'One for One promotions familiar v unfamiliar'
(AsPredicted #48072)
Created: 09/21/2020 11:21 AM (PT)
This is an anonymized version of the pre-registration. It was created by the author(s) to use during peer-review.
A non-anonymized version (containing author names) should be made available by the authors when the work it supports is made public.
1) Have any data been collected for this study already?No, no data have been collected for this study yet.
2) What's the main question being asked or hypothesis being tested in this study? Individuals will be more likely to purchase a product associated with a 1 for 1 promotion when the recipient of the promotion is familiar (from their hometown) than unfamiliar (from a developing country).
3) Describe the key dependent variable(s) specifying how they will be measured. Purchase intention for a pound of coffee
4) How many and which conditions will participants be assigned to? Participants will be assigned to 1 of the 3 following conditions:
1. Hedonic control condition (no 1 for 1 promotion)
2. Hedonic 1 for 1 condition familiar (recipient is ostensibly from the participant's hometown)
3. Hedonic 1 for 1 condition unfamiliar (recipient is ostensibly from a developing country)
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis. We will be conducting analysis of variance (ANOVA) on the purchase intention measure
6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations. Participants will be excluded for failing our attention check measures (there are 4 attention check measures)
7) How many observations will be collected or what will determine sample size?
No need to justify decision, but be precise about exactly how the number will be determined. We are targeting 180 participants, which would yield 60 participants per cell.
8) Anything else you would like to pre-register?
(e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?) Nothing else to pre-register.
