Are we all in this together?": Brand opportunism in covid-19 cause related marketing and the moderating role of consumer skepticism

37 citations

Abstract

This study examined how the roles of perceived brand-social cause fit (i.e., functional fit and image fit) and consumer skepticism in influencing consumers' perception of brand opportunism and its subsequent outcomes during COVID-19 pandemic. A 2 (high vs. low fit) × 2 (industry: travel vs. grocery) between-participants online experiments (*n* = 373) were conducted. Results showed that the lack of brand-social cause fit leads to less favorable consumer attitude due to their perception of the brand's opportunism. Specifically, with individuals high in skepticism, such perception of brand opportunism was greater, which in turn has a stronger negative influence on consumers' attitude toward the message and the brand. Theoretical contributions, managerial implications, limitations and future studies are also discussed.

37
Citations
Research
Paper Only

Study specs

Discipline
Marketing
Year
2021
Human Data Platform
Prolific

Peer Review & Critical Discussion

3 threads

Potential Selection Bias in 2023 Cohort

DSJDr. Sarah J.
Verified PhD Candidate
12 replies

The participant pool shows a concerning overrepresentation of users from high-income demographics. Looking at Table 3, we can see that 78% of respondents had annual incomes above $75k, which significantly limits the generalizability of these findings to broader populations.

2 hours ago

Non-naive Participants Issue

MCM. Chen (OpenAI)
Data Scientist
8 replies

I've noticed a methodological concern regarding participant naivety. Given that Prolific users often complete multiple studies, there's a real risk that participants had prior exposure to similar experimental paradigms, which could confound the results.

5 hours ago

RLHF Applicability to This Study Design

PRWProf. R. Williams
Verified Researcher
15 replies

The implications for RLHF training pipelines are understated. If we accept the authors' conclusions about preference stability, this has direct consequences for how we should structure reward model training. The temporal decay effect described in Section 4.2 is particularly relevant.

1 day ago

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