A Customer Satisfaction Model Based on the Emotion and

A Customer Satisfaction Model Based on the Emotion and
the Service Quality
LIU Qingfeng
Guangdong University of Business Studies, P. R. China, 510320
Abstract: This exploratory study examined the customer satisfaction. Basing on the review of the
literatures, we established a conceptual model which included the consumption emotions, the perceived
service quality and the customer satisfaction. Then, we conducted an on-site questionnaire survey in
supermarkets in Tianjin. A sample included 387 questionnaires was taken to analyses. We found that the
customer satisfaction model we established fitted the data satisfactorily. After we compared with two
competing models, we found that the model which included both the consumption emotions and the
perceived service quality had a stronger ability to explain cust*omer satisfaction than any model which
just included either perceived service quality or consumption emotions. Finally, we discussed the
implications for management and future research in this area.
Keywords: Consumption emotion, Customer satisfaction, Model, Perceived service quality
1. Introduction
Current models of customer satisfaction can be divided into two kinds. We can call them the quality
satisfaction model and the emotion satisfaction model. The quality model considers that the customer
satisfaction is relative to the customer expectation, the perceived value and the perceived quality, etc.
For example, in the Swedish Customer Satisfaction Barometer, the overall satisfaction is decided by the
perceived quality and the customer expectation. In the American Customer Satisfaction Index, the
overall satisfaction is surveyed through the customer expectation, the perceived quality and the
perceived value. In the European Customer Satisfaction Index, researchers increase the other two
variables: the image and the perceived personnel value. In China, professor Zhao ping, from Tsinghua
University, proposes a Chinese Customer Satisfaction Model in which the overall satisfaction is
combined by the above concepts. The emotion satisfaction model argues that the customer satisfaction is
a function of the consumption emotion. “Consumption emotion refers to the set of emotional responses
elicited specifically during product usage or consumption of emotional experience, as described either
by the distinctive categories of emotional experience and expression or by the structural dimensions
underlying emotional categories, such as pleasantness/ unpleasantness, relaxation /action, calmness/
excitement”.
These studies make important contributions to our understanding of the customer satisfaction.
However, either the quality model or the emotional model can unilaterally survey the customer
satisfaction. Edwardson argues that the consumption process is not only a conceived process but also an
emotion experience process. For example, when we go shopping, what we felt is not only the good
service and the good commodities, but also the emotions (such as excitement, happy, joy, or, angry,
hates). Therefore, when both of the quality and the emotion are explicated, the customer satisfaction can
reflect the situation in nature.
The purpose of our paper is to further explore the customer satisfaction that contains the
consumption emotion and the perceived service quality. Firstly, we present a model that explicates the
satisfaction based on the customer consumption emotion and the service quality. Then, we present
exploratory data from an empirical study that provides some initial support for these ideas. Finally, we
discuss implications for future research in this area.
*
This paper was ninth funded social science research projects of Guangzhou Federation of Social
Sciences
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2. Conceptual framework
In order to establish the conceptual framework of customer satisfaction in the service context, we
will review the literatures about the service quality, consumption emotion and customer satisfaction.
Consumption emotions can be divided into the positive emotion and the negative emotion. The
perceived service quality can be measured through the visible facility quality and the invisible service
quality) .
2.1 The perceived visible facility quality
The perceived visible facility quality has been studied in the context of satisfaction and service
quality. Parasuraman, Zeithaml & Berry point out that the visible facility quality affects the perceived
service quality. Gronroos also argues that customers inferred the service quality according to the visible
facility quality. Based on available findings regarding visible quality, we propose the following
hypothesis:
H1: The visible facility quality bears a positive affect on the perceived service quality
According to the theory of “conceive – emotion – behavior”, we know that the customer cognition
appraisal to the objective will affect people’s emotion. Gardner mentions that customers’ consumption
emotion is affected by environments. Many of the other studies also give proofs that surroundings can
directly affect the customer emotion and their behaviors. Biter suggests that firms can induce consumer
positive emotion (such as lighting, color, signs, texture, pattern, profile, temperature) by regulating the
visible factors. We think that the comfortable environment, the neat service-place and the artistic
arrangement can induce customer’s positive emotion. Otherwise, they will induce customer’s negative
emotion. Therefore, we suppose the following two hypotheses:
H2: The visible facility quality can bears a positive affect on customer positive emotion
H3: The visible facility quality can bears a negative affect on customer negative emotion
Parasuraman, Zeithaml & Berry argue that tangible is one of the five dimensions of the customer
perceived service quality. Tangible includes the visible facility, equipment, staff and communication
equipment. The perceived visible quality can directly bear positive affect to customer satisfaction. But,
in American Customer Satisfaction Index, researchers merger the visible facility quality and the
perceived service into the perceived quality, which affects the customer satisfaction. We think that
during the consumption process, the customers’ good conceive will improve their satisfaction degree,
otherwise, the bad conceive will decrease customers’ satisfaction degree. Therefore, we propose the
following hypothesis:
H4: The visible facility quality can bears a positive affect on customer satisfaction
2.2 The invisible service quality
Gardner points out that the consumption emotion is affected by the service procedures, service
environments and the exchanges between the consumer and personnel. And a lot of researchers give
experimental proofs to show the invisible services are affecting the customers’ emotion. We believe that,
in the service process, the personnel language, attitude, gesture and skills and ability to communicate
will affect customers’ emotions. A good conceive to service will enhance the customer positive emotion
and weaken the negative emotion. A poor conceive to service will weaken the customer positive emotion
and induce negative emotion. Therefore, we assume that:
H5: The invisible service quality can bears a positive affect on customers’ positive emotion
H6: The invisible service quality can bears a negative affect on customers’ negative emotion
Domestic and foreign scholars conduct empirical studies on the relationship between a service
quality and its’ customer satisfaction. They all reach the same conclusion that the invisible service
affects customer satisfaction. Han Xiaoyun and Wang Chunxiao, Chinese researchers, conduct an
empirical study and draw a conclusion that the invisible service quality has different effects on customer
satisfaction for different types of businesses and different types of customers. We believe that the
customer perception of service is an important factor in forming customer satisfaction process. The
service quality is a positive relationship to the customer satisfaction. Therefore, we suppose the
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following hypothesis:
H7: The perceived invisible service quality can bears a positive affect on customer satisfaction.
2.3 The Consumption emotions
Lijander & Strandvik believe that the customer satisfaction should include emotional factors, and
think that satisfaction doesn’t include the emotional factors is not comprehensive. Westbrook (1987) did
an empirical research on the Auto and TV consumers to explore the impact of the emotional experience
to their satisfaction. The results showed that the positive emotion had a significant positive impact on
customer satisfaction and the negative emotion had significant negative impact on customer satisfaction.
After studying the relationship between the consumption emotion and the customer satisfaction, other
scholars also reached the same conclusion that the consumption emotion was equivalent to the positive
relationship to customer satisfaction. We believe that consumption emotion is an emotional reaction in
customers’ psychology accompanying the consumption process. This emotion is always changing.
Customer satisfaction is an emotional and cognitive response in the consumer end. Customer
satisfaction is a stable evaluation. Consumer emotion is an import influencing factor to customer
satisfaction. Therefore, we suppose the following hypotheses:
H8: The positive consumption emotion can bears a positive affect on customer satisfaction.
H9: The negative consumption emotion can bears a negative affect on customer satisfaction.
We combined the above hypotheses into the same model--satisfaction model. See Fig.1.
3. Methodology
Our study is conducted in supermarkets to test our model. There are four reasons to do so. Firstly,
the supermarket is one of the most frequent industries with which customers can contact. Most
customers have repeatedly consumption emotional experience. Secondly, the supermarket industry is
relatively mature, and the competition among enterprise is fierce, so changes have also taken place in
consumer emotion. Thirdly, supermarket services’ items and styles constantly update, so customer
emotions are easy to observe and measure. At last, supermarket consumers are more concentrated and
easy to investigate.
Negative emotion
Satisfaction
Positive emotion
Visible quality
Service quality
Figer.1 Satisfaction model
Extensively drawing on the results from the fields of customer satisfaction, consumer emotion and
service quality, we designs scales to measure every concept. 7 levels LIKERT scale was adapted for all
concepts. Numerical “1” expresses “don’t agree at all”, and “4” expresses neutral, and “7” expresses
“very much agree”. The construct of the perceived visible quality include four items: the supermarket
has modern business facilities(X1); the supermarket staff’s wear is clean and decency (X2); the
supermarket items layout neatly and orderly, and the supermarket has a good lighting effects (X3); the
air is very suitable for the supermarket business establishments (X4). The above items were applied by
many researchers (such as Parasuraman, Zeithmal, Berry, 1985; Cronin, Joseph & Taylor, 2000). The
construct of the invisible service quality is measured by five items: the supermarket staff is always
willing to help you (Y1); the supermarket staff fully understand your needs (Y2); the supermarket staff
service you actively (Y3); the supermarket staff has the ability to communicate (Y4); the supermarket
staff provides service to you timely (Y5). Consumption emotion is measured using Izard’s and Russell’s
six-item adjective scale. It consists of: high interest (Y6), very happy (Y7), very relaxed (Y8), very
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angry (Y9), very depressed (Y10), very irritable (Y11). Satisfaction is measured using four items:
comparing with your expectation, you are satisfied with supermarket in general (Y12); the decision you
come here shopping is right (Y13); you are very satisfied with the supermarket services (Y14); you are
very satisfied with the consumer experience (Y15). The above items were applied in many researches.
May 2006, we conducted an on-site questionnaire survey at five supermarkets in Tianjin. A total of
540 questionnaires were sent, and 387 valid questionnaires were returned. The valid return rate is
71.7%.
4. Data analysis
4.1 Reliability and validity
We use SPSS13.0 software to analyze the reliability of all measurement scales. All Cronbachcoefficients of the variables is listed in Table.1. Data shows that all measurement scales are reliable.
α
Construct
Cronbach-
α
Visible quality
0.849
Construct
Visible facility quality
Invisible service quality
α
Table.1 Scales cronbach- coefficients
Service quality Positive emotion Negative emotion
0.900
0.908
0.918
Indicator
X1
X2
X3
X4
Y1
Y2
Y3
Y4
Y5
Table.2 Indicators’ load factor
Load factor
Construct
0.83
Positive emotion
0.85
0.75
0.65
Negative emotion
0.81
0.82
0.83
Satisfaction
0.77
0.75
Indicator
Y6
Y7
Y8
Y9
Y10
Y11
Y12
Y13
Y14
Y15
Satisfaction
0.812
Load factor
0.87
0.92
0.83
0.85
0.96
0.85
0.78
0.69
0.82
0.80
We apply confirmatory factory analysis (CFA) to ensure validity. In our study, confirmatory factor
analyses are performed for each construct, and the results are provided in Table.2. The results are
satisfactory, too, because every load factor indicator is greater than 0.7 (except X4, Y13, but they are
near to 0.7 also).
4.2 Structural model
We use LESREL8.7 software to estimate the path coefficients and the fit goodness indices for the
structural model. Maximum likelihood estimates of the parameters and goodness of fit for the model are
listed separately in Table.3 and Table.4.
Construct
Visible quality
Service quality
Positive emotion
Negative emotion
Table.3 Maximum likelihood estimates of the parameters
for the model
Endogenous variable
Service quality Positive emotion Negative emotion
0.26 (t=3.75)
0.12 (t=1.42
-0.10 (t=-1.27)
0.40 (t=5.68)
-0.49 (t=-7.23)
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Satisfaction
0.28 (t=2.02)
0.38 (t=4.25)
0.51 (t=9.75)
-0.46 (t=-8.32)
Absolute fit
Comparative fit
Table.4 goodness of fit for structural model
Statistics
Goodness of fit
Chi-square (Df=167)
294(p=0.00)
Standardized Root Mean Square Residual
0.051(<0.08)
(SRMR)
Root Mean Square Error of
0.047(<0.08)
Approximation(RMSEA)
Goodness of Fit Index (GFI)
0.78(<0.9)
Adjusted Goodness of Fit Index (AGFI)
0.84(<0.9)
Normed Fit Index(NFI)
0.98(>0.9)
Non-Normed Fit Index (NNFI)
0.99(>0.9)
Comparative Fit Index(CFI)
0.99(>0.9)
Table.4 shows that data fits the model with a good degree. In the model, the squared multiple
correlation (R2) (the proportion of the variable variance accounted for by its predictors) for Customer
Satisfaction is 0.812, indicating 81.2% of the variance of customer satisfaction is explained by this
model.
4.3 Hypothesis testing
Table.5 shows the results of the hypothesis testing of the satisfaction model. It is reassuring to see
that the effects of two sets of service quality and consumption emotion. We can see that: (1) almost
hypothesis were supported by the model, that is to say, the direct effects from visible quality, to service
quality, to satisfaction are significant; the direct effects from service quality to positive emotion, to
negative emotion and to satisfaction are significant, the direct effect from positive emotion to
satisfaction is significant, the direct effect from negative emotion to satisfaction is significant. (2)
Hypothesis H2 and H3 are not supported, in other words, the direct effect from visible quality to positive
emotion and to negative emotion are not significant.
Table.5 Results of the hypothesis-testing of satisfaction
To
Regression weights Hypothesis
Service quality
0.26
H1
Positive emotion
0.12
H2
Visible quality
Negative emotion
-0.10
H3
Satisfaction
0.28
H4
Positive emotion
0.40
H5
Service quality
Negative emotion
-0.49
H6
Satisfaction
0.38
H7
Positive emotion
Satisfaction
0.51
H8
Negative emotion
Satisfaction
-0.46
H9
From
Supported
Yes
No
No
Yes
Yes
Yes
Yes
Yes
Yes
4.4 Competition structural models
Two competing models are examined. The first model just includes perceived quality to measure
customer satisfaction (see Figer.2). The second model just includes consumption emotion to measure
customer satisfaction (see Figer.3).
These two competing models’ path coefficients and goodness of fit are listed in Table.6 and
Table.7.
Visible quality
Positive emotion
Satisfaction
Satisfaction
Service quality
Negative emotion
Figer.3 Competing model-2
Figer.2 Competing model-1
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According to goodness of fit, we know that these two competing models are acceptable. But the
squared multiple correlation (R2) for Customer Satisfaction in competing model-1 is 0.783, indicating
78.3% of the variance of customer satisfaction is explained by the model. And the squared multiple
correlation (R2) for Customer Satisfaction in competing model-2 is 0.729, indicating 72.9% of the
variance of customer satisfaction is explained by this model.
Table.6 Estimate of parameters and goodness of fit for the competing model-1
Construct
Satisfaction Chi-square SRMR
RMSEA
0.43
132
0.037
0.022
Visible quality
(t=8.27)
Df=68
0.59
NFI
NNFI
CFI
Service quality
(t=10.07)
1.00
0.99
1.00
Table.7 Estimate of parameters and goodness of fit for the competing model-2
RMSEA
Construct
Satisfaction Chi-square SRMR
0.51
129
0.042
0.027
Positive emotion
(t=17.30)
Df=67
-0.64
NFI
NNFI
CFI
Negative emotion
(t=-20.16)
1.00
0.99
1.00
5. Discussion
5.1 Reviews of findings
When we examine customer satisfaction just from the point of the perceived service quality, the
structural model is acceptable (competing medel-1). This shares the same view with Fornell (1996),
Parasuraman, Zeithaml, Berry (1985). When we examine customer satisfaction just from the point of the
consumption emotion, the structural model is acceptable (competing medel-2), too. This shares the same
view with Westbrook (1987, 1991) and Edwardson (1998).
But, when we examine customer satisfaction from the points both of the perceived quality and
consumption emotion, the structural model is better than the competing models, because R2 in our
satisfaction model is 81.2%, but R2 in competing models are 78.3% and 72.9%. In other words, the
model which included both emotion and quality has a stronger ability to explain customer satisfaction
than any model which just includes either service quality or consumption emotion. Therefore, we
suggest that when we want to measure customer satisfaction, we should establish a model based on the
consumption emotion and service quality in the same model, and would better not base on a simple set
of emotion or quality.
5.2 Managerial implication
From our results and findings, we think that the most take-away information is that in order to
succeed, a service firm needs to pay attention and train their staff well. There are several ways to
improve satisfaction: (1) since the approach of improving facility to induce positive emotion is not
effective, there is need to make greater efforts in this regard; (2) plan on intangible components to
satisfy customer expectation and try to exceed customer expectation-go for the delighted factor to raise
positive emotion; (3) collect customer feedback—either explicitly or implicitly—to improve service
quality; (4) provide more human interaction because it can create more positive feelings so as to
improve customer satisfaction.
5.3 Limitation of the study
The findings of this study may have limited generalizability because they are drawn from a sample
of customers in Tianjin, and may not represent the general population of supermarkets in China. Also,
this study focuses only on the supermarket industry, rather than service in general. Moreover, we
designed the instrument to collect cross-sectional data; however longitudinal- sectional data like
hypotheses were not examined. Also, a major part of this research is exploratory. In particular, the scale
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development and measuring of emotions and the concepts and the impact of service quality are
relatively new, and as a result, would benefit from further validation.
5.4 Suggestions for future research
(1)Because the results of this study were drawn from a small sample size of 384, a large size is
desired. (2) An extension in examining the impact of emotion and service quality can be further
explored in other service industries; (3) The studies of emotions and service quality can be extended to
the studies of customer loyalty, the emotional attachments of a brand and customer relationship
management; (4) The scales to measure emotion and quality can to be refined to yield better reliabilities.
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The author can be contacted from e-mail : [email protected]
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