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Received March 2000
Revised December 2000
Accepted February 2001
The contribution of emotional
satisfaction to consumer
loyalty
Yi-Ting Yu
Monash University, Singapore
Alison Dean
Monash University, Churchill, Australia
Keywords Loyalty, Customer satisfaction, Customer loyalty, Higher education
Abstract Many customer satisfaction studies have concluded that there is a significant
relationship between customer satisfaction and loyalty, but this finding has been questioned in
that most of the studies focus on measuring the cognitive component of customer satisfaction.
This study includes the cognitive component, but focuses on the affective component. It explores
the role of emotions in satisfaction, and then compares the predictive ability of the cognitive and
affective elements. Key findings are that both positive and negative emotions, and the cognitive
component of satisfaction correlate with loyalty. Regression analysis indicates that the affective
component serves as a better predictor of customer loyalty than the cognitive component. Further,
the best predictor of both overall loyalty and the most reliable dimension of loyalty, positive word
of mouth, is positive emotions. Thhe theoretical and practical implications of these findings are
discussed.
Introduction
It may appear unnecessary to study the relationship between customer
satisfaction and customer loyalty as many studies have confirmed that there is
a significant positive relationship between these two variables (see Colgate and
Stewart, 1998; Hocutt, 1998; Patterson and Spreng, 1997). However, many of the
satisfaction-loyalty relationship studies were done when the development of
the satisfaction construct was at an early stage, and customer satisfaction was
still seen as an ``elusive construct'' (Rosen and Surprenant, 1998). More recently,
scholars comment that it is inappropriate to ignore the emotional component of
satisfaction, and hence the reliability findings of the previous studies are
questioned (Liljander and Strandvik, 1997; Peterson and Wilson, 1992; Stauss
and Neuhaus, 1997; Wirtz and Bateson, 1999). Consequently, this paper reports
on a study which aims to:
.
explore the role of emotions in customer satisfaction; and
.
re-test the satisfaction-loyalty relationship when the emotional
component is included.
International Journal of Service
Industry Management,
Vol. 12 No. 3, 2001, pp. 234-250.
# MCB University Press, 0956-4233
First, we review the recent literature on customer satisfaction and customer
loyalty, and develop research propositions consistent with the research aims.
The research design is then described, and the results discussed. The paper
concludes with implications and recommendations for future research.
A brief review of customer satisfaction research
Emotional
In the early stages of services research, researchers attempted to diminish the satisfaction and
confusion between customer satisfaction and service quality by determining consumer loyalty
whether there is any distinction between them, and by exploring antecedents
(Cronin and Taylor, 1992; Oliver, 1993a). Oliver (1993a, p. 76) distinguishes
between the two constructs by suggesting that satisfaction is ``potentially all
235
salient dimensions'', it requires experience-dependency and involves emotions.
In his study, Oliver reverses the previous notion that satisfaction is the
antecedent of quality and claims that quality is the antecedent of satisfaction.
Spreng and Mackoy's (1996) study further tests and confirms Oliver's
conceptual model. Lately, customer satisfaction has been commonly accepted
as a different construct from service quality and the emphasis has been on
studying the relationships between them (Shemwell et al., 1998; Taylor and
Baker, 1994).
With consistent findings that service quality and satisfaction are different
constructs, and that service quality leads to customer satisfaction, the research
interest moved to studying the linkages between customer satisfaction, service
quality and customer loyalty/retention. While the direct relationship between
customer satisfaction and loyalty has been shown to be complex and
asymmetric (Bloemer and Kasper, 1995; Mittal and Lassar, 1998; Oliver, 1999),
and some research has shown that switching behavior and repurchase
intentions are not consistent with satisfaction levels (Stauss and Neuhaus,
1997), a number of studies suggest that there is a significant positive
relationship between customer satisfaction and customer loyalty/retention
(Anderson and Sullivan, 1993; Cronin, Brady and Hult, 2000; Shemwell et al.,
1998; Taylor and Baker, 1994). Hence an overall research proposition is
suggested as follows.
Research proposition 1: There is a significant positive relationship
between customer satisfaction and customer loyalty.
Before proceeding with further literature, we now briefly discuss the terms
satisfaction and loyalty and define them for the context of our study. Drawing
on the work of leading researchers in the services field for over 20 years, Roest
and Pieters (1997) developed a nomological net to distinguish service quality
and customer satisfaction. In doing so, they define satisfaction, as a relative
concept that involves both cognitive and affective components, is consumerrelated (rather than product-related), mainly transactional, and incorporating
an appraisal of both benefits and sacrifices. However, Roest and Pieters also
state that ``. . . eventually, satisfaction may become or influence product
attitude, which may be regarded as an aggregated but not relativistic construct
involving a readiness to act'' (1997, p. 345). In summary, we note the distinction
between transaction-specific and overall satisfaction, and we adopt the broader
definition of satisfaction whereby the overall measure is an aggregation of all
previous transaction-specific satisfaction, and involves both cognitive and
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affective components. Recently, the overall measure has been shown to be a
better predictor of repurchase intentions (Jones and Suh, 2000).
Loyalty is interpreted as true loyalty rather than repeat purchasing
behaviour, which is the actual rebuying of a brand, regardless of commitment
(Bloemer and Kasper, 1995). True loyalty, in this context, encompasses a nonrandom, behavioural response which results from evaluation processes that
result in commitment (Bloemer and Kasper, 1995). This is in contrast to
spurious brand loyalty which is a function of inertia. However, loyalty is a
multi-dimensional construct and includes both positive and negative responses
(Zeithaml et al., 1996). In this study, loyalty is to an educational provider and is
therefore service loyalty, rather than brand loyalty as has been developed in
relation to goods. In comparison to brand loyalty, service loyalty studies are
under-represented in the literature (Bloemer et al., 1999; Javalgi and Moberg,
1997).
Having established our overall research proposition as above, we
acknowledge that it would be meaningless to re-test the same proposition
without incorporating recent developments in the satisfaction literature. In
particular, it is argued that satisfaction includes both cognitive and emotional
components. The cognitive component refers to a customer's evaluation of the
perceived performance in terms of its adequacy in comparison to some kind of
expectation standards (Liljander and Strandvik, 1997; Oliver, 1980; Wirtz,
1993). The emotional component consists of various emotions, such as
happiness, surprise and disappointment (Cronin et al., 2000; Liljander and
Strandvik, 1997; Oliver, 1993b; Stauss and Neuhaus, 1997).
It is important to note that the emotional component is a form of affect, and
is a response to service delivery. In this study, ``consumption emotions are the
affective responses to one's perceptions of the series of attributes that compose
a product or service performance'' (Dube and Menon, 2000, p. 288). Such
emotions are usually intentional (that is, they have an object or referent) and
are different to the concept of mood, which is a generalised state induced by a
variety of factors, and is usually diffused and non-intentional (Bagozzi et al.,
1999). Emotions and mood (and attitudes) are all elements of a general category
for mental feeling processes, referred to as ``affect'' (Bagozzi et al., 1999). The
emotional component in the satisfaction judgment is therefore independent
from the overall affective sense present in the respondent at the time of the
service (de Rutyer and Bloemer, 1998). The cognitive and emotional
components of satisfaction are now considered separately.
Reflections on the cognitive component in customer satisfaction
studies
As indicated above, expectancy disconfirmation theory is the dominating
model for measuring customer satisfaction (Brookes, 1995). That is, satisfaction
is determined by the confirmation or disconfirmation of expectations with
perceptions of the perceived performance on various service items (Danaher
and Haddrell, 1996). The multi-item disconfirmation model has been applied in
many customer satisfaction studies, and has been proven to be very useful
Emotional
(Danaher and Haddrell, 1996; Wirtz and Bateson, 1999). Further, when satisfaction and
compared to other approaches, its benefits outweigh its main shortcoming, consumer loyalty
which is its conceptual overlap with service quality. Such benefits include
higher reliability, convergent and discriminant validity, face validity,
managerial value and a lower skewness problem (Danaher and Haddrell, 1996).
237
In relation to the overlap between service quality and satisfaction, the multiitem disconfirmation model is very similar to the most famous service quality
measurement scale, SERVQUAL. As both scales use disconfirmation of
expectations, it is doubtful whether the results of some previous satisfaction
studies show satisfaction or service quality. However, the two constructs
employ a different definition of expectations (Zeithaml et al., 1993), and have a
conceptual distinction in that satisfaction is an ``experience-dependency''
construct and service quality does not require experience (Danaher and
Haddrell, 1996; Oliver, 1993a). If the scale seeks respondents' assessment of
their ``perceived service experience'', it is alleged that it is essentially measuring
satisfaction rather than service quality (Danaher and Haddrell, 1996). This
study therefore employs the multi-item disconfirmation scale to measure the
cognitive component of satisfaction.
Many previous satisfaction studies, which focus on the cognitive component,
suggest that there is a positive relationship between satisfaction and loyalty
(see Andreassen and Lindestad, 1998; Colgate and Stewart, 1998; Danaher and
Haddrell, 1996; Mittal et al., 1998; Taylor and Baker, 1994), and we therefore
propose the following:
Research proposition 1a: There is a significant positive relationship
between the cognitive component of customer satisfaction and customer
loyalty.
However, focusing only on the cognitive component of satisfaction neglects an
important element, namely emotions, and may be insufficient to obtain a
comprehensive picture of consumer responses. The emotional element is now
pursued.
Affective measures in customer satisfaction
Although there is still debate about whether satisfaction is itself an emotional
construct or a cognitive construct which includes an emotional component (Babin
and Griffin, 1998; Bagozzi et al., 1999; Crooker and Near, 1998), it appears that
emotions may be one of the core components of satisfaction (Dube and Menon,
2000; Westbrook and Oliver, 1991). Further, it is suggested that emotions may
distinguish customer satisfaction from service quality (Oliver, 1993a).
Recent studies recognize that emotion is a core attribute in satisfaction and
suggest that customer satisfaction should include a separate emotional
component (Cronin et al., 2000). Stauss and Neuhaus (1997) argue that most
satisfaction studies only focus on the cognitive component, and that the
omission of the affective component is one of the main issues in satisfaction
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research. Their proposition is supported by Liljander and Strandvik (1997),
who argue that customer satisfaction includes both affective (or emotional) and
cognitive components. Further, Stauss and Neuhaus (1997) suggest that it is
inappropriate to assume that consumers experience the same emotions and
cognition when they give the same score for their overall satisfaction level. We
therefore propose to include a separate emotional component in satisfaction, as
the major contributor to the affective element.
It is proposed that one's emotions have an influence on behavior. This is due
to human nature, in that one responds to an event in certain ways to maintain a
positive emotion, such as happiness, and to avoid a negative emotion, such as
depression. Specifically, a person's positive emotions tend to link to his/her
decisions to stay or continue with what he/she has been doing. Conversely,
negative emotions tend to link to the opposite decisions, such as to leave and
discontinue involvement (Bagozzi et al., 1999). Positive emotions may also lead
one to share the positive experience with others, while negative emotions may
result in complaining behavior (Bagozzi et al., 1999; Liljander and Strandvik,
1997). Supported by the previous findings that there is a connection between
emotions and behavior (Bagozzi et al., 1999), and Stauss and Neuhaus' (1997)
study, which found that there is a significant relationship between emotions
and loyalty, we propose the following:
Research proposition 1b: There is a significant positive relationship
between the affective component of customer satisfaction and customer
loyalty.
The better predictor of customer loyalty: cognitive or affective?
While general research conclusions suggest that there is a positive relationship
between customer loyalty and both the cognitive and emotional components of
satisfaction, there is a lack of empirical evidence to determine which of the
components serves as a better predictor of satisfaction. This is particularly
important, as the cognitive component of satisfaction alone has failed to serve
as an effective predictor of customer loyalty (Stauss and Neuhaus, 1997).
To date there are very few affective/emotional scales specifically developed
to measure customer satisfaction emotions. Stauss and Neuhaus (1997)
developed a scale, originally with four dimensions, namely, optimism/
confidence, steadiness/trust, disappointment/indecision, and protest/
opposition. Stauss has now extended this to five with the addition of
indifference/resignation (personal communication, 1999). In 1997, Liljander and
Strandvik (1997), based on the previous literature, developed a more
comprehensive emotional scale that includes seven emotional attributes:
happy, hopeful, positively surprised, angry, depressed, guilty and humiliated.
Liljander and Strandvik also suggest that customer satisfaction emotions can
be divided into two groups: positive emotions and negative emotions. Positive
emotions include happy, hopeful and positively surprised, while negative
emotions include angry, depressed, guilty and humiliated. Although there is no
apparent consensus about the best way to measure the emotional component,
in traditional literature, positive and negative emotions are often used to
Emotional
compare effects (Crooker and Near, 1998).
satisfaction and
There is consensus among researchers that loyalty is a complex construct, consumer loyalty
evident in the variety of perspectives that have been used to study it (Javalgi
and Moberg, 1997). These perspectives include behavioral, attitudinal and
cognitive processes, however, the early customer loyalty studies focus mainly
239
on the behavioral perspective and then later shift to an attitudinal approach (de
Ruyter et al., 1998). Based on the attitudinal approach, customer loyalty can be
studied via its dimensions, such as word-of-mouth, complaining behavior and
purchase intention. However, there are different findings in relation to loyalty
dimensions, even when the same loyalty scales are employed. Parasuraman et
al. (1994) developed a loyalty scale and found that loyalty consists of loyalty to
company, propensity to switch, willingness to pay more, external response to
problem and internal response to problem. De Ruyter et al. (1998) later adopted
the same scale but found that loyalty consists of three dimensions: preference,
price indifference and dissatisfaction response. However, the same authors
suggest that the necessary elements to operationalise loyalty are captured in
the ``behavioral intentions battery'', refined by Parasuraman and his coworkers. (Bloemer et al., 1999; Zeithaml et al., 1996). This study therefore
adopts and customises this scale to explore the relationship between customer
satisfaction, including both cognitive and emotional components, and loyalty.
Methodology
Sample
The subjects in this study were on-campus undergraduate students in business
and economics at a large university in Australia. Convenience sampling was
employed and self-administered surveys were used to collect the data. A total
of 320 surveys were distributed and 122 valid returns were obtained, giving a
response rate of 37.5 per cent. The average age of respondents was 24. The
respondent profile was female (55.8 per cent), average age 24 years, and
comprising 57.9 per cent Australian and 42.1 per cent international students.
This cohort was considered representative by the head of the school.
Scales employed: customer satisfaction cognitive component
Seven-point Likert scales were employed to measure both customer satisfaction
and loyalty. The scale employed to measure the cognitive component of
customer satisfaction focused on educational service attributes, and was
customised from the instrument developed by Dean (1999). It is based on the
multi-item disconfirmation model, and uses a single column format. The scale
includes six groups of service attributes: course structure, teaching, lecturer's
interaction and support, administration support, feedback and assessment, and
physical presentation. A typical item reads, ``The written feedback on
assignments . . . 1 (failed to meet my expectations) . . . to 7 (far exceeded my
expectations)''. At the end of each group, an overall value for satisfaction with
the focus of the items was obtained.
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Scales employed: customer satisfaction affective component
To gain insights into the affective component, we used the emotional scale
developed and tested by Liljander and Strandvik (1997). The scale was adopted
in its entirety. A typical item reads ``So far, my overall studying experience at
(the provider institution) makes me feel . . . happy''. Responses are on a Likert
scale from 1 (never) . . . to 7 (often). Liljander and Strandvik were unable to
study the relationship between the customer satisfaction emotional component
and customer loyalty because, in the industry that they used, customers do not
have the choice to switch to another brand or another service provider. Our
study therefore builds on their work in pursuing the relationship.
Scales employed: customer loyalty
In terms of customer loyalty, Parasuraman et al.'s (1994) ``Reconfigured
behavioral-intentions battery'', subsequently refined by its authors (Zeithaml et
al., 1996) and also used by de Ruyter et al. (1998), and Bloemer et al. (1999) was
adopted and customised for this study. The original scale had 13 items
(discussed in relation to Table II), and five components: loyalty to company,
external response to problem, propensity to switch, willingness to pay more,
and internal response to problem. In their paper, Parasuraman et al. (1994) note
that their scale requires refinement particularly for the latter three of these
components, but that the ``loyalty'' component demonstrated excellent internal
consistency while the ``external response'' was adequate according to the
criteria of Nunnally (1978).
Results and discussion
The scales
Prior to exploring the findings with respect to the research aims, we include
some discussion about the scales that we used, their reliability and the factor
patterns that they produce.
Normality
In all cases, negative questions were reverse coded for consistency. Normality
tests, based on the different components in the survey, indicated adequate
results. Of particular interest is the degree of skewness as customer satisfaction
studies tend to be positively skewed (Coakes and Steed, 1999). The overall
scales did indicate some positive skewing (0.22 and 0.23 for emotional and
cognitive scales) but, given the nature of the study, these values were
considered adequate to continue with the analysis.
Reliability
The reliability of the scales was established by utilising Cronbach's alpha. The
cognitive component, emotional component and overall loyalty component had
alpha scores of 0.94, 0.80 and 0.77 respectively, all indicating acceptable values
(Nunnally, 1978).
Factor analysis: emotions scale
Emotional
It was intuitively expected that the emotions scale would divide into two factors, satisfaction and
representing positive and negative emotions. Principal components analysis with consumer loyalty
varimax rotation confirmed this expectation, with the two factors explaining 46.9
per cent and 19.1 per cent of the variance respectively (see Table I). However,
feelings related to anger loaded more highly with positive emotions than with
241
negative. This result is not easily explained but it is possible that, as anger is
usually directed at someone, its interpretation is confused. Or anger might
represent a third dimension of the emotional component and need to be further
explored. This possibility is consistent with the model conceptualised by DubeÂ
and Menon (2000) which suggests that negative emotions have three components,
``other-attributed'', ``self-attributed'' and ``situation-attributed''. In their model, the
``other-attributed'' component is related to anger. Another possibility is that both
positive and negative emotions can exist at the same time at a high level, thus
anger loads on both factors. It is suggested that customers may have a zone of
tolerance for negative emotions and that, within this zone, their negative emotions
do not affect their positive emotions, so that both positive and negative emotions
can exist at the same time (Liljander and Strandvik, 1997). In this study, a possible
interpretation is that the respondents have simultaneously experienced high
levels of positive emotions and anger. When anger is dropped from our scale, the
reliability only decreases by 0.1, so it is retained in our current analysis. However,
its role in customer satisfaction provides an interesting focus for future work on
the emotions scale.
Factor analysis: cognitive scale
The dimensions of the cognitive scale, the educational service attributes have
been developed and tested previously (Dean, 1999). However, as a number of
items were added to the original scale, to account for the different educational
context (on-campus classes versus distance education), a factor analysis was
performed. Principal components analysis with varimax rotation identified
Description
1. Positive emotions
Happy
Hopeful
Positively surprised
2. Negative emotions
Angrya
Depresseda
Guiltya
Humiliateda
Factor loading
1
Reliability
2
0.794
0.778
0.810
0.852
Note: Factor loadings less than 0.35 have been omitted;
0.546
0.657
0.829
0.771
a
reverse coded
0.77
0.75
Table I.
Emotions scale: factor
loadings and reliability
values
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seven factors with eigenvalues greater than one, accounting for 69.1 per cent of
the variance. The results are shown in Table II.
The factors shown in Table II have loaded essentially as expected, except for
the factor that we had labelled ``teaching'' which split across the factors we had
labelled ``teaching'' and ``course structure''. On reflection, this result is readily
Description
1. Feedback and assessment
Clearness of criteria
Written feedback
Assignment return time
Questions and subject aims
Fairness
2. Physical environment
Tables
Heating
Chairs
Lighting
Factor loading
1
2
3
6
7
0.362
0.372
0.879
0.817
0.811
0.594
0.803
0.792
0.720
4. Administration
Effectiveness
Efficiency
Time student advisor spent
Friendliness of staff
Visual presentation of lectures
0.847
0.772
0.698
0.567
0.464
5. Learning materials
Ease of reading
Learning materials
Clarity of objectives
Arrival in timely manner
0.390
6. Course structure and content
Variety
Flexibility
Ease of understanding
Knowledge or skills taught
Teaching techniques used
7. Technology
Technology in the classroom
5
0.821
0.763
0.641
0.608
0.594
3. Interaction and support
Feedback in class
Interaction with lecturers
Consultation times
Table II.
Cognitive scale: factor
loadings
4
0.423
0.415
0.422
Note: Factor loadings less than 0.35 have been omitted.
0.439
0.356
0.815
0.675
0.630
0.597
0.463
0.382
0.662
0.628
0.623
0.602
0.464
0.755
explained as the items left in ``teaching'' are all related to ``learning materials'',
Emotional
and ``course structure'' is really ``course structure and content''. Finally, the satisfaction and
single item relating to technology split out and formed a factor on its own. In consumer loyalty
summary, the seven factors that contribute to the cognitive scale, and the
percentage of variance that they explain, are feedback and assessment (11.2),
physical environment (11.1), interaction and support (10.8), administration
243
(10.6), learning materials (10.1), course structure and content (9.7), and
technology (5.5). As the overall cognitive scale demonstrated good reliability
(0.94) and was used in its entirety for our analysis, we did not pursue further
implications of the factor structure. However, the results provide a useful
starting point for further scale development.
Factor analysis: loyalty scale
When the items in the loyalty scale were analysed, four factors emerged, as
shown in Table III. These factors (positive word of mouth, complaining
behavior, switching behavior, and willingness to pay more) accounted for 28.9
per cent, 19.2 per cent, 10.7 per cent and 9.3 per cent of the variance
respectively. The first of our four factors contains four of the five items in
Parasuraman et al.'s (1994) ``loyalty to company'' factor. The fifth item, ``Do
Description
1. Positive word-of-mouth
Say positive things about the course
Recommend the course to someone else
Encourage friends to apply for the same course
Consider the same uni. as the first choice if pursue
further study
2. Complaining behavior
Complain to other students if experience problems
Complain to external agencies if experience problems
Complain to school staff if experience problems
3. Switching behavior
Try to switch to another campus of the same
university if experience problems
Try to switch to another university if experience
problems
Study in another uni. If it offers a better price
Try to study fewer subjects at this university
4. Willingness to pay more
Continue the same course if the price increases
Pay a higher price for the benefits currently received
Note: Factor loadings less than 0.35 have been omitted
Factor loading
1
2
0.887
0.954
0.933
0.544
3
Alpha
4
0.94
0.479
0.67
0.671
0.782
0.777
0.597
0.611
0.563
0.646
0.72
0.748
0.622
0.635
0.780
0.45
Table III.
Loyalty scale: factor
loadings and reliability
values
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more business with XYZ in the next few years'' was not included in our study
as we felt it would be confusing to respondents in the second or third year of
their degree programs. We refer to the first factor as ``positive word of mouth''
to indicate its primary focus. Consistent with Parasuraman et al.'s (1994) study,
the best reliability was demonstrated by this factor.
In relation to the other factors, ``willingness to pay more'' has the same two
items as Parasuraman et al. (1994) but is not internally consistent, while the
items in ``external response to problem'' and ``propensity to switch'' have been
customised and are shown in the manner in which they loaded in our study. We
have changed the names to facilitate clarity.
To conclude the discussion of the scales, we found that they have proven
sufficiently reliable to work with, and the items have generally loaded as
expected on the various dimensions. Having established that the instrument
was adequate to pursue the aims of the study, we now report and discuss the
findings with respect to the specific aims.
The role of emotions
To commence our investigation of the first aim, the role of emotions in the
measurement of customer satisfaction, we first consider the correlation
between the dimensions of loyalty and the cognitive and emotional components
of satisfaction (see Table IV). Consistent with research propositions 1a and 1b,
Table IV confirms that there is a significant correlation between the two major
components of customer satisfaction (emotional and cognitive) and loyalty.
However, there is a higher correlation between overall customer loyalty and the
emotional component than the cognitive component, at the 0.01 significance
level. Further, the emotional component has slightly higher correlation
coefficients for positive word of mouth, switching behavior and willingness to
pay more when compared to the cognitive component.
The correlation coefficients for the positive and negative emotions suggest
that positive emotions are associated with all dimensions of loyalty except
``complaining behavior''. This finding may be due to the emotions scale not
covering all the emotions that significantly correlate with the various loyalty
dimensions. Intuitively, we expect that positive and negative emotions would
link to complaining behavior (Liljander and Strandvik, 1997) but, as well as the
three positive emotions included, there are other positive emotions, such as
Table IV.
Correlation analysis
results
Overall loyalty
Positive word of mouth
Complaining behaviora
Switching behaviora
Willingness to pay more
Notes: * p < 0.05; ** p < 0.01;
a
Emotional
component
Cognitive
component
Positive
emotions
Negative
emotionsa
0.534**
0.590**
0.088
0.262**
0.350**
0.424**
0.517**
0.153
0.145
0.313**
0.516**
0.582**
0.007
0.246**
0.375**
0.404**
0.435**
0.133
0.206*
0.235*
items reverse coded
relief, elation and joy (Bagozzi et al., 1999), which were not included in the scale.
Emotional
There is no evidence to show that each emotion has the same influence on satisfaction and
different responses, such as complaining behavior, but rather that different consumer loyalty
emotions may trigger different behavioral intentions (see Stauss and Neuhaus,
1997).
Bagozzi et al. (1999) suggest that emotions influence decision making, and
245
that positive emotions particularly link to one's intention to maintain an
ongoing plan and share the outcome of a certain activity/event. This conclusion
is consistent with our research findings that positive emotions significantly
correlate with positive word of mouth (to share the positive experience),
switching behavior (negatively correlated) and willingness to pay more (in
order to stay where he/she is).
The association between loyalty and negative emotions (which have been
reverse coded) suggests that they have a significant impact on loyalty as well.
Of particular interest is the lack of association between negative emotions and
complaining behavior. Again, this may be due to the absence of specific
negative emotions from the scale, such as regret and disappointment, which are
more likely to cause complaining behavior (Zeelenberg and Pieters, 1999). The
seven emotions in our emotions scale do not correlate with the respondents'
complaining behavior in this study, and it is noteworthy that the findings
about the relationship between regret and disappointment with complaining
behavior are inconsistent in Zeelenberg and Pieters' (1999) studies. These
results emphasise the need to further explore the possible negative emotions
that may influence complaining behavior. They also indicate that education
providers need to seek out negative responses as these are unlikely to be
voluntarily provided by students.
The satisfaction-loyalty relationship revisited
The second major aim of our study was to re-test the satisfaction-loyalty
relationship when the emotional component of satisfaction is included. In
particular, we were keen to establish the best predictors of loyalty and so we
used regression analyses to explore the possible relationships.
Best predictors of overall loyalty
To gain a feel for the relative importance of the cognitive and emotional
components in predicting customer loyalty, in the first regression we used
overall loyalty as the dependent variable, with the cognitive and emotional
components as independent variables. The adjusted R2 = 0.336, and F(2, 98) =
26.325, sig = 0.000. The standardized beta coefficients are shown in Table V
Cognitive component
Emotional component
Beta
t
sig.
0.179
0.482
1.917
5.149
0.058
0.000
Table V.
Standardized beta
coefficients (dependent
variable: overall
loyalty)
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and, while only 33.6 per cent of the variance in loyalty is explained, the findings
indicate that the emotional component is an important factor in explaining
loyalty, apparently more important than the cognitive component.
To substantiate the finding that inclusion of the emotional component leads
to better results in explaining loyalty when compared to using the cognitive
component alone, we performed another regression with overall loyalty as the
dependent variable and only the cognitive component as the independent
variable. In this case, the adjusted R2 = 0.172, and F(1, 101) = 22.151, sig =
0.000. The beta value for the cognitive component equalled 0.424, t = 4.706,
sig = 0.000. This result suggests that the emotional component is an important
predictor of loyalty, and is consistent with the suggestions of Liljander and
Strandvik (1997) that customer satisfaction is better explained when emotions
are included.
The next question of interest is the relative effect of positive and negative
emotions. To explore this, another regression analysis was performed, again
using overall loyalty as the dependent variable, but including the factor scores
for the two types of emotions. While the same variance is explained, positive
emotions emerge as the best predictor of overall loyalty (beta = 0.336, t = 3.153,
sig = 0.002) with negative emotions also significant (beta = 0.232, t = 2.488, sig
= 0.015) and the overall cognitive assessment no longer significant. One would
expect that having positive emotions towards ``my overall studying experience
at service provider'', would result in more loyalty to that service provider. Our
finding supports this assumption and also indicates that there is a negative
association for negative feelings (as responses were reverse coded). How
students feel about their studying experience is therefore highly relevant to the
messages they are likely to give to others, and the personal responses they are
likely to make.
Best predictors of word of mouth behavior
As indicated in Table IV, positive word of mouth has the highest correlation with
the components of customer satisfaction and the highest reliability of the four
loyalty dimensions. Further, switching costs are high and price regimes are
generally inflexible in education, so we decided to conduct a further regression
analysis using the components of satisfaction with positive word of mouth as the
dependent variable. As there was no correlation between complaining behaviour
and the components of satisfaction, we did not pursue its analysis.
The results in Table VI indicate that positive emotions are an important
predictor of ``positive word of mouth'', but that the students' cognitive
Table VI.
Standardized beta
coefficients (dependent
variable: word of
mouth)
Positive emotions
Negative emotions
Cognitive component
Beta
t
sig.
0.369
0.152
0.263
3.720
1.735
2.882
0.000
0.086
0.005
assessment of satisfaction with educational attributes is also a significant
Emotional
predictor. The adjusted R2 = 0.395 and F(3, 100) = 23.402, sig = 0.000. Further, satisfaction and
while the t value for negative emotions is not significant at the 95 per cent consumer loyalty
confidence level, the result suggests that this is worthy of further investigation.
When a further regression was run, using positive word of mouth as the
dependent variable against the cognitive component only, the result confirmed
247
that, in this study, positive emotions are a better predictor of positive word of
mouth than the cognitive element. In particular, for the latter regression, the
adjusted R2 = 0.260 and F(1, 104) = 37.855, sig = 0.000.
In general then, if emotions were not included in the scale, and only the
cognitive component used to measure satisfaction, a comprehensive illustration
of satisfaction is not gained. Consequently, it is suggested that an emotional
scale needs to be included as part of customer satisfaction measurement.
Implications of the study
The main theoretical implication of this study is that the emotional component
of satisfaction, which has not been considered in some of the recent customer
satisfaction studies, serves as a better predictor of loyalty than the cognitive
component. In particular, positive emotions are positively associated with
positive word of mouth and willingness to pay more, and negatively associated
with switching behaviour. Similarly, negative emotions are negatively related
to positive word of mouth and willingness to pay more, and positively
associated with switching behaviour. However, as this study represents a
relatively small sample in one industry, these results require further
investigation and verification.
As there is a significant relationship between customer satisfaction
(especially the emotional component) and customer loyalty, and based on the
assumption that it is cheaper to retain existing customers than attract new
customers (see Alford and Sherell, 1996), it appears that managers need to reemphasise how customers ``feel'' about their experiences of service delivery. In
particular, they should try to achieve some balance in their pursuit of
satisfaction information. It seems feasible that, in endeavouring to adopt
measurement practices that are scientific and rigorous, managers may not
provide sufficient opportunity for comments with an affective base and,
consequently, fail to recognise the power and importance of emotions. An
obvious extension of this is that, in retaining or enhancing customer loyalty,
organizations need to explore and, as far as possible, manage the emotional
components.
Future research
It is suggested that expectations, perceived performance and/or satisfaction
level shift over time (Patterson et al., 1998; Peterson and Wilson, 1992). In this
study, emotions in customer satisfaction were measured at one specific point in
time and, hence, the result is only true for the time of completion of the
questionnaire. As the delivery of higher education is an extended service
IJSIM
12,3
248
encounter, the endurance of loyalty resulting from satisfaction may be
challenged (Oliver, 1999). Future longitudinal studies could explore this issue.
Demographic backgrounds also need to be considered. In particular, it is
suggested that different cultural backgrounds may affect one's beliefs and
behaviors (Hofstede, 1994; Winsted, 1997). That is, future research could
compare the sample being studied based on their demographic backgrounds to
see if the affective component still serves as a better predictor for customer
loyalty.
As in other satisfaction studies, there are still some methodological issues
that need to be addressed. These include the use of bipolar construct questions,
and positively skewed responses (Peterson and Wilson, 1992). Finally, there is a
need to develop and refine the emotion scales. This provides scope for much
interesting work.
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