The influence of positive and negative eWOM on purchase intention
Introduction and Conceptual Framework
Consumers rely on information from others to make purchasing decision, especially in
uncertain situations (Mitchell and McGoldrick 1996). Word of mouth (WOM) is an effective
way to acquire service evaluation and insightful information from other experienced
customers within a short period of time (Mazzarol, et al, 2007) and it can be positive or
negative. The intangible and experiential attribute of services (Zeithamal, 1981) make WOM
more influential and more credible than in product decision situation (Opperman, 2000), and
this is reflected in the large number of customers that switch service providers based on
WOM (Keaveney, 1995; East et al., 2001). Holiday destination choice is a complex one that
includes decisions of many services activities and is highly costly (Bargeman and Van der
Poel, 2002).
There is a rich body of literature on traditional face to face referral (Arndt, 1967; Bone,
1995). Electronic word of mouth (eWOM), that is, when the referral is received through
electronic communication, provides insights into how consumers use online information to
assist purchasing decision making through the use of online rating (Sparks and Browning,
2011), social media (Brown et al., 2007), online recommendation agents (Gershoff et al.
2003), and online forum (Harrison-Walker, 2001). However, there is little that leverages the
power of e-mail and the extended personal influence of e-mail, despite it being one of the
most used online communication activities (Purcell, 2011). Email is a tremendously powerful
communication tool for marketers (Stokes and Lomax, 2002). Therefore this study
investigates how unsolicited email referrals, influence purchasing intention of a holiday. In
particular, the study focuses on the influence of source (i.e., sender) expertise and similarity
on trustworthiness and purchase intention in both positive and negative email messages.
WOM is considered as more reliable and trustworthy than other sources of information
(Day, 1991) and is effective as a decision making aid when the consumer trusts the
recommender (Smith et al, 2005). The information source must be perceived as credible and
relevant for WOM to have an effect on the receiver. Expertise and trustworthiness are critical
components of credibility (Hovland et al., 1953). In addition, Lazarsfeld and Merton (1954)
argue that similarity between people encourages communication, and Festiger (1954) asserts
that people with similar attitudes and capabilities have similar needs and preferences. Thus
WOM from a source that is similar to the receiver is likely to be considered more relevant
than a referral from a dissimilar source.
Trustworthiness is also essential to credibility. The perception of trustworthiness is the
product of a set of beliefs that are centred on the integrity, benevolence and ability of the
trusted party (Mayer and Davis, 1999). Mayer and Davis (1999) defined ‘integrity’ as the
belief that the trusted party adheres to accepted rules of conduct, such as honesty,
‘benevolence’ as the belief that the trusted party wants to do good to the customer and
‘ability’ as concerned with beliefs about the skills and competence of the trusted party.
Research has shown that source expertise in the product or service has an impact on the
receiver’s purchasing decision and perceived trustworthiness (e.g., Smith, et al., 2005). A
source may be considered expert by virtue of “his or her occupation, social training, or
experience” (Schifman and Kanuk, 1997: p.335).
Online consumers are used to relying on other consumers’ product/service ratings to make
their purchasing decision (Sparks and Browning, 2011). In the specific context of this study,
the travel industry, people who are frequent travellers accumulate knowledge and retain
expertise from their experiences (Kerstetter and Cho, 2004). These characteristics may permit
consumers to effect others’ choices with respect to destination related alternatives (Kerstetter
and Cho, 2004). Therefore we incorporated sender expertise into our scenario and
hypothesise:
H1: The greater the perceived expertise of the source, the greater their perceived
trustworthiness.
Consumers appear to give more weight to recommendations coming from those with
greater knowledge about products and services. Consequently, information from an expert
source is also more influential (Bansaal and Voyer, 2000). Therefore we hypothesise that:
H2: The greater the perceived expertise of the source, the greater their perceived influence on
purchase intention.
Similarity is the degree to which individuals are similar in terms of certain attributes
including demographic and lifestyle (Wangenheim and Bayon, 2003) and perceptual believes
and values (Gilly, et al., 1998). Similarity between people facilitates the development of close
relationships and friendships (Lazarsfeld and Merton, 1954), as individuals tend to affiliate
with others who share similar interests or are in a similar situation (Schacter, 1959). Similarity
predisposes people towards a greater level of interpersonal attraction, trust and understanding
than would be expected among dissimilar individuals (Ruef et al., 2003). Thus we
hypothesise:
H3: The greater the perceived similarity of the source, the greater their perceived
trustworthiness.
Similarity facilitates the flow of product information due to a perception of ease associated
with the communication (Price and Feik, 1984). People with similar attributes, such as age,
gender, education or lifestyle are likely to have similar values and needs. Consequently,
WOM regarding product/service information from such source is perceived as more relevant
and will exert more influence (Gilly et al., 1998). Thus we hypothesise:
H4: The greater the perceived similarity of the source, the greater their perceived influence
on purchase intention.
When a message recipient is confident that an expert source will be willing to provide
accurate information because of his or her high trustworthiness, they may forgo the effortful
task of scrutinizing the message and instead unthinkingly accept the source’s conclusion as
valid. Information presented by trustworthy sources is, as such, more likely to be unthinkingly
accepted (Priester and Petty, 1995). Therefore we hypothesise that:
H5: The greater the perceived trustworthiness of the source, the greater its influence on
purchasing intention.
WOM can be positive or negative. Positive WOM (pWOM) refers to favourable
experiences and recommendations to buy, negative WOM (nWOM) to unfavourable
experiences and recommendations not to buy (Luo, 2009). Investigation of the differences in
the impact of nWOM and pWOM online has been increasing. Nevertheless, most of these
studies focus on product/brand choices rather than services. Studies on eWOM are generally
consistent with the negativity bias theory (Folkes and Kamins, 1999); negative eWOM has a
significantly higher impact on consumers’ evaluation of their emotional trust and intention to
shop online (Cheung and Lee, 2008). In addition, negative opinions receive more
consideration by recipients than positive opinion (Sparks and Browning, 2011). This may be
because negative opinions are perceived as more credible and easier to generalise than
positive opinions (Mizerski, 1982). Chatterjee (2001), however, disagrees with this notion as
the credibility of an online source is minimal when compared with face to face
communication. In contrast to other studies, Ahluwalia, (2002) and East et al. (2008) found
that positive information has a stronger impact on brand choice than negative information.
Consequently, we hypothesise that:
H6: The impact of source characteristics and trustworthiness on purchase intention will differ
according to email message direction (i.e., positive versus negative eWOM).
Research Design
A 2 (positive/negative) x 2 (expert/non-expert) x 2 (similar/non-similar), full factorial,
between subjects survey research design, using unsolicited e-mail scenarios, was used to
test the hypotheses. Two extreme scenarios – positive, expert, similar and, negative, nonexpert, dissimilar – are shown in Figure 1. As the study focuses on the relationships
between source characteristics and individual factors as they impact on behavioural
intentions, the sample needed to be (i) homogeneous and (ii) comfortable receiving
eWOM. Undergraduate students are homogenous in terms of age, interest and use of
computers and extensively use email, fulfilling both criteria. The survey was distributed
and administered during lectures, with an equal number of each scenario distributed. In
total, 650 questionnaires were returned. One hundred and seventy seven questionnaires
were discarded due to missing responses.
Figure 1: Scenarios
Scenario: Positive/ Expert/ Similar
You have received the following e-mail from your friend, who is similar to you. She/he travels abroad a lot
to different destinations and is telling you about her/his holiday. Please read the e-mail and complete the
questionnaire.
Hey sorry I wasn’t in-touch last week. I have been to yet another place for a holiday and have just got back
home. That holiday was good value. It was really fantastic. I should have gone there sooner. You should have
seen the beaches, really gorgeous, the place was fabulous, great weather, never been to such a brilliant place;
wow, I might even go back there again you’d love it.
Got to go, time to go out
See you around
Scenario: Negative/ Non-expert/ Dissimilar
You have received the following e-mail from your friend, who is not similar to you. She/he has never
travelled abroad before and is telling you about her/his holiday. Please read the e-mail and complete the
questionnaire.
Hi, sorry I have not been in-touch for a while. I have changed where I go to on my annual holiday and have
just got back home. That holiday was not good value. It was really awful. I should not have gone there. You
should have seen the beaches, really like a rubbish dump. The place was horrible, lousy weather. It is such a
boring place. It is not somewhere I’d go back to, definitely not worth visiting.
Look forward to seeing you when we have the chance
Catch up with you later
Expertise was measured using a five-item, seven point semantic differential scale
(Netemeyer and Bearden, 1992; Bansal and Voyer, 2000). The scale used to measure
similarity (Brown and Reingen, 1987; Gilly, et al., 1998) contained five items with responses
ranging from not similar at all to very similar. Trustworthiness consisted of three factors Ability, Benevolence, and Integrity (Mayer et al., 1995) – and was measured using seventeen
seven point Likert items: six for ability, five for benevolence and six for integrity. Purchase
intention was measured using five semantic differential items with seven response categories
(Brunner and Hensel, 1996).
Analysis
Refining the measurement model statistics resulted in deleting one item from the integrity
measure. The overall model fit statistics for the measurement model including all the
constructs was acceptable:
Figure 2: Positive and Negative eWOM models
CMIN (724) = 1325.472, p
=.000, CMIN/DF = 1.831,
TLI = .917, CFI = .926,
RMSEA = .042. Metric
invariance was also
established across the
positive/ negative scenarios.
AVEs were generally
acceptable (i.e., greater than
.5), though some of the subdimensions of trustworthiness
were marginal: benevolence =
.49 (negative model), .48
(positive model); integrity =
.42 (negative model). All the
CRs were above .7 except those associated with the lower than desired AVEs. The
discriminant validity of the
Table 1: Structural Paths Estimates
trustworthiness sub-dimensions
Paths
Path estimates
From
To
Both Positive Negative
was confirmed by the three factor
.333
Expertise
Ability
model being a significantly better
.286
Expertise
Integrity
fit of the data than a single factor
.228
Similarity
Ability
model (Hair et al., 2010).
Similarity
Integrity
Benevolence Ability
Integrity
Benevolence
Benevolence Purchase
Expertise
Purchase
Similarity
Purchase
In all cases p < .001
.219
.580
.866
The structural models were
fitted simultaneously. The model
.367
fit statistics were acceptable:
.242
CMIN (749) = 1353.142, p =.000,
.791
.382
CMIN/DF = 1.807, TLI = .919,
CFI = .926, RMSEA = .041. When
Table 2: Direct and indirect effects
the relationships between
Model
Direct Indirect Total
constructs were constrained to be
Positive eWOM
.242
--- ..242
equal across negative and positive
Expertise
Negative
eWOM
.242
.090
.332
eWOM models there was a
Positive
eWOM
.791
--.791
significant differences between the
Similarity
Negative eWOM
.382
.070
.452
two models (∆χ² (13) = 32.037,
p=.002), indicating differences between the positive and negative message scenarios. Each
path was then individually constrained to identify where the differences between the positive
and negative models occurred. Three paths differed: from Similarity to Ability, from
Similarity to Purchase Intention, and from Benevolence to Purchase Intention. The resulting
models are shown in Figure 2, Table 1 shows the regression weights and the effects of source
characteristics on purchase intentions are in Table 2.
Findings and Conclusions
This paper determined the impact of source expertise and similarity on purchase intention.
In particular, it examined whether source expertise and similarity impacted directly or through
trustworthiness, and whether their impact differed according to message direction (i.e.,
positive or negative). The analysis clearly showed that both expertise and similarity impacted
directly on purchase intention. However, there was little indirect impact on purchase intention
through trustworthiness. While, with negative eWOM, expertise and similarity acted directly
on purchase intention, but also through trustworthiness, with positive eWOM only a direct
effect was observed. However, despite the lack of any indirect effects, the impact of source
similarity on purchase intention was significantly greater with positive eWOM.
Table 3 summarises the hypotheses. The study’s findings support the hypotheses
concerning the direct effect of source expertise and similarity on purchase intentions (H2 and
H4), as well as showing that there are differences between positive and negative eWOM (H6).
The effect of source characteristics on trustworthiness (H1 and H3) is, however, only partially
support as the perception of benevolence is not influenced by either expertise or similarity,
and it is only with negative eWOM that similarity influences the assessment of integrity. H5
was largely unsupported as it was only with the negative model that a relationship is observed
between any of the trustworthiness sub-dimensions (specifically benevolence) and purchase
intention.
Table 3: Summary of Hypotheses
Hypothesis
The greater the perceived expertise of the source, the greater their perceived
H1
trustworthiness
The greater the perceived expertise of the source, the greater their perceived
H2
influence on purchase intention
The greater the perceived similarity of the source, the greater their perceived
H3
trustworthiness
The greater the perceived similarity of the source, the greater their perceived
H4
influence on purchase intention
The greater the perceived trustworthiness of the source, the greater its influence
H5
on purchasing intention
The impact of source characteristics and trustworthiness on purchase intention
H6 will differ according to email message direction (i.e., positive versus negative
eWOM)
Partially
supported
Supported
Partially
supported
Supported
Largely
unsupported
Supported
The relationships between source characteristics and trustworthiness are largely irrelevant
to eWOM as only benevolence is important to purchase intention and this only occurs with
negative messages. In contrast, the evidence for the direct effects of expertise and similarity
on purchase intention is much stronger. In most cases these relationships are equivalent across
negative and positive messages, however, similarity has a greater direct impact on purchase
intention with positive messages. Differences in attribution across negative and positive
messages might explain this. When negative experiences are reported attribution might be
being assigned to the source (i.e., they did something wrong), whereas with positive
experiences attribution could be being assigned to the situation (i.e., the holiday destination).
Overall, these findings indicate that similarity has a stronger impact on purchase intention
than expertise. The impact of similarity on purchase intention is clearly stronger with positive
messages, whereas the addition of indirect effects makes the impact of expertise on purchase
intention slight stronger with negative messages.
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