining the heterogeneity of its predictors across different handheld gaming consoles. We collected user reviews for Nintendo, Steam Deck, Logitech, and Razer consoles from Amazon.com and annotated them using NLP-LLM to obtain scores for TAM variables. Separate TAM regressions were fitted for each console and compared using coefficient tests and ANOVA. Results supported the heterogeneity hypotheses, revealing significant differences in TAM coefficients across consoles. Steam Deck emerged as a market leader, while Nintendo lagged behind competitors. Logitech and Razer demonstrated comparative advantages in Perceived Usefulness over Ease of Use. We demonstrated that he model heterogeneity enables utilizing TAM for practical applications such as product comparison and design improvement prioritization. Companies can identify strengths, weaknesses, and user priorities for their products by jointly examining model coefficients and mean user sentiment scores.