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2022 | OriginalPaper | Chapter

Effects of Temperature and Social Density on Consumer Choices with Multiple Options

Authors : Martina Katharina Schöniger, Susanne Jana Adler

Published in: Celebrating the Past and Future of Marketing and Discovery with Social Impact

Publisher: Springer International Publishing

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Abstract

Environmental contexts, like temperature and social density, can influence consumers’ decision making considerably. Although previous research established a bidirectional link between temperature and social proximity, it examined temperature and social density’s downstream consequences in isolation, neglecting possible interaction effects. Moreover, the research produced conflicting results (e.g., on preferences for premium products), suggesting fit effects and compensatory effects. We address this research gap in a preregistered experiment with an orthogonal design on temperature and social density, and expand research on temperature and social density’s downstream consequences by measuring preferences for products with different premium, innovativeness, safety, scarcity, or uniqueness levels. Building on previous research, we hypothesize that temperature and social density have similar effects, but find they have distinct effects. Specifically, the interaction effect for safety and premium products indicates that under cold or neutral temperature conditions high tier choices increase when social density is high, but not under warm conditions—suggesting that warmth has an attenuating effect. Furthermore, choices for high tier innovative products profit from cold and low social density primes, whereas the results for scarce and unique products are inconclusive. These findings suggest that temperature and social density have complex product-category-specific consequences and require follow-up research.

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Footnotes
1
More precisely: nwarm temp, high density = 32, nneutral temp, high density = 36, ncold temp, high density = 47, nwarm temp, middle density = 37, nneutral temp, middle density = 42, ncold temp, middle density = 34, nwarm temp, low density = 30, nneutral temp, low density = 40, ncold temp, low density = 43.
 
2
We asked the participants to estimate the number of people in the video (Mhigh density = 63.82, SDhigh density = 48.09, Mmiddle density = 15.24, SDmiddle density = 9.81, Mlow density = 3.12, SDlow density = 3.91) and the number of people that are currently around them (Mhigh density = 1.31, SDhigh density = 2.13, Mmiddle density = 1.03, SDmiddle density = 1.23, Mlow density = 1.82, SDlow density = 4.84). We found significant differences between all the groups in respect of the number of people in the video (F(2,338) = 144.3, p < .001, η2 = .461, all Tukey’s post hoc tests: t(338) ≥ 3.19, p ≤ .0045; Using log-values, we also found significant differences between all the groups with F(2,338) = 642.3, p < .001, η2 = .792, and all Tukey’s post hoc tests: t(338) ≥ 15.51, p ≤ .001). However, we found no significant differences in the participants’ estimation of the number of people around them (F(2,338) = 1.88, p = .154, η2 = .011, all Tukey’s post hoc tests: t(338) ≤ 1.92, all p ≥ .136), which is probably due to a high number of participants who completed the survey being either alone or, at most, having just one other person in their vicinity (n = 239; 70%).
 
Literature
go back to reference Meiselman, H. L. (2019). Context: The effects of environment on product design and evaluation. Cambridge: Woodhead Publishing. Meiselman, H. L. (2019). Context: The effects of environment on product design and evaluation. Cambridge: Woodhead Publishing.
Metadata
Title
Effects of Temperature and Social Density on Consumer Choices with Multiple Options
Authors
Martina Katharina Schöniger
Susanne Jana Adler
Copyright Year
2022
DOI
https://doi.org/10.1007/978-3-030-95346-1_36