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Examining the Role of Reviewer’s Mood State on
Evaluating Word-Of-Mouth MessageZhen Yang
INTRODUCTION
Word-of-mouth (WOM) has been recognized as critical information resource in
consumers’ purchase decision making. There are four major elements in the
WOM scheme: WOM message, message reviewer, message giver, and the context
(Figure 1). Studies on WOM have focused on the interactions among the four
components.
Based on its content, WOM message can be categorized as positive WOM
(PWOM) and negative WOM (NWOM). In general, researches show that PWOM
gives reviewer confidence and increase purchase intention, while NWOM has the
opposite effect. However, the cognitive processing of these two types of messages
has been largely ignored, which will be the focus of this study. Since WOM has
been proved to be emotionally contagious, we assume the reviewer’s mood state
will be salient in this process. We propose that the mood state of the reviewer will
impact his or her cognitive processing capability and perceived usefulness
towards PWOM and NWOM.
H1: People in sad mood are more WOM dependence when making
online purchase decisions, compared with people in happy mood.
• Mood-as-information theory: sad mood implies people the current situation is
problematic and something need to be done
• Risk reduction strategy: WOM can serve as risk reliever
H2: People in sad mood perceive PWOM more useful than NWOM.
H3: People in happy mood perceive NWOM more useful than PWOM.
• Construal level theory: Sad mood facilitates one’s local focus and is a low level
construal; happy mood fosters ones’ global view and is a high level construal.
High level construal focuses on desirability information – NWOM and neutral
WOM provide a “bigger picture” to assess the value at perceived risk of
purchase; low level construal emphasizes feasibility information – PWOM is
convenient to reduce perceived risk. Thus, PWOM receives greater weight in
sad mood state and NWOM receives greater weight in happy mood state.
H4: People in sad mood give more scrutiny on NWOM than PWOM.
H5: People in happy mood give more scrutiny on PWOM than NWOM.
• Hedonic contingency mood management theory: happy mood will inhibit
people’s message scrutiny on mood threatening message (NWOM), because
they intend to maintain the current affective state. In contrast, people in sad
mood will show scrutiny deficit on mood enhancement message, since they are
motivated to repair the sad mood.
THEORIES & HYPOTHESES
Two laboratory-based quasi-experiments will be conducted. H1, H2 and H3 will
be tested in Study 1, and H4 and H5 will be tested in Study 2.
Study 1
Participants: 100 undergraduate students
Research Structure: Cross-sectional Between-group • Mood manipulation will divide the subjects into two groups: happy or sad
mood. Subjects will be allocated to the two groups evenly and randomly
Manipulation: Subject’s mood state• Performance task (math problem solving) to remove out-lab mood differences
• Imagination task to produce happy and sad mood
Procedure: • Mood manipulation and manipulation check
• Participants will be asked to imagine they want to buy a laptop
• Question (H1): “How important is online review to help you make a good
online purchase decision?”
• Participants will be given five opportunities to read reviews, the options to
choose negative or positive reviews will be given each time
• Questions (H2 and H3): “How useful PWOM/NWOM is to help you make a
good online purchase decision?”
Study 2
Participants: 200 undergraduate students
Research Structure: Cross-sectional Between-group • 2 (mood: happy vs. sad) × 2 (PWOM vs. NWOM) × 2 (Quality: strong vs.
weak argument)
• Subjects will be allocated to the six conditions evenly and randomly
Manipulation: Subject’s mood state, WOM message• Same mood manipulation procedure as in study 1
• PWOM/ NWOM: positive produce experience/ negative product experience
• Strong/ Weak argument: WOM argument with/ without rational evidence
Procedure: • Mood manipulation and manipulation check
• Participants will be asked to imagine they want to buy a laptop
• Four types of WOM message will be presented to all participants with random
sequence: strong argument PWOM, weak argument PWOM, strong argument
NWOM and weak argument NWOM.
• Each arguments will follow by a persuasive evaluation request (H3 and H4):
“How persuasive do you think the online review you just read?”
RESEARCH METHODS & DESIGN
Study 1
Two one-way between subjects ANOVA will be conducted to test H1,
H2 and H3. If there’s effect of reviewers’ mood state on their WOM
dependence and also perceived usefulness on PWOM and NWOM
message, then the test results should be both statistically significant at
p < .05 level.
Study 2
In H4 and H5, we are expecting the mood state will impact people’s
scrutiny on PWOM and NWOM message. Significance at p <.05 level
in the 2 × 2 × 2 ANOVA will give us confidence about the existence of
effect. The effect could be plotted below (Figure 2).
EXPECTED RESULTS
Figure 1. Word-Of-Mouth Scheme
Message Giver
WOM message
Message Reviewer
Context
Strong Argument
Weak Argument
PWOMNWOM
7
6
5
4
3
2
1
Happy Mood
Per
suas
ive
Eval
uat
ion
Strong Argument
Weak Argument
PWOMNWOM
7
6
5
4
3
2
1
Sad Mood
Per
suas
ive
Eval
uat
ion
Figure 2. Scrutiny as a function of mood state and WOM content
DISCUSSION
Implications:To our best knowledge, this study will be the first to investigate individuals’
pre-purchase information processing towards two types of WOM (positive vs.
negative) under individuals’ two types of mood states ( happy vs. sad).
This study will extend the literature of the salience of happy mood and sad
mood in cognitive information processing model, and the motivation of
acquiring PWOM and NWOM.
Concerns:Happy and sad mood associate with other dimensions of mood state including
arousal level (activated vs. deactivated), intensity (strong vs. weak), duration
(long time vs. short time), agency (self-caused vs. circumstance-caused) which
may have confounding impacts in the experiments.
Future Directions: test the impact of mood from other dimensions on WOM
REFERENCES
• Trope, Yaacov L. (2012). Construal Level Theory. In P. K. Van Lange,
Handbook of Theories of Social Psychology (pp. 118-134). Washington DC:
Sage Publications Ltd.
• Chen, H., & He, G. (2011). The effect of construal level on intertemporal
choice and risky choice. Acta Psychologica Sinica, 442-452.