plag

Participants
were 40 Pakistani residents, recruited through an online panel, who completed
this study on voluntary basis. Participants’ age ranged between 18 and 24, with
a median age of 22(SD age = 2.33) and 57% were female. They were randomly
assigned to scenarios describing a complex (n = 20) or a simple product (n =
20). The scenarios described a wrist watch that consists of date and day dials.
To manipulate product complexity, following Burnham et al. (2003), it was
stated that one product requires some setup and calibration (i.e., complex),
while the other needs minimum setup (i.e., simple). For example, for the
complex product, subjects read descriptions like “…requires some preliminary
steps for best results … it is important that you follow a series of steps as
explained in the manual to synchronize date and day together”. On the other
hand, for the simple product, subjects read “…requires minimum setup for best
results … with just one button you can change all the dials”.

Upon
reading the scenario, respondents completed 4 items measuring product interest
(e.g.,” I think products of this type are interesting”) on a 7-point scale (1 =
strongly disagree, 7 =strongly agree; Cornbrash’s ? = .85) as the dependent
measure. Following Park and Kim (2015) we included 4 items measuring entity TOI
(Decks 1999) on a 6-point Likert scale (1 = strongly disagree, 6 = strongly
agree; Cornbrash’s ? = .97) as an independent measure. The items were “you have
a certain amount of intelligence, and you can’t really do much to change it;
your intelligence is something about you that you can’t change very much; to be
honest, you can’t really change how intelligent you are;” and “you can learn
new things, but you can’t really change your basic intelligence”. The survey
also included three items measuring product complexity as manipulation checks
at the end. These items (e.g., “I think the wrist watch was quite complex”)
were on a 7-point scale (1 = strongly disagree, 7 = strongly agree; Cornbrash’s
?= .83) such that higher ratings suggest higher perceived complexity.

Results:

            The
manipulation check for product complexity indicated that subjects perceived the

scenarios
as intended (product complexity: M complex = 4.30 vs. M simple = 3.51, t(85) =
3.06, p< .01).             To test the main hypotheses, we used model 1 of PROCESS by Hayes (2013) with TOI as the independent variable, product complexity (high vs. low) as the moderator, and product interest as the dependent variable. The results indicated main effects of product complexity (? = - 1.65, t(83) = -2.15, p < .05), TOI (? = -.76, t(83) = -2.00, p < .05) and an interaction between product complexity and TOI (? = .47, t(83) = 2.01, p < .05). We can also look at the data comparing reactions from incremental and entity theorists (1- incremental, 6-entity) to complex versus simple products. The following results are based on spotlight analysis (Krishna 2016), that is, one standard deviation below the mean (M = 1.59 – incremental theorists) and one standard deviation above the mean (M = 4.39 – entity theorists). Contrast tests indicated that for a complex product, incremental theorists had more favorable reactions than did entity theorists (M incremental = 5.62, M entity = 4.78; ? = -.29, t(83) = -1.69, p< .05, one-tailed), while for a simple product, incremental and entity theorists had similar reactions (M incremental = 4.71, M entity = 5.19; ? = .17, t(83) = 1.12, p > .1, one-tailed). Figure illustrates the
results.