TABLE 2 Summary Statistics and Measurement Model
Variables
M
SD
Factor
loadings
t value
α
Composite
reliability
Average
variance
extracted
Service Orientation
.78
77
.51
Customer focus
4.65
.33
.67
—
Prior customer
relationship
3.92
.92
.52
3.03
∗
Organizational
support
4.34
.47
.61
3.20
∗
Service under
pressure
a
1.81
.77
.49
3.27
∗
Service Quality
.96
.96
.87
Tangible I
5.37
.79
.60
—
Tangible II
5.16
.87
.58
6.05
∗
Tangible III
5.87
.66
.67
7.28
∗
Reliability
6.14
.57
.81
8.10
∗
Responsiveness &
assurance
5.89
.60
.85
8.25
∗
empathy
5.60
.80
.84
8.19
∗
Customer
Satisfaction
.76
.75
.82
Satisfaction I
4.72
.61
.75
—
Satisfaction II
5.83
.76
.89
10.27
∗
Customer Loyalty
.83
.85
.84
Future buying
intensions
6.08
.77
.90
—
Emotional
attachment
5.61
.90
.78
11.56
∗
Note. Factor loading values are based upon a completely standardized solution. Dashes indicate t values
were not computed as the parameters fixed to 1.00 during estimation.
a
Mean of the service under pressure variable is reverse coded.
∗
p
< .01.
TABLE 3 Standardized Path Coefficients for Structural Equation Model
Proposed model relations
LISREL
estimate
t value
Indirect effect
t value
Service Orientation
→
Perceived Service Quality
(
γ
11
)
.29
2.35
∗
.21 (Satisfaction)
2.01
∗
Service Orientation
→
Satisfaction (
γ
21
)
.08
1.01
Perceived Service Quality
→
Satisfaction (
β
21
)
.73
5.87
∗∗
.61 (Customer Loyalty)
4.93
∗∗
Perceived Service Quality
→
Customer Loyalty (
β
31
)
−.07
−0.09
Satisfaction
→ Customer
Loyalty (
β
32
)
.84
7.42
∗∗
∗
p
< .05.
∗∗
p
< .01.
Service Orientation, Service Quality, Satisfaction and Loyalty
631
composite construct reliability ranging from .77 to .96. Average variance
extracted ranged from .51 to .87, all above the standard of .50 recommended
by Fornell and Larcker (1981), suggesting adequate convergent validity.
In Table 3, the standardized path coefficient between service orienta-
tion and service quality supported the first hypothesis (H1); a high degree
of service orientation for the contact employee significantly affected the cus-
tomer’s perception of service quality (
γ
11
= .29, t = 2.05, p < .05). On
the other hand, the second hypothesis (H2) regarding the causal relation-
ship between service orientation and customer satisfaction was rejected. The
third hypothesis (H3) stating the positive relationship between perceived
service quality and satisfaction was supported; the perceived service quality
significantly influenced customer satisfaction (
β
21
= .73, t = 5.87, p < .01),
confirming the previous empirical result (Cronin & Taylor, 1992) that service
quality is an antecedent of customer satisfaction.
The sixth hypothesis (H6) regarding the mediating role of service qual-
ity between service orientation and customer satisfaction was supported;
service orientation showed a significant indirect effect on customer satis-
faction via service quality (
γ
11
× β
21
= .21, t = 2.50, p > .05). In other
words, contact employees’ high degree of service orientation was conveyed
via their service performance, which in turn led to high levels of customer
satisfaction. Further, the insignificant direct path from service orientation to
customer satisfaction suggested that service quality plays a role as a full
(rather than a partial) mediator between employee service orientation and
diners’ satisfaction in the restaurant setting (for the distinction between full
and partial mediators, see Baron & Kenny, 1986).
The fourth (H4) and fifth (H5) hypotheses focused on the effect of
service quality on customer loyalty and the effect of customer satisfaction
on customer loyalty, respectively. H4 was rejected, as service quality did
not have a significant, direct effect on customer loyalty. H5 was supported;
the result suggested that customer satisfaction has a significant influence on
customer loyalty (
β
32
= .84, t = 7.42, p < .01). The last hypothesis (H7)
regarding customer satisfaction as a mediator between service quality and
customer loyalty was supported as there was a significant indirect effect on
customer loyalty via customer satisfaction (
β
21
×
β
32
= .61, t = 4.93, p < .01).
Similar to H6, no significant path from service quality to customer loyalty
suggested the possibility of customer satisfaction as a full mediator between
perceived service quality and customer loyalty.
DISCUSSION AND MANAGERIAL IMPLICATIONS
This study contributes to the existing body of literature by its unique research
design. Previous studies that argue the positive associations between
frontline employees’ service orientation and customer outcome variables
632
H. J. Kim
such as satisfaction often gathered the ratings of all study variables from cus-
tomers (e.g., see Donavan & Hocutt, 2001; Brady & Cronin, 2001). However,
the present study depends on two data sources: Service oriented behav-
iors were reported by frontline employees themselves (i.e., servers and
bartenders) and dining customers provided their perceptions of service qual-
ity, satisfaction, and loyalty to the service company. This research design
reduces the impact of common method variance (i.e., single source) and
therefore the results are more likely to present reliable, true effects of ser-
vice orientation (predictor) on customer perceptions of a service company
(outcomes).
This study supports the prevalent theory or common belief that
customer-oriented companies benefit at multiple levels. Specifically, it shows
that frontline employees (i.e., servers and bartenders) with a high degree of
service orientation influence restaurant diners’ perceptions of service qual-
ity and ultimately lead to diners’ satisfaction and loyalty. It sends a crucial
message to restaurateurs as to how important it is to have customer-oriented
staff members. This study adopted the approach of service orientation as a
function of innate traits and situational or environmental factors. Following
this approach, restaurant operators should come up with a proper person-
ality trait profile and hire people that fit that profile. Some recent studies in
the hospitality field have pointed out the fundamental role of the individual
employee’s personality traits in work engagement and burnout (Kim, Shin,
& Swanger, 2009; Kim, Shin, & Umbreit, 2007). Despite such recruitment
efforts to select the applicants with suitable personality traits, companies
may find that employees, who are hired, have different levels of customer
focus. This situation indicates the significance of the other variable in the
service orientation equation—a situational or environmental factor. Practical
and useful environmental or situational factors to enhance employee service
orientation may include: offering ongoing training and rewarding good per-
formance of employees. The benefits of rewards and proper training in the
hospitality industry have been well documented (Kim, Tavitiyaman, & Kim,
2009).
Another key issue addressed in this study is the relationships among
service quality, customer satisfaction, and customer loyalty. The results con-
firmed that customers’ decisions to remain loyal depend directly on their
satisfaction (Cronin & Taylor, 1992) and found that customers’ perceptions
of service quality have an indirect influence on customer loyalty via customer
satisfaction (Perceived Service Quality
→ Customer Satisfaction → Customer
Loyalty). Rust and Oliver (1994) explained the relationship between service
quality and customer satisfaction best. They suggested that quality is one
of the many potential service dimensions that are factored into customer
satisfaction. Similarly, Westbrook (1981) indicated that satisfaction comes
from multiple sources, and a higher level of satisfaction with certain sources
might compensate for lower levels of satisfaction with others. Rust and
Service Orientation, Service Quality, Satisfaction and Loyalty
633
Oliver’s (1994) and Westbrook’s (1981) arguments, in a sense, justify the
current finding (service quality as an antecedent of customer satisfaction)
and help support the mediating effect of customer satisfaction: Perceived
Service Quality
→ Customer Satisfaction → Customer Loyalty.
In addition, Rust and Oliver’s (1994) and Westbrook’s (1981) arguments
imply that it may be wise to conduct a further investigation on how vital
it really is to provide a high level of service to customers in different din-
ing segments. For instance, high levels of service quality may be the most
significant predictor of customer satisfaction in fine dining restaurants, but
price or promotion may be more essential for customers at quick-service
restaurants. This kind of detailed information is more likely to be use-
ful for practitioners than the simple managerial implication that service
quality has a positive effect on customer satisfaction. Restaurant operators
should also note that satisfaction results from both current and past expe-
riences (Oliver, 1981). Customers are becoming more demanding as they
acquire a greater range of dining experiences and have more choices in
all food service segments. The operators who can ensure that their cus-
tomers are always satisfied are more likely to enjoy repeat business from
their customers.
Limitations and Future Research
First, although this study reduced the common method variance to some
extent by relying on two data sources (employees and customers), interre-
lationships among service quality, satisfaction, and loyalty are still subject to
common rater bias since these constructs are all assessed by customers. The
much stronger relationships are shown among customer outcome variables
(service quality to satisfaction and satisfaction to loyalty) than the path from
employee service orientation to service quality. Perhaps this may reflect the
common rater bias and therefore the relationships among service quality,
satisfaction, and loyalty should be attenuated and interpreted with some
caution.
Next, each participating employee was paired with a rather small num-
ber of customers. Although there is no concrete criterion about how many
customer responses are appropriate, the aggregated responses from three or
four customers may not be sufficient to make an objective, accurate judg-
ment about the quality of service provided by the individual employee. The
overall sample size of this research (n
= 169) is also quite small although
it falls into the acceptable range (100–200; Hair et al., 1998) to employ the
SEM method. These circumstances could contribute to resulting in weaker
associations (than expected) between service orientation and service qual-
ity. This study shows, although significant at the 0.05 level, the path from
service orientation to service quality was not significant at the conservative
0.01 level.
634
H. J. Kim
Third, Groves’ (1992) instrument used for this study is designed for the
restaurant business and the population of this study comprises employees in
casual dining restaurants in Korea. Therefore, generalization of this study’s
findings to other service industries (e.g., airlines, travel agencies, hotels) and
other cultures is limited. To validate the result of this study in different hos-
pitality or service segments, it is necessary to choose a service-orientation
measure that may be applicable to a broad spectrum of service jobs to assess
frontline employees’ service orientation. One exemplary measure is the
service-orientation scale recently developed by Donavan et al. (2004). Their
scale items are created using diverse service settings (e.g., travel agency,
financial services, food service) and the measure includes the four service
orientation components (pamper, read, deliver, and personal relationship).
Finally, the proposed model in this study is rather simple because it
investigates the impact of service orientation as a whole on customer satis-
faction and service quality. In the future, it is feasible to build more complex
service orientation models. For example, it would be interesting to see the
influence of service orientation on customer outcomes such as perceived
service quality, customer satisfaction, and revisit intention after splitting ser-
vice orientation into innate personality traits and environmental variables. In
this scenario, researchers could compare the two distinctive service orien-
tation components (personality vs. environmental factor) and assess which
component is more influential on customer outcome variables. The results
of these kinds of models may assist industry practitioners in terms of how
to prioritize the use of their financial resources in the human resource areas
(e.g., recruitment vs. service training).
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