persuasive effects of online reviews on consumer decision making and attitude
John Parry – 726181
6016BUSMK – Consumer Psychology
Marketing BA – Liverpool John Moores University
A fundamental goal of consumer
psychology research is to shed light on the underlying physiological factors
that drive consumer behaviour (Tormal and Briñol, 2015). A focus for this essay
will be how eWOM can be a driving factor for persuasion in the decision-making
process. The power of interpersonal influence through word-of-mouth
communication has been well recognised in consumer literature (Awad and
Ragowsky, 2008). Word-of-mouth being, interpersonal communication regarding
products or services where the receiver regards the communicator as impartial
(Stokes and Lomax, 2002).
With the rise of digital
consumption, has to a shift to eWOM (electronic word of mouth) we have access
to more information online than ever before, with this we also have access to
more opinions, changes in overall marketing communications had already been seen
in Kitchen (1993) describes marketing as having gone from a renaissance during
this period leading to mainstream web usage.
An early researcher in Festinger
(1954) focused on how people evaluated the correctness of their opinions by
comparing them to the opinions of others. Although traditional views held that credible
sources were more persuasive because people have a heuristic that, “if an
expert says it, it must be true” (Chaiken, 1980). In recent times, the internet
has made it convenient for consumers to both create and gather positive and
negative product information provided by peer consumers (Hennig-Thurau et al.
Persuasion theory itself studies
persuasive effect by changing the various factors including the communicators,
information contents, pathways and receivers, summing up the factors that influence
communication effect as source, message and receivers (Hovland, 2011). Our own
personal attitudes are formed from the world around us, our attitudes in term
affect our decision-making, attitudes refer to the general and relatively
enduring evaluations people have of other people, objects, or ideas (Tormal and
Briñol, 2015). Attitudes can differ in their extremity or the extent to which they
divide from neutral (Abelson, 1995).
A contemporary theoretical
framework of the Elaboration Likelihood Model (ELM) of persuasion (Petty and
Cacioppo, 1986). The ELM takes the form of two paths of persuasion and overall
attitude change. There are two routes the central route and the peripheral
route. The central route to persuasion consists of thoughtful
consideration of the arguments (ideas, content) of the message.
The peripheral route to persuasion occurs when the listener decides
whether to agree with the message based on other cues besides the strength of
the arguments or ideas in the message (Persuasion, 2004). ELM is one of the
most frequently used theoretical frameworks in studies on e-WOM (Chan and Ngai,
In this essay I shall be analysing
academic sources whom have researched the affects that eWOM can have on overall
consumer decision making through persuasion. Online customer reviews provide
product information and recommendations from the customer perspective (Lee,
Park and Han, 2008). Explored the idea by what degree to reviews online have an
effect on the overall attitude formation (Chatterjee, 2011).
Persuasion itself is often discussed
as three different factors the source, the message and recipient. Each of which
are important in distinguishing how exactly how our consumers are persuaded.
For my analytic research I shall be focusing on the first of these the source,
more precisely eWOM as a source for persuasion; with focus on online reviews.
Brinol and Petty (2009) summarize
the dimensions that source can have on overall message. Individuals are more certain of an attitude
when that attitude stems from a credible (i.e., trustworthy and expert) source
than from one that is not credible. For example, Clarkson, Tormala, and Rucker
(2008) exposed participants to a message for a department store that came from
a source low or high in credibility. They found that individuals were more
certain of their attitude when the source was high as opposed to low in
Source credibility is often the
most source factor discussed with regards to persuasion, this an interesting
topic within eWOM the source being that of fellow peers. Expertise and
Trustworthiness, trust from fellow users is high, as they have nothing to gain
from telling the truth about a product.
The decision-making process, is the
process by which a consumer decides to commit to the purchase of a product. Either
the process can be simple or complex but it is always personal. As marketers,
we want to be able to analyse the process so that we can best apply and target
theses said people. Kotler’s black box
model used as a basis for our understanding of decision-making. As the
black box refers to what we do not have control over rather these are personal
factors that we can look to craft and mould.
Attitude formation, frameworks for
this within consumer psychology from Petty can be used to analyse the formation
of attitudes and the differing types of consumers. Given the well-documented
link between attitudes and behaviour (Fishbein and Ajzen, 1975), its important
that we as marketers understand how consumer come to these decisions.
Word of mouth (WOM) is the process
of conveying information from person to person and plays a major role in
customer buying decisions (Richins & Root-Shaffer, 1988). By looking at
online reviews as a variable, we can see how this form of eWOM has helped to
form and construct attitudes. WOM is seen as more credible than advertising as
it is perceived as having passed through the evaluation of “people like me”
(Allsop et al., 2007). Therefore, marketers can use it as a powerful tool.
Review communities are among the
fastest growing on the internet, used for people voicing their opinions (Armstrong and Hagel 1996). Other people’s
opinions are useful in lowering the amount uncertainty and amount of
information that must be processed to make a decision (Olshavsky and Granbois
1979). Also a sense of belonging had relatively the
most impact on consumers’ eWOM intention (Cheung and Lee, 2012).
study by Lee, Rodgers and Kim, (2009) looked to see by what degree valance of
consumer reviews had an effect on consumers when looking to purchase a laptop. For
their research experiment they printed out webpages were used with information,
the study is experimental as when looking online we perceive and browse
multiple tabs, being forced to read one page.
and Hwang, 2009) performed a study to examine how eWOM effects consumer behaviour
and how we interpret messages. By understanding how consumers interpret eWOM we
can look to better understand overall review dissecting
Zhu and Zhang (2010) confirmed that
the number and the score of reviews can influence customer purchase intention
significantly by empirical methods. Their research shows similar findings to
previous research performed by (Wood et Al. 1994; Tormala, Petty & Densai,
2010) as people have been shown to more influenced by numerical majorities than
by numerical minorities. This could be because majorities are thought to be
more persuasive because people seek to belong to be accepted by the majority
group (Moscovi, 1980, 1985). This shows us that for online reviews to be
effective that they have to appear to be the opinion of not just one person but
a group of people, this can be see with the ability to rate other peoples
reviews online for their personal effectiveness and opinion validation.
A cognitive study by Lee (2009) adopts
the Elaboration Likelihood Model (ELM) to explore the effects of online reviews.
258 undergraduates were asked to review online reviews for a smart phone from Amazon,
those whom participated in the experiment for extra credit. From his research he
revealed that the argument quality of online reviews has a positive impact on
the purchasing intention of online shoppers. Moreover, the quantity of online
reviews has a positive impact on the purchasing intention online consumers (Lee,
2009); this is correlation to the research of (Zhu and Zhang, 2010). Lee’s
study is limited because it only examined the moderating role of extrinsic
motivation involvement (Haugtvedt et al., 1992).
Lee, Park and Han (2008) used the
ELM (Elaboration likelihood model) to explore the effects negative online
reviews had on product attitude. They were looking at the proportion and
quality of negative reviews The first argument that the argument quality of
online reviews has a positive effect on the purchasing intention of online
shoppers, he found that they are more persuasive than weak quality reviews that
are subjective and emotional. Because online reviews are published in a written
format they’re easier to observe and compare. Lee, Park and Han (2008) focused
on the effective that negative reviews can have on overall product attitude.
Their research based off the ELM model. By acting as an informant and
recommender, online consumer reviews have the capability of influencing the
decision-making process of consumers (Lee, Park and Han, 2008). Each subject was given a gift, which can sway
bias, as with real online information search we do not gain any pleasure out of
research. Their study in focusing on not only positive but negative effects of
online reviews, has expanding the use of the ELM.
It has been well documented that
within the travel industry, online reviews are very prominent with sites like
TripAdvisor and Expedia built with consumer input at the fore (Bearne, 2016). Filieri
and McLeay (2013) study on how consumers used online reviews, Travelers appear
to adopt both a peripheral and a central route to information adoption. The
peripheral route is primarily influenced by the ranking of accommodation. This
is complemented by adopting a central route and using specific information
quality dimensions to process information (Filieri and McLeay, 2013).
(Lee and Lee, 2009) examined
the actions of a customer when inferring product information from electronic
word-of-mouth (eWOM) material at a website.
Cheung and Thadani (2012) produced
an integrative framework for the study of impact of eWOM communication. The
framework based of five essential components of eWOM: communicators, stimuli,
receivers, responses and contextual factors.
Mayzlin and Chevalier (2006)
studied the effects of online book reviews of Amazon.com and Barnesandnoble.com
and found a positive influence of word of mouth on sales. Evidence from
review-length data also shows that consumers read review content rather than
relying only on summary statistics.
– Managerial Implications
As marketing managers, we give our
customers tools to comment and review as they see fit on our products, management
of online reviews has been increasingly integrated into marketing communication
strategy (Lee, 2009). Not only with the reviewing of products but with the reviewing
of the overall business, we see often now websites with trust pilot ratings,
and we as consumers who do not see a good combination of reviews as well as
quality will choose to take our custom elsewhere; this agrees with the research
It is important that we understand
how our content is being perceived, using brain scans we are able to see how on
neurological level. Neuromarketing is a new wave thinking of exploring the
thought processes of consumers through analysis and testing. the direct
observation of the reactions within the brain that is now available through the
use of steadily improving methods of imaging techniques, for example, positron
emission tomography (PET) or functional magnetic resonance imaging (fMRI), is
providing a completely different perspective (Plassmann et al., 2007).
This can be seen with Amazon’s acquired
of good reads, a way of seeing what books people are interested in and then
targeted them with offers based around the idea of reviews.
We have found that consumer conform
to online customer reviews.
In the cognitive studies of both
Lee and Zhu and Zhang. The quality and the amount of reviews is important in overall
effectiveness of persuasion, this is seen in studies by both lee and zhu and zhang.
We can take from this that us as marketers should look toensre that all of our
content is easily reviewable and it has the capacity to be apporartly reviwed
by our users.
Focus on the idea of consumer
Built on the theoretical framework
of the Elaboration Likelihood Model (ELM) of persuasion (Petty and Cacioppo,
The Aida model, developed by Strong
1925, is made up of Awareness Interest Decision and Action, these are fundamentals
within marketing communication.
Due to the conformity of consumers,
we should have a system in place that allows for reviews that receive an x number of downvotes to be removed. As most
opinions do not believe in what is being said although we should be transparent
in this as we do not want to be appearing to censor the opinions of the public.
One of the newest theories is metacognition this is the thought of
thinking about thinking, that is people thoughts about their own or other people’s
thoughts (look in textbook for references).
– Need To Put Into Havard style!
R. P. (1995). Attitude extremity. In R. E. Petty & J. A. Krosnick
(Eds.), Ohio State University series on attitudes and persuasion, Vol.
4. Attitude strength: Antecedents and consequences (pp. 25-41). Hillsdale,
NJ: Lawrence Erlbaum Associates.
DT, Bassett BR, Hoskins J A (2007). Word-of-Mouth Research: Principles and
Applications. J. Advert. Res. December pp.398-411.
Arthur R. and John Hagel III (1996), “The Real Value of On-Line Communities”, Harvard
Business Review, 74, 134-141.
S. (2016). How technology has transformed the travel industry. The
P., & Petty, R. E. (2009). Source factors in persuasion: A self-validation
approach. European Review of Social Psychology, 20(1),
S. (1980). Heuristic versus systematic information processing and the use of
source versus message cues in persuasion. Journal of Personality and
Social Psychology, 39(5), 752-766
Y. Y. Yolanda, and Eric W. T. Ngai. (2011). “Conceptualising Electronic Word of
Mouth Activity: An Input-Process-Output Perspective.” Marketing Intelligence
and Planning, 29 (5): 488-516.
Patrali (2001), “Online Reviews – Do Consumers Use Them?” ACR 2001 Proceedings,
eds. M. C. Gilly and J. Myers-Levy, Provo, UT: Association for Consumer
C. and Lee, M. (2012). What drives consumers to spread electronic word of mouth
in online consumer-opinion platforms. Decision Support Systems,
C. and Thadani, D. (2012). The impact of electronic word-of-mouth
communication: A literature analysis and integrative model. Decision
Support Systems, 54(1), pp.461-470.
J. J., Tormala, Z. L., & Rucker, D. D. (2008). A new look at the
consequences of attitude certainty: The amplification hypothesis. Journal of
Personality and Social Psychology, 95, 810–825.
S. and Hwang, J. (2009). How Consumers Evaluate eWOM (Electronic Word-of-Mouth)
Messages. CyberPsychology & Behavior, 12(2), pp.193-197.
Zhu, Xiaoquan (Michael) Zhang (2010) Impact of Online Consumer Reviews
on Sales: The Moderating Role of Product and Consumer Characteristics. Journal
of Marketing: March 2010, Vol. 74, No. 2, pp. 133-148.
L. (1954). A Theory of Social Comparison Processes. Human Relations,
R. and McLeay, F. (2013). E-WOM and Accommodation: An Analysis of the Factors
That Influence Travelers’ Adoption of Information from Online Reviews. Journal
of Travel Research, 53(1), pp.44-57.
M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior:
An Introduction to Theory and Research.Reading, MA: Addison-Wesley.
CP, Petty RE, Cacioppo JT (1992). Need for Cognition and Advertising:
Understanding the Role of Personality Variables in Consumer Behavior. J.
Consum. Psychol. 1(3): 239-260.
Thorsten, Kevin P. Gwinner, Gianfranco Walsh, and Dawyne D. Gremler (2004),
“Electronic Word-of Mouth via Consumer-Opinion Platforms: What Motivates
Consumers to Articulate Themselves on the Internet,” Journal oflnteractive
Marketing, 18 (Winter), 38-52.
C I, Janis I L, Kelley H H. (1953). Communication and persuasion. New Haven:
Yale University Press, 6-67.
P. (1993). Marketing Communications Renaissance. International Journal
of Advertising, 12(4), pp.367-386.
J. and Lee, J. (2009). Understanding the product information inference process
in electronic word-of-mouth: An objectivity–subjectivity dichotomy perspective. Information
& Management, 46(5), pp.302-311.
J., Park, D. and Han, I. (2008). The effect of negative online consumer reviews
on product attitude: An information processing view. Electronic
Commerce Research and Applications, 7(3), pp.341-352.
Sheng-Hsien. (2009). How do online reviews affect purchasing intention? African
Journal of Business Management Vol.3 (10), pp. 576-581
D, Chevalier JA (2006). The Effect of Word of Mouth on Sales: Online Book
Reviews. J. Mark. Res. August: 345-354.
Lee Ph.D. , Shelly Rodgers Ph.D. & Mikyoung Kim MA (2009) Effects of
Valence and Extremity of eWOM on Attitude toward the Brand and Website, Journal
of Current Issues & Research in Advertising, 31:2, 1-11
S. (1980). Toward a theory of conversion behavior. Advances in experimental
social psychology, 13, 209-239. Chicago
S. (1985). Social influence and conformity. The Hadbook of Social
Awad, A. Ragowsky, Establishing trust in electronic commerce through online word
of mouth: an examination across genders, Journal of Management Information Systems
24 (4) (2008) 101–121.
Richard W. and Donald H. Granbois (1979), “Consumer Decision Making: Fact or
Fiction?” Journal of Consumer Research, 6 (September), 93-100.
R. E., & Cacioppo, J. T. (1986). The Elaboration Likelihood Model of
Persuasion. In L. Berkowitz (Ed.), Advances in Experimental Social Psychology
(Vol. 19, pp. 123-205): Academic Press.
H, Ambler T, Sven B, Kenning P. 2007a. What can advertisers learn from
neuroscience? International Journal of Advertising 26(2): 151–175.
M, & Root-Shaffer, T (1988), ‘The Role of Involvement and Opinion
Leadership in Consumer Word-of-Mouth: An Implicit Model Made Explicit’, Advances
In Consumer Research, 15, 1, pp. 32-36
D. and Lomax, W. (2002). Taking control of word of mouth marketing: the case of
an entrepreneurial hotelier. Journal of Small Business and Enterprise
Development, 9(4), pp.349-357.
Z. L., & Briñol, P. (2015). Attitude change and persuasion: Past,
present and future directions. In M. I. Norton, D. D. Rucker, & C.
Lamberton (Eds.), Cambridge handbook of consumer psychology (pp.
29-64). Cambridge, MA: Cambridge University Press.
Z.L., Petty, R.E. and DeSensi, V.L., (2010). Multiple roles for minority
sources in persuasion and resistance. Minority influence and
innovation: Antecedents, processes, and consequences, pp.105-131.
W., Lundgren, S., Ouellette, J. A., Busceme, S., & Blackstone, T. (1994).
Minority influence: A meta-analytic review of social influence processes. Psychological
Bulletin, 115(3), 323-345.
Liu & L. J. Shrum (2009) A Dual-Process Model of Interactivity Effects,
Journal of Advertising, 38:2, 53-68
J Q, Craciun G, Shin D. (2010). When does electronic word-of-mouth matter? A
study of consumer product reviews. Journal of Business Research, 63(12):