Personal Attribute Judgments - Modeling Users' Experiences with Interactive Systems - page 19

Fig. 2.1 Multi-Dimensional Scaling on dissimilarity ratings for three products with latent
constructs fitted as vectors. Note that the latent constructs employed in this study fail to
explain the dissimilarity between products 1 and 3.

model fails to capture the full set of qualities that are meaningful to the participants
of the study.
Secondly, one could even wonder whether rating a product on quality dimensions
that are imposed by the researcher is always a meaningful activity for the user, for
example when the user does not consider a quality dimension as relevant for the spe-
cific product. A basic assumption that underlies the rating process is that the user is
able to understand, interpret and position a given statement within her own context.
For instance, if the user is asked to rate the product in terms of its usefulness, she
is expected to interpret usefulness in her own context, to identify what aspects of
her experience with the given product contribute to perceptions of usefulness and
summarize them in an overall index of usefulness. First, this process is an inher-
ently idiosyncratic process; thus, different users might reflect on different facets of
the construct. Secondly, users might fail in certain occasions to interpret the per-
sonal relevance of the statement in their own context, e.g. due to a failure to recall
experiential information that relates to the statement or due to lengthy and repetitive
questioning. Larsen et al. (2008b) reviewed a number of studies employing psycho-
metric scales in the field of Information Systems. They found for the majority of
studies the semantic similarity between items to be a significant predictor of partic-
ipants' ratings (.00 R 2 < < .63) . In such cases, they argued participants are more