Extending the technology acceptance model and empirically testing the conceptualised consumer goods acceptance model

The technology acceptance model (TAM) has not been applied beyond the technological context, despite its widespread applications. This study extends the TAM to consumer goods and validates the conceptualised consumer goods acceptance model (CGAM) using tea-to-go as a proxy for consumer goods. An exploratory research approach based on a quota sample is used to adjust and test the CGAM, showing that the adjusted CGAM and its measures are reliable and valid, thus supporting the hypothesis that extending the TAM to a non-technological context is possible. The results are discussed in light of the data collection, which is based on a cross-sectional setting, assuming consumers' knowledge of the good and forcing answers based on assumptions. The results show that despite major changes to the exogenous variables, the difference in variance levels between perceived usefulness (PU) and perceived ease of use (PEOU) is in accordance with TAM 3. Thus, PU is the strongest predictor of behavioural intention (BI), supporting the choice of constructs influencing PU. This also indicates that usefulness outweighs ease of use. The findings demonstrate that each variable category has a favourable influence on PU and PEOU. Specifically, cognitive instrumental processes (CIP) and value-related aspects (VRA) are significant predictors of PU, whereas CIP is the most critical driver, highlighting that consumer actions are driven by factors correlated with lifestyle, trends, and price. VRA_1 had the strongest impact on PU, accentuating the high potential of functional ingredients, such as vitamins. Furthermore, the results show that the anchor variables have a stronger impact on PEOU than the adjustment variables, emphasising the importance of enjoyment and indulgence in consumer goods, especially tea-to-go. These findings show that the empirically tested and adjusted CGAM provides a solid basis for measuring the acceptance of consumer goods and identifying key drivers.